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The evolution of electric propulsion systems in the maritime sector has been influenced significantly by technological advancements in power electronics and machine design. Traditionally, these systems have employed surface-mounted permanent magnet synchronous motors (PMSMs) in podded configurations. However, the advent of permanent magnet Vernier motors (PMVMs), which leverage magnetic gearing effects, presents a novel approach with promising potential. This study conducts a comparative analysis between PMVMs and conventional PMSMs at a power level of 5 MW for podded ship propulsion, with a particular focus on the impact of gear ratios ( G r ). An objective function was developed that integrates motor dimension constraints and the power factor (PF), a critical yet frequently neglected parameter in existing research. The findings indicate that PMVMs with lower G r have lower mass and cost compared to those with higher G r and traditional PMSMs, at a PF level of 0.7, which is high for Vernier machines. Moreover, PMVMs with lower G r achieve efficiencies exceeding 99%, outperforming both their higher G r counterparts and conventional PMSMs. The superior performance of PMVMs is attributed to lower current density and reduced copper loss, which contribute to their enhanced thermal performance. These details are elaborated on further in the paper. Consequently, these findings suggest that PMVMs with lower G r are particularly well suited for high-power maritime propulsion applications, offering advantages in terms of compactness, efficiency (EF), cost-effectiveness, and thermal performance. [ABSTRACT FROM AUTHOR]

This article aims to explore the impact of HLB (Hydrophile-Lipophile Balance) values on two key properties, namely the thermoelectric conductivities and the stability of the suspension, of a hybrid nanofluid composed of TiO2 and CuO nanoparticles. The present study employed a two-step synthesis method to prepare the polymeric nanofluid, which meant that the nanoparticles were mixed with the base fluid using an ultrasonic oscillator, which was easier and cheaper than the one-step synthesis method. To ensure that the nanoparticles remain evenly dispersed in the base fluid, two distinct polymer-emulsifier combinations with different HLB values were employed as the dispersing agents. The first pair of polymeric emulsifiers consisted of Span#20 and Tween#20, and the second pair was Span#80 and Tween#80 composed to four HLB values of 12, 13, 14, and 15. The experiment measured the properties of the nanofluid, including the particle size, Zeta potential, and thermoelectric conductivities at different temperatures from 20 °C to 50 °C. The experimental outcomes indicated that an HLB value of 13 was the best for the two sets of polymeric emulsifiers tested. This value corresponded to the most reduced particle size, measured at 170 nm, alongside the most elevated Zeta potential, recorded at −30 mV. Additionally, this HLB value was associated with the peak thermoelectric conductivity, which was 1.46 W/m∙K. This suggests that there may be some variation in the best HLB value depending on the type of polymeric emulsifiers and the temperature of the hybrid nanofluid. [ABSTRACT FROM AUTHOR]

The absorption and scattering of light in water usually result in the degradation of underwater image quality, such as color distortion and low contrast. Additionally, the performance of acquisition devices may limit the spatial resolution of underwater images, resulting in the loss of image details. Efficient modeling of long-range dependency is essential for understanding the global structure and local context of underwater images to enhance and restore details, which is a challenging task. In this paper, we propose an agent-guided non-local attention network using a multi-color space for underwater image enhancement and super-resolution. Specifically, local features with different receptive fields are first extracted simultaneously in the RGB, Lab, and HSI color spaces of underwater images. Then, the designed agent-guided non-local attention module with high expressiveness and lower computational complexity is utilized to model long-range dependency. Subsequently, the results from the multi-color space are adaptively fused with learned weights, and finally, the reconstruction block composed of deconvolution and the designed non-local attention module is used to output enhanced and super-resolution images. Experiments on multiple datasets demonstrated that our method significantly improves the visual perception of degraded underwater images and efficiently reconstructs missing details, and objective evaluations confirmed the superiority of our method over other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Acquiring phenotypic data from livestock constitutes a crucial yet cumbersome phase in the breeding process. Traditionally, obtaining livestock phenotypic data primarily involves manual, on-body measurement methods. This approach not only requires extensive labor but also induces stress on animals, which leads to potential economic losses. Presently, the integration of next-generation Artificial Intelligence (AI), visual processing, intelligent sensing, multimodal fusion processing, and robotic technology is increasingly prevalent in livestock farming. The advantages of these technologies lie in their rapidity and efficiency, coupled with their capability to acquire livestock data in a non-contact manner. Based on this, we provide a comprehensive summary and analysis of the primary advanced technologies employed in the non-contact acquisition of livestock phenotypic data. This review focuses on visual and AI-related techniques, including 3D reconstruction technology, body dimension acquisition techniques, and live animal weight estimation. We introduce the development of livestock 3D reconstruction technology and compare the methods of obtaining 3D point cloud data of livestock through RGB cameras, laser scanning, and 3D cameras. Subsequently, we explore body size calculation methods and compare the advantages and disadvantages of RGB image calculation methods and 3D point cloud body size calculation methods. Furthermore, we also compare and analyze weight estimation methods of linear regression and neural networks. Finally, we discuss the challenges and future trends of non-contact livestock phenotypic data acquisition. Through emerging technologies like next-generation AI and computer vision, the acquisition, analysis, and management of livestock phenotypic data are poised for rapid advancement. [ABSTRACT FROM AUTHOR]

Investigating the dynamic evolution process of the ocean and ionosphere in sudden sea conditions poses a challenging problem. To address this objective, this study utilizes actual data from high-frequency surface wave radar (HFSWR) to analyze, validate, summarize, and characterize the echo properties of the ocean and ionosphere during the severe Typhoon Muifa. By employing the short-time Fourier transform (STFT) method, the HFSWR ocean and ionosphere echoes stimulated by typhoon-induced gravity waves are observed, and the joint gravity wave features of the ocean and ionosphere echoes at different time scales are extracted. Additionally, the phase-space reconstruction method is employed to characterize the dynamical evolution of the joint gravity wave features in higher-dimensional space. Furthermore, the chaotic dynamics behavior of the joint gravity wave features is analyzed using the largest Lyapunov exponents. By combining the gravity wave features with chaotic dynamics, this study introduces a method to characterize the joint gravity wave features. The extraction of joint gravity wave features in HFSWR echoes stimulated by typhoons, along with the construction of a chaotic characterization scheme for the gravity wave features, provides an innovative approach and a solid technical foundation for studying the ocean and ionosphere using HFSWR under sudden sea conditions. [ABSTRACT FROM AUTHOR]

Most fault diagnosis models use a single input and have weak generalization performance. In order to obtain more fault information, a fault diagnosis method based on a Multi-channel Residual Attention Network with Efficient Channel Attention (ECA-MRANet) is proposed in this paper. In this method, the original time domain signal is first processed by a multi-domain transform, the result of which is input to the MRANet for feature extraction. Finally, the extracted features are fused by ECA to realize fault identification. The experimental results show that the proposed method can enhance the ability of the network to discriminate key features, and shows good generalization performance under different working conditions and with small-sample transfer between data sets. [ABSTRACT FROM AUTHOR]

DAPB, a new molecule including danshensu, borneol, and a mother nucleus of ACEI (Angiotensin-converting enzyme inhibitors), is being developed as an antihypertensive candidate compound. A rapid, accurate, and sensitive ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method was established and validated for the determination of DAPB in rat plasma. Chromatographic separation was performed on an Agilent SB-C18 column after protein precipitation by acetonitrile with a mobile phase consisting of acetonitrile and deionized water with 0.02% formic acid and 5 mM NH4F (v/v) at a flow rate of 0.2 mL/min. Quantification was performed using electrospray positive ionization mass spectrometry in the multiple reaction monitoring (MRM) mode. The method was linear over the range of 2–1000 ng/mL. The intra- and inter-day precision was within 12%, with accuracies less than 7%. Stability was within the acceptable limits under various storage and processing conditions. No apparent matrix effect was detected. The validated method was applied to the pre-clinical pharmacokinetic study of DAPB after oral administration of 30 mg/kg and intravenous administration of 6 mg/kg in rats. [ABSTRACT FROM AUTHOR]

The potential of satellite soil moisture (SM) in improving hydrological modeling has been addressed in synthetic experiments, but it is less explored in real data cases. Here, we investigate the added value of Soil Moisture and Passive (SMAP) and Advanced Scatterometer (ASCAT) SM data to distributed hydrological modeling with the soil and water assessment tool (SWAT) in a highly human disturbed catchment (126, 486 km2) featuring a network of SM and streamflow observations. The investigation is based on the ensemble Kalman filter (EnKF) considering SM errors from satellite data using the triple collocation. The assimilation of SMAP and ASCAT SM improved the surface (0–10 cm) and rootzone (10–30 cm) SM at >70% and > 50% stations of the basin, respectively. However, the assimilation effects on distributed streamflow simulation of the basin are un-significant and not robust. SM assimilation improved the simulated streamflow at two upstream stations, while it deteriorated the streamflow at the remaining stations. This can be largely attributed to the poor vertical soil water coupling of SWAT, suboptimal model parameters, satellite SM data quality, humid climate, and human disturbance to rainfall-runoff processes. This study offers strong evidence of integrating satellite SM into hydrological modeling in improving SM estimation and provides implications for achieving the added value of remotely sensed SM in streamflow improvement. [ABSTRACT FROM AUTHOR]

Traditional hydrogels, as wound dressings, usually exhibit poor mechanical strength and slow drug release performance in clinical biomedical applications. Although various strategies have been investigated to address the above issues, it remains a challenge to develop a simple method for preparing hydrogels with both toughness and controlled drug release performance. In this study, a tannic acid-reinforced poly (sulfobetaine methacrylate) (TAPS) hydrogel was fabricated via free radical polymerization, and the TAPS hydrogel was subjected to a simple electrophoresis process to obtain the hydrogels with a gradient distribution of copper ions. These gradient hydrogels showed tunable mechanical properties by changing the electrophoresis time. When the electrophoresis time reached 15 min, the hydrogel had a tensile strength of 368.14 kPa, a tensile modulus of 16.17 kPa, and a compressive strength of 42.77 MPa. It could be loaded at 50% compressive strain and then unloaded for up to 70 cycles and maintained a constant compressive stress of 1.50 MPa. The controlled release of copper from different sides of the gradient hydrogels was observed. After 6 h of incubation, the hydrogel exhibited a strong bactericidal effect on Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli, with low toxicity to NIH/3T3 fibroblasts. The high toughness, controlled release of copper, and enhanced antimicrobial properties of the gradient hydrogels make them excellent candidates for wound dressings in biomedical applications. [ABSTRACT FROM AUTHOR]

A clear understanding of the number of pigs plays a crucial role in breeding management. Computer vision technology possesses several advantages, as it is harmless and labour-saving compared to traditional counting methods. Nevertheless, the existing methods still face some challenges, such as: (1) the lack of a substantial high-precision pig-counting dataset; (2) creating a dataset for instance segmentation can be time-consuming and labor-intensive; (3) interactive occlusion and overlapping always lead to incorrect recognition of pigs; (4) existing methods for counting such as object detection have limited accuracy. To address the issues of dataset scarcity and labor-intensive manual labeling, we make a semi-auto instance labeling tool (SAI) to help us to produce a high-precision pig counting dataset named Count1200 including 1220 images and 25,762 instances. The speed at which we make labels far exceeds the speed of manual annotation. A concise and efficient instance segmentation model built upon several novel modules, referred to as the Instances Counting Network (ICNet), is proposed in this paper for pig counting. ICNet is a dual-branch model ingeniously formed of a combination of several layers, which is named the Parallel Deformable Convolutions Layer (PDCL), which is trained from scratch and primarily composed of a couple of parallel deformable convolution blocks (PDCBs). We effectively leverage the characteristic of modeling long-range sequences to build our basic block and compute layer. Along with the benefits of a large effective receptive field, PDCL achieves a better performance for multi-scale objects. In the trade-off between computational resources and performance, ICNet demonstrates excellent performance and surpasses other models in Count1200, A P of 71.4% and A P 50 of 95.7% are obtained in our experiments. This work provides inspiration for the rapid creation of high-precision datasets and proposes an accurate approach to pig counting. [ABSTRACT FROM AUTHOR]

Technological learning curve models have been continuously used to estimate the cost development of solar photovoltaics (PV) for climate mitigation targets over time. They can integrate several technical sources that influence the learning process. Yet, the accurate and realistic learning curve that reflects the cost estimations of PV development is still challenging to determine. To address this question, we develop four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technological experience and knowledge stock. We specifically adopt the system dynamics approach to focus on the non-linear relationship and dynamic interaction between the cost development and technological learning source. By applying this approach to Chinese PV systems, the results reveal that the suitability and accuracy of learning curve models for cost estimation are dependent on the development stages of PV systems. At each stage, different models exhibit different levels of closure in cost estimation. Furthermore, our analysis underscores the critical role of incorporating global technical sources into learning curve models. [ABSTRACT FROM AUTHOR]

Liver disease accounts for millions of deaths per year all over the world due to complications from cirrhosis and liver injury. In this study, a novel compound, dimethyl bisphenolate (DMB), was synthesized to investigate its role in ameliorating carbon tetrachloride (CCl4)-induced liver injury through the regulation of oxidative stress-related genes. The structure of DMB was confirmed based on its hydrogen spectrum and mass spectrometry. DMB significantly reduced the high levels of ALT, AST, DBIL, TBIL, ALP, and LDH in a dose-dependent manner in the sera of CCl4-treated rats. The protective effects of DMB on biochemical indicators were similar to those of silymarin. The ROS fluorescence intensity increased in CCl4-treated cells but significantly weakened in DMB-treated cells compared with the controls. DMB significantly increased the content of oxidative stress-related GSH, Nrf2, and GCLC dose-dependently but reduced MDA levels in CCl4-treated cells or the liver tissues of CCl4-treated rats. Moreover, DMB treatment decreased the expression levels of P53 and Bax but increased those of Bcl2. In summary, DMB demonstrated protective effects on CCl4-induced liver injury by regulating oxidative stress-related genes. [ABSTRACT FROM AUTHOR]

A wellbore's cleanliness affects drilling efficiency, economy and drilling safety directly in extended-reach drilling operations. Wellbore cleaning in extended-reach drilling has always been a tough problem. Field experience has shown that inefficient transport of small cuttings is a main factor for excessive drag and torque during extended-reach drilling. However, very little is known about the transport of small cuttings. In this paper, we use the data fitting method of dimensional analysis and regression analysis to establish a wellbore cleaning model for high-inclination sections, then use water and Polyanionic Cellulose (PAC) as a drilling fluid to analyze the settlement cleaning of small cuttings in the wellbore. The data from the example wells were used for field simulations to finally derive many factors like drilling fluid density, drilling fluid displacement, drill pipe rotation speed, diameter of cuttings and annulus hydraulic diameter, which affect the thickness of the dimensionless cutting bed. The results show that the dimensionless cutting thickness decreases with increasing drilling fluid density, drilling fluid displacement and drill pipe rotation speed; and increases with increasing cutting size and annular hydraulics diameter. Meanwhile, the effect of drilling fluid discharge, drill pipe rotation speed and cutting size on the thickness of the dimensionless cutting bed decreases as their values increase. This model can be utilized to design parameters in drilling and to predict the transport of cuttings in high-inclination sections. The successful establishment of the wellbore cleaning model for small cuttings in high-inclination sections of extended-reach drilling wells is highly innovative, which is a successful combination of theory and practice and has important guiding significance for promoting the development of wellbore cleaning technology. [ABSTRACT FROM AUTHOR]

Improving the structure of energy consumption (ECS) through green finance and the digital economy is one of the main paths to achieving the goal of carbon neutrality. This paper explores the impact of green finance and the digital economy on the ECS of 30 regions in China from 2007 to 2022 using the Generalized method of moments(GMM) model, further analyzes its heterogeneity, and then provides a reference for the scientific development of relevant decisions. The conclusions are as follows: (1) The change in the ECS is closely related to the degree of optimization of the ECS in the previous year, and this is a process of dynamic adjustment. The level of digital economy development can improve the ECS of the country as a whole and in the eastern and central regions, while the western regions have not yet played a significant role due to the underdevelopment of the digital economy. Green finance can inhibit fossil fuel energy consumption in all regions, and it promotes cleaner, more efficient, and low-carbon energy consumption, thereby improving the ECS. However, the impact effect is the largest in the east and smaller in the west. (2) The urbanization levels of the country as a whole and that of the central and western regions show a positive correlation with the results of energy consumption. However, in the eastern region, it shows an inhibitory effect on fossil fuel energy consumption, which can optimize the ECS. The industrial structures in all regions have positive impact coefficients; the development of industry is not conducive to the optimization of the ECS. Trade openness can improve the ECS only in the eastern region; technological progress in all regions can significantly improve the ECS. Based on the background of carbon neutrality, this paper reveals that green finance and the digital economy promote cleaner, more efficient, and lower carbon energy consumption and reduce the level of energy consumption. This paper also provides a reference for the scientific formulation of relevant decisions. [ABSTRACT FROM AUTHOR]

In recent years, underwater acoustic applications have attracted much attention, for example, for underwater environmental monitoring, underwater exploration, etc. Hydrophones play a particularly important role. Although hydrophone design has been in multifarious application forms, it still needs to consider increasing demand for low-cost, low-consumption, and multiple-function devices, as well as issues around miniaturization, lossless data collection, etc. In this paper, we design a compact underwater acoustic device that has the capability of underwater acoustic signal storage, underwater acoustic signal transmission via the Internet, and decoding based on the direct sequences spread spectrum (DSSS). The key problem is how to implement multiple functions in only one micro-controller unit (MCU). The hardware and software of the proposed multi-function hydrophone are described in detail. In particular, the MCU, the pre-amplifier with gain control, and the analog-to-digital integrated chip are introduced. Moreover, underwater acoustic data storage, underwater acoustic transmission, and the DSSS receiver are depicted in terms of software. The different functions of the hydrophone are verified in sea trial experiments. The results show that the proposed multi-function hydrophone is able to sample underwater acoustic data at high quality. In addition, to demonstrate configurable parameters, the DSSS receiver with different carrier frequencies is provided. The proposed multi-function hydrophone realizes zero bit error rate (BER) when carrier frequency f c = 9 kHz, and the BER with 10 − 3 order of magnitude when carrier frequency f c = 15.5 kHz. The results show that the proposed multi-function hydrophone has great potential to explore the ocean. [ABSTRACT FROM AUTHOR]

Megacities serve as crucial catalysts for national economic and social development, and Shanghai, one of China's most prominent metropolitan areas, exemplifies this transformative urbanization. To study Shanghai's urban expansion, we extracted urban land cover data from 1985 to 2020 using impervious area products and simulated urban expansion dynamics from 2021 to 2035 by employing the cellular automata model. Leveraging these data, we analyzed a 50-year period of urban expansion and investigated the drivers, including economic factors, population growth, and transportation infrastructure. Our findings indicate that the size of Shanghai's urban area in 2035 will be nearly 13 times that of 1985. Over these five decades, Shanghai's urban centroid shifted from the northeast to the southwest, with early urban expansion concentrated in the northeast and later expansion in the southwest. New urban patches primarily emerged at the edges of the initial urban area. As time progressed, areas with higher urban expansion intensity moved outward from the city center, mirroring the trend of urban expansion hotspots. Landscape indicators also demonstrated a trend of urban patches initially spreading and subsequently clustering. Overall, the development of Shanghai's metropolitan area exhibits substantial spatiotemporal heterogeneity. By integrating correlation analysis and generalized additive models, we quantified the impact of urban expansion drivers. The results show that economic and population factors had high correlation coefficients (over 0.97) with urban area, and proximity to the city center and road network greatly contributed to urban expansion. Our research amalgamates various theories and methods to analyze the spatiotemporal dynamics of urban expansion in metropolitan areas. This work provides a valuable data foundation to aid policymakers in designing effective metropolitan development policies. [ABSTRACT FROM AUTHOR]

Background: Normal tension glaucoma (NTG) is considered a neurodegenerative disease with glaucomatous damage extending to diffuse brain areas. Therefore, this study aims to explore the abnormalities in the NTG structural network to help in the early diagnosis and course evaluation of NTG. Methods: The structural networks of 46 NTG patients and 19 age- and sex-matched healthy controls were constructed using diffusion tensor imaging, followed by graph theory analysis and correlation analysis of small-world properties with glaucoma clinical indicators. In addition, the network-based statistical analysis (NBS) method was used to compare structural network connectivity differences between NTG patients and healthy controls. Results: Structural brain networks in both NTG and NC groups exhibited small-world properties. However, the small-world index in the severe NTG group was reduced and correlated with a mean deviation of the visual field (MDVF) and retinal nerve fiber layer (RNFL) thickness. When compared to healthy controls, degree centrality and nodal efficiency in visual brain areas were significantly decreased, and betweenness centrality and nodal local efficiency in both visual and nonvisual brain areas were also significantly altered in NTG patients (all p < 0.05, FDR corrected). Furthermore, NTG patients exhibited increased structural connectivity in the occipitotemporal area, with the left fusiform gyrus (FFG.L) as the hub (p < 0.05). Conclusions: NTG exhibited altered global properties and local properties of visual and cognitive-emotional brain areas, with enhanced structural connections within the occipitotemporal area. Moreover, the disrupted small-world properties of white matter might be imaging biomarkers for assessing NTG progression. [ABSTRACT FROM AUTHOR]

The grouting quality of the grouting sleeve connector is crucial for ensuring the stability of prefabricated building components. In practical engineering, the grouting sleeve is often arranged with multiple sleeves, and there is no feasible nondestructive testing method for testing the complex arrangement of the sleeve grouting joints in the embedded state. Building upon the feasibility of nondestructive detection of single socket grouting connectors, this study discusses the feasibility of defect detection and the severity of defects. Simulation results are used to investigate the choice of the best excitation signal. For different simulated damage cases, it is proven that the selected damage index can be very sensitive, and both the location and the extent of the damage can be detected successfully. The results demonstrate that with the section injury rate ranging from 10% to 40%, the reverse focus peak decreased from 20% to 60% compared to no injury. The effectiveness of the Lamb−wave−based time reversal method in detecting the internal grouting defects of multiple grouting sleeve joints is proven. This paper focuses on the detection study of the Lamb−wave−based time reversal method and proves its ability to perform the detection task effectively and accurately. [ABSTRACT FROM AUTHOR]

Large-scale short-term monitoring and prediction of surface deformation are of great significance for the prevention and control of geohazards in rapidly urbanizing developing cities. Most studies focus on individual cities, but it would be more meaningful to address large urban agglomerations and consider the relevance of the regions within them. In addition, the commonly used linear fitting prediction methods cannot accurately capture the dynamic mechanisms of deformation. In this study, we proposed an automatic PS extraction method (named PS-SBAS-InSAR) that improves SBAS-InSAR to extract surface deformation and an Informer-based short-term surface deformation prediction method for case studies in 16 typical cities of the Yangtze River Delta (YRD). The results show that PS-SBAS-InSAR successfully extracted accurate surface deformation sequences of the YRD. During the period from January 2019 to January 2021, the YRD experienced a slight deformation with an average deformation rate within [−4, 4] mm/year. Geographically neighboring cities may have associated deformation distributions and similar deformation trends, as indicated by average deformation rate maps and landscape metrics. Both types of deformation (i.e., subsidence/uplift) tend to occur simultaneously, with specific areas of subsidence/uplift occurring in close proximity to areas of concentrated deformation. The Informer model effectively captured the time-series variation in surface deformation, suggesting a slowdown of deformation over the next two months (February 2021–March 2021). Our work contributes to a better understanding of changes and trends in large-scale surface deformation and provides useful methods for monitoring and predicting surface deformation in coastal areas. [ABSTRACT FROM AUTHOR]

This paper presents a study on the seismic performance of rectangular hollow section (RHS) X-joints subjected to in-plane bending moment (IPBM). The study began by testing two RHS joint specimens with varying brace-to-chord width ratios (β) under quasi-static cyclic IPBM loading. The results showed that the final failure mode of the specimen with the large β value (β = 1.0) is the tearing of the weld near the brace root, while the specimen with the medium β value (β = 0.83) failed due to the tearing of both the weld and the adjacent chord face. The seismic performance of the X-joints depended considerably on the β value. The increase in β remarkably improved the strength of the X-joints but at the cost of energy dissipation capability, deformability and ductility. Our experimental results also demonstrated that the current code equations remarkably underestimate the flexural strength of RHS X-joints, while the modified equations that take the weld size into account can predict it well. In addition, the reason behind the experimental observation can be further explained by FE analysis and the proposed elastic-support plate analytical model. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a vital climate variable in the interaction process between the Earth's atmosphere and land. However, global soil moisture products from various satellite missions and land surface models are affected by inherently discontinuous observations and coarse spatial resolution, which limits their application at fine spatial scales. To address this problem, this paper integrates three diverse types of datasets from in situ, satellites, and models through Spherical cap harmonic analysis (SCHA) and Helmert variance component estimation (HVCE) to produce 1 km of spatio-temporally continuous SM products with high accuracy. First, this paper eliminates the bias between different datasets and in situ sites and resamples the datasets before data fusion. Then, multi-source SM data fusion is performed based on the SCHA and HVCE methods. Finally, this paper evaluates the fused products from three aspects, including the performance of representative sites under different climate types, the overall performance of validation sites, and the comparison with other products. The results show that the fused products have better performance than other SM products. In the representative sites, the minimal correlation coefficient (R) of the fused products is above 0.85, and the largest root mean square error (RMSE) is below 0.040 m3 m−3. For all validation sites, the R and RMSE of the fused products are 0.889 and 0.036 m3 m−3, respectively, while the R for other products is below 0.75 and the RMSE is above 0.06 m3 m−3. In comparison to other SM products, the fused products exhibit superior performance, generally align more closely with in situ measurements, and possess the ability to accurately and finely capture the spatial and temporal variability of surface SM. [ABSTRACT FROM AUTHOR]

The safety performance test of intelligent driving vehicles needs to rely on the collision scenarios in a real road traffic environment. In order to study the collision scenarios and accident characteristics of vehicles and two wheelers (TWs) in line with the complex traffic conditions in China, this paper proposes using clustering analysis to initially cluster traffic accident data to obtain the base scenarios and then applying the association rule algorithm to each base scenario to obtain the potential connection of its accident attributes and describe the collision scenarios in more detail. This study is based on data from 335 vehicle and two-wheeler crashes in the National Automobile Accident In-Depth Investigation System (NAIS). It used clustering analysis to cluster the crash data into different partitions to obtain eight clusters of vehicle and two-wheeler base scenarios and applied association rules to analyze the rest of the accident attributes, revealing common crash characteristics to describe the base scenarios in more detail. In the end, it constructed eleven types of detailed vehicle and two-wheeler collision scenarios covering straight roads, intersections, and T-junctions. The results provide richer and more suitable crash scenarios of vehicles and two wheelers in China's complex traffic and is an important reference for the development of intelligent driving testing scenarios in the future. [ABSTRACT FROM AUTHOR]

Transmission gear is a key component of vehicles and its surface integrity affects the safety of the transmission system as well as the entire mechanical system. The design and optimization of allowances in form grinding are important for improving dimensional accuracy and machining efficiency during the manufacturing of heavy-duty gears. This work aims to investigate the effects of grinding allowance allocation on surface morphology, grinding temperature, microstructure, surface roughness, and microhardness fluctuation during the form grinding of 20Cr2Ni4A gears. Results indicated that grinding temperature was primarily influenced by rough grinding involving significant grinding depths exceeding 0.02 mm. The ground surface exhibited slight work hardening, while thermal softening led to a reduction in microhardness of around 40 HV. Ground surface roughness Ra varied from 0.930 μm to 1.636 μm, with an allowance allocation of the last two passes exerting the most significant influence. Analysis of surface and subsurface microstructures indicated that a removal thickness of 0.02 mm during fine grinding was insufficient to eliminate the roughness obtained from rough grinding. Evident ridges, gullies, and surface defects such as material extraction, adhesion, and plastic deformation were also observed. The proposed grinding strategy was validated in practical manufacturing with good surface quality and geometrical accuracy. [ABSTRACT FROM AUTHOR]

Objective: Sound, natural dentin collagen can be stabilized against enzymatic degradation through exogenous crosslinking treatment for durable bonding; however, the effect on denatured dentin (DD) collagen is unknown. Hence, the ability of different crosslinkers to enhance/restore the properties of DD collagen was assessed. Methods: Demineralized natural and DD collagen films (7 mm × 7 mm × 7 µm) and beams (0.8 mm × 0.8 mm × 7 mm) were prepared. DD collagen was experimentally produced by heat or acid exposure, which was then assessed by various techniques. All specimens were then treated with 1 wt% of chemical crosslinker 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/n-hydroxysuccinimide (EDC/NHS) and two structurally different flavonoids—theaflavins (TF) from black tea and type-A proanthocyanidins from cranberry juice (CR) for either 30 s or 1 h. The controls were untreated. Dentin films were assessed for chemical interaction and cross-linking effect by FTIR, biostability against exogenous collagenase by weight loss (WL) and hydroxyproline release (HYP), and endogenous matrix metalloproteinases (MMPs) activity by confocal laser microscopy. Dentin beams were evaluated for tensile properties. Data were analyzed using ANOVA and Tukey's test (α = 0.05). Results: Compared with natural collagen, DD collagen showed pronounced structural changes, altered biostability and decreased mechanical properties, which were then improved to various degrees that were dependent on the crosslinkers used, with EDC/NHS being the least effective. Surprisingly, the well-known MMP inhibitor EDC/NHS showed negligible effect on or even increased MMP activity in DD collagen. As compared with control, cross-linking induced by TF and CR significantly increased collagen biostability (reduced WL and HYP release, p < 0.05), MMP inhibition (p < 0.001) and mechanical properties (p < 0.05), regardless of denaturation. Conclusions: DD collagen cannot or can only minimally be stabilized via EDC/NHS crosslinking; however, the challenging substrate of DD collagen can be enhanced or restored using the promising flavonoids TF and CR. [ABSTRACT FROM AUTHOR]

Currently, a large amount of greenhouse gas emissions has caused a series of problems such as serious environmental degradation, and China is facing enormous pressure to reduce emissions. In terms of meeting the needs of people's lives, cold chain logistics has undergone faster development, and its carbon emissions are relatively high. In response to the government's advocacy for green and low-carbon concepts, some technical measures taken will increase the cost of carbon emissions. Identifying measures to reduce carbon emissions using management methods is an ongoing problem that this paper intends to solve. To address the shortcomings of the traditional cost method that cannot accurately account for the cost of each calculation object and ignores the carbon emission cost, this paper constructs an activity-based cost model for cold chain logistics enterprises to more comprehensively account for the operation cost and carbon emission cost. Then, a typical enterprise YS cold chain logistics company is used as a case study for an empirical calculation and analysis. The following conclusions are drawn: (1) the results identify the main activity centers that affect the operating costs and carbon emission costs of different customers; (2) a comparison among the total cost of each project helps to identify high-quality customers; (3) clarifying the carbon emission cost of wasting resources is beneficial for further optimizing the match between production capacity and business volume. This paper provides a path reference for enterprises to efficiently implement logistics cost management and carbon emission control, which can help enterprises cope with cost reduction and efficiency enhancement in a low-carbon environment and promote the long-term development of the logistics industry and environmental protection. [ABSTRACT FROM AUTHOR]

Cultivated land is the basis of food security and an important component of the construction of ecological civilization. The sustainable use of cultivated land is an important issue in land resource management, and it is also an inevitable factor when addressing the contradiction between food demands and resource and environmental constraints. Cultivated land use is both a food production process and a water- and energy-intensive process. Therefore, sustainable use of cultivated land is important not only for cultivated land itself but also for the associated social, economic, and ecological impacts of water and energy input. Therefore, based on the water–land–energy–food nexus, this paper carries out a theoretical analysis of cultivated land use following the element–structure–function framework and builds an evaluation framework of the sustainable use of cultivated land. Finally, this paper selects appropriate evaluation indicators to evaluate the changes in element coordination and function trade-offs of cultivated land use in Quzhou County from 2000 to 2020; analyzes the key influencing factors in detail; and proposes future development directions. The results reflect the fact that the element coordination degree showed obvious continuous decline three times in a row, then a brief rise, and it finally stabilized at a high level, whereas the synergies between the functions decreased and then increased. This means that the sustainable use level of cultivated land in Quzhou County basically presents a good trend. At present, the obstacle that is restricting the efficient use of cultivated land and sustainable development is water, which should be improved by some measures in the future. The results of this evaluation have important theoretical and practical significance for identifying the characteristics of changes in cultivated land use and for guiding future sustainable use in Quzhou County and other regions. [ABSTRACT FROM AUTHOR]

Studying the distribution characteristics of bioaerosols and their interaction with the environment is crucial for dairy farms. The distribution of aerosols differs in dairy farming from farming of other livestock, and their sensitivity to environmental factors varies across sites. Field experiments were conducted in an intensive commercial dairy farm in Northern China to investigate the horizontal and vertical distribution of culturable bacterial bioaerosols. Concentration levels and particle size ranges were analyzed, and the impact of multiple environmental factors on culturable bacterial bioaerosols was assessed. Significant variations in culturable bacterial bioaerosol concentrations were observed across eight functional zones, ranging from 1.14 × 103 to 7.35 × 103 CFU/m3. Culturable bacterial bioaerosols exhibited consistent carrier distribution patterns across six different size ranges. Vertical analysis revealed significantly higher culturable bacterial bioaerosol concentrations at a 1 m height compared to 4 m (p < 0.05), while similar size distributions were observed at different heights of the same sampling location. The top three environmental factors influencing culturable bacterial bioaerosol concentrations were PM100 concentration, wind direction, and air temperature. This study provides insights into the distribution characteristics of culturable bacterial bioaerosols on dairy farms and their response to environmental factors. The findings serve as a reference for evaluating bioaerosol emissions and establishing daily disinfection management measures on dairy farms. [ABSTRACT FROM AUTHOR]

It is very important to understand the distribution and sources of typical potentially toxic elements in industrial sites in order to provide essential information for risk assessment and the process of land reclamation selection. Here, around 29 soil column samples of 6 m depth were collected using a geoprobe drill rig from a typical electroplating site located in the Yangtze River Delta, which has been operating for more than 20 years. Analysis in the laboratory, including measurement of elemental concentrations using ICP-OES, was carried out. The distribution and sources of typical heavy metals were investigated, and correlated risks were assessed using positive matrix factorization. As, Pb, and Cr were the dominant heavy metal pollutants, with ranges of 3.20–154 mg/kg, 13.9–9271 mg/kg, and 27.2–2970 mg/kg, which were 1.28 times, 11.6 times, and 3.71 times higher than the Chinese national standard, respectively. Pb was found to be accumulated in the top 0–2 m and As in the top 0–3 m due to the presence of a typical clay and loamy soil. Additionally, Cr could be transferred into the groundwater, with a maximum concentration of 497 mg/kg, due to frequent interaction between the groundwater and soil. A PMF model showed that the dominant sources of pollution were the electroplating process section, the glass melting process section, the production process section, and the electroplating wastewater. Pb, As, and Cr were mainly generated from the industrial production process, glass melting process, and electroplating process. The pH and CEC appeared to influence the chemical speciation greatly, with higher content observed bound to carbonates as a result of exchange processes in the case of high CEC and low pH conditions. Both the Pb and As observed could contribute to non-carcinogenic and carcinogenic health risks, respectively, based on PMF-HRA analysis, which should receive greater attention in risk management strategies for polluted sites. Identification of the main sources of heavy metals in a site could provide a basis for potential land reclamation. [ABSTRACT FROM AUTHOR]

Person re-identification is a technology used to identify individuals across different cameras. Existing methods involve extracting features from an input image and using a single feature for matching. However, these features often provide a biased description of the person. To address this limitation, this paper introduces a new method called the Dual Descriptor Feature Enhancement (DDFE) network, which aims to emulate the multi-perspective observation abilities of humans. The DDFE network uses two independent sub-networks to extract descriptors from the same person image. These descriptors are subsequently combined to create a comprehensive multi-view representation, resulting in a significant improvement in recognition performance. To further enhance the discriminative capability of the DDFE network, a carefully designed training strategy is employed. Firstly, the CurricularFace loss is introduced to enhance the recognition accuracy of each sub-network. Secondly, the DropPath operation is incorporated to introduce randomness during sub-network training, promoting difference between the descriptors. Additionally, an Integration Training Module (ITM) is devised to enhance the discriminability of the integrated features. Extensive experiments are conducted on the Market1501 and MSMT17 datasets. On the Market1501 dataset, the DDFE network achieves an mAP of 91.6% and a Rank1 of 96.1%; on the MSMT17 dataset, the network achieves an mAP of 69.9% and a Rank1 of 87.5%. These outcomes outperform most SOTA methods, highlighting the significant advancement and effectiveness of the DDFE network. [ABSTRACT FROM AUTHOR]

High rainfall environmental conditions can easily cause erosion or collapse of the granite residual soil slope. However, traditional slope reinforcement methods have drawbacks such as poor landscape effect, high energy consumption of raw materials, and environmental pollution. This study studied the application of microbial-induced calcite precipitation (MICP) in the reinforcement of granite residual soil. The consolidation effect of various methods was investigated, and the influence of cementing liquid concentration and pH value on consolidation under optimal curing conditions was explored. The results showed that the bacteria concentration reached OD600 = 3.0 and urease activity was 31.64 mM/min, which positively impact the production of calcium carbonate and the stability of crystal morphology. In addition, the soaking method was found to have the most effective consolidation effect on the surface soil samples, with the lowest disintegration rate. On the other hand, the peristaltic pump grouting method is the most effective in strengthening depth. This method resulted in a 513.65% increase in unconfined compressive strength (UCS), a 297.98% increase in cohesion, and a 101.75% increase in internal friction angle. This study also found that after seven rounds of grouting, the highest UCS was achieved in consolidated soil samples with a 0.5 mol/L cementing solution concentration, reaching 1.602 MPa. The UCS of soil samples increases as the pH value of the cementing fluid increases within the range of 6–8. As the pH value reaches 8–9, the strength increases and stabilizes gradually. These research findings can serve as an experimental basis for strengthening granite residual soil slopes and a guide for improving microbial geotechnical strengthening methods. [ABSTRACT FROM AUTHOR]

Background: Few studies have identified the links between physical activity (PA), clinical symptoms, and the quality of life (QoL) among mildly infected individuals with COVID-19. This cross-sectional study aims to evaluate how PA levels before infections affect the infectious symptoms and the QoL in mildly infected patients with COVID-19. Methods: An online questionnaire link including participants' sociodemographic and anthropometric characteristics, clinical symptoms during the COVID-19 infectious period, the QoL of the worst symptomatic day, and PA in the last seven days before COVID-19 infections was disclosed. Logistic regression and multiple linear regression analyses were applied to assess the relationships between PA levels in the last seven days before infections and COVID-19-related outcomes. The level of statistical significance was set at p < 0.05. Results: Compared to the low-PA-level group, the moderate-PA-level group presented a higher risk of headaches (OR = 1.34, 95% CI = 1.03 to 1.75, and p = 0.03) and the high-PA-level group presented a higher risk of muscle/body aches (OR = 1.42, 95% CI = 1.04 to 1.93, and p = 0.03). The adjusted linear regression analysis showed that no associations were found between PA levels in the last seven days before infections and the QoL index value on the worst symptomatic day (moderate-PA-level group: β = −0.04, and p = 0.08; high-PA-level group: β = −0.04, and p = 0.17). However, for the mobility and usual activities dimensions of EQ-5D-5L, the lower-PA-level group had a lower burden of QoL than the higher-PA-level group did on the worst-symptomatic day. Conclusions: Among mildly infected patients with COVID-19, a higher PA level is associated with a higher risk of experiencing clinical symptoms and a lower QoL. [ABSTRACT FROM AUTHOR]

Ecosystem services (ESs) are an important basis for maintaining farming household livelihood security and achieving the synergistic and efficient development of ecosystem services, and farming household livelihood security is important for maintaining sustainable development in the region. However, it is difficult to quantify the level of the coordinated development of ESs and farming household livelihood security in a region and their dynamic evolution. This study systematically analyzes the spatio-temporal evolution of the production-living-ecological space, ecosystem service values, and farming household livelihood security in the Dongting Lake from 2000 to 2020 based on land use data, as well as the level of coordinated development of ESs and livelihood security of farmers. The results indicate that more than 80% of the Dongting Lake area has a low level of coordinated development of ESs and farming household livelihood security at or below the level of imminent disorder, but it is on the rise, increasing by 6.32% in the past twenty years. This study can provide a reference for decision-making on the coordinated development of ecological environment and farmers' livelihoods in the Dongting Lake area. [ABSTRACT FROM AUTHOR]

Lake eutrophication due to excessive nutrient enrichment by human activity is one of the most studied ecosystem regime shifts. The suddenness and irreparability of such eutrophication in shallow lakes cause substantial socio-economic losses, especially in fast-developing areas in eastern China. Although eutrophication has been well documented in many lakes, a regional assessment of the eutrophication process is still missing. Here, we provided a regional assessment of water phosphorus changes since 1900 in eutrophic lakes in eastern China using paleolimnological records and diatom-/chironomid-TP transfer functions. We collated the reconstructed water total phosphorus (TP) of ten lakes and reconstructed the other five records based on identified diatom compositions in sediment cores from previous papers. We found three trend types of decrease, increase and fluctuate in the fifteen TP reconstructions according to cluster analysis of the data correlation results. Increase is the dominated trend, in which TP changes are highly correlated. Among eight lakes with an increasing nutrient, the time-series TP data of six lakes fit step functions better than linear regression models, indicating the main non-linear change in lake nutrient levels over time. Our results show how integrating spatial information on a large scale from paleolimnological records highlights the eutrophication process and further benefits current lake management. [ABSTRACT FROM AUTHOR]

This paper aims to propose a new approach to calculate the quantitative relations between morphostructural similarity degree and map scale change in multi-scale contour clusters for automatic contour generalization. Terrain lines were extracted by pre-processing of unclosed contour lines, and an indirect quantitative expression method of morphostructural similarity relation was proposed based on terrain line hierarchical trees. Thirteen groups of multi-scale contour clusters with different drainage areas of loess geomorphy were employed to explore the changing regularity of morphostructural similarity indices with map scale. Finally, the quantitative relations between morphostructural similarity degree and map scale change were calculated using 52 groups of points. The results show that power function is the best fit among the candidate functions, and the quantitative relations between the morphostructural similarity degree and map scale change can be expressed using the same power function, which facilitates the automation of contour generalization. [ABSTRACT FROM AUTHOR]

Marine natural products have been recognized as the most promising source of bioactive substances for drug discovery research. This review illustrates the diversity of culturable actinobacteria associated with marine algae, their bioactivity and metabolites, and approaches to their isolation and determination of their biological properties. Furthermore, actinobacteria associated with marine algae are presented as a new subject for an extensive investigation to find novel and active natural products, which make them a potentially rich and innovative source for new drug development deserving more attention and exploration. [ABSTRACT FROM AUTHOR]

Continuous climate change has become one of the challenges faced by the world, drawing much attention from governments. The forest industry is the main focus of strategic initiatives to realize a circular and green economy and achieve low emissions. In order to explore the relationship between forest resource endowment and green economic growth, this study represents the first attempt to verify how forest resource endowment affects green economic growth (GEG), with a theoretical analysis and an explanation of the effects of both. The following results were obtained: (1) The GEG of the lagging period can improve the GEG of the current period in all regions, which verifies the sustainability of GEG in China. (2) The regression coefficient of forest resource endowment is a negative primary term (except for the eastern region) and a positive quadratic term, indicating that there is a U-shaped nonlinear relationship between forest resource endowment and GEG in the national, central, and western regions. (3) Forest resource endowments inhibit green economic growth by crowding out human capital from high-tech industries and through such effects as "Dutch disease". The elasticity coefficient of the eastern region is positive but insignificant, while the forest resource inhibition effect is larger in the central and western regions, but the elasticity coefficient is significantly lower for the central region than the western region. (4) Human capital significantly contributes to GEG in the east and has a negative effect on GEG in the nation and the central and western regions. A possible reason for this is that there are more highly qualified people in the east than in the central and western regions; environmental regulation inhibits GEG in the nation and the east and has a negative but insignificant effect on GEG in the central and western regions, whereas green finance can promote GEG in all regions, and its promotion effect is highest in the east and lowest in the west, where it does not pass the significance test. [ABSTRACT FROM AUTHOR]

In recent years, there have been increasing research interests in investigating the compression and ballistic responses of metal-ceramic hybrid structures, mainly making use of the synergistic effects of conventional metal honeycomb structures and infilled ceramic matrix materials. In this paper, a novel hybrid auxetic re-entrant metal-ceramic lattice is designed and manufactured to overcome the intrinsic conflicts between the strength and toughness of architected mechanical metamaterials, synergistic effects of auxetic re-entrant metal honeycombs and infilled ceramic materials are experimentally and numerically studied, and auxetic deformation features and failure modes are characterized with the digital image correlation (DIC) technique as well. It was found that (1) the infilled ceramic matrix of conventional honeycomb frames only endure longitudinal compression or impact loading along the external loading direction, while auxetic metal re-entrant honeycomb components endure both longitudinal and transverse loading due to the negative Poisson′s ratio effect and (2) the collaborative effects of infilled auxetics and the constraint frames' hybrid structure dramatically moderate the stress concentration state and improve the impact resistance of single-phase ceramic materials. Our results indicate that the auxetic hybrid design exhibits promising industrial application potentials for blast protection engineering. [ABSTRACT FROM AUTHOR]

Hypertension is the main risk factor of cardiovascular and cerebrovascular diseases. In this paper, a novel compound known as 221s (2,9), which includes tanshinol, borneol and a mother nucleus of ACEI, was synthesized by condensation esterification, deprotection, amidation, deprotection, and amidation, with borneol as the initial raw material, using the strategy of combinatorial molecular chemistry. The structure of the compound was confirmed by 1H NMR, 13C NMR, and high-resolution mass spectrometry, with a purity of more than 99.5%. The compound 221s (2,9) can significantly reduce the systolic and diastolic blood pressure of SHR rats by about 50 mmHg and 35 mmHg after 4 weeks of administration. The antihypertensive effect of 221s (2,9) is equivalent to that of captopril. The use of 221s (2,9) can reduce the content of Ren, Ang II and ACE in the serum of SHR rats, inhibit the RAAS and enhance the vascular endothelial function by upregulating the level of NO. Pathological studies in this area have shown that high dosage of 221s (2,9) can notably protect myocardial fibrosis in rats and reduce the degeneration and necrosis of myocardial fibers, inflammatory cell infiltration, and proliferation of fibrous tissue in the heart of rat. Therefore, the existing work provided a foundation for preclinical research and follow-up clinical research of 221s (2,9) as a new drug. [ABSTRACT FROM AUTHOR]

Ambient black carbon (BC), a main constituent of atmospheric particulate matter (PM), is a primary particle that is mainly generated by the incomplete combustion of fossil fuel and biomass burning. BC has been identified as a potential health risk via exposure. However, the adverse effects of exposure to BC on the male reproductive system remain unclear. In the present study, we explored the effects of maternal exposure to oxidized black carbon (OBC) during pregnancy on testicular development and steroid synthesis in male offspring. Pregnant mice were exposed to OBC (467 μg/kg BW) or nanopure water (as control) by intratracheal instillation from gestation day (GD) 4 to GD 16.5 (every other day). We examined the testicular histology, daily sperm production, serum testosterone, and mRNA expression of hormone synthesis process-related factors of male offspring at postnatal day (PND) 35 and PND 84. Histological examinations exhibited abnormal seminiferous tubules with degenerative changes and low cellular adhesion in testes of OBC-exposed mice at PND 35 and PND 84. Consistent with the decrease in daily sperm production, the serum testosterone level of male offspring of OBC-exposed mice also decreased significantly. Correspondingly, mRNA expression levels of hormone-synthesis-related genes (i.e., StAR, P450scc, P450c17, and 17β-HSD) were markedly down-regulated in male offspring of PND 35 and PND 84, respectively. In brief, these results suggest that prenatal exposure has detrimental effects on mouse spermatogenesis in adult offspring. [ABSTRACT FROM AUTHOR]

Models play a crucial role in explaining internal processes, estimating states, and managing lithium-ion batteries. Electrochemical models can effectively illustrate the battery's mechanism; however, their complexity renders them unsuitable for onboard use in electric vehicles. On the other hand, equivalent circuit models (ECMs) utilize a simple set of circuit elements to simulate voltage–current characteristics. This approach is less complex and easier to implement. However, most ECMs do not currently account for the nonlinear impact of operating conditions on battery impedance, making it difficult to obtain accurate wideband impedance characteristics of the battery when used in online applications. This article delves into the intrinsic mechanism of batteries and discusses the influence of nonstationary conditions on impedance. An ECM designed for non-steady state conditions is presented. Online adaptive adjustment of model parameters is achieved using the forgetting factor recursive least squares (FFRLS) algorithm and varied parameters approach (VPA) algorithm. Experimental results demonstrate the impressive performance of the model and parameter identification method, enabling the accurate acquisition of online impedance. [ABSTRACT FROM AUTHOR]

Visible-infrared person re-identification aims to solve the matching problem between cross-camera and cross-modal person images. Existing methods strive to perform better cross-modal alignment, but often neglect the critical importance of feature enhancement for achieving better performance. Therefore, we proposed an effective method that combines both modal alignment and feature enhancement. Specifically, we introduced Visible-Infrared Modal Data Augmentation (VIMDA) for visible images to improve modal alignment. Margin MMD-ID Loss was also used to further enhance modal alignment and optimize model convergence. Then, we proposed Multi-Grain Feature Extraction (MGFE) Structure for feature enhancement to further improve recognition performance. Extensive experiments have been carried out on SYSY-MM01 and RegDB. The result indicates that our method outperforms the current state-of-the-art method for visible-infrared person re-identification. Ablation experiments verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

N-acetylneuraminic acid (Neu5Ac) is a functional metabolite and has been demonstrated to be a risk factor for cardiovascular diseases. It is not clear whether Neu5Ac is associated with a higher risk of cerebrovascular disorders, especially moyamoya disease (MMD). We sought to elucidate the association between serum Neu5Ac levels and MMD in a case–control study and to create a clinical risk model. In our study, we included 360 MMD patients and 89 matched healthy controls (HCs). We collected the participants' clinical characteristics, laboratory results, and serum Neu5Ac levels. Increased level of serum Neu5Ac was observed in the MMD patients (p = 0.001). After adjusting for traditional confounders, the risk of MMD (odds ratio [OR]: 1.395; 95% confidence interval [CI]: 1.141–1.706) increased with each increment in Neu5Ac level (per μmol/L). The area under the curve (AUC) values of the receiver operating characteristic (ROC) curves of the basic model plus Neu5Ac binary outcomes, Neu5Ac quartiles, and continuous Neu5Ac are 0.869, 0.863, and 0.873, respectively. Furthermore, including Neu5Ac in the model offers a substantial improvement in the risk reclassification and discrimination of MMD and its subtypes. A higher level of Neu5Ac was found to be associated with an increased risk of MMD and its clinical subtypes. [ABSTRACT FROM AUTHOR]

Eco-efficiency (EE) is an important indicator of regional sustainable development, which reflects the efficiency of regional economic development in using resources effectively to reduce environmental pressures, and foreign direct investment and environmental regulation are very important in promoting regional economic growth and enhancing eco-efficiency. In this paper, we chose China's panel data from 2009 to 2021, measured China's regional eco-efficiency using the super-efficient SBM model, and explored environmental regulation and the impact of FDI on EE in different regions using the Tobit model, with conclusions as follows: (1) The average value of national EE in China during 2009–2021 was about 0.631, which was at a low level, and there were significant differences between regions, with the highest EE in the eastern region, and the central and western regions being lower than the national average. (2) FDI at the national level had a significant promoting effect on regional EE, with an elasticity coefficient of 0.0213, which verifies that the "pollution paradise" effect does not exist at national level. FDI promoted EE in the eastern region, while not being significant in the other two regions. The impact of the environmental regulation act on EE at the national level did not pass the significance test, but the impact passed the significance test with positive coefficients for both the eastern and central regions, while in the western region it was not significant. (3) Financial investment in science and technology promoted EE in the national, east, and central regions significantly, while not being significant in the western region. The economic development level of all regions was positively correlated with EE; the impact of urbanization on EE was significantly positive in national, central, and western regions, but was not significant in the eastern region. The industrial structure of all regions was not conducive to the improvement of EE, with the western region having the most negative impact on EE. The study in this paper represents an important addition and refinement to research in related fields. [ABSTRACT FROM AUTHOR]

In this paper, a network consisting of an object localization module and a discriminative feature extraction module is designed for fine-grained image retrieval (FGIR). In order to reduce the interference of complex backgrounds, the object localization module is introduced into the network before feature extraction. By selecting the convolutional feature descriptors, the main object is separated from the background, and thus, most of the interference is filtered out. Further, in order to improve the overall performance of the network, a discriminative filter bank is introduced into the network as the local feature detector. Hence, the local discriminative features can be extracted directly from the original feature map. The experimental results based on the CUB-200-2011 and Cars-196 datasets demonstrate that the proposed method can improve the performance of FGIR. [ABSTRACT FROM AUTHOR]

In this study, based on the OneKP database and through comparative genetic analysis, we found that HMT and HDM may originate from Chromista and are highly conserved in green plants, and that during the evolution from algae to land plants, histone methylation modifications gradually became complex and diverse, which is more conducive to the adaptation of plants to complex and variable environments. We also characterized the number of members, genetic similarity, and phylogeny of HMT and HDM families in barley using the barley pangenome and the Tibetan Lasa Goumang genome. The results showed that HMT and HDM were highly conserved in the domestication of barley, but there were some differences in the Lasa Goumang SDG subfamily. Expression analysis showed that HvHMTs and HvHDMs were highly expressed in specific tissues and had complex expression patterns under multiple stress treatments. In summary, the amplification and variation of HMT and HDM facilitate plant adaptation to complex terrestrial environments, while they are highly conserved in barley and play an important role in barley growth and development with abiotic stresses. In brief, our findings provide a novel perspective on the origin and evolutionary history of plant HvHMTs and HvHDMs, and lay a foundation for further investigation of their functions in barley. [ABSTRACT FROM AUTHOR]

Over the past decade, immunotherapy has emerged as one of the most promising approaches to cancer treatment. The use of immune checkpoint inhibitors has resulted in impressive and durable clinical responses in the treatment of various cancers. Additionally, immunotherapy utilizing chimeric antigen receptor (CAR)-engineered T cells has produced robust responses in blood cancers, and T cell receptor (TCR)-engineered T cells are showing promising results in the treatment of solid cancers. Despite these noteworthy advancements in cancer immunotherapy, numerous challenges remain. Some patient populations are unresponsive to immune checkpoint inhibitor therapy, and CAR T cell therapy has yet to show efficacy against solid cancers. In this review, we first discuss the significant role that T cells play in the body's defense against cancer. We then delve into the mechanisms behind the current challenges facing immunotherapy, starting with T cell exhaustion due to immune checkpoint upregulation and changes in the transcriptional and epigenetic landscapes of dysfunctional T cells. We then discuss cancer-cell-intrinsic characteristics, including molecular alterations in cancer cells and the immunosuppressive nature of the tumor microenvironment (TME), which collectively facilitate tumor cell proliferation, survival, metastasis, and immune evasion. Finally, we examine recent advancements in cancer immunotherapy, with a specific emphasis on T-cell-based treatments. [ABSTRACT FROM AUTHOR]

This research measures the green economic efficiency (GEE) of 30 regions in China from 2009 to 2021 and verifies the financial agglomeration and environmental regulation impacts on GEE with the Tobit model. The conclusions are as follows: (1) The average GEE value in China is 0.596—which is still at a low level—and is highest in the eastern region and lowest in the western region. (2) Financial agglomeration can promote GEE in the whole country, in both the eastern and western regions; however, the western region effect is very low. In the central region, due to the "siphon effect" produced by the eastern region, the financial resources concentrated in the east thus suppress GEE. Environmental regulation inhibits GEE nationally and in the western region while showing a promotion effect in the eastern and central regions, but it is not significant in the central region. (3) Industrial structures inhibit GEE nationally and in the central and western regions, while industrial structures promote GEE in the eastern region; the GDP (gross domestic product) per capita also inhibits GEE nationally and in the central and western regions and promotes GEE in the eastern region. Government intervention inhibits green economic development in all regions, and urbanization inhibits GEE nationally and in the central and western regions while promoting GEE in the eastern region. [ABSTRACT FROM AUTHOR]

Aiming at the problem of fast divergence of pure inertial navigation system without correction under the condition of GNSS restricted environment, this paper proposes a multi-mode navigation method with an intelligent virtual sensor based on long short-term memory (LSTM). The training mode, predicting mode, and validation mode for the intelligent virtual sensor are designed. The modes are switching flexibly according to GNSS rejecting situation and the status of the LSTM network of the intelligent virtual sensor. Then the inertial navigation system (INS) is corrected, and the availability of the LSTM network is also maintained. Meanwhile, the fireworks algorithm is adopted to optimize the learning rate and the number of hidden layers of LSTM hyperparameters to improve the estimation performance. The simulation results show that the proposed method can maintain the prediction accuracy of the intelligent virtual sensor online and shorten the training time according to the performance requirements adaptively. Under small sample conditions, the training efficiency and availability ratio of the proposed intelligent virtual sensor are improved significantly more than the neural network (BP) as well as the conventional LSTM network, improving the navigation performance in GNSS restricted environment effectively and efficiently. [ABSTRACT FROM AUTHOR]

This paper focuses on the cooperative navigation of heterogeneous air-ground vehicle formations in a Global Navigation Satellite System (GNSS) challenged environment and proposes a cooperative navigation method based on motion estimation and a regionally optimal path planning strategy. In air-ground vehicle formations, unmanned ground vehicles (UGVs) are equipped with low-precision inertial navigation measurement units and wireless range sensors, which interact with unmanned aerial vehicles (UAVs) equipped with high-precision navigation equipment for cooperative measurement information and use the UAVs as aerial benchmarks for cooperative navigation. Firstly, the Interacting Multiple Model (IMM) algorithm is used to predict the next moment's motion position of the UGVs. Then regional real-time path optimization algorithms are introduced to design the motion position of the high-precision UAVs so as to improve the formation's configuration and reduce the geometric dilution of precision (GDOP) of the configuration. Simulation results show that the Dynamic Optimal Configuration Cooperative Navigation (DOC-CN) algorithm can reduce the GDOP of heterogeneous air-ground vehicle formations and effectively improve the overall navigation accuracy of the whole formation. The method is suitable for the cooperative navigation environment of heterogeneous air-ground vehicle formations under GNSS-challenged conditions. [ABSTRACT FROM AUTHOR]