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There is an urgent need for vaccines against Neisseria gonorrhoeae , the causative agent of gonorrhea. Vaccination with an outer membrane vesicle–based Neisseria meningitidis vaccine provides some protection from N. gonorrhoeae ; however, the mechanisms underlying this cross-protection are unknown. To address this need, we developed multiplexed bead-based assays for the relative quantification of human and mouse IgG and IgA against N gonorrhoeae antigens. The assays were evaluated for analyte independence, dilutional linearity, specificity, sensitivity, intra- and interassay variability, and robustness to sample storage conditions. The assay was then used to test samples from mice and humans immunized with an N meningitidis outer membrane vesicle vaccine. [ABSTRACT FROM AUTHOR]

Impaired intestinal homeostasis is a major pathological feature of inflammatory bowel diseases (IBD). Mannose and selenium (Se) both demonstrate potential anti-inflammatory and anti-oxidative properties. However, most lectin receptors bind free monosaccharide ligands with relatively low affinity and most Se species induce side effects beyond a very narrow range of dosage. This has contributed to a poorly explored therapies for IBD that combine mannose and Se to target intestinal epithelial cells (IECs) for normalization gut homeostasis. Herein, a facile and safe strategy for ulcerative colitis (UC) treatment was developed using optimized, mannose-functionalized Se nanoparticles (M-SeNPs) encapsulated within a colon-targeted hydrogel delivery system containing alginate (SA) and chitosan (CS). This biocompatible nanosystem was efficiently taken up by IECs and led to increased expression of Se-dependent glutathione peroxidases (GPXs), thereby modulating IECs' immune response. Using a mouse model of DSS-induced colitis, (CS/SA)-embedding M-SeNPs (C/S-MSe) were found to mitigate oxidative stress and inflammation through the inhibition of the NF-kB pathway in the colon. This stabilized mucosal homeostasis of IECs and ameliorated colitis-related symptoms, thereby providing a potential new approach for treatment of IBD. [ABSTRACT FROM AUTHOR]

Main conclusion: Lysine plays an essential role in the growth differences between male and female S. linearistipularis plants under salt stress. Furthermore, SlDHDPS is identified as a vital gene contributing to the differences in saline-alkali tolerance between male and female plants of S. linearistipularis. Soil salinization is a significant problem that severely restricts agricultural production worldwide. High salinity and low nutrient concentrations consequently prevent the growth of most plant species. Salix linearistipularis is the only woody plant (shrub) naturally distributed in the saline-alkali lands of the Songnen Plain in Northeast China, and it is one of the few plants capable of thriving in soils with extremely high salt and alkaline pH (>9.0) levels. However, insufficient attention has been given to the interplay between salt and nitrogen in the growth and development of S. linearistipularis. Here, the male and female plants of S. linearistipularis were subjected to salt stress with nitrogen-starvation or nitrogen-supplement treatments, and it was found that nitrogen significantly affects the difference in salt tolerance between male and female plants, with nitrogen-starvation significantly enhancing the salt stress tolerance of female plants compared to male plants. Transcriptional analyses showed 66 differentially expressed nitrogen-responsive genes in female and male roots, with most of them showing sexual differences in expression patterns under salinity stress. RNA-seq and RT-qPCR analysis demonstrated that six genes had an opposite salt-induced expression pattern in female and male roots. The expression of the 4-hydroxy-tetrahydrodipicolinate synthase encoding gene (SlDHDPS) in female roots was higher than that in male roots. Further treatment with exogenous lysine could significantly alleviate the inhibitory effect of salt stress on the growth of female and male plants. These results indicate that the SlDHDPS in the nitrogen metabolism pathway is involved in the resistance of S. linearistipularis to salt stress, which lays a foundation for further exploring the mechanism of nitrogen on salt tolerance of S. linearistipularis, and has a significant reference value for saline-alkali land management and sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Abnormal levels of catecholamine (CA) neurotransmitters and their metabolites in biological fluids can lead to various neurological disorders. Herein, a boric acid‐functionalized hypercrosslinked polymer was prepared and utilized as a sorbent for the dispersive solid‐phase extraction of CAs and their metabolites in rat serum. By combination with a high‐performance liquid chromatography‐fluorescence detector, the extraction parameters for the seven target analytes were optimized. Under the optimal extraction condition, the methodology for the quantitative analysis of CAs and their metabolites in rat serum samples was established. The limits of detection and limits of quantification were found to be in the ranges of 0.010–0.015 and 0.033–0.050 ng/mL, respectively. The results demonstrated satisfactory recoveries, with values ranging from 88.02% to 113.27%, accompanied by relative standard deviations within the range of 2.69%–9.59%. In addition, the method showed good anti‐interference ability (matrix effect ranged from 2.64% to 18.07%). The developed method was validated for the determination of CAs and their metabolites in normal and Alzheimer's disease model rats' serum, which proved the promising application of the method for CAs neurotransmitter analysis in biological samples. [ABSTRACT FROM AUTHOR]

Under the dual-carbon target, hydrogen energy, as a zero-carbon secondary energy source, has great scope for replacing fossil feedstocks in the fields of energy, transportation and industry. However, the current research on the competitiveness of hydrogen energy in various fields is not sufficiently addressed. In this paper, we use the LEAP model to predict the future scale of hydrogen use and the two-factor learning curve to predict the trend of hydrogen price change from 2025 to 2050, using Qinghai Province as the research background. At the same time, considering the carbon emission reduction benefits and raw material costs, the competitiveness of hydrogen energy in energy, transportation, industry and other fields in the future is compared. The results show that: 1) The hydrogen load scale in Qinghai Province will grow fast from 2025 to 2030. From 2030 to 2040, it slows under the steady and basic scenarios but remains high under the accelerated one. By 2040, the consumption scales are 1.057 million, 649,000 and 442,000 tons respectively. 2) The price of hydrogen energy will drop rapidly from the current 28 CNY/kg to about 20 CNY/kg in the next 5 years. By 2040, the price of hydrogen energy will be reduced to about 17 CNY/kg. 3) In terms of hydrogen energy competitiveness, when carbon emissions are not taken into account, hydrogen energy is currently competitive in the transportation field. During 2032-2038, it will be competitive in the field of methanol synthesis. By 2040, hydrogen energy will not be competitive in the fields of ammonia synthesis and power/heating. When considering carbon emissions, the competitiveness of hydrogen energy in the transportation field will become greater. The competitive year in the field of methanol synthesis will be 1-2 years ahead. By 2040, it will not be competitive in the field of synthetic ammonia and power/heating, but the gap will be significantly reduced due to the consideration of carbon emissions. [ABSTRACT FROM AUTHOR]

Metric-based meta-learning methods have demonstrated remarkable success in the domain of few-shot image classification. However, their performance is significantly contingent upon the choice of metric and the feature representation for the support classes. Current approaches, which predominantly rely on holistic image features, may inadvertently disregard critical details necessary for novel tasks, a phenomenon known as "supervision collapse". Moreover, relying solely on visual features to characterize support classes can prove to be insufficient, particularly in scenarios involving limited sample sizes. In this paper, we introduce an innovative framework named Patch Matching Metric-based Semantic Interaction Meta-Learning (PatSiML), designed to overcome these challenges. To counteract supervision collapse, we have developed a patch matching metric strategy based on the Transformer architecture to transform input images into a set of distinct patch embeddings. This approach dynamically creates task-specific embeddings, facilitated by a graph convolutional network, to formulate precise matching metrics between the support classes and the query image patches. To enhance the integration of semantic knowledge, we have also integrated a label-assisted channel semantic interaction strategy. This strategy merges word embeddings with patch-level visual features across the channel dimension, utilizing a sophisticated language model to combine semantic understanding with visual information. Our empirical findings across four diverse datasets reveal that the PatSiML method achieves a classification accuracy improvement of 0.65% to 21.15% over existing methodologies, underscoring its robustness and efficacy. [ABSTRACT FROM AUTHOR]

Accurately predicting flight delays remains a significant challenge in the aviation industry due to the complexity and interconnectivity of its operations. The traditional prediction methods often rely on meteorological conditions, such as temperature, humidity, and dew point, as well as flight-specific data like departure and arrival times. However, these predictors frequently fail to capture the nuanced dynamics that lead to delays. This paper introduces network centrality measures as novel predictors to enhance the binary classification of flight arrival delays. Additionally, it emphasizes the use of tree-based ensemble models, specifically random forest, gradient boosting, and CatBoost, which are recognized for their superior ability to model complex relationships compared to single classifiers. Empirical testing shows that incorporating centrality measures improves the models' average performance, with random forest being the most effective, achieving an accuracy rate of 86.2%, surpassing the baseline by 1.7%. [ABSTRACT FROM AUTHOR]

A diatomite-modified Fe2O3 (Fe2O3/Dia) catalyst was prepared to catalyze the ozonation degradation of sulfachloropyridazine sodium (SPDZ). The chemical oxygen demand (COD) was used as the index of pollutant degradation. The catalytic ozonation experiment showed that the COD removal rate of SPDZ was 87% under Fe2O3/Dia catalysis, which was much higher than that obtained when using Fe2O3 as the catalyst. The characteristics of the Fe2O3/Dia catalyst were investigated, and the successful synthesis of the Fe2O3/Dia composite catalyst was proved by XRD, XPS, SEM, FTIR, BET and other characterization methods. The catalytic mechanism of degradation by ozone with Fe2O3/Dia was analyzed. According to free-radical trapping experiments and an in situ electron paramagnetic spectrometer characterization analysis, the main oxidizing species in the catalytic Fe2O3/Dia ozone system is ·OH. The intermediates in the degradation process of SPDZ were detected and analyzed in detail by liquid chromatography-coupled mass spectrometry. The degradation mechanism and three degradation paths of SPDZ were proposed. [ABSTRACT FROM AUTHOR]

The context-dependent text-to-SQL task has profound real-world implications, as it facilitates users in extracting knowledge from vast databases, which allows users to acquire the information interactively for better accuracy. Unfortunately, current models struggle to address this task effectively due to the scarcity of data led by the high annotation overhead. The most straightforward method for addressing this problem is data augmentation, which aims at scaling up the parsing corpus. However, the naive methods suffer from the low diversity of the augmented data. To address this limitation, we propose the state-based CONtext-dependent text-to-SQL Data Augmentation (ConDA), which generate and filter augmented data based on the dialogue state, which has higher diversity. Experimental results show that ConDA yields performance improvement on all experimental datasets with an average boosting of 1.6 % , proving the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Integration of functional fillers into liquid metals (LM) induces rheology modification, enabling the free-form shaping of LM at the micrometer scale. However, integrating non-chemically modified low-dimensional materials with LM to form stable and uniform dispersions remain a great challenge. Herein, we propose a solvent-assisted dispersion (SAD) method that utilizes the fragmentation and reintegration of LM in volatile solvents to engulf and disperse fillers. This method successfully integrates MXene uniformly into LM, achieving better internal connectivity than the conventional dry powder mixing (DPM) method. Consequently, the MXene/LM (MLM) coating exhibits high electromagnetic interference (EMI) shielding performance (105 dB at 20 μm, which is 1.6 times that of coatings prepared by DPM). Moreover, the rheological characteristic of MLM render it malleable and facilitates direct printing and adaptation to diverse structures. This study offers a convenient method for assembling LM with low-dimensional materials, paving the way for the development of multifunctional soft devices. This work offers a convenient method (solvent-assisted dispersion) for assembling liquid metals with MXene and other low-dimensional materials, paving a path for the development of multifunctional soft devices. [ABSTRACT FROM AUTHOR]

The cultivation of microalgae from municipal wastewater, while simultaneously removing nutrients from the water column, has the potential to aid biodiesel production and carbon dioxide fixation, thereby alleviating the pressure of energy shortages. In this research, different ratios of sodium bicarbonate and glucose were used to prepare simulated municipal wastewater. The results demonstrated that microalgae were most effectively treated under one-stage direct treatment conditions. During direct culture, the most effective treatment was observed for IAA-3, which exhibited a dry weight of 1.4363 g/L and a lipid content of 25.05% after stimulation with 0.0005 M NaHCO3. In contrast, NaHCO3-2 demonstrated optimal performance during the secondary culture, with a dry weight of 1.6844 g/L and a lipid content of 18.05%. Finally, the economic, social and environmental benefits of direct treatment (IAA-3) and secondary treatment NaHCO3-2 were analyzed. The benefits of direct treatment were found to be USD 0.50989/L, while those of secondary treatment were USD 0.43172/L. For each tonne of municipal wastewater treated, the carbon sequestration benefits of IAA-3 during direct treatment and NaHCO3-2 during secondary treatment were USD 0.45645 and USD 0.85725, respectively. [ABSTRACT FROM AUTHOR]

Saline and alkaline stresses limit plant growth and reduce crop yield. Soil salinization and alkalization seriously threaten the sustainable development of agriculture and the virtuous cycle of ecology. Biofertilizers made from plant growth−promoting rhizobacteria (PGPR) not only enhance plant growth and stress tolerance, but also are environmentally friendly and cost-effective. There have been many studies on the mechanisms underlying PGPRs enhancing plant salt resistance. However, there is limited knowledge about the interaction between PGPR and plants under alkaline–sodic stress. To clarify the mechanisms underlying PGPR's improvement of plants' tolerance to alkaline–sodic stress, we screened PGPR from the rhizosphere microorganisms of local plants growing in alkaline–sodic land and selected an efficient strain, Bacillus altitudinis AD13−4, as the research object. Our results indicate that the strain AD13−4 can produce various growth-promoting substances to regulate plant endogenous hormone levels, cell division and differentiation, photosynthesis, antioxidant capacity, etc. Transcriptome analysis revealed that the strain AD13−4 significantly affected metabolism and secondary metabolism, signal transduction, photosynthesis, redox processes, and plant–pathogen interactions. Under alkaline–sodic conditions, inoculation of the strain AD13−4 significantly improved plant biomass and the contents of metabolites (e.g., soluble proteins and sugars) as well as secondary metabolites (e.g., phenols, flavonoids, and terpenoids). The 16S rRNA gene sequencing results indicated that the strain AD13−4 significantly affected the abundance and composition of the rhizospheric microbiota and improved soil activities and physiochemical properties. Our study provides theoretical support for the optimization of saline–alkali-tolerant PGPR and valuable information for elucidating the mechanism of plant alkaline–sodic tolerance. [ABSTRACT FROM AUTHOR]

In the global ecosystem, wetlands are vital carbon sinks, playing a crucial role in absorbing greenhouse gases such as carbon dioxide and mitigating global warming. Accurate estimation of wetland carbon content is essential for research on wetland carbon sinks. However, the carbon cycle of wetlands is complex, and the carbon sinking of wetlands is affected by climate, topography, water level conditions, vegetation types, soil types, and other factors. This has caused significant challenges in the estimation of wetland carbon sinks. In current studies, most research has focused on the impact of individual factors on wetland carbon sinks, often ignoring the interaction between various factors, which further leads to uncertainty in wetland carbon measurements. This paper aims to elucidate the process of the wetland carbon cycle, summarize the factors affecting wetland carbon sinks, and explore the interplay between various factors and their influence on wetland carbon sinks, aiming to provide theoretical support for the study of wetland carbon sinks. Additionally, this paper reviews the advantages and disadvantages of current wetland carbon measurement methods, proposes research directions for combining machine learning methods, identifies existing difficulties in current wetland carbon measurement, and offers suggestions to serve as a reference for future wetland carbon sink estimation and wetland management.Highlights: The potential and significance of wetland carbon sinks are explained. The advantages and disadvantages of current wetland carbon measurement techniques are summarized. The prospective method for integrating machine learning into integrated wetland carbon measurement is proposed. [ABSTRACT FROM AUTHOR]

According to the urgent low latency and the heavy computation tasks demands required for sixth‐generation (6G) wireless networks, the authors introduce the conventional resource allocation algorithms, including the game theory, artificial‐intelligence (AI) methods, and matching theory enabled framework, in which the multi‐access edge computing (MEC) scheme collaborative with the cloud platform to serve the primary users (PUs) and cognitive users (CUs) for next generation multiple access (NGMA). The proposed framework allows both the PUs and CUs to offload their computation tasks in a 6G‐enabled cognitive radio (CR) networks, so called cloud‐assisted CR‐MEC networks. In particular, the fundamentals of this conceived networks based on NGMA are first introduced. Hence, a number of methods based on the resource allocation algorithms are proposed in order to improve the quality of service for the mobile users, and reduce their transmission latency as well as the energy consumptions. Moreover, the motivations, challenges, and representative models for these conventional algorithms are described for integrated‐intelligent communication and computing aided NGMA networks. Furthermore, the open issues and future research directions for this conceived networks are summarised. [ABSTRACT FROM AUTHOR]

Full genomic sequence shows HLA‐G*01:19 differs from HLA‐G*01:04:01:01 only at position 99 in exon 2. [ABSTRACT FROM AUTHOR]

In order to meet the current needs of power transmission, people have turned their attention to direct current (DC) transmission. When the alternating current(AC) power grid (PG) fails, it is easy to cause commutation failure in the DC system, thereby increasing the fault scope of the system. Therefore, this article adopts a flexible DC transmission system. Flexible DC converters have many control parameters, and there are mutual influences and conflicts between these parameters. By applying intelligent algorithms to multi‐objective optimization (MOP), these complex MOP problems can be effectively solved and an optimal set of control parameter combinations can be found. This method has an important contribution and novelty for optimizing the converter control parameters of flexible DC transmission systems. This article achieves fast and accurate MOP of the control parameters of flexible DC transmission converters by continuously detecting the similarities between antibodies and maintaining the diversity of the population. The research results show that the average DC side current is about 405A in the first 20 seconds, and the DC side current fluctuates regularly after 20 seconds. This article lays the foundation for establishing a real‐time simulation model of flexible DC transmission systems suitable for real‐time simulation systems. [ABSTRACT FROM AUTHOR]

In the early Qing dynasty, the Jesuit missionary Louis de Poirot's (He Qingtai 賀清泰, 1735–1814) Chinese rendition of the Bible, Guxin Shengjing (The Ancient and New Testament) (古新聖經), reshaped the figure of Abraham. Contrary to the depiction by Chinese Jews of the era, de Poirot portrayed Abraham as a sage, resonating with the traditional Chinese concept of the "five cardinal relationships" (rulers to subjects, fathers to sons, husbands to wives, among siblings, and between friends), and an exemplar of virtue and faith, devoid of human flaws. Key differences emerged in translating Abraham's name, religious stature, and national identity, influenced by distinct belief systems, attitudes towards Confucian culture, and political dynamics. Analyzing these Catholic and Jewish perspectives on Abraham enhances our understanding of the Bible's contextualization and informs contemporary religious localization. [ABSTRACT FROM AUTHOR]

The lack of high‐performance electrodes is a key factor restricting the development of sodium‐ion batteries (SIBs), and usually a certain type of electrode material alone often fails to combine the merits of high capacity and good conductivity. Herein, nitrogen‐doped carbon (NC) was used as a multifunctional bridge to uniformly compound high‐capacity MoS2 nanoparticles with highly conductive Ti3C2Tx nanosheets to form Ti3C2Tx@MoS2/NC composite with flower‐like architecture. Ultrafine MoS2 nanoparticles were uniformly anchored on Ti3C2Tx nanosheets to form nanosheets primary building blocks with a sandwich‐like architecture, which not only shortens the ion transfer distance but also enlarges the layer spacing of Ti3C2Tx favoring the storage of more sodium ions as well as their transport capacity. Moreover, the flower‐like structures with abundant edges can provide an ample active sites and high pseudocapacitance behavior. As a result, flower‐like Ti3C2Tx@MoS2/NC displays a high electrochemical properties with an excellent cycling stability over 2000 cycles (81.4 % capacity retention) and preeminent rate capacity of 383 mAh g−1 at 30 A g−1. Furthermore, Ti3C2Tx@MoS2/NC‖Na3V2(PO4)3 full cell displays a capacity of 59 mAh g−1 at 0.4 A g−1 after 180 cycles. This work displays a high‐performance anode composite for SIBs and provides insight into the preparation of other composites. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5 ) poses a significant public health risk due to its association with respiratory and cardiovascular diseases. Given the limited availability of PM 2.5 monitoring stations, there is a pressing need for reliable real-time forecasting models. This study introduces TSPPM25, a novel Transformer-based model designed for spatiotemporal prediction of PM 2.5 levels. TSPPM25 leverages multiple data embedding techniques and various attention layers to effectively capture the intricate spatiotemporal relationships in multivariate data. The model's performance is evaluated using a California Aerosol Optical Depth PM 2.5 dataset and compared with several baseline models, including LSTM, Bi-LSTM, Linear Regression, and basic heuristics models. The results demonstrate that TSPPM25 exhibits superior spatiotemporal learning capabilities, robustness, and stability, outperforming other models across MSE, MAE, and SMAPE metrics. Furthermore, the study explores the underlying patterns in PM 2.5 data through harmonic analysis, revealing that TSPPM25 performs exceptionally well even in complex scenarios characterized by mixed wave patterns. Conclusively, TSPPM25 emerges as a valuable tool for predicting PM 2.5 levels demonstrating its efficacy in the California region, and thereby contributing significantly to the field of air quality forecasting. [ABSTRACT FROM AUTHOR]

This article, published in Experimental Dermatology, explores the levels of interleukin 38 (IL-38) in patients with pemphigus vulgaris (PV), an autoimmune bullous disease. The study found that patients with PV had significantly lower serum levels of IL-38 compared to healthy controls. Immunohistochemical staining also revealed reduced expression of IL-38 in the epidermal layers of PV patients' skin. These findings suggest that IL-38 may play a role in modulating inflammatory responses and could have implications for understanding autoimmune and inflammatory conditions. However, further research with larger sample sizes is needed to confirm these preliminary findings. [Extracted from the article]

To optimize the energy supply potential and complementary advantages of distributed energy, this paper focuses on the dispatching optimization of cogeneration virtual power plant considering uncertainty. First of all, wind power, photovoltaic, combined heat and power (CHP) units, electric boilers, and controllable loads are integrated into a CHP virtual power plant. Then, carbon capture and electric-to-gas devices are introduced to realize carbon recycling. Furthermore, quantify the risk of real-time dispatching of virtual power plants through uncertainty scenario generation and conditional value at risk (CVaR) theory, and the multi-objective stochastic dispatching optimization model of virtual power plants is built with the aim at minimizing the operation cost, carbon emissions, and operation risk as the objectives, and the CRITIC weighting method is adopted to solve it. Finally, the calculation results show that: 1) the electric boiler can use wind and photovoltaic power to supply heat for the system, reduce the dependence ofthe virtual power plant (VPP) on the CHP unit, and make the electric output of the unit more flexible. 2) The risk quantification method proposed can fully measure the risk situation in real-time dispatching, arrange the wind and photovoltaic power generation plan and backup plan more reasonably, and enable the VPP to get more benefits while avoiding the risks in real-time dispatching. [ABSTRACT FROM AUTHOR]

Against the backdrop of global attention to climate change and environmental sustainability, the development timing and comprehensive cost of regional renewable energy power generation projects have become a focus of attention. By constructing effective models to evaluate them, it can help promote the healthy development of renewable energy projects. The research aims to quantitatively evaluate the development status of local renewable energy projects by constructing a comprehensive evaluation model, minimize information loss, and improve the accuracy of evaluation results. This study adopted a comprehensive evaluation model that combines Analytic Hierarchy Process (AHP) based on accelerated genetic algorithm, entropy weight method, and ideal point method. Firstly, the subjective weights of the development evaluation indicators for regional renewable energy power generation projects are calculated. Secondly, the entropy weight method is used to analyze the trend of each indicator and obtain objective weights. Finally, combined with the objective weights and the evaluation results calculated using the TOPSIS method, a comprehensive evaluation of renewable energy power generation projects in various regions is conducted. Through analysis, the core indicators of the development level of renewable energy power generation projects in various regions show specific performance, such as Hebei's evaluation value of 0.4945 in the proportion of comprehensive energy development, and Inner Mongolia's evaluation value of 0.4045 in the proportion of comprehensive energy installed capacity. Meanwhile, genetic optimization methods exhibit significant advantages in the calculation of optimization schemes compared to dynamic programming methods, possessing strong global search capabilities and high-precision solutions. This study provides a new research method and approach for the evaluation of regional renewable energy power generation projects, demonstrating the practical value and certain advantages of the research method. [ABSTRACT FROM AUTHOR]

Herein, a magnetic borate‐functionalized MXene composite with multiple boronic affinity sites was fabricated by embedding Fe3O4 nanoparticles with 4‐formylphenylboronic acid functionalized Ti3C2Tx nanosheets and served as sorbent for the simultaneous extraction of catecholamines (CAs) in urine samples. The morphology and structure of the magnetic materials were investigated using scanning microscopy, vibrating sample magnetometer, X‐ray photoelectron spectrometer, and X‐ray diffraction. The introduction of polyethyleneimine can amplify the bonded boronic acid groups, thereby effectively improving the adsorption capacities for CAs based on the multiple interactions of boronic affinity, hydrogen bonding, and metal coordination. The adsorption performance was investigated using the kinetics and isotherms models, and the main parameters that influence the extraction efficiency were optimized. Under the most favorable magnetic solid‐phase extraction condition, a sensitive method for the analysis of CAs in urine samples was developed by combining magnetic solid‐phase extraction conditions with high‐performance liquid chromatography detection. The findings illustrated that the proposed approach possessed a wide linearity range of 0.05–250 ng/mL with an acceptable correlation coefficient (R2 ≥ 0.9984) and detection limits of 0.010–0.015 ng/mL for the target CAs. The research not only provides a notable composite with multiple boronic affinity sites but also offers an effective and feasible measure for the detection of CAs in biological samples. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown the interaction between age and socioeconomic status (SES) on the risk of infertility in the UK, but the association is still unclear in the United States. Therefore, the present study investigated the effect of age on the relationship between SES and the risk of infertility in American women. Methods: The study included adults who participated in the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2018. The poverty income ratio (PIR) was used to represent the SES of the population. With participants stratified according to age category (< 35 years; ≥ 35 years), we further assessed differences in the relationship between PIR and infertility risk among participants of different age groups using multivariate logistic regression and interaction tests. Results: Approximately 3,273 participants were enrolled in the study. There were 399 cases of infertility and 2,874 cases without infertility. In women ≥ 35 years of age, PIR levels were significantly higher in infertile participants than in non-infertile participants, but no such difference was found in those < 35 years of age. The association of PIR with the risk of infertility appeared to differ between age < 35 years and age ≥ 35 years (OR: 0.99, 95%Cl: 0.86–1.13 vs. OR: 1.24, 95%Cl: 1.12–1.39) in a fully adjusted model. Furthermore, an interaction between age and PIR increased the risk of infertility (p-value for interaction < 0.001). Conclusion: Our study found that age may influence the association between PIR and infertility. It is imperative to perform further studies to provide more evidence. [ABSTRACT FROM AUTHOR]

Background: Psoriasis is a chronic skin inflammatory disease characterized by epidermal proliferation and inflammatory cell infiltration. AXL is a tyrosine kinase receptor that promotes cell proliferation and invasion in cancer cells, and its expression is elevated in multiple tumors. However, less is known about its expression and function in inflammatory diseases. Objectives: The aim of this study is to examine AXL expression in psoriasis and investigate the biological function of AXL under psoriatic conditions. Results: AXL mRNA expression was decreased in psoriatic skin compared to healthy skin, and an inverse correlation with neutrophil‐to‐lymphocyte ratio and platelet‐to‐lymphocyte ratio was observed. Immunohistochemical staining of psoriatic skin revealed decreased AXL expression of the epidermis and an increased number of AXL‐positive dendritic cells in the dermis. Stimulation of epidermal keratinocytes with antimicrobial peptide LL37, but not with IL‐17A, resulted in decreased AXL expression. Knockdown of AXL in epidermal keratinocytes did not affect cell proliferation or expression of psoriasis‐associated cytokines and chemokines. Conclusion: Decreased epidermal AXL expression and increased infiltration of AXL‐expressing dendritic cells were revealed in psoriasis. [ABSTRACT FROM AUTHOR]

The Cu(II) complexes (H-5-FAP)2CuBr4 (1) and (H-2,3-dimpy)2CuCl4 (2) have been prepared and characterized structurally and magnetically (H-5-FAP = 2-amino-5-fluoropyridinium; H-2,3-dimpy = 2,3-dimethylpyridinium). They crystallize in the space groups P-1 and Pbcn, respectively, in comparison to their halido counterparts (H-5-FAP)2CuCl4 (1a) and (H-2,3-dimpy)2CuBr4 (2a) which crystallize in the space groups P21/c and P21/n. The differences in crystal packing, resulting in part from the difference in distortion of the CuX42− ions, create different magnetic lattices. Data for 1 were fit to the strong-rail ladder model resulting in a Curie constant of 0.400(8) emu-K/mol-Oe, J/kB-rail = −5.77(1) K and J/kB-rung = 3.17(3) K. Data for 2 were fit to the Curie-Weiss law resulting in a Curie constant of 0.398(1) emu-K/mol-Oe and θ = −0.11(4) K, indicating a virtual lack of magnetic exchange interactions. The structures and magnetic properties are compared to literature compounds and general trends noted. The differences in the chloride/bromide ions in the structure lead to significant differences in the packing in the cases of both 1 and 2, which result in differences in the antiferromagnetic exchange in both complexes and, in the case of 2, versus 2a, an elimination of the antiferromagnetic properties. [ABSTRACT FROM AUTHOR]

Background: Caesarean scar pregnancy (CSP) is a special type of ectopic pregnancy with a high risk of massive haemorrhage. Few studies have focused on the efficacy of prophylactic abdominal aortic balloon occlusion as a minimally invasive method in caesarean section. This study aimed to evaluate the effectiveness and safety of prophylactic abdominal aortic balloon occlusion for patients with type III CSP. Methods: This was a prospective cohort study. Patients with type III CSP in the First Affiliated Hospital of Zhengzhou University from January 2020 to June 2022 were enrolled. Eligible patients received prophylactic abdominal aortic balloon occlusion (defined as the AABO group) or uterine artery embolization (defined as the UAE group) before laparoscopic surgery. Clinical outcomes included intraoperative blood loss, body surface radiation dose, hospitalization expenses, and time to serum β-hCG normalization, and safety were also assessed. Results: A total of 68 patients met the criteria for the study, of whom 34 patients were in the AABO group and 34 patients were in the UAE group. The median intraoperative blood loss in the AABO and UAE groups was 17.5 (interquartile ranges [IQR]: 10, 45) and 10 (IQR: 6.25, 20) mL, respectively (P = 0.264). The body surface radiation dose of the AABO group was much lower than that of the UAE group (5.22 ± 0.44 vs. 1441.85 ± 11.59 mGy, P < 0.001). The AABO group also had lower hospitalization expenses than the UAE group (2.42 ± 0.51 vs. 3.42 ± 0.85 *10^5 yuan, P < 0.001). The average time to serum β-hCG normalization in the AABO group was 28.9 ± 3.21 d, which was similar to that in the UAE group (30.3 ± 3.72 d, P = 0.099). In addition, the incidence of adverse events in the AABO group was lower than that in the UAE group (5.9% vs. 58.8%, P < 0.001). Conclusion: Prophylactic AABO was equally as effective as UAE in patients with type III CSP but was safer than UAE during and after the operation. [ABSTRACT FROM AUTHOR]

In the production process of oil and gas wells, the migration of solid particles, such as mud and sand, often leads to screen pipe clogging, resulting in production reduction or even shutdown. Controlled plasma pulse plugging removal technology is a new physical method for unplugging. Plasma, generated by the electrical explosion of the wire, then triggers a shock wave, which can remove the plugging. In this paper, the performance of controllable plasma pulse plugging removal technology is evaluated by simulating the plugging state of the downhole screen through laboratory experiments. The test results of screen plate unplugging effect evaluation fully show that the plasma pulse decongestion technology can carry out effective decongestion, can effectively reduce the pressure behind the clogging zone and increase the flow rate of the clogging zone, and is suitable for different screen plate blockage states such as mild, moderate and severe. Thus, this technology has a good application prospect. [ABSTRACT FROM AUTHOR]

Forecasting time series data is a big challenge due to the temporal and multivariate dependencies in the data. In this paper, we present a new approach named as TPPM25 (Transformer-based Prediction of PM 2.5 ) for forecasting PM 2.5 , a key air quality indicator. It is based on the state-of-the-art Transformer neural network and various data embedding techniques. By performing attention calculations among features over time steps, TPPM25 mimics cognitive attention and selectively enhances essential parts of the input data while diminishing other parts. TPPM25 is able to effectively capture temporal relations to multiple influencing meteorological features. Experiments demonstrate its effectiveness by comparing with a cutting-edge ensemble deep learning model from Zhang et al. (Inf Sci 544:427–445, 2021). Our TPPM25 model outperforms Zhang et al.'s model under the same experimental setting on a well-researched benchmark dataset. As Zhang et al.'s model is restricted to univariate PM 2.5 prediction, our TPPM25 model bypasses this restriction and further improves the prediction accuracy when considering more influencing meteorological features. Moreover, our TPPM25 model is able to maintain high prediction accuracy over longer periods of time as compared to the Long-Short Term Memory (LSTM) and Bidirectional LSTM models. [ABSTRACT FROM AUTHOR]

Museum was a public space to display order, cultivate citizens, and construct cultural identity, which exerted a major influence on modern life, and then became an object of literary writing. William Morris affirmed the museum's education role, and viewed museums as a field to realize his socialist ideals. However, under the capitalist system, museums are subject to political power and follow the logic of capital. The direction the museums taking is contrary to Morris's political ideal. In News from Nowhere, Morris attacks the manipulative purpose of museum visits, and attempts to construct a museum as an equal, interactive and sharing space to highlight art and social ethics. From the perspective of Ethical Literary Criticism, the political and capital intervention of collection and exhibition serves as the ethical knot of the museum narrative, while the visitors' identity anxiety as its ethical line, and they interweave with each other to constitute the museums' existential crisis. [ABSTRACT FROM AUTHOR]

In this study, a borate hyper‐crosslinked polymer was synthesized by crosslinking 1‐naphthalene boric acid and dimethoxymethane via the Friedel‐Crafts reaction. The prepared polymer exhibits excellent adsorption performance toward alkaloids and polyphenols with maximum adsorption capacities ranging from 25.07 to 39.60 mg/g. Adsorption kinetics and isotherms model results indicated the adsorption was a monolayer and chemical process. Under the optimal extraction conditions, a sensitive method was established for the simultaneous quantification of alkaloids and polyphenols in green tea and Coptis chinensis by coupling with the proposed sorbent and ultra‐high performance liquid chromatography detection. The proposed method exhibited a wide linear range of 5.0–5000.0 ng/ml with R2 ≥ 0.99, a low limit of detection (0.66–11.25 ng/ml), and satisfactory recoveries (81.2%–117.4%). This work provides a simple and convenient candidate for the sensitive determination of alkaloids and polyphenols in green tea and complex herbal products. [ABSTRACT FROM AUTHOR]

Recently, great efforts have been made to explore high-performance microwave absorbing (MA) materials, which aim to reduce the booming electromagnetic wave (EMW) pollution caused by electronic devices. MXenes (i.e., two-dimensional (2D) transition metal carbide/nitride), an emerging family of 2D nanomaterials, demonstrate superiority to conventional nanomaterials, such as tunable electrical conductivity, unique layer structure, abundant terminal groups, and great physico-chemical properties, becoming potential candidate materials for high-efficiency MA. By hybridizing MXenes with other lossy mediums and designing novel microstructures, MA properties can be further optimized and enhanced for practical applications. Furthermore, MXene-based materials, with smartly designed multi-functionality, become a research priority to develop new or advanced applications for the coming "intelligent era". This review focuses on using MXenes to effectively absorb EMW energy. In the first part, the fabricating methods of MXenes are systematically introduced followed by a second part on the progress of MXene-based materials regarding the MA performances, as well as a summarization on their next-generation smart multifunctional materials. In the final part, opinions on the future perspectives and opportunities of MXene-based MA materials are presented. It is believed that this review will pave the way for further flourishing the development of MXene-based materials in MA field. [ABSTRACT FROM AUTHOR]

Saline–alkali soil seriously inhibits crop growth and yields and threatens the sustainable development of agriculture. Corn straw compost can alleviate saline–alkali stress and improve crop growth and development. In this study, we demonstrate that corn straw compost (CSC) improved soil physicochemical properties, e.g., decreased pH and electrical conductivity (EC), but increased soil nutrients, e.g., available nitrogen and phosphorus, and soluble organic carbon, as well as activities of sucrase and urease in saline–alkali soil. CSC affected the structure of water-stable aggregates (WSA) and the composition of soil microflora in saline–alkali soil. With the increase in the content of CSC, the abundances of some genera, e.g., Thermobacillus, Thermopolyspora, and Thermobispora, were significantly increased, suggesting that they play an important role in improving soil nutrient components and physicochemical properties, which subsequently improved plant growth and development. Consequently, the biomass and yields of rice grown in saline–alkali soil were greatly improved. In conclusion, CSC can improve saline–alkali soil activities and microbial communities, thus improving crop growth and yields. Our findings provide a theoretical basis for the sustainable development of modern agriculture. [ABSTRACT FROM AUTHOR]

Soil saline–alkalization inhibits plant growth and development and seriously affects crop yields. Over their long-term evolution, plants have formed complex stress response systems to maintain species continuity. R2R3-MYB transcription factors are one of the largest transcription factor families in plants, widely involved in plant growth and development, metabolism, and stress response. Quinoa (Chenopodium quinoa Willd.), as a crop with high nutritional value, is tolerant to various biotic and abiotic stress. In this study, we identified 65 R2R3-MYB genes in quinoa, which are divided into 26 subfamilies. In addition, we analyzed the evolutionary relationships, protein physicochemical properties, conserved domains and motifs, gene structure, and cis-regulatory elements of CqR2R3-MYB family members. To investigate the roles of CqR2R3-MYB transcription factors in abiotic stress response, we performed transcriptome analysis to figure out the expression file of CqR2R3-MYB genes under saline–alkali stress. The results indicate that the expression of the six CqMYB2R genes was altered significantly in quinoa leaves that had undergone saline–alkali stress. Subcellular localization and transcriptional activation activity analysis revealed that CqMYB2R09, CqMYB2R16, CqMYB2R25, and CqMYB2R62, whose Arabidopsis homologues are involved in salt stress response, are localized in the nucleus and exhibit transcriptional activation activity. Our study provides basic information and effective clues for further functional investigation of CqR2R3-MYB transcription factors in quinoa. [ABSTRACT FROM AUTHOR]

The cellulosome of Ruminiclostridium thermocellum was one of the most efficient cellulase systems in nature. However, the product of cellulose degradation by R. thermocellum is cellobiose, which leads to the feedback inhibition of cellulosome, and it limits the R. thermocellum application in the field of cellulosic biomass consolidated bioprocessing (CBP) industry. In a previous study, R. thermocellum M3, which can hydrolyze cellulosic feedstocks into monosaccharides, was isolated from horse manure. In this study, the complete genome of R. thermocellum M3 was sequenced and assembled. The genome of R. thermocellum M3 was compared with the other R. thermocellum to reveal the mechanism of cellulosic saccharification by R. thermocellum M3. In addition, we predicted the key genes for the elimination of feedback inhibition of cellobiose in R. thermocellum. The results indicated that the whole genome sequence of R. thermocellum M3 consisted of 3.6 Mb of chromosomes with a 38.9% of GC%. To be specific, eight gene islands and 271 carbohydrate-active enzyme-encoded proteins were detected. Moreover, the results of gene function annotation showed that 2,071, 2,120, and 1,246 genes were annotated into the Clusters of Orthologous Groups (COG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively, and most of the genes were involved in carbohydrate metabolism and enzymatic catalysis. Different from other R. thermocellum, strain M3 has three proteins related to β-glucosidase, and the cellobiose hydrolysis was enhanced by the synergy of gene BglA and BglX. Meanwhile, the GH42 family, CBM36 family, and AA8 family might participate in cellobiose degradation. [ABSTRACT FROM AUTHOR]

Alloy-based catalysts with high corrosion resistance and less self-aggregation are essential for oxygen reduction/evolution reactions (ORR/OER). Here, via an in situ growth strategy, NiCo alloy-inserted nitrogen-doped carbon nanotubes were assembled on a three-dimensional hollow nanosphere (NiCo@NCNTs/HN) using dicyandiamide. NiCo@NCNTs/HN exhibited better ORR activity (half-wave potential (E1/2) of 0.87 V) and stability (E1/2 shift of only −13 mV after 5000 cycles) than commercial Pt/C. NiCo@NCNTs/HN displayed a lower OER overpotential (330 mV) than RuO2 (390 mV). The NiCo@NCNTs/HN-assembled zinc–air battery exhibited high specific-capacity (847.01 mA h g−1) and cycling-stability (291 h). Synergies between NiCo alloys and NCNTs facilitated the charge transfer to promote 4e− ORR/OER kinetics. The carbon skeleton inhibited the corrosion of NiCo alloys from surface to subsurface, while inner cavities of CNTs confined particle growth and the aggregation of NiCo alloys to stabilize bifunctional activity. This provides a viable strategy for the design of alloy-based catalysts with confined grain-size and good structural/catalytic stabilities in oxygen electrocatalysis. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to explore an effective 124I labeling strategy and improve the signal-to-noise ratio when evaluating the expression of PD-L1 using an 124I-iodinated durvalumab (durva) F(ab')2 fragment. Methods: The prepared durva F(ab')2 fragments were incubated with N-succinimidyl-3-(4-hydroxyphenyl) propionate (SHPP); after purification, the HPP-durva F(ab')2 was iodinated using Iodo-Gen method. After the radiochemical purity, stability, and specific activities were determined, the binding affinities of probes prepared using different labeling strategies were compared in vitro. The clinical application value of [124I]I-HPP-durva-F(ab')2 was confirmed by PET imaging. To more objectively evaluate the in vivo distribution and clearance of tracers, the pharmacokinetics and biodistribution assays were also performed. Results: After being modified with SHPP, the average conjugation number of SHPP per durva-F(ab')2 identified by LC–MS was about 8.92 ± 2.84. The prepared [124I]I-HPP-durva F(ab')2 was obtained with a satisfactory radiochemical purity of more than 98% and stability of more than 93% when incubated for 72 h. Compared with unmodified [124I]I-durva F(ab')2, the specific activity of [124I]I-HPP-durva-F(ab')2 was improved (52.91 ± 5.55 MBq/mg and 15.91 ± 0.74 MBq/mg), while the affinity did not significantly change. The biodistribution experiments and PET imaging showed that the prepared [124I]I-HPP-durva-F(ab')2 exhibited an accelerated clearance and improved tumor-to-background ratio compared with [124I]I-durva-F(ab')2. The specificity of [124I]I-HPP-durva-F(ab')2 to PD-L1 was well demonstrated both in vitro and in vivo. Conclusions: A PD-L1 PET imaging probe [124I]I-HPP-durva F(ab')2 was successfully synthesized through the SHPP modification strategy. The prepared probe was able to accurately evaluate the PD-L1 expression level through high-contrast noninvasive imaging. [ABSTRACT FROM AUTHOR]

Saline-alkali stress seriously affects the yield and quality of crops, threatening food security and ecological security. Improving saline-alkali land and increasing effective cultivated land are conducive to sustainable agricultural development. Trehalose, a nonreducing disaccharide, is closely related to plant growth and development and stress response. Trehalose 6-phosphate synthase (TPS) and trehalose-6-phosphate phosphatase (TPP) are key enzymes catalyzing trehalose biosynthesis. To elucidate the effects of long-term saline-alkali stress on trehalose synthesis and metabolism, we conducted an integrated transcriptome and metabolome analysis. As a result, 13 TPS and 11 TPP genes were identified in quinoa (Chenopodium quinoa Willd.) and were named CqTPS1-13 and CqTPP1-11 according to the order of their Gene IDs. Through phylogenetic analysis, the CqTPS family is divided into two classes, and the CqTPP family is divided into three classes. Analyses of physicochemical properties, gene structures, conservative domains and motifs in the proteins, and cis-regulatory elements, as well as evolutionary relationships, indicate that the TPS and TPP family characteristics are highly conserved in quinoa. Transcriptome and metabolome analyses of the sucrose and starch metabolism pathway in leaves undergoing saline-alkali stress indicate that CqTPP and Class II CqTPS genes are involved in the stress response. Moreover, the accumulation of some metabolites and the expression of many regulatory genes in the trehalose biosynthesis pathway changed significantly, suggesting the metabolic process is important for the saline-alkali stress response in quinoa. [ABSTRACT FROM AUTHOR]

Systemic inflammation plays a central role in the pathophysiology of psoriasis. This study examined accessible systemic inflammatory markers in patients with psoriasis vulgaris and psoriatic arthritis. We aimed to evaluate their association with psoriasis severity, the presence of arthritis, and drug continuation rates. The findings revealed that neutrophil, monocyte, and platelet count, neutrophil/lymphocyte ratio, monocyte/lymphocyte ratio, systemic inflammation response index, systemic immune/inflammation index (SII), and CRP were positively correlated with Psoriasis Area and Severity Index scores. Patients presenting with higher platelet/lymphocyte ratio (PLR) or CRP values were more likely to be diagnosed with psoriatic arthritis than with psoriasis vulgaris in the multivariate regression analysis. Importantly, patients with higher pretreatment neutrophil or platelet count, PLR, and SII were associated with lower treatment continuation rates of conventional systemic agents. Higher pretreatment scores of systemic inflammatory markers did not affect treatment retention rates of biologics. These findings suggest that several accessible systemic inflammatory markers may effectively assess underlying systemic inflammation and may provide an indication for a therapeutic approach in patients with psoriasis vulgaris and psoriatic arthritis. [ABSTRACT FROM AUTHOR]

With the rapid development of hyperspectral imaging technology, object tracking in hyperspectral video has become a research hotspot. Real-time object tracking for hyperspectral video is a great challenge. We propose a fast hyperspectral object tracking method via a channel selection strategy to improve the tracking speed significantly. First, we design a strategy of channel selection to select few candidate channels from many hyperspectral video channels, and then send the candidates to the subsequent background-aware correlation filter (BACF) tracking framework. In addition, we consider the importance of local and global spectral information in feature extraction, and further improve the BACF tracker to ensure high tracking accuracy. In the experiments carried out in this study, the proposed method was verified and the best performance was achieved on the publicly available hyperspectral dataset of the WHISPERS Hyperspectral Objecting Tracking Challenge. Our method was superior to state-of-the-art RGB-based and hyperspectral trackers, in terms of both the area under the curve (AUC) and DP@20pixels. The tracking speed of our method reached 21.9 FPS, which is much faster than that of the current most advanced hyperspectral trackers. [ABSTRACT FROM AUTHOR]

We explored a new artificial intelligence-assisted method to assist junior ultrasonographers in improving the diagnostic performance of uterine fibroids and further compared it with senior ultrasonographers to confirm the effectiveness and feasibility of the artificial intelligence method. In this retrospective study, we collected a total of 3870 ultrasound images from 667 patients with a mean age of 42.45 years ± 6.23 [SD] for those who received a pathologically confirmed diagnosis of uterine fibroids and 570 women with a mean age of 39.24 years ± 5.32 [SD] without uterine lesions from Shunde Hospital of Southern Medical University between 2015 and 2020. The DCNN model was trained and developed on the training dataset (2706 images) and internal validation dataset (676 images). To evaluate the performance of the model on the external validation dataset (488 images), we assessed the diagnostic performance of the DCNN with ultrasonographers possessing different levels of seniority. The DCNN model aided the junior ultrasonographers (Averaged) in diagnosing uterine fibroids with higher accuracy (94.72% vs. 86.63%, P < 0.001), sensitivity (92.82% vs. 83.21%, P = 0.001), specificity (97.05% vs. 90.80%, P = 0.009), positive predictive value (97.45% vs. 91.68%, P = 0.007), and negative predictive value (91.73% vs. 81.61%, P = 0.001) than they achieved alone. Their ability was comparable to that of senior ultrasonographers (Averaged) in terms of accuracy (94.72% vs. 95.24%, P = 0.66), sensitivity (92.82% vs. 93.66%, P = 0.73), specificity (97.05% vs. 97.16%, P = 0.79), positive predictive value (97.45% vs. 97.57%, P = 0.77), and negative predictive value (91.73% vs. 92.63%, P = 0.75). The DCNN-assisted strategy can considerably improve the uterine fibroid diagnosis performance of junior ultrasonographers to make them more comparable to senior ultrasonographers. [ABSTRACT FROM AUTHOR]

We explored a new artificial intelligence-assisted method to assist junior ultrasonographers in improving the diagnostic performance of uterine fibroids and further compared it with senior ultrasonographers to confirm the effectiveness and feasibility of the artificial intelligence method. In this retrospective study, we collected a total of 3870 ultrasound images from 667 patients with a mean age of 42.45 years ± 6.23 [SD] for those who received a pathologically confirmed diagnosis of uterine fibroids and 570 women with a mean age of 39.24 years ± 5.32 [SD] without uterine lesions from Shunde Hospital of Southern Medical University between 2015 and 2020. The DCNN model was trained and developed on the training dataset (2706 images) and internal validation dataset (676 images). To evaluate the performance of the model on the external validation dataset (488 images), we assessed the diagnostic performance of the DCNN with ultrasonographers possessing different levels of seniority. The DCNN model aided the junior ultrasonographers (Averaged) in diagnosing uterine fibroids with higher accuracy (94.72% vs. 86.63%, P < 0.001), sensitivity (92.82% vs. 83.21%, P = 0.001), specificity (97.05% vs. 90.80%, P = 0.009), positive predictive value (97.45% vs. 91.68%, P = 0.007), and negative predictive value (91.73% vs. 81.61%, P = 0.001) than they achieved alone. Their ability was comparable to that of senior ultrasonographers (Averaged) in terms of accuracy (94.72% vs. 95.24%, P = 0.66), sensitivity (92.82% vs. 93.66%, P = 0.73), specificity (97.05% vs. 97.16%, P = 0.79), positive predictive value (97.45% vs. 97.57%, P = 0.77), and negative predictive value (91.73% vs. 92.63%, P = 0.75). The DCNN-assisted strategy can considerably improve the uterine fibroid diagnosis performance of junior ultrasonographers to make them more comparable to senior ultrasonographers. [ABSTRACT FROM AUTHOR]

External magnetic field assisted laser welding (MALW) is proved to be effective in improving welding stability, inhibiting welding defects and enhancing mechanical properties. Large numbers of researches are focusing on this technology and aiming at revealing the mechanisms and effects of magnetic field on molten pool dynamics, weld appearances and microstructures. The MALW is an advanced welding method being potential for industrial extension due to its flexible and cost-effective features. However, a comprehensive summarization on recent researches and the latest achievements is lacking. This review is significant in developing advanced welding techniques and promoting application of magnetic field in materials processing. This paper reviews the recent progress of magnetic field assisted laser welding in three aspects: (i) Mechanisms, the fundamental interaction mechanisms between magnetic field and fluid flow basing on magnetohydrodynamics (MHD); (ii) Technologies, the technologies developed basing on magnetic field assisted laser welding; (iii) Effects, the effects of magnetic fields on defects, microstructures and properties. Finally, the main conclusions of current researches and potential prospects are discussed to supply useful directions for future exploration in related fields. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa) is one of the most important crops grown worldwide, and saline–alkali stress seriously affects the yield and quality of rice. It is imperative to elucidate the molecular mechanisms underlying rice response to saline–alkali stress. In this study, we conducted an integrated analysis of the transcriptome and metabolome to elucidate the effects of long-term saline–alkali stress on rice. High saline–alkali stress (pH > 9.5) induced significant changes in gene expression and metabolites, including 9347 differentially expressed genes (DEGs) and 693 differentially accumulated metabolites (DAMs). Among the DAMs, lipids and amino acids accumulation were greatly enhanced. The pathways of the ABC transporter, amino acid biosynthesis and metabolism, glyoxylate and dicarboxylate metabolism, glutathione metabolism, TCA cycle, and linoleic acid metabolism, etc., were significantly enriched with DEGs and DAMs. These results suggest that the metabolites and pathways play important roles in rice's response to high saline–alkali stress. Our study deepens the understanding of mechanisms response to saline–alkali stress and provides references for molecular design breeding of saline–alkali resistant rice. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. In this paper, we propose to employ unmanned aerial vehicles (UAVs) to assist the clustered IoT data collection with blockchain-based security provisioning. In particular, the UAVs generate candidate blocks based on the collected data, which are then audited through a lightweight proof-of-stake consensus mechanism within the UAV-based blockchain network. To motivate efficient blockchain while reducing the operational cost, a stake pool is constructed at the active UAV while encouraging stake investment from other UAVs with profit sharing. The problem is formulated to maximize the overall profit through the blockchain system in unit time by jointly investigating the IoT transmission, incentives through investment and profit-sharing, and UAV deployment strategies. Then, the problem is solved in a distributed manner while being decoupled into two layers. The inner layer incorporates IoT transmission and incentive design, which are tackled with large-system approximation and one-leader-multi-follower Stackelberg game analysis, respectively. The outer layer for UAV deployment is undertaken with a multi-agent deep deterministic policy gradient approach. Results show the convergence of the proposed learning process and the UAV deployment, and also demonstrated the performance superiority of our proposal as compared with the baselines. [ABSTRACT FROM AUTHOR]

The residues of pharmaceutical compounds such as nonsteroidal anti-inflammatory drugs in aquatic environments are a matter of global concern because they may pose deleterious risks to human health and ecosystems. In this study, a novel composite was prepared by grafting ionic liquid hypercrosslinked polymer onto the surface of the melamine sponge skeleton. The resultant hypercrosslinked polymer@sponge was characterized using SEM, BET, FT-IR, TG-DSC, XPS, and a zeta potential analyzer. The composite can provide strong ion exchange sites and multiple interactions, which had a strong interaction with the target NSAIDs. The adsorption conditions, including pH, extraction time, salt concentration, and initial concentration of the drugs, were systematically optimized to obtain the maximum removal efficiency. Studies revealed that the prepared IL-HCPs@MS had a strong affinity for NSAIDs, particularly for diclofenac and ketoprofen. The adsorption isotherms and kinetics data of both these IL-HCPs@MS were in alignment with the Langmuir model (R2 > 0.98) and the pseudo-second-order model (R2 > 0.99), respectively. The results showed the removal of NSAIDs by the HCPs@MS was mainly based on the chemisorption process, monolayer adsorption with an endothermic mechanism, and an enthalpy-driven process. The composite will be a promising sorbent with potential applications in water environment remediation. [ABSTRACT FROM AUTHOR]