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Reactive chlorine species play a crucial role as precursors to Cl radicals, which can significantly impact the atmospheric oxidation capacity and influence the levels of trace gases related to climate and air quality. However, their anthropogenic sources remain uncertain and require further investigation. In previous studies, we developed the Anthropogenic Chlorine Emission Inventory for China (ACEIC) for the years 2012 and 2014. This inventory focused solely on the emissions of hydrogen chloride (HCl) and chlorine gas (Cl2) from coal combustion and prescribed waste incineration. In the present study, we updated this inventory to include data from a more recent year (2018) and expanded the range of species considered (HCl, fine particulate Cl-, Cl2, and hypochlorous acid (HOCl)) as well as the number of anthropogenic sources (41 specific sources). The emission factors used in this updated inventory were primarily based on localized survey data. The total emissions of HCl, fine particulate Cl-, Cl2, and HOCl in mainland China for the year 2018 were estimated to be 454 (-48 %~45 %), 238 (-59 %~89 %), 17 (-44 %~58 %), and 73 (-44 %~79 %) Gg, respectively. To facilitate analysis, we aggregated the chlorine emissions from various sources into five economic sectors: power, industry, residential, agriculture, and biomass burning. HCl emissions were primarily derived from biomass burning (45 %), industry (35 %), and residential (15 %) sectors. The biomass burning and industry sectors accounted for 78 % and 14 % of the fine particulate Cl- emissions, respectively. Residential and industry sectors contributed 59 % and 31 % of the total Cl2 emissions. HOCl emissions were predominantly from the residential sector, constituting 90 % of the total emissions. Notably, the usage of chlorine-containing disinfectants was identified as the most significant source of Cl2 and HOCl emissions in the residential sector. Geographically, regions with high HCl and fine particulate Cl- emissions were found in northeast China, the North China Plain, and the Sichuan Basin, whereas the Pearl River Delta, Yangtze River Delta, and Beijing-Tianjin-Hebei regions exhibited elevated levels of Cl2 and HOCl emissions. Regarding monthly variation, emissions of HCl and fine particulate Cl- were relatively higher during early summer (June–July) and October due to intensified agricultural activities, while Cl2 and HOCl emissions were higher in the summer months due to increased demand for water disinfection. This updated inventory contributes to a better understanding of anthropogenic sources of reactive chlorine species and can aid in the formulation of emission control strategies to mitigate secondary pollution in China.

Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower at Guangzhou, the core megacity in South China, and interpret the measurements with a one-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10 m, 118 m, 168 m, and 488 m, with the highest 488 m measurement platform higher than the typical height of nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with nighttime (daytime) ozone at the 488 m height being 2.4–5.4 (1.5–2.4) times as that at the 10 m height. This indicates a persistent high ozone level and oxidation capacity aloft the surface. The ozone vertical gradient between the 10 m and 488 m height (∆O3/∆H10–488 m) is 3.6–6.4 ppbv/hm in nighttime and 4.4–5.8 ppbv/hm daytime. We identify a strong ozone residual capacity, defined as the ratio of the ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 67 %–90 % in January, April and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer, by constraining the exchange of RL ozone with ozone inside the nocturnal stable boundary layer that is subject to strong chemical destruction and deposition. The tower-based measurement also indicates that nighttime surface Ox (Ox=O3+NO2) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both nighttime and the following day’s daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe significant decrease in ozone and increase in NO2 and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to NOE event by introducing ozone-rich air in the RL to enter the nighttime stable boundary layer and weakens the titration effect by diluting NOx concentrations. The CMAQ model simulations also demonstrate enhanced positive contribution of vertical diffusion (ΔVDIF) to ozone at the 10 m and 118 m and negative contribution at the 168 m and 488 m during the NOE event. We also observe strong correlation between nighttime RL ozone and the following day’s surface MDA8 ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of convective mixing layer, which is supported by the CMAQ simulated increase in positive ΔVDIF of +50 ppbv·hr−1 at the 10 m and negative ΔVDIF of -10 ppbv·hr−1 at 488 m at early morning (08:00–09:00 LT), suggesting that the mixing of ozone-rich air from nighttime RL downward to surface via the entrainment is an important mechanism to aggravate ozone pollution in the following day. We find that the bias of CMAQ simulated surface MDA8 ozone in the following day shows a strong correlation coefficient (r=0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics.

Partial scan is a common approach to accelerate Magnetic Resonance Imaging (MRI) data acquisition in both 2D and 3D settings. However, accurately reconstructing images from partial scan data (i.e., incomplete k-space matrices) remains challenging due to lack of an effectively global receptive field in both spatial and k-space domains. To address this problem, we propose the following: (1) a novel convolutional operator called Faster Fourier Convolution (FasterFC) to replace the two consecutive convolution operations typically used in convolutional neural networks (e.g., U-Net, ResNet). Based on the spectral convolution theorem in Fourier theory, FasterFC employs alternating kernels of size 1 in 3D case) in different domains to extend the dual-domain receptive field to the global and achieves faster calculation speed than traditional Fast Fourier Convolution (FFC). (2) A 2D accelerated MRI method, FasterFC-End-to-End-VarNet, which uses FasterFC to improve the sensitivity maps and reconstruction quality. (3) A multi-stage 3D accelerated MRI method called FasterFC-based Single-to-group Network (FAS-Net) that utilizes a single-to-group algorithm to guide k-space domain reconstruction, followed by FasterFC-based cascaded convolutional neural networks to expand the effective receptive field in the dual-domain. Experimental results on the fastMRI and Stanford MRI Data datasets demonstrate that FasterFC improves the quality of both 2D and 3D reconstruction. Moreover, FAS-Net, as a 3D high-resolution multi-coil (eight) accelerated MRI method, achieves superior reconstruction performance in both qualitative and quantitative results compared with state-of-the-art 2D and 3D methods.

El cáncer representa un enorme desafío a nivel mundial. 1 de cada 2 hombres y 1 de cada 3 mujeres será diagnosticada de cáncer a lo largo de su vida. Cáncer de mama, pulmón, colorrectal y próstata son los más frecuentes. Se puede constatar una mayor incidencia de cáncer en los hombres que en las mujeres, además la tipología es más diversa entre los hombres, mientras que un tercio de los tumores en las mujeres son diagnosticados como cáncer de mama. Sin embargo, el cáncer de pulmón, cuya incidencia y mortalidad está disminuyendo en hombres, se prevé que pase a ser la primera causa de muerte entre las mujeres en 2025, principalmente por el hábito tabáquico.

In Europe, cancer is the second leading cause of death from disease, behind only cardiovascular diseases. Research progress has been reported in scientific publications whose analysis has included bibliometric studies on the content and authorship of scientific activity with emphasis on gender participation. The aim of this work has been to evaluate the gender gap in Spanish cancer research over the las decade by analyzing the authorships in the derived publications and their correlation with respect to i) the integration of the sex and gender variable in the study carried out, and ii) the type of cancer investigated.

The adverse impacts of extremely large oil spill incidents such as Deepwater Horizon Oil Spill have been widely studied in recent years. Catastrophic oil spill disasters such as Deepwater Horizon Oil Spill have been widely studied. While vast smaller oil spills, which also could result in significant amount of oil release, still lack attention. This research assessed distributions and environmental impacts caused by historical oil spill incidents in U.S. We first analyzed the spatial and temporal characteristics of oil spills. Then the relationship between spillage amount and spill frequency is evaluated via statistical approaches. Last, based on a thorough literature review of environmental, ecological, and economic impacts of oil spill, we proposed a framework to estimate the impact of oil spill incidents.

Yajun Chen, Yiming Liu, Menghao Wang Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Menghao Wang; Yiming Liu, Email 305849@hospital.cqmu.edu.cn; doctorliu@hospital.cqmu.edu.cnBackground: Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor with an extremely poor prognosis. Pyroptosis has been demonstrated to play an important role in tumor prognosis. However, the expression of pyroptosis-related genes in PAAD and their correlations with prognosis remains unclear.Methods: In this study, the 36 pyroptosis-related genes that were differentially expressed between normal pancreatic tissues and PAAD tissues were identified via the “limma” R package. Based on these differentially expressed genes (DEGs), a five-gene signature was established by applying the least absolute shrinkage and selection operator Cox regression in the TCGA cohort and was validated in the GEO cohort. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of DEGs based on the risk model indicated that immune-associated biological processes and pathways were enriched. In vivo, we detected the expressions of CASP4 and CHMP4C by immunohistochemistry in tumor tissues and adjacent normal tissues. In vitro, we silenced CASP4 and CHMP4C to explore their effects on pancreatic cancer cells.Results: PAAD patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group. The expressions of CASP4 and CHMP4C in tumor tissue were higher than those in the adjacent normal tissues in vivo. The knockdown of CASP4 significantly inhibited the invasion and migration but not the proliferation of PANC-1 cells. The knockdown of CHMP4C obviously inhibited the proliferation, migration, and invasion of PANC-1 cells.Conclusion: Pyroptosis-related genes play important roles in predicting the prognosis of PAAD, and CASP4 and CHMP4C affect the metastasis of PAAD.Keywords: pancreatic adenocarcinoma, pyroptosis, signature, prognosis, CASP4, CHMP4C

Tong Zhao, Dongdong Zhang, Yiming Liu, Mingming Feng, Ze Xu, Haoyue Huang, Luoya Zhang, Wenjie Li, Xing Li Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People’s Republic of ChinaCorrespondence: Xing LiDepartment of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People’s Republic of ChinaTel +86 371 6778 1305Email lixing530@zzu.edu.cnBackground: GC (group-specific component globulin) encoding VDBP (Vitamin D binding protein) polymorphisms have been associated with susceptibility to some diseases such as diabetes, obesity, osteoporosis, and polycystic ovary syndrome, but the evidence for metabolic syndrome (MetS) in the Chinese rural population is inconclusive. Therefore, we investigated the relationship between GC variants (rs7041, rs4588, rs2282679, and rs705117) and MetS risk as well as VDBP levels in the Chinese rural population.Patients and Methods: The participants (range of age: 20– 90 years) of this case–control study were recruited from the northern Chinese Han rural population. We matched 445 MetS cases with non-MetS controls in a 1:1 ratio by sex, age (within 5 years). Real-time PCR technology was carried out by TaqMan assays to examine the four variants of rs7041, rs4588, rs2282679, and rs705117 within the GC gene. To identify the association of GC gene polymorphisms with MetS, we calculated ORs using a conditional logistic regression model adjusted for potential confounding factors.Results: We observed inverse associations of CA and AA genotypes of rs4588 with risk of MetS (OR = 0.678, 95% CI 0.505– 0.910, P = 0.010; 0.603, 95% CI 0.373– 0.973, P = 0.039, respectively) compared with carriers of CC genotype. A similar relationship was also found between rs2282679 and MetS, showing that carrying AC genotype of rs2282679 can decrease the risk of MetS (OR = 0.683, 95% CI 0.509– 0.917, P = 0.011) compared with carriers of AA genotype. The results of correlation analysis between MetS components and GC polymorphisms showed that the ORs of AA genotype of rs4588 with high level of TG (triglycerides) and low level of HDL-C (high-density lipoprotein cholesterol) were 0.473 (95% CI 0.245– 0.911, P = 0.025) and 0.268 (95% CI 0.117– 0.615, P = 0.002), respectively; the ORs of CC genotype of rs2282679 with high level of TG and low level of HDL-C were 0.428 (95% CI 0.217– 0.842, P = 0.014) and 0.263 (95% CI 0.110– 0.628, P = 0.003), respectively. However, there was no significant association between the concentration of VDBP and MetS risk.Conclusion: Among the Chinese rural population, GC polymorphism was associated with lower metabolic syndrome susceptibility, which might be through affecting blood lipid levels (TG and HDL-C).Keywords: GC, polymorphism, metabolic syndrome, rural population

Gravitational waves can generate electromagnetic effects inside a strong electric or magnetic field within the Standard Model and general relativity. Here we propose using a quarterly split cavity and LC-resonance circuit to detect a high-frequency gravitational wave from 0.1 MHz to GHz. We perform a full 3D simulation of the cavity's signal for sensitivity estimate. Our sensitivity depends on the coherence time scale of the high-frequency gravitational wave sources and the volume size of the split cavity. We discuss the resonant measurement schemes for narrow-band gravitational wave sources and also a non-resonance scheme for broadband signals. For a meter-sized split cavity under a 14 Tesla magnetic field, the LC resonance enhanced sensitivity to the gravitational wave strain is expected to reach $h\sim 10^{-20}$ around $10$ MHz., Comment: 8 pages, 7 figures

Additional file 1: Supplementary Table 1. The antibacterial effect of rifaximin (E = final log10CFU/gland – initial logl0CFU/gland). Supplementary Table 2. In vitro time bactericidal curve of rifaximin against E. coli ATCC 25922 with 106 CFU/ml initial bacterial load. Supplementary Table 3. In vitro time bactericidal curve of rifaximin against E. coli ATCC 25922 with 107 CFU/ml initial bacterial load. Supplementary Table 4. The concentration of rifaximin in CD-1 mouse mammary glands following intramammary administration doses of 400 ug/gland. (ug/g). Supplementary Table 5. The concentration of rifaximin in CD-1 mouse mammary glands following intramammary administration doses of 200 ug/gland. (ug/g). Supplementary Table 6. The concentration of rifaximin in CD-1 mouse mammary glands following intramammary administration doses of 100 ug/gland. (ug/g). Supplementary Table 7. The concentration of rifaximin in CD-1 mouse mammary glands following intramammary administration doses of 50 ug/gland. (ug/g). Supplementary Table 8. The relationship between PK/PD parameters and bactericidal effect of rifaximin (∆log10CFU/gland).

Additional file 4. Additional information on the methods.

We provide evidence on how responsibility-shifting through delegation occurred in China’s implementation of the one-child policy. We show that trust in local governments was reduced when they were the primary enforcer of the policy (1979–1990), while trust in neighbors was reduced when civilians were incentivized to report neighbors’ violations of the policy to the authorities (1991–2015). This effect was more pronounced among parents of a firstborn daughter, who were more likely to violate the policy due to the deep-rooted son preference. This study provides the first set of field evidence on the responsibility-shifting effect of delegation.

Additional file 3. Additional tables.

Graphite carbon nitride nanosheets (g-C3N4NSs) exhibite excellent electrochemiluminescence (ECL) performance and good film-forming properties. In this paper, g-C3N4NSs were used as an ECL material to be fixed on a glassy carbon electrode(GCE). A molecularly imprinted polymer (MIP) was prepared by molecular self-assembly with chlorpyrifos (CPF) as template molecule and methacrylic acid (MAA) as functional monomer. The polymer was then introduced into g-C3N4NSs modified electrode to construct a MIP-ECL sensor. After removing the template molecule, the sensor can specifically recognize CPF. Based on the specific recognition and quenching effect of CPF on the ECL signal of g-C3N4NSs, the high sensitive and selective detection of CPF was achieved. The sensor shows a linear response to CPF in range of 1.0×10-8-1.0×10-4 mol·L-1 and limit of detection (LOD) of 5.0 nmol·L-1. It was used to detect CPF residues in vegetables and the results were satisfactory.

The project lines out the planned investigation into teachers’ usage and actions within an online learning platform and the relationship between these interactions on their students’ learning outcomes. While studies have already shown strong evidence of the effectiveness of tutoring platforms (such as ASSISTments), it is unclear whether teachers beyond a structured study environment (e.g., with training and coaching on formative assessments) are using these platforms sufficiently well to harness the benefits. The investigation involves a planned analysis of the ASSISTments 2020/2021 dataset loaded on OSF. Analysis plans include the use of multi levelling techniques to investigate teaching practices (most likely the use of assignment and student reports and use of ASSISTment within a synchronized class environment) and their association with outcome factors (likely assignment completion). If the results are conclusive, plans are to use clustering to review profiles of teachers.

In this paper, we use the dimensional reduction technique to study the central limit theory (CLT) random quadratic forms based on sample means and sample covariance matrices. Specifically, we use a matrix denoted by $U_{p\times q}$, to map $q$-dimensional sample vectors to a $p$ dimensional subspace, where $q\geq p$ or $q\gg p$. Under the condition of $p/n\rightarrow 0$ as $(p,n)\rightarrow \infty$, we obtain the CLT of random quadratic forms for the sample means and sample covariance matrices.

The results of our study indicate that, to date, women are clearly at a disadvantage in editorial committees in the area of Information Science and Library Science, at least in the variables that have been analysed. According to the data obtained, women are not only less present in journals indexed in higher quartiles, but are also less present in general, since it is more common for the same male editor to be on several committees than for a woman. In addition, if the journal is also indexed in the SCIE, the presence of women is lower, which is in line with the lower presence of women in the area of STEM in general, a fact that has been highlighted on several occasions.

Intelligent edge network is maturing to enable smart and efficient transportation systems. In this letter, we consider unmanned aerial vehicle (UAV)-assisted vehicular networks where UAVs provide caching and computing services in complement with base station (BS). One major challenge is that vehicles need to obtain timely situational awareness via orchestration of ubiquitous caching and computing resources. Note that cached data for vehicles' perception tasks contains time-varying context information, thus freshness of cached data should be considered in conjunction with task execution to guarantee timeliness of obtained status updates. To this end, we propose a two-stage performance metric to quantify the impact of cache refreshing and computation offloading decisions on the age of status updates. We formulate an energy minimization problem by jointly considering cache refreshing, computation offloading and aging of status updates. To facilitate online decision making, we propose a deep deterministic policy gradient(DDPG)-based solution procedure and incorporate differentiated experience replay mechanism to accelerate convergence. Simulation results show that the performance of proposed solution is competitive in terms of energy consumption for obtaining fresh status updates.

This paper investigated the joint influence of particle crushing and intermediate principal stress coefficient on the macro and micro performances of granular assembles by using 3D discrete element method. The soil particle was modeled by crushable agglomerate. Numerical true triaxial tests with crushable agglomerates were performed. The mechanical behaviors of specimens with unbreakable agglomerates were also tested in this study. The results demonstrated that grain breakage can significantly affect the behaviors of granular soils in both macro and micro scales. Moreover, the present paper also showed that particle breakage did not influence the unique relationship between the intermediate principal stress coefficient b and the deviatoric fabric of strong contacts. This can provide a good basis for developing micro-parameter-based constitutive model considering particle breakage for granular soils.

The kang-stove system (KSS) is a combination cooking and heating system and is the core element of the living space of many rural houses in northern China. The traditional KSS is usually single kan...

Purpose: Long scan time in phase encoding for forming complete K-space matrices is a critical drawback of MRI, making patients uncomfortable and wasting important time for diagnosing emergent diseases. This paper aims to reducing the scan time by actively and sequentially selecting partial phases in a short time so that a slice can be accurately reconstructed from the resultant slice-specific incomplete K-space matrix. Methods: A transformer based deep reinforcement learning framework is proposed for actively determining a sequence of partial phases according to reconstruction-quality based Q-value (a function of reward), where the reward is the improvement degree of reconstructed image quality. The Q-value is efficiently predicted from binary phase-indicator vectors, incomplete K-space matrices and their corresponding undersampled images with a light-weight transformer so that the sequential information of phases and global relationship in images can be used. The inverse Fourier transform is employed for efficiently computing the undersampled images and hence gaining the rewards of selecting phases. Results: Experimental results on the fastMRI dataset with original K-space data accessible demonstrate the efficiency and accuracy superiorities of proposed method. Compared with the state-of-the-art reinforcement learning based method proposed by Pineda et al., the proposed method is roughly 150 times faster and achieves significant improvement in reconstruction accuracy. Conclusions: We have proposed a light-weight transformer based deep reinforcement learning framework for generating high-quality slice-specific trajectory consisting of a small number of phases. The proposed method, called TITLE (Transformer Involved Trajectory LEarning), has remarkable superiority in phase-encode selection efficiency and image reconstruction accuracy., 12 pages, 7 figures

The study considers a complex technique for developing nanostructured carbon coatings, which consists in the deposition of a sublayer based on polymer and metal formates, subsequent heat treatment, and further deposition of carbon layers from the plasma of a pulsed cathode-arc discharge.

Intuitive and efficient physical human-robot collaboration relies on the mutual observability of the human and the robot, i.e. the two entities being able to interpret each other's intentions and actions. This is remedied by a myriad of methods involving human sensing or intention decoding, as well as human-robot turn-taking and sequential task planning. However, the physical interaction establishes a rich channel of communication through forces, torques and haptics in general, which is often overlooked in industrial implementations of human-robot interaction. In this work, we investigate the role of haptics in human collaborative physical tasks, to identify how to integrate physical communication in human-robot teams. We present a task to balance a ball at a target position on a board either bimanually by one participant, or dyadically by two participants, with and without haptic information. The task requires that the two sides coordinate with each other, in real-time, to balance the ball at the target. We found that with training the completion time and number of velocity peaks of the ball decreased, and that participants gradually became consistent in their braking strategy. Moreover we found that the presence of haptic information improved the performance (decreased completion time) and led to an increase in overall cooperative movements. Overall, our results show that humans can better coordinate with one another when haptic feedback is available. These results also highlight the likely importance of haptic communication in human-robot physical interaction, both as a tool to infer human intentions and to make the robot behaviour interpretable to humans.

Magnetic resonance imaging plays an essential role in clinical diagnosis by acquiring the structural information of biological tissue. Recently, many multi-contrast MRI super-resolution networks achieve good effects. However, most studies ignore the impact of the inappropriate foreground scale and patch size of multi-contrast MRI, which probably leads to inappropriate feature alignment. To tackle this problem, we propose the Flexible Alignment Super-Resolution Network (FASR-Net) for multi-contrast MRI Super-Resolution. The Flexible Alignment module of FASR-Net consists of two modules for feature alignment. (1) The Single-Multi Pyramid Alignment(S-A) module solves the situation where low-resolution (LR) images and reference (Ref) images have different scales. (2) The Multi-Multi Pyramid Alignment(M-A) module solves the situation where LR and Ref images have the same scale. Besides, we propose the Cross-Hierarchical Progressive Fusion (CHPF) module aiming at fusing the features effectively, further improving the image quality. Compared with other state-of-the-art methods, FASR-net achieves the most competitive results on FastMRI and IXI datasets. Our code will be available at \href{https://github.com/yimingliu123/FASR-Net}{https://github.com/yimingliu123/FASR-Net}.

Additional file 1: Table S1. Comparation of clinical core features between probable DLB and PDD. Table S2. Correlation between APOE ε4 allele, basic and clinical characteristics in probable DLB and PDD. Table S3. Associations between APOE ε4 allele and clinical core features in DLB and PDD.

The conversational recommender systems (CRSs) have received extensive attention in recent years. However, most of the existing works focus on various deep learning models, which are largely limited by the requirement of large-scale human-annotated datasets. Such methods are not able to deal with the cold-start scenarios in industrial products. To alleviate the problem, we propose FORCE, a Framework Of Rule-based Conversational Recommender system that helps developers to quickly build CRS bots by simple configuration. We conduct experiments on two datasets in different languages and domains to verify its effectiveness and usability., Comment: AAAI 2022 (Demonstration Track)

Additional file 1: eAppendix 1. Information of participating clinics. eAppendix 2. Details of APOE genotyping. eAppendix 3. MRI parameters and review. Table S1. Sex-specific characteristics of the four groups

In the Standard Model Effective Field Theory (SMEFT), operators involving the top quark are generally difficult to probe, and can generate sizable loop contributions to the electroweak precision observables, measured by past and future lepton colliders. Could the high precision of the electroweak measurements compensate the loop suppression and provide competitive reaches on these operators? Would the inclusion of these contributions introduce too many additional parameters for a meaningful global electroweak analysis to be done? In this paper, we perform a detailed phenomenological study to address these two important questions. Focusing on eight dimension-6 operators that generate anomalous couplings between the electroweak gauge bosons and the third-generation quarks, we calculate their one loop contributions to the $e^+e^- \to f\bar{f}$ processes both on and off the Z-pole and the $e^-e^+ \to WW$ process. A global analysis is performed with these eight operators and the ones that contribute to the above processes at tree level, using the measurements at LEP, SLC and several low energy experiments. We find that, while the current electroweak precision measurements are sensitive to the one-loop effects of the top-quark operators, it is difficult to separate them from the operators that contribute at the tree level, making a global analysis rather challenging. Under more assumptions, competitive reaches could be obtained in a global fit. Another important finding of our study is that the two operators that generate dipole interactions of the bottom quark have significant impacts in the Z-pole measurements and should not be omitted. We also discuss the implication of the recently reported W-boson mass measurement at CDF to our results. Finally, we estimate the reaches of future lepton colliders in probing the top-quark operators with precision electroweak measurements., 38 pages, 14 figures

Around the problem of workpiece machining accuracy, a model of autonomous behavior of equipment and the method of establishing patterns in knowledge base have been developed in this paper. Two self-learning models based on pattern comparison: deterministic knowledge and uncertain knowledge self-learning model are presented, while a scene understanding method for intelligent autonomous behavior of equipment is proposed. The research scheme of intelligent autonomous behavior optimization of equipment based on scene understanding and the specific research framework of workpiece machining precision are produced. Finally, focusing on the actual production process of bearing end cover, the flexible automatic production line of bearing end cover is established, the workpiece machining accuracy research based on independent behavior of equipment for CMM and CNC machine tools is preliminarily realized with the help of automatic line control end, it lays a solid foundation for the overall autonomous and intelligent cooperation between the testing area and the processing area.

It is speculated that the changes in seawater temperature may cause population migration of the North Sea Mackerel and Herring fisheries. To assess the situation and propose some remedies which can help improving the economy, the paper establish a series of models. The paper set a revenue-cost model to figure out the maximum sailing distance and area by willingness of fishermen to define how migration of mackerel and herring influence the net profit of companies. The longer distance brings the larger total cost, the smaller total revenue, and the smaller net profit. The paper establish the total cost-time model which divide to fixed assets, wage, and fuel fare and the total revenue-time model which is influenced by freshness, to define the maximum sailing distance. Combining with the prediction of fisheries, it is clearly that fisheries will migrate out of the willingness area completely 78 years later. To avoid the awful condition of fishing, suggest fishermen take some strategies to reduce the loss of fish migration. According to the Barycenter method, consider Anstruther, Eyemouth and Buckie as the best three city for fisheries by using the administrative division of Scotland and the prediction of fisheries. Or fishermen can buy a certain percent advanced equipment according to the maximum net profit model.

These files are created for Penget al. (2021) -- 'Formation of East Asian stagnant slabs due to a pressure-driven Cenozoic mantle wind following Mesozoic subduction'. The dataof thepresent-day temperature, dynamic pressure and velocity along 32ºN and 43ºN in model 1at thepresent-day are provided (global.32050.32.xxxx.xyz and global.32050.43.xxxx.xyz). The python scriptplot_temp_pres.pycan be used to plot (using GMT4) a figure with two panels, with the upper one being temperature and velocity, and the lower one being dynamic pressure and velocity. The present-day temperature at 500 km, velocities at 500, 300 km and the surface in model 1are also provided (global.32050.xxxx.zxxx, in which the postfix z083is at 500 km deep, z094 is 300 km, z113 is the surface). The python scriptmap_plot_EastAsia.pyplots (using GMT4) a map of temperature with velocities on it.

We present a novel spectral machine learning (SML) method in screening for pancreatic mass using CT imaging. Our algorithm is trained with approximately 30,000 images from 250 patients (50 patients with normal pancreas and 200 patients with abnormal pancreas findings) based on public data sources. A test accuracy of 94.6 percents was achieved in the out-of-sample diagnosis classification based on a total of approximately 15,000 images from 113 patients, whereby 26 out of 32 patients with normal pancreas and all 81 patients with abnormal pancreas findings were correctly diagnosed. SML is able to automatically choose fundamental images (on average 5 or 9 images for each patient) in the diagnosis classification and achieve the above mentioned accuracy. The computational time is 75 seconds for diagnosing 113 patients in a laptop with standard CPU running environment. Factors that influenced high performance of a well-designed integration of spectral learning and machine learning included: 1) use of eigenvectors corresponding to several of the largest eigenvalues of sample covariance matrix (spike eigenvectors) to choose input attributes in classification training, taking into account only the fundamental information of the raw images with less noise; 2) removal of irrelevant pixels based on mean-level spectral test to lower the challenges of memory capacity and enhance computational efficiency while maintaining superior classification accuracy; 3) adoption of state-of-the-art machine learning classification, gradient boosting and random forest. Our methodology showcases practical utility and improved accuracy of image diagnosis in pancreatic mass screening in the era of AI., 17 pages, 3 figures

Recycled concrete aggregate (RCA) is a typical construction and demolition (C&amp, D) material generated in civil engineering activities and has been widely used as the coarse-grained filler added to sand for roadbed fillings. The effect of RCA content on the mechanical behavior of sand–RCA mixtures is complicated and still not fully understood. To explore the effect of RCA content on the macroscale and microscopic behavior of the sand–RCA mixtures with various RCA contents, laboratory direct shear tests and numerical simulations using the 3D discrete element method were performed. Experimental direct shear tests on sand–RCA mixtures with different contents of RCA were first carried out. Numerical direct shear models were then established to represent the experimental results. The particle shape effect was also considered using a new realistic shape modeling method to model the RCA particles. Good agreement was observed between the DEM simulation and experimental results, verifying the ability of the numerical direct shear models to represent the direct shear behavior of sand–RCA mixtures. The macroscopic responses of both experimental and numerical tests showed that all samples presented an initial hardening followed by a post-peak strain softening. The peak-state friction angles increased with the RCA content for samples under the same vertical stress. The effect of RCA content on the microscopic behavior based on DEM simulation was also found. The microscopic properties of RCA–sand mixtures, such as coordination numbers, PDFs and contact force transformation features, were analyzed and related to the macroscopic results.

The aim of this study was to investigate the effect of minocycline in rats with rotenone-induced Parkinson’s disease (PD). The open field test was performed to determine the motor ability of the rats. Double immunofluorescence staining was used to detect the expression of tyrosine hydroxylase (TH) and Nurr1 in the substantia nigra (SN) of rats. The relative protein levels of TH, Nurr1, and the total- and phosphorylated-cAMP-response element binding protein (CREB) were determined by western blot analysis. The production of reactive oxygen species (ROS) and nitric oxide (NO) was detected by commercial kits. After exposure to rotenone for 28 days, rats exhibited decreased ambulation and rearing frequency and prolonged immobility time with loss of TH positive neurons in the SN. The phosphorylation levels of CREB and Nurr1 expression decreased significantly accompanied with the release of ROS and NO. Minocycline alleviated the motor deficits of rats lesioned by rotenone and elevated the expression of TH, as well as suppressing the release of ROS and NO in the SN. That was in line with the elevated phosphorylation levels of CREB and Nurr1 expression. In conclusion, our present study showed minocycline protected against neurotoxicity in a rotenone-induced rat model of PD, which was correlated with upregulation of Nurr1.

Engineered Cementitious Composites (ECC) is a family of high-performance fiber-reinforced cementitious composites with high tensile ductility and emerging in steel-concrete composite structures. In the composite structures, shear force transfer through shear connectors plays a critical role to integrate the steel and concrete. This study experimentally investigates the static and fatigue behaviors of short studs embedded in ECC through push-out tests of nine specimens. The test results of the shear strength, slip capacity, and fatigue resistance are compared with current design codes. The shear strength agrees well with that obtained from AASHTO LRFD, while the Eurocode 4 and Chinese code underestimate the shear strength. The slip capacity satisfies the ductility requirement in Eurocode 4. Based on the fatigue tests results, an S-N curve related to a survival probability of 95% is proposed. Empirical formulas are derived as a tool to help predict the load-slip behavior of the specimen under fatigue loading.

Charge-coupled device (CCD) vertical blooming is inevitable in silicon-based cameras when near-infrared lasers are measured. In this study, we analyze the mechanism responsible for the influence of CCD vertical blooming on the beam quality factor (M2) measurement with a quadriwave lateral shearing interferometer (QWLSI). Based on a CCD vertical blooming model, we reconstruct the bloomed interferogram, which is used to retrieve the intensity and phase distributions of the laser. Then, the relationship between the M2 and degree of CCD vertical blooming is revealed. In addition, the M2 of single- and multi-mode lasers is measured with the QWLSI under different degrees of vertical blooming streaks. The results from the experiment are reasonably consistent with the simulation results. Meanwhile, the method of improving the exposure time of CCD camera for suppressing the blooming is also analyzed, indicating that the method can effectively suppress the influence of the blooming on the M2 measurement in a QWLSI.

In this study, the mechanical performances of assembled hub (AH) joints under axial loads are investigated. Firstly, analytical solutions for the load-deformation characteristics of the AH joint system are proposed based on the rigid foundation-beam assumption. Axial tension and compression tests as well as finite element analysis are conducted to reveal the failure modes of AH joints with different design parameters. Moreover, a design method for AH joints is proposed to guide engineering applications. The type I AH joints exhibited three failure modes during the tension test: hub punching failure, hub fracture, and excessive deformation of the closure plate. Comparatively, the failure of joints was mainly caused by excessive hub deformation during the compression test. The initial stiffness and plastic capacity of the AH joints under two loading cases were identical. However, after entering the plastic phase, the tensile stiffness of the joints increased steadily, while the compressional stiffness declined with the plastic deformation. The type II AH joints exhibited brittle failure during the test. The initial stiffness and axial capacities obtained from the theoretical analysis agree strongly with the experimental results. The proposed theoretical formulae are useful for preliminary estimation of the mechanical performances of a new joint system.

With increasing traffic volumes, fatigue of orthotropic steel decks (OSDs) has become a critical issue in recent years. In this study, an innovative composite deck composed of large-size U-ribs, a thin ultra-high-performance concrete (UHPC) layer and headed studs is proposed to enhance the fatigue properties of OSDs. Experimental and numerical approaches were combined to investigate the transverse fatigue behaviour of the proposed composite deck. A large-scale composite deck specimen was fabricated and tested under cyclic loading. The experimental results revealed the progressive failure process of the composite deck. The effects of damage accumulation in UHPC layer and headed studs on the mechanical behaviour of steel-UHPC composite deck were evaluated. The results indicated that the mechanical degradation in the composite deck system accelerated the damage accumulation in the fatigue-prone details of OSDs. It is necessary to consider the effects of mechanical degradation in fatigue resistance evaluation.

The recommendation system [1] can quickly find the information that users are interested in from the complex information and recommend it to the user, and it has been widely used in web-based services. However, the current mainstream recommendation models all have data sparseness [2] and imbalance problems. To address these problems, we propose a deep separation graph neural network recommendation model (DSGNR) based on the idea of graph information aggregation. In the experiment, we used the classic recommendation system data set to verify and analyze the proposed DSGNR model and compared it with the seven mainstream recommendation models. Experimental results show that the proposed algorithm is generally better than the current mainstream recommendation methods in terms of accuracy and efficiency.

Atmospheric ammonia (NH3) can affect nitrogen deposition, particle acidity, and gas-particle partitioning. Although the inorganic chemistry of NH3 in fine particulate (PM2.5) formation are well-constrained, the understanding of interactions between NH3 and secondary organic aerosol (SOA) are rather insufficient until recently. Laboratory studies indicate that NH3 molecule can react with SOA then forms nitrogen-containing organic compounds (NOCs), which can further react to form heterocyclic organic compounds. In this study, we use a modified version of the CMAQ model to simulate the potential importance of the SOA-ammonia uptake mechanism on air quality over China in summer and winter 2017, considering a range of assumed NH3 uptake coefficients (10−3–10−5). Our results show that uptake of NH3 by SOA leads to a decrease in gas-phase NH3 mixing ratio, by as much as 27.5% and 19.0% for the highest uptake coefficient scenario (10−3) in summer and winter, respectively. The largest reduction of ammonia occurs over the Sichuan Basin and the North China Plain. The reduction of gas-phase NH3 engenders a decrease of ammonium nitrate, by up to 30%, but has little impact on the ammonium sulfate concentration. Uptake of NH3 does not significantly affect SOA concentrations owing to overall moderate changes in aerosol acidity, and thus small effects on SOA formation from isoprene. Altogether, NH3 uptake led to a reduction in the average PM2.5 concentration up to 8.9% and 8.7% for the highest uptake coefficient (10−3) in summer and winter, respectively. These results highlight the need for better constraints on the NH3-SOA interactions.

The worldwide spread of Covid-19 pandemic caused a dramatic cutback of human activities and triggered a large-scale atmospheric composition experiment. This unfortunate situation provides the opportunity to investigate the response of atmospheric composition to the shutdown measures. Our focus will be on China, where the pandemic emerged in January 2020, and thence strict lockdowns were enforced. Substantial, large-scale decreases in pollutants levels over China and subsequent recovery were revealed by spaceborne observations from TROPOMI instrument on board Sentinel-5 Precursor, as well as by in situ measurements. Most published work on this topic relied on observed changes in column abundances of nitrogen dioxide (NO2), a predominantly anthropogenic compound and an important precursor for ozone production and secondary aerosol formation. Our work adds to this picture by studing the evolution of two other satellite-derived compounds, formaldehyde (HCHO) and peroxyacylnitrate (PAN), observed by TROPOMI and IASI, respectively. HCHO is an intermediate product in the chemical processing of volatile organic compounds (VOCs) of anthropogenic and natural origin. PAN is formed in the oxidation of anthropogenic and biogenic VOCs, and constitute the principal tropospheric NOx reservoir, enabling the transport and release of NOx away from the sources. Chemistry-transport simulations of PAN are challenging due to large uncertainties in formation mechanisms and precursor emissions. We will evaluate and analyze the observed variability of NO2, HCHO, and PAN columns using model simulations with the MAGRITTE v1.1 regional CTM run at 0.5ox0.5o resolution over China for 2019 and 2020. The model uses updated anthropogenic emissions from the CONFORM dataset, which takes into account the reductions during the shutdowns based on traffic and other economic activity data.

Litter decomposition is a fundamental path for nutrient cycling in a natural ecosystem. However, it remains unclear how species diversity, including richness and evenness, affects the decomposition dynamics in the context of grassland degradation. Using a litter bag technique, we investigated the litter-mixing effects of two coexisting dominant species (Leymus chinensis Lc and Phragmites australis Pa), as monocultures and mixtures with evenness (Lc:Pa) from M1 (30:70%), M2 (50:50%), and M3 (70:30%), on decomposition processes over time (60 and 365 days). The litter bags were placed on the soil surface along a degradation gradient [near pristine (NP), lightly degraded (LD), and highly degraded (HD)]. We found that 1) mass loss in mixture compositions was significantly and positively correlated with initial nitrogen (N) and cellulose contents; 2) litter mixing (richness and evenness) influenced decomposition dynamics individually and in interaction with the incubation days and the degradation gradients; 3) in a general linear model (GLM), nonadditive antagonistic effects were more prominent than additive or neutral effects in final litter and nutrients except for carbon (C); and 4) in nutrients (C, N, lignin) and C/N ratio, additive effects shifted to nonadditive with incubation time. We speculated that the occurrence of nonadditive positive or negative effects varied with litter and nutrients mass remaining in each degraded gradient under the mechanism of initial litter quality of monoculture species, soil properties of experimental sites, and incubation time. Our study has important implications for grassland improvement and protection by considering species biodiversity richness, as well as species evenness.

In this letter, we study the outage probability of intelligent reflecting surface (IRS) assisted full duplex two-way communication systems, which characterizes the performance of overcoming the transmitted data loss caused by long deep fades. To this end, we first derive the probability distribution of the cascaded end-to-end equivalent channel with an arbitrarily given IRS beamformer. Our analysis shows that deriving such probability distribution in the considered case is more challenging than the case with the phase-matched IRS beamformer. Then, with the derived probability distribution of the equivalent channel, we obtain the closed-form expression of the outage probability performance. It theoretically shows that the reflecting element number has a conspicuous effect on the improvement of the system reliability. Extensive numerical results verify the correctness of the derived results and confirm the superiority of the considered IRS assisted two-way communication system comparing to the one-way counterpart.

Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image. Recent progress on image deblurring always designs end-to-end architectures and aims at learning the difference between blurry and sharp image pairs from pixel-level, which inevitably overlooks the importance of blur kernels. This paper reveals an intriguing phenomenon that simply applying ReLU operation on the frequency domain of a blur image followed by inverse Fourier transform, i.e., frequency selection, provides faithful information about the blur pattern (e.g., the blur direction and blur level, implicitly shows the kernel pattern). Based on this observation, we attempt to leverage kernel-level information for image deblurring networks by inserting Fourier transform, ReLU operation, and inverse Fourier transform to the standard ResBlock. 1x1 convolution is further added to let the network modulate flexible thresholds for frequency selection. We term our newly built block as Res FFT-ReLU Block, which takes advantages of both kernel-level and pixel-level features via learning frequency-spatial dual-domain representations. Extensive experiments are conducted to acquire a thorough analysis on the insights of the method. Moreover, after plugging the proposed block into NAFNet, we can achieve 33.85 dB in PSNR on GoPro dataset. Our method noticeably improves backbone architectures without introducing many parameters, while maintaining low computational complexity. Code is available at https://github.com/DeepMed-Lab/DeepRFT-AAAI2023., Comment: AAAI 2023

A temperature error compensation scheme for fiber optic gyroscope (FOG) based on radial basis function (RBF) neural network is proposed in this paper. By using the data preprocessing and orthogonal least square (OLS) learning method, the training performance of the network is improved and the over-fitting of the network is prevented. The experimental results illustrate that the proposed method has a 15–40% performance improvement compared with the conventional linear regression model.