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A series of quinoxalinone-1,2,3-triazole derivatives have been synthesized and tested for antifungal activity against phytopathogenic fungus through mycelial growth inhibition in vitro, spore germination inhibition in vitro and control effect in vivo. The results showed that the pharmacophore quinoxalinone and 1,2,3-triazole displayed promising antifungal activity. The EC50 value against C. gloeosporioides of 6a-1 was 1.17 μg/mL and the compound 6c-1 showed the good bioactivity against C. fragariae Brooks and P. oryzae Cav., displaying EC50 values of 5.56, 4.62 μg/mL, respectively. The inhibitory of spore germination by 6a-1 was performed with EC50 value of 1.91 μg/mL. In addition, the in vivo bioassay indicated that 6a-1 possessed effective control against Pepper Anthrax Disease in protective treatment. For given activity data of target compounds, structure-activity relationship (SAR) study was operated, hoping for optimizing the target structure to find lead compound with higher activity.

Abstract Septic cardiomyopathy is one of the most severe and common complications in patients with sepsis and poses a great threat to their prognosis. However, the potential mechanisms and effective therapeutic drugs need to be explored. The control of cardiac cell death by miRNAs has emerged as a prominent area of scientific interest in the diagnosis and treatment of heart disorders in recent times. In the present investigation, we discovered that overexpression of miR-31-5p prevented LPS-induced damage to H9C2 cells and that miR-31-5p could inhibit BAP1 production by binding to its 3’-UTR. BRCA1-Associated Protein 1 (BAP1) is a ubiquitin carboxy-terminal hydrolase. BAP1 upregulation blocked effect of miR-31-5p on H9C2 cell injury. Moreover, BAP1 inhibited the expression of solute carrier family 7 member 11 (SLC7A11) by deubiquitinating histone 2 A (H2Aub) on the promoter of SLC7A11. Furthermore, overexpression of miR-31-5p and downregulation of BAP1 inhibited SLC7A11 mediated ferroptosis. In addition, the downregulation of SLC7A11 reversed the inhibitory effect of miR-31-5p on the expression of myocardial injury and inflammatory factors, and cell apoptosis was reversed. In conclusion, these results indicate that miR-31-5p alleviates malignant development of LPS-induced H9C2 cell injury by targeting BAP1 and regulating SLC7A11 deubiquitination-mediated ferroptosis, which confirmed the protective effect of miR-31-5p on H9C2 cell injury and revealed potential mechanisms that may provide new targets for treatment of septic cardiomyopathy.

Karst landscapes, characterized by unique soluble geological features, provide essential ecosystem services (ESs). However, they are currently facing significant challenges due to rapid land use/land cover (LULC) changes. Research that combines LULC and karst lithological features with ecosystem service bundles (ESBs) is scarce. Therefore, this study aimed to investigate the future spatial distributions and landscape pattern features of ESBs in different lithological areas based on land use projections, and providing a basis for informing zoning land use planning and management. Firstly, multiple scenario simulations were conducted to project future land use changes in Huanjiang County, China. Next, based on the assessments of ESs and identification of ESBs, the correlations between LULC, ESBs, and landscape features in different lithological areas were explored. The results revealed the following: (1) a potential synergistic relationship between built-up land and ESB3, while a negative impact of transitioning from forest to cropland on ESB2; (2) the limestone area exhibited the highest overall split level of ESBs, while the non-karst area showed the greatest diversity, evenness, cohesion, and largest patches of ESBs; (3) the landscape heterogeneity of ESBs in different lithological areas was mainly reflected in split, cohesion, and division levels rather than aggregation. Finally, implications and site-specific suggestions for zoning land use planning and management in Huanjiang County were discussed.

Abstract Mitochondria are important for the activation of endothelial cells and the process of angiogenesis. NDUFS8 (NADH:ubiquinone oxidoreductase core subunit S8) is a protein that plays a critical role in the function of mitochondrial Complex I. We aimed to investigate the potential involvement of NDUFS8 in angiogenesis. In human umbilical vein endothelial cells (HUVECs) and other endothelial cell types, we employed viral shRNA to silence NDUFS8 or employed the CRISPR/Cas9 method to knockout (KO) it, resulting in impaired mitochondrial functions in the endothelial cells, causing reduction in mitochondrial oxygen consumption and Complex I activity, decreased ATP production, mitochondrial depolarization, increased oxidative stress and reactive oxygen species (ROS) production, and enhanced lipid oxidation. Significantly, NDUFS8 silencing or KO hindered cell proliferation, migration, and capillary tube formation in cultured endothelial cells. In addition, there was a moderate increase in apoptosis within NDUFS8-depleted endothelial cells. Conversely, ectopic overexpression of NDUFS8 demonstrated a pro-angiogenic impact, enhancing cell proliferation, migration, and capillary tube formation in HUVECs and other endothelial cells. NDUFS8 is pivotal for Akt-mTOR cascade activation in endothelial cells. Depleting NDUFS8 inhibited Akt-mTOR activation, reversible with exogenous ATP in HUVECs. Conversely, NDUFS8 overexpression boosted Akt-mTOR activation. Furthermore, the inhibitory effects of NDUFS8 knockdown on cell proliferation, migration, and capillary tube formation were rescued by Akt re-activation via a constitutively-active Akt1. In vivo experiments using an endothelial-specific NDUFS8 shRNA adeno-associated virus (AAV), administered via intravitreous injection, revealed that endothelial knockdown of NDUFS8 inhibited retinal angiogenesis. ATP reduction, oxidative stress, and enhanced lipid oxidation were detected in mouse retinal tissues with endothelial knockdown of NDUFS8. Lastly, we observed an increase in NDUFS8 expression in retinal proliferative membrane tissues obtained from human patients with proliferative diabetic retinopathy. Our findings underscore the essential role of the mitochondrial protein NDUFS8 in regulating endothelial cell activation and angiogenesis.

【Objective】High-quality flue-cured tobacco varieties are important guarantees for showcasing the quality characteristics of tobacco producing areas. Exploring the differences in nitrogen metabolism and carotenoid metabolism characteristics between high-quality flue-cured tobacco varieties and conventional main varieties during the field growth period in Jiangxi tobacco region, and analyzing the common physiological metabolism characteristics of high-quality flue-cured tobacco varieties can provide theoretical and technical support for in-depth exploration of variety characteristics and optimization of variety matching cultivation techniques.【Method】The Minyan 312, Minyan 12 with good sensory quality and the conventional variety of Yunyan 87 (CK) were used as materials. The changes in the contents of related substances and gene expression levels in middle leaves of different varieties during key growth periods were analyzed.【Result】In terms of carotenoid metabolism, the contents of lutein and β-carotene in Minyan 312 and Minyan 12 were 3.27-6.14 mg/g and 0.67-1.59 mg/g respectively during the budding stage to foot leaf mature period, which were significantly lower than those in Yunyan 87. However, the contents of lutein in the middle leaf maturity of the two varieties were 2.31 mg/g and 2.58 mg/g, respectively, which were significantly higher than those in Yunyan 87 (0.17 mg/g and 0.44 mg/g). The peak expression of carotenoid synthesis-related genes mainly occurred in the vigorous growing period to budding stage. The relative expression of PSY and other carotenoid synthesis-related genes in Minyan 312 and Minyan 12 were higher than those in Yunyan 87 before the maturity of waist leaf, with a maximum difference of 2.53. In terms of nitrogen metabolism, the total nitrogen content (1.58%-3.36%) and protein content (7.14%-14.81%) in Minyan 312 and Minyan 12 were significantly lower than those in Yunyan 87 during the budding stage to foot leaf mature period. The expression levels of NR, NIR1 and GS1-5 genes in Minyan 312 and Minyan 12 were higher than those in Yunyan 87 during the vigorous growing period to foot leaf mature period, while the expression levels of GS1-5 genes were lower during the waist leaf mature period. In terms of correlation analysis, there was a significant or extremely significant positive correlation between NIRI, GS1-5, PSY, CRTISO and other genes, lutein and β-carotene.【Conclusion】There was a significant correlation between nitrogen metabolism and carotenoid metabolism. Compared with Yunyan 87, the middle leaves of high-quality flue-cured tobaccos Minyan 312 and Minyan 12 exhibited stronger activity of carotenoid synthesis related genes before maturity and higher lutein content during maturity in terms of carotenoid metabolism. In addition, the Minyan 312 and Minyan 12 had higher nitrogen absorption and assimilation ability before maturity, and had lower nitrogen utilization ability at maturity in terms of nitrogen metabolism.

Abstract Using Challenging Minisatellite Payload (CHAMP) observations, responses of ionospheric radial current (IRC) in F‐layer to sawtooth substorms in different magnetic local times are investigated. The zonal wind effect alone cannot entirely explain the variability of the substorm time disturbance IRC. When substorms commence amid stable southward interplanetary magnetic field (IMF), it induces an eastward (westward) equatorial electric field in the daytime (nighttime). This electric field induces an equatorward (poleward) Hall current at low latitudes, consequently generating an upward (downward) perturbation in IRC. Conversely, substorms with varying IMF Bz, where IMF is southward but with a reduced magnitude or turned north after the onset, induce a westward (eastward) equatorial electric field in the daytime (nighttime). This electric field induces a poleward (equatorward) Hall current at low latitudes, consequently generating a downward (upward) disturbed IRC. Notably, this effect is primarily attributed to the varying IMF Bz rather than solely to substorm onset.

Resumo Fundamento: O antibiótico quimioterápico antraciclina doxorrubicina (DOX) pode induzir cardiotoxicidade cumulativa e levar à disfunção cardíaca. RNAs não codificantes longos (lncRNAs) podem funcionar como importantes reguladores na lesão miocárdica induzida por DOX. Objetivo: Este estudo tem como objetivo investigar o papel funcional e o mecanismo molecular do RNA antisense lncRNA OXCT1 1 (OXCT1-AS1) na lesão celular miocárdica induzida por DOX in vitro. Métodos: Cardiomiócitos humanos (AC16) foram estimulados com DOX para induzir um modelo de lesão celular miocárdica. A expressão de OXCT1-AS1, miR-874-3p e BDH1 em células AC16 foi determinada por RT-qPCR. A viabilidade das células AC16 foi medida pelo ensaio XTT. A citometria de fluxo foi empregada para avaliar a apoptose de células AC16. Western blotting foi utilizado para avaliar os níveis proteicos de marcadores relacionados à apoptose. O ensaio repórter de luciferase dupla foi conduzido para verificar a capacidade de ligação entre miR-874-3p e OXCT1-AS1 e entre miR-874-3p e BDH1. O valor de p

The Spin-Exchange Relaxation-Free (SERF) atomic magnetometers play an increasingly significant roles in cardiac and brain magnetometry fields, etc. For the SERF atomic magnetometer, the evolution and interaction with the magnetic field of atomic spins can be described by the Bloch equation. However, the traditional Bloch equation does not take into account the transport phenomena caused by the atomic density gradient within the vapor cell, which makes it unable to accurately reflect the polarization distribution in the vapor cell, thereby reducing the accuracy of magnetic field measurement. To achieve a more accurate representation of the evolution characteristics of the spatial distribution of the atomic ensemble, a diffusion term for the polarization strength is introduced into the Bloch equation. Furthermore, a new unsupervised Physics-Informed Neural Network (PINN) model with lightweight self-attention (LSA) module is proposed to solve the modified nonlinear equation. The introduction of LSA enhances the adaptive representational capability of PINN, enabling it to more effectively extract global features and consequently obtain more accurate numerical solutions of the Bloch equation. The experimental results show that LSA-PINN achieves a minimum loss value of 3.98×10-2, which is 62 % lower than the traditional PINN. This study provides new insights and methods to address the limitations of traditional Bloch equation and gain a deeper understanding of system behavior.

Hydrogels have emerged as a focal point of research in the biomedical field due to their applications in tissue repair. However, the majority of hydrogels lack the capability to release oxygen, constraining their therapeutic outcomes in environments with hypoxic tissues. In recent years, oxygen‐releasing hydrogels have garnered extensive attention in the field of tissue engineering, owing to their ability to modulate oxygen release and meet the diverse oxygenation requirements of various tissues. These hydrogels can enhance repair efficiency and promote tissue regeneration in hypoxic tissue environments. The design of oxygen‐releasing hydrogels primarily involves the utilization of diverse oxygen sources, such as algae, perfluorocarbons, and peroxides, to achieve optimal tissue oxygenation. This review provides a comprehensive summary of the design and fabrication strategies of oxygen‐releasing hydrogels, discusses deeply into their underlying oxygen‐releasing mechanisms, and their myriad applications in tissue repair along with the prospective challenges.

Effusion cooling is often regarded as one of the critical techniques to protect solid surfaces from exposure to extremely hot environments, such as inside a combustion chamber where temperature can well exceed the metal melting point. Designing such efficient cooling features relies on thorough understanding of the underlying flow physics for the given engineering scenarios, where physical testing may not be feasible or even possible. Inevitably, under these circumstances, modelling and numerical simulation become the primary predictive tools. This review aims to give a broad coverage of the numerical methods for effusion cooling, ranging from the empirical models (often based on first principles and conservation laws) for solving the Reynolds-Averaged Navier–Stokes (RANS) equations to higher-fidelity methods such as Large-Eddy Simulation (LES) and hybrid RANS-LES, including Detached-Eddy Simulation (DES). We also highlight the latest progress in machine learning-aided and data-driven RANS approaches, which have gained a lot of momentum recently. They, in turn, take advantage of the higher-fidelity eddy-resolving datasets performed by, for example, LES or DES. The main examples of this review are focused on the applications primarily related to internal flows of gas turbine engines.

The prolonged utilization of copper (Cu)-containing fungicides results in Cu accumulation and affects soil ecological health. Thus, a pot experiment was conducted using Citrus reticulata cv. Shatangju with five Cu levels (38, 108, 178, 318, and 388 mg kg−1) to evaluate the impacts of the soil microbial processes, chemistry properties, and citrus growth. These results revealed that, with the soil Cu levels increased, the soil total Cu (TCu), available Cu (ACu), organic matter (SOM), available potassium (AK), and pH increased while the soil available phosphorus (AP) and alkali-hydrolyzable nitrogen (AN) decreased. Moreover, the soil extracellular enzyme activities related to C and P metabolism decreased while the enzymes related to N metabolism increased, and the expression of soil genes involved in C, N, and P cycling was regulated. Moreover, it was observed that tolerant microorganisms (e.g., p_Proteobacteria, p_Actinobacteria, g_Lysobacter, g_Sphingobium, f_Aspergillaceae, and g_Penicillium) were enriched but sensitive taxa (p_Myxococcota) were suppressed in the citrus rhizosphere. The citrus biomass was mainly positively correlated with soil AN and AP; plant N and P were mainly positively correlated with soil AP, AN, and acid phosphatase (ACP); and plant K was mainly negatively related with soil β−glucosidase (βG) and positively related with the soil fungal Shannon index. The dominant bacterial taxa p_Actinobacteriota presented positively correlated with the plant biomass and plant N, P, and K and was negatively correlated with plant Cu. The dominant fungal taxa p_Ascomycota was positively related to plant Cu but negatively with the plant biomass and plant N, P, and K. Notably, arbuscular mycorrhizal fungi (p_Glomeromycota) were positively related with plant P below soil Cu 108 mg kg−1, and pathogenic fungi (p_Mortierellomycota) was negatively correlated with plant K above soil Cu 178 mg kg−1. These findings provided a new perspective on soil microbes and chemistry properties and the healthy development of the citrus industry at increasing soil Cu levels.

The recently introduced complex-valued convolutional neural network (CV-CNN) has shown considerable advancements for polarimetric synthetic aperture radar (PolSAR) image classification by effectively incorporating both magnitude and phase information. However, a solitary 2D or 3D CNN encounters challenges such as insufficiently extracting scattering channel dimension features or excessive computational parameters. Moreover, these networks’ default is that all information is equally important, consuming vast resources for processing useless information. To address these issues, this study presents a new hybrid CV-CNN with the attention mechanism (CV-2D/3D-CNN-AM) to classify PolSAR ground objects, possessing both excellent computational efficiency and feature extraction capability. In the proposed framework, multi-level discriminative features are extracted from preprocessed data through hybrid networks in the complex domain, along with a special attention block to filter the feature importance from both spatial and channel dimensions. Experimental results performed on three PolSAR datasets demonstrate our present approach’s superiority over other existing ones. Furthermore, ablation experiments confirm the validity of each module, highlighting our model’s robustness and effectiveness.

Straw and biochar, two commonly used soil amendments, have been shown to enhance soil fertility and the composition of microbial communities. To compare the effects of straw and biochar on soil fertility, particularly focusing on soil dissolved organic matter (DOM) components, and the physiochemical properties of soil and microbial communities, a combination of high-throughput sequencing and three-dimensional fluorescence mapping technology was employed. In our study, we set up four treatments, i.e., without biochar and straw (B0S0); biochar only (B1S0); straw returning only (B0S1); and biochar and straw (B1S1). Our results demonstrate that soil organic matter (SOM), available nitrogen (AN), and available potassium (AK) were increased by 34.71%, 22.96%, and 61.68%, respectively, under the B1S1 treatment compared to the B0S0 treatment. In addition, microbial carbon (MBC), dissolved organic carbon (DOC), and particulate organic carbon (POC) were significantly increased with the B1S1 treatment, by 55.13%, 15.59%, and 125.46%, respectively. The results also show an enhancement in microbial diversity, the composition of microbial communities, and the degree of soil humification with the application of biochar and straw. Moreover, by comparing the differences in soil fertility, DOM components, and other indicators under different treatments, the combined treatments of biochar and straw had a more significant positive impact on paddy soil fertility compared to biochar. In conclusion, our study revealed the combination of straw incorporation and biochar application has significant impacts and is considered an effective approach to improving soil fertility.

Straw return utilizes waste resources to reduce the use of chemical fertilizers worldwide. However, information is still lacking on the relative impact of straw return on soil fertility, the nutrient composition of different soil aggregates, and soil microbial communities. Therefore, this study aimed to understand the effects of different management practices on the crop yield, soil fertility, and soil community composition in a 14-year wheat–rice rotation system. The treatments included a control (without fertilizer and straw addition), chemical fertilization (NPK), straw return without fertilizer (S), and straw addition with chemical fertilizer (NPKS). The results showed that NPKS improved the wheat and rice yield by 185.12% and 88.02%, respectively, compared to the CK treatment. Additionally, compared to the CK treatment, the N, P, and K contents of the wheat stem were increased by 39.02%, 125%, and 20.23% under the NPKS treatment. Compared to the CK treatment, SOM, TN, TP, AN, AP, AK, CEC, AFe, AMn, ACu, and AZn were increased by 49.12%, 32.62%, 35.06%, 22.89%, 129.36%, 48.34%, 13.40%, 133.95%, 58.98%, 18.26% and 33.33% under the NPKS treatment, respectively. Moreover, straw addition promoted the creation and stabilization of macro-aggregates in crop soils. The relative abundance of macro-aggregates (0.25–2 mm) increased from 37.49% to 52.97%. Straw addition was associated with a higher proportion of aromatic and carbonyl carbon groups in the soil, which, in turn, promoted the formation of macro-aggregates. Redundancy analysis showed that straw return significantly increased the microbial community diversity. These findings demonstrate that straw addition together with chemical fertilizer could increase the crop yield by improving soil fertility, soil aggregate stability, and the diversity of fungi.

Earthworms are soil macrofauna that control soil ecosystems by strongly influencing soil nematodes, microorganisms, and nutrient cycling, as well as soil environmental factors. We have discovered an earthworm cyclic peptide that disrupts nematode DNA, affecting its lifespan, reproduction, and feeding preferences. To investigate the effects of this peptide on soil, it was added to soil, and changes in soil nematode, bacterial and fungal communities, soil nutrient contents, and basal respiration were measured on days 5 and 21. The results showed that the peptide reduced soil basal respiration on day 5 and soil NO3-N on day 21, decreased soil fungivores nematodes on day 5 and soil nematode abundance on day 21, and increased soil fungal community richness and diversity. It also altered the soil bacterial community structure between day 5 and the soil fungal community structure on days 5 and 21. The peptide regulates the soil environment by influencing the structure of soil bacterial and fungal communities through the soil nematode community, as demonstrated by partial least squares path modelling (PLS-PM) analyses. Earthworm cyclic peptides mediates tri-trophic interactions between earthworms, nematodes, microbes, and environmental factors, providing new insights into soil biota interactions and feedback in dynamic soil food webs.

Coastal levees play a role in protecting coastal areas from storm surges and high waves, and they provide important input information for inundation damage simulations. However, coastal levee data with uniformity and sufficient accuracy for inundation simulations are not always well developed. Against this background, this study proposed a method to extract coastal levees by inputting high spatial resolution optical satellite image products (RGB images, digital surface models (DSMs), and slope images that can be generated from DSM images), which have high data availability at the locations and times required for simulation, into a deep learning model. The model is based on U-Net, and post-processing for noise removal was introduced to further improve its accuracy. We also proposed a method to calculate levee height using a local maximum filter by giving DSM values to the extracted levee pixels. The validation was conducted in the coastal area of Ibaraki Prefecture in Japan as a test area. The levee mask images for training were manually created by combining these data with satellite images and Google Street View, because the levee GIS data created by the Ibaraki Prefectural Government were incomplete in some parts. First, the deep learning models were compared and evaluated, and it was shown that U-Net was more accurate than Pix2Pix and BBS-Net in identifying levees. Next, three cases of input images were evaluated: (Case 1) RGB image only, (Case 2) RGB and DSM images, and (Case 3) RGB, DSM, and slope images. Case 3 was found to be the most accurate, with an average Matthews correlation coefficient of 0.674. The effectiveness of noise removal post-processing was also demonstrated. In addition, an example of the calculation of levee heights was presented and evaluated for validity. In conclusion, this method was shown to be effective in extracting coastal levees. The evaluation of generalizability and use in actual inundation simulations are future tasks.

This study aimed to determine the optimal growth stage and additives for producing high quality millet silage through two experiments. Experiment 1: Whole-plant millet from the same field and under uniform management was harvested at the heading, sizing, milking, dough, and full-maturity stages. Then, it was chopped into 2–3 cm segments, vacuum-sealed in plastic bags without any further treatment, stored at 20 °C, and opened after 60 days. The results indicated that the dough stage had the highest water-soluble carbohydrate (WSC) and crude protein (CP) contents. The lactic acid (LA) and acetic acid (AA) contents during the dough and maturity stages were significantly higher than other stages, with the lowest pH observed during the dough stage. Experiment 2: The whole-plant millet was harvested at the dough stage. It was then chopped into 2–3 cm segments using a forage chopper, mixed thoroughly, and subjected to different treatments—inoculation with 106 CFU/g FM of Lactiplantibacillus plantarum (LP), adding of 1% FM sucrose (S), and a combination of Lactiplantibacillus plantarum and sucrose (MIX)—with a control group (CK) receiving an equivalent amount of water. The MIX treatment significantly enhanced the WSC content compared to other treatments (p < 0.05), and both the LP and MIX treatments showed superior LA and AA contents and lactic acid bacteria counts. These additives significantly altered the bacterial community, shifting dominance from Proteobacteria in the CK and raw materials to Firmicutes. Klebsiella dominated the CK group but was significantly reduced in the additive treatments, where Lentilactobacillus became the dominant genus. Therefore, we recommend harvesting millet at the dough stage and adding a mixture of Lactiplantibacillus plantarum and sugar to improve fermentation quality and aerobic stability. [ABSTRACT FROM AUTHOR]

Organic–inorganic hybrid perovskite materials have become promising photovoltaic materials due to their excellent optoelectronic properties and low-cost processing techniques. Among them, formamidine-cesium (FA-Cs) lead perovskite has attracted widespread attention because of its ability to enhance the stability of perovskite solar cells. However, large formamidinium (FA) cations cause severe micro-strain in the perovskite film, leading to defects and non-radiative recombination, which significantly impair the efficiency and long-term stability of the devices. In this study, by introducing π-conjugated molecules, such as bromobenzoic acid (BAC) additives, into the perovskite precursor solution, the micro-strain in the film was effectively relieved. Combining their π-electron conjugation at the grain boundaries of the film, they enhanced the carrier transport on the surface of the perovskite, ultimately improving the device efficiency from 22.70% to 24.02%, while also further enhancing the stability of the device. This work provides an effective approach for designing high-performance FA-Cs-based perovskite devices and offers important references for the selection and design of π-conjugated molecules. [ABSTRACT FROM AUTHOR]

In the region between two closely located stiff inclusions, the stress, which is the gradient of a solution to the Lamé system with partially infinite coefficients, may become arbitrarily large as the distance between interfacial boundaries of inclusions tends to zero. The primary aim of this paper is to give a sharp description in terms of the asymptotic behavior of the stress concentration, as the distance between interfacial boundaries of inclusions goes to zero. For that purpose, we capture all the blow‐up factor matrices, whose elements comprise of some certain integrals of the solutions in the case when two inclusions are touching. Then, we are able to establish the asymptotic formulas of the stress concentration in the presence of two close‐to‐touching m$$ m $$‐convex inclusions in all dimensions. Furthermore, an example of curvilinear squares with rounded‐off angles is also presented for future application in numerical computations and simulations. [ABSTRACT FROM AUTHOR]

Named entity recognition is a fundamental subtask for knowledge graph construction and question-answering in the agricultural diseases and pests field. Although several works have been done, the scarcity of the Chinese annotated dataset has restricted the development of agricultural diseases and pests named entity recognition(ADP-NER). To address the issues, a large-scale corpus for the Chinese ADP-NER task named AgCNER was first annotated. It mainly contains 13 categories, 206,992 entities, and 66,553 samples with 3,909,293 characters. Compared with other datasets, AgCNER maintains the best performance in terms of the number of categories, entities, samples, and characters. Moreover, this is the first publicly available corpus for the agricultural field. In addition, the agricultural language model AgBERT is also fine-tuned and released. Finally, the comprehensive experimental results showed that BiLSTM-CRF achieved F1-score of 93.58%, which would be further improved to 94.14% using BERT. The analysis from multiple aspects has verified the rationality of AgCNER and the effectiveness of AgBERT. The annotated corpus and fine-tuned language model are publicly available at https://doi.org/XXX and https://github.com/guojson/AgCNER.git. [ABSTRACT FROM AUTHOR]

Wide‐bandgap (WBG) perovskite solar cell (PSC) plays a pivotal role as the top subcell in all‐perovskite tandem solar cells (TSCs), facilitating the absorption of high‐energy photons and affording a large open‐circuit voltage (VOC). Nonetheless, the stability and efficiency of WBG PSCs are constrained by light‐induced halide segregation and non‐radiative recombination losses. In this study, this work presents an approach of utilizing 2‐methylpiperazinium bromide (2‐MePBr) via interfacial engineering to realize high‐efficiency WBG (1.77 eV) PSCs. The C─NH─C functional group in 2‐MePBr, serving as an electron donor, can interact with under‐coordinated lead defects at the perovskite surface. Consequently, the treatment with 2‐MePBr mitigates interfacial non‐radiative recombination, enhances charge transport, inhibits ion migration, and thus delivers an improved power conversion efficiency (PCE) of 19.30% with a VOC of 1.29 V, and a fill factor of 83.08%. Notably, the WBG PSCs manifest enhanced stability, preserving 80% of the initial PCE after 337 h of continuous operation under 1 sun illumination at the maximum power point. Furthermore, the all‐perovskite TSCs based on this WBG subcell achieve a PCE of 27.47%, showing its promising application in perovskite‐based tandem solar cells. [ABSTRACT FROM AUTHOR]

X-ray detection plays a vital role in medical imaging, industrial defect detection, security screening and scientific research. Direct X-ray detectors are of greater interest to researchers because they offer the advantages of faster imaging, higher resolution and simpler construction than indirect detectors. Due to their intrinsic properties, traditional materials have inherent problems that limit their performance in detector applications. Perovskite is a new material with excellent properties that has great potential in the field of X-ray detectors. This paper summaries the research progress of perovskite materials in the field of X-ray detectors. First, the problems of traditional materials are listed according to the principle and material requirements of X-ray detectors. Then, the problems and challenges of different types of perovskite materials are divided from the classification of perovskite materials, from organic to inorganic materials, and from halide perovskites to lead-free perovskites. The intention is to provide ideas for the development of more environmentally friendly and higher-performance X-ray detectors. [ABSTRACT FROM AUTHOR]

Cs3Bi2I9 (CBI) is a promising material for direct X‐ray detectors. However, for the solution method, due to the difference in the chemical potential of Cs+, Bi3+, I− ions in the solvent, the composition of CBI single crystals (SCs) prepared by the solution method often deviates from the stoichiometric ratio, resulting in the formation of many defects in the material, which degrades the quality of the SC. Herein, Br− and Cl− are used as dopants to produce CBI SCs by the top seed solution method. It can be speculated that the dopant ions can reduce the VI defects in the CBI by means of density functional theory calculations. The carrier lifetimes of CBI SCs doped with Br− and Cl− have been increased to 41.7 and 13.0 ns, respectively. Meanwhile, the defect densities of the SCs are reduced to 1.02 × 109 and 1.85 × 109 cm−3, respectively. X‐ray detectors based on Br‐doped CBI and Cl‐doped CBI SCs exhibit high X‐ray sensitivity of 23071.3 and 18525.3 μC Gyair−1 cm−2 at an electric field of 40 V mm−1, respectively. In addition, the X‐ray detection limit reaches 1.07 and 1.35 nGyairs−1 at an electric field of 2.5 V mm−1, respectively. [ABSTRACT FROM AUTHOR]

Controlling the crystallization to achieve high‐quality homogeneous perovskite film is the key strategy in developing perovskite electronic devices. Here, an in situ dynamic optical probing technique is demonstrated that can monitor the fast crystallization of perovskites and effectively minimize the influence of laser excitation during the measurement. This study finds that the typical static probing technique would damage and induce phase segregation in the perovskite films during the excitation. These issues can be effectively resolved with the dynamic probing approach. It also found that the crystallization between MAPbI3 and MAPbI2Br is strikingly different. In particular, MAPbI2Br suffers from inefficient nucleation during the spin‐coating that strongly affects the uniform crystal growth in the annealing process. The commonly used pre‐heating process is found at a lower temperature not only can further promote the nucleation but also to complete the crystallization of MAPbI2Br. The role of further annealing at a higher temperature is to facilitate ion‐dissociation on the crystal surface to form a passivation layer to stabilize the MAPbI2Br lattices. The device performance is strongly correlated with the film formation mechanism derived from the in situ results. This work demonstrates that the in situ technique can provide deep insight into the crystallization mechanism, and help to understand the growth mechanism of perovskites with different compositions and dimensionalities. [ABSTRACT FROM AUTHOR]

Background: Oocytes, the largest cells in mammals, harbor numerous mitochondria within their cytoplasm. These highly dynamic organelles are crucial for providing energy resources and serving as central regulators during oogenesis. Mitochondrial dynamics ensure proper energy distribution for various cellular processes involved in oocyte maturation. Previous studies have used alterations in mitochondrial distribution as a biomarker to assess the oocyte health. However, there are discrepancies between studies regarding mitochondrial distribution profiles in healthy oocytes. Consequently, a comprehensive mitochondrial distribution profile in oocytes during maturation has not been fully characterized. Additionally, there is a lack of objective, quantitative methods to evaluate alterations in mitochondrial distribution profiles in oocytes., Methods: This study aims to provide an in-depth overview of mitochondrial distribution profiles in mouse oocytes at different maturation stages: germinal vesicle (GV) stage, metaphase I (MI), and mature metaphase II (MII). Freshly collected mouse GV, MI and MII oocytes were stained with MitoTracker Red. Confocal microscopy was used to obtain images of mitochondrial distribution profiles in these oocytes. Using the Imaris software, we reconstructed three-dimensional (3D) surface renderings of each oocyte and quantitatively illustrated the mitochondrial distribution profiles., Results: At the GV stage, mitochondria in oocytes were evenly distributed throughout the ooplasm. As oocytes progressed to MI and MII stages, mitochondria aggregated and formed clusters, the mean size of mitochondrial clusters and the proportions of clustered mitochondria increased along with the maturation of oocytes., Conclusions: Our findings reveal that mitochondria in mouse oocytes are highly dynamic, undergoing significant reorganizations during oocyte maturation. We for the first time provided comprehensive mitochondrial distribution profiles in mouse oocytes at the GV, MI and MII stages. These mitochondrial distribution profiles were further quantitatively evaluated. Our methods provide an objective and standardized approach for evaluating alterations in mitochondrial dynamics, which can be used as biomarkers to monitor oocyte conditions during maturation., (© 2024. The Author(s).)

This study investigated the influence of co-regulation on public speaking self-efficacy in the context of collaborative oral presentations. A total of 237 students enrolled in an English course at a university in China took part in the research. The factor analysis findings revealed that learners' co-regulation in public speaking encompass five components: co-planning, co-monitoring, co-evaluation, effort regulation, and help-seeking. Public speaking self-efficacy, on the other hand, pertains to learners' confidence in aspects including the topic, language use, organization, and delivery during public speaking engagements. The path analysis demonstrated that co-planning was a significant predictor of students' self-efficacy in terms of the topic and organization. Moreover, the co-monitoring strategy exhibited direct and positive correlations with language and topic self-efficacy. Similarly, the co-evaluation strategy showed direct and positive relationships with language, delivery, and organization self-efficacy. Furthermore, both effort regulation and help-seeking strategies were found to have direct and positive impacts on organization self-efficacy. This study offers valuable implications for educators, trainers, and individuals aiming to enhance their public speaking self-efficacy in collaborative environments., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hao and Chen.)

The new shoot density of slash pine serves as a vital indicator for assessing its growth and photosynthetic capacity, while the number of new shoots offers an intuitive reflection of this density. With deep learning methods becoming increasingly popular, automated counting of new shoots has greatly improved in recent years but is still limited by tedious and expensive data collection and labeling. To resolve these issues, this paper proposes a semi-supervised counting network (MTSC-Net) for estimating the number of slash pine new shoots. First, based on the mean-teacher framework, we introduce the improved VGG19 to extract multiscale new shoot features. Second, to connect local new shoot feature information with global channel features, attention feature fusion module is introduced to achieve effective feature fusion. Finally, the new shoot density map and density probability distribution are processed in a fine-grained manner through multiscale dilated convolution of the regression head and classification head. In addition, a masked image modeling strategy is introduced to encourage the contextual understanding of global new shoot features and improve the counting performance. The experimental results show that MTSC-Net outperforms other semi-supervised counting models with labeled percentages ranging from 5% to 50%. When the labeled percentage is 5%, the mean absolute error and root mean square error are 17.71 and 25.49, respectively. These findings demonstrate that our work can be used as an efficient semi-supervised counting method to provide automated support for tree breeding and genetic utilization., Competing Interests: Competing interests: The authors declare that they have no known competing interests., (Copyright © 2024 Zhaoxu Zhang et al.)

The Cs 3 Bi 2 I 9 single crystal, as an all-inorganic non-lead perovskite, offers advantages such as stability and environmental friendliness. Its superior photoelectric properties, attributed to the absence of grain boundary influence, make it an outstanding X-ray detection material compared to polycrystals. In addition to material properties, X-ray detector performance is affected by the thickness of the absorption layer. Addressing this, a space-confined method is proposed. The temperature field is determined through finite element simulation, effectively guiding the design of the space-confined method. Through this innovative method, a series of thickness-controlled perovskite single crystal wafers (PSCWs) are successfully prepared. Corresponding X-ray detectors are then prepared, and the impact of single crystal thickness on device performance is investigated. With an increase in single crystal thickness, a rise followed by a decline in device sensitivity is observed, reaching an optimal value at 0.7 mm thickness at 40V mm -1 with a device performance of 11313.6µC Gy -1  cm -2 . This space-confined method enables the direct growth of high-quality perovskite single crystals with specified thickness, eliminating the need for slicing or etching., (© 2024 Wiley‐VCH GmbH.)

Efforts to understand the complexities of human biology encompass multidimensional aspects, with proteins emerging as crucial components. However, studying the human ovary introduces unique challenges due to its complex dynamics and changes over a lifetime, varied cellular composition, and limited sample access. Here, four new RNA-seq samples of ovarian cortex spanning ages of 7 to 32 were sequenced and added to the existing data in the Human Protein Atlas (HPA) database www.proteinatlas.org, opening the doors to unique possibilities for exploration of oocyte-specific proteins. Based on transcriptomics analysis of the four new tissue samples representing both prepubertal girls and women of fertile age, we selected 20 protein candidates that lacked previous evidence at the protein level, so-called "missing proteins" (MPs). The proteins were validated using high-resolution antibody-based profiling and single-cell transcriptomics. Fourteen proteins exhibited consistent single-cell expression patterns in oocytes and granulosa cells, confirming their presence in the ovary and suggesting that these proteins play important roles in ovarian function, thus proposing that these 14 proteins should no longer be classified as MPs. This research significantly advances the understanding of MPs, unearthing fresh avenues for prospective exploration. By integrating innovative methodologies and leveraging the wealth of data in the HPA database, these insights contribute to refining our understanding of protein roles within the human ovary and opening the doors for further investigations into missing proteins and human reproduction.