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Although channel consistency and seamlessness have been regarded as two critical factors in conducting omnichannel business, their combined effect has yet to be revealed. By employing a polynomial regression, this study disentangles the combined effect of channel consistency and seamlessness on customer experience in the omnichannel context. The results indicate that enhancing channel consistency and seamlessness simultaneously can improve the omnichannel customer experience. The combined effect of a high (low) level of channel consistency and a low (high) level of channel seamlessness on the omnichannel customer experience is also positive. Data vulnerability can strengthen the combined effect of channel consistency and seamlessness on customer experience in the omnichannel context. This study not only uncovers the complex influences of different combinations of channel consistency and seamlessness but also provides new insights into conducting omnichannel retail for practitioners.

Acute kidney injury (AKI) constitutes a severe condition characterized by a sudden decrease in kidney function. Utilizing lineage-restricted stem/progenitor cells, directly reprogrammed from somatic cells, is a promising therapeutic option in personalized medicine for serious and incurable diseases such as AKI. The present study describes the therapeutic potential of induced nephron progenitor cell-sourced molecules (iNPC-SMs) as a cell-free strategy against cisplatin (CP)-induced nephrotoxicity, employing hyaluronic acid (HA) hydrogel-mediated local delivery to minimize systemic leakage and degradation. iNPC-SMs exhibited anti-apoptotic effects on HK-2 cells by inhibiting CP-induced ROS generation. Additionally, the localized biodistribution facilitated by hydrogel-mediated iNPC-SM delivery contributed to enhanced renal function, anti-inflammatory response, and renal regeneration in AKI mice. This study could serve as a ‘proof of concept’ for injectable hydrogel-mediated iNPC-SM delivery in AKI and as a model for further exploration of the development of cell-free regenerative medicine strategies.

This paper investigates the mechanism of thermal-induced errors in interferometric fiber optic gyroscopes (IFOGs) caused by temperature changes in a vacuum environment, proposing a method for calculating thermal-induced errors in small fiber coils. Firstly, based on the Shupe effect and the thermal stress caused by temperature changes around the fiber coil, a three-dimensional thermal-induced error model for small fiber coils is established. Secondly, a spatial fiber optic inertial measurement unit (IMU) model is designed using the Creo 3D modeling software (creo 7.0.0). The model is then imported into the Ansys finite element simulation software (ANSYS Workbench 15.0), where a temperature field is applied to the IMU based on actual temperature profiles to obtain the temperature distribution of the fiber coil at different times in a vacuum state. These data are then used in the three-dimensional thermal-induced error model to calculate the thermal-induced error of the FOG. Finally, a thermal vacuum experimental platform is set up to collect temperature variation data from the inertial measurement components. The experimental data are compared with the three-dimensional error model proposed in this paper as well as traditional error models. The root mean square error is approximately 33% lower than that of traditional error calculation methods, which also proves the theoretical accuracy.

The leaf is not only the main site of photosynthesis, but also an important organ reflecting plant salt tolerance. Discovery of salt-stress-responding genes in the leaf is of great significance for the molecular improvement of salt tolerance in wheat varieties. In this study, transcriptome sequencing was conducted on the leaves of salt-tolerant wheat germplasm CH7034 seedlings at 0, 1, 6, 24, and 48 h after NaCl treatment. Based on weighted gene correlation network analysis of differentially expressed genes (DEGs) under salt stress, 12 co-expression modules were obtained, of which, 9 modules containing 4029 DEGs were related to the salt stress time-course. These DEGs were submitted to the Wheat Union database, and a total of 904,588 SNPs were retrieved from 114 wheat germplasms, distributed on 21 wheat chromosomes. Using the R language package and GAPIT program, association analysis was performed between 904,588 SNPs and leaf salt injury index of 114 wheat germplasms. The results showed that 30 single nucleotide polymorphisms (SNPs) from 15 DEGs were associated with salt tolerance. Then, nine candidate genes, including four genes (TaBAM, TaPGDH, TaGluTR, and TaAAP) encoding enzymes as well as five genes (TaB12D, TaS40, TaPPR, TaJAZ, and TaWRKY) encoding functional proteins, were identified by converting salt tolerance-related SNPs into Kompetitive Allele-Specifc PCR (KASP) markers for validation. Finally, interaction network prediction was performed on TaBAM and TaAAP, both belonging to the Turquoise module. Our results will contribute to a further understanding of the salt stress response mechanism in plant leaves and provide candidate genes and molecular markers for improving salt-tolerant wheat varieties.

Matched field processing (MFP) is an established technique for source localization in known multipath acoustic environments. Unfortunately, in many situations, imperfect knowledge of the actual propagation environment and sidelobes due to modal interference prevent accurate propagation modeling and source localization via MFP. To suppress the sidelobes and improve the method’s robustness, a linear frequency-difference matched field processing (LFDMFP) method for estimating the source range is proposed. A two-neighbor-frequency high-order cross-spectrum between the measurement and the replica of each hydrophone of the vertical line array is first computed. The cost function can then be derived from the dual summation or double integral of the high-order cross-spectrum with respect to the depth of the hydrophones and the candidate sources of the replicas, where the range that corresponds to the minimum is the optimal estimation. Because of the larger modal interference distances, LFDMFP can efficiently provide only one optimal range within the same range search interval rather than some conventional matched field processing. The efficiency of the presented method was verified using simulations and experiments. The LFDMFP unambiguously estimated the source range in two experimental datasets with average relative errors of 2.2 and 1.9%.

Lake Taihu, a subtropical shallow lake in the Yangtze River Basin, is the third-largest freshwater lake in China. It serves not only as a crucial source of drinking water and an ecological resource but also holds significant economic, tourism, and fisheries value. Phytoplankton, a vital component of aquatic ecosystems, plays a critical role in nutrient cycling and maintaining water structure. Its community composition and concentration reflect changes in the aquatic environment, making it an important biological indicator for monitoring ecological conditions. Understanding the impact of water quality on phytoplankton is essential for maintaining ecological balance and ensuring the sustainable use of water resources. This paper focuses on Lake Taihu, with water samples collected in February, May, August, and November from 2011 to 2019. Using quantile regression, a robust statistical analysis tool, the study investigates the heterogeneous effects of water quality on phytoplankton and seasonal variations. The results indicate significant seasonal differences in water quality in Lake Taihu, which substantially influence phytoplankton, showing weakly alkaline characteristics. When phytoplankton concentrations are low, pondus hydrogenii (pH), chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), water temperature (WT), and conductivity significantly affect them. At medium concentrations, COD, TP, TN, and WT have significant effects. At high concentrations, transparency and dissolved oxygen (DO) significantly impact phytoplankton, while TP no longer has a significant effect. These findings provide valuable insights for policymakers and environmental managers, supporting the prevention and control of harmful algal blooms in Lake Taihu and similar aquatic systems.

Two species of trichomonads, Tetratrichomonas buttreyi and Pentatrichomonas hominis, are common intestinal parasites that can impact animal health and productivity. Severe infection by these parasites can lead to diarrhea and wasting in affected animals. Notably, P. hominis is known to cause diarrhea and has the potential to be transmitted between animals and humans. Donkeys hold significant economic importance in China’s agricultural sector. However, whether donkeys are infected with T. buttreyi and P. hominis remains unknown globally. To address this gap in knowledge, 815 fecal samples were collected from donkeys in three representative regions in Shanxi Province, North China. Then, the presence and genetic characteristics of T. buttreyi and P. hominis were examined using species-specific PCR primers amplifying the small subunit ribosomal RNA genes. The overall prevalence was detected to be 25.4% (207/815) for T. buttreyi and 0.7% (6/815) for P. hominis in donkeys in Shanxi Province. All obtained P. hominis sequences were identified as genotype CC1. Genetic analysis revealed that all P. hominis isolates from donkeys were clustered into the same branch with isolates detected in humans, suggesting possible zoonotic transmission. This study is the first to report the occurrence and prevalence of T. buttreyi and P. hominis in donkeys globally. These findings expand the host range of trichomonads and improve our understanding of their genetic diversity and zoonotic potential, providing essential baseline data for the prevention and control of these parasites in donkeys in the region.

Semi-enclosed bays are significantly influenced by the interactions between land and sea, as well as human activities. One notable human activity, land reclamation, impacts water exchange within these bays. However, the variability of sediment transport and cross-bay transport following reclamation remains poorly understood. This study aims to enhance the understanding of sediment dynamics and the responses of cross-bay transport to reclamation. A well-validated three-dimensional numerical model was developed in the Laizhou Bay (LB). Following reclamation, tidal currents suspended sediment concentration, and erosion increased seaward, while these factors decreased landward. In LB, surface and bottom subtidal currents flowed in opposite directions, with the direction of volume transport primarily determined by bottom currents. In the western LB, volume and sediment transport exhibited an anticyclonic pattern, with pronounced seasonal variations observed elsewhere. During summer, volume and sediment transport predominantly occurred from the northeast to the southwest. In winter, volume transport in northern LB was directed westward, while it was eastward in the southern part; sediment transport was primarily eastward. Advection played a significant role in sediment transport dynamics. The pathway of cross-bay sediment transport was primarily located in the central part of the bay. Notably, the cross-bay sediment transport flux in winter was approximately 3.5 times greater than in summer, with reclamation resulting in a reduction in cross-bay transport flux by about 22.17%.

Estimating the line spectra of ship-radiated noise is a crucial remote sensing technique for detecting and recognizing underwater acoustic targets. Improving the signal-to-noise ratio (SNR) makes the low-frequency components of the target signal more prominent. This enhancement aids in the detection of underwater acoustic signals using sonar. Based on the characteristics of low-frequency narrow-band line spectra signals in underwater target radiated noise, we propose a dual-stream deep learning network with frequency characteristics transformation (DS_FCTNet) for line spectra estimation. The dual streams predict amplitude and phase masks separately and use an information exchange module to swap learn features between the amplitude and phase spectra, aiding in better phase information reconstruction and signal denoising. Additionally, a frequency characteristics transformation module is employed to extract convolutional features between channels, obtaining global correlations of the amplitude spectrum and enhancing the ability to learn target signal features. Through experimental analysis on ShipsEar, a dataset of underwater acoustic signals by hydrophones deployed in shallow water, the effectiveness and rationality of different modules within DS_FCTNet are verified.Under low SNR conditions and with unknown ship types, the proposed DS_FCTNet model exhibits the best line spectrum enhancement compared to methods such as SEGAN and DPT_FSNet. Specifically, SDR and SSNR are improved by 14.77 dB and 13.58 dB, respectively, enabling the detection of weaker target signals and laying the foundation for target localization and recognition applications.

LiFePO4 (LFP) batteries are well known for their long cycle life. However, there are many reports of significant capacity degradation in LFP battery packs after only three to five years of operation. This study assesses the second-life potential of commercial LFP batteries retired from electric vehicles (EVs) by evaluating their aging characteristics at the cell and module levels. Four LFP cells and four modules were subjected to aging tests under various conditions. The results indicate that LFP cells exhibit long life cycles with gradual capacity degradation and a minimal internal resistance increase. Module-level analysis reveals significant balance issues impacting capacity recovery. Incremental capacity analysis (ICA) and post-mortem analysis identify the loss of active materials and lithium inventory as key aging mechanisms. This study provides the optimal working conditions of second-life LFP batteries and suggests that, with proper balancing systems, LFP batteries can achieve extended second-life use in stationary energy storage applications, emphasizing the importance of effective balance management for sustainable battery utilization.

Plastic wastes, widely distributed in the environment, can be transformed into microplastics, posing a huge threat to ecosystems and human health due to their stability and adsorbability to other toxic pollutants (e.g., heavy metals and antibiotics). Recently, microbial degradation of (micro)plastics has gained widespread attention because of its green and sustainable properties. Microbial degradation of (micro)plastics is based on the cascade effects of various enzymes secreted by microorganisms, which can convert (micro)plastics into oligomers and monomers, or even mineralize them into CO2 and H2O. The microbial degradation of (micro)plastics is affected by multiple factors, such as microbial species, plastic properties, and environmental conditions. Currently, limited efficient plastic-degrading microorganisms have been discovered, and their degradation mechanisms are still unclear. Furthermore, the efficiency of microbial degradation needs to be improved for future application. Therefore, this review systematically summarizes the sources and properties of existing plastics, identifies pure cultures and mixed cultures for plastic degradation, and examines their influencing factors. In particular, the microbial degradation behaviors of (micro)plastics, including relevant enzymes, degradation efficiency, and degradation mechanisms, were thoroughly discussed. Additionally, the augmentation technologies coupling with microbial degradation, such as advanced oxidation, electrochemical, and genetic engineering technologies, were introduced and highlighted for their potential prospects. This review provides a reference for future research and development of (micro)plastic biodegradation technology.

Supercooled water in mixed-phase clouds plays a significant role in precipitation formation, atmospheric radiation, weather modification, and aircraft flight safety. Identifying supercooled water in mixed-phase clouds is a crucial-frontier scientific issue in atmospheric detection research. In this study, we propose a new algorithm for identifying supercooled water based on the multi-spectral peak characteristics in cloud radar power spectra, combined with radar reflectivity factor and mean Doppler velocity. Using microwave radiometer data, we conducted retrieval analyses on two stratocumulus cases in the spring over the northeastern Daxing’anling region, China. The retrieval results show that the supercooled water in the spring stratocumulus clouds over the region is widespread, with liquid water content (LWC) ranging around 0.1 ± 0.05 g/m3, and particle sizes not exceeding 10 μm. The influence of updrafts on supercooled water is evident, with both showing good consistency in spatiotemporal variation trends. Comparing the liquid water path (LWP) variations retrieved from cloud radar and microwave radiometer, both showed good consistency in variation trends and high LWC areas, indicating the reliability of the identification algorithm developed in this study.

Individual tree canopy extraction plays an important role in downstream studies such as plant phenotyping, panoptic segmentation and growth monitoring. Canopy volume calculation is an essential part of these studies. However, existing volume calculation methods based on LiDAR or based on UAV-RGB imagery cannot balance accuracy and real-time performance. Thus, we propose a two-step individual tree volumetric modeling method: first, we use RGB remote sensing images to obtain the crown volume information, and then we use spatially aligned point cloud data to obtain the height information to automate the calculation of the crown volume. After introducing the point cloud information, our method outperforms the RGB image-only based method in 62.5% of the volumetric accuracy. The AbsoluteError of tree crown volume is decreased by 8.304. Compared with the traditional 2.5D volume calculation method using cloud point data only, the proposed method is decreased by 93.306. Our method also achieves fast extraction of vegetation over a large area. Moreover, the proposed YOLOTree model is more comprehensive than the existing YOLO series in tree detection, with 0.81% improvement in precision, and ranks second in the whole series for mAP50-95 metrics. We sample and open-source the TreeLD dataset to contribute to research migration.

Computational fluid dynamics (CFD) software was used to simulate the feeding behavior in a bottom-blown lead-smelting furnace. The results show that when the particle size is less than 30 μm, 20% of the particles are suspended in the gas phase and do not enter the melt pool for smelting, thus resulting in material loss. When the particle size exceeds 75 μm, the particles settle in the metal layer. When the particle size is 40–60 μm, the particles are distributed in the slag and metal phases, and the material is uniformly distributed in the molten pool; additionally, the average velocity of the particles exceeds 1.4 m/s, the average temperature exceeds 960 K, and the particles exhibit better behavior within this range, thus rendering it the optimal range of particle sizes for feeding.

The endoplasmic reticulum (ER) is indispensable for maintaining normal life activities. Dysregulation of the ER function results in the accumulation of harmful proteins and lipids and the disruption of intracellular signaling pathways, leading to cellular dysfunction and eventual death. Protein misfolding within the ER disrupts its delicate balance, resulting in the accumulation of misfolded or unfolded proteins, a condition known as endoplasmic reticulum stress (ERS). Renal fibrosis, characterized by the aberrant proliferation of fibrotic tissue in the renal interstitium, stands as a grave consequence of numerous kidney disorders, precipitating a gradual decline in renal function. Renal fibrosis is a serious complication of many kidney conditions and is characterized by the overgrowth of fibrotic tissue in the glomerular and tubular interstitium, leading to the progressive failure of renal function. Studies have shown that, during the onset and progression of kidney disease, ERS causes various problems in the kidneys, a process that can lead to kidney fibrosis. This article elucidates the underlying intracellular signaling pathways modulated by ERS, delineating its role in triggering diverse forms of cell death. Additionally, it comprehensively explores a spectrum of potential pharmacological agents and molecular interventions aimed at mitigating ERS, thereby charting novel research avenues and therapeutic advancements in the management of renal fibrosis.

Cadmium (Cd) contamination in agricultural soils has emerged as a significant concern, particularly due to its potential impact on plant-based food. Soil pH reductions can exacerbate Cd mobility, leading to excessive accumulation in crops. While liming has been demonstrated as an effective method to mitigate Cd accumulation in rice grains in acid soils of southern China, its efficacy in remediating acid soils in northern China remains unclear. In this study, a multi-year field experiment was conducted on farmland impacted by zinc ore smelting at coordinates of 33.92° N 112.46° E to investigate the use of limestone for controlling Cd accumulation in wheat and maize grains. The results indicated that applying 7.5 t ha−1 of limestone significantly raised the soil pH from 4.5 to 6.8 as anticipated. Different rates of limestone application (2.25, 4.45, and 7.50 t ha−1) reduced Cd bioavailability in the soil by 20–54%, and Cd accumulation in wheat grains by 5–38% and maize grains by 21–63%, without yield penalty. The remediation effects were sustained for at least 27 months, highlighting limestone as a promising ameliorant for smelting-affected farmland in northern China.

In recent years, with the increase in environmental awareness, people have become more and more concerned about the effectiveness with which coal burns. Laser-induced breakdown spectroscopy (LIBS) has become an important way of coal elemental analysis because of its uncomplicated sample handling, remote sensing capability, and superior sensitivity in identifying a wide range of elements, including both major and minor constituents, down to trace levels. However, the complexity of its mechanism of action, the experimental environmental factors, and the presence of matrix effects in its measurement spectrum have affected the measurement accuracy. In this paper, on the basis of introducing the experimental process and principle of LIBS, we summarize and analyze the influence of each factor on the LIBS detection medium, summarize the mainstream model analysis algorithms, and analyze the advantages and disadvantages of each model. While summarizing the LIBS in media detection in recent years, it aims to provide strong support and guidance for subsequent more in-depth exploration and research.

With the growing adoption of battery energy storage systems in renewable energy sources, electric vehicles (EVs), and portable electronic devices, the effective management of battery systems has become increasingly critical. The advent of wireless battery management systems (wBMSs) represents a significant innovation in battery management technology. Traditional wired battery management systems (BMSs) face challenges, including complexity, increased weight, maintenance difficulties, and a higher chance of connection failure. In contrast, wBMSs offer a robust solution, eliminating physical connections. wBMSs offer enhanced flexibility, reduced packaging complexity, and improved reliability. Given that wBMSs are still in a preliminary stage, this review paper explores their evolution, current state, and future directions. A comprehensive survey of state-of-the-art wBMS technologies, including academic and commercial solutions, is elaborated in this paper. We compare wireless communication technologies like Bluetooth Low Energy (BLE), Zigbee, Near-Field Communication (NFC), Wi-Fi, and cellular networks in the context of wBMSs. We discuss their performance in terms of efficiency, reliability, scalability, and security. Despite its promising outlook, wBMSs still face challenges such as data security, signal interference, regulatory and standardization issues, and competition from the continued advancement of wired BMS technologies, making the advantages of wBMSs less evident. This paper concludes with guidelines for future research and development of wBMSs, aiming to address these challenges and pave the way for a broad adoption of wBMSs across various applications. This paper aims to inspire further research and innovation in the field, contributing to developing an industry-ready wBMS.

This paper proposes a single-phase, transformer-less, seven-level inverter that utilizes eight switches, three capacitors, and two diodes to produce seven voltage levels with triple boosting ability. The availability of the common-ground point eliminates the leakage current in PV applications. The proposed Transformer-Less Triple-Boosting Seven-Level Inverter (TLTB7LI) has the ability to feed different types of loads from non-unity to unity power factors. The voltage balancing of capacitors takes place naturally without the need for auxiliary circuits and complicated control strategies. This paper investigates the appropriateness of the proposed TLTB7LI for grid-connected application. The Peak Current Controller (PCC) is employed to generate the switching pulses and regulate the active/reactive power transfer between the converter and the output, which guarantees the high quality of injected current to the output. Moreover, the operational principles, its control technique, as well as the design procedure of the key components of the proposed inverter have been presented. The superiority of the proposed inverter over existing counterparts has been verified through comparative analysis. The simulation and experimental analysis validated the proper operation of the proposed TLTB7LI.

Blastocystis spp. and Giardia duodenalis are two prevalent zoonotic intestinal parasites that can cause severe diarrhea and intestinal diseases in humans and many animals. Black goat (Capra hircus) farming is increasingly important in China due to the remarkable adaptability, high reproductive performance, rapid growth rate, and significant economic value of black goats. A number of studies have indicated that black goats are the potential reservoir of multiple zoonotic protozoans in China; however, the prevalence and zoonotic status of G. duodenalis and Blastocystis spp. in black goats in Shanxi Province is still unknown. Thus, a total of 1200 fecal samples of black goats were collected from several representative regions at different altitudes in Shanxi Province and were examined for the presence and genotypes of G. duodenallis and Blastocystis spp. by amplifying the beta-giardin (bg), glutamate dehydrogenase (gdh), and triosephosphate isomerase (tpi) loci of G. duodenalis and SSU rRNA of Blastocystis spp. using PCR and sequence analysis methods, respectively. The overall prevalence of G. duodenalis and Blastocystis spp. in black goats in Shanxi Province were 7.5% and 3.5%, respectively. Two assemblages (B and E) of G. duodenalis and four subtypes (ST5, ST10, ST14, and ST30) of Blastocystis spp. were identified, with assemblage E and ST10 as the prevalent genotype and subtype in black goats, respectively. One novel multilocus genotype (MLG) was identified in MLG-E and was designated as MLG-E12. For both G. duodenalis and Blastocystis spp., the prevalence was significantly related to the region and age groups (p < 0.05). This is the first report on the prevalence of G. duodenalis and Blastocystis spp. in black goats in Shanxi Province. These results not only provide baseline data for the prevention and control of both parasites in black goats in Shanxi Province, but also enhance our understanding of the genetic composition and zoonotic potential of these two parasites.

The passive estimation of harmonic sound source depth is of great significance for underwater target localization and identification. Passive source depth estimation using a single hydrophone with an unknown seabed geoacoustic property is a crucial challenge. To address this issue, a harmonic sound source depth estimation algorithm, seabed independent depth estimation (SIDE) algorithm, is proposed. This algorithm combines the estimated mode depth functions, modal amplitudes, and the sign of each modal to estimate the sound source depth. The performance of the SIDE algorithm is analyzed by simulations. Results show that the SIDE is insensitive to the initial range of the sound source, the source depth, the hydrophone depth, the source velocity, and the type of the seabed. Finally, the effectiveness of the SIDE algorithm is verified by the SWellEX-96 data.

Due to insufficient molecular biology and genetic research on Rosa anemoniflora, this endangered plant has not yet received effective protection. Therefore, the complete chloroplast genome sequence of R. anemoniflora, along with comparative analysis of the chloroplast genomes of related species, is necessary and crucial for reconstructing phylogenetic relationships and developing genetic markers to conserve these species. A series of analyses, including genome structure, GC content, gene number, selection pressure, and nucleotide diversity, were performed by comparing the chloroplast genomes of R. anemoniflora and its relatives. The results indicate that the chloroplast genomes of R. anemoniflora and its close relatives are highly conserved in all genome characteristics, and all protein-coding genes in R. anemoniflora have not experienced significant positive or negative selection pressures. Comparative analysis revealed several variation hotspots, such as the atpH-atpI region, which can serve as a DNA barcode for distinguishing R. anemoniflora from its close relatives. Finally, the results confirmed that R. anemoniflora belongs to Rosa section Synstylae and that R. anemoniflora and its close relatives likely originated from the Fujian and Taiwan regions of China and diverged approximately 3.24 million years ago. This study provides crucial information for future biodiversity conservation and genetic resource management.

Hydronephrosis resulting from unilateral ureteral obstruction (UUO) is a common cause of renal injury, often progressing to late-stage renal fibrosis or even potential renal failure. Renal injury and repair processes are accompanied by changes in cellular senescence phenotypes. However, the mechanism is poorly understood. The purpose of this study is to clarify the changes in senescence phenotype at different time points in renal disease caused by UUO and to further investigate whether eliminating senescent cells using the anti-senescence drug ABT263 could attenuate UUO-induced renal disease. Specifically, renal tissues were collected from established UUO rat models on days 1, 2, 7, and 14. The extent of renal tissue injury and fibrosis in rats was assessed using histological examination, serum creatinine, and blood urea nitrogen levels. The apoptotic and proliferative capacities of renal tissues and phenotypic changes in cellular senescence were evaluated. After the intervention of the anti-senescence drug ABT263, the cellular senescence as well as tissue damage changes were re-assessed. We found that before the drug intervention, the UUO rats showed significantly declined renal function, accompanied by renal tubular injury, increased inflammatory response, and oxidative stress, alongside aggravated cellular senescence. Meanwhile, after the treatment with ABT263, the rats had a significantly lower number of senescent cells, attenuated renal tubular injury and apoptosis, enhanced proliferation, reduced oxidative stress and inflammation, improved renal function, and markedly inhibited fibrosis. This suggests that the use of the anti-senescence drug ABT263 to eliminate senescent cells can effectively attenuate UUO-induced renal injury. This highlights the critical role of cellular senescence in the transformation of acute injury into chronic fibrosis.

Geotechnical engineering is civil engineering constructed in rock and soil and includes three main types: underground, foundation, and slope engineering [...]

In scientific computing, neural networks have been widely used to solve partial differential equations (PDEs). In this paper, we propose a novel RBF-assisted hybrid neural network for approximating solutions to PDEs. Inspired by the tendency of physics-informed neural networks (PINNs) to become local approximations after training, the proposed method utilizes a radial basis function (RBF) to provide the normalization and localization properties to the input data. The objective of this strategy is to assist the network in solving PDEs more effectively. During the RBF-assisted processing part, the method selects the center points and collocation points separately to effectively manage data size and computational complexity. Subsequently, the RBF processed data are put into the network for predicting the solutions to PDEs. Finally, a series of experiments are conducted to evaluate the novel method. The numerical results confirm that the proposed method can accelerate the convergence speed of the loss function and improve predictive accuracy.

Ulcerative colitis (UC) is an inflammatory bowel disease with an increasing prevalence year over year, and the medications used to treat patients with UC clinically have severe side effects. Oyster peptides (OPs) have anti-inflammatory and antioxidant properties as functional foods that can alleviate a wide range of inflammatory conditions. However, the application of oyster peptides in ulcerative colitis is not well studied. In this work, an animal model of acute colitis was established using 3% dextran sulfate sodium (DSS), and the impact of OP therapy on colitis in mice was examined. Supplementing with OPs prevented DSS-induced colitis from worsening, reduced the expression of oxidative stress and inflammatory markers, and restored the intestinal barrier damage caused by DSS-induced colitis in mice. The 16S rDNA results showed that the OP treatment improved the gut microbiota structure of the UC mice, including increasing microbial diversity, increasing beneficial bacteria, and decreasing harmful bacteria. In the UC mice, the OP therapy decreased the relative abundance of Family_XIII_AD3011_group and Prevotella_9 and increased the relative abundance of Alistipes. In conclusion, OP treatment can inhibit the TLR4/NF-κB pathway and improve the intestinal microbiota in UC mice, which in turn alleviates DSS-induced colitis, providing a reference for the treatment of clinical UC patients.

The substantial data volume within dynamic point clouds representing three-dimensional moving entities necessitates advancements in compression techniques. Motion estimation (ME) is crucial for reducing point cloud temporal redundancy. Standard block-based ME schemes, which typically utilize the previously decoded point clouds as inter-reference frames, often yield inaccurate and translation-only estimates for dynamic point clouds. To overcome this limitation, we propose an advanced patch-based affine ME scheme for dynamic point cloud geometry compression. Our approach employs a forward-backward jointing ME strategy, generating affine motion-compensated frames for improved inter-geometry references. Before the forward ME process, point cloud motion analysis is conducted on previous frames to perceive motion characteristics. Then, a point cloud is segmented into deformable patches based on geometry correlation and motion coherence. During the forward ME process, affine motion models are introduced to depict the deformable patch motions from the reference to the current frame. Later, affine motion-compensated frames are exploited in the backward ME process to obtain refined motions for better coding performance. Experimental results demonstrate the superiority of our proposed scheme, achieving an average 6.28% geometry bitrate gain over the inter codec anchor. Additional results also validate the effectiveness of key modules within the proposed ME scheme.

Sensors are a key component in industrial automation systems. A fault or malfunction in sensors may degrade control system performance. An engineering system model is usually disturbed by input uncertainties, which brings a challenge for monitoring, diagnosis, and control. In this study, a novel estimation technique, called adaptive unknown-input observer, is proposed to simultaneously reconstruct sensor faults as well as system states. Specifically, the unknown input observer is used to decouple partial disturbances, the un-decoupled disturbances are attenuated by the optimization using linear matrix inequalities, and the adaptive technique is explored to track sensor faults. As a result, a robust reconstruction of the sensor fault as well as system states is then achieved. Furthermore, the proposed robustly adaptive fault reconstruction technique is extended to Lipschitz nonlinear systems subjected to sensor faults and unknown input uncertainties. Finally, the effectiveness of the algorithms is demonstrated using an aircraft system model and robotic arm and comparison studies.

Several trichomonad species have already been identified in pigs, and their pathogenic potential may not be ruled out. To date, however, no information is available regarding the prevalence of trichomonads in pigs in Shanxi Province, North China. In the present study, a total of 362 fecal samples collected from pigs in three representative counties (Qi, Jishan, and Shanyin) in this province were examined for Tetratrichomonas buttreyi, Tritrichomonas foetus, and Pentatrichomonas hominis using a nested polymerase chain reaction (PCR) with primers targeting the small subunit ribosomal RNA (SSU rRNA) gene. The overall prevalence of T. buttreyi was 49.72%, and region and age were found to be significantly associated with T. buttreyi infection, respectively. Only one pig fecal sample from Qi County was found to be positive for T. foetus, and all samples were negative for P. hominis. Molecular evolutionary analysis revealed that some T. buttreyi isolates showed complete genetic identity with those reported previously, and some T. buttreyi isolates and one T. foetus isolate showed minor allelic variations compared with those reported previously. This is the report of the molecular epidemiology of T. foetus and T. buttreyi in pigs in Shanxi Province, North China. These findings not only enrich the knowledge on the distribution of these trichomonad species in pigs in China but also provide baseline information for planning future research and control strategies.

There is a pressing need across various applications for efficiently compressing point clouds. While the Moving Picture Experts Group introduced the geometry-based point cloud compression (G-PCC) standard, its attribute compression scheme falls short of eliminating signal frequency-domain redundancy. This paper proposes a texture-guided graph transform optimization scheme for point cloud attribute compression. We formulate the attribute transform coding task as a graph optimization problem, considering both the decorrelation capability of the graph transform and the sparsity of the optimized graph within a tailored joint optimization framework. First, the point cloud is reorganized and segmented into local clusters using a Hilbert-based scheme, enhancing spatial correlation preservation. Second, the inter-cluster attribute prediction and intra-cluster prediction are conducted on local clusters to remove spatial redundancy and extract texture priors. Third, the underlying graph structure in each cluster is constructed in a joint rate–distortion–sparsity optimization process, guided by geometry structure and texture priors to achieve optimal coding performance. Finally, point cloud attributes are efficiently compressed with the optimized graph transform. Experimental results show the proposed scheme outperforms the state of the art with significant BD-BR gains, surpassing G-PCC by 31.02%, 30.71%, and 32.14% in BD-BR gains for Y, U, and V components, respectively. Subjective evaluation of the attribute reconstruction quality further validates the superiority of our scheme.

Ulcerative colitis (UC) is a chronic intestinal ailment which cannot be completely cured. The occurrence of UC has been on the rise in recent years, which is highly detrimental to patients. The effectiveness of conventional drug treatment is limited. The long-term usage of these agents can lead to substantial adverse effects. Therefore, the development of a safe and efficient dietary supplement is important for the prevention of UC. Echinacea purpurea polysaccharide (EPP) is one of the main bioactive substances in Echinacea purpurea. EPP has many favorable effects, such as antioxidative, anti-inflammatory, and antitumor effects. However, whether EPP can prevent or alleviate UC is still unclear. This study aims to analyze the effect and mechanism of EPP on UC in mice using a 3% dextran sulfate sodium (DSS)-induced UC model. The results showed that dietary supplementation with 200 mg/kg EPP significantly alleviated the shortening of colon length, weight loss, and histopathological damage in DSS-induced colitis mice. Mechanistically, EPP significantly inhibits the activation of the TLR4/NF-κB pathway and preserves the intestinal mechanical barrier integrity by enhancing the expression of claudin-1, ZO-1, and occludin and reducing the loss of goblet cells. Additionally, 16S rRNA sequencing revealed that EPP intervention reduced the abundance of Bacteroides, Escherichia–Shigella, and Klebsiella; the abundance of Lactobacillus increased. The results of nontargeted metabonomics showed that EPP reshaped metabolism. In this study, we clarified the effect of EPP on UC, revealed the potential function of EPP, and supported the use of polysaccharide dietary supplements for UC prevention.

The incidence of ulcerative colitis (UC) is increasing annually, and UC has a serious impact on patients’ lives. Polysaccharides have gained attention as potential drug candidates for treating ulcerative colitis (UC) in recent years. Huaier (Trametes robiniophila Murr) is a fungus that has been used clinically for more than 1000 years, and its bioactive polysaccharide components have been reported to possess immunomodulatory effects, antitumour potential, and renoprotective effects. In this study, we aimed to examine the protective effects and mechanisms of Huaier polysaccharide (HP) against UC. Based on the H2O2-induced oxidative stress model in HT-29 cells and the dextran sulphate sodium salt (DSS)-induced UC model, we demonstrated that Huaier polysaccharides significantly alleviated DSS-induced colitis (weight loss, elevated disease activity index (DAI) scores, and colonic shortening). In addition, HP inhibited oxidative stress and inflammation and alleviated DSS-induced intestinal barrier damage. It also significantly promoted the expression of the mucin Muc2. Furthermore, HP reduced the abundance of harmful bacteria Escherichia-Shigella and promoted the abundance of beneficial bacteria Muribaculaceae_unclassified, Anaerotruncus, and Ruminococcaceae_unclassified to regulate the intestinal flora disturbance caused by DSS. Nontargeted metabolomics revealed that HP intervention would modulate metabolism by promoting levels of 3-hydroxybutyric acid, phosphatidylcholine (PC), and phosphatidylethanolamine (PE). These results demonstrated that HP had the ability to mitigate DSS-induced UC by suppressing oxidative stress and inflammation, maintaining the intestinal barrier, and modulating the intestinal flora. These findings will expand our knowledge of how HP functions and offer a theoretical foundation for using HP as a potential prebiotic to prevent UC.

Spectrally resolved interferometry utilizing a femtosecond laser is widely employed for absolute distance measurement. However, deviations in the output time pulse of the conventional algorithm through inverse Fourier transform are inevitable. Herein, an improved data processing algorithm employing a time-shifting parameter is proposed to improve the accuracy of spectrally resolved interferometry. The principle of the proposed time-shifting algorithm is analyzed theoretically after clarifying the deviation source of the conventional algorithm. Simulation and experimental work were conducted to indicate the improvement in the accuracy of the output absolute distance. The results demonstrated that the proposed algorithm could reduce the deviation of output distances towards the reference values, reaching 0.58 μm by half compared to the conventional algorithm. Furthermore, the measurement uncertainty was evaluated using the Guide to the Expression of Uncertainty in Measurement (GUM), resulting in an expanded uncertainty of 0.71 μm with a 95% confidence.

In order to study the temperature change law of a nitrogen pre-cooling LNG unloading pipeline, a three-dimensional numerical simulation of an LNG pipeline with a bellow expansion bend was conducted using Fluent software (2020 R2). This simulation involved progressively controlling the nitrogen injection temperature and flow rate. The results show that increasing the nitrogen flow rate can improve the pre-cooling rate and reduce the top–bottom temperature difference of the pipeline, but there is an optimal value. Under the same nitrogen injection velocity conditions, it was found that smaller pipe diameters result in smaller temperature differences between the top and bottom of the pipeline. However, due to the reduced cooling capacity of the nitrogen injection, this leads to a decrease in the pre-cooling rate. The top–bottom temperature difference of the pipeline is mainly related to the strength of the natural convection in the pipeline. The stronger the natural convection, the greater the temperature difference between the top and bottom. Gr and Gr/Re2 reflect the relative magnitude of the natural convection intensity and forced convection intensity in the pipe. The larger the Gr and Gr/Re2, the stronger the natural convection. Therefore, Gr and Gr/Re2 are positively correlated with the top–bottom temperature difference, and the variation trend of the top–bottom temperature difference can be judged by the values of Gr and Gr/Re2.

In this study, an ecological framework was developed to sort out the existing forest fire prevention techniques. The subsequent analysis involved comparing the ecological values and application prospects of these techniques developed in different time periods. As ecological applications, fire regimes reflect vegetation response to wildfires, providing valuable insights for shaping the fire risk and behaviors in forests through fuel treatment and vegetation modification. Fuel treatment and the construction of green fire barriers are both rooted in existing ecosystems and possess ecological characteristics. While fuel thinning focuses on reducing the potential fire intensity and severity, green fire barriers have been more targeted for fire prevention purposes. Among these techniques, green fire barriers demonstrate unique sustainability and have the potential to generate long-term ecological and environmental benefits. Through the comprehensive utilization of several fuel management formulas, we can effectively combine the fire prevention demands with ecological maintenance and environment protection. This integrated approach promotes the development of fire-resilient ecosystems and desirable living environments in a more realistic and sustainable manner.

In order to tackle the issue of carbon emissions in logistics and distribution, a vehicle routing model was proposed with the aim of minimizing the overall cost, which includes the vehicle’s fixed cost, transportation costs, and carbon emission costs. An enhanced genetic algorithm, based on a modified Nearest Neighbor Construction (NNC) method, was developed to solve this model. A comparative analysis was conducted using the Solomon dataset to study the impact of carbon emissions on vehicle routing optimization, comparing scenarios with and without considering carbon emission costs. The research findings revealed that the Improved NNC (INNC) method exhibited faster convergence compared with the random generation and random insertion methods. Despite a slight increase of 0.5127% in transportation cost when factoring in carbon emission costs, there was a decrease of 4.6914% in carbon emission costs and 0.3578% in total cost. These results offer theoretical insights and empirical evidence to inform the development of models for the logistics industry in the context of a low-carbon economy.

The excavation and utilization of dormancy loci in breeding are effective endeavors for enhancing the resistance to pre-harvest sprouting (PHS) of wheat varieties. CH1539 is a wheat breeding line with high-level seed dormancy. To clarify the dormant loci carried by CH1539 and obtain linked molecular markers, in this study, a recombinant inbred line (RIL) population derived from the cross of weak dormant SY95-71 and strong dormant CH1539 was genotyped using the Wheat17K single-nucleotide polymorphism (SNP) array, and a high-density genetic map covering 21 chromosomes and consisting of 2437 SNP markers was constructed. Then, the germination percentage (GP) and germination index (GI) of the seeds from each RIL were estimated. Two QTLs for GP on chromosomes 5A and 6B, and four QTLs for GI on chromosomes 5A, 6B, 6D and 7A were identified. Among them, the QTL on chromosomes 6B controlling both GP and GI, temporarily named QGp/Gi.sxau-6B, is a major QTL for seed dormancy with the maximum phenotypic variance explained of 17.66~34.11%. One PCR-based diagnostic marker Ger6B-3 for QGp/Gi.sxau-6B was developed, and the genetic effect of QGp/Gi.sxau-6B on the RIL population and a set of wheat germplasm comprising 97 accessions was successfully confirmed. QGp/Gi.sxau-6B located in the 28.7~30.9 Mbp physical position is different from all the known dormancy loci on chromosomes 6B, and within the interval, there are 30 high-confidence annotated genes. Our results revealed a novel QTL QGp/Gi.sxau-6B whose CH1539 allele had a strong and broad effect on seed dormancy, which will be useful in further PHS-resistant wheat breeding.

The widespread use of non-renewable phosphate fertilizers in agriculture poses a significant pollution threat to soil, necessitating the exploration of sustainable alternatives for phosphate fertility. Releasing phytate phosphorus through microbial phytases presents an eco-friendly solution for sustainable phosphate fertility in agriculture. This study directly inoculated dual-domain β-propeller alkaline phytase (phyHT) derived from Bacillus sp. HJB17 into the soil. The study analyzed the impact of inoculated phyHT on the physicochemical properties of the soil, assessed the variations in enzyme activity of phyHT within the soil, and examined the effects of the treated soil on wheat growth. Additionally, the study explored the enhancement of the available phosphorus in the soil through the inoculation of phyHT in both crop residues and organic fertilizer. PhyHT exhibited the highest catalytic activity at 37 °C and pH 8.0. After soil adsorption, phyHT maintained stable enzymatic activity. PhyHT markedly boosted the available phosphorus in the soil while reducing the soil phytate content by about 20%, increasing the phosphorus levels and enhancing soil fertility. PhyHT effectively degraded phytates in an organic fertilizer and crop residues, increasing the available phosphorus. PhyHT supplementation enhanced growth, biomass, and phosphorus content in both the shoot and root weights of Triticum aestivum. This study establishes phyHT as a viable and eco-friendly method to enhance phosphorus fertility in soil. The direct application of microbial phytases can serve as a sustainable source of phosphate fertility in soil.

The underground utility tunnel in a soft foundation is generally affected by the serious disturbance of the vehicle load during the operation period. Therefore, in this study, for the typical utility tunnel engineering in Suqian City of Jiangsu Province, China, field tests were conducted to monitor the performance of the utility tunnel structure in a soft foundation affected by the ground traffic loads during the operation period. Based on the test results, the datasets whose number is 15,376, composed of the five main disturbance factors (four vehicle operating load parameters and one operating time parameter), and the corresponding two main structure responses (displacement and stress) have been constructed. Based on the obtained datasets, using the proposed new deep learning model called WO-DBN, in which the seven hyperparameters of a deep belief network (DBN) are determined by the whale optimization algorithm (WOA), the safety responses of the utility tunnel structure have been predicted. The results show that for the prediction results, the average absolute error for the displacement is 0.1604, and for the stress, it is 12.3726, which are not significant and can meet the requirement of the real engineering. Therefore, the deep learning model can accurately predict the performance of the utility tunnel structure under a vehicle load and other disturbances, and the model has good applicability.

This paper studies the plastic behavior of the ZK61M magnesium alloy through a combination method of experiments and theoretical models. Based on a dog-bone specimen under different loading directions, mechanical tests under uniaxial tension were carried out, and the hardening behavior was characterized by the Swift–Voce hardening law. The von Mises yield function and the pressure-coupled Drucker yield function were used to predict the load–displacement curves of the ZK61M magnesium alloy under various conditions, respectively, where the material parameters were calibrated by using inverse engineering. The experimental results show that the hardening behavior of the ZK61M magnesium alloy has obvious anisotropy, but the effect of the stress state is more important on the strain hardening behavior of the alloy. Compared with the von Mises yield function, the pressure-coupled Drucker yield function is more accurate when characterizing the plastic behavior and strain hardening in different stress states of shear, uniaxial tension, and plane strain tension for the ZK61M alloy.

In order to solve the star identification problem in the lost space mode for scientific cameras with small fields of view and higher instruction magnitudes, this paper proposes a star identification algorithm based on a hybrid grid pattern. The application of a hybrid pattern generated by multi-calibration stars in the initial matching enables the position distribution features of neighboring stars around the main star to be more comprehensively described and avoids the interference of position noise and magnitude noise as much as possible. Moreover, calibration star filtering is adopted to eliminate incorrect candidates and pick the true matched navigation star from candidate stars in the initial match. Then, the reference star image is utilized to efficiently verify and determine the final identification results of the algorithm via the nearest principle. The performance of the proposed algorithm in simulation experiments shows that, when the position noise is 2 pixels, the identification rate of the algorithm is 96.43%, which is higher than that of the optimized grid algorithm by 2.21% and the grid algorithm by 4.05%; when the magnitude noise is 0.3 mag, the star identification rate of the algorithm is 96.45%, which is superior to the optimized grid algorithm by 2.03% and to the grid algorithm by 3.82%. In addition, in the actual star image test, star magnitude values of ≤12 mag can be successfully identified using the proposed algorithm.

The vertical mass exchange of ozone (O3) plays an important role in determining surface O3 air quality, the understanding of which, however, is greatly limited by the lack of continuous measurements in the vertical direction. Here, we characterize O3 variations at a high-altitude monitoring site at the top of Shanghai Tower (SHT) and discuss the potential impacts of the vertical exchange of air pollutants on O3 air quality within the urban planetary boundary layer (PBL) based on continuous measurements during 2017–2018. During the daytime, two distinct patterns of vertical O3 gradient are detected. In summer, the daytime O3 formation at SHT is observed to be more limited by nitrogen oxides (NOx) than the surface, which, together with the efficient vertical mixings, results in higher O3 levels in the upper mixing layer. In cold months, the opposite vertical gradient is observed, which is associated with weak vertical exchange and NOx-saturated O3 formation. A nighttime O3 reservoir layer and consistent morning O3 entrainments are detected all year round. These results provide direct evidence of the vertical mixings within the urban PBL, underscoring the pressing need for improving vertical resolution in near-surface layers of air quality models.

The concrete piers in steep mountain areas are highly susceptible to damage disasters due to the impact of debris avalanches, which pose a serious threat to the safe operation of bridge structures. In order to investigate the impact load characteristics of debris avalanches on bridge pier structures in V-shaped valley mountain areas, Particle Flow Code 3D (PFC3D) models based on a discrete element method were applied in this study to establish a full-scale three-dimensional model of a debris avalanche in a V-shaped valley. By installing double-column piers in the influence zone of the debris avalanche, the impact force, accumulation morphology, motion characteristics of debris particles, internal force response of the double-column piers, and impact energy indicators were investigated. In addition, parameters such as the layout position of the piers and the impact angle of the debris were studied. The results showed that the particles at the front edge of the debris avalanche have a significant impact on the magnitude and distribution of the impact force on the piers. It is important to consider the layout position of the piers and the impact angle of the debris when designing bridge pier structures in high, steep mountain areas. There was a significant difference in the movement patterns between the particles at the front and rear edges of the landslide. The particles at the front edge had a higher velocity and stronger impact, while the particles at the rear edge had a slower velocity and were more likely to be obstructed by bridge piers, leading to accumulation. The obstruction effect of the piers on the debris particles was closely related to their positioning and the impact angle. Piers that were closer to the center of the valley and had a larger impact angle have a more significant obstruction effect, and the topography of the valley had a significant focusing effect on the debris avalanche, resulting in a greater impact force and energy on the piers located closer to the center of the valley. The impact force amplitude and duration of landslide debris on bridge piers showed a significant difference between the bottom and upper piers, as well as between the piers on the upstream and downstream sides. These research findings can provide valuable references for the design and disaster assessment of bridge piers for impact prevention in steep slopes and mountainous areas with deep ravines.

China possesses abundant wild germplasm resources and a wide range of cultivated strains of Stropharia rugosoannulata. However, issues such as genetic diversity and unclear genetic relationships have had an impact on the classification and preservation of germplasm resources, the breeding of new varieties, and the promotion of superior strains. There is an urgent need for genetic diversity analysis and assessment of germplasm resources. In this study, we conducted whole-genome resequencing of 50 cultivated and wild strains collected from various regions across the country. After applying a series of filtering parameters, we obtained 888,536 high-quality Single Nucleotide Polymorphism (SNP) markers. Using these SNP markers, we performed principal component analysis, population structure analysis, and phylogenetic clusters analysis on the 50 strains. Most cultivated strains exhibited high genetic similarity, while significant genetic diversity was observed among wild strains. Based on factors such as marker distribution throughout the entire genome and marker quality, we selected 358 core SNP markers to construct SNP fingerprints. Two-dimensional barcodes were generated for each strain to enable specific identification. Additionally, the mycelial growth rate of strains was evaluated on Potato Dextrose Agar (PDA) and substrate culture media. We also assessed their lignin degradation capability using guaiacol agar plates assay. It was observed that the mycelial growth rate on PDA and substrate culture medium exhibited a significant correlation with the diameter of the mycelial colony on guaiacol agar medium. Additionally, the correlation between the mycelial growth rate on the substrate medium and that on the guaiacol agar plate was stronger than that on PDA medium. This study provided molecular-level identification and assessment of germplasm resources. It clarified the genetic relationships among strains and the characteristics of mycelium growth-related agronomic traits of each strain. This research contributed to the enrichment and development of utilizable germplasm resources and breeding materials for S. rugosoannulata, offering a scientific basis for further research.

As an extremely important energy source, improving the efficiency and accuracy of coal classification is important for industrial production and pollution reduction. Laser-induced breakdown spectroscopy (LIBS) is a new technology for coal classification which has the ability to rapidly analyze coal compared with traditional coal analysis methods. In the practical application of LIBS, a large amount of labeling data is usually required, but it is quite difficult to obtain labeling data in industrial sites. In this paper, to address the problem of insufficient labeled data, a semi-supervised classification model (SGAN) based on adversarial neural network is proposed, which can utilize unlabeled data to improve the classification accuracy. The effects of labeled and unlabeled samples on the classification accuracy of the SGAN model are investigated, and the results show that the number of labeled and unlabeled samples are positively correlated, and the highest average classification accuracy that the model can achieve is 98.5%. In addition, the classification accuracies of SGAN and other models (e.g., CNN, RF) are also compared, and the results show that, with the same number of labeled samples in the three models, SGAN performs better after the number of unlabeled samples reaches a certain level, with an improvement of 0.7% and 2.5% compared to the CNN and RF models, respectively. This study provides new ideas for the application of semi-supervised learning in LIBS.

Marine propellers work under severe service conditions, where they commonly suffer from mechanical, electrochemical, and biological corrosion damage. The major mechanical corrosion involves cavitation, erosion, and impingement corrosion. On the other hand, the major electrochemical corrosion involves galvanic corrosion and electrolysis. As a result, consideration of both desired mechanical and electrochemical properties is necessary when designing a marine propeller coating. In this study, a PVB (polyvinyl butyral) and an epoxy coating were formulated without corrosion inhibitors to investigate the desired coating properties for marine propeller applications. The two coatings were compared with a Cr-containing commercial marine propeller coating to investigate the advantages and disadvantages of using PVB and epoxy for marine propeller coatings. It was found that it is desirable for marine propeller coatings to be flexible to avoid cracking and flaking; to be able to withstand high pH in order to resist cathodic disbondment (electrolysis); to have adequate primer–substrate adhesion; and, ideally, to be able to self-heal when the coating is damaged (cavitation). It was found that the PVB-ZO coating has more desirable properties, and introducing self-healing properties could be one of the options for further optimization in the future.

The as-cast (Fe50Mn30Co10Cr10)97C2Mo1 HEA (high entropy alloy) was prepared and cold-rolled at 70%. Subsequently, annealing heat treatment at different temperatures (900 °C, 950 °C, 1000 °C) was carried out. The microstructure evolution and mechanical properties of the HEA were systematically investigated. The results showed that the HEA annealed at 900 °C and 950 °C exhibited uneven grain size and rich σ precipitation phase at grain boundaries. The grains began to grow and complete recrystallization, and no σ phases were observed in HEA annealed at 1000 °C, which resulted in a higher tensile strength of ~885 MPa and elongation of ~68% compared with other annealed HEAs. The higher volume fraction of annealing twins with 60° orientation was produced in HEA annealed at 1000 °C, which enhanced the tensile strength and plasticity via the Twinning-induced plasticity (TWIP) mechanism.

Revascularization of coronary chronic total occlusion (CTO) still remains controversial. The factors that impact collateral circulation and myocardial perfusion are of interest. Circular RNA (circRNA) has been shown to regulate the process of angiogenesis. However, the effects of circ-membrane-bound O-acyltransferase domain containing 2 (circ-MBOAT2) on angiogenesis in patients with CTO were unclear. In this study, we evaluated circulating circRNAs and miRNAs in patients with CTO and stable coronary artery disease using high-throughput sequencing. Another cohort of patients were selected to verify the expressions of circ-MBOAT2 and miR-495. The role and mechanism of circ-MBOAT2 in the process of angiogenesis were explored through in vitro and vivo studies. Finally, we came back to a clinical perspective and investigated whether circ-MBOAT2 and miR-495 were associated with the improvement of myocardial perfusion evaluated by single-photon emission computed tomography (SPECT). We found that the expression of circ-MBOAT2 was significantly up-regulated while miR-495 was significantly down-regulated in patients with CTO. The expression of circ-MBOAT2 was negatively correlated with miR-495 in patients with CTO. In an in vitro study, we found that circ-MBOAT2 promoted tube formation and cell migration via the miR-495/NOTCH1 axis in endothelial cells. In an in vivo study, we showed that the inhibition of miR-495 caused the increase in collateral formation in mice after hindlimb ischemia. In a human study, we showed the expressions of circ-MBOAT2 and miR-495 were associated with myocardial perfusion improvement after revascularization of CTO. In conclusion, circ-MBOAT2 regulates angiogenesis via the miR-495/NOTCH1 axis and associates with myocardial perfusion in patients with CTO. Our findings suggest that circ-MBOAT2 and miR-495 may be potential therapeutic targets and prognostic factors for patients with CTO.

Carotenoids are extensively used in drugs, cosmetics, nutrients, and foods, owing to their antioxidant and anti-inflammatory characteristics. Diverse marine heterotrophic prokaryotes can accumulate carotenoids and become promising alternatives for the advancement of carotenoids production. In this research, 55 strains were isolated and cultivated from tidal flat sediment in Zhoushan and classified into the phyla Pseudomonadota (n = 24), Bacillota (n = 18), Bacteroidota (n = 9), and Actinomycetota (n = 4). Nine of them accumulated carotenoids, and most of them belonged to the families Flavobacteriaceae (n = 4) and Erythrobacteraceae (n = 4). Among those carotenoid-producing strains, one strain, designated as D39T, was proposed as one novel species belonging to the genus Croceibacterium through polyphasic taxonomy approaches. Genomic annotations and carotenoid compound determinations revealed that strain D39T encoded crtEBIYZG genes and mainly accumulated zeaxanthin as major carotenoids. Furthermore, carotenoid biosynthesis pathway in the majority of Croceibacterium strains were identical with that in the strain D39T, implying that Croceibacterium members can be sources of producing zeaxanthin. This study enhances knowledge of microbial biodiversity in tidal flats, proposes a novel carotenoid-producing Croceibacterium species, and elucidates carotenoid biosynthesis pathway in the genus Croceibacterium, which contribute to enriching marine carotenoid-producing strains and promoting a comprehensive insight into genomic contents of them.

Transit-oriented development (TOD) has become a dominant form of spatial planning and land use in large cities internationally. As the intersections of urban space and rail transportation, metro station areas play a key public service function in the lives of city residents. Based on the “5D” index and Node-Place theory in the metro station area, current research on the built environment in metro station areas focuses on improving the economic and transportation efficiency while neglecting public perception of the construction of station space. Sentiments, as an important part of the individual’s perception, are closely related to the built environment. Therefore, this study takes 187 metro stations within the fifth ring road of Beijing, China, as an example and extracts public sentiment information from social media data using a wide range of natural language processing techniques to quantitatively analyze the distribution of the public’s sentiment characteristics (including intensity, polarity, and category) in the metro station area and deeply explores the spatial correlation with the distribution of the objective built environment elements. The study shows that influenced by the spatial design of the metro station, density, land use functions, etc., the sentiment intensity of the station area within the Fifth Ring Road of Beijing is “strong in the east and weak in the west, strong in the north and weak in the south”, and the sentiment polarity has the characteristic of gradually negative from inside to outside in a circular pattern. Synthesizing the sentiment perception in the metro station area, our study further divided the Beijing metro station area into four major categories and eight specific subtypes.