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2,106 results on '"Yue Meng"'

1. Chromosome-level genome assembly and annotation of xerophyte secretohalophyte Reaumuria soongarica

Author: Miaomiao Song, Wei Gong, Yunyun Tian, Yue Meng, Tingyu Huo, Yanan Liu, Yeming Zhang, and Zhenhua Dang
Subjects: Science
Abstract: Abstract Reaumuria soongarica is a xerophytic shrub belonging to the Tamaricaceae family. The species is widely distributed in the deserts of Central Asia and is characterized by its remarkable adaptability to saline and barren desert environments. Using PacBio long-read sequencing and Hi-C technologies, we assembled a chromosome-level genome of R. soongarica. The genome assembly has a size of 1.28 Gb with a scaffold N50 of 116.15 Mb, and approximately 1.25 Gb sequences were anchored in 11 pseudo-chromosomes. A completeness assessment of the assembled genome revealed a BUSCO score of 97.5% and an LTR Assembly Index of 12.37. R. soongarica genome had approximately 60.07% repeat sequences. In total, 21,791 protein-coding genes were predicted, of which 95.64% were functionally annotated. This high-quality genome will serve as a foundation for studying the genomic evolution and adaptive mechanisms to arid-saline environments in R. soongarica, facilitating the exploration and utilization of its unique genetic resources.
Published: 2024
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2. Alternative molecular mechanisms for force transmission at adherens junctions via β-catenin-vinculin interaction

Author: Nicole Morales-Camilo, Jingzhun Liu, Manuel J. Ramírez, Patricio Canales-Salgado, Juan José Alegría, Xuyao Liu, Hui Ting Ong, Nelson P. Barrera, Angélica Fierro, Yusuke Toyama, Benjamin T. Goult, Yilin Wang, Yue Meng, Ryosuke Nishimura, Kedsarin Fong-Ngern, Christine Siok Lan Low, Pakorn Kanchanawong, Jie Yan, Andrea Ravasio, and Cristina Bertocchi
Subjects: Science
Abstract: Abstract Force transmission through adherens junctions (AJs) is crucial for multicellular organization, wound healing and tissue regeneration. Recent studies shed light on the molecular mechanisms of mechanotransduction at the AJs. However, the canonical model fails to explain force transmission when essential proteins of the mechanotransduction module are mutated or missing. Here, we demonstrate that, in absence of α-catenin, β-catenin can directly and functionally interact with vinculin in its open conformation, bearing physiological forces. Furthermore, we found that β-catenin can prevent vinculin autoinhibition in the presence of α-catenin by occupying vinculin´s head-tail interaction site, thus preserving force transmission capability. Taken together, our findings suggest a multi-step force transmission process at AJs, where α-catenin and β-catenin can alternatively and cooperatively interact with vinculin. This can explain the graded responses needed to maintain tissue mechanical homeostasis and, importantly, unveils a force-bearing mechanism involving β-catenin and extended vinculin that can potentially explain the underlying process enabling collective invasion of metastatic cells lacking α-catenin.
Published: 2024
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3. Short-term outcome of intracorporeal ileocolonic anastomosis in patients with visceral obesity

Author: Fangliang Guo, Cong Xia, Zongheng Wang, Ruiqi Wang, Yue Meng, Qianshi Zhang, and Shuangyi Ren
Subjects: Intracorporeal ileocolic anastomosis, Laparoscopic right colectomy, Prolonged postoperative ileus, Visceral obesity, Medicine, Science
Abstract: Abstract The primary objective of this study was to compare short-term outcomes between Intracorporeal ileocolic anastomosis (IIA) and extracorporeal ileocolic anastomosis (EIA) after laparoscopic right hemicolectomy in patients with visceral obesity. The secondary objective was to identify risk factors associated with prolonged postoperative ileus (PPOI) after laparoscopic right hemicolectomy. This single-center retrospective study analyzed visceral obesity patients who underwent laparoscopic right hemicolectomy for primary bowel cancer between January 2020 and June 2023. Patients were categorized into IIA and EIA groups based on the type of anastomosis, and a 1:1 propensity score-matched analysis was performed. A total of 129 patients were initially included in this study, with 45 patients in each group following propensity score matching. The IIA group had significantly longer anastomosis times (p
Published: 2024
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4. A swin transformer based bird nest detection approach with unmanned aerial vehicle images for power distribution and pole towers

Author: Yue Meng, Yu Song, Yuquan Chen, Xin Zhang, Mei Wu, and Biao Du
Subjects: computer vision, object detection, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95
Abstract: Abstract The authors propose a novel object detection algorithm for identifying bird nests in medium voltage power line aerial images, which is crucial for ensuring the safe operation of the power grid. The algorithm utilises an improved Swin Transformer as the main feature extraction network of Fast R‐CNN, further enhanced with a channel attention and modified binary self‐attention mechanism to improve the feature representation ability. The proposed algorithm is evaluated on a newly constructed image dataset of medium voltage transmission lines containing bird nests, which are annotated and classified. Experimental results show that the proposed algorithm achieves satisfied accuracy and robustness in recognising bird nests compared to traditional algorithms.
Published: 2024
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5. Response of Corn Yield to Water Retaining Agents, Inhibitors, and Corn Stalks Addition in Semi-arid Cropland

Author: Kaikuo Wu, Na Lv, Wei Bai, Yue Meng, Mei Han, Yan Xue, Yuchao Song, Xueshi Xie, Tingting Wang, Ping Gong, and Lili Zhang
Subjects: polyacrylamide, potassium polyacrylate, nbpt, dmpp, corn stalks, Biotechnology, TP248.13-248.65
Abstract: Drought, excessive use of nitrogen fertilizer, and decline in soil organic matter threaten corn production. This study investigated the potential of water retaining agents, inhibitors, and corn stalks in enhancing soil physicochemical properties to bolster corn yield in semi-arid farmlands. In our study, polyacrylamide addition increased the content of ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3--N) in the seedling stage, exchangeable potassium (K) in the mature stage but decreased the content of available phosphorus (P) in the seedling stage. Potassium polyacrylate addition increased the content of NH4+-N and decreased the content of available P in the seedling stage. The addition of inhibitors decreased the content of NH4+-N and available P in the seedling stage, NO3--N and available P in the jointing stage, and NH4+-N in the mature stage, respectively. Corn stalks returning could maintain soil moisture, decrease the content of NH4+-N in the seedling stage and exchangeable K in the mature stage, and increase the content of available P and exchangeable K in the seedling stage. Combined application of inhibitors and corn stalks could increase soil organic carbon (SOC) and ensure corn yield, which was the best fertilization mode in semi-arid cropland.
Published: 2024

6. Importance of computed tomography perfusion on assessing collateral circulation and prognosis of patients with acute anterior circulation large vessel occlusion after endovascular therapy

Author: Lei Chen, Guangjun Bian, Xiufang Zhu, Xinxiu Duan, Yue Meng, and Lei Li
Subjects: Acute anterior circulation great vessel occlusion, Computed tomography perfusion, Endovascular therapy, Collateral circulation, Prognosis, Biotechnology, TP248.13-248.65, Medical technology, R855-855.5
Abstract: This study probed the importance of computed tomography perfusion (CTP) on assessing collateral circulation and prognosis in patients with acute anterior circulation large vessel occlusion (AAC-LVO) after endovascular therapy (EVT). Retrospective analysis was performed on the case data of 124 AAC-LVO patients who achieved EVT in the First People's Hospital of Lianyungang. All patients received computed tomography (CT) examination. Based on the multi-phase computed tomography angiography (mCTA) score, patients were separated into poor collateral circulation group and good collateral circulation group. Based on modified Rankin scale (mRS) score, patients were separated into good prognosis group and poor prognosis group. The receiver operating characteristic (ROC) curve was used to measure the efficacy of CTP parameters in predicting good collateral circulation or good prognosis. Correlation between CTP parameters with mCTA collateral and 90-day mRS circulation score was analyzed using the Spearman correlation analysis. The age and admission national Institutes of Health stroke scale (NIHSS) scores of the good collateral circulation group were lower than the poor collateral circulation group, and low perfusion area volume with Tmax > 6 s (VTmax>6 s), infarct core area volume (VCBF6 s, VCBF6 s and VCBF6 s, VCBF6 s, Alberta Stroke Program Early CT(ASPECT) score, and higher mCTA score. Spearman correlation analysis unveiled that ASPECT score, mCTA score and 90-day mRS were negatively correlated. The final infarct volume, perfusion parameters HIR and VCBF
Published: 2024
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7. An estrogen-regulated long non-coding RNA NCALD promotes luminal breast cancer proliferation by activating GRHL2

Author: Yue Meng, Dianrong Zhou, Ying Luo, Jierong Chen, and Hui Li
Subjects: Luminal breast cancer, LncRNA NCALD, LncRNA, GRHL2, ERα, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282, Cytology, QH573-671
Abstract: Abstract Purpose Luminal breast cancer (BC) is a prevalent subtype associated with an increased risk of late disease recurrence and mortality. Long noncoding RNAs (lncRNAs) likely play significant roles in regulating tissue-specific gene expression during tumorigenesis. However, the biological function and underlying mechanisms of specific dysregulated lncRNAs in luminal BC remain largely unknown, which has drawn our attention. Methods The expression pattern of lncRNA NCALD in luminal BC was predicted and validated in collected tissue samples. Following cell transfection with knockdown of lncRNA NCALD and ESR1 and overexpression of GRHL2 and ESR1, we investigated the interactions among lncRNA NCALD, ESR1, and GRHL2. Additionally, their regulatory functions in luminal BC cell biological processes were studied. Subsequently, a xenograft tumor model was prepared for validation. Results Our study identified a specific overexpression of the lncRNA NCALD in luminal BC, which correlated with an unfavorable prognosis. Suppression of lncRNA NCALD or ESR1 led to inhibition of GRHL2 expression, while concurrent overexpression of ESR1 and lncRNA NCALD potentially elevated GRHL2 expression. Mechanistically, ERα may drive the expression of lncRNA NCALD. Furthermore, the 1–151 nt fragment of lncRNA NCALD was found to recruit ERα and interact with its oest-Recep domain located in the promoter region of GRHL2, ultimately inducing GRHL2 transcription. Conclusions These findings reveal the involvement of lncRNA NCALD and its specific expression pattern in luminal BC. Targeting lncRNA NCALD could be a potential therapeutic strategy for delaying the progression of BC.
Published: 2024
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8. Fracture behavior of AZ31B magnesium alloy under high-temperature ultrasonic-assisted shearing with related ductile-brittle transformation mechanism

Author: Yue Meng, Lifeng Ma, Weitao Jia, Zhiquan Huang, Hongbo Xie, Fangkun Ning, and Junyi Lei
Subjects: Magnesium alloy sheet, Shearing, Ultrasonic-assisted machining, Fracture behavior, Microstructure, Microhardness, Mining engineering. Metallurgy, TN1-997
Abstract: A wide width is one of the fundamental requirements for magnesium alloy sheets to fulfill the lightweight needs of the aerospace and rail transportation industries. Nevertheless, ensuring the dimensional integrity of wide-format magnesium alloy sheets is a challenge in most manufacturing facilities. Simultaneously, processing operations are susceptible to encountering production issues, including but not limited to significant loss of raw materials, elevated costs, environmental contamination, and safety risks. Therefore, to fulfill the operational demands of the hot rolling finishing line for wide sheets made of magnesium alloy, the present study employed ultrasonic-assisted shearing (UAS) to carry out a high-temperature shearing test investigation on the AZ31B magnesium alloy sheet. In this research, we employed scanning electron microscopy, optical microscopy, and a micro-hardness tester to investigate the relationship between ultrasonic amplitude and fracture behavior, deformation mechanism, and mechanical properties of magnesium alloy sheets following exposure to ultrasonic vibration. The fracture morphology of the sheet fracture demonstrates that the behavior of the magnesium alloy sheet fractures under ultrasonic vibration changes from ductile fracture under conventional shearing to brittle fracture under ultrasonic-assisted shearing. The primary cause of this transformation between ductile and brittle is the effect of ultrasonic vibration on the material's internal energy. High-energy ultrasonic amplitude action causes magnesium to absorb a significant amount of ultrasonic energy. This results in an increase in the number of dynamic re-crystallization grains in the material organization, a decrease in the number of twins, and significant refinement of the grains. The sheet's hardness also changes along the rolling and normal directions, with a uniform distribution. The magnesium alloy sheet's fracture quality is optimal when the ultrasonic amplitude is 10 μm in the UAS process. This treatment results in notable enhancements in the section's straightness and brightness. Our study aims to advance the mass manufacturing of wide-format magnesium alloy sheets by investigating a cost-effective and high-yield technique for shearing magnesium alloy sheets.
Published: 2024
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9. The Continuity of eSports Athletes’ Careers: Skill Transformation, Personal Development, and Well-Being

Author: Yupei Zhao, Yue Meng-Lewis, Bin Ni, Gavin Lewis, and Zhongxuan Lin
Subjects: History of scholarship and learning. The humanities, AZ20-999, Social Sciences
Abstract: Despite the rapid growth of the eSports industry with respect to its economic scale and the demand for eSports players, the career transformation experiences and well-being of eSports athletes have been largely overlooked. This study aims to explore eSports athletes’ personal development in terms of career continuity, associated skill transformation, and well-being after retirement. Employing non-participatory observations and semi-structured interviews, we unpack two different pedagogical contexts of retiring eSports athletes: one is “continuity paths” (three transformation options and associated skill sets), and the other is “desire for continuity” (psychological strengths and explicit tacit knowledge). Our findings provide practical guidance for the career transition experiences of eSports athletes and contribute to understanding the sustainable framework required for the self-development of talent within eSports education and the eSports industry. The findings suggest that psychological consultants and athletic rehabilitation therapists should be employed to provide professional advice, interventions, and treatment to eSports athletes before and after retirement.
Published: 2024
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10. Combined First-Principles and Experimental Investigation into the Reactivity of Codeposited Chromium–Carbon under Pressure

Author: Paul V. Marshall, Scott D. Thiel, Elizabeth E. Cote, Rostislav Hrubiak, Matthew L. Whitaker, Yue Meng, and James P. S. Walsh
Subjects: Materials of engineering and construction. Mechanics of materials, TA401-492
Published: 2023
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11. Effects of Corn Stalks Returning on Soil Microbial Carbon Use Efficiency and Corn Yield in Semi-Arid Cropland

Author: Yue Meng, Kaikuo Wu, Ping Gong, Zhe Zhang, Mei Han, Zhanbo Wei, Lingli Wang, Na Lv, Wei Bai, and Lili Zhang
Subjects: microbial carbon use efficiency, corn stalks resources, o-labeled water approach, corn field, corn biological indicators, Biotechnology, TP248.13-248.65
Abstract: Soil microbial carbon use efficiency (CUE) is a key parameter controlling the short-term carbon (C) cycle in terrestrial ecosystems. The effect of urea application (156 kg N ha-1) and corn stalks returning (9.0 tons ha-1) on soil microbial CUE and corn yield in semi-arid cropland was studied using the 18O-labeled water approach during a one-year experiment. In semi-arid cropland, applying urea reduced soil microbial CUE by 44%, while the soil microbial CUE was increased significantly by 34% after returning corn stalks to the field. The application of urea increased the total nitrogen content of soil by 23%, and corn stalks returning further increased nitrate nitrogen (NO3--N) by 45%, dissolved organic carbon (DOC) by 53%, and dissolved organic nitrogen (DON) by 122%. Compared with no fertilization, urea application increased the corn height by 4% and the corn yield by 21%. Corn stalks returning combined with urea reduced the corn stalks by 37% compared with no fertilizer. There was no significant difference in corn yield between corn stalks returning combined with urea and single urea application. Therefore, corn stalks returning combined with urea may be an effective agronomic measure to increase soil carbon sequestration, improve soil fertility, maintain corn yield, restore soil fertility, and improve production capacity.
Published: 2023

12. Nomogram for predicting the surgical difficulty of laparoscopic total mesorectal excision and exploring the technical advantages of robotic surgery

Author: Fangliang Guo, Cong Xia, Zongheng Wang, Ruiqi Wang, Jianfeng Gao, Yue Meng, Jiahao Pan, Qianshi Zhang, and Shuangyi Ren
Subjects: total mesorectal excision, surgical difficulty, laparoscopic surgery, robotic surgery, technically challenging rectal cancer, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: BackgroundTotal mesorectal excision (TME), represents a key technique in radical surgery for rectal cancer. This study aimed to construct a preoperative nomogram for predicting the surgical difficulty of laparoscopic total mesorectal excision (L-TME) and to investigate whether there were potential benefits of robotic TME (R-TME) for patients with technically challenging rectal cancer.MethodsConsecutive midlow rectal cancer patients receiving total mesorectal excision were included. A preoperative nomogram to predict the surgical difficulty of L-TME was established and validated. Patients with technically challenging rectal cancer were screened by calculating the prediction score of the nomogram. Then patients with technically challenging rectal cancer who underwent different types of surgery, R-TME or L-TME, were analyzed for comparison.ResultsA total of 533 consecutive patients with midlow rectal cancer who underwent TME at a single tertiary medical center between January 2018 and January 2021 were retrospectively enrolled. Multivariable analysis demonstrated that mesorectal fat area, intertuberous distance, tumor size, and tumor height were independent risk factors for surgical difficulty. Subsequently, these variables were used to construct the nomogram model to predict the surgical difficulty of L-TME. The area under the receiver operating characteristic curve of the nomogram was 0.827 (95% CI 0.745 - 0.909) and 0.809 (95% CI 0.674- 0.944) in the training and validation cohort, respectively. For patients with technically challenging rectal cancer, R-TME was associated with a lower diverting ileostomy rate (p = 0.003), less estimated blood loss (p < 0.043), shorter procedure time (p = 0.009) and shorter postoperative hospital stay (p = 0.037).ConclusionIn this study, we established a preoperative nomogram to predict the surgical difficulty of L-TME. Furthermore, this study also indicated that R-TME has potential technical advantages for patients with technically challenging rectal cancer.
Published: 2024
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13. Age‐aware relay strategy with simultaneous wireless information and power transfer in remote monitoring systems

Author: Yujia Tian, Yue Meng, Xinlong Zhao, Xu Wen, Lei Meng, and Xiaoqi Qin
Subjects: Age of Information, Internet of Things, SWIPT, Telecommunication, TK5101-6720
Abstract: Abstract Remote monitoring systems has emerged to automate public services, where Internet of Things (IoT) devices are deployed to collect and relay streams of status updates to a remote control centre. The freshness of collected data is of critical importance to system performance, which can be quantified by the concept of age of information (AoI). To obtain timely perception of the monitored area, each sensor tends to sample status updates at the maximum frequency, which may lead to device drop‐outs due to limited battery capacity. Simultaneous wireless information and power transfer (SWIPT) is considered as a promising technology to prolong network lifetime. In this paper, a SWIPT‐enabled two‐hop relay network, where a relay node uses power splitting protocol to assist data transmissions from multiple source nodes to the destination is considered. The impact of power splitting coefficients, data arrival pattern and time‐varying channel conditions on the averaged age performance and expected lifetime of the system is theoretically analysed. Moreover, a lightweight relay strategy which selectively forward packets based on a reward function consisting of energy level at relay node and expected age reduction is developed. Simulation results show that the proposed strategy outperforms existing schemes in collecting status updates in a timely and energy‐efficient manner.
Published: 2023
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14. Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model

Author: Haoyue Wu, Bangwen Ding, Lu Liu, Lei Zhou, Yue Meng, and Xiangjiang Zheng
Subjects: agricultural land-use carbon emissions, greenhouse gas emissions, emission peak, Tapio decoupling index, environmental Kuznets curve, spatial Durbin model, Agriculture
Abstract: Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude.
Published: 2024
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15. Bias learning improves data driven models for streamflow prediction

Author: Yongen Lin, Dagang Wang, Yue Meng, Wei Sun, Jianxiu Qiu, Wei Shangguan, Jingheng Cai, Yeonjoo Kim, and Yongjiu Dai
Subjects: Streamflow prediction, Data driven model, Bias learning, Machine learning, Physical geography, GB3-5030, Geology, QE1-996.5
Abstract: Study region: Andun river basin of Southern China and 273 watersheds across the continental United States. Study focus: Owing to the data incompleteness and the changing environment, there is bias existing in the data driven models for streamflow prediction, greatly limiting their application in actual practice. In this paper, we incorporate the bias learning components into the data driven models to establish the mapping-bias-learning models, and design two groups of experiments, one in the Andun River basin in China and the other in 273 watersheds in the continental United States (CONUS). In the first group of experiments, we respectively apply three machine learning algorithms and one traditional statistical method to generate sixteen mapping-bias-learning models ae well as four mapping-learning-alone models. We also explore the effectiveness of different bias learning strategies, including multiple bias learning, stacking bias learning and incremental updating bias learning. In the second group of experiments, we apply the mapping-bias-learning models to the streamflow prediction in 273 watersheds of CONUS to verify the universality and robustness of the bias learning method. New hydrological insights for the region: The mapping-bias-learning models significantly outperform the mapping-learning-alone models, and the machine learning methods are superior to the traditional statistical method in term of the ability of bias learning. In addition, adopting the appropriate bias learning strategies can further improve the streamflow forecast performance of data-driven models. The bias learning method is applicable to various watersheds with different hydrological conditions and play efficient roles at different streamflow levels. The median of MRE drops from 0.156 for mapping-learning-alone models to 0.131 for mapping-bias-learning models, while median of NSE increases from 0.918 for mapping-learning-alone models to 0.932 for mapping-bias-learning models. More inspiringly, the bias learning method can still play roles in data driven models under the environmental conditions that never occurred before, suggesting its remarkable superiority. This study highlights the power of the bias learning method for data driven models in streamflow prediction, and the promising prospect of the combination between bias learning and machine learning methods in hydrological modelling.
Published: 2023
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16. An integrated process by ultrasonic enhancement in the deep eutectic solvents system for extraction and separation of chlorogenic acid from Eucommia ulmoides leaves

Author: Yue Meng, Xiaoyu Sui, Xu Pan, Ying Yang, Huimin Sui, Tao Xu, Honglian Zhang, Tingting Liu, Jicheng Liu, and Pengling Ge
Subjects: Deep eutectic solvents, Eucommia ulmoides leaves, Chlorogenic acid, Ultrasonic wave-enhanced, Macroporous adsorption resin, Chemistry, QD1-999, Acoustics. Sound, QC221-246
Abstract: This study established an integrated process for the extraction and enrichment of chlorogenic acid (CGA) from Eucommia ulmoides leaves in a deep eutectic solvent system via ultrasonic wave-enhanced adsorption and desorption practices utilizing macroporous resins. Although deep eutectic solvents (DESs) have the advantages of chemical stability, good dissolving capacity, and nonvolatilization, routine solvent recovery operations are not suitable for subsequent separation in this solvent system. Based on the above characteristics, this study integrated the extraction and enrichment processes, in which DESs extracts directly loaded onto the macroporous adsorption resin, avoiding the loss of target components in solvent recovery and redissolution processes. The screening results of solvents and resin types further showed that choline chloride-malic acid (1:1) was the optimal DES, and the NKA-II resin had high adsorption and elution performance for CGA. The viscosities of the DESs were much higher than those of water and conventional organic solvents; thus, the mass transfer resistance was large, which could also affect the adsorption behaviour of the macroporous resin. The thermal and mechanical effects of ultrasound could effectively enhance the efficiency of the mass transfer, adsorption, and desorption in the DES systems. When compared to no sonication treatment, the CGA adsorption at various ultrasonic powers (120–600 W) was examined. At optimal ethanol concentration (60%), the effect of the ultrasonic treatment on the recovery of the DESs (water eluting process) and the desorption capability of CGA were confirmed. The use of three volumes of water elution could recover the DESs without loss of CGA. The adsorption process significantly differed depending on the ultrasonic settings, and the absorption balance time and experimental adsorption capacity at equilibrium were enhanced. Additionally, the adsorption procedure of the NKA-II macroporous resin for CGA under ultrasonic treatment could be clarified by the pseudo second order kinetic equation and the Freundlich isotherm model. Thermodynamic and dynamic parameters indicated that physical adsorption was the main process of the entire procedure, and it was a spontaneous, exothermic, and entropy-reducing physical adsorption process. This study potentially indicates that the use of ultrasonication, as a high-efficiency, environmentally friendly method, can enhance the features of the macroporous resin to better purify target chemicals from a DES extract.
Published: 2023
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17. Preparation, Purification, Characterization and Antioxidant Activity of Rice Bran Fermentation Broth with Hypsizigus marmoreus

Author: Yanping Chi, Lining Kang, Xiangying Liu, Hongrui Sun, Yue Meng, Jialin Zhang, You Kang, and Yonggang Dai
Subjects: rice bran fermentation broth, preparation, purification, characterization, antioxidant activity, Fermentation industries. Beverages. Alcohol, TP500-660
Abstract: The main purpose of this study was to investigate the composition, characterization and antioxidant activity of rice bran fermentation broth, and provide a new way for high-value utilization of rice bran. Firstly, we fermented rice bran with Hypsizigus marmoreus and purified fermentation broth with macroporous resins. We took feruloyl oligosaccharides (FOs) concentration as the measure index, and the results showed that the maximum concentration of FOs was 0.72 mmol/L on the 6th day of rice bran fermentation. We took D101 macroporous resin as adsorption resin for rice bran fermentation broth, and the result showed that FOs concentration reached 2.38 mmol/L with the optimal purification process at pH 4.5, temperature 29 °C, ethanol concentration 55%, sample flow rate 1.5 mL/min, sample concentration 1.7 mL/min and elution flow rate 2.0 mmol/L. Secondly, the characters of rice bran fermentation broth were identified by high-performance liquid chromatography (HPLC) and Fourier-transform infrared spectroscopy (FTIR). These methods showed the presence of ferulic acid (FA), arabinose, xylose and glucose in rice bran fermentation broth. Finally, the in vitro antioxidant activities of rice bran fermentation broth were tested and the result showed that fermentation broth had good antioxidant activities and significantly improved after purification.
Published: 2024
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18. The Potential Role of Genic-SSRs in Driving Ecological Adaptation Diversity in Caragana Plants

Author: Qinglang Wang, Xing’er Chen, Yue Meng, Miaomiao Niu, Yuanyuan Jia, Lei Huang, Wenhong Ma, Cunzhu Liang, Zhiyong Li, Liqing Zhao, and Zhenhua Dang
Subjects: Caragana, genic-SSR, ecological adaptability diversity, functional trait, climate factor, transcriptome sequencing, Biology (General), QH301-705.5, Chemistry, QD1-999
Abstract: Caragana, a xerophytic shrub genus widely distributed in northern China, exhibits distinctive geographical substitution patterns and ecological adaptation diversity. This study employed transcriptome sequencing technology to investigate 12 Caragana species, aiming to explore genic-SSR variations in the Caragana transcriptome and identify their role as a driving force for environmental adaptation within the genus. A total of 3666 polymorphic genic-SSRs were identified across different species. The impact of these variations on the expression of related genes was analyzed, revealing a significant linear correlation (p < 0.05) between the length variation of 264 polymorphic genic-SSRs and the expression of associated genes. Additionally, 2424 polymorphic genic-SSRs were located in differentially expressed genes among Caragana species. Through weighted gene co-expression network analysis, the expressions of these genes were correlated with 19 climatic factors and 16 plant functional traits in various habitats. This approach facilitated the identification of biological processes associated with habitat adaptations in the studied Caragana species. Fifty-five core genes related to functional traits and climatic factors were identified, including various transcription factors such as MYB, TCP, ARF, and structural proteins like HSP90, elongation factor TS, and HECT. The roles of these genes in the ecological adaptation diversity of Caragana were discussed. Our study identified specific genomic components and genes in Caragana plants responsive to heterogeneous habitats. The results contribute to advancements in the molecular understanding of their ecological adaptation, lay a foundation for the conservation and development of Caragana germplasm resources, and provide a scientific basis for plant adaptation to global climate change.
Published: 2024
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19. Model-independent Approach of the JUNO 8B Solar Neutrino Program

Author: Jie Zhao, Baobiao Yue, Haoqi Lu, Yufeng Li, Jiajie Ling, Zeyuan Yu, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Abid Aleem, Tsagkarakis Alexandros, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Weidong Bai, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Ilya Butorov, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Chi Chan, Jinfan Chang, Yun Chang, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Chen, Jie Cheng, Yaping Cheng, Alexander Chepurnov, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Marta Colomer Molla, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Zhengyong Fei, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Maxim Gromov, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Yuduo Guan, Nunzio Guardone, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Yuxiang Hu, Zhuojun Hu, Guihong Huang, Hanxiong Huang, Kaixuan Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Ignacio Jeria, Xiaolu Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Xiaoping Jing, Cécile Jollet, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Daozheng Li, Demin Li, Fei Li, Fule Li, Gaosong Li, Huiling Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Rui Li, Shanfeng Li, Tao Li, Teng Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yichen Li, Zepeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Zonghai Li, Hao Liang, Jiajun Liao, Ayut Limphirat, Guey-Lin Lin, Shengxin Lin, Tao Lin, Ivano Lippi, Fang Liu, Haidong Liu, Haotian Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Daibin Luo, Fengjiao Luo, Guang Luo, Shu Luo, Wuming Luo, Xiaojie Luo, Vladimir Lyashuk, Bangzheng Ma, Bing Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Jingyu Mai, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Alexey Nikolaev, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Yu Peng, Zhaoyuan Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Mariia Redchuk, Bin Ren, Jie Ren, Barbara Ricci, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Xichao Ruan, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Utane Sawangwit, Julia Sawatzki, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Jun Su, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Katharina von Sturm, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Apimook Watcharangkool, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiang Xiao, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Jiaxuan Ye, Mei Ye, Ziping Ye, Frédéric Yermia, Na Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zezhong Yu, Cenxi Yuan, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Noman Zafar, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Bin Zhang, Binting Zhang, Feiyang Zhang, Guoqing Zhang, Honghao Zhang, Jialiang Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Mohan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xin Zhang, Xuantong Zhang, Xueyao Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yu Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Rong Zhao, Runze Zhao, Shujun Zhao, Dongqin Zheng, Hua Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou
Subjects: Solar neutrinos, Astrophysics, QB460-466
Abstract: The physics potential of detecting ^8 B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model-independent manner by using three distinct channels of the charged current (CC), neutral current (NC), and elastic scattering (ES) interactions. Due to the largest-ever mass of ^13 C nuclei in the liquid scintillator detectors and the expected low background level, ^8 B solar neutrinos are observable in the CC and NC interactions on ^13 C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC, and ES channels to guarantee the observation of the ^8 B solar neutrinos. From the sensitivity studies performed in this work, we show that JUNO, with 10 yr of data, can reach the 1 σ precision levels of 5%, 8%, and 20% for the ^8 B neutrino flux, ${\sin }^{2}{\theta }_{12}$ , and ${\rm{\Delta }}{m}_{21}^{2}$ , respectively. Probing the details of both solar physics and neutrino physics would be unique and helpful. In addition, when combined with the Sudbury Neutrino Observatory measurement, the world's best precision of 3% is expected for the measurement of the ^8 B neutrino flux.
Published: 2024
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20. Density-oriented deep eutectic solvent-based system for the selective separation of polysaccharides from Astragalus membranaceus var. Mongholicus under ultrasound-assisted conditions

Author: Yue Meng, Xiaoyu Sui, Xu Pan, Xinyi Zhang, Huimin Sui, Tao Xu, Honglian Zhang, Tingting Liu, Jicheng Liu, and Pengling Ge
Subjects: Sonocrystallisation, Astragalus membranaceus var. Mongholicus roots, High-density natural deep eutectic solvents, Polysaccharides, Selective separation, Preprocessing optimization, Chemistry, QD1-999, Acoustics. Sound, QC221-246
Abstract: The water extraction and ethanol precipitation method is an extraction method based on the solubility characteristics of polysaccharides that offers wide applicability in the extraction and separation of plant polysaccharides. However, this method leads to large amounts of proteins, nucleic acids, pigments, and other impurities in the polysaccharides products, which makes downstream purification complicated and time-consuming. In this study, a green, high-density natural deep eutectic solvents was used for the high-purity extraction and separation of polysaccharides from Astragalus membranaceus (Fisch) Bge. var. Mongholicus (Bge.) Hsiao roots under ultrasound-assisted conditions. In this study, 16 different natural deep eutectic solvents were designed to screen the best solvent for extracting Astragalus polysaccharides (APSs). Based on the yield and recovery of APSs, a natural deep eutectic solvents composed of choline chloride and oxalic acid with a molar ratio of 1:2 was selected. The related factors affecting polysaccharides extraction and solvent precipitation were investigated. To improve the operating methodology, single-factor trials, a Plackett-Burman design, and a Box-Behnken design were used. The optimal extraction process conditions were obtained as follows: water content of 55%, liquid–solid ratio of 24 mL/g, ultrasonic irradiation time of 54 min, ultrasonic irradiation temperature of 50 °C, ultrasonic irradiation power of 480 W, ethanol precipitation time of 24 h, and ethanol concentration of 75%. Under optimal extraction conditions, the recovery of APSs was 61.4 ± 0.6 mg/g. Considering the special matrix characteristics of A. membranaceus var. Mongholicus roots, physical-technology-based ultrasonic waves promote penetration, and the mass transfer function also solves the bottleneck of high-viscosity deep eutectic solvents in the extraction stage. In comparison with the conventional method, the proposed method based on deep eutectic solvents isolation can significantly increase APSs recovery, which is beneficial to simplifying the process of polysaccharides purification by using solvent properties to separate extracts and reduce impurities in APSs.
Published: 2023
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21. Elevated estradiol levels on hCG trigger day adversely effects on the clinical pregnancy rates of blastocyst embryo transfer but not cleavage-stage embryo transfer in fresh cycles: a retrospective cohort study

Author: Yue Meng, Linlin Tao, Tingting Xia, Jieru Zhu, Xiaoqi Lin, Wen Zhou, Yuxia Liu, Jianping Ou, and Weijie Xing
Subjects: Fresh embryo transfer, Clinical pregnancy, High estradiol, Embryo stage, Medicine, Biology (General), QH301-705.5
Abstract: Background Elevated estradiol (E2) levels are an inevitable outcome of the controlled ovulation hyperstimulation. However, the effect of this change on pregnancy is still uncertain. Our study aimed to analyze the impact of increased serum E2 at the day of human chorionic gonadotropin (hCG) administration on the clinical outcomes of women with fresh embryo transfer (ET) cycles. Methods This study included 3,009 fresh ET cycles from October 2015 to September 2021. Based on the stage of embryos transferred, these cycles were categorized into the cleavage group and blastocyst group. Both groups were then divided into four sets according to E2 levels when hCG was administered: set 1 (E2 ≤ 2,000 pg/ml), set 2 (E2 = 2,001–3,000 pg/ml), set 3 (E2 = 3,001–4,000 pg/ml), and set 4 (E2 > 4,000 pg/ml). The primary outcome was the clinical pregnancy rate (CPR). Binary logistics regression analysis was established to explore the association between CPR and E2 levels. Specifically, the threshold effect of serum E2 on CPR was revealed using the two-piecewise linear regression analyses. Results The multivariate regression model in the cleavage group showed that patients’ CPR in set 4 was 1.59 times higher than those in reference set 1, but the statistical difference was insignificant (P = 0.294). As for the blastocyst group, patients in set 4 had a lower CPR with adjusted ORs of 0.43 (P = 0.039) compared to patients in set 1. The inflection point for the blastocyst group was 39.7 pg/dl according to the results of the two-piecewise linear regression model. When E2 levels were over the point, the CPR decreased by 17% with every 1 pg/dl increases in serum E2 (adjusted OR = 0.83, 95% CI [0.72–0.96], P = 0.012). Conclusions Elevated E2 levels (>39.7 pg/dl) on hCG trigger day were associated with decreased CPR in patients with fresh blastocyst ET. However, it had no similar effect on the CPR of patients with fresh cleavage-stage ET.
Published: 2023
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22. Mass testing and characterization of 20-inch PMTs for JUNO

Author: Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Abid Aleem, Tsagkarakis Alexandros, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Weidong Bai, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Jose Busto, Ilya Butorov, Anatael Cabrera, Barbara Caccianiga, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Chi Chan, Jinfan Chang, Yun Chang, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Chen, Jie Cheng, Yaping Cheng, Yu Chin Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Marta Colomer Molla, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Zhengyong Fei, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Yuduo Guan, Nunzio Guardone, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Yuxiang Hu, Zhuojun Hu, Guihong Huang, Hanxiong Huang, Kaixuan Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Ignacio Jeria, Xiaolu Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Amina Khatun, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Daozheng Li, Demin Li, Fei Li, Fule Li, Gaosong Li, Huiling Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Rui Li, Shanfeng Li, Tao Li, Teng Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yichen Li, Yufeng Li, Zepeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Zonghai Li, Hao Liang, Jiajun Liao, Ayut Limphirat, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Haotian Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Daibin Luo, Fengjiao Luo, Guang Luo, Shu Luo, Wuming Luo, Xiaojie Luo, Vladimir Lyashuk, Bangzheng Ma, Bing Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Jingyu Mai, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Luca Pelicci, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Yu Peng, Zhaoyuan Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Mariia Redchuk, Bin Ren, Jie Ren, Barbara Ricci, Mariam Rifai, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Xichao Ruan, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Utane Sawangwit, Julia Sawatzki, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Jun Su, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Zhengyang Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Eric Theisen, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Katharina von Sturm, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Apimook Watcharangkool, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiang Xiao, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhao Xin, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Jiaxuan Ye, Mei Ye, Ziping Ye, Frédéric Yermia, Na Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Cenxi Yuan, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Baobiao Yue, Noman Zafar, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Bin Zhang, Binting Zhang, Feiyang Zhang, Guoqing Zhang, Honghao Zhang, Jialiang Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Mohan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xin Zhang, Xuantong Zhang, Xueyao Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yu Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Runze Zhao, Shujun Zhao, Dongqin Zheng, Hua Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Jingsen Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou, and JUNO Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Main goal of the JUNO experiment is to determine the neutrino mass ordering using a 20 kt liquid-scintillator detector. Its key feature is an excellent energy resolution of at least 3% at 1 MeV, for which its instruments need to meet a certain quality and thus have to be fully characterized. More than 20,000 20-inch PMTs have been received and assessed by JUNO after a detailed testing program which began in 2017 and elapsed for about four years. Based on this mass characterization and a set of specific requirements, a good quality of all accepted PMTs could be ascertained. This paper presents the performed testing procedure with the designed testing systems as well as the statistical characteristics of all 20-inch PMTs intended to be used in the JUNO experiment, covering more than fifteen performance parameters including the photocathode uniformity. This constitutes the largest sample of 20-inch PMTs ever produced and studied in detail to date, i.e. 15,000 of the newly developed 20-inch MCP-PMTs from Northern Night Vision Technology Co. (NNVT) and 5000 of dynode PMTs from Hamamatsu Photonics K. K.(HPK).
Published: 2022
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23. Low radioactive material screening and background control for the PandaX-4T experiment

Author: The PandaX-4T collaboration, Zhicheng Qian, Lin Si, Abdusalam Abdukerim, Zihao Bo, Wei Chen, Xun Chen, Yunhua Chen, Chen Cheng, Yunshan Cheng, Xiangyi Cui, Yingjie Fan, Deqing Fang, Changbo Fu, Mengting Fu, Lisheng Geng, Karl Giboni, Linhui Gu, Xuyuan Guo, Ke Han, Changda He, Jinrong He, Di Huang, Yanlin Huang, Zhou Huang, Ruquan Hou, Xiangdong Ji, Yonglin Ju, Chenxiang Li, Mingchuan Li, Shu Li, Shuaijie Li, Qing Lin, Jianglai Liu, Xiaoying Lu, Lingyin Luo, Wenbo Ma, Yugang Ma, Yajun Mao, Yue Meng, Xuyang Ning, Ningchun Qi, Xiangxiang Ren, Nasir Shaheed, Changsong Shang, Guofang Shen, Wenliang Sun, Andi Tan, Yi Tao, Anqing Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Zhou Wang, Mengmeng Wu, Weihao Wu, Jingkai Xia, Mengjiao Xiao, Xiang Xiao, Pengwei Xie, Binbin Yan, Xiyu Yan, Jijun Yang, Yong Yang, Chunxu Yu, Jumin Yuan, Ying Yuan, Dan Zhang, Minzhen Zhang, Peng Zhang, Tao Zhang, Li Zhao, Qibin Zheng, Jifang Zhou, Ning Zhou, Xiaopeng Zhou, and Yong Zhou
Subjects: Dark Matter and Double Beta Decay (experiments), Rare Decay, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract PandaX-4T is a ton-scale dark matter direct detection experiment using a dual-phase TPC technique at the China Jinping Underground Laboratory. Various ultra-low background technologies have been developed and applied to material screening for PandaX-4T, including HPGe gamma spectroscopy, ICP-MS, NAA, radon emanation measurement system, krypton assay station, and alpha detection system. Low background materials were selected to assemble the detector. Surface treatment procedures were investigated to further suppress radioactive background. Combining measured results and Monte Carlo simulation, the total material background rates of PandaX-4T in the energy region of 1–25 keVee are estimated to be (9.9 ± 1.9) × 10 −3 mDRU for electron recoil and (2.8 ± 0.6) × 10 −4 mDRU for nuclear recoil. In addition, natKr in the detector is estimated to be < 8 ppt.
Published: 2022
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24. Damping signatures at JUNO, a medium-baseline reactor neutrino oscillation experiment

Author: The JUNO collaboration, Jun Wang, Jiajun Liao, Wei Wang, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Nikita Balashov, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Riccardo Callegari, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Ran Du, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Arsenii Gavrikov, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Wei Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Arslan Lukanov, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Roberto Carlos Mandujano, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Marco Danilo Claudio Torri, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Moritz Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Kaile Wen, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou
Subjects: Neutrino Detectors and Telescopes (experiments), Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract We study damping signatures at the Jiangmen Underground Neutrino Observatory (JUNO), a medium-baseline reactor neutrino oscillation experiment. These damping signatures are motivated by various new physics models, including quantum decoherence, ν 3 decay, neutrino absorption, and wave packet decoherence. The phenomenological effects of these models can be characterized by exponential damping factors at the probability level. We assess how well JUNO can constrain these damping parameters and how to disentangle these different damping signatures at JUNO. Compared to current experimental limits, JUNO can significantly improve the limits on τ 3/m 3 in the ν 3 decay model, the width of the neutrino wave packet σ x , and the intrinsic relative dispersion of neutrino momentum σ rel.
Published: 2022
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25. The design and sensitivity of JUNO’s scintillator radiopurity pre-detector OSIRIS

Author: Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Guangpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Salvatore Costa, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Can Fang, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Christoph Genster, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, Daojin Hong, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Michael Karagounis, Narine Kazarian, Waseem Khan, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Jingjing Liang, Jiajun Liao, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Pavithra Muralidharan, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, MinhThuan NguyenThi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Nina Parkalian, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Gongxing Sun, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cornelius Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kangpu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou, and JUNO Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The OSIRIS detector is a subsystem of the liquid scintillator filling chain of the JUNO reactor neutrino experiment. Its purpose is to validate the radiopurity of the scintillator to assure that all components of the JUNO scintillator system work to specifications and only neutrino-grade scintillator is filled into the JUNO Central Detector. The aspired sensitivity level of $$10^{-16}\hbox { g/g}$$ 10 - 16 g/g of $$^{238}\hbox {U}$$ 238 U and $$^{232}\hbox {Th}$$ 232 Th requires a large ( $$\sim 20\,\hbox {m}^3$$ ∼ 20 m 3 ) detection volume and ultralow background levels. The present paper reports on the design and major components of the OSIRIS detector, the detector simulation as well as the measuring strategies foreseen and the sensitivity levels to U/Th that can be reached in this setup.
Published: 2021
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26. Radioactivity control strategy for the JUNO detector

Author: The JUNO collaboration, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Davide Basilico, Eric Baussan, Marco Bellato, Antonio Bergnoli, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Oliviero Cremonesi, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Rebin Karaparambil, Narine Kazarian, Waseem Khan, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Jiajun Liao, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Matthias Mayer, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Paolo Montini, Michele Montuschi, Axel Müller, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Moritz Cornelius Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Xiaochuan Xie, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Chengfeng Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jin Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kangfu Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, and Jiaheng Zou
Subjects: Neutrino Detectors and Telescopes (experiments), Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract JUNO is a massive liquid scintillator detector with a primary scientific goal of determining the neutrino mass ordering by studying the oscillated anti-neutrino flux coming from two nuclear power plants at 53 km distance. The expected signal anti-neutrino interaction rate is only 60 counts per day (cpd), therefore a careful control of the background sources due to radioactivity is critical. In particular, natural radioactivity present in all materials and in the environment represents a serious issue that could impair the sensitivity of the experiment if appropriate countermeasures were not foreseen. In this paper we discuss the background reduction strategies undertaken by the JUNO collaboration to reduce at minimum the impact of natural radioactivity. We describe our efforts for an optimized experimental design, a careful material screening and accurate detector production handling, and a constant control of the expected results through a meticulous Monte Carlo simulation program. We show that all these actions should allow us to keep the background count rate safely below the target value of 10 Hz (i.e. ∼1 cpd accidental background) in the default fiducial volume, above an energy threshold of 0.7 MeV.
Published: 2021
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27. Analysis of inventive problem-solving capacities for renewable energy storage investments

Author: Yue Meng, Ronghua Zhou, Hasan Dinçer, Serhat Yüksel, and Chong Wang
Subjects: Energy storage investments, TRIZ, Spherical fuzzy sets, DEMATEL, Shapley value, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: The energy storage process becomes very important due to the imbalances in energy supply and demand. Therefore some factors need to be considered to increase the efficiency of the energy storage system, such as cost–benefit analysis and technological improvements. This study aims to examine the inventive problem-solving capacities for renewable energy storage investments. A new model is suggested for this objective by considering fuzzy decision-making methodology. It is concluded that prior action and dynamicity are the most essential capacities of renewable energy storage investments. Additionally, dynamicity plays the most critical role when all factors are considered in renewable energy investment projects in a collaborative manner. Hence, it is recommended that the companies should mainly consider the initial developments of the storage facilities. Moreover, location selection for effective energy storage should also be considered to increase the performance of these investments.
Published: 2021
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28. JUNO sensitivity to low energy atmospheric neutrino spectra

Author: Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Guangpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Eric Baussan, Marco Bellato, Antonio Bergnoli, Enrico Bernieri, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Alexey Chetverikov, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Salvatore Costa, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Dmitry Dolzhikov, Georgy Donchenko, Jianmeng Dong, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Can Fang, Jian Fang, Wenxing Fang, Marco Fargetta, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Christoph Genster, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Maxim Gonchar, Guanghua Gong, Hui Gong, Oleg Gorchakov, Yuri Gornushkin, Alexandre Göttel, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Sohaib Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, Daojin Hong, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Qinhua Huang, Wenhao Huang, Xin Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Antonio Insolia, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Ignacio Jeria, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Michael Karagounis, Narine Kazarian, Waseem Khan, Khanchai Khosonthongkee, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Zinovy Krumshteyn, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Mengzhao Li, Min Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhaohan Li, Zhibing Li, Ziyuan Li, Hao Liang, Jingjing Liang, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Xiwen Liu, Yan Liu, Yunzhe Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Bangzheng Ma, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Davit Mayilyan, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Salvatore Monforte, Paolo Montini, Michele Montuschi, Axel Müller, Pavithra Muralidharan, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Minh Thuan Nguyen Thi, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Rainer Othegraven, Hsiao-Ru Pan, Alessandro Paoloni, Nina Parkalian, Sergio Parmeggiano, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Oliver Pilarczyk, Luis Felipe Piñeres Rico, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Zhen Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Usman Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Taras Rezinko, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Giuseppe Salamanna, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Jacky Schuler, Cédric Schwab, Konstantin Schweizer, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Arina Shaydurova, Jingyan Shi, Yanan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Sergey Sokolov, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondřej Šrámek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Gongxing Sun, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Nikita Ushakov, Johannes van den Boom, Stefan van Waasen, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Moritz Cornelius Vollbrecht, Cristina Volpe, Vit Vorobel, Dmitriy Voronin, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Muhammad Waqas, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Wenlu Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Wenjie Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Hangkun Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Taylor Yan, Wenqi Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Na Yin, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Zezhong Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Vitalii Zavadskyi, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Aiqiang Zhang, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Jinnan Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Xueyao Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Tong Zhou, Xiang Zhou, Jiang Zhu, Kejun Zhu, Zhihang Zhu, Bo Zhuang, Honglin Zhuang, Liang Zong, Jiaheng Zou, and The JUNO Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Atmospheric neutrinos are one of the most relevant natural neutrino sources that can be exploited to infer properties about cosmic rays and neutrino oscillations. The Jiangmen Underground Neutrino Observatory (JUNO) experiment, a 20 kton liquid scintillator detector with excellent energy resolution is currently under construction in China. JUNO will be able to detect several atmospheric neutrinos per day given the large volume. A study on the JUNO detection and reconstruction capabilities of atmospheric $$\nu _e$$ ν e and $$\nu _\mu $$ ν μ fluxes is presented in this paper. In this study, a sample of atmospheric neutrino Monte Carlo events has been generated, starting from theoretical models, and then processed by the detector simulation. The excellent timing resolution of the 3” PMT light detection system of JUNO detector and the much higher light yield for scintillation over Cherenkov allow to measure the time structure of the scintillation light with very high precision. Since $$\nu _e$$ ν e and $$\nu _\mu $$ ν μ interactions produce a slightly different light pattern, the different time evolution of light allows to discriminate the flavor of primary neutrinos. A probabilistic unfolding method has been used, in order to infer the primary neutrino energy spectrum from the detector experimental observables. The simulated spectrum has been reconstructed between 100 MeV and 10 GeV, showing a great potential of the detector in the atmospheric low energy region.
Published: 2021
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29. Constraints on the axial-vector and pseudo-scalar mediated WIMP-nucleus interactions from PandaX-4T experiment

Author: Zhou Huang, Chencheng Han, Abdusalam Abdukerim, Zihao Bo, Wei Chen, Xun Chen, Yunhua Chen, Chen Cheng, Zhaokan Cheng, Xiangyi Cui, Yingjie Fan, Deqing Fang, Changbo Fu, Mengting Fu, Lisheng Geng, Karl Giboni, Linhui Gu, Xuyuan Guo, Ke Han, Changda He, Jinrong He, Di Huang, Yanlin Huang, Ruquan Hou, Xiangdong Ji, Yonglin Ju, Chenxiang Li, Jiafu Li, Mingchuan Li, Shu Li, Shuaijie Li, Qing Lin, Jianglai Liu, Xiaoying Lu, Lingyin Luo, Yunyang Luo, Wenbo Ma, Yugang Ma, Yajun Mao, Yue Meng, Xuyang Ning, Ningchun Qi, Zhicheng Qian, Xiangxiang Ren, Nasir Shaheed, Changsong Shang, Xiaofeng Shang, Guofang Shen, Lin Si, Wenliang Sun, Andi Tan, Yi Tao, Anqing Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Zhou Wang, Yuehuan Wei, Mengmeng Wu, Weihao Wu, Jingkai Xia, Mengjiao Xiao, Xiang Xiao, Pengwei Xie, Binbin Yan, Xiyu Yan, Jijun Yang, Yong Yang, Chunxu Yu, Jumin Yuan, Zhe Yuan, Xinning Zeng, Dan Zhang, Minzhen Zhang, Peng Zhang, Shibo Zhang, Shu Zhang, Tao Zhang, Yingxin Zhang, Yuanyuan Zhang, Li Zhao, Qibin Zheng, Jifang Zhou, Ning Zhou, Xiaopeng Zhou, Yong Zhou, and Yubo Zhou
Subjects: Dark matter, Mediator, Axial-vector, Pseudo-scalar, Physics, QC1-999
Abstract: We present the constraints on the axial-vector and pseudo-scalar mediated WIMP-nucleus interactions from the PandaX-4T experiment, using the data set corresponding to a total exposure of 0.63 tonne⋅year. No significant signal excess is observed, and the most stringent constraints to date on the mediator mass are set for the axial-vector and pseudo-scalar simplified models. The maximum excluded mass of an axial-vector mediator is 825 GeV/c2 and that of a pseudo-scalar mediator is 106 GeV/c2. In addition, the upper limits on the spin-dependent WIMP-nucleon scattering cross-section for conventional neutron-only and proton-only interactions are derived.
Published: 2022
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30. Discovery and Characterization of Cross-Area and Intra-Area SSOs Sensitive to Delay in Droop Control of Grid-Forming Converters

Author: Karunaratne, Lilan, Chaudhuri, Nilanjan Ray, Yogarathnam, Amirthagunaraj, and Yue, Meng
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: Subsynchronous oscillations (SSOs) involving grid-forming converters (GFCs) are in a less familiar territory of power system dynamics. This letter reports a new phenomenon namely cross-area SSOs in grids with 100% droop-controlled GFC-based renewable penetration, which was discovered during our study on evaluating the adequacy of quasistationary phasor calculus (QPC) and space phasor calculus (SPC)-based models in capturing SSOs. We present frequency-domain characterization of such oscillatory modes in addition to intra-area SSOs in grids involving GFCs and study the impact of a delay in power-frequency droop feedback loop in regards to their stability. Electromagnetic transient (EMT) simulations validate our findings.
Published: 2024

31. A search for two-component Majorana dark matter in a simplified model using the full exposure data of PandaX-II experiment

Author: Ying Yuan, Abdusalam Abdukerim, Zihao Bo, Wei Chen, Xun Chen, Yunhua Chen, Chen Cheng, Xiangyi Cui, Yingjie Fan, Deqing Fang, Changbo Fu, Mengting Fu, Lisheng Geng, Karl Giboni, Linhui Gu, Xuyuan Guo, Ke Han, Changda He, Jinrong He, Di Huang, Yanlin Huang, Zhou Huang, Ruquan Hou, Xiangdong Ji, Yonglin Ju, Chenxiang Li, Mingchuan Li, Shu Li, Shuaijie Li, Qing Lin, Jianglai Liu, Xiaoying Lu, Lingyin Luo, Wenbo Ma, Yugang Ma, Yajun Mao, Yue Meng, Nasir Shaheed, Xuyang Ning, Ningchun Qi, Zhicheng Qian, Xiangxiang Ren, Changsong Shang, Guofang Shen, Lin Si, Wenliang Sun, Andi Tan, Yi Tao, Anqing Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Zhou Wang, Mengmeng Wu, Weihao Wu, Jingkai Xia, Mengjiao Xiao, Xiang Xiao, Pengwei Xie, Binbin Yan, Xiyu Yan, Jijun Yang, Yong Yang, Chunxu Yu, Jumin Yuan, Dan Zhang, Minzhen Zhang, Peng Zhang, Tao Zhang, Li Zhao, Qibin Zheng, Jifang Zhou, Ning Zhou, Xiaopeng Zhou, and Yong Zhou
Subjects: Two-component Majorana dark matter, Simplified model, Direct detection, Physics, QC1-999
Abstract: In the two-component Majorana dark matter model, one dark matter particle can scatter off the target nuclei, and turn into a slightly heavier component. In the framework of a simplified model with a vector boson mediator, both the tree-level and loop-level processes contribute to the signal in direct detection experiment. In this paper, we report the search results for such dark matter from PandaX-II experiment, using total data of the full 100.7 tonne⋅day exposure. No significant excess is observed, so strong constraints on the combined parameter space of mediator mass and dark matter mass are derived. With the complementary search results from collider experiments, a large range of parameter space can be excluded.
Published: 2022
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32. Synechococcus sp. PCC7002 Uses Peroxiredoxin to Cope with Reactive Sulfur Species Stress

Author: Daixi Liu, Jinyu Chen, Yafei Wang, Yue Meng, Yuanning Li, Ranran Huang, Yongzhen Xia, Huaiwei Liu, Nianzhi Jiao, Luying Xun, and Jihua Liu
Subjects: peroxiredoxin, reactive sulfur species, cyanobacteria, sulfane sulfur reduction, Microbiology, QR1-502
Abstract: ABSTRACT Cyanobacteria are a widely distributed group of microorganisms in the ocean, and they often need to cope with the stress of reactive sulfur species, such as sulfide and sulfane sulfur. Sulfane sulfur refers to the various forms of zero-valent sulfur, including persulfide, polysulfide, and element sulfur (S8). Although sulfane sulfur participates in signaling transduction and resistance to reactive oxygen species in cyanobacteria, it is toxic at high concentrations and induces sulfur stress, which has similar effects to oxidative stress. In this study, we report that Synechococcus sp. PCC7002 uses peroxiredoxin to cope with the stress of cellular sulfane sulfur. Synechococcus sp. PCC7002 contains six peroxiredoxins, and all were induced by S8. Peroxiredoxin I (PrxI) reduced S8 to H2S by forming a disulfide bond between residues Cys53 and Cys153 of the enzyme. A partial deletion strain of Synechococcus sp. PCC7002 with decreased copy numbers of the prxI gene was more sensitive to S8 than was the wild type. Thus, peroxiredoxin is involved in maintaining the homeostasis of cellular sulfane sulfur in cyanobacteria. Given that peroxiredoxin evolved before the occurrence of O2 on Earth, its original function could have been to cope with reactive sulfur species stress, and that function has been preserved. IMPORTANCE Cyanobacteria are the earliest microorganisms that perform oxygenic photosynthesis, which has played a key role in the evolution of life on Earth, and they are the most important primary producers in the modern oceans. The cyanobacterium Synechococcus sp. PCC7002 uses peroxiredoxin to reduce high levels of sulfane sulfur. That function is possibly the original role of peroxiredoxin, as the enzyme evolved before the appearance of O2 on Earth. The preservation of the reduction of sulfane sulfur by peroxiredoxin5-type peroxiredoxins may offer cyanobacteria an advantage in the complex environment of the modern oceans.
Published: 2022
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33. Fiber Laser-Based Lasso-Shaped Biosensor for High Precision Detection of Cancer Biomarker-CEACAM5 in Serum

Author: Jie Hu, Enlai Song, Yuhui Liu, Qiaochu Yang, Junhui Sun, Jinna Chen, Yue Meng, Yanwei Jia, Zhiguang Yu, Yang Ran, Liyang Shao, and Perry Ping Shum
Subjects: optical fiber biosensor, fiber laser, lasso structure, CEACAM5 protein, human serum, Biotechnology, TP248.13-248.65
Abstract: Detection of trace tumor markers in blood/serum is essential for the early screening and prognosis of cancer diseases, which requires high sensitivity and specificity of the assays and biosensors. A variety of label-free optical fiber-based biosensors has been developed and yielded great opportunities for Point-of-Care Testing (POCT) of cancer biomarkers. The fiber biosensor, however, suffers from a compromise between the responsivity and stability of the sensing signal, which would deteriorate the sensing performance. In addition, the sophistication of sensor preparation hinders the reproduction and scale-up fabrication. To address these issues, in this study, a straightforward lasso-shaped fiber laser biosensor was proposed for the specific determination of carcinoembryonic antigen (CEA)-related cell adhesion molecules 5 (CEACAM5) protein in serum. Due to the ultra-narrow linewidth of the laser, a very small variation of lasing signal caused by biomolecular bonding can be clearly distinguished via high-resolution spectral analysis. The limit of detection (LOD) of the proposed biosensor could reach 9.6 ng/mL according to the buffer test. The sensing capability was further validated by a human serum-based cancer diagnosis trial, enabling great potential for clinical use. The high reproduction of fabrication allowed the mass production of the sensor and extended its utility to a broader biosensing field.
Published: 2023
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34. Carbon-Emission Density of Crop Production in China: Spatiotemporal Characteristics, Regional Disparities, and Convergence

Author: Haoyue Wu, Wanqi Yan, Xiangjiang Zheng, Lei Zhou, Jinshan Ma, Lu Liu, and Yue Meng
Subjects: carbon emissions, crop production, carbon footprint, spatiotemporal characteristics, convergence test, spatial econometric model, Agriculture (General), S1-972
Abstract: An analysis of carbon emissions of crop production provides paths for global warming mitigation. Existing studies have focused on the magnitude of the carbon emissions from crop production, which is unreasonable for inter-location comparison due to neglecting regional variations in cultivation technologies and planting scale. Different from the conventional idea, this paper estimated the carbon-emission density of crop production (CEDCP) based on carbon emissions per hectare of crop production. With the 30 Chinese provinces between 2000 and 2020 as the study area, temporal dynamics and spatial patterns of the CEDCP were explored, regional disparities of the CEDCP were discussed based on the Theil index, and the possibility of regional coordinated optimization for the CEDCP was explored by relying on the convergence tests. The results show that the average annual CEDCP in China was 1.462 t/hm2, reaching a peak of 1.576 t/hm2 in 2015. The national carbon-emission densities of agricultural materials, rice fields, soil management, and straw burning were 0.492 t/hm2, 0.390 t/hm2, 0.189 t/hm2, and 0.391 t/hm2, respectively. In many provinces, the CEDCP increased first and then decreased, presenting a spatial pattern of high in the eastern region and low in the western region. Regional disparities of CEDCP shrank early but expanded later, and the disparities within the western region had always contributed considerably to the overall disparities. The CEDCP had shown σ- and β- convergence in both national and regional scales, and the convergence process had positive spillover effects. These findings suggest that inter-provincial cooperation may facilitate the CEDCP to converge.
Published: 2023
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35. A hybrid heterogeneous Pythagorean fuzzy group decision modelling for crowdfunding development process pathways of fintech-based clean energy investment projects

Author: Yue Meng, Haoyue Wu, Wenjing Zhao, Wenkuan Chen, Hasan Dinçer, and Serhat Yüksel
Subjects: Crowdfunding, Project financing, Clean energy investments, New service development, PERT, Group decision making, Public finance, K4430-4675, Finance, HG1-9999
Abstract: Abstract This study aims to evaluate the crowdfunding alternatives regarding new service development process pathways of clean energy investment projects. In this framework, a new model has been generated by considering the consensus-based group decision-making with incomplete preferences, Pythagorean fuzzy decision-making trial and evaluation laboratory (DEMATEL) and technique for order preference by similarity to ideal solution (TOPSIS). Moreover, a comparative evaluation has been performed with Vise Kriterijumska Optimizacija I. Kompromisno Resenje methodology and sensitivity analysis has been made by considering 4 different cases. The main contribution is to identify appropriate crowdfunding-based funding alternatives for the improvement of the clean energy investments with a novel MCDM model. By considering the iteration technique and consensus-based analysis, the missing parts in the evaluations can be completed and opposite opinion problems can be reduced. Furthermore, with the help of hybrid MCDM model by combining DEMATEL and TOPSIS, more objective results can be reached. It is concluded that the analysis results are coherent and reliable. The findings indicate that the full launch is the most significant criterion for equity and debt-based crowdfunding alternatives. On the other side, the analysis has the highest weight for reward and donation-based alternatives whereas design is the most essential item regarding the royalty-based alternative. Additionally, it is also defined that equity-based crowdfunding alternative is the most significant for the service development process of clean energy investment projects. In this way, it will be possible to provide a continuous resource for clean energy investment projects. On the other hand, by providing financing with equity, there will be no fixed financing cost for clean energy investors. If these investors make a profit, they distribute dividends with the decision of their authorized bodies.
Published: 2021
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36. Calibration strategy of the JUNO experiment

Author: The JUNO collaboration, Angel Abusleme, Thomas Adam, Shakeel Ahmad, Rizwan Ahmed, Sebastiano Aiello, Muhammad Akram, Fengpeng An, Guangpeng An, Qi An, Giuseppe Andronico, Nikolay Anfimov, Vito Antonelli, Tatiana Antoshkina, Burin Asavapibhop, João Pedro Athayde Marcondes de André, Didier Auguste, Andrej Babic, Wander Baldini, Andrea Barresi, Eric Baussan, Marco Bellato, Antonio Bergnoli, Enrico Bernieri, Thilo Birkenfeld, Sylvie Blin, David Blum, Simon Blyth, Anastasia Bolshakova, Mathieu Bongrand, Clément Bordereau, Dominique Breton, Augusto Brigatti, Riccardo Brugnera, Riccardo Bruno, Antonio Budano, Mario Buscemi, Jose Busto, Ilya Butorov, Anatael Cabrera, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Cai, Antonio Cammi, Agustin Campeny, Chuanya Cao, Guofu Cao, Jun Cao, Rossella Caruso, Cédric Cerna, Jinfan Chang, Yun Chang, Pingping Chen, Po-An Chen, Shaomin Chen, Shenjian Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Chen, Jie Cheng, Yaping Cheng, Davide Chiesa, Pietro Chimenti, Artem Chukanov, Anna Chuvashova, Gérard Claverie, Catia Clementi, Barbara Clerbaux, Selma Conforti Di Lorenzo, Daniele Corti, Salvatore Costa, Flavio Dal Corso, Olivia Dalager, Christophe De La Taille, Jiawei Deng, Zhi Deng, Ziyan Deng, Wilfried Depnering, Marco Diaz, Xuefeng Ding, Yayun Ding, Bayu Dirgantara, Sergey Dmitrievsky, Tadeas Dohnal, Georgy Donchenko, Jianmeng Dong, Damien Dornic, Evgeny Doroshkevich, Marcos Dracos, Frédéric Druillole, Shuxian Du, Stefano Dusini, Martin Dvorak, Timo Enqvist, Heike Enzmann, Andrea Fabbri, Lukas Fajt, Donghua Fan, Lei Fan, Can Fang, Jian Fang, Marco Fargetta, Anna Fatkina, Dmitry Fedoseev, Vladko Fekete, Li-Cheng Feng, Qichun Feng, Richard Ford, Andrey Formozov, Amélie Fournier, Haonan Gan, Feng Gao, Alberto Garfagnini, Alexandre Göttel, Christoph Genster, Marco Giammarchi, Agnese Giaz, Nunzio Giudice, Franco Giuliani, Maxim Gonchar, Guanghua Gong, Hui Gong, Oleg Gorchakov, Yuri Gornushkin, Marco Grassi, Christian Grewing, Vasily Gromov, Minghao Gu, Xiaofei Gu, Yu Gu, Mengyun Guan, Nunzio Guardone, Maria Gul, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Guo, Paul Hackspacher, Caren Hagner, Ran Han, Yang Han, Muhammad Hassan, Miao He, Wei He, Tobias Heinz, Patrick Hellmuth, Yuekun Heng, Rafael Herrera, Daojin Hong, YuenKeung Hor, Shaojing Hou, Yee Hsiung, Bei-Zhen Hu, Hang Hu, Jianrun Hu, Jun Hu, Shouyang Hu, Tao Hu, Zhuojun Hu, Chunhao Huang, Guihong Huang, Hanxiong Huang, Qinhua Huang, Wenhao Huang, Xingtao Huang, Yongbo Huang, Jiaqi Hui, Lei Huo, Wenju Huo, Cédric Huss, Safeer Hussain, Antonio Insolia, Ara Ioannisian, Roberto Isocrate, Beatrice Jelmini, Kuo-Lun Jen, Xiaolu Ji, Xingzhao Ji, Huihui Jia, Junji Jia, Siyu Jian, Di Jiang, Xiaoshan Jiang, Ruyi Jin, Xiaoping Jing, Cécile Jollet, Jari Joutsenvaara, Sirichok Jungthawan, Leonidas Kalousis, Philipp Kampmann, Li Kang, Michael Karagounis, Narine Kazarian, Amir Khan, Waseem Khan, Khanchai Khosonthongkee, Patrick Kinz, Denis Korablev, Konstantin Kouzakov, Alexey Krasnoperov, Svetlana Krokhaleva, Zinovy Krumshteyn, Andre Kruth, Nikolay Kutovskiy, Pasi Kuusiniemi, Tobias Lachenmaier, Cecilia Landini, Sébastien Leblanc, Victor Lebrin, Frederic Lefevre, Ruiting Lei, Rupert Leitner, Jason Leung, Demin Li, Fei Li, Fule Li, Haitao Li, Huiling Li, Jiaqi Li, Jin Li, Kaijie Li, Mengzhao Li, Nan Li, Qingjiang Li, Ruhui Li, Shanfeng Li, Shuaijie Li, Tao Li, Weidong Li, Weiguo Li, Xiaomei Li, Xiaonan Li, Xinglong Li, Yi Li, Yufeng Li, Zhibing Li, Ziyuan Li, Hao Liang, Jingjing Liang, Daniel Liebau, Ayut Limphirat, Sukit Limpijumnong, Guey-Lin Lin, Shengxin Lin, Tao Lin, Jiajie Ling, Ivano Lippi, Fang Liu, Haidong Liu, Hongbang Liu, Hongjuan Liu, Hongtao Liu, Hu Liu, Hui Liu, Jianglai Liu, Jinchang Liu, Min Liu, Qian Liu, Qin Liu, Runxuan Liu, Shuangyu Liu, Shubin Liu, Shulin Liu, Xiaowei Liu, Yan Liu, Alexey Lokhov, Paolo Lombardi, Claudio Lombardo, Kai Loo, Chuan Lu, Haoqi Lu, Jingbin Lu, Junguang Lu, Shuxiang Lu, Xiaoxu Lu, Bayarto Lubsandorzhiev, Sultim Lubsandorzhiev, Livia Ludhova, Fengjiao Luo, Guang Luo, Pengwei Luo, Shu Luo, Wuming Luo, Vladimir Lyashuk, Qiumei Ma, Si Ma, Xiaoyan Ma, Xubo Ma, Jihane Maalmi, Yury Malyshkin, Fabio Mantovani, Francesco Manzali, Xin Mao, Yajun Mao, Stefano M. Mari, Filippo Marini, Sadia Marium, Cristina Martellini, Gisele Martin-Chassard, Agnese Martini, Davit Mayilyan, Axel Müller, Ints Mednieks, Yue Meng, Anselmo Meregaglia, Emanuela Meroni, David Meyhöfer, Mauro Mezzetto, Jonathan Miller, Lino Miramonti, Salvatore Monforte, Paolo Montini, Michele Montuschi, Nikolay Morozov, Waqas Muhammad, Pavithra Muralidharan, Massimiliano Nastasi, Dmitry V. Naumov, Elena Naumova, Diana Navas-Nicolas, Igor Nemchenok, Feipeng Ning, Zhe Ning, Hiroshi Nunokawa, Lothar Oberauer, Juan Pedro Ochoa-Ricoux, Alexander Olshevskiy, Domizia Orestano, Fausto Ortica, Hsiao-Ru Pan, Alessandro Paoloni, Nina Parkalian, Sergio Parmeggiano, Teerapat Payupol, Yatian Pei, Nicomede Pelliccia, Anguo Peng, Haiping Peng, Frédéric Perrot, Pierre-Alexandre Petitjean, Fabrizio Petrucci, Luis Felipe Piñeres Rico, Oliver Pilarczyk, Artyom Popov, Pascal Poussot, Wathan Pratumwan, Ezio Previtali, Fazhi Qi, Ming Qi, Sen Qian, Xiaohui Qian, Hao Qiao, Zhonghua Qin, Shoukang Qiu, Muhammad Rajput, Gioacchino Ranucci, Neill Raper, Alessandra Re, Henning Rebber, Abdel Rebii, Bin Ren, Jie Ren, Taras Rezinko, Barbara Ricci, Markus Robens, Mathieu Roche, Narongkiat Rodphai, Aldo Romani, Bedřich Roskovec, Christian Roth, Xiangdong Ruan, Xichao Ruan, Saroj Rujirawat, Arseniy Rybnikov, Andrey Sadovsky, Paolo Saggese, Giuseppe Salamanna, Simone Sanfilippo, Anut Sangka, Nuanwan Sanguansak, Utane Sawangwit, Julia Sawatzki, Fatma Sawy, Michaela Schever, Jacky Schuler, Cédric Schwab, Konstantin Schweizer, Dmitry Selivanov, Alexandr Selyunin, Andrea Serafini, Giulio Settanta, Mariangela Settimo, Zhuang Shao, Vladislav Sharov, Jingyan Shi, Vitaly Shutov, Andrey Sidorenkov, Fedor Šimkovic, Chiara Sirignano, Jaruchit Siripak, Monica Sisti, Maciej Slupecki, Mikhail Smirnov, Oleg Smirnov, Thiago Sogo-Bezerra, Julanan Songwadhana, Boonrucksar Soonthornthum, Albert Sotnikov, Ondrej Sramek, Warintorn Sreethawong, Achim Stahl, Luca Stanco, Konstantin Stankevich, Dušan Štefánik, Hans Steiger, Jochen Steinmann, Tobias Sterr, Matthias Raphael Stock, Virginia Strati, Alexander Studenikin, Gongxing Sun, Shifeng Sun, Xilei Sun, Yongjie Sun, Yongzhao Sun, Narumon Suwonjandee, Michal Szelezniak, Jian Tang, Qiang Tang, Quan Tang, Xiao Tang, Alexander Tietzsch, Igor Tkachev, Tomas Tmej, Konstantin Treskov, Andrea Triossi, Giancarlo Troni, Wladyslaw Trzaska, Cristina Tuve, Stefan van Waasen, Johannes van den Boom, Guillaume Vanroyen, Nikolaos Vassilopoulos, Vadim Vedin, Giuseppe Verde, Maxim Vialkov, Benoit Viaud, Cristina Volpe, Vit Vorobel, Lucia Votano, Pablo Walker, Caishen Wang, Chung-Hsiang Wang, En Wang, Guoli Wang, Jian Wang, Jun Wang, Kunyu Wang, Lu Wang, Meifen Wang, Meng Wang, Ruiguang Wang, Siguang Wang, Wei Wang, Wenshuai Wang, Xi Wang, Xiangyue Wang, Yangfu Wang, Yaoguang Wang, Yi Wang, Yifang Wang, Yuanqing Wang, Yuman Wang, Zhe Wang, Zheng Wang, Zhimin Wang, Zongyi Wang, Apimook Watcharangkool, Lianghong Wei, Wei Wei, Yadong Wei, Liangjian Wen, Christopher Wiebusch, Steven Chan-Fai Wong, Bjoern Wonsak, Diru Wu, Fangliang Wu, Qun Wu, Wenjie Wu, Zhi Wu, Michael Wurm, Jacques Wurtz, Christian Wysotzki, Yufei Xi, Dongmei Xia, Mengjiao Xiao, Yuguang Xie, Zhangquan Xie, Zhizhong Xing, Benda Xu, Cheng Xu, Donglian Xu, Fanrong Xu, Jilei Xu, Jing Xu, Meihang Xu, Yin Xu, Yu Xu, Baojun Yan, Xiongbo Yan, Yupeng Yan, Anbo Yang, Changgen Yang, Huan Yang, Jie Yang, Lei Yang, Xiaoyu Yang, Yifan Yang, Haifeng Yao, Zafar Yasin, Jiaxuan Ye, Mei Ye, Ziping Ye, Ugur Yegin, Frédéric Yermia, Peihuai Yi, Xiangwei Yin, Zhengyun You, Boxiang Yu, Chiye Yu, Chunxu Yu, Hongzhao Yu, Miao Yu, Xianghui Yu, Zeyuan Yu, Chengzhuo Yuan, Ying Yuan, Zhenxiong Yuan, Ziyi Yuan, Baobiao Yue, Noman Zafar, Andre Zambanini, Shan Zeng, Tingxuan Zeng, Yuda Zeng, Liang Zhan, Feiyang Zhang, Guoqing Zhang, Haiqiong Zhang, Honghao Zhang, Jiawen Zhang, Jie Zhang, Jingbo Zhang, Peng Zhang, Qingmin Zhang, Shiqi Zhang, Shu Zhang, Tao Zhang, Xiaomei Zhang, Xuantong Zhang, Yan Zhang, Yinhong Zhang, Yiyu Zhang, Yongpeng Zhang, Yuanyuan Zhang, Yumei Zhang, Zhenyu Zhang, Zhijian Zhang, Fengyi Zhao, Jie Zhao, Rong Zhao, Shujun Zhao, Tianchi Zhao, Dongqin Zheng, Hua Zheng, Minshan Zheng, Yangheng Zheng, Weirong Zhong, Jing Zhou, Li Zhou, Nan Zhou, Shun Zhou, Xiang Zhou, Jiang Zhu, Kejun Zhu, Honglin Zhuang, Liang Zong, and Jiaheng Zou
Subjects: Neutrino Detectors and Telescopes (experiments), Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract We present the calibration strategy for the 20 kton liquid scintillator central detector of the Jiangmen Underground Neutrino Observatory (JUNO). By utilizing a comprehensive multiple-source and multiple-positional calibration program, in combination with a novel dual calorimetry technique exploiting two independent photosensors and readout systems, we demonstrate that the JUNO central detector can achieve a better than 1% energy linearity and a 3% effective energy resolution, required by the neutrino mass ordering determination.
Published: 2021
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37. Tendon‐to‐bone healing after repairing full‐thickness rotator cuff tear with a triple‐loaded single‐row method in young patients

Author: He-Bei He, Tao Wang, Min-Cong Wang, Hui-Feng Zhu, Yue Meng, Cheng-Long Pan, Yong Hu, Xiao-Min Chao, Chun Yang Yang, Min Wang, and Jian Feng Ou-Yang
Subjects: Rotator cuff tear, Arthroscopic repair, Single‐row, Regeneration, Bone marrow vents, Diseases of the musculoskeletal system, RC925-935
Abstract: Abstract Background Arthroscopic repair is recommended for young patients with full-thickness rotator cuff tears (RCTs), but the healing rates have raised concerns. The Southern California Orthopedic Institute (SCOI) row method has been developed based on greater than 3 decades of experience with excellent clinical outcomes; however, studies with a focus on the younger patient population are limited in number. The current study assessed the short-term clinical outcome and the initial tendon-to-bone healing in a young cohort after repair of a full-thickness RCT using the SCOI row method. Methods A retrospective cohort study was performed. Patients
Published: 2021
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38. Less blood loss in supercapsular percutaneously assisted versus posterolateral total hip arthroplasty

Author: Yong Hu, Min-Cong Wang, Tao Wang, Yue Meng, Xiao-Min Chao, Hui-Feng Zhu, Cheng-Guo Li, Cheng-Long Pan, and He-Bei He
Subjects: Total hip arthroplasty, Supercapsular percutaneously assisted, Minimally invasive, Blood loss, Transfusion, Orthopedic surgery, RD701-811, Diseases of the musculoskeletal system, RC925-935
Abstract: Abstract Background Although excellent clinical outcomes of supercapsular percutaneously assisted total hip arthroplasty (SuperPath) have been reported, the peri-operative blood loss has rarely been reported. The current study determined the blood loss during SuperPath and compared the blood loss with conventional posterolateral total hip arthroplasty (PLTH). Methods This retrospective study enrolled patients who underwent unilateral primary THA between January 2017 and December 2019. The demographic data, diagnoses, affected side, radiographic findings, hemoglobin concentration, hematocrit, operative time, transfusion requirements, and intra-operative blood loss were recorded. The peri-operative blood loss was calculated using the OSTHEO formula. Blood loss on the 1st, 3rd, and 5th post-operative days was calculated. Hidden blood loss (HBL) was determined by subtracting the intra-operative blood loss from the total blood loss. Results Two hundred sixty-three patients were included in the study, 85 of whom were in the SuperPath group and 178 in the posterolateral total hip arthroplasty (PLTH) group. Patient demographics, diagnoses, affected side, operative times, and pre-operative hemoglobin concentrations did not differ significantly between the two groups (all P > 0.05). Compared to the PLTH group, the SuperPath group had less blood loss, including intra-operative blood loss, 1st, 3rd, and 5th post-operative days blood loss, and HBL (all P
Published: 2021
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39. Reliability Assessment Model of IMA Partition Software Using Stochastic Petri Nets

Author: Wu Zhijun, Ma Haolin, and Yue Meng
Subjects: Integrated modular avionics, partition software, stochastic petri nets, reliability, fault tree analysis, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: In order to reduce the failure rate of Integrated Modular Avionics (IMA) partition software, due to the reliability block diagram (RBD) method, fault tree analysis (FTA) method and GO method cannot describe the state transition process of partition software, according to the ARINC 653 standard and the actual running status of the partition software, this paper determines the state machine and conversion delay of the partition software, and establishes the stochastic Petri nets (SPN) reliability quantitative model of the partition software. By proving that each transition in the SPN model of the partition software approximately obeying exponential distribution, and according to the reachable state tree of the SPN isomorphic to a homogeneous Markov chain (MC), the steady-state probability of the partition software in the fault state is calculated to be 5.2778*10-9 by using MC stochastic process theory. The factors affecting the reliability of the partition software are obtained, and the sensitivity of each factor to the model is studied. Finally, the relevant conclusions are drawn to provide guidance for improving the reliability of partition software.
Published: 2021
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40. TRIZ-Based Green Energy Project Evaluation Using Innovation Life Cycle and Fuzzy Modeling

Author: Yue Meng, Hasan Dincer, and Serhat Yuksel
Subjects: Green energy, PERT, TRIZ, innovation life cycle, integer code series, DEMATEL, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: This study evaluates theory of the solution of inventive problems (TRIZ)-based green energy project network based on innovation life cycle. In this context, TRIZ-based combinations are obtained by integer patterns for green energy projects. In the next phase, activity priorities of TRIZ-based principles are measured for green energy projects with Pythagorean fuzzy (PF) technique for order preference by similarity to ideal solution (TOPSIS). Finally, project evaluation review technique (PERT) and PF decision making trial and evaluation laboratory (DEMATEL) approaches are taken into consideration to score the green energy projects based on innovation life cycle using inventive problem-solving principles. TRIZ-based principles are also ranked by using Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Additionally, all calculations have also been made with Spherical fuzzy (SF) sets in addition to the PF sets. It is concluded that the analysis results are quite reliable. The main contribution of this study is that innovative strategies are identified for green energy investment projects with a novel methodology. The findings indicate that dynamicity and transformation of properties play a crucial role in this process. Therefore, green energy investors should closely follow technological developments in this area and the products used in green energy investments should be easily adapted to these developments. Additionally, the principal of prior action should be considered to reduce the costs instead of periodic action. It is obvious that the necessary controls should be made before the project starts to increase the efficiency and productivity.
Published: 2021
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41. Superconductivity in SrB_{3}C_{3} clathrate

Author: Li Zhu, Hanyu Liu, Maddury Somayazulu, Yue Meng, Piotr A. Guńka, Thomas B. Shiell, Curtis Kenney-Benson, Stella Chariton, Vitali B. Prakapenka, Hyeok Yoon, Jarryd A. Horn, Johnpierre Paglione, Roald Hoffmann, R. E. Cohen, and Timothy A. Strobel
Subjects: Physics, QC1-999
Abstract: We predict superconductivity for the carbon–boron clathrate SrB_{3}C_{3} with T_{c}=27–43K for Coulomb pseudopotential (μ^{*}) values between 0.17 and 0.10 using first-principles calculations with conventional electron–phonon coupling. Electrical transport measurements, facilitated by an in situ experimental design compatible with extreme synthesis conditions (>3000K at 50 GPa), show nonhysteretic resistivity drops that track the calculated magnitude and pressure dependence of superconductivity for μ^{*}≈0.15, and transport measurements collected under applied magnetic fields indicate superconductivity with an onset T_{c} of approximately 20 K at 40 GPa. Carbon-based clathrates thus represent a class of superconductors similar to other covalent metals like MgB_{2} and doped fullerenes. Carbon clathrates share structures similar to superconducting superhydrides with wide potential for tunable properties, and covalent C–B bonds allow metastable persistence at ambient conditions.
Published: 2023
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42. Silk fibroin hydrolysate improves memory impairment via multi-target function

Author: Siyuan Yao, Zheng Xu, Song Chen, Yue Meng, Yue Xue, Wenbing Yao, and Xiangdong Gao
Subjects: Silk fibroin hydrolysate, Alzheimer’s disease, Neuroinflammation, MAPKs /NF-κB signaling pathway, Neuroprotection, Nutrition. Foods and food supply, TX341-641
Abstract: Previously we have reported a specific hydrolysate form of silk fibroin named SFH and in vitro beneficial effects of SFH on neuron, however, evidence in vivo for the specific neuroprotective function of SFH on AD is urgently needed and our understanding for mechanism underlying SFH function is far from completion. In this study, we report here the amelioration of neurodegenerative changes in Aβ25-35-induced rat models of AD by SFH. We found that SFH in vivo significantly attenuated impairment of spatial learning and memory, prevented neuronal damages and decreased multisite tau hyperphosphorylation induced by Aβ25-35. In vivo and in vitro results also further indicated that the beneficial effect of SFH on AD may be due to its interference with microglia-mediated neuroinflammation. SFH can inhibit abnormal activation of microglial and expressions of proinflammatory mediators in Aβ25-35-induced rat and rat primary microglia models can be inhibited by SFH via MAPKs /NF-κB signaling pathway.
Published: 2022
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43. Determination of Double Beta Decay Half-Life of 136Xe with the PandaX-4T Natural Xenon Detector

Author: Lin Si, Zhaokan Cheng, Abdusalam Abdukerim, Zihao Bo, Wei Chen, Xun Chen, Yunhua Chen, Chen Cheng, Yunshan Cheng, Xiangyi Cui, Yingjie Fan, Deqing Fang, Changbo Fu, Mengting Fu, Lisheng Geng, Karl Giboni, Linhui Gu, Xuyuan Guo, Ke Han, Changda He, Jinrong He, Di Huang, Yanlin Huang, Zhou Huang, Ruquan Hou, Xiangdong Ji, Yonglin Ju, Chenxiang Li, Jiafu Li, Mingchuan Li, Shu Li, Shuaijie Li, Qing Lin, Jianglai Liu, Xiaoying Lu, Lingyin Luo, Yunyang Luo, Wenbo Ma, Yugang Ma, Yajun Mao, Yue Meng, Nasir Shaheed, Xiaofeng Shang, Xuyang Ning, Ningchun Qi, Zhicheng Qian, Xiangxiang Ren, Changsong Shang, Guofang Shen, Wenliang Sun, Andi Tan, Yi Tao, Anqing Wang, Meng Wang, Qiuhong Wang, Shaobo Wang, Siguang Wang, Wei Wang, Xiuli Wang, Zhou Wang, Yuehuan Wei, Mengmeng Wu, Weihao Wu, Jingkai Xia, Mengjiao Xiao, Xiang Xiao, Pengwei Xie, Binbin Yan, Xiyu Yan, Jijun Yang, Yong Yang, Chunxu Yu, Jumin Yuan, Ying Yuan, Zhe Yuan, Dan Zhang, Minzhen Zhang, Peng Zhang, Shibo Zhang, Shu Zhang, Tao Zhang, Li Zhao, Qibin Zheng, Jifang Zhou, Ning Zhou, Xiaopeng Zhou, and Yong Zhou
Subjects: Science
Abstract: Precise measurement of two-neutrino double beta decay (DBD) half-life is an important step for the searches of Majorana neutrinos with neutrinoless double beta decay. We report the measurement of DBD half-life of 136Xe using the PandaX-4T dual-phase Time Projection Chamber (TPC) with 3.7-tonne natural xenon and the first 94.9-day physics data release. The background model in the fiducial volume is well constrained in situ by events in the outer active region. With a 136Xe exposure of 15.5 kg-year, we establish the half-life as 2.27±0.03stat.±0.10syst.×1021 years. This is the first DBD half-life measurement with natural xenon and demonstrates the physics capability of a large-scale liquid xenon TPC in the field of rare event searches.
Published: 2022
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44. A Case Study on Modeling Adequacy of a Grid with Subsynchronous Oscillations Involving IBRs

Author: Karunaratne, Lilan, Chaudhuri, Nilanjan Ray, Yogarathnam, Amirthagunaraj, and Yue, Meng
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: A case study on modeling adequacy of a grid in presence of renewable resources based on grid-forming converters (GFCs) is the subject matter of this paper. For this purpose, a 4-machine 11-bus IEEE benchmark model is modified by considering GFCs replacing synchronous generators that led to unstable subsynchronous oscillations (SSOs). We aim to: (a) understand if transmission network dynamics should be considered in such cases, (b) revisit the space-phasor-calculus (SPC) in d-q frame under balanced condition that captures such phenomena and lends itself to eigenvalue analysis, and (c) emphasize limitations of such models while underscoring their importance for large-scale power system simulations. Time-domain and frequency-domain results from SPC and quasistationary phasor calculus (QPC) models are compared with electromagnetic transient (EMT)-based simulations. It is shown that models with transmission line dynamics in SPC framework can capture the SSO mode while QPC models that neglect these dynamics fail to do so., Comment: 5 pages, 9 figures. arXiv admin note: substantial text overlap with arXiv:2403.07835
Published: 2024

45. Incidence of and risk factors for surgical site infection after colorectal surgery: A multiple-center prospective study of 3,663 consecutive patients in China

Author: Tie-Ying Hou, Hui-Quan Gan, Jing-Fang Zhou, Ya-Jie Gong, Liu-Yi Li, Xin-Qiang Zhang, Yue Meng, Jie-Rong Chen, Wei-Jiang Liu, Long Ye, Xiao-Xiao Wang, Yun-Hu Zhao, and Yu Zhang
Subjects: Surgical site infection, Colorectal surgery, Risk factor, Prevalence, China, Infectious and parasitic diseases, RC109-216
Abstract: Background: Surgical site infection (SSI) after colorectal surgery (CRS) remains a significant problem for its negative clinical outcomes. However, it is poorly understood in China. This study aims to investigate the incidence, risk factors and microbiology of SSI after CRS. Methods: A nationwide prospective multicenter design was applied. Patients in 19 Chinese hospitals from 2015 to 2018 were prospectively monitored for SSI after CRS. Demographic data, hospital characteristics, and potential perioperative risk factors were collected and analyzed, using univariate and multivariate logistic regression models. Results: Among 3,663 study participants, 134(3.66%) episodes of SSI were identified. The incidence rate of SSI decreased from 5.9 infections per 100 procedures in 2015 to 3.1 infections per 100 procedures in 2018 (incidence rate ratio, 0.52; 95% CI, 0.28–0.94). The SSI rates were 1.88, 4.15, 6.27 and 11.58 per 100 operations for the National Nosocomial Infections Surveillance system (NNIS) risk index categories of 0, 1, and 2 or 3, respectively. Escherichia coli (54/134, 40.3%) and Klebsiella pneumoniae (10/134, 7.5%) were the most frequently isolated microorganisms. A high prevalence of antibiotic resistance were observed in our study, with rates of extended spectrum beta-lactamase-producing or carbapenem-resistant Escherichia coli and Klebsiella pneumonia of 50.0%(27/54) and 30.0%(3/10) respectively. Preoperative hospital stay ≥ 48 h (OR = 2.28, 95% CI: 1.03-5.02, P = 0.042) and contaminated or dirty wound (OR = 3.38, 95% CI: 1.88-6.06, P = 4.50 × 10−5) were significantly associated with increasing risk of SSI after CRS. Conclusion: A statistically significant but modest decrease in the incidence rate of CRS SSI over the 4-year study period was observed in this study. Noticeably, the relatively high rates of multidrug-resistant pathogens causing SSI after CRS should be alert, while more studies with large population are needed due to the small number of isolates identified in our survey.
Published: 2020
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46. A model for spatial spreading and dynamics of fox rabies on a growing domain

Author: Yue Meng, Zhigui Lin, and Michael Pedersen
Subjects: sei model, fox rabies, growing domain, basic reproduction number, stability, Mathematics, QA1-939
Abstract: In order to explore the impact of the growth rate of the habitat on the transmission of rabies, we consider a SEI model for fox rabies on a growing spatial domain. The basic reproduction number is introduced using the next infection operator, spectral analysis and the corresponding eigenvalue problem. The stability of equilibria is also established using the upper and lower solutions method in terms of this number. Our results show that a large growth rate of the domain has a negative impact on the prevention and control of rabies. Numerical simulations are presented to verify our theoretical results.
Published: 2020
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47. Low-Rate DDoS Attack Detection Based on Factorization Machine in Software Defined Network

Author: Wu Zhijun, Xu Qing, Wang Jingjie, Yue Meng, and Liu Liang
Subjects: Low-rate denial of service, factorization machine, software defined network, detection, multi-feature, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: As the Software Define Network (SDN) adopts centralized control logic, it is vulnerable to various types of Distributed Denial of Service (DDoS) attacks. At present, almost all the research work focuses on high-rate DDoS attack against the SDN control layer. Moreover, most of the existing detection methods are effective for high-rate DDoS attack detection of the control layer, while a low-rate DDoS attack against the SDN data layer is highly concealed, and the detection accuracy against this kind of attack is low. In order to improve the detection accuracy of the low-rate DDoS attack against the SDN data layer, this paper studies the mechanism of such attacks, and then proposes a multi-feature DDoS attack detection method based on Factorization Machine (FM). The features extracted from the flow rules are used to detect low-rate DDoS attacks, and the detection of low-rate DDoS attacks based on FM machine learning algorithms is implemented. The experimental results show that the method can effectively detect the low-rate DDoS attack against the SDN data layer, and the detection accuracy reaches 95.80 percent. Because FM algorithm can achieve fine-grained detection for low-rate DDoS attack, which provides a reliable condition for defending against such attacks. Finally, this paper proposes a defense method based on dynamic deletion of flow rules, and carries out experimental simulation and analysis to prove the effectiveness of the defense method, and the success rate of forwarding normal packets reached 97.85 percent.
Published: 2020
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48. Low-Rate DoS Attacks, Detection, Defense, and Challenges: A Survey

Author: Wu Zhijun, Li Wenjing, Liu Liang, and Yue Meng
Subjects: Low-rate Denial of Service attacks (LDoS), detection method, attack prevention system, defense mechanism, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: Low-rate Denial of service (LDoS) attacks has become one of the biggest threats to the Internet, cloud computing platforms, and big data centers. As an evolutionary species of DDoS attack, LDoS attack is essentially different from the DDoS attack. DDoS attacks are the behavior of malicious blocking legitimate network traffic by destroying the targets and the infrastructure around it with huge network traffic. While, LDoS attacks are the behavior of intentional degrading the quality of TCP links by throttling TCP flows to a small fraction of its ideal rate with periodic small pulse sequence. Hence, LDoS attack has a very small flow (around 10%–20% of the background traffic), it is easy to eluding the detection of routers and counter-DoS mechanisms. We try to reveal the mechanism of the LDoS attack and attempt to figure out the generation principle of LDoS attack in this paper. We classify the LDoS attacks and existing defense methods according to time domain and frequency domain in which detection and defense are performed. Furthermore, we highlight the filter approach to defense against LDoS attack. The initial purpose of our work is to encourage researchers to study effective ways to detect and defend against LDoS attacks with innovation and aggressiveness.
Published: 2020
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49. Prevalence of healthcare-associated infections and antimicrobial use in China: Results from the 2018 point prevalence survey in 189 hospitals in Guangdong Province

Author: Yu Zhang, Zhen-Feng Zhong, Shu-Xian Chen, Dian-Rong Zhou, Zheng-Kang Li, Yue Meng, Jing-Fang Zhou, and Tie-Ying Hou
Subjects: Infectious and parasitic diseases, RC109-216
Abstract: Background: Limited data on healthcare-associated infections (HAIs) are available from the developing world, thus a point prevalence survey was conducted to determine the prevalence of HAIs and antimicrobial use in Guangdong Province, China. Methods: A standardized methodology for point prevalence surveys on HAIs and antimicrobial use has been developed by the Chinese Nosocomial Infection Control and Quality Improvement Center. The prevalence of HAIs, antimicrobial use, and baseline hospital-level variables were collected in 189 hospitals from June 2017 to May 2018. Results: Of 5 868 147 patients, 72 976 had one or more HAIs (1.24%), with 82 700 distinct HAIs. The prevalence rates of device-associated infections, including ventilator-associated pneumonia, catheter-associated urinary tract infection, and central line-associated bloodstream infection were 7.92, 2.06, and 0.63 per 1000 catheter-days, respectively. A total of 10 591 (0.18%) HAIs caused by multidrug-resistant organisms were identified. Carbapenem non-susceptibility rates were highest in Acinetobacter species (53.86%) and Pseudomonas aeruginosa (21.60%). Forty-six percent (2 712 258/5 868 147) of inpatients were receiving at least one antimicrobial during this survey. Conclusions: This survey indicated the relatively lower prevalence of HAIs but higher antimicrobial using in Guangdong Province compared with other mid to low-income and high-income countries. Further studies are warranted to elucidate which HAI-related indicators are the best measures of HAI performance and thus allow improvements leading to better patient outcomes. Keywords: Healthcare-associated infection, Point prevalence survey, Antimicrobial use, Multidrug-resistant organism, China
Published: 2019
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50. Target Detection Based on Spectral Derivation in HSI Shadow Region Classified by Convolutional Neural Networks

Author: Xuefeng Liu, Congcong Wang, Yue Meng, Hao Wang, Min Fu, and Salah Bourennane
Subjects: Environmental sciences, GE1-350, Technology
Abstract: Because of the low reflection value of the shadow regions in hyperspectral image (HSI), these regions were deleted directly or ignored in target detection or classification. There are some studies on improving the reflectivity of shadow regions, but it is still difficult to determine the actual substances contained in shadow regions. In this paper, an improved target detection method in shadow regions in HSI is proposed by combining the convolution neural network (CNN) and the adaptive cosine consistency estimation (ACE) of the spectral derivative image. Firstly, the derivative image could be obtained by deriving the original HSI in the spectral dimension. The following steps would be performed simultaneously on the original HSI and the derivative image. Next, the shadow regions in HSI could be determined through two-dimensional (2D) CNN model whose main parameters have been adjusted to optimize the network performance. Finally, the substances contained in the shadow regions would be detected by ACE algorithm. The performance of the proposed method was evaluated and analyzed on the real-world HSIs. The experiments show that the spectral derivation can help to improve the target detection and it is worth taking into account the shadow regions for processing HSI data.
Published: 2019
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