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Simple Summary: The dark black chafer, Holotrichia parallela Motschulsky (Coleoptera: Scarabaeidae), is an important subterranean insect in China due to its wide distribution and the high degree of damage it causes. Selecting stable reference genes is crucial for accurate quantitative polymerase chain reaction (qPCR) and gene expression analysis. This study evaluated the expression stability of 11 candidate reference genes in H. parallela under various biological conditions and environmental stresses. Our findings suggest that the optimum reference genes were as follows: RPL18 and RPL13a for developmental stages and RNAi conditions, RPL13a, RPL18, and RPL32 for female and male adults, RPL13a and RPS3 for different tissues, RPL32, RPL13a, and RPS3 for varying photoperiod conditions, and Actin and RPL13a for different temperatures. These discoveries will serve as a foundation for subsequent precise qPCR and gene expression studies in H. parallela and other closely related insect species. Holotrichia parallela is among the world's most destructive pests. For accurate qPCR and gene expression studies, the selection of stable and appropriate reference genes is crucial. However, a thorough evaluation of potential reference genes for use in H. parallela research is lacking. In this study, 11 reference genes (GAPDH, RPL32, RPL7A, RPS18, RPL13a, RPL18, Actin, RPS7, RPS3, VATB,and EF1A) were evaluated under different biological conditions and environmental stresses. The stability of 11 potential reference gene transcripts was evaluated through various computational tools, including geNorm, BestKeeper, NormFinder, theΔCt method, and the RefFinder program. Under various developmental stages and RNAi conditions, RPL18 and RPL13a exhibited the greatest stability. RPL13a, RPL18, and RPL32 were the most stable genes in both male and female adults. Under differing tissue conditions, RPL13a and RPS3 stood out as the most reliable. Moreover, under varying photoperiod conditions, RPL13a, RPS3 and RPL32 were the most stable genes. Lastly, Actin and RPL13a were the most stable genes across different temperatures. These findings offer essential criteria for selecting suitable reference genes across diverse experimental settings, thereby establishing a solid basis for accurate gene expression studies in H. parallela using RT-qPCR. [ABSTRACT FROM AUTHOR]

Nitrile Butadiene Rubber (NBR) is widely used as a sealing material due to its excellent mechanical properties and good oil resistance. However, when using NBR material, the seal structure is unable to avoid the negative effects of rubber aging. Hence, the influence of oil and thermal aging on the characteristics of NBR seals was studied by coupling the mechanical behavioral changes with the tribological behavioral changes of NBR in oil and the thermal environment. For this paper, aging testing and compression testing of NBR were carried out. Additionally, friction testing between friction pairs under different aging times was carried out. The surface morphology of the NBR working surface under different aging conditions was also observed. Finally, coefficients of different test conditions were introduced into the finite element model of NBR seals. It can be seen from the results that the elastic modulus increased with the increase in aging time in the thermal oxidative aging testing. The elastic modulus after 7 days of thermal oxidative aging increased by 135.45% compared to the unaged case, and the elastic modulus after 7 days of oil aging increased by 15.03% compared to the unaged case. The compression set rate of NBR increased significantly with the increase in aging time and temperature. The coefficient of friction (COF) between friction pairs increased first and then decreased with the increase in aging time. The maximum contact pressure decreased by 2.43% between the shaft and sealing ring and decreased by 4.01% between the O-ring and groove. The proportion of the effective sealing area decreased by 3.05% between the shaft and sealing ring and decreased by 6.11% between the O-ring and groove. Furthermore, the sealing characteristics between the O-ring and groove were better than those between the shaft and sealing ring. [ABSTRACT FROM AUTHOR]

Phase-change cold storage technology is recommended as a solution for energy conservation and carbon neutrality in air conditioning systems of buildings. This study focuses on the development of binary composite phase-change materials comprising octanoic acid–tetradecanol (OA-TD). To enhance its thermal conductivity, expanded graphite (EG) was employed as an additive carrier, and the surface modification of EG particles using hexadecyltrimethoxysilane (HDTMOS) was attempted to make up for the instability and further to improve the performance of OA-TD/EG CPCMs. The OA-TD/EG-HDTMOS CPCMs were synthesized by EG mixed with EG-HDTMOS at a 1:1 mass ratio. The thermal performance and stability of the OA-TD/EG-HDTMOS CPCMs were thoroughly evaluated by multi-cycle melting–solidification and thermal conductivity measurements. The results revealed that the OA-TD mixture, when at a mass ratio of 77:23, exhibited a phase-transition temperature of 11.4 °C and a latent heat ranging from 150 to 155 J/g. Then, the OA-TD/EG-HDTMOS composite material, at a 12:1 mass ratio of OA-TD to EG-HDTMOS, solidified and melted at temperatures of 9.2 °C and 11.2 °C, with a latent heat ranging from 138 to 143 J/g, and significantly improved the thermal conductivity to 0.7 W/(m·K), representing a remarkable 133% increase compared to that of OA-TD alone. Even after undergoing 100 melting–solidification cycles, the OA-TD/EG-HDTMOS maintained superior phase-change thermal performance and stability, making it suitable for cold storage and energy conservation in air conditioning. [ABSTRACT FROM AUTHOR]

An electrochemical CO2 reduction reaction (CO2RR) is an effective way to reduce greenhouse gases by converting CO2 into high-value-added chemical products using electricity generated from renewable energy. In this paper, a Cu2O spherical catalyst was prepared by ascorbic acid reduction. The precipitated Cu-Ag spherical catalyst (P-CuO-Ag) was successfully prepared by calcining Cu2O-Ag with the introduction of an Ag component as the substrate. During the electrochemical reduction of CO2, the FE of the P-CuO-Ag catalyst for C2H4 at a potential of −1.1 V vs. RHE was as high as 39.8%, which was nearly twice that of the CuO catalyst, while the local current density JC2H4 for C2H4 reached 6 mA cm−2. The incorporation of Ag gives the spherical CuO catalyst higher electrochemical activity and better kinetic performance than the catalyst without Ag. [ABSTRACT FROM AUTHOR]

Chua's circuit is a well-established model for studying chaotic phenomena and is extensively implemented in fields like encrypted communication. However, a traditional Chua's circuit has large volume, high component precision requirements and limited adjustable parameter range, which are not conducive to application. In order to solve these problems, we propose an improved implementation of Chua's circuit on an active inductor and non-autonomous system. First, we adopt the strategy of using active inductors instead of traditional passive inductors, achieving the miniaturization of the circuit and improving the accuracy of inductance. In addition, we present the theory of substituting non-autonomous systems for classical autonomous systems to reduce the requirements for the accuracy of components and improve the robustness of the circuit. Lastly, we connect the extension resistor in parallel with Chua's diode to optimize circuit structure, thereby increasing the range of the adjustable parameter. Based on the three improvements above, experiments have shown that the average maximum error tolerance of components of our improved design has been increased from 1.88% to 7.38% when generating a single vortex, and from 4.73% to 12.61% when generating a double vortex, compared with the traditional Chua's circuit. The range of the adjustable parameter has been increased by 195.83% and 36.98%, respectively, when generating a single vortex and double vortex. In summary, our improved circuit is more practical than the traditional Chua's circuit and has good application value. [ABSTRACT FROM AUTHOR]

The construction of community elderly care facilities (CECF) is pivotal for promoting healthy aging and "aging in place" for older people. This study focuses on the low utilization rates of community elderly care facilities in the Dongcheng and Xicheng Districts, core areas of Beijing. The explainable machine learning method is used to analyze data across three dimensions: the elderly's individual attributes, characteristics of the community elderly care station (CECS), and features of the built environment around CECS and subdistrict, to identify the important factors that influence the usage frequency of overall CECS and its different functional spaces, and also the correlation between factors and usage frequency of CECS. It shows that the most important factors are the features of CSCF, including the degree of space acceptance and satisfaction with services provided, which influence the usage frequency of nine functional spaces (R2 ≥ 0.68) and overall (R2 = 0.56). In addition, older people's individual factors, such as age and physical condition, significantly influence the usage of specific spaces such as rehabilitation therapy rooms and assistive bathing rooms. The influence of built environment characteristics is relatively low, with factors such as the density of bus stations and housing prices within the subdistrict and the mean distance from CECF to the nearest subway stations being more important. These findings provide a reference for the construction of indoor environments, management of service quality, and optimal site selection for future community elderly care facilities. [ABSTRACT FROM AUTHOR]

Nano silica (NS) has been found to have a positive impact on enhancing the microporous structure of Ultra-High-Performance Concrete (UHPC). However, there is a lack of effective methods to accurately characterize the regulatory improvement mechanism of NS on the pore structure of UHPC. In this study, our objective is to investigate the influence of NS on various characteristic parameters of the pore structure in UHPC, including porosity, average pore size, box fractal dimension, and multifractal spectral parameters. To analyze these effects, we employ a combination of X- CT image processing techniques and fractal theory. Furthermore, we conducted regression analysis using linear functions to explore the correlation between these parameters and the 28d compressive strength of UHPC. The experimental results demonstrate that NS promotes the refinement of matrix pore size, leading to a denser microstructure of the matrix. Fractal analysis revealed that the pore structure of NS-modified UHPC exhibited favorable fractal characteristics. The fractal dimension and multiple fractal parameters provided complementary insights into the pore structure of NS-modified UHPC from different perspectives. The fractal dimension described the global information, indicating that NS improved matrix defects and reduced the complexity of the pore structure. On the other hand, the multiple fractal parameters supplemented local information, highlighting how the increase in micropores contributed to the heterogeneity of the pore structure. The results of the correlation analysis indicate that the developed mathematical model has a good fit with the 28d compressive strength of UHPC. [ABSTRACT FROM AUTHOR]

Aluminosilicates, abundant and crucial in both natural environments and industry, often involve uncontrollable chemical components when derived from minerals, making further chemical purification and reaction more complicated. This study utilizes pure alumina and fumed silica powders as more controllable sources, enhancing aluminosilicate reactivity through room temperature (non-firing) processing and providing a robust framework that resists mechanical stress and high temperature. By embedding iron-based metal–organic frameworks (Fe-MOF/non-firing aluminosilicate membranes) within the above matrix, these ceramic membranes not only preserve their mechanical robustness but also gain significant chemical functionality, enhancing their capacity to removing phytochromes from the vegetables. Sodium hydroxide and sodium silicate were selected as activators to successfully prepare high-strength, non-firing aluminosilicate membranes. These membranes demonstrated a flexural strength of 8.7 MPa under wet-culture conditions with a molar ratio of Al2O3:SiO2:NaOH:Na2SiO3 at 1:1:0.49:0.16. The chlorophyll adsorption of spinach conducted on these membranes showed a removal rate exceeding 90% at room temperature and pH = 9, highlighting its potential for the selective adsorption of chlorophyll. This study underscores the potential of MOF-enhanced aluminosilicate ceramic membranes in environmental applications, particularly for agricultural pollution control. [ABSTRACT FROM AUTHOR]

In space laser communication, the wide divergence angle of beacon light leads to substantial spatial losses, compounded by background light and detector noise; this results in compromised precision in the detection of the beacon light position. To solve this problem, a high-precision detection technique and communication composite technology employing a four-quadrant detector (QD) with beacon spread-spectrum modulation are proposed. Pseudo-random sequences (PRNs) are employed to spread the beacon communication spectrum, with the spread-spectrum signal utilized to modulate the intensity of the transmitted beacon light at the transmitter end. At the receiver, QD photocurrent signals are cross-correlated with an identical PRN that is used for modulation. The strong auto-correlation properties of PRNs, which are uncorrelated with noise, enhance the output signal-to-noise ratio (SNR), enabling precise position detection and beacon communication under high-SNR conditions. Theoretical analysis is used to explore the effects of spreading gain on the sensitivity of system detection and the precision of position detection. The experimental results demonstrate that the beacon spread-spectrum modulation scheme effectively detects the position of the light spot. At a received optical power of −37 dBm and spreading sequence PRN depths of 1023, 127, and 31, the root-mean-square error (RMSE) values are 0.983 μm, 2.876 μm, and 7.275 μm, respectively. This corresponds to improvements of 14.96 dB, 10.29, dB, and 6.26 dB compared to direct detection precision (30.811 μm). Additionally, under an identical signal bandwidth, the sensitivity improves by 14.6 dB, 10.1 dB, and 6.4 dB, respectively. The proposed beacon spread-spectrum scheme mitigates the limitations of hardware reception sensitivity and position-detection precision, demonstrating its potential application in high-precision detection in long-distance interstellar laser communication. [ABSTRACT FROM AUTHOR]

Simple Summary: The fate and development of birds largely depend on their reproductive strategies, which vary, either diverging or converging among different species and populations. We studied the reproductive strategies of White-rumped Shama (Copsychus malabarica) and Oriental Magpie Robin (C. saularis), which may be convergent because of their kin relationships or divergent because of niche differentiation under sympatric competition. We observed that they differed in certain reproductive strategies, such as nest-site selection and egg incubation patterns, but were similar in others, including nestling heating, sexual synchronization in nestling feeding, and coordination of nestling feeding and nest cleaning. Reproduction plays a crucial role in determining the development, fate, and dynamics of bird populations. However, reproductive strategies vary among species and populations. In this study, we investigated the reproductive strategies of the Oriental Magpie Robin (Copsychus saularis) and White-rumped Shama (C. malabarica), which are closely related passerines that reproduce in sympatric areas. We found that although these two species were both cavity nesting, their nest-site selection differed; the Shama preferred nesting close to trees and forests, whereas the Magpie Robin nested close to human residential areas. Furthermore, their egg incubation patterns differed; the Shama increased daily incubation frequency with incubation time, but the Magpie Robin maintained its daily incubation time regardless of changes in incubation frequency. However, the nestling heating patterns of these two species were similar, indicating a critical demand for regulating hatchling body temperature during this crucial stage. The feeding frequencies of male parents were strongly correlated with those of females in both species, suggesting equal contribution and good synchronization between the sexes. Nestling feeding frequency was also correlated with nest cleaning frequency, implying coordination between feeding and defecation by parents and offspring, respectively. This research explored the divergence and convergence of reproductive strategies between these two sympatric species, providing valuable insights into the niche differentiation theory. [ABSTRACT FROM AUTHOR]

Free space optical communication is developing towards laser communication networking. A novel method of quadrant detector (QD) multi-spot position detection based on orthogonal frequency division multiplexing (OFDM) is proposed for multi-spot laser communication systems. The mathematical model is constructed, and the Monte Carlo method is used to validate it. The position calculation of three beams incident on QD is simulated. The influence of key parameters on the accuracy of position detection is analyzed when the spots are at the same position and a different position. The results show that when the SNR of the system is 31.74 dB, the radius of the Gauss spot is 2 mm, the number of FFT (fast Fourier transform) points is 1024, and the center of the multi-spot is at the same position of the detector target; the accuracy of signal position detection calculated by the equation is 1.433 μm, and the simulation results are 1.351 μm, 1.354 μm, and 1.389 μm, respectively. When the center position of the multi-spot is at different positions of the detector target, the detection accuracy calculated by the formula is 1.438 μm, 1.433 μm, and 1.434 μm, respectively, and the simulation results are 1.419 μm, 1.387 μm, and 1.346 μm, respectively. The experimental results verify the effectiveness of the proposed multi-target simultaneous detection method. This article proposes a new multi-spot position detection method which can not only achieve one-to-multiple node laser communication but also improve the accuracy of point position detection. [ABSTRACT FROM AUTHOR]

Scale variation presents a significant challenge in object detection. To address this, multi-level feature fusion techniques have been proposed, exemplified by methods such as the feature pyramid network (FPN) and its extensions. Nonetheless, the input features provided to these methods and the interaction among features across different levels are limited and inflexible. In order to fully leverage the features of multi-scale objects and amplify feature interaction and representation, we introduce a novel and efficient framework known as a multi-resolution and semantic-aware bidirectional adapter (MSBA). Specifically, MSBA comprises three successive components: multi-resolution cascaded fusion (MCF), a semantic-aware refinement transformer (SRT), and bidirectional fine-grained interaction (BFI). MCF adaptively extracts multi-level features to enable cascaded fusion. Subsequently, SRT enriches the long-range semantic information within high-level features. Following this, BFI facilitates ample fine-grained interaction via bidirectional guidance. Benefiting from the coarse-to-fine process, we can acquire robust multi-scale representations for a variety of objects. Each component can be individually integrated into different backbone architectures. Experimental results substantiate the superiority of our approach and validate the efficacy of each proposed module. [ABSTRACT FROM AUTHOR]

Spam detection has been a topic of extensive research; however, there has been limited focus on multimodal spam detection. In this study, we introduce a novel approach for multilingual multimodal spam detection, presenting the Multilingual and Multimodal Spam Detection Model combining Text and Document Images (MMTD). Unlike previous methods, our proposed model incorporates a document image encoder to extract image features from the entire email, providing a holistic understanding of both textual and visual content through a single image. Additionally, we employ a multilingual text encoder to extract textual features, enabling our model to process multilingual text content found in emails. To fuse the multimodal features, we employ a multimodal fusion module. Addressing the challenge of scarce large multilingual multimodal spam datasets, we introduce a new multilingual multimodal spam detection dataset comprising over 30,000 samples, which stands as the largest dataset of its kind to date. This dataset facilitates a rigorous evaluation of our proposed method. Extensive experiments were conducted on this dataset, and the performance of our model was validated using a five-fold cross-validation approach. The experimental results demonstrate the superiority of our approach, with our model achieving state-of-the-art performance, boasting an accuracy of 99.8% when compared to other advanced methods in the field. [ABSTRACT FROM AUTHOR]

The objectives of this study were to investigate the effect of different dietary lipid levels on the serum biochemistry, antioxidant responses, initial immunity, and mTOR pathway of juvenile genetic improvement-farmed tilapia (GIFT, Oreochromis niloticus). Six groups of the juveniles (initial body weight 20.66 ± 1.33 g) in triplicate were fed for 90 days using six iso-nitrogen diets with different lipid levels (0.35%, 3.35%, 6.35%, 9.35%, 12.35%, and 15.35%). The main results were as follows: Compared with the control group (0.35%), the diets with different lipid supplementation significantly improved (p < 0.05) the contents of total protein (TP), albumin (ALB), globulin (GLB), glucose (GLU), triglyceride (TG), total cholesterol (T-CHO), high-density lipoprotein (HDL), low-density lipoprotein (LDL), total antioxidant capacity (T-AOC), malondialdehyde (MDA), complement 3 (C3), and immunoglobulin M (IgM), the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT), lysozyme (LYZ), and alkaline phosphatase (ALP), the expression level of phosphatidylinositol-3-kinase (PI3K), Akt protein kinase B (Akt), and mammalian target of rapamycin (mTOR) genes in juvenile tilapia. However, diets with different lipid supplementation significantly reduced (p < 0.05) the expression level of tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) genes of juvenile tilapia. In conclusion, the with different lipid supplementation could significantly affect the serum biochemistry, antioxidant responses, initial immunity, and mTOR pathway of juvenile tilapia. [ABSTRACT FROM AUTHOR]

The phenomenon of population aging in rural China presents a compelling societal challenge, necessitating a growing demand for both the quantity and quality of facilities supporting the needs of older people. However, a lack of comprehensive understanding concerning the underlying mechanisms that drive the emergence of these facilities, coupled with the distinctive historical backdrop and social development stage of the nation, engenders complexities in achieving sustainable rural eldercare services. This paper endeavors to comprehensively elucidate diverse eldercare facility types in rural China, delineating their intrinsic characteristics and prerequisites for construction. Additionally, the research delves into the political and economic contexts and advancements in healthcare and eldercare services, culminating in the formulation of an integrated framework that interconnects eldercare support patterns with the political landscape and public service provisions. The implications derived from this nuanced framework provide insightful reflections on significant historical transitions, intricacies faced by rural eldercare facilities, and strategic pathways for fostering future eldercare service delivery systems and allied facilities. The paper's findings furnish insights for bolstering the well-being of the aging population in rural China and lay a substantive foundation for addressing the evolving requisites of eldercare within this distinctive context. [ABSTRACT FROM AUTHOR]

Holotrichia parallela is an important plant pest. Comparative feeding experiments showed that the egg production, oviposition duration and survival rate of H. parallela beetles were significantly higher when they fed on elm leaves than when they fed on willow or purpus privet leaves. RNA sequencing was used to determine transcriptomic changes associated with oviposition. Comparative transcriptome analysis revealed that the beetles that fed on elm and willow had a total of 171 genes with differential expression. When the beetles fed on elm and purpus privet, 3568 genes had differential expression. The vitellogenesis, ovarian serine protease, odorant-binding proteins, acyl-CoA synthetase and follicle cell proteins were commonly upregulated genes in elm-fed beetles compared with those fed on willow/purpus privet leaves. The involvement of the follicle cell protein 3C gene in the regulation of oviposition was confirmed using RNA interference. The results provide insights into the molecular mechanisms underlying oviposition in H. parallela feeding on different host plants. This study also describes a method for identifying potentially effective genes for pest control. [ABSTRACT FROM AUTHOR]

Synchronous generators with three phases are crucial components of modern integrated power systems in ships. These generators provide power for the entire operation of the vessel. Therefore, it is of paramount importance to diagnose short-circuit faults at the generator terminal in the ship's power system to ensure the safe and stable operation of modern ships. In this study, a generator terminal short-circuit fault diagnosis method is proposed based on a hybrid model that combines the Multi-Level Wavelet Decomposition Network, Deep-Gated Recurrent Neural Network, and Fully Convolutional Network. Firstly, the Multi-Level Wavelet Decomposition Network is used to decompose and denoise the collected electrical signals, thus dividing them into sub-signals and extracting their time-domain and frequency-domain features. Secondly, synthetic oversampling based on Gaussian random variables is employed to address the problem of imbalance between normal data and fault data, resulting in a balanced dataset. Finally, the dataset is fed into the hybrid model of the Deep-Gated Recurrent Neural Network and Fully Convolutional Network for feature extraction and classification of faults, ultimately outputting the fault diagnosis results. To validate the performance of the proposed method, simulations and comparative analysis with other algorithms are conducted on the fault diagnosis method. The proposed algorithm's accuracy reaches 96.82%, precision reaches 97.35%, and the area under curve reaches 0.85, indicating accurate feature extraction and classification for identifying short-circuit faults at the generator terminals. [ABSTRACT FROM AUTHOR]

In swarm-robotics foraging, the purpose of task allocation is to adjust the number of active foraging robots dynamically based on the task demands and changing environment. It is a difficult challenge to generate self-organized foraging behavior in which each robot can adapt to environmental changes. To complete the foraging task efficiently, this paper presents a novel self-organized task allocation strategy known as the dynamic response threshold model (DRTM). To adjust the behavior of the active foraging robots, the proposed DRTM newly introduces the traffic flow density, which can be used to evaluate the robot density. Firstly, the traffic flow density and the amount of obstacle avoidance are used to adjust the threshold which determines the tendency of a robot to respond to a stimulus in the environment. Then, each individual robot uses the threshold and external stimulus to calculate the foraging probability that determines whether or not to go foraging. This paper completes the simulation and physical experiments, respectively, and the performance of the proposed method is evaluated using three commonly used performance indexes: the average deviation of food, the energy efficiency, and the number of obstacle avoidance events. The experimental results show that the DRTM is superior to and more efficient than the adaptive response threshold model (ARTM) in all three indexes. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing utilization of lightweight engineered cementitious composites (LECC) for the reinforcement and restoration of contemporary building structures. This study focuses on the incorporation of zeolite, serving as an internal reservoir for moisture maintenance, and examines its impact on various performance indicators, including apparent density, compressive strength, tensile strength, and autogenous shrinkage. Additionally, the influence of zeolite on the tensile and ductile properties of LECC is elucidated with the aid of scanning electron microscopy (SEM). The findings reveal that the addition of zeolite enables the preservation of excellent mechanical properties of LECC while further reducing its density. Notably, the introduction of a substantial amount of zeolite leads to a decrease in matrix density, average crack width, and ultimate tensile strain. The ultimate tensile strain exceeds 8% to reach 8.1%, while the decrease in compressive and tensile strengths is marginal. Zeolite's internal curing capability facilitates the complete hydration of unhydrated cement, concurrently alleviating the autogenous shrinkage of LECC. Consequently, the durability and reliability of the material are enhanced. The ability of zeolite, with its porous framework structure, to significantly improve the ultimate tensile strain of the matrix can be attributed to the amplified occurrence of active defects and a shift in the pull-out mode of PE fibers from "pull-out" to "pull-through". This study presents a promising alternative material in the field of engineering, holding potential for diverse building and infrastructure projects, as it enhances their durability and reliability. [ABSTRACT FROM AUTHOR]

Using machine learning methods to estimate brain effective connectivity networks from functional magnetic resonance imaging (fMRI) data has garnered significant attention in the fields of neuroinformatics and bioinformatics. However, existing methods usually require retraining the model for each subject, which ignores the knowledge shared across subjects. In this paper, we propose a novel framework for estimating effective connectivity based on an amortization transformer, named AT-EC. In detail, AT-EC first employs an amortization transformer to model the dynamics of fMRI time series and infer brain effective connectivity across different subjects, which can train an amortized model that leverages the shared knowledge from different subjects. Then, an assisted learning mechanism based on functional connectivity is designed to assist the estimation of the brain effective connectivity network. Experimental results on both simulated and real-world data demonstrate the efficacy of our method. [ABSTRACT FROM AUTHOR]

A new prediction method was proposed based on the positive feedback relationship between tool geometry and tool wear rate. Dry orthogonal cutting of Inconel 718 was used as a case study. Firstly, tool wear rate models and a tool wear prediction flowchart were proposed. Secondly, the evolution of the tool geometry during tool wear was analyzed considering the combined effect of tool crater wear and tool flank wear. Thirdly, the evolution of the cutting temperature, normal stress and tool–chip relative sliding velocity on the tool wear surface was studied, the evolution of the tool wear rate during tool wear was revealed. Finally, the evolution of the tool geometry and tool wear rate during tool wear were applied to the tool wear prediction method to accurately predict the tool wear. The prediction error of KT is less than 15% in comparison with the experimental results. The tool wear prediction method in this paper is helpful to improve the prediction accuracy of tool crater wear. [ABSTRACT FROM AUTHOR]

The moistening impact of El Niño on the tropical lower stratosphere has been extensively studied, yet a long-standing challenge is its potential nonlinearities regarding the strength of El Niño. Extreme El Niño's hydration in 2015/2016 was unprecedented in the satellite era, providing a great opportunity to distinguish the differential response of water vapor to extreme and moderate El Niño. Using ERA5 and MERRA-2 reanalysis data from 1979–2019, we compare the composite tropical lower stratospheric water vapor anomalies throughout all extreme and moderate El Niño episodes since the satellite era. We validate the variations in the lower stratospheric water vapor during the two distinct El Niño episodes using a three-dimensional chemistry transport model simulating the same period. The model reproduces the observed pattern in lower stratospheric water vapor. Both demonstrate that robust moistening during extreme El Niño events occurs throughout the tropical lower stratosphere. However, moderate El Niño events seem to have a weak effect on lower stratospheric water vapor. In comparison to moderate El Niño, the strong convective activities induced by extreme El Niño release large amounts of latent heat, causing extensive and intense warming in the tropical upper troposphere and lower stratosphere, thus greatly increasing the water vapor content in the tropical lower stratosphere. Additionally, moderate El Niño events have strong seasonality in their hydration effect in the tropics, whereas the intense moistening effect of extreme El Niño events prevails in all seasons during their episodes. [ABSTRACT FROM AUTHOR]

Alluvial fans are an important land resource with agricultural potential in Qinghai–Tibet Plateau. The spatiotemporal variation in land use/cover is an important indicator to understand the value of alluvial fans and protect and make scientific use of such fans. In this study, the spatiotemporal characteristics of land use/cover are determined by analysing the land use/cover changes of alluvial fans in the Lhasa River Basin (LRB) at different times, counties/districts, altitudes, and gradients. Results show that the area of cultivated land and the artificial land provided by alluvial fans for LRB has continuously increased. In 2000, 2010, and 2020, 17.72%, 21.84%, and 24.17% of cultivated land and 7.89%, 7.51%, and 25.24% of artificial land in LRB were provided by alluvial fans, respectively. At all altitudes and slopes, cultivated land and artificial land are increasing but the increasing part is basically due to the massive loss of grassland. The spatiotemporal changes in all land use/cover types of alluvial fans were dominated by human activities, although they were also influenced by natural factors to some degree. [ABSTRACT FROM AUTHOR]

Stimuli-responsive drug release and photodynamic therapy (PDT) have aroused extensive attention for their enormous potential in antitumor treatment. pH-responsive drug delivery systems (PFE-DOX-1 and PFE-DOX-2) based on water-soluble conjugated polymers were constructed in this work for high-performance synergistic chemo-/PDT therapy, in which the anticancer drug doxorubicin (DOX) is covalently attached to the side chains of the conjugated polymers via acid-labile imine and acylhydrazone bonds. Concurrently, the intense fluorescence of poly(fluorene-co-ethynylene) (PFE) is effectively quenched due to the energy/electron transfer (ET) between the PFE-conjugated backbone and DOX. Effective pH-responsive drug release from PFE-DOX-2 is achieved by the cleavage of acylhydrazone linkages in the acidic tumor intracellular microenvironment. Additionally, the drug release process can be monitored by the recovered fluorescence of conjugated polymers. Furthermore, the conjugated polymers can produce reactive oxygen species (ROS) under light irradiation after drug release in an acidic environment, which prevents possible phototoxicity to normal tissues. It is noted that PFE-DOX-2 demonstrates remarkable antitumor cell performance, which is attributed to its efficient cell uptake and powerful synergistic chemo-/PDT therapeutic effectiveness. This report thus provides a promising strategy for in vivo anticancer treatment with the construction of a stimuli-responsive multifunctional drug delivery system. [ABSTRACT FROM AUTHOR]

Accurate load forecasting is conducive to the formulation of the power generation plan, lays the foundation for the formulation of quotation, and provides the basis for the power management system and distribution management system. This study aims to propose a high precision load forecasting method. The power load forecasting model, based on the Improved Seagull Optimization Algorithm, which optimizes SVM (ISOA-SVM), is constructed. First, aiming at the problem that the random selection of internal parameters of SVM will affect its performance, the Improved Seagull Optimization Algorithm (ISOA) is used to optimize its parameters. Second, to solve the slow convergence speed of the Seagull Optimization Algorithm (SOA), three strategies are proposed to improve the optimization performance and convergence accuracy of SOA, and an ISOA algorithm with better optimization performance and higher convergence accuracy is proposed. Finally, the load forecasting model based on ISOA-SVM is established by using the Mean Square Error (MSE) as the objective function. Through the example analysis, the prediction performance of the ISOA-SVM is better than the comparison models and has good prediction accuracy and effectiveness. The more accurate load forecasting can provide guidance for power generation and power consumption planning of the power system. [ABSTRACT FROM AUTHOR]

Simple Summary: No previous studies have focused on pain perception and management in intensively raised dairy cattle in China. The results of this survey study show that severely painful conditions such as parturition and fracture have the highest score in pain perception. Pain perception is highly associated with pain management willingness. To promote animal welfare and reduce unnecessary production losses, training in pain perception and management should be emphasised. Pain in dairy cattle is gaining attention globally. This study investigated the current attitudes of Chinese dairy practitioners to pain and its management in intensively raised dairy cattle. A total of 465 valid questionnaires with 26 painful conditions scored on numerical rating scales were collected from dairy practitioners. Data were analysed by descriptive statistics, analysis of variance, principal component analysis, and multivariate regression models. Dystocia was perceived as the most painful, while mild mastitis with milk changes only was perceived as the least painful. Respondents who agreed with the statement "pain management is worthwhile" tended to give a higher pain score. Young respondents (≤23 years old) and those from farms with ≤1000 cattle had lower pain scores for conditions with severe pain and low variability but higher pain scores for conditions with less severe pain and high variability, whereas highly educated respondents had consistently lower pain scores. As for pain management, older respondents (≥24 years old) tended to choose non-steroidal anti-inflammatory drugs, and farms with >1000 cattle were more likely to use analgesics. Training in pain perception and management should be emphasised with the hope of promoting animal welfare and reducing unnecessary production losses. [ABSTRACT FROM AUTHOR]

Simple Summary: Most birds build nests for laying eggs and rearing their offspring. They frequently clean their nests by removing foreign objects, such as leaves, small branches, stones, and feces. Further, some birds recognize and remove foreign eggs deposited by brood parasites. Nest sanitation and egg rejection are related behaviors as both impact brood survival and involve an accept/reject decision regarding the content of the nest. Here, we examined these behaviors in barn swallows (Hirundo rustica), one of the most abundant and widespread birds in the world. The results suggest that nest sanitation may be a more ancient behavior because it occurs more frequently, and foreign objects were removed sooner upon discovery than egg rejection. Therefore, nest sanitation may constitute an evolutionary precursor to foreign egg rejection; however, nest sanitation rarely increases egg rejection regarding probability and response latency. Female and male swallows engaged in nest sanitation and egg rejection, implying that both sexes are affected by this type of natural selection. Bird nests function as vessels for eggs and nestlings, and an environment for rearing offspring. However, foreign objects falling into bird nests and nestling eggshells may be harmful. Moreover, the smell of fecal sacs increases the risk of detection by predators. Many bird species have evolved nest sanitation to prevent damage to their nests. Furthermore, egg rejection evolved in some birds to thwart brood parasites that lay eggs in their nests. We studied 133 nests of barn swallows (Hirundo rustica) in an island population through a nest content manipulation experiment to determine nest sanitation and egg rejection behaviors and their relationship. Swallows rejected non-egg foreign objects more frequently (100% vs. 58.6%) and sooner than parasite eggs, which supports the hypothesis that nest sanitation is a pre-adaptation to egg rejection. However, nest sanitation did not increase egg rejection, either in probability or latency. Furthermore, both sexes incubated the eggs, cleaned the nests, and removed parasite eggs, implying that both are confronted with natural selection related to nest sanitation and brood parasitism. However, females invested more time in these behaviors than males. This provides evidence for the evolutionary relationship of nest sanitation and egg rejection behaviors in barn swallows. [ABSTRACT FROM AUTHOR]

Radiation exposure can immediately trigger a burst of reactive oxygen species (ROS), which can induce severe cell death and long-term tissue damage. Therefore, instantaneous release of sufficient radioprotective drugs is vital to neutralize those accumulated ROS in IR-exposed areas. To achieve this goal, we designed, synthesized, and evaluated a novel oral ROS-responsive radioprotective compound (M1) with high biocompatibility and efficient ROS-scavenging ability to act as a promising oral drug for radiation protection. The compound is stably present in acidic environments and is hydrolyzed in the intestine to form active molecules rich in thiols. M1 can significantly remove cellular ROS and reduce DNA damage induced by γ-ray radiation. An in vivo experiment showed that oral administration of M1 effectively alleviates acute radiation-induced intestinal injury. Immunohistochemical staining showed that M1 improved cell proliferation, reduced cell apoptosis, and enhanced the epithelial integrity of intestinal crypts. This study provides a promising oral ROS-sensitive agent for acute intestinal radiation syndrome. [ABSTRACT FROM AUTHOR]

Intelligent power grid fault diagnosis is of great significance for speeding up fault processing and improving fault diagnosis efficiency. However, most of the current fault diagnosis methods focus on rule diagnosis, relying on expert experience and logical rules to build a diagnosis model, and lack the ability to automatically extract fault knowledge. For switch refusal events, it is difficult to determine a refusal switch without network topology. In order to realize the non-operating switch identification without network topology, this paper proposes a power grid fault diagnosis method based on deep reinforcement learning for alarm information text. Taking the single alarm information of the non-switch refusal sample as the research object, through the self-learning ability of deep reinforcement learning, it learns the topology connection relationship and action logic relationship between equipment, protection and circuit breakers contained in the alarm information, and realizes the detection of fault events. The correct prediction of the fault removal process after the occurrence, based on this, determines the refusal switch when the switch refuses to operate during the fault removal process. The calculation example results show that the proposed method can effectively diagnose the refusal switch of the switch refusal event, which is feasible and effective. [ABSTRACT FROM AUTHOR]

Based on the daily minimum air temperature (Tmin) data and the daily precipitation data from the NCC/CMA combined with the NCEP/DOE reanalysis data, the intraseasonal features and circulations of the winter cold precipitation events (CPEs) in southern China under the influence of strong Madden–Julian oscillation (MJO) were explored. The results show that: (1) Winter temperatures in southern China are characterized by intraseasonal oscillations (ISOs) of 10–30-d and 30–60-d, with six CPEs under strong MJO all occurring during these two intraseasonal scales in cooling phases. The invasion of cold air coupled with the availability of appropriate moisture conditions in southern China is more conducive to the CPEs. (2) A cyclone and anticyclone lying to the east of the Ural Mountains and the northwest of Lake Baikal at 925-hPa gradually move southeastward. The merging of the low-frequency (LF) blocking highs over the Ural Mountains and the North Pacific Ocean at 500-hPa leads to the contraction and southward movement of the LF cold vortex. The following anomalous northerly winds steer the cold air towards southern China. The cold advection is the dominant term in the cooling process, while the adiabatic cooling accompanied with ascending motion is also beneficial to the cooling process. (3) MJO has some effect on the LF blocking highs and the cold vortex in the mid-high latitudes and induces the CPEs over southern China. The joint effect of mid-high and low latitudes on the 30–60-d intraseasonal oscillation scale can have a significant impact on the cooling and precipitation processes of CPEs. [ABSTRACT FROM AUTHOR]

Obesity is a prevalent chronic disease worldwide. In this study, we screened lactic acid bacteria (LAB) suitable for fermenting Shenheling extract (SHLE) to enhance its anti-obesity efficacy and improve flavor. Using SHLE as the medium, a single strain was inoculated and the lactic acid bacteria suitable for growth in SHLE were preliminarily screened through a growth curve. The growth of the initially screened LAB was characterized in detail by the pH value, titration acidity and viable bacteria count. At the same time, appropriate LAB were selected with the lipase activity inhibition rate, α-glucosidase activity inhibition rate and a sensory evaluation as the response indicators. As a result, 6 of the 12 strains of lactic acid bacteria grew well in SHLE. The fermentation of five representative LAB could significantly improve the inhibition rate of the lipase activity of SHLE and maintain the inhibition rate of the α-glucosidase activity at a high level. In addition, fermentation removed the original flavors of SHLE such as grass, bitterness and cassia and added a sour taste, fruity aroma and cool taste. Among them, Lactobacillus fermentum grx08 and Lactobacillus rhamnosus hsryfm1301 gave SHLE a soft sour taste after fermentation. L. fermentum grx08, L. rhamnosus grx10 and hsryfm1301 imparted a moderately fruity aroma to SHLE after fermentation. In summary, L. fermentum grx08 and L. rhamnosus hsryfm1301 were the candidate strains for fermenting SHLE to produce good-flavored slimming functional drinks. [ABSTRACT FROM AUTHOR]

Construction machinery is necessary in postdisaster emergency rescue missions involving the destruction of ruins. However, their mechanical vibrations can interfere with the detection of human survivors using ultrawideband (UWB) radar. Traditional methods detect and identify humans by determining maximum energy and checking respiratory frequency. However, they lose effectiveness because mechanical vibration is associated with a frequency band which is similar to the human respiration band, but it has higher energy. This study proposes a novel method to distinguish human vibrations from mechanical vibrations. After preprocessing, wavelet entropy decomposition was implemented on the radar data. An improved, censored mean-level detector, constant false-alarm rate algorithm was utilized to automatically identify the position of human and mechanical vibrations. A novel feature is then extracted by calculating the half-height width of the target's wavelet entropy. Finally, the results of two independent sample t-tests prove that there is a significant statistical difference between the feature values of humans and the mechanical vibrations (p < 1.9 × 10−6), thus proving the effectiveness of the method. We envisage that the proposed method can be used in postdisaster rescue missions to improve the accuracy and speed of identifying human targets. Therefore, more survivors may be rescued. [ABSTRACT FROM AUTHOR]

The propulsion systems of hybrid electric ship output and load demand have substantial volatility and uncertainty, so a hierarchical collaborative control energy management scheme of the ship propulsion system is proposed in this paper. In a layer of control scheme, the traditional perturbation algorithm is improved. Increasing the oscillation detection mechanism and establishing the dynamic disturbance step length realizes the real-time stability of maximum power point tracking control. In the second-layer control scheme, the power sensitivity factor and voltage and current double closed-loop controller is introduced. By designing a two-layer coordinated control strategy based on the dynamic droop coefficient, the problem of voltage and frequency deviation caused by load switching is solved. In the third-layer control scheme, due to the need of the optimal scheduling function, the multi-objective particle swarm optimization algorithm was improved through three aspects: introducing the mutation factor, improving the speed formula, and re-initializing the strategy. Compared with other algorithms, this algorithm proves its validity in day-ahead optimal scheduling strategy. The superiority of the hierarchical collaborative optimization control schemes proposed was verified, in which power loss was reduced by 39.3%, the overall tracking time was prolonged by 15.4%, and the environmental cost of the diesel generator was reduced by 8.4%. The control strategy solves the problems of the steady-state oscillation stage and deviation from the tracking direction, which can effectively suppress voltage and frequency fluctuations. [ABSTRACT FROM AUTHOR]

Geopolymer is a porous inorganic material with a three-dimensional mesh structure, good mechanical properties, a simple preparation process (no sintering) and a low economic cost, and it is environmentally friendly. Geopolymer concrete has been widely used in the construction field, and many other studies have revealed that geopolymer will become one of the most promising inorganic materials with unique structure and properties. This paper provides a review of the development and current status of geopolymers and briefly explains the effects of material proportioning, experimental factors and activators on geopolymer performance. Because of the advantages of high specific surface area and high porosity, geopolymers could be used as adsorbent materials. This paper summarizes the research progresses of the adsorption of metal cations, anions, dyes, and gases by geopolymers, which emphasizes the geopolymer membranes in adsorption, and discusses the challenges and opportunities for the development of more efficient, sustainable and practical adsorption protocols. [ABSTRACT FROM AUTHOR]

Bipolar membranes, a new type of composite ion exchange membrane, contain an anion exchange layer, a cation exchange layer and an interface layer. The interface layer or junction is the connection between the anion and cation exchange layers. Water is dissociated into protons and hydroxide ions at the junction, which provides solutions to many challenges in the chemical, environmental and energy fields. By combining bipolar membranes with electrodialysis technology, acids and bases could be produced with low cost and high efficiency. The interface layer or junction of bipolar membranes (BPMs) is the connection between the anion and cation exchange layers, which the membrane and interface layer modification are vital for improving the performance of BPMs. This paper reviews the effect of modification of a bipolar membrane interface layer on water dissociation efficiency and voltage across the membrane, which divides into three aspects: organic materials, inorganic materials and newly designed materials with multiple components. The structure of the interface layer is also introduced on the performance of bipolar membranes. In addition, the remainder of this review discusses the challenges and opportunities for the development of more efficient, sustainable and practical bipolar membranes. [ABSTRACT FROM AUTHOR]

Data-driven approaches to urban flooding management require a comprehensive understanding of how heterogenous data are leveraged in tackling this problem. In this paper, we conduct an integrative review of related studies, and this is structured based on two angles: tasks and data. From the selected 69 articles on this topic, diverse tasks in tackling urban flooding are identified and categorized into eight categories, and heterogeneous data are summarized by their content type and source into eight categories. The links between tasks and data are identified by synthesizing what data are used to support the tasks in the studies. The task–data links are a many-to-many relationship in the sense that one particular data category supports multiple tasks, and one particular task uses data from multiple categories. The future research opportunities are also discussed based on our observations. This paper serves a signpost for researchers who wish to gain an overview of the heterogenous data and their use in this field and lays a foundation for studies that aim to develop a data-driven approach to tackle urban flooding. [ABSTRACT FROM AUTHOR]

The rapid development of electric vehicles (EVs) has posed challenges to power grids and transportation networks. Accurately capturing the usage patterns of EV users is a prerequisite for EVs' interaction with electrified transportation networks. Thus, this paper proposes a full data chain (FDC) driven model to mine EVs' comprehensive characteristics. By collecting the data of 150 private electric vehicles (PREVs), 100 commercial electric vehicles (CEVs), and 50 official electric vehicles (OEVs) in Chongqing, China, the driving characteristics are firstly mined by the adoption of origin-destination (OD) distribution and driving portrait. Moreover, the charging characteristics are extracted based on the state recognition for data chains. Then, vehicle usage characteristics of different types of users are comprehensively described based on the density-based spatial clustering of applications with noise (DBSCAN). Finally, the results of EV user characteristics are analyzed, and the effectiveness of the proposed model is verified by regional charging load analysis and urban road traffic flow comparison. The findings provide a data source and user behavior model for the planning, operation, and control of power grids and transportation networks. [ABSTRACT FROM AUTHOR]

Simple Summary: Microbeams are useful tools in studies on non-target effects, such as the radiation-induced bystander effect, and responses related to cytoplasmic irradiation. A micrometer or even sub-micrometer-level beam size enables the precise delivery of radiation energy to a specific target. Here we summarize the observations of the bystander effect and the cytoplasmic irradiation-related effect using different kinds of microbeam irradiators as well as discuss the cellular and molecular mechanisms that are involved in these responses. Non-target effects may increase the detrimental effect caused by radiation, so a more comprehensive knowledge of the process will enable better evaluation of the damage resulting from irradiation. Although direct damage to nuclear DNA is considered as the major contributing event that leads to radiation-induced effects, accumulating evidence in the past two decades has shown that non-target events, in which cells are not directly irradiated but receive signals from the irradiated cells, or cells irradiated at extranuclear targets, may also contribute to the biological consequences of exposure to ionizing radiation. With a beam diameter at the micrometer or sub-micrometer level, microbeams can precisely deliver radiation, without damaging the surrounding area, or deposit the radiation energy at specific sub-cellular locations within a cell. Such unique features cannot be achieved by other kinds of radiation settings, hence making a microbeam irradiator useful in studies of a radiation-induced bystander effect (RIBE) and cytoplasmic irradiation. Here, studies on RIBE and different responses to cytoplasmic irradiation using microbeams are summarized. Possible mechanisms related to the bystander effect, which include gap-junction intercellular communications and soluble signal molecules as well as factors involved in cytoplasmic irradiation-induced events, are also discussed. [ABSTRACT FROM AUTHOR]

Obesity is a common global problem. There are many fat-reducing herbal prescriptions in traditional Chinese medicine that have been proven to be safe and functional during long-term application. Microbial fermentation can improve the efficacy of herbal medicine and improve the unsavory flavor. In this study, Shenheling extract (SHLE) composed of six medicine food homology materials was used as the research object. The purpose of this study was to evaluate the effects of Lactobacillusfermentum grx08 fermentation on the antiobesity efficacy and flavor of SHLE. We found that L. fermentum grx08 grew well in SHLE. After 72 h of fermentation, the total polysaccharides, total flavonoids, total polyphenols and total saponins of SHLE decreased, but the lipase inhibitory activity and total antioxidant capacity (FRAP) were significantly increased (p < 0.01). There were no significant differences in the α-glucosidase inhibition rate and DPPH· clearance rate before or after fermentation (p > 0.05). In addition, the fermentation reduces the unpleasant flavors of SHLE such as bitterness and grassy and cassia flavors. This study demonstrates that SHLE fermented by L. fermentum grx08 improved some anti-obesity functions and improved the unpleasant flavor. [ABSTRACT FROM AUTHOR]

To improve the operating efficiency and economic benefits, this article proposes a modified rainbow-based deep reinforcement learning (DRL) strategy to realize the charging station (CS) optimal scheduling. As the charging process is a real-time matching between electric vehicles '(EVs) charging demand and CS equipment resources, the CS charging scheduling problem is duly formulated as a finite Markov decision process (FMDP). Considering the multi-stakeholder interaction among EVs, CSs, and distribution networks (DNs), a comprehensive information perception model was constructed to extract the environmental state required by the agent. According to the random behavior characteristics of the EV charging arrival and departure times, the startup of the charging pile control module was regarded as the agent's action space. To tackle this issue, the modified rainbow approach was utilized to develop a time-scale-based CS scheme to compensate for the resource requirements mismatch on the energy scale. Case studies were conducted within a CS integrated with the photovoltaic and energy storage system. The results reveal that the proposed method effectively reduces the CS operating cost and improves the new energy consumption. [ABSTRACT FROM AUTHOR]

This paper develops the coordination structure and method for utilizing flexibilities in a Micro-Grid (MG), an Active Distribution Network (ADN) and a Transmission Grid (TG), which can play an essential role in addressing the uncertainties caused by renewable energy power generation (REPG). For cooperative dispatching, both flexibilities and uncertainties on the interface of MG–ADN and ADN–TG are portrayed in unified forms utilizing robust optimization (RO), based on the modified equipment-level model of flexible resources. The Constraint-and-Column Generation method is adopted to solve the RO control problems. Simulations on the modified IEEE case-6 and case-33 systems are carried out. The results suggest that the proposed algorithm can exploit flexible resources in both an MG and an ADN, improving the economy and promoting REPG consumption within each level (MG, ADN and TG) while reducing uncertainties and providing flexibilities for superior operators. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have attracted growing attention in recent years. However, most existing research has not utilized actual traffic data and has not considered real psychological decision-making of owners in analyzing the charging demand. On this basis, an urban EV fast-charging demand forecasting model based on a data-driven approach and human decision-making behavior is presented in this paper. In this methodology, Didi ride-hailing order trajectory data are firstly taken as the original dataset. Through data mining and fusion technology, the regenerated data and rules of traffic operation are obtained. Then, the single EV model with driving and charging behavior parameters is established. Furthermore, a human behavior decision-making model based on Regret Theory is introduced, which comprises the utility of time consumption and charging cost to plan driving paths and recommend fast-charging stations for vehicles. The rules obtained from data mining together with established models are combined to construct the 'Electric Vehicles–Power Grid–Traffic Network' fusion architecture. At last, the actual urban traffic network in Nanjing is selected as an example to design the fast-charging demand load experiments in different scenarios. The results demonstrate that this proposed model is able to effectively predict the spatio-temporal distribution characteristics of urban fast-charging demands, and it more realistically simulates the decision-making psychology of owners' charging behavior. [ABSTRACT FROM AUTHOR]

Alcoholic liver disease (ALD) is a major cause of chronic liver disease worldwide. It is a complex process, including a broad spectrum of hepatic lesions from fibrosis to cirrhosis. Our previous study suggested that astaxanthin (AST) could alleviate the hepatic inflammation and lipid dysmetabolism induced by ethanol administration. In this study, a total of 48 male C57BL/6J mice were divided into 4 groups: a Con group (fed with a Lieber–DeCarli liquid diet), an AST group (fed with a Lieber–DeCarli liquid diet and AST), an Et group (fed with an ethanol-containing Lieber–DeCarli liquid diet), and a EtAST group (fed with an ethanol-containing Lieber–DeCarli liquid diet and AST). Then, comparative hepatic transcriptome analysis among the groups was performed by Illumina RNA sequencing. Gene enrichment analysis was conducted to identify pathways affected by the differentially expressed genes. Changes of the top genes were verified by quantitative real-time PCR (qRT-PCR) and Western blot. A total of 514.95 ± 6.89, 546.02 ± 15.93, 576.06 ± 21.01, and 690.85 ± 54.14 million clean reads were obtained for the Con, AST, Et, and EtAST groups, respectively. Compared with the Et group, 1892 differentially expressed genes (DEGs) (including 351 upregulated and 1541 downregulated genes) were identified in the AST group, 1724 differentially expressed genes (including 233 upregulated and 1491 downregulated genes) were identified in the Con group, and 1718 DEGs (including 1380 upregulated and 338 downregulated genes) were identified in the EtAST group. The enrichment analyses revealed that the chemokine signaling, the antigen processing and presentation, the nucleotide-binding and oligomerization domain (NOD)-like receptor signaling, and the Toll-like receptor signaling pathways enriched the most differentially expressed genes. The findings of this study provide insights for the development of nutrition-related therapeutics for ALD. [ABSTRACT FROM AUTHOR]

The development and progression of alcoholic fatty liver disease (AFLD) is influenced by the intestinal microbiota. Astaxanthin, a type of oxygenated carotenoid with strong antioxidant and anti-inflammatory properties, has been proven to relieve liver injury. However, the relationship between the gut microbiota regulation effect of astaxanthin and AFLD improvement remains unclear. The effects of astaxanthin on the AFLD phenotype, overall structure, and composition of gut microbiota were assessed in ethanol-fed C57BL/6J mice. The results showed that astaxanthin treatment significantly relieves inflammation and decreases excessive lipid accumulation and serum markers of liver injury. Furthermore, astaxanthin was shown to significantly decrease species from the phyla Bacteroidetes and Proteobacteria and the genera Butyricimonas, Bilophila, and Parabacteroides, as well as increase species from Verrucomicrobia and Akkermansia compared with the Et (ethanol)group. Thirteen phylotypes related to inflammation as well as correlated with metabolic parameters were significantly altered by ethanol, and then notably reversed by astaxanthin. Additionally, astaxanthin altered 18 and 128 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways involved in lipid metabolism and xenobiotic biodegradation and metabolism at levels 2 and 3, respectively. These findings suggest that Aakkermansia may be a potential target for the astaxanthin-induced alleviation of AFLD and may be a potential treatment for bacterial disorders induced by AFLD. [ABSTRACT FROM AUTHOR]

It takes electric vehicles (EVs) a long time to charge, which is bound to influence the charging experience of vehicle owners. At the same time, large-scale charging behavior also brings about large load pressure on, and elevates the overload risk of, the power distribution network. To solve these problems, we proposed a high-efficiency charging service system based on charging reservation and charging pile binding services. The system can shorten the average charging time of EVs and improve the average immediate utilization rate of new energy sources at charging stations (CSs). In addition, the system also guarantees that the EVs are charged within the allowable range of the capacity of the distribution network and avoids overloading of the distribution network caused by the charging of EVs. The key support for the utility of the system is rooted in the three-level CS selection model and the CS energy control algorithm (CSECA) proposed in the research. Finally, the proposed model and algorithm were verified to be valid through numerous simulation experiments. [ABSTRACT FROM AUTHOR]