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Background: Murraya tetramera Huang is a traditional Chinese woody medicine. Its leaves contain flavonoids, alkaloids, and other active compounds, which have anti-inflammatory and analgesic effects, as well as hypoglycemic and lipid-lowering effects, and anti-tumor effects. There are significant differences in the content of flavonoids and alkaloids in leaves during different growth cycles, but the synthesis mechanism is still unclear. Results: In April 2021, new leaves (one month old) and old leaves (one and a half years old) of M. tetramera were used as experimental materials to systematically analyze the changes in differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) with transcriptomics and metabolomics technology. This was done to identify the signaling pathways of flavonoid and alkaloid synthesis. The results showed that the contents of total alkaloids and flavonoids in old leaves were significantly higher than those in new leaves. Thirteen flavonoid compounds, three isoflavone compounds, and nineteen alkaloid compounds were identified, and 125 and 48 DEGs related to flavonoid and alkaloid synthesis were found, respectively. By constructing the KEGG (Kyoto Encyclopedia of Genes and Genomes) network of DEGs and DAMs, it was shown that the molecular mechanism of flavonoid biosynthesis in M. tetramera mainly focuses on the "flavonoid biosynthetic pathway" and the "flavonoid and flavonol biosynthetic pathway". Among them, p-Coumaryl alcohol, Sinapyl alcohol, Phloretin, and Isoquercitrin were significantly accumulated in old leaves, the up-regulated expression of CCR (cinnamoyl-CoA reductase) might promote the accumulation of p-Coumaryl alcohol, upregulation of F5H (ferulate-5-hydroxylase) might promote Sinapyl alcohol accumulation. Alkaloids, including indole alkaloids, pyridine alkaloids, imidazole alkaloids, and quinoline alkaloids, were significantly accumulated in old leaves, and a total of 29 genes were associated with these substances. Conclusions: These data are helpful to better understand the biosynthesis of flavonoids and alkaloids in M. tetramera and provide a scientific basis for the development of medicinal components in M. tetramera. [ABSTRACT FROM AUTHOR]

Mass spectrometry (MS) is a powerful analytical technique in metabolomics, enabling the identification and quantification of metabolites. However, analyzing MS data poses challenges such as batch effects, outliers, and high-dimensional data. In this paper, we propose a comprehensive framework for MS data analysis. The framework integrates data calibration, outlier detection, and automatic classification modules. Data calibration is performed using a deep autoencoder to remove batch effects. Outlier detection combines multiple algorithms through ensemble learning to identify and remove outliers. Automatic classification utilizes a transformer model to handle high-dimensional data and capture global feature relationships. Experimental results on myocardial infarction (MI) and coronary heart disease (CHD) datasets demonstrate the effectiveness of the framework. It outperforms traditional classification models and achieves higher accuracy. The proposed framework provides a robust solution for MS data analysis, facilitating more accurate classification and enabling reliable biological insights in metabolomics research. [Display omitted] • Novel framework integrates three steps for MS data analysis. • Deep AE removes batch effects, while an ensemble approach removes outliers. • Transformer captures intrinsic relationships in MS data for accurate classification. • The framework provides a comprehensive solution to improve classification accuracy. • The framework also facilitates reliable biological insights. [ABSTRACT FROM AUTHOR]

The combination of achiral Cp*Rh(III) with chiral carboxylic acids (CCAs) represents an efficient catalytic system in transition metal‐catalyzed enantioselective C−H activation. However, this hybrid catalysis is limited to redox‐neutral C−H activation reactions and the adopt to oxidative enantioselective C−H activation remains elusive and pose a significant challenge. Herein, we describe the development of an electrochemical Cp*Rh(III)‐catalyzed enantioselective C−H annulation of sulfoximines with alkynes enabled by chiral carboxylic acid (CCA) in an operationally friendly undivided cell at room temperature. A broad range of enantioenriched 1,2‐benzothiazines are obtained in high yields with excellent enantioselectivities (up to 99 % yield and 98 : 2 er). The practicality of this method is demonstrated by scale‐up reaction in a batch reactor with external circulation. A crucial chiral Cp*Rh(III) intermediate is isolated, characterized, and transformed, providing rational support for a Rh(III)/Rh(I) electrocatalytic cycle. [ABSTRACT FROM AUTHOR]

The combination of achiral Cp*Rh(III) with chiral carboxylic acids (CCAs) represents an efficient catalytic system in transition metal‐catalyzed enantioselective C−H activation. However, this hybrid catalysis is limited to redox‐neutral C−H activation reactions and the adopt to oxidative enantioselective C−H activation remains elusive and pose a significant challenge. Herein, we describe the development of an electrochemical Cp*Rh(III)‐catalyzed enantioselective C−H annulation of sulfoximines with alkynes enabled by chiral carboxylic acid (CCA) in an operationally friendly undivided cell at room temperature. A broad range of enantioenriched 1,2‐benzothiazines are obtained in high yields with excellent enantioselectivities (up to 99 % yield and 98 : 2 er). The practicality of this method is demonstrated by scale‐up reaction in a batch reactor with external circulation. A crucial chiral Cp*Rh(III) intermediate is isolated, characterized, and transformed, providing rational support for a Rh(III)/Rh(I) electrocatalytic cycle. [ABSTRACT FROM AUTHOR]

The illustration highlights thermally resilient, phase-invertible, ultra-stable water-in-water (W/W) droplets by pH-modulated casein colloidal particles. It includes radar plots contrasting the robustness of W/W droplets stabilized by casein colloidal particles with those stabilized by other protein/polymer particles reported in literature (see also Table S1). [Display omitted] The essence of compartmentalization in cells is the inspiration behind the engineering of synthetic counterparts, which has emerged as a significant engineering theme. Here, we report the formation of ultra-stable water-in-water (W/W) emulsion droplets. These W/W droplets demonstrate previously unattained stability across a broad pH spectrum and exhibit resilience at temperatures up to 80℃, overcoming the challenge of insufficient robustness in dispersed droplets of aqueous two-phase systems (ATPS). The exceptional robustness is attributed to the strong anchoring of micelle-like casein colloidal particles at the PEO/DEX interface, which maintains stability under varying environmental conditions. The increased surface hydrophobicity of these particles at high temperatures contributes to the formation of thermally-stable droplets, enduring temperatures as high as 80℃. Furthermore, our study illustrates the adaptable affinity of micelle-like casein colloidal particles towards the PEO/DEX-rich phase, enabling the formation of stable DEX-in-PEO emulsions at lower pH levels, and PEO-in-DEX emulsions as the pH rises above the isoelectric point. The robust nature of these W/W emulsions unlocks new possibilities for exploring various biochemical reactions within synthetic subcellular modules and lays a solid foundation for the development of novel biomimetic materials. [ABSTRACT FROM AUTHOR]

This article explores the use of computational chemistry in studying the feasibility of biomimetic syntheses of polycyclic furanocembrane derivatives. The authors emphasize the significance of natural products, particularly marine natural products, in pharmaceutical research due to their unique structures and diverse biological activities. Biomimetic synthesis, which involves creating complex molecules from simple natural precursors, is an effective method for synthesizing natural products. Quantum chemical calculations are employed to analyze proposed biosynthetic reactions and design optimal reaction pathways. The article provides an overview of the computational methodology used in these studies and presents specific examples of polycyclic furanocembrane derivatives and their proposed biomimetic syntheses. The authors stress the importance of computational studies in assessing the reliability of these proposed connections and how they can assist synthetic chemists in developing biomimetic synthesis pathways. The article concludes by highlighting the continued interest in utilizing computational chemistry for natural product synthesis. [Extracted from the article]

Introduction: The objective of this study was to investigate changes in vision‐related resting‐state activity in patients with suprasellar tumors (ST) who experienced vision deterioration after surgery. Methods: Twelve patients with ST and vision deterioration after surgery were included in the study. Resting‐state functional connectivity (FC) was compared before and after surgery using a seed‐based analysis with a priori specified regions of interest (ROIs) within the visual areas. The differences between the two groups were identified using a paired t‐test. Results: The data showed a decrease in FC within and between the dorsal and ventral pathways, as well as in the third pathway in ST patients. The middle temporal visual cortex (MT+) showed a decreased FC with more regions than other visual ROIs. The data also revealed an increase in FC between the visual ROIs and higher‐order cortex. The superior frontal gyrus/BA8 showed an increased FC with more ROIs than other high‐order regions, and the hOC4d was involved in an increased FC with more high‐order regions than other ROIs. Conclusions: The study results indicate significant neural reorganization in the vision‐related cortex of ST patients with postoperative vision damage. Most subareas within the visual cortex showed remarkable neural dysfunction, and some highe‐order cortex may be primarily involved in top‐down control of the subareas within the visual cortex. The hot zones may arise in the processing of "top‐down" influence. [ABSTRACT FROM AUTHOR]

Geoherb usually represents high-quality medicinal herbs with better clinical therapeutic effects, and elucidating the geoherbalism is essential for the quality improvement of traditional Chinese Medicine. However, few researches were conducted to clarify the geoherbalism based on a large scale of transcriptomics. In the present study, we compared the transcriptomes of Rheum palmatum complex derived from top-geoherb and non-geoherb areas to show the geoherbalism properties of rhubarb. A total of 412.32 Gb clean reads were obtained with unigene numbers of 100,615 after assembly. Based on the obtained transcriptome datasets, key enzyme-encoding genes involved in the anthraquinones biosynthesis were also obtained. We also found that 21 anthraquinone-related unigenes were differentially expressed between two different groups, and some of these DEGs were correlated to the content accumulation of five free anthraquinones, indicating that the gene expression profiles may promote the geoherbalism formation of rhubarb. In addition, the selective pressure analyses indicated that most paired orthologous genes between these two groups were subject to negative selection, and only a low proportion of orthologs under positive selection were detected. Functional annotation analyses indicated that these positive-selected genes related to the functions such as gene expression, substance transport, stress response and metabolism, indicating that discrepant environment also enhanced the formation of geoherbalism. Our study not only provided insights for the genetic mechanism of geoherbalism of rhubarb, but also laid more genetic cues for the future rhubarb germplasms improvement and utilization. [ABSTRACT FROM AUTHOR]

[Display omitted] The inherent poor ionic and electronic conductivity and relatively low capacity seriously limit the development of Na 3 V 2 (PO 4) 3 (NVP). Currently, Y3+ substitution is proposed for the first time and corresponding Y-doped NVP samples are successfully synthesized by traditional solid phase method. By replacing V3+ (0.64 Å) of Y3+ (0.9 Å) with large ionic radius, the transport channel of Na+ is expanded, accelerating the migration rate of Na+. Meanwhile, the strong Y-O chemical bond reinforces the crystal structure of NVP and improves its stability. It is worth noting that Y3+ reacts with slightly excess Na+ during the sintering process to form a new conductive phase NaYO 2 coated on the surface of NVP particles. NaYO 2 possesses excellent semiconductor properties and can form a double conductive construction together with the amorphous carbon layer to improve the kinetics of NVP system. Moreover, the unique heterojunction could be generated between the boundaries of Na 3 V 2 (PO 4) 3 -NaYO 2 , further elevating the ionic conductivity. According to the investigations of ex-situ XRD and in-situ EIS, NaYO 2 can provide active Na+, participating in the electrochemical process to supply extra reversible capacity. Comprehensively, the optimized NVP-Y0.07/C releases a high capacity of 125.2 mAh/g at 0.1 C, far exceeding the theoretical value of NVP (117.6 mAh/g). Even at 60 C, a high specific capacity of 94.2 mAh g−1 can be achieved. When cycled at 250 C, it maintains 85.5 % after 2000 cycles. Besides, the assembled NVP-Y0.07/C//hard carbon full cell can deliver a reversible value of 118.2 mAh/g, suggesting the superior practical application potentials. [ABSTRACT FROM AUTHOR]

Background: The Qinghai-Tibet Plateau is the "sensitive area" of climate change, and also the "driver" and "amplifier" of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale. Results: Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30–70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source). Conclusions: The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community's understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve "carbon neutrality" by 2060. Highlights: This study designed a carbon sink estimation method for Qinghai-Tibet Plateau by integrating machine learning and multiple scale ground- and remote sensed-based data. The estimated total carbon sink of the Qinghai-Tibet Plateau is 22.3 Tg C/year, accounting for about 10% of China's total carbon sink. The carbon sink of former estimation maybe greatly underestimated due to the underestimation of carbon input in the Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

Soybean dregs are a by-product of soybean processing, with high nutritional value. In addition to various nutrients such as protein, dietary fiber and minerals, they also contain many active substances, such as soybean isoflavones and soybean polysaccharides. Soybean dregs can be directly used in livestock and poultry breeding, and can also be improved by microbial fermentation and cooperative fermentation of bacterial enzymes to degrade anti-nutritional factors in soybean dregs feed, and improve the nutritional value of soybean dregs feed and the utilization rate of nutrient components. Fermented soybean dregs can promote the growth and development of livestock and poultry, improve the production performance of livestock and poultry, improve the antioxidant capacity and improve the body resistance. On the basis of introducing the nutrient composition of soybean dregs, the application of soybean dregs in feed and its application in livestock and poultry breeding were discussed in the paper, in order to provide reference for the further popularization and applying of soybean dregs in breeding. [ABSTRACT FROM AUTHOR]

Axially chiral styrenes, a type of atropisomer analogous to biaryls, have attracted great interest because of their unique presence in natural products and asymmetric catalysis. Since 2016, a number of methodologies have been developed for the atroposelective construction of these chiral skeletons, involving both transition metal catalysis and organocatalysis. In this feature article, we aim to provide a comprehensive understanding of recent advances in the asymmetric synthesis of axially chiral styrenes catalyzed by transition metals, integrating scattered work with different catalytic systems together. This feature article is cataloged into five sections according to the strategies, including asymmetric coupling, enantioselective C–H activation, central-to-axial chirality transfer, asymmetric alkyne functionalization, and atroposelective [2+2+2] cycloaddition. [ABSTRACT FROM AUTHOR]

Electromagnetically induced transparency (EIT) plays an important role in sensors, optical memories, and integrated metamaterials. However, most of the structures can produce only one transparent window, and there are few reports on the application of carbon nanotubes (CNTs) films in EIT. Here, we proposed a terahertz (THz) metasurface based on CNTs, which can produce dual-mode EIT windows. We prepared the CNTs films and extracted the conductivity parameter of the films in the THz region. The EIT transmission spectra have been calculated theoretically by applying the dispersion relation of surface plasmon polariton (SPP) and a three-stage system, which is consistent with the simulation results in each mode. The two EIT windows are tunable as the variation of the incident angles. In addition, the group delays of the two modes reach 16.77 ps and 14.61 ps, respectively. And the group delays are also affected by the incident angles of THz waves. This scheme can further extend to other functional metasurfaces, which offer new methods and platforms for multifunctional THz devices. [ABSTRACT FROM AUTHOR]

The Western Pacific Coasts (WPC) are the outlets of many large Asian rivers. In recent years, the interplay of climate changes and human activities has persistently altered the suspended sediment concentrations (SSC) in the WPC, triggering substantial shifts in coastal ecosystems. However, the scarcity of coastal observation stations hampered comprehensive investigations at large scales. This study employed three representative SSC retrieval models and utilized Landsat images acquired from 1990 to 2020 to estimate the SSC in the WPC with a focused endeavor to dissect the intricate spatial and temporal variability of SSC in the region. The findings revealed the following insights: (1) The outcomes derived from the three distinct SSC models consistently manifested a discernible decreasing pattern in SSC changes over the past three decades across all six major estuaries (Liao River Estuary, Yellow River Estuary, Yangtze River Estuary, Hangzhou Bay, Pearl River Estuary, and Mekong River Estuary). (2) The seasonal attributes of the six major estuaries differed, primarily due to distinct dominant influencing factors like precipitation, upstream sediment load, wind, and tides. (3) Collectively, SSC tends to be relatively higher in the Yangtze River Estuary, Hangzhou Bay, and Yellow River Estuary, while the Pearl River and Mekong River Estuaries exhibit relatively lower levels. Notably, the SSC exhibited distinct spatial traits along the coastlines of different estuaries. (4) SSC in the non-estuarine regions along the WPC, a similar significant declining trend in SSC is observed as in the estuaries, albeit the rate of decline generally appeared to be less pronounced. Furthermore, regions with faster rates of SSC reduction are typically concentrated near major estuaries in the northern part of the Coasts. The decline in estuarine SSC plays an important role in the overall decrease in SSC across the WPC. These study outcomes held substantial significance for advancing the stability and sustainable evolution of the WPC. [ABSTRACT FROM AUTHOR]

Global warming has caused changes in the area and thickness of permafrost on the Qinghai-Tibet Plateau and prompted the transition from permafrost to seasonally frozen soil, which has affected the soil moisture, soil temperature, and distribution of plant roots. This, in turn, affects grassland vegetation productivity and aboveground/belowground biomass. In this study, we took Qinghai Province in the northeastern Qinghai-Tibet Plateau as the research area to model the spatial pattern of grassland biomass and then evaluated the potential influence of frozen soil type information on aboveground and belowground biomass. Our research shows that there are significantly more biomass observations in seasonally frozen soil regions than in permafrost regions. However, when we ignore the type of frozen soil, the model does not show more accurate simulation in seasonally frozen soil regions, mainly because the stronger correlation between permafrost biomass and environmental factors, such as precipitation, compensates for the lack of observational data. In addition, we found that the biomass estimation error can be reduced significantly by building different models for each type of frozen soil, which implies that the type of frozen soil has an important impact on grassland biomass. Therefore, in considering the effects of future climate warming, more attention should be given to the impact of changes in frozen soil type on regional vegetation productivity. In addition, our investigation contributes a benchmark dataset of above- and belowground vegetation carbon storage in different frozen soil types, which provides the research community with useful information for optimizing process-based carbon cycle models. [ABSTRACT FROM AUTHOR]

Shear failure often occurs during the construction of the geotechnical engineering projects, especially under dynamic loading condition. To investigate the effect of loading rate and normal stress on the shear responses of rock materials, a bonded-particle model (BPM) was adopted to insight the failure process from a micro-mechanical perspective using the moment tensor. Firstly, we propose a novel calibration methodology for direct shear test, which provides a possibility to effectively derive microscopic parameters of PBM for obtaining the macroscopic properties of rocks considering loading rates under direct shear. Validation results show that the simulation demonstrated good agreement with the experimental results. Then, a series of simulated direct shear tests under different normal stresses ranging from 0 to 20 MPa and loading rate ranging from 10–3 to 10–1 mm/s were performed. The results demonstrate that both normal stress and loading rate have a positive influence on shear strength. However, normal stress has a greater impact on the shear strength compared to loading rate, and the effect of loading rate on shear strength weakens as the normal stress level increases. Increasing the loading rate and normal stress level led to a higher distribution of AE events in the nonlinear stage. At lower loading rates and normal stress, intense AE activity was concentrated around the peak stress point. In contrast, under higher situations, the nonlinear stage is prolonged, resulting in an increased number of AE events in the nonlinear and post-peak stages. Normal stress has a greater impact on the generation and propagation of micro-cracks compared to loading rate. With higher normal stress, the failure mode shifts from a shear-dominated to a mixed mode with tensile micro-cracks in a dominant role. Highlights: A numerical model was established using DEM to investigate the mechanical properties and failure mode evolution of rock specimens under shear loading, taking into account the influence of loading rate and normal stress factor. A novel calibration procedure was proposed for the direct shear model, and the results showed that it effectively improved the calibration efficiency compared with traditional methods, as validated by experimental data. The fracture behavior of the specimen under different strain rates and normal stress states was monitored using numerical simulation based on moment tensor theory of acoustic emission, which allowed for analysis of the shear failure process. [ABSTRACT FROM AUTHOR]

The permutation flow shop scheduling problem (PFSP) stands as a classic conundrum within the realm of combinatorial optimization, serving as a prevalent organizational structure in authentic production settings. Given that conventional scheduling approaches fall short of effectively addressing the intricate and ever-shifting production landscape of PFSP, this study proposes an end-to-end deep reinforcement learning methodology with the objective of minimizing the maximum completion time. To tackle PFSP, we initially model it as a Markov decision process, delineating pertinent states, actions, and reward functions. A notably innovative facet of our approach involves leveraging disjunctive graphs to represent PFSP state information. To glean the intrinsic topological data embedded within the disjunctive graph's underpinning, we architect a policy network based on a graph isomorphism network, subsequently trained through proximal policy optimization. Our devised methodology is compared with six baseline methods on randomly generated instances and the Taillard benchmark, respectively. The experimental results unequivocally underscore the superiority of our proposed approach in terms of m a k e s p a n and computation time. Notably, the m a k e s p a n can save up to 183.2 h in randomly generated instances and 188.4 h in the Taillard benchmark. The calculation time can be reduced by up to 18.70 s for randomly generated instances and up to 18.16 s for the Taillard benchmark. [ABSTRACT FROM AUTHOR]

Background: CDC42 is a member of Rho GTPase family, acting as a molecular switch to regulate cytoskeleton organization and junction maturation of epithelium in organ development. Tooth root pattern is a highly complicated and dynamic process that dependens on interaction of epithelium and mesenchyme. However, there is a lack of understanding of the role of CDC42 during tooth root elongation. Methods: The dynamic expression of CDC42 was traced during tooth development through immunofluorescence staining. Then we constructed a model of lentivirus or inhibitor mediated Cdc42 knockdown in Herwig's epithelial root sheath (HERS) cells and dental papilla cells (DPCs), respectively. Long-term influence of CDC42 abnormality was assessed via renal capsule transplantation and in situ injection of alveolar socket. Results: CDC42 displayed a dynamic spatiotemporal pattern, with abundant expression in HERS cells and apical DPCs in developing root. Lentivirus-mediated Cdc42 knockdown in HERS cells didn't disrupt cell junctions as well as epithelium-mesenchyme transition. However, inhibition of CDC42 in DPCs undermined cell proliferation, migration and odontogenic differentiation. Wnt/β-catenin signaling as the downstream target of CDC42 modulated DPCs' odontogenic differentiation. The transplantation and in situ injection experiments verified that loss of CDC42 impeded root extension via inhibiting the proliferation and differentiation of DPCs. Conclusions: We innovatively revealed that CDC42 was responsible for guiding root elongation in a mesenchyme-specific manner. Furthermore, CDC42-mediated canonical Wnt signaling regulated odontogenic differentiation of DPCs during root formation. [ABSTRACT FROM AUTHOR]

Abstract As a passive information behavior, information avoidance (IA) may undermine the sustainable development of social media platforms. Previous research has focused on the enabling effect of negative cognitions and emotions on IA, and has seldom considered the inhibitors of IA. This research tries to fill the gap by integrating a dual perspective of both enablers and inhibitors. Drawing on the cognitive dissonance theory (CDT) and psychological empowerment theory (PET), this research examined social media users’ IA. We adopted a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to conduct data analysis. The results showed that social support (SS) and information quality (IQ) affect psychological empowerment (PE), which further inhibits IA. In contrast, social comparison (SC), and perceived overload (PO) affect cognitive dissonance, which leads to IA. The fsQCA results found three paths that trigger users’ IA. The results imply that social media platforms need to mitigate cognitive dissonance and enhance PE in order to prevent users’ IA. This research contributes to a comprehensive understanding of the development process of IA. The limitation is that the results need to be generalized to other samples, such as the elderly. [ABSTRACT FROM AUTHOR]

Background: The Qinghai-Tibet Plateau is the "sensitive area" of climate change, and also the "driver" and "amplifier" of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale. Results: Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30–70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source). Conclusions: The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community's understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve "carbon neutrality" by 2060. Highlights: This study designed a carbon sink estimation method for Qinghai-Tibet Plateau by integrating machine learning and multiple scale ground- and remote sensed-based data. The estimated total carbon sink of the Qinghai-Tibet Plateau is 22.3 Tg C/year, accounting for about 10% of China's total carbon sink. The carbon sink of former estimation maybe greatly underestimated due to the underestimation of carbon input in the Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

Designing high-efficiency catalysts for overall water splitting is critical to reduce the cost of hydrogen fuel as a clean and renewable energy source in future society. In this work, a Mo-, P-codoped NiFeSe was successfully synthesized on nickel foam (NF) by one-step electrodeposition. Through the doping strategy, the conductivity can be well promoted, and the production of nanosheets on the catalyst surface and active phases during hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) provided much more active sites, which leaded to efficient HER/OER performances of as-synthesized Mo-, P-codoped NiFeSe catalysts, i.e., a low overpotential of 100 mV/200 mV at current density of 10 mA cm−2 in 1.0 M KOH with stability of 95 h/60 h, respectively. It only required 1.53 V to deliver a current density of 10 mA cm−2 in overall water splitting and maintained outstanding durability for 100 h. This work is beneficial to future design of high efficient and low-cost bifunctional catalysts for overall water splitting. [Display omitted] • NiFeSe–Mo–P/NF bifunctional electrocatalysts are synthesized by one-step electrodeposition. • The codoping of Mo and P enhances HER and OER performances. • Catalytic mechanisms are also discussed. • It requires 1.53 V to deliver a current density of 10 mA cm−2 in overall water splitting with stability of 100 h. [ABSTRACT FROM AUTHOR]

The reliable circulation of automotive supply chain data is crucial for automotive manufacturers and related enterprises as it promotes efficient supply chain operations and enhances their competitiveness and sustainability. However, with the increasing prominence of privacy protection and information security issues, traditional data sharing solutions are no longer able to meet the requirements for highly reliable secure storage and flexible access control. In response to this demand, we propose a secure data storage and access control scheme for the supply chain ecosystem based on the enterprise-level blockchain platform Hyperledger Fabric. The design incorporates a dual-layer attribute-based auditable access control model for access control, with four smart contracts aimed at coordinating and implementing access policies. The experimental results demonstrate that the proposed approach exhibits significant advantages under large-scale data and multi-attribute conditions. It enables fine-grained, dynamic access control under ciphertext and maintains high throughput and security in simulated real-world operational scenarios. [ABSTRACT FROM AUTHOR]

Both edible fungal polysaccharides (Auricularia and Tremellan) and Crataegus flavonoids promote the balance of dyslipidemia, which have a positive biological regulating effect on intestinal flora. In this study, the extraction of water‐soluble polysaccharides from Auricularia and Tremellan was investigated and optimized firstly. Polysaccharides and flavonoids were then combined to study the effects on the mediating role of abnormal blood lipid concentration and intestinal flora in vivo. The rats were divided into 10 groups, the NC (normal control), HM (model), PCI (Simvastatin control), PCII (Fenofibrate control), AAP (Auricularia auricular Polysaccharide), TFP (Tremella fuciformis Polysaccharide), HF (Crataegus Flavonoid), LDC (Low‐dose combination), MDC (Medium dose combination), and HDC (High‐dose combination), used to explore the impact of polysaccharides and flavonoids complex on state of blood lipid, liver, and intestinal flora of dyslipidemia rats. The results showed that the combination of polysaccharides and flavonoids could significantly decrease the levels of triglyceride (TG), total cholesterol (TC), low‐density lipoprotein (LDL‐C), and increase the level of high‐density lipoprotein cholesterol (HDL‐C). It also significantly decreased the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) and improved liver morphology. What is more, the HDC favorably alters the intestinal microflora balance, promotes intestinal integrity and mobility, and inhibits the growth of harmful bacteria such as Escherichia coli/Shigella and Clostridium compared with HM group. In brief, the combination of polysaccharides and flavonoids had a synergistic effect on the remission of dyslipidemia, and promoted health by improving lipid metabolism, protecting liver tissue, and regulating the intestinal flora in hyperlipidemia rats. [ABSTRACT FROM AUTHOR]

Loss of neurons in chronic neurodegenerative diseases may occur over a period of many years. Once initiated, neuronal cell death is accompanied by distinct phenotypic changes including cell shrinkage, neurite retraction, mitochondrial fragmentation, nuclear condensation, membrane blebbing and phosphatidylserine (PS) exposure at the plasma membrane. It is still poorly understood which events mark the point of no return for dying neurons. Here we analyzed the neuronal cell line SH-SY5Y expressing cytochrome C (Cyto.C)-GFP. Cells were exposed temporarily to ethanol (EtOH) and tracked longitudinally in time by light and fluorescent microscopy. Exposure to EtOH induced elevation of intracellular Ca2+ and reactive oxygen species, cell shrinkage, neurite retraction, mitochondrial fragmentation, nuclear condensation, membrane blebbing, PS exposure and Cyto.C release into the cytosol. Removing EtOH at predetermined time points revealed that all phenomena except Cyto.C release occurred in a phase of neuronal cell death in which full recovery to a neurite-bearing cell was still possible. Our findings underscore a strategy of treating chronic neurodegenerative diseases by removing stressors from neurons and harnessing intracellular targets that delay or prevent trespassing the point of no return. [ABSTRACT FROM AUTHOR]

BACKGROUND: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that begins in early infancy and childhood and is characterized by impaired social communication and repetitive stereotyped behaviors. OBJECTIVE: The purpose of this study was to examine the development of the corpus callosum and its relationship to neurobehavior in young children with high-risk (HR) ASD using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). METHODS: Twenty-one children with HR-ASD who visited Anhui Children's Hospital between January 2020 and December 2021 were selected as the study group, while 19 matched children with normal development during the same time were adopted as the control group. Cranial MRI + DTI were performed for all of the enrolled children and fractional anisotropy (FA) measurements were taken in each region of the corpus callosum. RESULTS: The FA values in all regions of the corpus callosum were higher in the study group than in the control group (0.417 ± 0.016 vs. 0.412 ± 0.02 in the corpus callosum knee, 0.439 ± 0.018 vs. 0.431 ± 0.023 in the corpus callosum body, and 0.446 ± 0.017 vs. 0.434 ± 0.019 in the splenium of corpus callosum [SCC]), where the difference in the FA in the SCC was statistically significant between the two groups (P < 0.05). There was a positive correlation between the FA in the corpus callosum knee and speech scores in the neuropsychological development of the study group (P < 0.05). CONCLUSION: There was a premature development tendency for corpus callosum myelination in young children with HR-ASD, and the developmental tendency was visible in the SCC. There was also a positive relationship between corpus callosum knee development and language function. [ABSTRACT FROM AUTHOR]

Objectives: To determine whether a CT-based machine learning (ML) can differentiate benign renal tumors from renal cell carcinomas (RCCs) and improve radiologists' diagnostic performance, and evaluate the impact of variable CT imaging phases, slices, tumor sizes, and region of interest (ROI) segmentation strategies. Methods: Patients with pathologically proven RCCs and benign renal tumors from our institution between 2008 and 2020 were included as the training dataset for ML model development and internal validation (including 418 RCCs and 78 benign tumors), and patients from two independent institutions and a public database (TCIA) were included as the external dataset for individual testing (including 262 RCCs and 47 benign tumors). Features were extracted from three-phase CT images. CatBoost was used for feature selection and ML model establishment. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the ML model. Results: The ML model based on 3D images performed better than that based on 2D images, with the highest AUC of 0.81 and accuracy (ACC) of 0.86. All three radiologists achieved better performance by referring to the classifier's decision, with accuracies increasing from 0.82 to 0.87, 0.82 to 0.88, and 0.76 to 0.87. The ML model achieved higher negative predictive values (NPV, 0.82–0.99), and the radiologists achieved higher positive predictive values (PPV, 0.91–0.95). Conclusions: A ML classifier based on whole-tumor three-phase CT images can be a useful and promising tool for differentiating RCCs from benign renal tumors. The ML model also perfectly complements radiologist interpretations. Key Points: • A machine learning classifier based on CT images could be a reliable way to differentiate RCCs from benign renal tumors. • The machine learning model perfectly complemented the radiologists' interpretations. • Subtle variances in ROI delineation had little effect on the performance of the ML classifier. [ABSTRACT FROM AUTHOR]

"Alto2" is a new biomass sorghum variety, which has the characteristics of fast growth, high growth, and strong cadmium (Cd) resistance, so it has the application prospect of soil remediation plants. In order to reveal the Cd resistance mechanism of this plant and pave the way for genetic breeding and cultivation of efficient remediation plants in the future, in this research, through the determination of Cd content in various tissues of sorghum under Cd stress and the physicochemical response combined with RNA-Seq analysis, the mechanism of Cd resistance of "Alto2" was initially revealed. The results show biomass sorghum "Alto2" was mainly connected with aboveground and underground parts through the MAPK signaling pathway and plant hormone signaling pathway, and transmit stress signal in response to Cd stress. Chelase and metal-binding proteins may be the functional genes mainly responsible for Cd enrichment and transport and regulated by stress signals. However, the expression of aboveground transporters was not significant. This may be because Cd in biomass sorghum is mainly concentrated in the underground part and is enriched by the chelation of secondary metabolites from plant roots by the cell wall leading to inhibition of aboveground transporter expression. The results of this study indicate that the biomass sorghum "Alto2" on Cd has high resistance, but the lack of the aboveground enrichment of transportability requires further research to improve the Cd transportability of this plant. [ABSTRACT FROM AUTHOR]

As the market for polyethylene consumption continues to expand, the amount of waste polyethylene is also increasing. Modifying asphalt with waste polyethylene (PE) is economical and environmentally friendly. The low-temperature performance and storage stability of PE-modified asphalt has long been an insurmountable problem. The high vinyl acetate (VA) content of ethylene–vinyl acetate (EVA) and PE blended into asphalt can improve the compatibility of PE and asphalt. It compensates for the high VA content of EVA brought about by the lack of high-temperature resistance to permanent deformation but is still not conducive to the stable storage of PE at high temperatures. The effect of furfural extraction oil, a crosslinking (DCP) agent, a silicone coupling agent (KH-570), and calcium carbonate (CaCO3) on the rheological properties and compatibility of PE/EVA-modified asphalt was investigated in this study. The conventional physical properties of PE/EVA-modified asphalt were tested after introducing furfural extraction oil, DCP, KH570, and CaCO3 to determine the correlations of these materials. In addition, frequency sweep, multiple stress creep and recovery (MSCR), and linear amplitude sweep (LAS) were utilized to characterize the rheological properties and fatigue behavior. The results reveal that the addition of suitable ratios of furfural extract oil, DCP, KH-570, and CaCO3 to PE/EVA-modified asphalt produces a remarkable improvement in the viscoelastic characteristics and viscosity compared with PE/EVA-modified asphalt. Furthermore, fluorescence microscopy (FM) was utilized to evaluate the modification mechanism, which shows that PE/EVA undergoes significant crosslinking in asphalt, forming a three-dimensional network structure that dissolves in the asphalt. The storage stability of the PE-modified bitumen was fully determined, and its high-temperature rheology was substantially improved. [ABSTRACT FROM AUTHOR]

With the construction of the Power Internet of Things (PIoT) in full swing as well as the development of wireless communication technology, the deployment of wireless sensor networks is the key to the intelligent transformation of power systems. This paper proposes an asymmetric double-layer wireless sensor network coverage scheme for the intelligent substation. We conducted field measurements in the substation to record the received power at different locations, which were compared with the prediction results of the simulation model established by Winprop to verify the effectiveness of the simulation method. Based on the simulation platform, two different simulation models of substation scenarios are built, including a 220 kV outdoor substation and a 110 kV GIS room. The coverage of received power and line-of-sight (LOS) transmission are analyzed for various nodes of different layers. Several node distribution planning methods are proposed and proven to be feasible according to the simulation results. The wireless coverage scheme can provide useful references for the implementation of PIoT in substations. [ABSTRACT FROM AUTHOR]

When subjected to significant loading, damage occurs in rock, leading to degradation of mechanical properties and increased wave attenuation. Although wave propagation in porous and jointed rocks has been extensively studied, influences of damage evolution on wave propagation are not fully understood. In this study, damage evolution and its influence on ultrasonic wave propagation in unconfined uniaxially loaded granite specimens were experimentally investigated. Granite specimen was firstly compressed to a certain load to generate damage and then unloaded immediately. The stress-driven damages in granite specimens during and after loading were quantified by acoustic emission and micro-CT scanning, respectively. Meanwhile, ultrasonic wave propagation in granite specimen along the loading direction was measured during and after loading, respectively. Results showed that the stress-driven damage in granite specimen is highly nonlinear, it increases drastically to the peak when the axial stress approaches the peak point. The stress-driven damage during loading is higher than that after loading. Wave propagation in granite is stress-dependent during compression. Both wave amplitude and velocity increase first and then decrease before the axial stress increasing to approximately 60 and 90% of the uniaxial compressive strength of the granite, respectively. However, compared with wave velocity, wave amplitude is more sensitive to stress and the stress-driven damage. The findings of this study could facilitate a better understanding of the relationship between damage evolution and wave propagation and attenuation in rocks. Highlights: The acoustic emission and micro-CT scanning can be adopted to quantify stress-driven damage in granite specimens. Wave amplitude is much more sensitive to stress and the stress-driven damage than wave velocity. Wave propagation is affected by the competition between the enhancing effect due to closure of initial cracks and the weakening effect due to generation of new cracks. [ABSTRACT FROM AUTHOR]

Background: Leptomeningeal metastasis (LM) is the most devastating complication of non-small cell lung cancer (NSCLC), and its incidence is increasing. There is currently no standard treatment for LM, and the efficacy of traditional intravenous drug treatment is low, making refractory LM a difficult problem. In this study, we evaluated the efficacy and safety of intrathecal chemotherapy (IC)-based regimens in patients with refractory LM. Methods: We retrospectively enrolled NSCLC patients with confirmed LM who received IC and systemic therapy at the Second Affiliated Hospital of Nanchang University from December 2017 to July 2022. We analysed overall survival (OS), intracranial progression-free survival (iPFS), clinical response, and safety in these patients. Results: A total of 41 patients were enrolled. The median number of IC treatments was seven (range: 2–22). Seven patients received intrathecal methotrexate, and 34 patients received intrathecal pemetrexed. Clinical manifestations related to LM improved after IC and systemic therapy in 28 (68.3%) patients. The median iPFS in the whole cohort was 8 months (95% confidence interval [CI]: 6.4–9.7 months), and the median OS was 10.1 months (95% CI: 6.8–13.4 months). Multivariate analysis of the 41 patients with LM using a Cox proportional risk model showed that bevacizumab was an independent prognostic factor in patients treated with combination therapy (p = 0.002; hazard ratio [HR] 0.240; 95% CI: 0.097–0.595). Poor ECOG performance status remained a significant predictor of poor prognosis for survival (p = 0.048; HR 2.560; 95% CI: 1.010–6.484). Myelosuppression was the major adverse event over all IC dose levels. There were 18 cases of myelosuppression, 15 cases of leukopenia, and nine cases of thrombocytopenia. Eleven patients had myelosuppression above grade 3, including four with thrombocytopenia and seven with leukopenia. Conclusions: Combination therapy based on IC had good curative effects, was safe to use, and was associated with prolonged survival in NSCLC patients with LM. The use of bevacizumab is a good prognostic factor for NSCLC LM patients with combination therapy. [ABSTRACT FROM AUTHOR]

Background and Aims: There are currently no clear conclusions about whether major depression (MD) and bipolar disorder (BD) increase the risk of erectile dysfunction (ED). In our study, we used a Mendelian randomization (MR) analysis to discover the causal associations between MD, BD and ED. Methods: We got single-nucleotide polymorphisms (SNPs) related to MD, BD and ED from the MRC IEU Open genome-wide association study (GWAS) datasets. After a series of selection, SNPs left were selected as instrumental variables (IVs) of MD and BD for the following MR test to evaluate the relationship of genetically predicted MD or BD with the incidence of ED. Among them, we used the random-effects inverse-variance weighted (IVW) method as the main analysis. Finally, sensitivity analyses were further performed using Cochran's Q test, funnel plots, MR-Egger regression, Leave-one-out method and MR- pleiotropy residual sum and outlier (PRESSO). Results: Genetically-predicted MD was causally related to the incidence of ED in the IVW methods (odds ratio (OR), 1.53; 95% confidence interval (CI), 1.19–1.96; p = 0.001), while no causal impact of BD on the risk of ED (OR = 0.95, 95% CI 0.87–1.04; p = 0.306). The results of sensitivity analyses supported our conclusion, and no directional pleiotropy were found. Conclusion: The findings of this research found evidence of a causal relationship between MD and ED. However, we did not find a causal relationship between BD and ED in European populations. [ABSTRACT FROM AUTHOR]

Species in Gentiana section Cruciata are important alpine plants with a center of diversity and speciation in Qinghai–Tibet Plateau (QTP), and some of these species are sympatrically distributed in northeastern QTP. Studies on genome features and natural selection signatures of sympatric species in section Crucata have been impeded by a lack of genomic resources. Here, we showed transcript characterizations and molecular footprints of selection effects on G. straminea, G. dahurica and G. officinalis based on the comparative transcriptome. A total of 62.97 Gb clean reads were obtained with unigene numbers per species ranging from 141,819 to 236,408 after assembly. We found that these three species had similar distribution of functional categories in different databases, and key enzyme-encoding genes involved in the iridoids biosynthesis were also obtained. The selective pressure analyses indicated that most paired orthologs between these three species were subject to negative selection, and only a low proportion of the orthologs that underwent positive selection were detected. We found that some positive selected genes were involved in "catalytic activity", "metabolic process", "response to stimulus" and "response to stress". Besides, large numbers of SSR primer pairs with transferabilities were successfully designed based on the available transcriptome datasets of three Gentiana species. The phylogenetic relationships reconstructed based on 352 single-copy nuclear genes provided a rough phylogenetic framework for this genus and confirmed the monophyly of section Cruciata. Our study not only provides insights for the natural selection effects on sympatric Gentiana species, but also enhances future genetic breeding or evolutionary studies on Qinjiao species. [ABSTRACT FROM AUTHOR]

Truck platooning is considered as a promising approach to improve traffic stability and to reduce fuel consumption and emissions on freeways. This article develops a two-stage trajectory planning model for cooperative and automated trucks (CATs) traveling on freeways to minimize overall fuel consumption considering platooning time and velocity change. In the first stage, five different strategies are proposed to determine the permutation of the platoon given the initial states and travel information of CATs. Once the feasibility is confirmed, the model is formulated as a mixed-integer programming to optimize the trajectories of all CATs on the entire freeway section. The results from the numerical experiments show that the platooning time optimization (PTO) strategy has superior performance in optimizing overall platooning time. Moreover, the velocity change under the condition of maximum platooning time is generally lower for the PTO and the passing time minimum strategies. These characteristics make the PTO strategy combined with the trajectory optimization program a suitable application for cooperative truck platooning management. [ABSTRACT FROM AUTHOR]

• Summarizing various models of GAN. • Discussing the advantages and applications of GAN in medical image fusion field. • Analyzing the challenges faced by GAN and envisioning the future directions of GAN. Generative Adversarial Network (GAN) is a research hotspot in deep generative models, which has been widely used in the field of medical image fusion. This paper summarizes GAN models from the following four aspects: firstly, the basic principles of GAN are expounded from two aspects: basic model and training process; secondly, variant GAN models are summarized into three directions (Probability Distribution Distance, Overall Network Architecture, Neural Network Structure), from the methods based on f-divergence, the methods based on IPM, Single-Generator and Dual-Discriminators GAN, Multi-Generators and Single-Discriminator GAN, Multi-Generators and Multi-Discriminators GAN, Conditional Constraint GAN, Convolutional Neural Network structure GAN and Auto-Encoder Neural Network structure GAN are eight dimensions to summarize the typical models in recent years; thirdly, the advantages and application of GAN models in the field of medical image fusion are explored from three aspects; fourthly, the main challenges faced by GAN and the challenges faced by GAN models in medical image fusion field are discussed and the future prospects are given. This paper systematically summarizes various models of GAN, advantages and challenges of GAN models in medical image fusion field, which is very important for the future research of GAN. [Display omitted] [ABSTRACT FROM AUTHOR]

Understanding how smart city investment influences the environment has valuable implications for increasing the environmental performance of smart cities. This study adopted spatial econometric models to explore the environmental impacts of smart city investments using data from 100 smart cities in China for the period 2014–2019. Smart city investment includes investment in information and communication technologies (ICT) and human capital. Environmental performance was measured in terms of air quality, green space and energy consumption. The results reveal that smart city investment can produce spatial spillover effects and that the environmental quality of cities is spatially correlated. ICT reduces air quality but increases green space and electricity consumption. In addition, human capital contributes to electricity conservation but does not influence air quality and green space. The impacts of smart city investments on the environment vary according to economic development level. Moreover, policy implications for the implementation of smart city investments that increase environmental performance are proposed. [ABSTRACT FROM AUTHOR]

Background: Colibactin is a genotoxin produced by Escherichia coli and other Enterobacteriaceae that is believed to increase the risk of colorectal cancer (CRC) of their symbiosis hosts, including human. A peptidase ClbP is the key enzyme for activation of colibactin. Inhibition of ClbP is considered to impede maturation of precolibactin into genotoxic colibactin. Therefore, ClbP-specific inhibitors could potentially prevent the onset of CRC, one of the leading causes of cancer-related deaths in the world. This study intends to establish an efficient screening system for identifying inhibitors that are specific to ClbP. Methods: Two types of assays were applied in the screening procedure: a probe assay and an LC–MS assay. For the probe assay, we employed the synthesized probe which we described in our previous report. This probe can be hydrolyzed efficiently by ClbP to release a fluorophore. Hence it was applied here for detection of inhibition of ClbP. For the LC–MS assay, formation of the byproduct of precolibactin maturation process, N-myristoyl-D-asparagine, was quantified using a liquid chromatography–mass spectrometry (LC–MS) technique. The probe assay can be performed much faster, while the LC–MS assay is more accurate. Therefore, our method employed the two assays in sequence to screen a large number of compounds for inhibition of ClbP. Results: A library of 67,965 standard compounds was evaluated by the screening method established in the current study, and one compound was found to show a moderate inhibitory activity against ClbP. Conclusion: A simple screening method for ClbP-specific inhibitors was established. It was proven to be reliable and is believed to be useful in developing potential prophylactic agents for CRC. [ABSTRACT FROM AUTHOR]

Free-space detection plays a pivotal role in autonomous vehicle applications, and its state-of-the-art algorithms are typically based on semantic segmentation of road areas. Recently, hyperspectral images have proven useful supplementary information in multi-modal segmentation for providing more texture details to the RGB representations, thus performing well in road segmentation tasks. Existing multi-modal segmentation methods assume that all the inputs are well-aligned, and then the problem is converted to fuse feature maps from different modalities. However, there exist cases where sensors cannot be well-calibrated. In this paper, we propose a novel network named multi-modal cross-attention network (MMCAN) for multi-modal free-space detection with uncalibrated hyperspectral sensors. We first introduce a cross-modality transformer using hyperspectral data to enhance RGB features, then aggregate these representations alternatively via multiple stages. This transformer promotes the spread and fusion of information between modalities that cannot be aligned at the pixel level. Furthermore, we propose a triplet gate fusion strategy, which can increase the proportion of RGB in the multiple spectral fusion processes while maintaining the specificity of each modality. The experimental results on a multi-spectral dataset demonstrate that our MMCAN model has achieved state-of-the-art performance. The method can be directly used on the pictures taken in the field without complex preprocessing. Our future goal is to adapt the algorithm to multi-object segmentation and generalize it to other multi-modal combinations. [ABSTRACT FROM AUTHOR]

The bile acid transport system is a natural physiological cycling process between the liver and the small intestine, occurring approximately 6–15 times during the day. There are various bile acid transporter proteins on hepatocytes that specifically recognize bile acids for transport. Therefore, in this paper, a novel liposome, cholic acid-modified irinotecan hydrochloride liposomes (named CA-CPT-11-Lip), was prepared based on the "Trojan horse" strategy. The liposomes preparation process was optimized, and some important quality indicators were investigated. The distribution of irinotecan hydrochloride in mice was then analyzed by high-performance liquid chromatography (HPLC), and the toxicity of liposomes to hepatocellular carcinoma cells (HepG-2) was evaluated in vitro. As a result, CA-CPT-11-Lip was successfully prepared. It was spherical with a particle size of 154.16 ± 4.92 nm, and the drug loading and encapsulation efficiency were 3.72 ± 0.04% and 82.04 ± 1.38%, respectively. Compared with the conventional liposomes (without cholic acid modification, named CPT-11-Lip), CA-CPT-11-Lip had a smaller particle size and higher encapsulation efficiency, and the drug accumulation in the liver was more efficient, enhancing the anti-hepatocellular carcinoma activity of irinotecan hydrochloride. The novel nanoliposome modified by cholic acid may help to expand the application of irinotecan hydrochloride in the treatment of hepatocellular carcinoma and construct the drug delivery system mode of drug liver targeting. [ABSTRACT FROM AUTHOR]

To avoid the problems of the conventional precast segmental bridge columns (PSBCs) such as the concrete crushing at column ends, joint openings between segments, and torsional deformation under seismic attacks, a novel type of precast segmental bridge column confined by a grouted steel tube (TPSBC) was proposed, and herein the axial compressive behavior of the TPSBCs was investigated by testing of 14 specimens. The main parameters of the tested specimens included the diameter-thickness ratios of the steel tubes, the number of the precast segments, reinforcement arrangements in the precast hollow segments, initial prestress levels, sandwich concrete strengths, and loading forms. The effects of the parameters on the failure modes, loading bearing capacity, ductility, and steel strain development of the specimens were evaluated. The test results indicate that the proposed TPSBCs with proper configurations exhibited desirable compressive behavior with significantly improved load bearing capacity and deformability compared with the PSBCs. Based on the analysis of the confinement effects, analytical models were developed for predicting the axial bearing capacity of the TPSBCs under the different loading forms. [ABSTRACT FROM AUTHOR]

A combination of short‐insert paired‐ended and mate‐pair libraries of large insert sizes is used as a standard method to generate genome assemblies with high contiguity. The third‐generation sequencing techniques also are used to improve the quality of assembled genomes. However, both mate‐pair libraries and the third‐generation libraries require high‐molecular‐weight DNA, making the use of these libraries inappropriate for samples with only degraded DNA. An in silico method that generates mate‐pair libraries using a reference genome was devised for the task of assembling target genomes. Although the contiguity and completeness of assembled genomes were significantly improved by this method, a high level of errors manifested in the assembly, further to which the methods for using reference genomes, was not optimized. Here, we tested different strategies for using reference genomes to generate in silico mate‐pairs. The results showed that using a closely related reference genome from the same genus was more effective than using divergent references. Conservation of in silico mate‐pairs by comparing two references and using those to guide genome assembly reduced the number of misassemblies (18.6%–46.1%) and increased the contiguity of assembled genomes (9.7%–70.7%), while maintaining gene completeness at a level that was either similar or marginally lower than that obtained via the current method. Finally, we developed a pipeline of the optimized in silico method and compared it with another reference‐guided assembler, RagTag. We found that RagTag produced longer scaffolds (17.8 Mbp vs 3.0 Mbp), but resulted in a much higher misassembly rate (85.68%) than our optimized in silico mate‐pair method. This optimized in silico pipeline developed in this study should facilitate further studies on genomics, population genetics, and conservation of endangered species. [ABSTRACT FROM AUTHOR]

In general relativity, an inertial frame can only be established in a small region of spacetime, and local inertial frames are mathematically represented by a tetrad field in gravity. The tetrad field is not unique due to the freedom to perform Lorentz transformations in local inertial frames, and there exists freedom to choose the local inertial frame at each spacetime point. The local Lorentz transformations are known as non-Abelian gauge transformations for the tetrad field, and to fix the gauge freedom corresponding to the Lorentz gauge ∂ μ A μ = 0 and the Coulomb gauge ∂ i A i = 0 in electrodynamics, the Lorentz gauge and Coulomb gauge for tetrad fields are proposed in the present work. Moreover, properties of the Lorentz gauge and the Coulomb gauge for tetrad fields are discussed to show their similarities to those in electromagnetic fields. [ABSTRACT FROM AUTHOR]

A series of γ-Al 2 O 3 supported gold-palladium (Au-Pd) alloy nanoparticles (NPs) catalysts were synthesized by a one-pot approach applying mercapto-propyl-trimethoxysilane (MPTMS) as an anchoring ligand. Homogeneously dispersed Au-Pd alloy NPs were observed on the prepared catalysts and their catalytic performance in benzyl alcohol partial oxidation was investigated. Results showed that the highest benzaldehyde yield was achieved on catalyst Au-Pd/7%MPTMS-γ-Al 2 O 3 with a benzaldehyde selectivity of 90%. By establishing the structure-performance relationship, the high activity of catalysts with MPTMS modification was attributed to the anchoring and dispersion effect of MPTMS on Au-Pd NPs, while the high benzaldehyde selectivity was due to the formation of more surface Lewis acid sites after introducing MPTMS, protecting the benzaldehyde from over-oxidation to byproducts. [Display omitted] • The presence of MPTMS led to well-dispersed Au-Pd alloy nanoparticles on alumina support. • The introduction of MPTMS produced more surface Lewis acid sites. • Lewis acid sites interacted with benzaldehyde, inhibiting over-oxidation and achieving high benzaldehyde selectivity. [ABSTRACT FROM AUTHOR]

Na3V2(PO4)3 (NVP) materials have emerged as prospective cathodes for sodium-ion batteries (SIBs). However, its weak intrinsic conductivity has limited deeper research. Herein, we adopt the strategy of simultaneous K/Co co-substitution and Ti3C2Tx MXene (MX) introduction to optimize NVP. The K/Co co-substitution brings about the synergetic effect of NVP framework stabilization. Doping Co2+ generates beneficial holes and accelerating electronic conductivity. The MX plates are stacked at random to form a porous construction, increasing the contact areas to provide more active sites for Na+ shuttling and buffering the volume change. Furthermore, the lamellar MX and the carbon layers form efficient conductive networks that increase electron migration. Notably, K0.1Na2.95V1.95Co0.05(PO4)3@MX (KC05@MX) exhibited an initial capacity of 116 mA h g−1 under 1 C with an extraordinary retention of 86.8% at the 400th cycle. It realized high performance under 20 C and 50 C, and the outputs were 93.5 and 82.4 mA h g−1 at the 1st cycle and 66.6 and 53.4 mA h g−1 at the 1000th cycle, respectively, with slight capacity loss at 0.028% and 0.035%. Furthermore, the Bi2Se3//KC05@MX asymmetric full cell expressed great electrochemical properties, indicating the superior practical application prospect of KC05@MX. [ABSTRACT FROM AUTHOR]

Energy saving in palletizing robot is a fundamental problem in the field of industrial robots. However, the palletizing robot often suffers from the problems of high energy consumption and lacking flexibility. In this work, we introduce a novel differential evolution algorithm to address the adverse effects caused by the instability of the initial trajectory parameters while reducing the energy. Specially, a simplified analytical model of the palletizing robot is firstly developed. Then, the simplified analytical model and the differential evolutionary algorithm are combined to form a planner with the goal of reducing energy consumption. The energy saving planner optimizes the initial parameters of the trajectories collected by the bionic demonstration system, which in turn enables a reduction in the operating power consumption of the palletizing robot. The major novelty of this article is the use of a differential evolutionary algorithm that can save the energy consumption as well as boosting its flexibility. Comparing with the traditional algorithms, the proposed method can achieve the state-of-the-art performance. Simulated and actual experimental results illustrate that the optimized trajectory parameters can effectively reduce the energy consumption of palletizing robot by 16%. [ABSTRACT FROM AUTHOR]

Streptococcus agalactiae (group B streptococcus, GBS), a broad-spectrum pathogen, causes great economic losses in fish aquaculture, especially the industry of tilapia. Until now, the knowledge of the immune response mechanism against S. agalactiae infection in tilapia has been limited. In the present study, the gill transcriptome of the tilapia from the GBS and the phosphate buffered saline (PBS) groups were sequenced. The transcriptomic analysis results presented the differentially expressed genes (DEGs) at different time points (DEGs number, 6 h: 2122, 9 h: 1851, 15 h: 1791, and 18 h: 2395) after GBS injection, and significantly enriched immune-related gene ontology (GO) terms such as the innate immune response. The significantly enriched immune pathways included the Toll-like receptor signaling pathway, the nucleotide oligomerization domain (NOD)-like receptor signaling pathway, the cytosolic-DNA sensing pathway, and the intestinal immune network for Immunoglobulin A (IgA) production. Most of the DEGs in Toll-like receptor signaling, NOD-like receptor signaling, and cytosolic-DNA sensing pathways presented upregulations at 18 h, which indicated that the innate immune pathways were activated. Two immune-related pathways (phagosome and cell adhesion molecules) were significantly enriched at all time points, suggesting that these two pathways might also play important roles in the immune response against the GBS infection. The results of HE staining showed that the gills of tilapia were damaged seriously at 9 h post-infection, which might be due to the possibility of pyroptosis resulting from the changes of DEGs in the NOD-like receptor signaling pathway. This study provided new insight into the mechanisms of gill damage in fish infected with S. agalactiae. [ABSTRACT FROM AUTHOR]

We probed the anatase (101) surface irradiated by near-infrared and infrared photons in different ambient gases by monitoring the surface lattice phonon mode using sum-frequency spectroscopy. We found that even under the irradiation of such low energy photons, the stability of surface oxygen vacancies, in comparison to sub-surface oxygen vacancies, can increase sensibly. The variation of this surface phonon mode is also in accordance with the photo-induced hydrophilicity of titanium oxide surfaces, which may provide the microscopic insight into this phenomenon. [ABSTRACT FROM AUTHOR]

Context: Testing patients for estrogen-receptor (ER) expression has become an important factor in the prognosis and prediction of breast cancer. Many studies have shown that endocrine therapy has no benefit for breast-cancer patients with low ER (ER+) expression, in which the proportion of positively stained cells is 1% to 9%.Objective: The study intended to explore the response to endocrine therapy of ER+ breast-cancer patients and to evaluate the benefits of the clinical use of endocrine therapy for treatment.Design: The research team designed a retrospective analysis and reviewed the data and survival rates of patients with early breast cancer.Setting: The study took place at the Hebei Breast Disease Clinic at the Fourth Hospital of Hebei Medical University in Shijiazhuang, China.Participants: Eligible participants in the study were 862 patients were diagnosed at and admitted to the clinic with early, nonadvanced breast cancer between January and December 2012.Outcome Measures: Based on ER-expression levels, participants were divided into ER negative (ER-), which indicates no positive staining of cells; ER+; and ER positive (ER++)-high expression in which the proportion of positively stained cells is ≥10%. The clinicopathological characteristics and the survival rates of the three groups were compared.Results: The clinicopathological features were similar for the ER- and ER+ groups. Compared to participants in the ER++ group, participants in the ER+ group: (1) were in an earlier stage, (2) had larger tumors, (3) were more likely to be positive for human epidermal growth factor receptor-2 (HER-2), (4) had a higher expression rate of Ki-67, (5) had a lower progesterone-receptor (PR) expression rate, (6) were more likely to receive chemotherapy, and (7) were less likely to receive endocrine therapy. Regardless of whether a participant received endocrine therapy or not, the seven-year overall survival (OS) between the ER- group and the ER+ group showed no significant difference, but both were in a worse condition than the ER++ group (P = .026).Conclusions: The current study found that the clinicopathological features of ER+ breast cancers were different from those of ER++ breast cancers and similar to those of ER-negative breast cancers. The benefits of endocrine therapy for ER+ breast-cancer patients weren't obvious. [ABSTRACT FROM AUTHOR]

As the number of elderly patients with dementia is increasing year by year, accompanying products for the elderly with dementia are becoming more and more important. Senile dementia has become a major disease that affects countries around the world and, at the same time, it has brought enormous pressure on social care. Therefore, this research aims to obtain a new set of design methods for dementia elderly care products by introducing the combination of AHP and fuzzy evaluation methods and applying them to design examples. And then break through the existing design path of accompanying products for the elderly with dementia, and relieve the social burden. This study takes the intelligent care robot for the elderly with dementia as an example. Due to the particularity of user groups, this article proposed a design method for elderly care products that integrates mathematical theoretical models. This design method is convenient for designers to have a more accurate data reference when designing and positioning, and summarizing the supporting product design scheme that can better meet the actual needs of the elderly with dementia. Through SET factors to analyze the driving force of demand for dementia elderly care products, and combined with a questionnaire survey to establish the design requirements of dementia elderly care products for analysis of hierarchy process, it effectively defines the design demand attributes of dementia elderly intelligent care robots. The research results are applied to the design of the intelligent accompanying care robot for the demented elderly, the comprehensive fuzzy evaluation of the design scheme is carried out, and the direction of further optimization of the scheme is obtained. This article proposed a design method for accompanying care products for the elderly with dementia by combining F-AHP (Fuzzy Comprehensive Evaluation Method and Analytic Hierarchy Process). This design method is based on a rigorous mathematical theoretical model. Compared with the traditional design method, this research focused on quantitative analysis and evaluation of the actual design requirements of the dementia elderly care products and had more accurate design priority data reference in the scheme design. The research results show that based on the combination of F-AHP, this article redefines the design path of accompanying products for the elderly with dementia, and concludes that the functions that need to be improved and optimized in the future of intelligent accompanying robots for the elderly with dementia are mainly: executive ability training, computing ability training, and observation ability training. At the same time, the design process of the intelligent escort robot for the elderly with dementia can also be applied to the design of intelligent elderly products, which can improve the service experience of intelligent elderly products in a targeted manner. [ABSTRACT FROM AUTHOR]