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This study explores multi-component garnet-based materials as solid electrolytes for all-solid-state lithium batteries. Through a combination of computational and experimental approaches, we investigate the thermodynamic and structural properties of lithium lanthanum zirconium oxide garnets doped with various elements. Applying density functional theory, the influence of dopants on the thermodynamic stability of these garnets was studied. Probable atomic configurations and their impact on materials’ properties were investigated with the focus on understanding the influence of these configurations on structural stability, phase preference, and ionic conductivity. In addition to the computational study, series of cubic-phase garnet compounds were synthesized and their electrochemical performance was evaluated experimentally. Our findings reveal that the stability of cubic phase in doped Li-garnets is primarily governed by enthalpy, with configurational entropy playing a secondary role. Moreover, we establish that the increased number of doping elements significantly enhances the cubic phase’s stability. This in-depth understanding of materials’ properties at atomic level establishes the basis for optimizing high-entropy ceramics, contributing significantly to the advancement of solid-state lithium batteries and other applications requiring innovative material solutions.

Quantification of energetic electron precipitation caused by wave-particle interactions is fundamentally important to understand the cycle of particle energization and loss of the radiation belts. One important way to determine how well the wave-particle interaction models predict losses through pitch-angle scattering into the atmospheric loss cone is the direct comparison between the ionization altitude profiles expected in the atmosphere due to the precipitating fluxes and the ionization profiles actually measured with incoherent scatter radars. This paper reports such a comparison using a forward propagation of loss-cone electron fluxes, calculated with the electron pitch angle diffusion model applied to Van Allen Probes measurements, coupled with the Boulder Electron Radiation to Ionization model, which propagates the fluxes into the atmosphere. The density profiles measured with the Poker Flat Incoherent Scatter Radar operating in modes especially designed to optimize measurements in the D-region, show multiple instances of close quantitative agreement with predicted density profiles from precipitation of electrons caused by wave-particle interactions in the inner magnetosphere, alternated with intervals with large differences between observations and predictions. Several-minute long intervals of close prediction-observation approximation in the 65-93 km altitude range indicate that the whistler wave-electron interactions models are realistic and produce precipitation fluxes of electrons with energies between 10 keV and >100 keV that are consistent with observations. The alternation of close model-data agreement and poor agreement intervals indicates that the regions causing energetic electron precipitation are highly spatially localized.

In neurodegenerative disorders, neuronal firing patterns and oscillatory activity are remarkably altered in specific brain regions, which can serve as valuable biomarkers for the identification of deep brain regions. The subthalamic nucleus (STN) has been the primary target for DBS in patients with Parkinson’s disease (PD). In this study, changes in the spike firing patterns and spectral power of local field potentials (LFPs) in the pre-STN (zona incerta, ZI) and post-STN (cerebral peduncle, cp) regions were investigated in PD rats, providing crucial evidence for the functional localization of the STN. Sixteen-channel microelectrode arrays (MEAs) with sites distributed at different depths and widths were utilized to record neuronal activities. The spikes in the STN exhibited higher firing rates than those in the ZI and cp. Furthermore, the LFP power in the delta band in the STN was the greatest, followed by that in the ZI, and was greater than that in the cp. Additionally, increased LFP power was observed in the beta bands in the STN. To identify the best performing classification model, we applied various convolutional neural networks (CNNs) based on transfer learning to analyze the recorded raw data, which were processed using the Gram matrix of the spikes and the fast Fourier transform of the LFPs. The best transfer learning model achieved an accuracy of 95.16%. After fusing the spike and LFP classification results, the time precision for processing the raw data reached 500 ms. The pretrained model, utilizing raw data, demonstrated the feasibility of employing transfer learning for training models on neural activity. This approach highlights the potential for functional localization within deep brain regions.

Aiming at the design challenges of multi-branch orthogonal compliant test stand, a finite element method with beam connection units is proposed, and finite element models of force branches and test stand are established using this method. Structural characteristics analysis is carried out for six branch forms and lateral layout forms. Based on this, combined with a case study of test stand, detailed parameter design is conducted using the finite element model, resulting in a compact and minimally coupled structure. Calibration tests for the three load components of the test stand (axial force, normal force, and pitching moment) are performed, with uncertainties of calibration around 0.5% of the full scale (FS). To address the significant impact of the loading accuracy of high-load test stands on calibration measurements, a performance evaluation method based on the ratio of load to measurement is proposed. Through this method, the repeatability of the three-component measurement of the designed test stand is around 0.4%FS, and the hysteresis of large-range measurement is within 0.7%FS. The research findings have quite reference significance for the structural design and performance analysis of orthogonal test stands.

Abstract Background One-pot synthesis of metal nanoparticles under ambient temperature and pressure using reducing and stabilizing materials from microbes is energy-effective and ecofriendly, but upstream extraction of biological raw materials and downstream purification of nanoparticles from bioreactors are laborious and expensive. To simplify the productive process for using metal nanoparticles as microbicides to control plant pathogens, we use an endospore-forming Bacillus biocontrol agent to produce the nano-microbicide and use the bacterial raw materials as bio-microbicides together with the nano-microbicide. Results Bacillus cells at the stationary phase form endospores and tolerate Ag+ and Ag nanoparticles (AgNPs), while the cell-free culture supernatant (CFCS) mediates the synthesis of AgNPs. AgNPs produced from the Bacillus culture and CFCS show similar physical, chemical, and electrical characteristics, and bactericidal and anti-biofilm activities. Moreover, the diluted products effectively protect the kiwifruit leaves from the infection of the pathogen Pseudomonas syringae pv. actinidiae. Conclusions This coproduction of bio-microbicide and nano-microbicide is a totally green one-pot synthesis process without extraction and purification and without production of waste and can be easily scaled up using the existing fermentation processing of Bacillus biocontrol agents. The application of the synergistic bio-microbicide and nano-microbicide can effectively control the bacterial canker disease of kiwifruit plants. Graphical Abstract

Objective To investigate the effect of moist exposed burn therapy (MEBT) /moist exposed burn ointment (MEBO) on the expression of inducible nitric oxide synthase (iNOS) and arginase 1 (Arg1) in diabetic wounds. Methods Forty-eight male Wistar rats were randomly divided into four groups: blank group, MEBO group, Beifuxin group and control group, with 12 rats in each group. The blank group was used to build the acute wound model of normal rats, and the MEBO group, Beifuxin group and control group were used to build the wound model of diabetes rats. After the establishment of the model, MEBO group and Beifuxin group were given two layers of MEBO gauze and recombinant bovine basic fibroblast growth factor gel (Beifuxin®) gauze for external application on the wound surface respectively, and the control group and the blank group were covered with two layers of normal saline gauze. HE staining, immunofluorescence and qRT-PCR were used to observe the wound healing, histomorphological changes and the expression changes of M1/M2 macrophage markers iNOS and Arg1 in the wound tissue of rats in each group on the 3rd, 7th and 14th days after modeling. Results On the 7th and 14th days after modeling, the healing rates of MEBO group, blank group and Beifuxin group were higher than those of the control group (P＜0.05). On the third day of modeling, the expression level of iNOS mRNA in MEBO group, control group and Beifuxin group was higher than that in blank group, while the expression level of Arg1 mRNA was lower than that in blank group (P＜0.05). On the 7th and 14th day after modeling, compared with the control group, the expression level of Arg1 mRNA in MEBO group, and Beifuxin group was higher, while the expression level of iNOS mRNA was lower (P＜0.05). Conclusion MEBT/MEBO can accelerate diabetic wound healing, and its mechanism may be related to inhibiting iNOS, promoting Arg1 expression, and participating in regulating macrophage M1/M2 polarization.

Abstract Regulation of alternative splicing (AS) enables a single transcript to yield multiple isoforms that increase transcriptome and proteome diversity. Here, we report that spliceosome component Usp39 plays a role in the regulation of hepatocyte lipid homeostasis. We demonstrate that Usp39 expression is downregulated in hepatic tissues of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) subjects. Hepatocyte-specific Usp39 deletion in mice leads to increased lipid accumulation, spontaneous steatosis and impaired autophagy. Combined analysis of RNA immunoprecipitation (RIP-seq) and bulk RNA sequencing (RNA-seq) data reveals that Usp39 regulates AS of several autophagy-related genes. In particular, deletion of Usp39 results in alternative 5’ splice site selection of exon 6 in Heat shock transcription factor 1 (Hsf1) and consequently its reduced expression. Importantly, overexpression of Hsf1 could attenuate lipid accumulation caused by Usp39 deficiency. Taken together, our findings indicate that Usp39-mediated AS is required for sustaining autophagy and lipid homeostasis in the liver.

Abstract Cities are the main spaces to study a low-carbon economy. This paper introduces basic concepts covering “tolerance of planning carbon emissions,” “inevitable carbon emissions” and “excessive carbon emissions,” then discusses the problem with optimal city carbon emissions under the condition of tolerance. Theoretical analysis and scenario analysis were employed. First, according to optimal allocation theory of resources, we discuss how optimal society carbon emissions take place. Then, the deviation of optimal city carbon emissions was explored and analyzed, which was mostly caused by the missing price of carbon emissions allowance, excessive carbon emissions, and so on. Third, we analyzed optimal city carbon emissions under different conditions, in which different types of tolerance were included. Results show that theoretical investigations on optimal city carbon emissions provide relative ideas for determining control index and optimizing control countermeasures. Policy implications include improving the control index of city carbon emissions through environment enhancement, setting a reasonable control index of city carbon emissions under the consideration of the relationship between city economy and its environment, and establishing trading allowance and compensation mechanism of city carbon emissions, etc.

Soybean is a primary source of plant-based oil and protein for human diets. Seed size and weight are important agronomic traits that significantly influence soybean yield. Despite their importance, the genetic mechanisms underlying soybean seed size and weight remain to be fully elucidated. In order to identify additional, major quantitative trait loci (QTL) associated with seed size and weight, we developed segregating populations by crossing a large-seeded soybean variety “Kebaliang” with a small-seeded soybean variety “SUZUMARU”. We evaluated seed length, width, thickness, and hundred-seed weight across two generations, F4 and F5, in 2022 and 2023. Employing bulked segregate analysis with whole-genome resequencing (BSA-seq), we detected 18 QTLs in the F4 population and 12 QTLs in the F5 population. Notably, six QTLs showed high stability between the two generations, with five derived from two pleiotropic loci (qSS4-1 and qSS20-1) and one specific to seed width (qSW14-1). Further validation and refinement of these loci were carried out through linkage mapping using molecular markers in the F5 population. Additionally, we identified 18 candidate genes within these stable loci and analyzed their sequence variations and expression profiles. Together, our findings offered a foundational reference for further soybean seed size research and unveiled novel genetic loci and candidate genes that could be harnessed for the genetic enhancement of soybean production.

In order to minimize the disparity between visible and infrared modalities and enhance pedestrian feature representation, a cross-modality person re-identification method is proposed, which integrates modality generation and feature enhancement. Specifically, a lightweight network is used for dimension reduction and augmentation of visible images, and intermediate modalities are generated to bridge the gap between visible images and infrared images. The Convolutional Block Attention Module is embedded into the ResNet50 backbone network to selectively emphasize key features sequentially from both channel and spatial dimensions. Additionally, the Gradient Centralization algorithm is introduced into the Stochastic Gradient Descent optimizer to accelerate convergence speed and improve generalization capability of the network model. Experimental results on SYSU-MM01 and RegDB datasets demonstrate that our improved network model achieves significant performance gains, with an increase in Rank-1 accuracy of 7.12% and 6.34%, as well as an improvement in mAP of 4.00% and 6.05%, respectively.

In an effort to enhance the efficiency and accuracy of deep-sea manganese nodule grasping behavior by a manipulator, a novel approach employing an improved YOLOv5 algorithm is proposed for the extraction of the shortest paths to manganese nodules targeted by the manipulator. The loss function of YOLOv5s has been improved by integrating a dual loss function that combines IoU and NWD, resulting in better accuracy for loss calculations across different target sizes. Additionally, substituting the initial C3 module in the network backbone with a C2f module is intended to improve the flow of gradient information while reducing computational demands. Once the geometric center of the manganese nodules is identified with the improved YOLOv5 algorithm, the next step involves planning the most efficient route for the manipulator to pick up the nodules using an upgraded elite strategy ant colony algorithm. Enhancements to the ACO algorithm consist of implementing an elite strategy and progressively decreasing the number of ants in each round. This method reduces both the number of iterations and the time required for each iteration, while also preventing the occurrence of local optimal solutions. The experimental findings indicate that the improved YOLOv5s detection algorithm boosts detection accuracy by 2.3%. Furthermore, when there are fewer than 30 target planning points, the improved algorithm requires, on average, 24% fewer iterations than the ACO algorithm to determine the shortest path. Additionally, the speed of calculation for each iteration is quicker while still providing the optimal solution.

The Nb-16Si-24Ti-2Al-2Cr alloy was prepared by plasma rotating electrode process (PREP) technology and the hot-pressing (HP) method, and the effects of sintering temperature on the microstructure, mechanical properties and fracture behavior were investigated. The HP alloys sintered at temperatures below 1400 °C are composed of Nbss (Nb solid solution), Nb3Si and Nb5Si3 phases. When the sintering temperature reaches 1450 °C, the Nb3Si phase is completely decomposed into Nbss and Nb5Si3 phases. Meanwhile, the microstructure coarsens significantly. Compared with the cast alloy, the HP alloy shows better mechanical properties. The fracture toughness of the alloy sintered at 1400 °C reaches 20.2 MPa·m1/2, which exceeds the application threshold. The main reason for the highest fracture toughness is attributed to the decomposition of large-sized brittle Nb3Si phase and the formation of a fine microstructure, which greatly increases the number of phase interfaces and improves the chance of crack deflection. In addition, the reduction in the size and content of silicides also reduces their plastic constraints on the ductile Nbss phase.

Applying graphene (Gr) coatings to high-entropy alloys (HEA) is anticipated to enhance their tribological characteristics. The current understanding of the mechanism by which the Gr/HEA is enhanced at the atomic level is still limited. Molecular dynamics simulations revealed the mechanical behavior and strengthening mechanism of the Gr/AlCoCrFeNi HEA during nanoindentation and nanoscratch. The results demonstrate a substantial increase in the indentation hardness of the Gr/AlCoCrFeNi HEA by about 2.4 times. When Gr changed from a single layer to three layers, it further improved (3.2 times for a double layer and 3.9 times for three layers). At the same time, the friction coefficient is effectively reduced. Furthermore, the elevated in-plane stiffness of the Gr coating leads to an expansion of the effective loading area, resulting in increased Shockley dislocation and stair-rod dislocation density within the Gr/AlCoCrFeNi HEA, thereby amplifying the strain hardening effect and reducing subsurface damage. Qualitative experiments confirmed the excellent wear resistance of the Gr/HEA, and coating Gr increased the width of scratches, effectively confirming our simulation results. These findings provide valuable insights for the development and design of Gr/HEA composite coatings with enhanced mechanical properties. [ABSTRACT FROM AUTHOR]