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Type 2 diabetes (T2D) represents the most prevalent metabolic condition that is primarily distinguished by a range of metabolic imbalances, including hyperglycemia, hyperlipidemia, and insulin resistance (IR). Currently, mitophagy has become increasingly recognized as an important process involved in the pathogenesis and progression of T2D. Therefore, it is very important to explore the role of mitochondrial damage and autophagy-related genes in T2D. This study investigated the role of mitophagy in the development of T2D, and 12 MRHGs associated with T2D were identified using bioinformatic analysis and machine learning methods. Our findings provide the first insight into mitophagy-related genes and their mechanisms in T2D. This study aimed to investigate possible molecular targets for therapy and the underlying mechanisms involved in T2D. This information might be useful to further elucidate the pathogenesis of T2D-related diseases and identify more optimal therapeutic approaches.

The development of conductive coatings has significant implications for microelectronics and electrochemistry. However, conductive coatings may exhibit different electrochemical properties when prepared on different substrate materials. This research explores the comparative performance of graphene, graphene oxide (GO), and silver nanoparticle (Ag NP) composites as conductive coatings on diverse substrate materials, including polydimethylsiloxane (PDMS), polymethyl methacrylate (PMMA), and glass. The study employed various preparation methods, such as mixing conductive materials with substrate materials and preparing copolymer composite materials. The conductive coating approach was found to be the most straightforward and convenient, with broader development prospects and fewer restrictive conditions. The results indicate that the distinct surface characteristics of the substrate materials influence the conductive properties of coating materials. Consequently, results show that graphene exhibits the highest conductivity on all three substrates, while GO is more conductive than Ag NPs on PMMA and PDMS but less conductive than Ag NPs on glass. That offers valuable insights into the selection of substrate materials and coating materials for the preparation of conductive materials.

Chronic obstructive pulmonary disease (COPD) is a respiratory and systemic disease affecting more than 300 million people globally every year, and it also becomes a substantial economic burden. COPD is commonly comorbid with various underlying diseases such as cancer, cardiovascular diseases, cerebrovascular diseases, diabetes mellitus, osteoporosis, etc. It has been shown that statins can improve a significant decline in pulmonary function among COPD patients due to their pleiomorphic effect. Some systematic reviews also reported that statins reduced the risk of COPD-related events such as cancer and cardiovascular events, eventually resulting in more favorable outcomes than for non-statin user COPD patients. However, the physiological mechanism is still elucidated. Recently, it has been reported that statins influence the gut microbial composition with increased relative abundance of Akkermansia muciniphila and Faecalibacterium prausnitzii and act with pleiomorphic effects such as anti-inflammatory and anti-cancer effects through modulating gut dysbiosis. We described this review to focus on whether statins can be a useful preventive option for COPD.

In this study, we consider the introduction of new mobility services and technologies into the megacity of Beijing, China, as per developed strategy and action plans, in order to investigate their potential contribution to sustainable mobility. This includes population relocation (decentralization), the construction of new rail lines, the introduction of shared bike services as a feeder to subway stations, the electrification of passenger vehicles and the adoption of automated and shared vehicles. The well-established, system dynamics-based MARS model is adapted to Beijing and further improved via the inclusion of these new services, technologies and policies. We find that decentralization can have a profound effect on overall sustainability if not considered in conjunction with other policies and that new rail lines and shared bikes may only have benefits in specific zones. Shared and automated vehicles could increase VKT by 60% and reduce active and public transport trips by a quarter. As such, nuanced integrated policy approaches will be required that are similar to those currently in place, such as imposed car shedding and taxi fleet control.

Acute lung injury (ALI) and its most severe form, acute respiratory distress syndrome (ARDS), are pulmonary conditions that cause significant morbidity and mortality. The common etiologies of these conditions include pneumonia, pulmonary contusion, fat embolism, smoke inhalation, sepsis, shock, and acute pancreatitis. Inflammation, oxidative stress, apoptosis, and autophagy are key pathophysiological mechanisms underlying ALI. Hydrogen sulfide (H2S) and sulfur dioxide (SO2) are sulfur-containing gas signaling molecules that can mitigate these pathogenic processes by modulating various signaling pathways, such as toll-like receptor 4 (TLR4)/nod-like receptor protein 3 (NLRP3), extracellular signal-regulating protein kinase 1/2 (ERK1/2), mitogen-activated protein kinase (MAPK), phosphatidyl inositol 3 kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR), and nuclear factor kappa B (NF-κB), thereby conferring protection against ALI. Given the limited clinical effectiveness of prevailing ALI treatments, investigation of the modulation of sulfur-containing gas signaling molecules (H2S and SO2) in ALI is imperative. This article presents an overview of the regulatory pathways of sulfur-containing gas signaling molecules in ALI animal models induced by various stimuli, such as lipopolysaccharide, gas inhalation, oleic acid, and ischemia-reperfusion. Furthermore, this study explored the therapeutic prospects of diverse H2S and SO2 donors for ALI, stemming from diverse etiologies. The aim of the present study was to establish a theoretical framework, in order to promote the new treatment of ALI.

Gynostemma pentaphyllum (Thunb.) Makino (GP), a plant with homology of medicine and food, as a traditional Chinese medicine, possesses promising biological activities in the prevention and treatment of type 2 diabetes mellitus (T2DM). However, the material basis and the mechanism of action of GP in the treatment of T2DM have not been fully elucidated. This study aimed to clarify the active components, potential targets and signaling pathways of GP in treating T2DM. The chemical ingredients of GP were collected by combining UPLC-HRMS analysis and literature research. Network pharmacology revealed that GP had 32 components and 326 potential targets in treating T2DM. The results showed that GP affected T2DM by mediating the insulin resistance signaling pathway, PI3K/Akt signaling pathway and FoxO1 signaling pathway, which had a close relationship with T2DM. Molecular docking results showed that STAT3, PIK3CA, AKT1, EGFR, VEGFA and INSR had high affinity with the active compounds of GP. In vitro, GP extracts obviously increased the glucose uptake and glucose consumption in IR-HepG2 cells. GP extracts increased the levels of PI3K, p-AKT, p-GSK3β and p-FoxO1 and decreased the expression of p-IRS1, p-GS, PEPCK and G6Pase, which indicated that GP could promote glycogen synthesis and inhibit gluconeogenesis by regulating the IRS1/PI3K/Akt signaling pathway. The results demonstrated that GP could improve insulin resistance by promoting glucose uptake and glycogen synthesis and inhibiting gluconeogenesis through regulating the IRS1/PI3K/Akt signaling pathway, which might be a potential alternative therapy for T2DM.

In this study, we report the effect of Zr4+ doping on the optical energy gap and microwave dielectric properties of rutile TiO2. Rietveld analysis explicitly confirmed that Zr4+ occupies the octahedral site, forming a single-phase tetragonal structure below the solubility limit (x < 0.10). Notably, at x = 0.025, a significant enhancement in Q × fo was observed. This enhancement was attributed to the reduction in dielectric loss, associated with a decrease in oxygen vacancies and a lower concentration of Ti3+ paramagnetic centers. This conclusion was supported by Raman and electron paramagnetic resonance spectroscopy, respectively. The origin of high τf in rutile Ti1−xZrxO2 is explained on the basis of the octahedral distortion/tetragonality ratio, covalency, and bond strength.

Background: Despite the prevalence and incidence of kidney stones progressively increasing worldwide, public awareness of this condition remains unclear. Understanding trends of awareness can assist healthcare professionals and policymakers in planning and implementing targeted health interventions. This study investigated online search interest in “kidney stone” by analyzing Google Trends, focusing on stationarity of the trends and predicting future trends. Methods: We performed time series analysis on worldwide Google monthly search data from January 2004 to November 2023. The Augmented Dickey–Fuller (ADF) test was used to assess the stationarity of the data, with a p-value below 0.05 indicating stationarity. Time series forecasting was performed using the autoregressive integrated moving average to predict future trends. Results: The highest search interest for “kidney stone” (score 100) was in August 2022, while the lowest was in December 2007 (score 36). As of November 2023, search interest remained high, at 92. The ADF test was significant (p = 0.023), confirming data stationarity. The time series forecasting projected continued high public interest, likely reflecting ongoing concern and awareness. Notably, diverse regions such as Iran, the Philippines, Ecuador, the United States, and Nepal showed significant interest, suggesting widespread awareness of nephrolithiasis. Conclusion: This study highlighted that “kidney stone” is a consistently relevant health issue globally. The increase and stationarity of search trends, the forecasted sustained interest, and diverse regional interest emphasize the need for collaborative research and educational initiatives. This study’s analysis serves as a valuable tool for shaping future healthcare policies and research directions in addressing nephrolithiasis related health challenges.

Cultural routes are a composite set of heritage sites that refer to historical routes of human communication. As key products of cultural tourism, they provide visitors with rich cultural experiences across regions. We systematically review reports and studies related to the tourism development of 38 cultural route cases worldwide, with a special focus on their distribution, typology, planning patterns, and tools for cultural tourism. We summarized eight tools and found some differences in how often these eight tools are used by the different types of routes and different planning patterns for route tourism. This study also developed an evaluation system based on the conservation principles of cultural routes to determine how different tourism tools affect the conservation and development of historical regions. Although tourism decision-makers have made numerous efforts to protect and develop cultural routes, there are still many problems and challenges in the process of tourism development along cultural routes. We conclude the paper by making recommendations for decision-makers and researchers concerning future route tourism planning and study.

Background: Pancreas transplantation is a crucial surgical intervention for managing diabetes, but it faces challenges such as its invasive nature, stringent patient selection criteria, organ scarcity, and centralized expertise. Despite the steadily increasing number of pancreas transplants in the United States, there is a need to understand global trends in interest to increase awareness of and participation in pancreas and islet cell transplantation. Methods: We analyzed Google Search trends for “Pancreas Transplantation” and “Islet Cell Transplantation” from 2004 to 14 November 2023, assessing variations in search interest over time and across geographical locations. The Augmented Dickey–Fuller (ADF) test was used to determine the stationarity of the trends (p < 0.05). Results: Search interest for “Pancreas Transplantation” varied from its 2004 baseline, with a general decline in peak interest over time. The lowest interest was in December 2010, with a slight increase by November 2023. Ecuador, Kuwait, and Saudi Arabia showed the highest search interest. “Islet Cell Transplantation” had its lowest interest in December 2016 and a more pronounced decline over time, with Poland, China, and South Korea having the highest search volumes. In the U.S., “Pancreas Transplantation” ranked 4th in interest, while “Islet Cell Transplantation” ranked 11th. The ADF test confirmed the stationarity of the search trends for both procedures. Conclusions: “Pancreas Transplantation” and “Islet Cell Transplantation” showed initial peaks in search interest followed by a general downtrend. The stationary search trends suggest a lack of significant fluctuations or cyclical variations. These findings highlight the need for enhanced educational initiatives to increase the understanding and awareness of these critical transplant procedures among the public and professionals.

In the present work, we evaluated the antifungal activities of two novel ebselen analogs, N-allyl-benzisoselenazol-3(2H)-one (N-allyl-bs) and N-3-methylbutylbenzisoselenazol-3(2H)-one (N-3mb-bs). Colorimetric and turbidity assays were performed to determine the minimum inhibitory concentration (MIC) of these compounds in S1 (fluconazole-sensitive) and S2 (fluconazole-resistant) strains of C. albicans. N-3mb-bs was more active than the N-allyl-bs compound. It is noteworthy that the concentration of N-3mb-bs observed to inhibit fungal growth by 50% (18.2 µM) was similar to the concentration observed to inhibit the activity of the yeast plasma membrane H+-ATPase (Pma1p) by 50% (19.6 µM). We next implemented a mouse model of vulvovaginal candidiasis (VVC) using the S1 strain and examined the mouse and yeast proteins present in the vaginal lavage fluid using proteomics. The yeast proteins detected were predominately glycolytic enzymes or virulence factors associated with C. albicans while the mouse proteins present in the lavage fluid included eosinophil peroxidase, desmocollin-1, and gasdermin-A. We then utilized the N-3mb-bs compound (12.5 mg/kg) in the mouse VVC model and observed that it significantly reduced the vaginal fungal burden, histopathological changes in vagina tissue, and expression of myeloperoxidase (MPO). All in all, the present work has identified a potentially promising drug candidate for VVC treatment.

The high-speed railway (HSR) system imposes stringent requirements for track smoothness. However, conventional seismic isolation bearings frequently fail to meet these demands. To address this challenge, a novel seismic isolation bearing was developed based on the principle of functional separation design. This innovative bearing effectively achieves the multistage control objectives, including amplitude limitation to ensure track smoothness during frequent earthquakes, energy dissipation to guarantee train running safety during design earthquakes, and structural integrity maintenance to prevent beam collapse during rare earthquakes. Firstly, an overview of the novel isolation bearing’s structural design and operational principle is provided. Subsequently, a corresponding mechanical model is formulated, with the parameters of the new bearing determined through finite element analysis. The study then compares the seismic performance of the general rubber bearing and the new bearing, using an HSR simply supported bridge as an engineering background. The dynamic response of the bridge under varying seismic waves, pier heights, and bridge spans is meticulously analyzed. The results indicate that the new bearing can achieve multistage control. Compared to general bearings, it reduces bridge displacement vibration by over 46.4% under frequent, design, and rare earthquakes. The bridge deformation under frequent earthquakes remains below 3 mm, thus meeting the track smoothness requirements for normal HSR operations. Additionally, the study reveals that higher pier heights increase the seismic response, peaking at 15 m. The vibration reduction provided by the new bearing varies but remains effective in most earthquake scenarios, with maximum reductions of 92.9% for displacement and 74.17% for bending moment. Furthermore, larger bridge spans also increase the seismic response, with the 24 m span bridge outperforming the 32 m span bridge. In conclusion, the novel seismic isolation bearing significantly enhances the seismic performance of HSR bridges, ensuring train running safety and operational reliability.

Enhancing global agricultural sustainability critically requires improving the physicochemical properties of saline–alkali soil. Biochar has gained increasing attention as a strategy due to its unique properties. However, its effect on the physicochemical properties of saline–alkali soil varies significantly. This study uses psychometric meta-analysis across 137 studies to synthesize the findings from 1447 relatively independent data sets. This study investigates the effects of biochar with different characteristics on the top 20 cm of various saline–alkali soils. In addition, aggregated boosted tree (ABT) analysis was used to identify the key factors of biochar influencing the physicochemical properties of saline soils. The results showed that biochar application has a positive effect on improving soil properties by reducing the sodium adsorption ratio (SAR) and the exchangeable sodium percentage (ESP) by 30.31% and 28.88%, respectively, with a notable 48.97% enhancement in cation exchange capacity (CEC). A significant inverse relationship was found between soil salinity (SC) and ESP, while other factors were synergistic. Biochar application to mildly saline soil (0.4%). However, the reduction in SC in highly saline soil was 4.9 times greater than in moderately saline soils. The enhancement of soil physical properties positively correlated with higher biochar application rates, largely driven by soil movements associated with the migration of soil moisture. Biochar produced at 401–500 °C was generally the most effective in improving the physicochemical properties of various saline–alkali soils. In water surplus regions, for mildly saline soil with pH < 8.5, mixed biochar (pH 6–8) at 41–80 t ha−1 was the most effective in soil improvement. Moreover, in water deficit areas with soil at pH ≥ 8.5, biochar with pH ≤ 6 applied at rates of >80 t ha−1 showed the greatest benefits. Agricultural residue biochar showed superior efficiency in ameliorating highly alkaline (pH ≥ 8.5) soil. In contrast, the use of mixed types of biochar was the most effective in the amelioration of other soil types.

With the rapid evolution of the Internet of Things (IoT), smart home systems have greatly improved people’s lifestyles and quality of life. However, smart home systems based on a single sensor cannot efficiently control multiple terminals, which limits product penetration into lower-end markets. Here, we have developed a dual-mode smart home system based on a porous triboelectric nanogenerator (TENG), which effectively compensates for the shortcomings of smart home systems being unable to control multiple appliances through a single switch. Benefitting from the remarkable electronegativity of MXene and the ameliorative specific surface area of the friction layer, the output characteristics of the porous TENG are greatly improved. Under the identical external stimulus, the open-circuit voltage (VOC) and short-circuit current (ISC) of the porous TENG were 3.03 and 3.04 times higher than those of the TENG with a pure PVDF membrane used as the friction layer. Thanks to the excellent output performance and good linear relationship between pressure and voltage, the developed dual-mode smart home system could efficiently control multiple terminals through a single sensor. This work not only provides theoretical support for developing high-performance TENGs but also paves the way to designing multifunctional smart home systems.

Advances in biomimetic triboelectric nanogenerators (TENGs) have significant implications for electronic skin (e-skin) and human–machine interaction (HMI). Emphasizing the need to mimic complex functionalities of natural systems, particularly human skin, TENGs leverage triboelectricity and electrostatic induction to bridge the gap in traditional electronic devices’ responsiveness and adaptability. The exploration begins with an overview of TENGs’ operational principles and modes, transitioning into structural and material biomimicry inspired by plant and animal models, proteins, fibers, and hydrogels. Key applications in tactile sensing, motion sensing, and intelligent control within e-skins and HMI systems are highlighted, showcasing TENGs’ potential in revolutionizing wearable technologies and robotic systems. This review also addresses the challenges in performance enhancement, scalability, and system integration of TENGs. It points to future research directions, including optimizing energy conversion efficiency, discovering new materials, and employing micro-nanostructuring techniques for enhanced triboelectric charges and energy conversion. The scalability and cost-effectiveness of TENG production, pivotal for mainstream application, are discussed along with the need for versatile integration with various electronic systems. The review underlines the significance of making bioinspired TENGs more accessible and applicable in everyday technology, focusing on compatibility, user comfort, and durability. Conclusively, it underscores the role of bioinspired TENGs in advancing wearable technology and interactive systems, indicating a bright future for these innovations in practical applications.

Skin photoaging, resulting from prolonged exposure to ultraviolet radiation, is a form of exogenous aging that not only impacts the aesthetic aspect of the skin but also exhibits a strong correlation with the onset of skin cancer. Nonetheless, the safety profile of non-natural anti-photoaging medications and the underlying physiological alterations during the process of photoaging remain inadequately elucidated. Consequently, there exists a pressing necessity to devise more secure interventions involving anti-photoaging drugs. Multiple studies have demonstrated the noteworthy significance of marine biomolecules in addressing safety concerns related to anti-photoaging and safeguarding the skin. Notably, bioactive peptides have gained considerable attention in anti-photoaging research due to their capacity to mitigate the physiological alterations associated with photoaging, including oxidative stress; inflammatory response; the abnormal expression of matrix metalloproteinase, hyaluronidase, and elastase; and excessive melanin synthesis. This review provides a systematic description of the research progress on the anti-photoaging and skin protection mechanism of marine bioactive peptides. The focus is on the utilization of marine bioactive peptides as anti-photoaging agents, aiming to offer theoretical references for the development of novel anti-photoaging drugs and methodologies. Additionally, the future prospects of anti-aging drugs are discussed, providing an initial reference for further research in this field.

Clostridial fermentation is the determining process causing the spoilage of direct-cut alfalfa silage, and the application of lactic acid bacteria (LAB) inoculant is considered as the most promising technology for inhibiting clostridial fermentation. In order to screen target-based LAB strains, identification and correlation analysis of key Clostridia and LAB species in alfalfa silage were conducted in this study. Three alfalfa cultivars (Sanditi, SD; Celsius, CE; SW5909, SW) were harvested at the early bloom stage and ensiled without (CK) or with LAB inoculant (LB) and sucrose (SC) for 60 d. Single-molecule real-time sequencing was used to identify dominant Clostridia and LAB species, and LAB with significant inhibitory effects on dominant Clostridia was screened via correlation network analysis. The results showed that silages CK and LB encountered severe clostridial fermentation as indicated by large amounts of butyric acid (BA) and ammoniacal nitrogen (NH3-N) production. Compared to silages CK and LB, SC treatment decreased (p < 0.05) BA and NH3-N concentrations, as well as decreasing (p < 0.05) the bacterial community indexes of Shannon and Chao1. Lactiplantibacillus pentosus was the first dominant LAB in silage CK of alfalfa SD and CE. The first dominant LAB in silage LB was also identified as L. pentosus, rather than Lentilactobacillus buchneri and Lactiplantibacillus plantarum in the used inoculant. L. buchneri became more abundant in silage SC of alfalfa SD and CE, accounting for the high fermentation quality of these silages. Clostridium tyrobutyricum, Clostridium luticellarii, Garciella sp._GK3, Clostridium sporogenes, Clostridium perfringens, and Clostridium sp._BTY5 were the most dominant Clostridia species in alfalfa silage. Furthermore, Enterococcus faecalis, L. buchneri, and L. pentosus exhibited significant (p < 0.05) inhibitory effects on C. tyrobutyricum, C. luticellarii, and Garciella sp._GK3, respectively, which were the top three Clostridia species associated with clostridial fermentation. In conclusion, E. faecalis, L. buchneri, and L. pentosus were screened and can be used as potential LAB inoculants for the targeted inhibition of clostridial fermentation.

Since the characteristics of plug seedlings affect the effectiveness of automatic transplanting, this study aimed to explore the effect of the addition of biochar into substrates on the growth of plug seedlings before and after transplanting. The physicochemical properties of substrates with 0%, 5%, 10%, 15%, 20%, and 25% biochar addition all met the requirements of seedling cultivation. The growth trend, root systems, and mechanical properties of seedlings before transplanting and the leaf gas exchange parameters of seedlings after transplanting were measured in this study. The results indicated that the seedlings cultivated with 10% biochar added to the substrate achieved the best growth trend and physiological indices, and the root systems under this treatment were also stronger than those of other treatments, while the seedlings cultivated with 25% biochar treatment were the worst, with less than 22.23% of the growth seen in the 10% biochar treatment, and even less than 1.5% of the growth of the seedlings cultivated without biochar treatment. Since the strong root systems could enhance the mechanical properties of seedling pots, the seedling pots cultivated with 10% biochar added into the substrate possessed the best compression resistance properties, with the maximum value of 49.52 N, and could maintain maximum completeness after free-fall impacting, wherein the loss of root and substrate was only 8.22%. The analysis results of seedlings cultivated after impacting proposed that the seedlings with better growth trends and root systems before transplanting could obtain better leaf gas exchange parameters during the flower stage after transplanting, so the seedlings cultivated with 5%~10% biochar added into the substrate grew better after impacting and then transplanting. It was noticed that the seedlings cultivated with appropriate biochar added into the substrate were able to achieve the optimal growth parameters and mechanical properties before and after transplanting, which were better able to meet the requirements of automatic transplanting. Thus, this study can promote the development of automatic transplanting technology to some extent.

Nitrogen fertilization is widely known to affect plant metabolism, which subsequently influences phytophagous insects through a bottom-up effect. The interplay between plants and insects is often overlooked in studies examining the effects of nitrogen fertilization on insect performance. Here, we assessed the performance of green and red morphs of pea aphid Acyrthosiphon pisum feeding on alfalfa Medicago truncatula with and without nitrogen fertilization and examined how nitrogen fertilization and aphid infestation affect plant amino acid composition and phytohormone-dependent defenses. The results showed that nitrogen fertilization significantly enhanced the growth rate and fecundity of the green-morph aphid but only slightly increased the growth rate of the red morph. The feeding behaviors of the two morphs of aphid were similarly inhibited by nitrogen fertilization, manifested as prolonged stylet pathway duration and shortened phloem ingestion duration. With nitrogen fertilization, the green-morph-aphid-infested plant accumulated more free amino acids, particularly essential amino acids, when compared with the red-morph aphid. Furthermore, the infestation of both morphs of aphid repressed the expression of genes involved in salicylic acid-dependent defense while enhancing those involved in jasmonic acid/ethylene signaling under nitrogen fertilization. These results suggest that nitrogen fertilization and aphid infestation interact in manipulating plant metabolism, with nutritional changes playing a vital role in the aphid morph-specific growth and fecundity response to nitrogen fertilization.

Acanthocepola indica, a deep-sea snake fish, is primarily found in the Indo-west Pacific region, including India, Korea, Japan, and the South China Sea. The taxonomic classification of A. indica based on morphological characteristics remains inaccurate and unclear. In this study, we utilized next-generation sequencing to generate comprehensive genomic data for A. indica. The estimated genome size of A. indica was 422.95 Mb, with a heterozygosity ratio of 1.02% and a sequence repeat ratio of 22.43%. Our analysis suggested that A. indica is diploid, and the draft genome assembly consists of 1,059,784 contigs with a contig N50 of 1942 bp. We identified a total of 444,728 simple sequence repeats in the genome of A. indica. Furthermore, we successfully assembled the complete mitochondrial genome (16,439 bp) of A. indica, which included 13 protein-coding genes, 22 tRNA genes and 2 rRNA genes. Phylogenetic analysis based on mitochondrial genomes revealed that A. indica is closely related to Acanthocepola krusensternii and Cepola schlegelii, providing evidence that the family Cepolidae belongs to the order Priacanthiformes. Population size dynamics analysis indicated that A. indica experienced a bottleneck effect during the Pleistocene Glacial Epoch, likely due to the changes in glacial cycles and sea level fluctuations since ~800 Kya.

Daily behavioral analysis of group-housed pigs provides critical insights into early warning systems for pig health issues and animal welfare in smart pig farming. In this study, our main objective was to develop an automated method for monitoring and analyzing the behavior of group-reared pigs to detect health problems and improve animal welfare promptly. We have developed the method named Pig-ByteTrack. Our approach addresses target detection, Multi-Object Tracking (MOT), and behavioral time computation for each pig. The YOLOX-X detection model is employed for pig detection and behavior recognition, followed by Pig-ByteTrack for tracking behavioral information. In 1 min videos, the Pig-ByteTrack algorithm achieved Higher Order Tracking Accuracy (HOTA) of 72.9%, Multi-Object Tracking Accuracy (MOTA) of 91.7%, identification F1 Score (IDF1) of 89.0%, and ID switches (IDs) of 41. Compared with ByteTrack and TransTrack, the Pig-ByteTrack achieved significant improvements in HOTA, IDF1, MOTA, and IDs. In 10 min videos, the Pig-ByteTrack achieved the results with 59.3% of HOTA, 89.6% of MOTA, 53.0% of IDF1, and 198 of IDs, respectively. Experiments on video datasets demonstrate the method’s efficacy in behavior recognition and tracking, offering technical support for health and welfare monitoring of pig herds.

As an important mollusk in reef ecosystems, Tridacna squamosa forms pro-survival symbiotic relationships that hinge on an exquisite redox equilibrium between the host and the photosynthetic symbiont, zooxanthellae. The exact regulatory mechanisms thereof remain poorly understood. In this study, a novel Nfe2-like transcription factor in T. squamosa was identified and characterized with respect to its antioxidant and cytoprotective roles. Gene structure and phylogenetic analysis reveal that T. squamosa possesses a single transcription factor TsNfe2l in contrast to mammalian Nfe2l1 (Nrf1) and Nfe2l2 (Nrf2), belonging to protein members of the bZIP-NFE2 subfamily and functionally resembling the mammalian Nfe2l1. A conserved bZIP domain permits its binding to the antioxidant response element (ARE) in vitro and in HEK293T cells. Further analyses such as promoter prediction suggest that TsNfe2l target genes engage mainly in the regulation of multiple enzymes involved in antioxidation and allied pathways. Notably, TsNfe2l transcriptionally upregulates carnosine synthase (TsATPGD), which subsequently produces L-carnosine abundantly to shield cells from oxidative damage. Moreover, the blockage of TsNfe2l nucleic acid binding reduced the expression of TsATPGD and L-carnosine content in the gill, resulting in elevated lipid peroxidation. Collectively, our findings establish novel molecular insight into TsNfe2l as a critical regulator of redox homeostasis in T. squamosa through carnosine synthesis.

High-speed reducers in electric vehicles, characterized by high rotation speeds, heavy loads, large helix angles, and high contact ratios, are prone to tooth surface scuffing due to high sliding speeds. This scuffing is caused by adhesion wear from excessive instantaneous friction flash temperatures. The prevailing approach to gear scuffing analysis relies on the standard formula method, which is a relatively rudimentary technique. This method lacks the precision required to accurately assess the intricate distribution of tooth surface flash temperature (TSFT), limiting its efficacy in targeted tooth optimization. This study introduces an enhanced semi-analytical method to calculate TSFT and analyzes its variation under different conditions: increased tooth number and reduced module, altered pressure angle, and varied helix angle. The aim is to understand how these geometric parameters affect TSFT and the scuffing load capacity of high-speed reducer gears. This study calculates load distribution and TSFT under peak operating conditions and shows that increasing the tooth number, pressure angle, and helix angle can reduce maximum TSFT by more than 30%, improving scuffing safety and load capacity. However, these improvements must consider the gear’s allowable bending safety factor and bearing service life. The research concludes that optimizing these geometric parameters can significantly enhance the scuffing load capacity of gearsets.

The widespread reuse of code in the open-source community has led to the proliferation of homologous vulnerabilities, which are security flaws propagated across diverse software systems through the reuse of vulnerable code. Such vulnerabilities pose serious cybersecurity risks, as attackers can exploit the same weaknesses across multiple platforms. Deep learning has emerged as a promising approach for detecting homologous vulnerabilities in binary code due to their automated feature extraction and high efficiency. However, existing deep learning methods often struggle to capture deep semantic features in binary code, limiting their effectiveness. To address this limitation, this paper presents GMN+, which is a novel graph matching neural network with enhanced attention for detecting homologous vulnerabilities. This method comprehensively considers the information contained in instructions and incorporates types of input instruction. Masked Language Modeling and Instruction Type Prediction are developed as pre-training tasks to enhance the ability of GMN+ in extracting semantic information from basic blocks. GMN+ utilizes an attention mechanism to focus concurrently on the critical semantic information within functions and differences between them, generating robust function embeddings. Experimental results indicate that GMN+ outperforms state-of-the-art methods in various tasks and achieves notable performance in real-world vulnerability detection scenarios.

The traditional scoliosis examination based on X-ray film is not suitable for large-scale screening, and it is also not suitable for dynamic evaluation during rehabilitation. Therefore, based on computer vision technology, this paper puts forward an evaluation method of scoliosis with different photos of the back taken by mobile phones, which involves three aspects: first, based on the key point detection model of YOLOv8, an algorithm for judging the type of spinal coronal curvature is proposed; second, an algorithm for evaluating the coronal plane of the spine based on the key points of the human back is proposed, aiming at quantifying the deviation degree of the spine in the coronal plane; third, the measurement algorithm of trunk rotation (ATR angle) based on multi-scale automatic peak detection (AMPD) is proposed, aiming at quantifying the deviation degree of the spine in sagittal plane. The public dataset and clinical paired data (mobile phone photo and X-ray) are used to test. The results show that this method has high accuracy and effectiveness in distinguishing the type of spinal curvature and evaluating the degree of deviation, which is higher than other deep learning algorithms.

This study experimentally investigated a water-cooled four-cylinder turbocharged diesel engine (DE) under different loads and fuel blend ratios. The integration of Computational Fluid Dynamics (CFD) simulations enables a deeper analysis of the combustion process. Through an in-depth analysis of the combustion process, the focus was placed on investigating the specific impacts of ethanol and n-butanol additives on diesel engine performance. Research shows that a fuel mixture consisting of 70% diesel, 10% biodiesel, and 20% ethanol reduced NOx emissions by 5.56% compared to pure diesel at 75% load. Furthermore, this study explores the combustion performance of diesel/biodiesel blended with butanol/ethanol. The findings indicate that n-butanol improves thermal efficiency, particularly at 100% load, with the D70B10E20 and D70B10BU20 blends demonstrating thermal efficiencies of 9.94%and 8.72% higher than that of diesel alone, respectively. All mixed fuels exhibited reduced hydrocarbon and CO emissions under different loads, with a notable reduction in hydrocarbon emissions of 34.4% to 46.1% at 75% load.

China ranks first in apple production worldwide, making the assessment of apple quality a critical factor in agriculture. Sucrose concentration (SC) is a key factor influencing the flavor and ripeness of apples, serving as an important quality indicator. Nondestructive SC detection has significant practical value. Currently, SC is mainly measured using handheld refractometers, hydrometers, electronic tongues, and saccharimeter analyses, which are not only time-consuming and labor-intensive but also destructive to the sample. Therefore, a rapid nondestructive method is essential. The fluorescence hyperspectral imaging system (FHIS) is a tool for nondestructive detection. Upon excitation by the fluorescent light source, apples displayed distinct fluorescence characteristics within the 440–530 nm and 680–780 nm wavelength ranges, enabling the FHIS to detect SC. This study used FHIS combined with machine learning (ML) to predict SC at the apple’s equatorial position. Primary features were extracted using variable importance projection (VIP), the successive projection algorithm (SPA), and extreme gradient boosting (XGBoost). Secondary feature extraction was also conducted. Models like gradient boosting decision tree (GBDT), random forest (RF), and LightGBM were used to predict SC. VN-SPA + VIP-LightGBM achieved the highest accuracy, with Rp2, RMSEp, and RPD reaching 0.9074, 0.4656, and 3.2877, respectively. These results underscore the efficacy of FHIS in predicting apple SC, highlighting its potential for application in nondestructive quality assessment within the agricultural sector.

The detection and classification of foodborne pathogenic bacteria is crucial for food safety monitoring, consequently requiring rapid, accurate and sensitive methods. In this study, the surface-enhanced Raman spectroscopy (SERS) technique coupled with chemometrics methods was used to detect and classify six kinds of foodborne pathogenic bacteria, including Salmonella typhimurium (S. typhimurium), Escherichia coli (E. coli) O157:H7, Staphylococcus aureus (S. aureus), Listeria monocytogenes (L. monocytogenes), Listeria innocua (L. innocua), and Listeria welshimeri (L. welshimeri). First, silver nanoparticles (AgNPs) with different particle sizes were prepared as SERS-enhanced substrates by changing the concentration of sodium citrate, and the volume ratio of silver nanosol to bacterial solution was optimised to obtain the optimal SERS signal. Then, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to classify the SERS spectra of six bacteria at three classification levels (Gram type level, genus level and species level), and appropriate classification models were established. Finally, these models were validated on 540 spectra using linear discriminant analysis (LDA), achieving an average accuracy of 95.65%. Overall, it was concluded that the SERS technique combined with chemometrics methods could achieve the rapid detection and classification identification of foodborne pathogenic bacteria, providing an effective means for food safety monitoring.

This paper, grounded in the Stimulus–Organism–Response (SOR) model and event system theory, examines the mechanisms through which public recognition—specifically novel, disruptive, and critical recognition—of the intensity of food safety incidents influences willingness to engage in food safety governance. Risk perception is identified as a mediating variable, while risk communication serves as a moderating variable. Based on survey data, the study found that various forms of public recognition significantly impact governance willingness. Furthermore, risk perception plays a crucial mediating role, and risk communication has a notable moderating effect on the relationship between risk perception and food safety governance willingness. These findings illuminate the intrinsic connection between public recognition of food safety incidents and governance willingness, offering robust theoretical support and practical guidance for enhancing food safety governance. This research contributes to the ongoing improvement and optimization of food safety governance systems.

Industrial product e-commerce refers to the specific application of the e-commerce concept in industrial product transactions. It enables industrial enterprises to conduct transactions via Internet platforms and reduce circulation and operating costs. Industrial literature, such as policies, reports, and standards related to industrial product e-commerce, contains much crucial information. Through a systematical analysis of this information, we can explore and comprehend the development characteristics and trends of industrial product e-commerce. To this end, 18 policy documents, 10 industrial reports, and five standards are analyzed by employing text-mining methods. Firstly, natural language processing (NLP) technology is utilized to pre-process the text data related to industrial product commerce. Then, word frequency statistics and TF-IDF keyword extraction are performed, and the word frequency statistics are visually represented. Subsequently, the feature set is obtained by combining these processes with the manual screening method. The original text corpus is used as the training set by employing the skip-gram model in Word2Vec, and the feature words are transformed into word vectors in the multi-dimensional space. The K-means algorithm is used to cluster the feature words into groups. The latent Dirichlet allocation (LDA) method is then utilized to further group and discover the features. The text-mining results provide evidence for the development characteristics and trends of industrial product e-commerce in China.

The sterile insect technique (SIT) stands as an eco-friendly approach for mosquito control, but it is impeded by the limited availability of γ-ray radiation source. This research sought to investigate a different radiation source—the Varian Clinac 23EX linear accelerator, which is frequently used for X-ray therapy in cancer treatment. Evaluation parameters including emergence rate, average survival time, induced sterility (IS), male mating competitiveness of irradiated males and fecundity (the number of eggs per female per batch), and the egg hatch rate of females mated with irradiated males were assessed to gauge the application potential of this cancer treatment equipment in the realm of the SIT. The results indicated that X-rays from radiation therapy equipment can effectively suppress the hatch rate of offspring mosquitoes without adversely affecting the emergence rate of irradiated males or the fecundity of females. In addition, at an X-ray dose of 60 Gy, the induced sterility in Ae. aegypti was comparable to the sterility induced by 40 Gy of γ-rays with both treatments resulting in 99.6% sterility. Interestingly, when a release ratio of 7:1 (irradiated males:unirradiated males) was used to competitively mate with females, the IS results resulted by 60 Gy X-rays and 40 Gy γ-rays were still at 70.3% and 73.7%, respectively. In conclusion, the results underscored the potential of the Varian Clinac 23EX linear accelerator as an X-ray source in SIT research.

Despite the great success in the global exploration and development of reef reservoirs, research on bioclastic shoals under reefs is still in its infancy. Bioclastic shoal reservoirs are very thin, with multiple vertical levels and fast lateral changes, which makes accurate prediction of the reservoir’s location much tougher. To further implement the reservoir distribution, under the guidance of sequence stratigraphy, the prediction of thin shoals under the control of an isochronous stratigraphic framework was established. Using the combination of spectrum shaping and F-X domain noise suppression techniques and utilizing the signal-to-noise ratio spectrum set as the reference, logging curve as supervision, and well seismic calibration and isochronal amplitude slicing as quality control, the seismic frequency band was extended, and the seismic data resolution and signal-to-noise ratio were improved. After frequency extension, the global optimal seismic automatic interpretation technique was used to construct an isochronal stratigraphic framework model. Through waveform facies-controlled inversion and waveform facies-controlled simulation techniques, the elastic properties of the shoal reservoir were obtained, from which the planar distribution of the reservoir was accurately predicted. The above methods were applied to the prediction of the bioclastic shoal reservoir in the lower submember of the Changxing formation in the Yuanba gas field (China). The plane distribution of bioclastic shoal in the first and second levels was identified, which provides a guideline for the prediction of thin shoal reservoirs.

Elucidating the dynamics of soil microbial diversity in coastal wetlands is essential for understanding the changes in ecological functions within these ecosystems, particularly in the context of climate change and improper management practices. In this study, the diversity patterns and influencing factors of soil bacterial and fungal communities in a muddy coastal wetland in China were investigated using Illumina sequencing of 16S rRNA and ITS1, across wetlands dominated by different vegetations and varying proximity to the coastline. The wetlands include four plots dominated by Spartina alterniflora (SA1), four plots dominated by Suaeda glauca (SG2), additional four plots of Suaeda glauca (SG3), and four plots dominated by Phragmites australis (PA4), ranging from the nearest to the coast to those farther away. The results revealed significant differences in bacterial richness (Observed_species index) and fungal diversity (Shannon index) across different wetlands, with SG3 demonstrating the lowest bacterial Observed_species value (1430.05), while SA1 exhibited the highest fungal Shannon value (5.55) and PA4 showing the lowest fungal Shannon value (3.10). Soil bacterial and fungal community structures differed significantly across different wetlands. The contents of soil available phosphorus and total phosphorus were the main drivers for fungal Observed_species and Shannon index, respectively. Soil organic carbon, pH, and salinity were indicated as the best predictors of bacterial community structure, accounting for 28.1% of the total variation. The total nitrogen content and soil salinity contributed mostly to regulating fungal community structure across different wetlands, accounting for 19.4% of the total variation. The results of this study offer a thorough understanding of the response and variability in soil microbial diversity across the muddy coastal wetlands in China.

The 7A04 Al alloy is a commonly used lightweight metal material; however, its low wear resistance limits its application. In this study, the wear resistance of this alloy was improved by preparing micro-arc oxidation (MAO) coatings, MAO/MoS2 composite coatings, and hard-anodized (HA) coatings on its surface. The friction and wear behaviors of these three coatings with diamond-like coated (DLC) rings under oil lubrication conditions were investigated using a ring–block friction tester. The wear rates of the coatings on the block surfaces were determined using laser confocal microscopy, and the wear trajectories of the coatings were examined using scanning electron microscopy. The results indicated that, among the three coatings, the MAO/MoS2 coating had the lowest coefficient of friction of 0.059, whereas the HA coating had the lowest wear rate of 1.47 × 10−6 mm/Nm. The MAO/MoS2 coatings exhibited excellent antifriction properties compared to the other coatings, whereas the HA coatings exhibited excellent anti-wear properties. The porous structure of the MAO coatings stored lubricant and replenished the lubrication film under oil lubrication. Meanwhile, the introduced MoS2 enhanced the densification of the coating and functioned as a solid lubricant. The HA coating exhibited good wear resistance owing to the dense structure of the amorphous-phase aluminum oxide. The mechanisms of abrasive and adhesive wear of the coatings under oil lubrication conditions and the optimization of the tribological properties by the solid–liquid synergistic lubrication effect were investigated. This study provides an effective method for the surface modification of Al alloys with potential applications in the aerospace and automotive industries.

The notion of matched pair (F,G,▹,◃) of finite groups was introduced by Takeuchi in 1981, which is equivalent to a factorization of the group F⋈G. We find in this paper some sufficient conditions when equations νm(F⋈G)=νm(F)νm(G) for all m≥0 imply that F⋈G is the external direct product of F×G, where νm denotes m-th indicator of the regular representation of a finite group. A comparison with indicators of bismash product Hopf algebras CG#CF is also mentioned.

Lithium is an important non-renewable resource, and the study of the tiered separation of rare earths and lithium from rare earth molten salt slag is an important approach to solving the current global resource shortage. This article adopts a sulfuric acid leaching process and a lithium-containing solution iron lithium extraction separation process to recover lithium from rare earth molten salt slag. The method systematically investigates the impact of sulfuric acid concentration, liquid-to-solid ratio, leaching temperature, leaching time, pH, P507 concentration, phase ratio, extraction temperature, and extraction time on the lithium extraction effect and iron lithium separation effect in rare earth molten salt slag. The results show that under the conditions of a sulfuric acid concentration of 0.9 mol/L, a liquid-to-solid ratio of 8:1 mL/g, a leaching temperature of 70 °C, a leaching time of 90 min, a pH of 0.9, a P507 concentration of 50%, a phase ratio of 5:3, an extraction temperature of 30 °C, and an extraction time of 20 min, the lithium leaching rate reaches 97.8%, and the separation of iron and lithium is fully achieved. This method can efficiently recover the valuable element lithium from rare earth molten salt slag, which is of great significance for the subsequent preparation of lithium products and the realization of a closed-loop production of rare earth alloys by molten salt electrolysis.

A simple and innovative method was introduced for the production of green and recoverable flame-retardant cotton fabrics, where sulfonated cotton fabric (COT-SC) was synthesized by oxidizing cotton fabric with sodium periodate, followed by a sulfonation step with sodium bisulfite to provide active sites, which further chelated barium ions (Ba2+) to achieve flame retardancy. The morphological and structural characterizations of the fabricated cotton fabrics (COT-SC-Ba) demonstrated that the cleavage of C2-C3 free hydroxy groups within the cellulose macromolecule was chemically modified for grafting a considerable number of sulfonic acid groups, and Ba2+ ions were effectively immobilized on the macromolecule of the cotton fabric through a chelation effect. Results from cone calorimeter tests (CCTs) revealed that COT-SC-Ba became nonflammable, displayed a delayed ignition time, and decreased the values of the heat release rate (HRR), total smoke release (TSR), effective heat of combustion (EHC), and CO/CO2 ratio. TG/DTG analysis demonstrated that COT-SC-Ba possessed greater thermal stability, fewer flammable volatiles, and more of a char layer during burning than that of the original cotton fabric. Its residual mass was increased from 0.02% to 26.9% in air and from 8.05% to 26.76% in N2, respectively. The COT-SC-Ba not only possessed a limiting oxygen index (LOI) of up to 34.4% but could also undergo vertical burning tests evidenced by results such as the non-afterflame, non-afterglow, and a mere 75 mm char length. Those results demonstrated that the combination of SO3− and Ba2+ promoted the formation of a char layer. Moreover, cotton fabric regained its superior flame retardancy after being washed and re-chelated with Ba2+. Additional characteristics of the cotton fabric, such as the rupture strength, white degree, and hygroscopicity, were maintained at an acceptable level. In conclusion, this research can offer a fresh perspective on the design and development of straightforward, efficient, eco-friendly, and recoverable fire-retardant fabrics.

Constructing highly efficient catalysts for the degradation of organic pollutants driven by solar light in aquatic environments is a promising and green strategy. In this study, a novel hexagonal sheet-like Pt/SnS2 heterojunction photocatalyst is successfully designed and fabricated using a hydrothermal method and photodeposition process for photocatalytic tetracycline (TC) degradation. The optimal Pt/SnS2 hybrid behaves with excellent photocatalytic performance, with a degradation efficiency of 91.27% after 120 min, a reaction rate constant of 0.0187 min−1, and durability, which can be attributed to (i) the formation of a metal/semiconductor interface field caused by loading Pt nanoparticles (NPs) on the surface of SnS2, facilitating the separation of photo-induced charge carriers; (ii) the local surface plasmon resonance (LSPR) effect of Pt NPs, extending the light absorption range; and (iii) the sheet-like structure of SnS2, which can shorten the transmission distance of charge carriers, thereby allowing more electrons (e−) and holes (h+) to transfer to the surface of the catalyst. This work provides new insights with the utilization of sheet-like structured materials for highly active photocatalytic TC degradation in wastewater treatment and environmental remediation.

Compounds with rigid planar structures can insert into tumor cell DNA, thereby inducing DNA damage in tumor cells. In this study, quinazoline, a compound with a planar structure, was used as the core scaffold. A rigid planar 1,2,3-triazole moiety was introduced into its structure, and its activity was tested on HepG2 liver cancer cells. The results showed that most compounds exhibited inhibitory effects on HepG2 cells, and the IC50 values of the most effective compounds were 3.08 ± 0.37 μM and 3.60 ± 0.53 μM. We found that the designed compounds significantly upregulated the expression of γ-H2AX in tumor cells, inducing DNA damage while reducing PARP levels, thereby weakening the DNA damage repair capacity of tumor cells and leading to apoptosis. Additionally, these compounds inhibited the migration and invasion of HepG2 cells. One of the compounds was found to be low in toxicity in mice, suggesting its potential as a targeted DNA anti-tumor drug.

Rice bacterial blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is a major threat to rice production and food security. Exploring new resistance genes and developing varieties with broad-spectrum and high resistance has been a key focus in rice disease resistance research. In a preliminary study, rice cultivar Fan3, exhibiting high resistance to PXO99A and susceptibility to AH28, was developed by enhancing the resistance of Yuehesimiao (YHSM) to BB. This study performed a transcriptome analysis on the leaves of Fan3 and YHSM following inoculation with Xoo strains AH28 and PXO99A. The analysis revealed significant differential expression of 14,084 genes. Among the transcription factor (TF) families identified, bHLH, WRKY, and ERF were prominent, with notable differences in the expression of OsWRKY62, OsWRKY76, and OsbHLH6 across samples. Over 100 genes were directly linked to disease resistance, including nearly 30 NBS–LRR family genes. Additionally, 11 SWEET family protein genes, over 750 protein kinase genes, 63 peroxidase genes, and eight phenylalanine aminolysase genes were detected. Gene ontology (GO) analysis showed significant enrichment in pathways related to defense response to bacteria and oxidative stress response. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that differentially expressed genes (DEGs) were enriched in phenylpropanoid biosynthesis and diterpenoid biosynthesis pathways. Gene expression results from qRT-PCR were consistent with those from RNA-Seq, underscoring the reliability of the findings. Candidate genes identified in this study that may be resistant to BB, such as NBS–LRR family genes LOC_Os11g11960 and LOC_Os11g12350, SWEET family genes LOC_Os01g50460 and LOC_Os01g12130, and protein kinase-expressing genes LOC_Os01g66860 and LOC_Os02g57700, will provide a theoretical basis for further experiments. These results suggest that the immune response of rice to the two strains may be more concentrated in the early stage, and there are more up-regulated genes in the immune response of the high-resistant to PXO99A and medium-resistant to AH28, respectively, compared with the highly susceptible rice. This study offers a foundation for further research on resistance genes and the molecular mechanisms in Fan3 and YHSM.

Perennial rice has recently garnered global attention due to its potential to save on seeds and labor costs and its high production efficiency. The “mid-season rice–ratoon forage” mode is a new planting system that has emerged in recent years. However, detailed information is still lacking on the regenerative characteristics, grain and ratoon forage yields, and forage nutrient content of perennial rice under different planting densities, nitrogen (N) rates, stubble heights, and water management practices. Four experiments with perennial rice were conducted in Sichuan Province, Southwest China, from 2017 to 2022. The results show that the rice grain and ratoon forage yields were significantly affected by year, planting density, and N. The grain yield was 28.18% and 60.81% lower in 2018F and 2019F, respectively, than in 2017F; similarly, the ratoon forage yield was 29.01% and 52.74% lower in 2018S and 2019S, respectively, than in 2017S. The low grain yield was mainly associated with lower numbers of spikelets per panicle and panicles per m2, which resulted from a lower regrowth rate, and the low ratoon forage yield was mainly attributed to the lower regrowth rate. The rice grain and ratoon forage yields increased with an increase in the N rate and planting density. The ratoon forage was found to be rich in crude protein, crude fat, crude fiber, calcium, nitrogen, phosphorus, potassium, and other nutrients. Moreover, the content of these nutrients increased significantly with an increase in the N rate. The regrowth rate and maximum tillers showed trends of first increasing and then decreasing with an increase in the stubble height under dry and wet alternation irrigation during the winter season. When the relative soil moisture decreased to below 80% during the winter season, the regrowth rate and seedling development index could reach more than 99% and 84%, respectively. Our results suggest that integrating N, water, and other management practices (including the combination of a 150 kg ha−1 N rate, 18.0 hills per m2, 10–20 cm rice stubble height, and alternating dry and wet irrigation during the winter season) is a feasible approach for achieving high grain and ratoon forage yields in perennial rice systems.

The integration of ground-penetrating radar (GPR) with unmanned aerial vehicles (UAVs) enables efficient non-contact detection, performing exceptionally well in complex terrains and extreme environments. However, challenges in data processing and interpretation remain significant obstacles to fully utilizing this technology. To mitigate the effects of numerical dispersion, this paper develops a high-order finite-difference time-domain (FDTD(2,4)) three-dimensional code suitable for airborne GPR numerical simulations. The simulation results are compared with traditional FDTD methods, validating the accuracy of the proposed approach. Additionally, a Kirchhoff migration algorithm that considers the influence of the air layer is developed for airborne GPR. Different processing strategies are applied to flat and undulating terrain models, significantly improving the identification of shallowly buried targets. Particularly under undulating terrain conditions, the energy ratio method is introduced, effectively suppressing the interference of surface reflections caused by terrain variations. This innovative approach offers a new technical pathway for efficient GPR data processing in complex terrains. The study provides new insights and methods for the practical application of airborne GPR.

In the context of drought events caused by global warming, there is limited understanding of vegetation loss caused by drought and the subsequent recovery of vegetation after drought ends. However, employing a single index representing a specific vegetation characteristic to explore drought’s impact on vegetation may overlook vegetation features and introduce increased uncertainty. We applied the enhanced vegetation index (EVI), fraction of vegetation cover (FVC), gross primary production (GPP), leaf area index (LAI), and our constructed remote sensing vegetation index (RSVI) to assess vegetation drought in Central Asia. We analyzed the differences in drought experiences for different climatic regions and vegetation types and vegetation loss and recovery following drought events. The results indicate that during drought years (2012 and 2019), the differences in vegetation drought across climatic regions were considerable. The vegetation in arid, semiarid, and Mediterranean climate regions was more susceptible to drought. The different indices used to assess vegetation loss exhibited varying degrees of dynamic changes, with vegetation in a state of mild drought experiencing more significantly during drought events. The different vegetation assessment indices exhibited significant variations during the drought recovery periods (with a recovery period of 16 days: EVI of 85%, FVC of 50%, GPP of 84%, LAI of 61%, and RSVI of 44%). Moreover, the required recovery periods tended to decrease from arid to humid climates, influenced by both climate regions and vegetation types. Sensitivity analysis indicated that the primary climatic factors leading to vegetation loss varied depending on the assessment indices used. The proposed RSVI demonstrates high sensitivity, correlation, and interpretability to dry–wet variations and can be used to assess the impact of drought on vegetation. These findings are essential for water resource management and the implementation of measures that mitigate vegetation drought.

Transformer-based methods have demonstrated impressive performance in image super-resolution tasks. However, when applied to large-scale Earth observation images, the existing transformers encounter two significant challenges: (1) insufficient consideration of spatial correlation between adjacent ground objects; and (2) performance bottlenecks due to the underutilization of the upsample module. To address these issues, we propose a novel distance-enhanced strip attention transformer (DESAT). The DESAT integrates distance priors, easily obtainable from remote sensing images, into the strip window self-attention mechanism to capture spatial correlations more effectively. To further enhance the transfer of deep features into high-resolution outputs, we designed an attention-enhanced upsample block, which combines the pixel shuffle layer with an attention-based upsample branch implemented through the overlapping window self-attention mechanism. Additionally, to better simulate real-world scenarios, we constructed a new cross-sensor super-resolution dataset using Gaofen-6 satellite imagery. Extensive experiments on both simulated and real-world remote sensing datasets demonstrate that the DESAT outperforms state-of-the-art models by up to 1.17 dB along with superior qualitative results. Furthermore, the DESAT achieves more competitive performance in real-world tasks, effectively balancing spatial detail reconstruction and spectral transform, making it highly suitable for practical remote sensing super-resolution applications.

When there are time division multiple access (TDMA) signals with large bandwidth, waveform aliasing, and fast frequency-hopping in space, current methods have difficulty achieving the accurate localization of radiation sources and signal-sorting from multiple network stations. To solve the above problems, a distributed passive positioning and network stations sorting method for broadband frequency-hopping signals based on two-level parameter estimation and joint clustering is proposed in this paper. Firstly, a two-stage filtering structure is designed to achieve control filtering for each frequency point. After narrowing down the parameter estimation range through adaptive threshold detection, the time difference of arrival (TDOA) and the velocity difference of arrival (VDOA) can be obtained via coherent accumulating based on the cross ambiguity function (CAF). Then, a multi-station positioning method based on the TDOA/VDOA is used to estimate the position of the target. Finally, the distributed joint eigenvectors of the multi-stations are constructed, and the signals belonging to different network stations are effectively classified using the improved K-means method. Numerical simulations indicate that the proposed method has a better positioning and sorting effect in low signal-to-noise (SNR) and low snapshot conditions compared with current methods.

High-capacity communication networks are built to provide high throughput and low latency to accommodate the growing demand for bandwidth. However, the provision of these features is subject to a robust underlying network, which can provide high capacity with maximum reliability in terms of the system’s connection availability. This work optimizes an existing 2D spectral–spatial optical code division multiple access (OCDMA) passive optical network (PON) to maximize connection availability while maintaining desirable communication capacity and capital expenditure. Optimization is performed by employing ring topology at the feeder level, which is used to provide a redundant path in case of connection failures. Furthermore, high transmission capacity is ensured by utilizing a pseudo-3D double-weight zero cross-correlation (DW-ZCC) code. The analysis is performed with Optisystem simulations to observe the performance of the system in terms of bit error rate (BER), received power, and eye openings. It is observed that the introduction of ring topology at the feeder level of the PON does not impact the overall transmission capacity of the system. The system can still support maximum transmission capacity at receiver sensitivities of up to −19 dB. Reliability analysis also shows that the optimized ring-based architecture can provide desirable connection availability compared to the existing system.

Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements in robotics, robotic venous blood collection has the potential to replace traditional manual methods. The success of this robotic approach is heavily dependent on the quality of vein imaging. In this paper, we develop a vein imaging device based on the simulation analysis of vein imaging parameters and propose a U-Net+ResNet18 neural network for vein image segmentation. The U-Net+ResNet18 neural network integrates the residual blocks from ResNet18 into the encoder of the U-Net to form a new neural network. ResNet18 is pre-trained using the Bootstrap Your Own Latent (BYOL) framework, and its encoder parameters are transferred to the U-Net+ResNet18 neural network, enhancing the segmentation performance of vein images with limited labelled data. Furthermore, we optimize the AD-Census stereo matching algorithm by developing a variable-weight version, which improves its adaptability to image variations across different regions. Results show that, compared to U-Net, the BYOL+U-Net+ResNet18 method achieves an 8.31% reduction in Binary Cross-Entropy (BCE), a 5.50% reduction in Hausdorff Distance (HD), a 15.95% increase in Intersection over Union (IoU), and a 9.20% increase in the Dice coefficient (Dice), indicating improved image segmentation quality. The average error of the optimized AD-Census stereo matching algorithm is reduced by 25.69%, and the improvement of the image stereo matching performance is more obvious. Future research will explore the application of the vein imaging system in robotic venous blood collection to facilitate real-time puncture guidance.

Rosa Roxburghii (RR), a traditional Chinese medicinal fruit, is rich in bioactive substances that make it a potential natural antioxidant resource. This research aimed to study the antioxidant properties of RR by in vitro experiments and through intracellular assessment in H2O2-induced HepG2 cells. A non-targeted metabolic analysis was conducted to indicate changes in intracellular and extracellular metabolites. Differential metabolites and metabolic pathways were explored using PCA, PLS-DA, and KEGG pathway analysis. The results showed that RR rich in bioactive substances exhibited a significant antioxidative property in vitro and intracellularly. This property may be achieved by scavenging free radicals, increasing the activity of catalase (CAT), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), and the levels of bicinchoninic acid (BCA) while reducing the reactive oxygen species (ROS) generation. This study identified 13 differential metabolites intracellularly and 7 extracellularly, among which the key differential metabolites included D-glucopyranose, D-mannose, fructose, citric acid, malic acid, cholesterol, and cholestenone. These key metabolites primarily regulated glucose-related metabolism, the citrate cycle, and the primary bile acid biosynthesis pathway in H2O2-induced HepG2 cells. These findings provide potential application evidence of RR in the development of natural resources for functional foods.

Colon cancer is a common and lethal malignancy, ranking second in global cancer-related mortality, highlighting the urgent need for novel targeted therapies. The sea cucumber (Apostichopus japonicus) is a marine organism known for its medicinal properties. After conducting a bioinformatics analysis of the cDNA library of Apostichopus japonicus, we found and cloned a cDNA sequence encoding histidine-rich peptides, and the recombinant peptide was named rAj-HRP. Human histidine-rich peptides are known for their anti-cancer properties, raising questions as to whether rAj-HRP might exhibit similar effects. To investigate whether rAj-HRP can inhibit colon cancer, we used human colon cancer HCT116 cells as a model and studied the tumor suppressive activity in vitro and in vivo. The results showed that rAj-HRP inhibited HCT116 cell proliferation, migration, and adhesion to extracellular matrix (ECM) proteins in vitro. It also disrupted the cytoskeleton and induced apoptosis in these cells. In vivo, rAj-HRP significantly inhibited the growth of HCT116 tumors in BALB/c mice, reducing tumor volume and weight without affecting the body weight of the tumor-bearing mice. Western blot analysis showed that rAj-HRP inhibited HCT116 cell proliferation and induced apoptosis by upregulating BAX and promoting PARP zymogen degradation. Additionally, rAj-HRP inhibited HCT116 cell adhesion and migration by reducing MMP2 levels. Further research showed that rAj-HRP downregulated EGFR expression in HCT116 cells and inhibited key downstream molecules, including AKT, P-AKT, PLCγ, P38 MAPK, and c-Jun. In conclusion, rAj-HRP exhibits significant inhibitory effects on HCT116 cells in both in vitro and in vivo, primarily through the EGFR and apoptosis pathways. These findings suggest that rAj-HRP has the potential as a novel targeted therapy for colon cancer.

The past three decades have witnessed extensive studies on motion-planning and tracking-control for autonomous vehicles (AVs). There is, however, a lack of studies on effective design methods for AVs, which consist of the subsystems of the mechanical vehicle, tracking-control, motion-planning, etc. To tackle this problem, this paper proposes a design approach for AVs. The proposed method features a design framework with two layers: at the upper layer, a particle swarm optimization (PSO) algorithm serves as a solver to a multi-objective optimization problem for desired AV trajectory-tracking performance; at the lower layer, a coupled dynamic analysis is conducted among the three subsystems, i.e., a nonlinear model for the mechanical vehicle, a motion-planning module, and a controller based on nonlinear model predictive control (NLMPC) for direction control. The simulation results demonstrate that the proposed method can effectively determine the desired design variables for the NLMPC controller and the mechanical vehicle to achieve optimal trajectory-tracking performance. The research findings from this work provide guidelines for designing AVs.