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Abstract Cell surface proteins are responsible for many crucial physiological roles, and they are also the major category of drug targets as the majority of therapeutics target membrane proteins on the surface of cells to alter cellular signaling. Despite its great significance, ligand discovery against membrane proteins has posed a great challenge mainly due to the special property of their natural habitat. Here, we design a new chemical proteomic probe OPA-S-S-alkyne that can efficiently and selectively target the lysines exposed on the cell surface and develop a chemical proteomics strategy for global analysis of surface functionality (GASF) in living cells. In total, we quantified 2639 cell surface lysines in Hela cell and several hundred residues with high reactivity were discovered, which represents the largest dataset of surface functional lysine sites to date. We discovered and validated that hyper-reactive lysine residues K382 on tyrosine kinase-like orphan receptor 2 (ROR2) and K285 on Endoglin (ENG/CD105) are at the protein interaction interface in co-crystal structures of protein complexes, emphasizing the broad potential functional consequences of cell surface lysines and GASF strategy is highly desirable for discovering new active and ligandable sites that can be functionally interrogated for drug discovery.

Perilla oil from the medicinal crop Perilla frutescens possess a wide range of biological activities and is generally used as an edible oil in many countries. The molecular basis for its formation is of particular relevance to perilla and its breeders. Here in the present study, four PfFAD2 genes were identified in different perilla cultivars, PF40 and PF70, with distinct oil content levels, respectively. Their function was characterized in engineered yeast strain, and among them, PfFAD2-1PF40, PfFAD2-1PF70 had no LA biosynthesis ability, while PfFAD2-2PF40 in cultivar with high oil content levels possessed higher catalytic activity than PfFAD2-2PF70. Key amino acid residues responsible for the enhanced catalytic activity of PfFAD2-2PF40 was identified as residue R221 through sequence alignment, molecular docking, and site-directed mutation studies. Moreover, another four amino acid residues influencing PfFAD2 catalytic activity were discovered through random mutation analysis. This study lays a theoretical foundation for the genetic improvement of high-oil-content perilla cultivars and the biosynthesis of LA and its derivatives.

Evidence shows that tropomodulin 1 (TMOD1) is a powerful diagnostic marker in the progression of several cancer types. However, the regulatory mechanism of TMOD1 in tumor progression is still unclear. Here, we showed that TMOD1 was highly expressed in acute myeloid leukemia (AML) specimens, and TMOD1-silencing inhibited cell proliferation by inducing autophagy in AML THP-1 and MOLM-13 cells. Mechanistically, the C-terminal region of TMOD1 directly bound to KPNA2, and TMOD1-overexpression promoted KPNA2 ubiquitylation and reduced KPNA2 levels. In contrast, TMOD1-silencing increased KPNA2 levels and facilitated the nuclear transfer of KPNA2, then subsequently induced autophagy and inhibited cell proliferation by increasing the nucleocytoplasmic transport of p53 and AMPK activation. KPNA2/p53 inhibitors attenuated autophagy induced by silencing TMOD1 in AML cells. Silencing TMOD1 also inhibited tumor growth by elevating KPNA2-mediated autophagy in nude mice bearing MOLM-13 xenografts. Collectively, our data demonstrated that TMOD1 could be a novel therapeutic target for AML treatment.

Background: Chronic atrophic gastritis (CAG) is a global digestive system disease and one of the important causes of gastric cancer. The incidence of CAG has been increasing yearly worldwide. Purpose: This article reviews the latest research on the common causes and future therapeutic targets of CAG as well as the pharmacological effects of corresponding clinical drugs. We provide a detailed theoretical basis for further research on possible methods for the treatment of CAG and reversal of the CAG process. Results: CAG often develops from chronic gastritis, and its main pathological manifestation is atrophy of the gastric mucosa, which can develop into gastric cancer. The drug treatment of CAG can be divided into agents that regulate gastric acid secretion, eradicate Helicobacter. pylori (H. pylori), protect gastric mucous membrane, or inhibit inflammatory factors according to their mechanism of action. Although there are limited specific drugs for the treatment of CAG, progress is being made in defining the pathogenesis and therapeutic targets of the disease. Growing evidence shows that NF-κB, PI3K/AKT, Wnt/ β-catenin, MAPK, Toll-like receptors (TLRs), Hedgehog, and VEGF signaling pathways play an important role in the development of CAG.

While diagnosing multiple lesion regions in chest X-ray (CXR) images, radiologists usually apply pathological relationships in medicine before making decisions. Therefore, a comprehensive analysis of labeling relationships in different data modes is essential to improve the recognition performance of the model. However, most automated CXR diagnostic methods that consider pathological relationships treat different data modalities as independent learning objects, ignoring the alignment of pathological relationships among different data modalities. In addition, some methods that use undirected graphs to model pathological relationships ignore the directed information, making it difficult to model all pathological relationships accurately. In this paper, we propose a novel multi-label CXR classification model called MRChexNet that consists of three modules: a representation learning module (RLM), a multi-modal bridge module (MBM) and a pathology graph learning module (PGL). RLM captures specific pathological features at the image level. MBM performs cross-modal alignment of pathology relationships in different data modalities. PGL models directed relationships between disease occurrences as directed graphs. Finally, the designed graph learning block in PGL performs the integrated learning of pathology relationships in different data modalities. We evaluated MRChexNet on two large-scale CXR datasets (ChestX-Ray14 and CheXpert) and achieved state-of-the-art performance. The mean area under the curve (AUC) scores for the 14 pathologies were 0.8503 (ChestX-Ray14) and 0.8649 (CheXpert). MRChexNet effectively aligns pathology relationships in different modalities and learns more detailed correlations between pathologies. It demonstrates high accuracy and generalization compared to competing approaches. MRChexNet can contribute to thoracic disease recognition in CXR.

Abstract Lymph node (LN) metastasis is one of the key prognostic factors in bladder cancer, but its underlying mechanisms remain unclear. Here, we found that elevated expression of WD repeat domain 4 (WDR4) in bladder cancer correlated with worse prognosis. WDR4 can promote the LN metastasis and proliferation of bladder cancer cells. Mechanistic studies showed that WDR4 can promote the nuclear localization of DEAD-box helicase 20 (DDX20) and act as an adaptor to bind DDX20 and Early growth response 1 (Egr1), thereby inhibiting Egr1-promoted transcriptional expression of arrestin beta 2 (ARRB2) and ultimately contributing to the progression of bladder cancer. Immunohistochemical analysis confirmed that WDR4 expression is also an independent predictor of LN metastasis in bladder cancer. Our results reveal a novel mechanism of LN metastasis and progression in bladder cancer and identify WDR4 as a potential therapeutic target for metastatic bladder cancer.

Auxin Response Factors (ARFs) make up a plant-specific transcription factor family that mainly couples perception of the phytohormone, auxin, and gene expression programs and plays an important and multi-faceted role during plant growth and development. Lemongrass (Cymbopogon flexuosus) is a representative Cymbopogon species widely used in gardening, beverages, fragrances, traditional medicine, and heavy metal phytoremediation. Biomass yield is an important trait for several agro-economic purposes of lemongrass, such as landscaping, essential oil production, and phytoremediation. Therefore, we performed gene mining of CfARFs and identified 26 and 27 CfARF-encoding genes in each of the haplotype genomes of lemongrass, respectively. Phylogenetic and domain architecture analyses showed that CfARFs can be divided into four groups, among which groups 1, 2, and 3 correspond to activator, repressor, and ETTN-like ARFs, respectively. To identify the CfARFs that may play major roles during the growth of lemongrass plants, RNA-seq was performed on three tissues (leaf, stem, and root) and four developmental stages (3-leaf, 4-leaf, 5-leaf. and mature stages). The expression profiling of CfARFs identified several highly expressed activator and repressor CfARFs and three CfARFs (CfARF3, 18, and 35) with gradually increased levels during leaf growth. Haplotype-resolved transcriptome analysis revealed that biallelic expression dominance is frequent among CfARFs and contributes to their gene expression patterns. In addition, co-expression network analysis identified the modules enriched with CfARFs. By establishing orthologous relationships among CfARFs, sorghum ARFs, and maize ARFs, we showed that CfARFs were mainly expanded by whole-genome duplications, and that the duplicated CfARFs might have been divergent due to differential expression and variations in domains and motifs. Our work provides a detailed catalog of CfARFs in lemongrass, representing a first step toward characterizing CfARF functions, and may be useful in molecular breeding to enhance lemongrass plant growth.

Home-based movement neuro-rehabilitation is quite necessary when the patient goes back home from hospital. Due to lack of supervision from doctors, rehabilitation at home is often forgotten. As an alternate to doctor-supervision, in this research, we explore the wireless device-free localization technique to assist the rehabilitation procedure. The localization technique can judge whether the patient is near the rehabilitation equipment and even obtain the movement trajectory. The most challenging problem in the wireless device-free localization system is that the received-signal-strength (RSS) of the electromagnetic-wave is unpredictable, which increases the localization error. How to select the informative RSS is pretty important. This research proposes a new criterion (i.e., fluctuation-level) to select the informative RSS. Experimental results show the effectiveness of the proposed fluctuation-level in reducing the localization error.

This study was conducted in response to the Beijing–Tianjin–Hebei mega heavy rainfall event at the end of July 2023, and the severely affected and representative Jiangou village in Beijing was selected as the study area. A variety of methods were used to synthesize and analyze the situation and propose an adaptive response to heavy rainfall and flooding in the village. Based on multi-source remote sensing (RS) data, a comprehensive topographic and hydrological characterization was carried out, and the precipitation before and after the disaster was analyzed; the flood inundation area was extracted using the improved normalized water body index (MNDWI) and OTSU thresholding methods, and the changes of water bodies during the flooding period were quantitatively analyzed; and an improved convolutional-neural-network-based building identification and extraction model was constructed to extract the research distribution of buildings in the area. The sponge city construction (SPCC) method was improved to obtain a method that can mitigate flood risk and adapt to villages by constructing small artificial lakes and local topographic buffers to improve the water storage and drainage capacity of villages. The study shows that these methods are innovative in flood hazard analysis and mitigation but still need further improvement in data accuracy, simulation depth, and system evaluation.

Abstract Background Hepatocellular carcinoma (HCC) is a highly malignant type of tumor that is insensitive to cytotoxic chemotherapy and often develops drug resistance. Nevadensin, a bioflavonoid, exhibits anti-cancer properties in some cancers. However, the precise underlying mechanism of nevadensin against liver cancer are poorly understood. We aim to evaluate the efficacy as well as the molecular mechanism of nevadensin in the treatment of liver cancer. Methods Effects of nevadensin on HCC cell proliferation and apoptosis were detected using EdU labeling and flow cytometry assays. The molecular mechanism of nevadensin on HCC was determined using RNAseq. The effects of nevadensin on hippo-Yap signaling were verified using western blot and RT-PCR. Results In this study, we show that nevadensin significantly inhibits growth of HCC cells via inducing cell cycle arrest and apoptosis. RNAseq analysis showed that nevadensin regulates multiple functional signaling pathways associated with cancer including Hippo signaling. Western Blot analysis revealed that nevadensin notably induces activation of the MST1/2- LATS1/2 kinase in HCC cells, further resulting in the primary effector molecule YAP phosphorylation and subsequent degradation. These results indicated that nevadensin might exert its anti-HCC activity through the Hippo-ON mechanism. Moreover, nevadensin could increase the sensitivity of HCC cells to sorafenib by down-regulating YAP and its downstream targets. Conclusions The present study indicates that nevadensin could be a potential effective approach to treating HCC, and overcoming sorafeni resistance via inducing activation of Hippo signaling.

Abstract As a globally important staple crop, wheat seeds provide us with nutrients and proteins. The trend of healthy dietary has become popular recently, emphasizing the consumption of whole-grain wheat products and the dietary benefits. However, the dynamic changes in nutritional profiles of different wheat seed regions (i.e., the embryo, endosperm and outer layers) during developmental stages and the molecular regulation have not been well studied. Here, we provide this multi-omic resource of wheat seeds and describe the generation, technical assessment and preliminary analyses. This resource includes a time-series RNA-seq dataset of the embryo, endosperm and outer layers of wheat seeds and their corresponding metabolomic dataset, covering the middle and late stages of seed development. Our RNA-seq experiments profile the expression of 63,708 genes, while the metabolomic data includes the abundance of 984 metabolites. We believe that this was the first reported transcriptome and metabolome dataset of wheat seeds that helps understand the molecular regulation of the deposition of beneficial nutrients and hence improvements for nutritional and processing quality traits.

Abstract Central carbon metabolism (CCM), including glycolysis, tricarboxylic acid cycle and the pentose phosphate pathway, is the most fundamental metabolic process in the activities of living organisms that maintains normal cellular growth. CCM has been widely used in microbial metabolic engineering in recent years due to its unique regulatory role in cellular metabolism. Using yeast and Escherichia coli as the representative organisms, we summarized the metabolic engineering strategies on the optimization of CCM in eukaryotic and prokaryotic microbial chassis, such as the introduction of heterologous CCM metabolic pathways and the optimization of key enzymes or regulatory factors, to lay the groundwork for the future use of CCM optimization in metabolic engineering. Furthermore, the bottlenecks in the application of CCM optimization in metabolic engineering and future application prospects are summarized.

The traditional Chinese medicine (TCM) Rehmanniae Radix (RR) refers to the fresh or dried root tuber of the plant Rehmannia glutinosa Libosch of the family Scrophulariaceae. As a traditional Chinese herbal medicine (CHM), it possesses multiple effects, including analgesia, sedation, anti-inflammation, antioxidation, anti-tumor, immunomodulation, cardiovascular and cerebrovascular regulation, and nerve damage repair, and it has been widely used in clinical practice. In recent years, scientists have extensively studied the active components and pharmacological effects of RR. Active ingredients mainly include iridoid glycosides (such as catalpol and aucuboside), phenylpropanoid glycosides (such as acteoside), other saccharides, and unsaturated fatty acids. In addition, the Chinese patent medicine (CPM) and Chinese decoction related to RR have also become major research subjects for TCM practitioners; one example is the Bolus of Six Drugs, which includes Rehmannia, Lily Bulb and Rehmannia Decoction, and Siwu Decoction. This article reviews recent literature on RR; summarizes the studies on its chemical constituents, pharmacological effects, and clinical applications; and analyzes the progress and limitations of current investigations to provide reference for further exploration and development of RR.

Abstract Background We aimed to analyze the genotype-phenotype correlations of STXBP1 pathogenic variants, prognostic factors and the treatment choices in a case-series of STXBP1-related disorders from China. Methods The clinical data and genetic results of the children diagnosed with STXBP1-related disorders at Xiangya hospital from 2011 to 2019 were collected retrospectively, and analyzed. We divided our patients into groups for comparison purposes: patients with missense variants and nonsense variants, patients who are seizure-free and not seizure-free, patients with mild to moderate intellectual disability (ID) and severe to profound global developmental delay (GDD). Results Nineteen patients were enrolled: 17 (89.5%) unrelated and 2 (10.5%) familial. Twelve (63.2%) were females. Developmental epileptic encephalopathy (DEE) was observed in 18 (94.7%) patients and ID alone in 1 (5.3%) individual. Thirteen patients (68.4%) had profound ID/GDD, 4 (23.53%) severe, 1 (5.9%) moderate and 1 (5.9%) mild. Three patients (15.8%) with profound ID died. A total of 19 variants were detected: pathogenic (n = 15) and likely pathogenic (n = 4). Seven were novel variants: c.664-1G>-, M486R, H245N, H498Pfs*44, L41R, L410del, and D90H. Of the 8 previous reported variants, 2 were recurrent: R406C and R292C. Anti-seizure medications were used in combinations, and 7 patients became seizure-free, and most of them achieved seizure freedom within the first 2 years of life irrespective of the type of the mutation. Effective medications for the seizure-free individuals included adrenocorticotropic (ACTH) and/or levetiracetam and/or phenobarbital and/or sodium valproate and/or topiramate and/or vigabatrin and/or nitrazepam. There was no correlation between the types of pathogenic variants and the phenotypes. Conclusion Our case-series showed that there is no genotype-phenotype correlation in patients with STXBP1-related disorders. This study adds 7 novel variants which expand the spectrum of STXBP1-related disorders. Combinations of levetiracetam and/or sodium valproate and/or ACTH and/or phenobarbital and/or vigabatrin and/or topiramate and/or nitrazepam were more often associated with seizure freedom in our cohort within 2 years of life.

Abstract The monitoring of wooden pagodas is a very important task in the restoration of wooden pagodas. Traditionally, this labor has always been carried out by surveying personnel, who manually check all parts of the pagoda, which not only consumes huge manpower, but also suffers from low efficiency and measurement errors. This article evaluates the feasibility of combining portable 3D light detection and ranging (LiDAR) scanning and unmanned aerial vehicle (UAV) photogrammetry to perform these inspection tasks easily and accurately. The wooden pagoda's exterior picture and inside point cloud are acquired using a UAV and a LiDAR scanner, respectively. We propose a feature−based global alignment method to register the site point cloud. The error equation of the column of observed values is utilized as the beginning value of the feature constraint for global leveling. The beam method leveling model solves the spatial transformation parameters and the unknown point leveling values. Then, the Structure from Motion (SfM) algorithm of computer vision is used to realize the fusion of the dense point cloud of the exterior of the wooden pagoda generated from multiple non−measured images by global optimization and the LiDAR point cloud of the interior of the wooden pagoda to obtain the complete point cloud of the wooden pagoda, which makes the deformation monitoring of the pagoda more detailed and comprehensive. After experimental verification, the overall registration accuracy of the Yingxian wooden pagoda reaches 0.006 m. Compared with the scanning point cloud data in 2018, the model is more accurate and complete. By analyzing and comparing the data of the second floor of the wooden pagoda, we knew that the inclination of a second bright layer and a second dark layer is still developing steadily. Overall, the western outer trough inclines thoughtfully, and the column frame slopes from southwest to northeast. Some internal columns showed a negative offset in 2020, and the deformation analysis of a single column was realized by comparing it with the standard column model. The main contribution of this method lies in the effective integration of UAV images and point cloud data to provide accurate data sources for good modeling. This research will provide theoretical and methodological support for the digital protection of architectural heritage and GIS data modeling. The analysis results can provide a scientific basis for the restoration scheme design.

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.

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).

The Leikoupo Formation of the Middle Triassic is one of the hot strata of marine natural gas exploration in the western Sichuan Basin in recent years. Petroleum geologists have different opinions on the reservoir-forming conditions and the types of gas pools. The research shows that the 4th member of Leikoupo Formation in the western Sichuan Basin has favorable hydrocarbon accumulation conditions. It not only has a large-scale stable distribution of the tidal flat dolomite reservoirs, but also develops two sets of source rocks: the Permian source rock and the Leikoupo Formation source rock. There are three models of hydrocarbon accumulation in the 4th member of Leikoupo Formation from the east to the west in the Western Sichuan Depression. That is the “lower generation and upper storage” structural gas reservoir transported by cross-layer source faults and fractures, the “lower generation and upper storage” structure-formation gas reservoirs transported by the relay combination of small source faults and intra-layer fractures, and the “self-generating and self-accumulation” lithologic gas reservoir transported by intra-layer fractures. After the proved reserves of 100 × 109 m3 of the structural gas reservoir in the 4th member of Leikoupo Formation in the western Sichuan Basin, it is considered that the area near the pinch-out line of the 4th member of Leikoupo Formation in the eastern depression is a favorable area for exploration of tectonic-stratigraphical gas reservoirs, and the middle and lower part of the eastern slope (Guanghan slope) in the Western Sichuan Depression is a favorable area to explore lithologic gas reservoirs.

Abstract Background Occupational exposure may be associated with an increased risk of developing hyperuricemia. This study sheds lights on the association between occupational exposure and hyperuricemia in steelworkers. Method A nested case–control study was conducted within a cohort of workers in steel companies to explore the association between occupational exposure and hyperuricemia. The case group consisted of a total of 641 cases of hyperuricemia identified during the study period, while 641 non-hyperuricemia subjects with the same age and gender distribution were randomly selected from the cohort as the control group. Results The incidence rate of hyperuricemia among workers in the steel company was 17.30%, with an incidence density of 81.32/1,000 person-years. In comparison to the reference group, the risks of developing hyperuricemia for steelworkers undergoing ever shifts, current shifts, heat exposure, and dust exposure were 2.18 times, 1.81 times, 1.58 times and 1.34 times higher respectively. The odds ratios (ORs) and 95% confidence intervals (CIs) were 1.87(1.12–3.13) and 2.02(1.21–3.37) for the cumulative number of days of night work at 0–1,972.80 and ≥ 1,972.80 (days), respectively. Compared to the group with the cumulative heat exposure of 0 (°C/year), the ORs (95% CI) for the risk of developing hyperuricemia in the groups with the cumulative heat exposure of 0–567.83 and ≥ 567.83 (°C/year) were 1.50(1.02–2.22) and 1.64(1.11–2.43), respectively. The OR (95% CI) for the risk of developing hyperuricemia was 1.56(1.05–2.32) at the cumulative dust exposure of ≥ 30.02 (mg/m3/year) compared to that at the cumulative dust exposure of 0 (mg/m3/year). Furthermore, there was a multiplicative interaction between heat exposure and dust exposure in the development of hyperuricemia. Conclusion Shift work, heat, and dust are independent risk factors for the development of hyperuricemia in steelworkers. Additionally, there is a multiplicative interaction between heat exposure and dust exposure in the development of hyperuricemia. Interventions for shift work, heat and dust may help to reduce the incidence rate of hyperuricemia and improve the health of steelworkers.

In the two-step flocculation process, shear has a significant impact on the rheological properties of the flocculating slurry. In this study, the orthogonal experiments of two-step flocculation process for fine iron tailings were designed. Based on the change of shear ratio, different shear rates and shear time were designed, the yield stress, plastic viscosity and maximum packing fraction of the flocculated suspension in each group were measured and calculated with a rheometer. The result of range and variance analysis shows the shear rate in the primary broken phase was the biggest factor affecting the yield stress and plastic viscosity of the flocculated slurry in two-step flocculation process. When the shear rate increased from 100 s-1 to 400 s-1, the yield stress and the plastic viscosity of the flocculated slurry increased by 7.14% and 21.30%, respectively. When the shear rate changed from 400 s-1 to 800 s-1, they decreased by 23.27% and 33.17%, respectively. Since the shear ratio in a two-step flocculation process is also related to both shear action and floc structure parameter, the shear ratio was introduced into the first-order reversible kinetic rate equation. Through establishing the relationship between the shear ratio and the floc structural parameter of flocculating suspension, a theoretical model of the shear-dependent maximum packing fraction was established. The measured values and theoretical calculated values of the maximum packing fraction in two-step flocculation experiments were in good agreement and the error was within 5%. Last but not least, the internal mechanism of the theoretical model was discussed from the microscopic point of view.

Ultrasound has been proven to enhance the mass transfer process and impact the fabrication of anodic aluminum oxide (AAO). However, the different effects of ultrasound propagating in different media make the specific target and process of ultrasound in AAO remain unclear, and the effects of ultrasound on AAO reported in previous studies are contradictory. These uncertainties have greatly limited the application of ultrasonic-assisted anodization (UAA) in practice. In this study, the bubble desorption and mass transfer enhancement effects were decoupled based on an anodizing system with focused ultrasound, such that the dual effects of ultrasound on different targets were distinguished. The results showed that ultrasound has the dual effects on AAO fabrication. Specifically, ultrasound focused on the anode has a nanopore-expansion effect on AAO, leading to a 12.24 % improvement in fabrication efficiency. This was attributed to the promotion of interfacial ion migration through ultrasonic-induced high-frequency vibrational bubble desorption. However, AAO nanopores were observed to shrink when ultrasound was focused on the electrolyte, accompanied by a 25.85 % reduction in fabrication efficiency. The effects of ultrasound on mass transfer through jet cavitation appeared to be the reason for this phenomenon. This study resolved the paradoxical phenomena of UAA in previous studies and is expected to guide AAO application in electrochemistry and surface treatments.

There are lots of sphere–plane air gaps in valve halls in extra-high-voltage and ultra-high-voltage converter stations. Accurate prediction for discharge characteristics of sphere–plane gaps is of great significance for the selection of shielding structure and determining the dielectric strength of the valve hall. In this paper, based on the physical process of corona inception and continuous leader inception, a computational model for calculating the discharge voltage of a sphere–plane air gap under positive switching impulse voltage is proposed, and the leader characteristics and discharge voltage are analyzed. Then, the switching impulse discharge test of the sphere–plane gap with 0.15, 2, and 0.3 m radius spherical electrodes is carried out to verify the correctness of the model. The results show that the discharge voltage calculated by the proposed method is consistent with the test results, and the error is within 7.3%. The leader inception voltage and inception time increase with the increasing spherical electrode radius at the same gap distance, and an identical spherical electrode require higher leader inception voltage and faster leader inception time with the increasing gap distance.

Sorghum (Sorghum bicolor L. Moench), a monocot C4 crop, is an important staple crop for many countries in arid and semi-arid regions worldwide. Because sorghum has outstanding tolerance and adaptability to a variety of abiotic stresses, including drought, salt, and alkaline, and heavy metal stressors, it is valuable research material for better understanding the molecular mechanisms of stress tolerance in crops and for mining new genes for their genetic improvement of abiotic stress tolerance. Here, we compile recent progress achieved using physiological, transcriptome, proteome, and metabolome approaches; discuss the similarities and differences in how sorghum responds to differing stresses; and summarize the candidate genes involved in the process of responding to and regulating abiotic stresses. More importantly, we exemplify the differences between combined stresses and a single stress, emphasizing the necessity to strengthen future studies regarding the molecular responses and mechanisms of combined abiotic stresses, which has greater practical significance for food security. Our review lays a foundation for future functional studies of stress-tolerance-related genes and provides new insights into the molecular breeding of stress-tolerant sorghum genotypes, as well as listing a catalog of candidate genes for improving the stress tolerance for other key monocot crops, such as maize, rice, and sugarcane.

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.

Background: Brain-derived neurotrophic factor (BDNF)–tropomyosin-related kinase B (TrkB) plays a critical role in the pathogenesis of depression by modulating synaptic structural remodeling and functional transmission. Previously, we have demonstrated that the ginsenoside Rb1 (Rb1) presents a novel antidepressant-like effect via BDNF–TrkB signaling in the hippocampus of chronic unpredictable mild stress (CUMS)-exposed mice. However, the underlying mechanism through which Rb1 counteracts stress-induced aberrant hippocampal synaptic plasticity via BDNF–TrkB signaling remains elusive. Methods: We focused on hippocampal microRNAs (miRNAs) that could directly bind to BDNF and are regulated by Rb1 to explore the possible synaptic plasticity-dependent mechanism of Rb1, which affords protection against CUMS-induced depression-like effects. Results: Herein, we observed that brain-specific miRNA-134 (miR-134) could directly bind to BDNF 3′UTR and was markedly downregulated by Rb1 in the hippocampus of CUMS-exposed mice. Furthermore, the hippocampus–targeted miR-134 overexpression substantially blocked the antidepressant-like effects of Rb1 during behavioral tests, attenuating the effects on neuronal nuclei-immunoreactive neurons, the density of dendritic spines, synaptic ultrastructure, long-term potentiation, and expression of synapse-associated proteins and BDNF–TrkB signaling proteins in the hippocampus of CUMS-exposed mice. Conclusion: These data provide strong evidence that Rb1 rescued CUMS-induced depression-like effects by modulating hippocampal synaptic plasticity via the miR-134-mediated BDNF signaling pathway.

Accurate digital mapping of farmland soil organic carbon (SOC) contributes to sustainable agricultural development and climate change mitigation. Farmland landscape pattern has changed greatly under anthropogenic influence, which should be considered an environmental variable to characterize the impact of human activities on SOC. In this study, we verified the feasibility of integrating landscape patterns in SOC prediction on Lower Liaohe Plain. Specifically, ten variables (climate, topographic, and landscape pattern variables) were selected for prediction with Random Forest (RF) and Support Vector Machines (SVMs). The effectiveness of landscape metrics was verified by establishing different variable combinations: (1) natural variables, and (2) natural and landscape pattern variables. The results confirmed that landscape variables improved mapping accuracy compared with natural variables. R2 of RF and SVM increased by 20.63% and 20.75%, respectively. RF performed better than SVM with smaller prediction error. Ranking of importance of variables showed that temperature and precipitation were the most important variables. The Aggregation Index (AI) contributed more than elevation, becoming the most important landscape variable. The Mean Contiguity Index (CONTIG-MN) and Landscape Contagion Index (CONTAG) also contributed more than other topographic variables. We conclude that landscape patterns can improve mapping accuracy and support SOC sequestration by optimizing farmland landscape management policies.

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.

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.

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.

Summary: Glioblastoma (GBM) is identified to share common signal pathways between glioma and immune cells. Here, we find that T cell immunoglobulin domain and mucin domain protein 3 (TIM-3) is one of the most common co-inhibitory immune checkpoints in GBM shared by tumor and non-tumor cells. Glioma cell-intrinsic TIM-3 is involved in not only regulating malignant behaviors of glioma cells but also inducing macrophage migration and transition to anti-inflammatory/pro-tumorigenic phenotype by a TIM-3/interleukin 6 (IL6) signal. In mechanism, as one of the major regulators of IL6, TIM-3 regulates its expression through activating NF-κB. Blocking this feedback loop by Tocilizumab, an IL6R inhibitor, inhibited the above effects and repressed the tumorigenicity of GBM in vivo. Our work identifies glioma cell-intrinsic functions of TIM-3/IL6 signal mediating the crosstalk feedback loop between glioma cells and tumor-associated macrophages (TAMs). Blocking this feedback loop may provide a novel therapeutic strategy for GBM.

Changes in water level of the Three Gorges Reservoir are easy to induce the deformation and failure of the reservoir slope. Periodic impoundment changes in the groundwater seepage field and stress field in the reservoir slope reduce the shear strength of rock and soil mass, and have a great impact on the stability of the reservoir bank slope and rock mass. It is urgent for the deformation monitoring of bank slopes in the reservoir area. It is difficult to find out the overall change of rock mass by setting fixed observation points, and the terrestrial laser scanning method (TLS) can obtain the point cloud data of the overall rock mass surface with centimeter accuracy, which is very suitable for the monitoring of rock mass of characteristics of no contact with the target, fast acquisition speed and high precision. In this paper, the terrestrial laser scanning method is used to monitor the dangerous rock mass of Jianchuandong in Wuxia county for two years (2017—2018) and three periods data are acquired. The stable rock mass data around the observation target of the first period is selected as datum and the iterative closest point registration (ICP) is carried out with the overlapping point cloud. The registration accuracy of the point cloud is better than ± 2.7 cm, which realizes the accurate alignment of multi-period data. According to the change of dangerous rock mass in the observation period, the datum TIN model of dangerous rock body area is constructed, and the deformation of dangerous rock mass is analyzed with the nearest distance method from point to reference surface combined with the change range of dangerous rock mass. Through the comparative analysis of the 3 periods observation data of the Jianchuandong dangerous rock mass, it is found that the dangerous rock mass has the expansion trend in 2018 compared with the left rock mass in 2017. In the reservoir water storage stage, there are obvious sag changes in some parts of the dangerous rock body, and the local deformation is about 30-70 mm due to the influence of water storage. The experiment proves the correctness and validity of the proposed monitoring method, which provides reference for the monitoring of dangerous rock state and the prevention and control of geological disasters in the Three Gorges Reservoir area.

The acceptance of kiwifruit by consumers is significantly affected by its slow ripening and susceptibility to deterioration. Ready-to-eat “Guichang” kiwifruit and its preparation technology were studied by the regulation of ethylene and 1-MCP. Harvested kiwifruits were treated with 100–2000 μl L−1ethylene for 36 h (20°C) and then treatment with 0–0.5 μl L−1 1-MCP. The results showed that the preservation effect of 0.5 μl L−1 1-MCP is inefficient when the soluble solid content of kiwifruit exceeded 15%. The ethylene-treated fruits reached an “edible window” after 24 h, but a higher concentration of ethylene would not further improve ripening efficiency, while the optimal ethylene concentration was 250 μl L−1. Moreover, after 250 μl L−1 ethylene treatment, 0.5 μl L−1 1-MCP would effectively prolong the “edible window” of fruits by approximately 19 days. The volatile component variety and ester content of 0.5 μl L−1 1-MCP-treated fruits were not different from those of the CK group. Principal component analysis and hierarchical cluster analysis indicated that the eating quality of fruits treated with 0.5 μl L−1 1-MCP was similar to that of fruits treated with ethylene. Consequently, ready-to-eat “Guichang” kiwifruit preparation includes ripening with 250 μl L−1 (20°C, 36 h) ethylene without exceeding the 1-MCP threshold and then treated with 0.5 μl L−1 1-MCP (20°C, 24 h). This study highlights the first development of a facile and low-cost preparation technology for ready-to-eat “Guichang” kiwifruit, which could reduce the time for harvested kiwifruit to reach the “edible window” and prolong the “edible window” of edible kiwifruit.

Abstract Scene classification for remote sensing is a popular topic, and many recent convolutional neural networks (CNNs)‐based methods have shown the great model capacity and learning ability of highly discriminative features. Given a large number of training data, CNN can extract extensive features and learn to predict a remote sensing image. However, for supervised learning tasks, deep models often rely on a large number of labelled remote sensing images, which are difficult to pre‐process. Thus, training a lightweight deep learning model is essential. Easy‐classified and hard samples may also cause an imbalance of training set and lead the model to overwhelm the loss function. Accordingly, a novel Efficient Recurrent Attention Network (ERANet) for remote sensing scene classification is proposed. Different from traditional deep learning methods, Efficientnet‐B0 is introduced as a lightweight backbone for the ARCNet framework, replacing the original one. By applying the modified efficient backbone, the low Floating Point Operations (FLOPs) and parameter numbers of the proposed ERANet are maintained. The significance of focal loss is determined and applied to address the sample imbalance problem and yield a desirable performance. Extensive experiments on several challenging remote sensing scene classification data sets prove the efficiency of the proposed ERANet.

Abstract In order to realize the storage of the residual coal in the goaf on the flue gas of the power plant, the adsorption characteristics of nitrogen dioxide in the flue gas of the power plant were studied. The Gaussian09 was used to study the adsorption process of NO2 molecules on coal at the density functional (DFT) B3LYP/6-311G level, and the model of NO2 adsorption by coal was established. Different quantities were obtained using orbital energy changes and molecular bond length changes. According to the principle of molecular adsorption, the adsorption of NO2 by coal is considered to be physical adsorption with endothermic heat. On the basis of simulation, using self-organized experimental devices, the single-component NO2 gas and the simulated coal-fired power plant flue gas were introduced into anthracite, bituminous coal and lignite. In single-component adsorption, the adsorption of NO2 by lignite increases with time. The time to reach equilibrium is related to the properties of the coal itself. In the process of simulated flue gas adsorption, the order of the adsorption amount of coal to flue gas is CO2 > NO2 > N2 > O2. In the simulated flue gas, coal is easy to absorb NO2 and CO2, and the competition between gases reduces the frequency of contact between NO2 and the coal surface. Simulation and experimental results show that coal has obvious adsorption characteristics for NO2, and it is feasible for the residual coal in the goaf to adsorb NO2 in the flue gas of power plants.

BackgroundHyperpolarization-activated cyclic nucleotide-gated (HCN) current reduces dendritic summation, suppresses dendritic calcium spikes, and enables inhibitory GABA-mediated postsynaptic potentials, thereby suppressing epilepsy. However, it is unclear whether increased HCN current can produce epilepsy. We hypothesized that gain-of-function (GOF) and loss-of-function (LOF) variants of HCN channel genes may cause epilepsy.ObjectivesThis systematic review aims to summarize the role of HCN channelopathies in epilepsy, update genetic findings in patients, create genotype–phenotype correlations, and discuss animal models, GOF and LOF mechanisms, and potential treatment targets.MethodsThe review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, for all years until August 2021.ResultsWe identified pathogenic variants of HCN1 (n = 24), HCN2 (n = 8), HCN3 (n = 2), and HCN4 (n = 6) that were associated with epilepsy in 74 cases (43 HCN1, 20 HCN2, 2 HCN3, and 9 HCN4). Epilepsy was associated with GOF and LOF variants, and the mechanisms were indeterminate. Less than half of the cases became seizure-free and some developed drug-resistant epilepsy. Of the 74 cases, 12 (16.2%) died, comprising HCN1 (n = 4), HCN2 (n = 2), HCN3 (n = 2), and HCN4 (n = 4). Of the deceased cases, 10 (83%) had a sudden unexpected death in epilepsy (SUDEP) and 2 (16.7%) due to cardiopulmonary failure. SUDEP affected more adults (n = 10) than children (n = 2). HCN1 variants p.M234R, p.C329S, p.V414M, p.M153I, and p.M305L, as well as HCN2 variants p.S632W and delPPP (p.719–721), were associated with different phenotypes. HCN1 p.L157V and HCN4 p.R550C were associated with genetic generalized epilepsy. There are several HCN animal models, pharmacological targets, and modulators, but precise drugs have not been developed. Currently, there are no HCN channel openers.ConclusionWe recommend clinicians to include HCN genes in epilepsy gene panels. Researchers should explore the possible underlying mechanisms for GOF and LOF variants by identifying the specific neuronal subtypes and neuroanatomical locations of each identified pathogenic variant. Researchers should identify specific HCN channel openers and blockers with high binding affinity. Such information will give clarity to the involvement of HCN channelopathies in epilepsy and provide the opportunity to develop targeted treatments.

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.

Among so many autonomous driving technologies, autonomous lane changing is an important application scenario, which has been gaining increasing amounts of attention from both industry and academic communities because it can effectively reduce traffic congestion and improve road safety. However, most of the existing researchers transform the multi-objective optimization problem of lane changing trajectory into a single objective problem, but how to determine the weight of the objective function is relatively fuzzy. Therefore, an optimization method based on the combination of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which provides a new idea for solving the multi-objective optimization problem of lane change trajectory algorithm, is proposed in this paper. Firstly, considering the constraints of lane changing and combining with the collision detection algorithm, the feasible lane changing trajectory cluster is obtained based on the quintic polynomial. In order to ensure the comfort, stability and high efficiency of the lane changing process, the NSGA-II Algorithm is used to optimize the longitudinal displacement and time of lane changing. The continuous ordered weighted averaging (COWA) operator is introduced to calculate the weights of three objective optimization functions. Finally, the TOPSIS Algorithm is applied to obtain the optimal lane change trajectory. The simulations are conducted, and the results demonstrate that the proposed method can generate a satisfactory trajectory for automatic lane changing actions.

Abstract Background The prevalence of metabolic syndrome continues to rise sharply worldwide, seriously threatening people’s health. The optimal model can be used to identify people at high risk of metabolic syndrome as early as possible, to predict their risk, and to persuade them to change their adverse lifestyle so as to slow down and reduce the incidence of metabolic syndrome. Methods Design existing circumstances research. A total of 1468 workers from an oil company who participated in occupational health physical examination from April 2017 to October 2018 were included in this study. We established the Logistic regression model, the random forest model and the convolutional neural network model, and compared the prediction performance of the models according to the F1 score, sensitivity, accuracy and other indicators of the three models. Results The results showed that the accuracy of the three models was 82.49,95.98 and 92.03%, the sensitivity was 87.94,95.52 and 90.59%, the specificity was 74.54, 96.65 and 94.14%, the F1 score was 0.86,0.97 and 0.93, and the area under ROC curve was 0.88,0.96 and 0.92, respectively. The Brier score of the three models was 0.15, 0.08 and 0.12, Observed-expected ratio was 0.83, 0.97 and 1.13, and the Integrated Calibration Index was 0.075,0.073 and 0.074, respectively, and explained how the random forest model was used for individual disease risk score. Conclusions The study showed that the prediction performance of random forest model is better than other models, and the model has higher application value, which can better predict the risk of metabolic syndrome in oil workers, and provide corresponding theoretical basis for the health management of oil workers.

Converting floodwater into power without increasing flood risk is critical for energy-stressed regions. Over the past decades, numerous methods have been proposed to solve this problem. However, few studies have investigated the theoretical explanation of the trade-offs between power generation and flood risk. This study establishes an analytical framework to derive optimal hedging rules (OHR) and explains the economic insights into flood risk reduction and power generation improvement. A two-stage model based on the concept of dynamic control of carryover storage (DCCS) was developed as part of the framework, considering forecast uncertainty and risk tolerance. The results illustrated that hedging and trade-offs between power generation and flood risk during DCCS only occurs when the forecasted inflow and forecast uncertainty are within certain ranges, beyond which there is no hedging and trade-offs analysis; either power generation or flood risk becomes the dominant objective. The OHR was divided into three cases under different levels of forecast uncertainty and risk tolerance. Compared to forecast uncertainty, downstream risk tolerance plays a more important role in determining which case of the OHR is adopted in real-world operations. The analysis revealed what and how intense trade-offs are between power generation and flood risk under different scenarios of forecasted inflow, forecast uncertainty, and risk tolerance. The framework serves as a guideline for less abundant water resources or energy-stressed areas of operational policy. Nierji Reservoir (located in northeast China) was taken as a case study to illustrate the analysis, and the application results showed that OHR increases the average annual power generation by 4.09% without extra flood risk compared to current operation rules.

Hydrological processes regulate the ecological processes of a basin. Climate change and anthropological activities lead to changes in the natural hydrological process of rivers, whereas variations in hydrological processes can disrupt the stability of ecosystems, resulting in various ecological challenges. Quantitative evaluation of ecological water demand and its key components can play a key role in the sustainable development of ecosystems. The studies of ecohydrological variation and multi-objective ecological water demand are of great significance for ecological protection and remediation due to the unique characteristics of each river basin and diverse ecological protection objectives. This study identified ecohydrological variation in ecosystems, focusing on the Irtysh River Basin as a case study, and improved methods for ecological water demand of valley forests and grasslands in terrestrial ecosystems and for the ecological water level of lake ecosystems. The results demonstrated that: (1) a drastic decrease in the annual average river flow of the basin and significant changes in ecohydrological characteristics can lead to reduced biomass; (2) the ecological water demand of valley forests and grasslands during the critical ecological stage (April–September) was 521 million m³, with 52.4% of total demand occurring in June and July. The minimum ecological water levels of the Burultokay and Jili lakes were 478.66 m and 480.66 m, whereas the maximum levels were 482.80 m and 483.20 m, respectively; (3) ecological regulation based on catchwork irrigation technology can create hydrological processes that meet the water demands of valley forests and grasslands and achieve remediation of the terrestrial ecosystem. The ecological water levels and the ecosystem balance of the Burultokay and Jili lakes can be maintained by optimizing the replenishment flow from the Irtysh River to the Burultokay Lake under different precipitation levels. This study can act as a reference for the ecological protection and remediation of the Irtysh River Basin and similar ecosystems globally.

Imaging artifacts induced by the multipath interference in Radio-Frequency sensing network usually significantly degrade the performance of Radio Tomographic Imaging (RTI) and thereby has become a major challenge in the Device-Free Localization (DFL). The multipath in the environment often invalidates the commonly used sparsity-regularized methods for RTI reconstruction because the sparse multipath-induced imaging artifacts may be misestimated as the sparse target-induced attenuation. To enhance the sensing ability of the target's effect in RTI, for the first time, this paper utilized the Low-Rank and Sparse Decomposition (LRSD) to cope with the multipath-induced imaging artifacts and infer the sparse target-induced attenuation accurately. The experimental results demonstrated the significant advantages of the proposed LRSD method in the reconstructed RTI quality, DFL accuracy, and time complexity in comparison to the presenting commonly used methods, including Tikhonov Regularization and Bayesian Compressive Sensing (BCS). The above advantages make the proposed LRSD method highly expected to improve the RTI performance and also make it applicable for real-time DFL applications.

Abstract Background Geosocial networking smartphone applications (apps) are popular tools for seeking sexual partners among men who have sex with men (MSM). We evaluated app use and risk of sexually transmitted infections (STIs) in app-using MSM (app-users) by a systematic review and meta-analysis. Methods A literature search for relevant studies was performed. We extracted date of STIs (ever being diagnosed with human immunodeficiency virus [HIV], syphilis, gonorrhea and chlamydia) and sexual behavior (e.g., number of app-met partners, unprotected anal/oral sex, HIV testing) from the eligible studies. Pooled proportions and odds ratios (ORs) with 95% confidence intervals (95% CIs) were estimated. Results Twenty-five studies were included. The self-reported prevalence of prior diagnosis of HIV among app-users ranged from 2.2 to 37.7%, and the pooled prevalence of HIV infection was 6% (95% CI, 4–11%). Compared with non-users, app-users were more likely to have gonorrhea (OR = 2.36; 95% CI, 2.07–2.70) and chlamydia (OR = 2.22; 95% CI, 1.92–2.56). The two groups were similar in terms of diagnoses of HIV (OR = 0.89, 95% CI, 0.68–1.16) and syphilis (OR = 1.92; 95% CI, 0.91–4.03). However, when one study that caused substantial heterogeneity was omitted, the pooled OR for app-users to contract syphilis became 3.00 (95% CI, 1.84–4.91) . Conclusions MSM who seek sexual partners using apps may be more likely to have STIs as than are non-users.

Aiming at the narrow and long tunnel structure, few internal features, and a large amount of point cloud data, the existing registration algorithms and commercial software registration results are not ideal, an iterative global registration algorithm is proposed for massive underground tunnel point cloud registration, which is composed of local initial pose acquisition and global adjustment. Firstly, the feature point coordinates in the point cloud are extracted, and then the station-by-station registration is performed according to the Rodrigues matrix. Finally, the registration result is considered as the initial value of the parameter, and the global adjustment of all observations is carried out. The observation values are weighted by the selection weight iteration method and the weights are constantly modified in the iteration process until the threshold conditions are met and the iteration stops. In this paper, the experimental data, made up of 85 stations of point cloud data, are from the Xiamen subway tunnel, which is about 1300 m long. When the accumulated error of station-to-station registration is too large, several stations are regarded as partial wholes, and the optimal registration is achieved through multiple global adjustments, and the registration accuracy is within 5 mm. Experimental results confirm the feasibility and effectiveness of the algorithm, which provides a new method for point cloud registration of underground space tunnel.

Objective: The aim of this study was to explore the diagnostic value of gastroscopy under local anesthesia for congenital pyriform sinus fistula (CPSF).Methods: This research was a diagnostic study. Patients received gastroscopy under local anesthesia to diagnose CPSF, and suspension laryngoscopy under general anesthesia was performed 2 days after gastroscopy. Various conditions of the internal opening of CPSF were then recorded. Patients were grouped according to lesion sides, age, time after the inflammation subsided, and history of previous surgery. The sensitivity, specificity, area under the receiver operating characteristic curve (AUC), accuracy, and positive and negative predictive values of gastroscopy were compared between the groups.Results: A total of 48 patients were recruited in this study, and no patients had severe gastroscopy-related complications. The diagnostic values of gastroscopy in 41 cases (85.4%) were consistent with suspension laryngoscopy. The sensitivity of gastroscopy was 86.4%, the specificity was 75%, the AUC was 0.807, the positive prediction rate was 97.4%, the negative prediction rate was 33.3%, the accuracy rate was 85.4%, and the diagnostic odds ratio (DOR) was 2.1. The kappa consistency test results had statistical significance (P = 0.0026, kappa = 0.3913). The diagnostic value of gastroscopy was better for the patients with inflammation subsiding for more than 4 weeks (P < 0.0001).Conclusion: Gastroscopy under local anesthesia is a safe, effective, reliable and novel diagnostic method for CPSF, and it is especially recommended as a diagnostic method for the patients with inflammation subsiding for more than 4 weeks.

In order to breed virus-free plantlets of the kiwifruit cultivar “Guichang,” which belongs to Actinidia deliciosa, in this study, stem segments with buds were used as explants, the establishment of a tissue culture rapid propagation system was carried out, and then the virus status of tissue culture plantlets was detected via the real-time reverse transcription-polymerase chain reaction (RT-qPCR) method. The tissue culture rapid propagation system proved that the contamination and browning rates could be controlled below 20% and the survival rate could be exceeded by 70% when the single bud stem segment of “Guichang” kiwifruit was sterilized with 70% alcohol for 30–60 s and 15% NaClO for 15 min, respectively. Meanwhile, we screened the hormone concentration to get better results, and the appropriate medium for adventitious bud induction was MS + 6-BA (1.0 mg/L) + IBA (0.2 mg/L); for proliferation, it was MS + 6-BA (1.0 mg/L) + IBA (0.1 mg/L); and for rooting, it was 1/2 MS + IBA (0.3 mg/L), and the efficiency of induction, proliferation, and rooting could reach 74.07%, 79.63%, and 85.18%, respectively. In addition, the RT-qPCR results demonstrated that the infection rate of 9 viruses: apple stem grooving virus (ASGV), cucumber mosaic virus (CMV), Actinidia virus X (AVX), cucumber necrosis virus (CNV), ribgrass mosaic virus (RMV), citrus leaf blotch virus (CLBV), Actinidia virus B (AcVB), Pelargonium zonate spot virus (PZSV), and cherry leaf roll virus (CLRV) in the “Guichang” kiwifruit tissue culture plantlets was 0. This study could lay a foundation for the production of “Guichang” kiwifruit tissue culture seedlings, and the medium formula provided in this study was useful for the industrial rapid propagation of “Guichang” plantlets.

Activity recognition is fundamental to many applications envisaged in pervasive computing, especially in smart environments where the resident’s data collected from sensors will be mapped to human activities. Previous research usually focuses on scripted or pre-segmented sequences related to activities, whereas many real-world deployments require information about the ongoing activities in real time. In this paper, we propose an online activity recognition model on streaming sensor data that incorporates the spatio-temporal correlation-based dynamic segmentation method and the stigmergy-based emergent modeling method to recognize activities when new sensor events are recorded. The dynamic segmentation approach integrating sensor correlation and time correlation judges whether two consecutive sensor events belong to the same window or not, avoiding events from very different functional areas or with a long time interval in the same window, thus obtaining the segmented window for every single event. Then, the emergent paradigm with marker-based stigmergy is adopted to build activity features that are explicitly represented as a directed weighted network to define the context for the last sensor event in this window, which does not need sophisticated domain knowledge. We validate the proposed method utilizing the real-world dataset Aruba from the CASAS project and the results show the effectiveness.

The SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) gene family affects plant architecture, panicle structure, and grain development, representing key genes for crop improvements. The objective of the present study is to utilize the well characterized SPLs’ functions in rice to facilitate the functional genomics of TaSPL genes. To achieve these goals, we combined several approaches, including genome-wide analysis of TaSPLs, comparative genomic analysis, expression profiling, and functional study of TaSPL3 in rice. We established the orthologous relationships of 56 TaSPL genes with the corresponding OsSPLs, laying a foundation for the comparison of known SPL functions between wheat and rice. Some TaSPLs exhibited different spatial–temporal expression patterns when compared to their rice orthologs, thus implicating functional divergence. TaSPL2/6/8/10 were identified to respond to different abiotic stresses through the combination of RNA-seq and qPCR expression analysis. Additionally, ectopic expression of TaSPL3 in rice promotes heading dates, affects leaf and stem development, and leads to smaller panicles and decreased yields per panicle. In conclusion, our work provides useful information toward cataloging of the functions of TaSPLs, emphasized the conservation and divergence between TaSPLs and OsSPLs, and identified the important SPL genes for wheat improvement.

Thermal insulation gunite (TIG) in roadways is an effective method for regional thermal hazard control in mines. The development of mine TIG materials is the foundation of thermal insulation technique. However, some conventional and advanced insulation materials are inapplicable to deep mines which are rather humid with high in situ stress and high geo-temperature. In this study, a kind of fly ash-inorganic mineral TIG material was developed and applied to the modelling of a high geo-temperature roadway. Moreover, the thermal insulation effect of the TIG layer was analyzed, and the temperature field characteristics of the TIG surrounding rock were discussed. Results reveal that (1) the TIG layer has a significant impact on the heat release of the wall and stability of the surrounding rock temperature field; (2) the initial temperature disturbance times, temperature disturbance ranges, and temperature drop rates differ with whether a TIG layer exists or not; (3) after the TIG roadway starts to be ventilated, the thermal flux densities tend to be consistent, which indicates the end of temperature disturbance; besides, the dimensionless temperature shares an exponential relation with the dimensionless radius; and (4) the characteristics of temperature drops vary with the radial positions of the surrounding rock. The research results provide a certain reference for thermal hazard control, temperature prediction, and ventilation network adjustment.

Abstract: On the basis of the characterization of microscopic pore-throats in shale oil reservoirs by high-pressure mercury intrusion technique, a grading evaluation standard of shale oil reservoirs and a lower limit for reservoir formation were established. Simultaneously, a new method for the classification of shale oil flow units based on logging data was established. A new classification scheme for shale oil reservoirs was proposed according to the inflection points and fractal features of mercury injection curves: microscopic pore-throats (less than 25 nm), small pore-throats (25−100 nm), medium pore-throats (100−1 000 nm) and big pore-throats (greater than 1 000 nm). Correspondingly, the shale reservoirs are divided into four classes, I, II, III and IV according to the number of microscopic pores they contain, and the average pore-throat radii corresponding to the dividing points are 150 nm, 70 nm and 10 nm respectively. By using the correlation between permeability and pore-throat radius, the permeability thresholds for the reservoir classification are determined at 1.00× 10−3 μm2, 0.40×10−3 μm2 and 0.05×10−3 μm2 respectively. By using the exponential relationship between porosity and permeability of the same hydrodynamic flow unit, a new method was set up to evaluate the reservoir flow belt index and to identify shale oil flow units with logging data. The application in the Dongying sag shows that the standard proposed is suitable for grading evaluation of shale oil reservoirs. Key words: shale oil, microscopic pore-throat, high pressure mercury injection, lower limit of reservoir formation, grading evaluation, Bohai Bay Basin, Dongying sag

Bacterial canker caused by Pseudomonas syringae pv. actinidiae (Psa) has led to considerable losses in all major kiwifruit-growing areas. There are no commercial products in the market to effectively control this disease. Therefore, the defense resistance of host plants is a prospective option. In our previous study, sulfur could improve the resistance of kiwifruit to Psa infection. However, the mechanisms of inducing resistance remain largely unclear. In this study, disease severity and protection efficiency were tested after applying sulfur, with different concentrations in the field. The results indicated that sulfur could reduce the disease index by 30.26 and 31.6 and recorded high protection efficiency of 76.67% and 77.00% after one and two years, respectively, when the concentration of induction treatments was 2.0 kg/m3. Ultrastructural changes in kiwifruit stems after induction were demonstrated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and the activities of phenylalanine ammonia-lyase (PAL), peroxidase (POD) and polyphenol oxidase (PPO), and the accumulation of lignin were determined by biochemical analyses. Our results showed that the morphological characteristics of trichomes and lenticels of kiwifruit stem were in the best defensive state respectively when the sulfur concentration was 3.0 kg/m3 and 1.5 kg/m3. Meanwhile, in the range of 0.5 to 2.0 kg/m3, the sulfur could promote the chloroplast and mitochondria of kiwifruit stems infected with Psa to gradually return to health status, increasing the thickness of the cell wall. In addition, sulfur increased the activities of PAL, POD and PPO, and promoted the accumulation of lignin in kiwifruit stems. Moreover, the sulfur protection efficiency was positively correlated with PPO activity (p < 0.05) and lignin content (p < 0.01), which revealed that the synergistic effect of protective enzyme activity and the phenolic metabolism pathway was the physiological effect of sulfur-induced kiwifruit resistance to Psa. This evidence highlights the importance of lignin content in kiwifruit stems as a defense mechanism in sulfur-induced resistance. These results suggest that sulfur enhances kiwifruit canker resistance via an increase in phenolic components and morphology structure modification in the kiwifruit stems. Therefore, this study could provide insights into sulfur to control kiwifruit canker caused by Psa.