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In order to enhance the development efficiency of thick and complex carbonate reservoirs in the Middle East, a case study was conducted on M oilfield in Iraq. This study focused on reservoir characterization, injection-production modes, well pattern optimization, and other related topics. As a result, key techniques for the high-efficiency development of thick carbonate reservoirs were established. The research findings include the following: (1) the discovery of hidden "low-velocity" features within the thick gypsum-salt layer, which led to the development of a new seismic velocity model; (2) the differential dissolution of grain-supported limestones is controlled by lithofacies and petrophysical properties, resulting in the occurrence of "porphyritic" phenomena in core sections. The genetic mechanism responsible for reversing petrophysical properties in dolostones is attributed to "big hole filling and small hole preservation" caused by dense brine refluxing; (3) fracture evaluation technology based on anisotropy and dipole shear wave long-distance imaging was developed to address challenges associated with quantitatively assessing micro-fractures; (4) through large-scale three-dimensional physical models and numerical simulations, it was revealed that water–oil displacement mechanisms involving "horizontal breakthrough via hyper-permeability" combined with vertical differentiation due to gravity occur in thick and heterogeneous reservoirs under spatial injection-production modes; (5) a relationship model linking economic profit with well pattern density was established for technical service contracts in the Middle East. Additionally, an innovative stepwise conversion composite well patterns approach was introduced for thick reservoirs to meet production ramp-up requirements while delaying water cut rise; (6) a prediction technology for the oilfield development index, considering asphaltene precipitation, has been successfully developed. These research findings provide robust support for the efficient development of the M oilfield in Iraq, while also serving as a valuable reference for similar reservoirs' development in the Middle East. [ABSTRACT FROM AUTHOR]

Simple Summary: This study presents a deep learning-based multi-object tracking method to enhance the accuracy of cattle detection and tracking, thereby improving farming efficiency and health management. The proposed method mitigates detection errors and omissions in complex environments while reducing identity switching and trajectory prediction errors through algorithmic enhancements. Experimental results show that the method achieves superior accuracy in cattle detection and behavioral tracking, operating in real time at 31.2 frames per second. This approach provides strong technical support for long-term monitoring and contactless cattle management, offering considerable practical value. In smart ranch management, cattle behavior recognition and tracking play a crucial role in evaluating animal welfare. To address the issues of missed and false detections caused by inter-cow occlusions and infrastructure obstructions in the barn environment, this paper proposes a multi-object tracking method called YOLO-BoT. Built upon YOLOv8, the method first integrates dynamic convolution (DyConv) to enable adaptive weight adjustments, enhancing detection accuracy in complex environments. The C2f-iRMB structure is then employed to improve feature extraction efficiency, ensuring the capture of essential features even under occlusions or lighting variations. Additionally, the Adown downsampling module is incorporated to strengthen multi-scale information fusion, and a dynamic head (DyHead) is used to improve the robustness of detection boxes, ensuring precise identification of rapidly changing target positions. To further enhance tracking performance, DIoU distance calculation, confidence-based bounding box reclassification, and a virtual trajectory update mechanism are introduced, ensuring accurate matching under occlusion and minimizing identity switches. Experimental results demonstrate that YOLO-BoT achieves a mean average precision (mAP) of 91.7% in cattle detection, with precision and recall increased by 4.4% and 1%, respectively. Moreover, the proposed method improves higher order tracking accuracy (HOTA), multi-object tracking accuracy (MOTA), multi-object tracking precision (MOTP), and IDF1 by 4.4%, 7%, 1.7%, and 4.3%, respectively, while reducing the identity switch rate (IDS) by 30.9%. The tracker operates in real-time at an average speed of 31.2 fps, significantly enhancing multi-object tracking performance in complex scenarios and providing strong support for long-term behavior analysis and contactless automated monitoring. [ABSTRACT FROM AUTHOR]

In clinical settings, computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) are commonly employed in brain imaging to assist clinicians in determining the type of stroke in patients. However, these modalities are associated with potential hazards or limitations. In contrast, microwave imaging emerges as a promising technique, offering advantages such as non-ionizing radiation, low cost, lightweight, and portability. The primary challenges faced by microwave tomography include the severe ill-posedness of the electromagnetic inverse scattering problem and the time-consuming nature and unsatisfactory resolution of iterative quantitative algorithms. This paper proposes a learning electric field enhancement imaging method (LEFEIM) to achieve quantitative brain imaging based on a microwave tomography system. LEFEIM comprises two cascaded networks. The first, based on a convolutional neural network, utilizes the electric field from the receiving antenna to predict the electric field distribution within the imaging domain. The second network employs the electric field distribution as input to learn the dielectric constant distribution, thereby realizing quantitative brain imaging. Compared to the Born Iterative Method (BIM), LEFEIM significantly improves imaging time, while enhancing imaging quality and goodness-of-fit to a certain extent. Simultaneously, LEFEIM exhibits anti-noise capabilities. [ABSTRACT FROM AUTHOR]

The flow of six kinds of fresh concrete under different flow rates and lubrication layer thickness (TLL) values in the horizontal pipe was numerically simulated. The influence of the TLL on the pressure per unit length (PL) was analyzed. It was determined that the formation of the lubrication layer (LL) significantly reduces the PL in concrete pumping. As the TLL increased, the PL decreased. However, the degree of reduction in the PL gradually decreased as the TLL increased. Relating the simulated PL with the experimental PL, the size of the TLL was obtained, which was between 1 and 3 mm. The minimum and maximum were 1.23 and 2.58 mm, respectively, and the average value was 1.97 mm. The strength (S24, S50), the size of the aggregate (A10, A20, A25), and the flow rate of pumping all affected the TLL. The type of fresh concrete and the flow rate of pumping significantly affected the PL, which impacted the TLL. However, the TLL also impacted the PL. Finally, this made the TLL change within a certain range. When PL > 14,000 Pa/m, 2 mm < TLL< 3 mm; on the other hand, 1 mm < TLL< 2 mm. Therefore, we can use CFD to simulate the flow of all types of concrete in the actual pumping pipeline with a TLL of 2 mm to obtain their pumping pressure and guide the actual construction. [ABSTRACT FROM AUTHOR]

Employing drones and hyperspectral imagers for large-scale, precise evaluation of nitrogen (N) concentration in Carya cathayensis Sarg canopies is crucial for accurately managing nitrogen fertilization in C. cathayensis Sarg cultivation. This study gathered five sets of hyperspectral imagery data from C. cathayensis Sarg plantations across four distinct locations with varying environmental stresses using drones. The research assessed the canopy nitrogen concentration of C. cathayensis Sarg trees both during singular growth periods and throughout their entire growth cycles. The objective was to explore the influence of band combinations and spectral index formula configurations on the predictive capability of the hyperspectral indices (HIs) for canopy N concentration (CNC), optimize the performance between HIs and machine learning approaches, and validate the efficacy of optimized HI algorithms. The findings revealed the following: (i) Optimized HIs demonstrated optimal predictive performance during both singular growth periods and the full growth cycles of C. cathayensis Sarg. The most effective HI model for singular growth periods was the optimized–modified–normalized difference vegetation index (opt-mNDVI), achieving an adjusted coefficient of determination (R2) of 0.96 and a root mean square error (RMSE) of 0.71. For the entire growth cycle, the HI model, also opt-mNDVI, attained an R2 of 0.75 and an RMSE of 2.11; (ii) optimized band combinations substantially enhanced HIs' predictive performance by 16% to 71%, while the choice between three-band and two-band combinations influenced the predictive capacity of optimized HIs by 4% to 46%. Hence, utilizing optimized HIs combined with Unmanned Aerial Vehicle (UAV) hyperspectral imaging to evaluate nitrogen concentration in C. cathayensis Sarg trees under complex field conditions offers significant practical value. [ABSTRACT FROM AUTHOR]

In the network environment of power systems, payload generation is used to construct data packets, which are used to obtain data for the security management of network assets. Payloads generated by existing methods cannot satisfy the specifications of the protocols in power systems, resulting in low efficiency and information errors. In this paper, a payload generation model, LoadGAN, is proposed by using generative adversarial networks (GANs). Firstly, we find segmentation points to cut payloads into different segment sequences using sliding window schema based on Bayesian optimization. Then, we use different payload segments to train several child generators to generate corresponding parts of a whole payload. Segment sequences generated by these generators are assembled to form a whole new payload that is compliant with the specifications of the original network protocol. Experiments on the Mozi botnet dataset show that LoadGAN achieves precise payload segmentation while maintaining a high payload effectiveness of 85.5%, which is a 40% improvement compared to existing methods. [ABSTRACT FROM AUTHOR]

Aroma in food plays an important role in food perception and acceptance, which depends on various mixtures of volatile organic compounds (VOCs). Moreover, VOCs are of great significance for aroma identification. In this study, headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–mass spectrometry (GC-MS) technology was used to determine the VOCs in 10 pear syrups. A total of 127 VOCs were quantitatively determined, including 9 common VOCs and 46 characteristic VOCs of 10 pear syrups. The pear syrups were divided into three categories by cluster analysis, and thirty-eight differential VOCs were obtained using orthogonal partial least squares discrimination analysis (OPLS-DA) and fourteen key VOCs were selected by odor activity value (OAV). It was revealed that the key and common aroma components of pear syrups were butanoic acid, methyl ester, 2-methyl-, methyl ester and Hexanoic acid, and ethyl ester. The characteristic and differential VOCs were 10-Undecen-1-ol, Hexadecanal, n-Propylacetate, Cyclohexanol, 5-methyl-2-(1-methylethyl)-, (1S,2R,5S)-, Methional, Disulfide, dimethyl, 8-Nonenoic acid, ethyl ester, Naphthalene, 1,2-dihydro-1,1,6-trimethyl-, 3H-Purin-6-amine, N,N,3-trimethyl-, 2-Octanol,2,6-dimethyl-, Furyl hydroxymethyl ketone, Heptane, 2,2,4,6,6-pentamethyl-, and Butanoic acid,2-methyl-,methyl ester. The above results showed that different pear syrups had rich diversity in aroma compounds, with some components being shared among them while others are exclusive to specific syrups. [ABSTRACT FROM AUTHOR]

Lithium–sulfur (Li-S) batteries offer a high theoretical energy density but suffer from poor cycling stability and polysulfide shuttling, which limits their practical application. To address these challenges, we developed a PANI-modified MoS2-NG composite, where MoS2 nanoflowers were uniformly grown on graphene oxide (GO) through PANI modification, resulting in an increased interlayer spacing of MoS2. This expanded spacing exposed more active sites, enhancing polysulfide adsorption and catalytic conversion. The composite was used to prepare MoS2-NG/PP separators for Li-S batteries, which achieved a high specific capacity of 714 mAh g−1 at a 3 C rate and maintained a low capacity decay rate of 0.085% per cycle after 500 cycles at 0.5 C. The larger MoS2 interlayer spacing was key to improving redox reaction kinetics and suppressing the shuttle effect, making the MoS2-NG composite a promising material for enhancing the performance and stability of Li-S batteries. [ABSTRACT FROM AUTHOR]

A balanced inflammatory response is crucial for the organism to defend against external infections, however, an exaggerated response may lead to detrimental effects, including tissue damage and even the onset of disease. Therefore, anti-inflammatory drugs are essential for the rational control of inflammation. In this study, we found that a previously screened peptide TaY (KEKKEVVEYGPSSYGYG) was able to inhibit the LPS-induced RAW264.7 inflammatory response by decreasing a series of proinflammatory cytokines, such as TNF-α, IL-6, and nitric oxide (NO). To elucidate the underlying mechanism, we conducted further investigations. Western blot analysis showed that TaY reduced the phosphorylation of key proteins (IKK-α/β, IκB-α,NF-κB (P65)) in the TLR4-NF-κB signaling pathway and inhibited the inflammatory response. Furthermore, molecular docking and molecular dynamic simulations suggested that TaY binds to the hydrophobic pocket of MD2 through hydrogen bonding and hydrophobic interactions, potentially competing with LPS for MD2 binding. Collectively, TaY is a promising candidate for the development of novel therapeutic strategies against inflammatory disorders. [ABSTRACT FROM AUTHOR]

The challenge of producing polymer vesicles remains difficult, despite numerous attempts to modulate the kinetics of polymer vesicle budding and achieve precise control over the membrane characteristics. An innovative approach that incorporates the use of copolymer-loaded single-emulsion droplets is proposed to address this challenge. This method enables the precise manipulation of micelles and polymer vesicles' composition, structures and dimensions. The emulsion contracts and forms microspheres when the copolymer concentrations exceed > 0.5 wt%, resulting in the formation of nano polymer vesicles. Conversely, the copolymer spontaneously forms micro polymer vesicles and micelles through vesicle budding at lower concentrations. The spontaneous production of vesicles and micelles can be induced by modifying the copolymer concentration in the emulsion. Our discoveries have a significant impact relative to the development of copolymer membranes and contribute to an enhanced comprehension of the mass manufacturing of polymer vesicles from single emulsions. [ABSTRACT FROM AUTHOR]

Federated learning, as a novel distributed machine learning mode, enables the training of machine learning models on multiple devices while ensuring data privacy. However, the existence of single-point-of-failure bottlenecks, malicious threats, scalability of federated learning implementation, and lack of incentive mechanisms have seriously hindered the development of federated learning technology. In recent years, as a distributed ledger, blockchain has the characteristics of decentralization, tamper-proof, transparency, security, etc., which can solve the issues encountered in the above-mentioned federated learning. Particularly, the integration of federated learning and blockchain leads to a new paradigm, called blockchain-based federated learning (BFL), which has been successfully applied in many application scenarios. This paper aims to provide a comprehensive review of recent efforts on blockchain-based federated learning. More concretely, we propose and design a taxonomy of blockchain-based federated learning models, along with providing a comprehensive summary of the state of the art. Various applications of federated learning based on blockchain are introduced. Finally, we expand on current trends and provide new perspectives pertaining to this new and exciting development in the field. [ABSTRACT FROM AUTHOR]

High-pressure processing (HPP) is a promising technology for increasing the shelf life of food, with minimal effects on the nutritional or sensory quality. However, there has been a concern that high-oil-content foods may protect food pathogens in HPP, and that HPP can affect the quality of lipids. We inoculated Listeria monocytogenes and Salmonella Typhimurium into 34% and 54% oil-content pesto sauce, processed them either with HPP (600 MPa, 4 min) or thermal processing (82 °C, 5 min), and analyzed bacteria counts, pH, GC-MS (Terpene compounds), the time–kill kinetic study, and lipid oxidation value for 60 days in refrigerating storage (5 ± 2 °C). Our findings show that HPP significantly reduced the number of bacteria (more than 4-log) compared to thermal processing or non-processing. Additionally, we discovered terpene compounds (highest-level terpene: L-linalool, eugenol, and 1,8-cineol) in pesto oil that exhibit antimicrobial activity. Different oil content did not have any significant effect on bacteria levels. Regarding chemical results, all samples were of acceptable quality, and the processes did not show any negative effect on lipid oxidation (Peroxide and P-Anisidine value under 10 meq per kilogram of oil). In conclusion, our study indicates that HPP is a suitable method for high-oil-content pesto sauce. In addition, functional compounds naturally present in pesto may contribute to maintaining its microbial and chemical quality. [ABSTRACT FROM AUTHOR]

Coal-bearing strata belong to sedimentary strata, and there are multiple aquifers. The accurate detection of deep aquifers is helpful to the safe mining of the working face. In order to provide guidance for the interpretation of the surface-to-underground transient electromagnetic method (SUTEM) that can be used to detect deep aquifers, we used theoretical analysis and numerical simulation methods in this study. Taking uniform half-spaces, single aquifers, and double aquifers as examples, we systematically studied the data characteristics and degree of influence of SUTEM under the influence of shallow aquifers. The results indicate the following: Under the influence of the primary field distribution, the x or y component of the induced electromotive force received by the underground receiving point has a positive and negative inflection point, which increases the difficulty of data interpretation, and the z component is easier to use for data interpretation. The influence of the aquifer on the early data of the underground receiving point is much greater than that of the ground receiving point, and the late influence is closer to the ground receiving point. The change in resistivity of the shallow aquifer has the greatest influence on the ability of each measuring point to detect the data of the deep aquifer; this influence is followed by change in thickness, and change in depth has the least influence on the detection capability of each measuring point. [ABSTRACT FROM AUTHOR]

Previous studies have focused on the impact of individual factors on lane departure warning (LDW) utility during driving. However, comprehensive analysis has not been considered based on multiple variables, such as driver characteristics. This paper aims to propose a methodology in exploring the utility of LDW under varied warning timing situations, focusing on changes in driving style and distraction level to obtain the optimal warning timing matching relationship. A driving simulator experiment with a mixed 4 × 3 factor design was conducted. The design matrix includes four level of secondary task (ST) conditions and three warning timings situations for drivers with various driving styles. To estimate the utility of the LDW system, lane departure duration (LDD) was selected as a time-based measure of utility. Both the Kaplan-Meier method and COX model were applied and compared. Combined with questionnaire results, the results indicate that both driving style and distraction state are significant influence factors. Generally, the results suggest that the more aggressive drivers lead to the more severe lane departure behavior and they preferred late warning. In terms of distraction state, the LDD increases with the level of ST remarkably. This implies that the earlier warning timing should be given for the higher-level distraction state condition. It was also observed that adaptive warning timing is needed based on the analysis of the interactive effect among multiple variables. The results provide empirical data for the optimization of LDW system design. [ABSTRACT FROM AUTHOR]

Simple Summary: This study demonstrates that the duck embryo fibroblast cell line CCL-141 can undergo adipogenesis, vital for understanding fat cell development in ducks. Treatments with chicken serum, fatty acids, insulin, and all-trans retinoic acid induced fat cell formation, as evidenced by Oil Red O staining and a gene expression analysis. Moreover, the CRISPR/Cas9 knockout of the adipogenesis gene PPARγ in CCL-141 cells confirmed the cell line's utility for studying adipogenesis-related gene functions. These findings validate CCL-141 as a model for adipogenesis research, which will aid in uncovering its regulatory mechanisms. The duck embryo fibroblast cell line CCL-141, which is currently the only commercialized duck cell line, has been underexplored in adipogenesis research. (1) Background: This study establishes an experimental protocol to induce adipogenesis in CCL-141 cells, addressing the importance of understanding gene functions in this process. (2) Methods: Chicken serum, fatty acids, insulin, and all-trans retinoic acid were used to treat CCL-141 cells, with adipogenesis confirmed by Oil Red O staining and gene expression quantification. CRISPR/Cas9 technology was applied to knockout PPARγ, and the resulting adipogenic phenotype was assessed. (3) Results: The treatments promoted adipogenesis, and the knockout of PPARγ validated the cell line's utility for gene function studies. (4) Conclusions: CCL-141 cells are a suitable model for investigating duck adipogenesis, contributing to the understanding of regulatory factors in this biological process. [ABSTRACT FROM AUTHOR]

Raindrop size distribution (DSD) has an essential effect on rainfall kinetic energy estimation (RKEE) and dual-polarization radar quantitative precipitation estimation (QPE); DSD is a key factor for establishing a dual-polarization radar QPE scheme and RKEE scheme, particularly in mountainous areas. To improve the understanding of seasonal DSD-based RKEE, dual-polarization radar QPE, and the impact of rainfall types and classification methods, we investigated RKEE schemes and dual-polarimetric radar QPE algorithms across seasons and rainfall types based on two classic classification methods (BR09 and BR03) and DSD data from a disdrometer in the Tianshan Mountains during 2020–2022. Two RKEE schemes were established: the rainfall kinetic energy flux–rain rate (KEtime–R) and the rainfall kinetic energy content–mass-weighted mean diameter (KEmm–Dm). Both showed seasonal variation, whether it was stratiform rainfall or convective rainfall, under BR03 and BR09. Both schemes had excellent performance, especially the KEmm–Dm relationship across seasons and rainfall types. In addition, four QPE schemes for dual-polarimetric radar—R(Kdp), R(Zh), R(Kdp,Zdr), and R(Zh,Zdr)—were established, and exhibited characteristics that varied with season and rainfall type. Overall, the performance of the single-parameter algorithms was inferior to that of the double-parameter algorithms, and the performance of the R(Zh) algorithm was inferior to that of the R(Kdp) algorithm. The results of this study show that it is necessary to consider different rainfall types and seasons, as well as classification methods of rainfall types, when applying RKEE and dual-polarization radar QPE. In this process, choosing a suitable estimator—KEtime(R), KEmm(Dm), R(Kdp), R(Zh), R(Kdp,Zdr), or R(Zh,Zdr)—is key to improving the accuracy of estimating the rainfall KE and R. [ABSTRACT FROM AUTHOR]

High temperatures and droughts are two natural disasters that cause forest fires. During climate change, the frequent occurrence of high temperatures, droughts, and their coupled effects significantly increase the forest fire risk. To reveal the seasonal and spatial differences in the coupled effects of high temperatures and droughts on forest fires, this study used the Copula method and proposed the compound extremely high-temperature and drought event index ( CTDI ). The results indicated that the study area was subject to frequent forest fires in spring (71.56%), and the burned areas were mainly located in forests (40.83%) and the transition zone between farmland and forests (36.91%). The probability of forest fires in summer increased with high temperatures and drought intensity, with high temperatures playing a dominant role. The highest forest fire hazard occurred in summer (>0.98). The probability of a forest fire occurring under extreme meteorological conditions in summer and fall was more than twice as high as that in the same zone under non-extreme conditions. Droughts play a significant role in the occurrence and spread of forest fires during fall. These results can provide decision-making support for forest fire warnings and fire fighting in the Northeast China forest zone. [ABSTRACT FROM AUTHOR]

Long-term and extensive mineral mining in the Kuermutu mine section of the Two Rivers Nature Reserve in the Altai region has disrupted the ecological balance between soil and vegetation. To assess the effectiveness of various restoration measures in this abandoned mine area, we compared two restoration approaches—natural turf transplantation (NTT) and replanted economic crop grassland (ARGC)—against an unaltered control (original grassland). We employed 11 evaluation indices to conduct soil and vegetation surveys. We developed a comprehensive evaluation model using the Analytic Hierarchy Process (AHP) to assess restoration outcomes for each grassland type. Our findings indicate that both NTT and ARGC significantly improved ecological conditions, such as reducing soil fine particulate matter loss and restoring vegetation cover. This brought these areas closer to their original grassland state. The species composition and community structure of the NTT and ARGC vegetation communities improved relative to the original grassland. This was due to a noticeable increase in dominant species' importance value. Vegetation cover averaged higher scores in NTT, while the average height was greater in ARGC. The soil water content and soil organic carbon (SOC) varied significantly with depth (p < 0.05), following a general 'V' pattern. NTT positively impacted soil moisture content (SMC) at the surface, whereas ARGC influenced SMC in deeper layers, with the 40–50 cm soil layer achieving 48.13% of the original grassland's SMC. SOC levels were highest in the control (original grassland), followed by ARGC and NTT, with ARGC showing the greatest organic carbon content at 20–30 cm depths. A comprehensive AHP ecological-economic evaluation revealed that restoration effectiveness scores were 0.594 for NTT and 0.669 for ARGC, translating to 59.4% and 66.9%, respectively. ARGC restoration was found to be more effective than NTT. These results provide valuable insights into ecological restoration practices for abandoned mines in Xinjiang and can guide future effectiveness evaluations. [ABSTRACT FROM AUTHOR]

Water quality assessment is an important method for understanding the spatial-temporal variation characteristics of water quality. Therefore, the present study has been performed to evaluate the water quality for a typical plain river network area in Changzhou City, Jiangsu, China, where the river system is characterized by reciprocal flow and diverse pollution sources. The water quality samples from 2017 to 2021 were comprehensively assessed using comprehensive methods that combine the single-factor pollution index (SFPI) method with multivariate statistical analysis. Initially, statistical analyses were conducted to evaluate water quality exceedances and correlations and the SFPI method was applied to classify water quality categories. Furthermore, principal component analysis (PCA) and cluster analysis (CA) were employed to reduce the dimensionality of water quality indicators and group monitoring sections with similar characteristics. The results indicate that the overall water quality in Changzhou City is lightly polluted with a trend of improvement. The primary pollutants identified are total phosphorus (TP) and ammonia nitrogen (NH3-N). This study highlights that organic pollution, self-purification capacity, and eutrophication of river water bodies are the most significant factors affecting water quality. The sampling sites were classified into three groups (good, moderate, and poor). The water quality assessment results of this study provide a theoretical reference for water environment management and ecological protection in plain river network areas. [ABSTRACT FROM AUTHOR]

Serine/arginine-rich (SR) proteins mostly function as splicing factors for pre-mRNA splicing in spliceosomes and play critical roles in plant development and adaptation to environments. However, detailed study about SR proteins in legume plants is still lacking. In this report, we performed a genome-wide investigation of SR protein genes in wild soybean (Glycine soja) and identified a total of 31 GsSR genes from the wild soybean genome. The analyses of chromosome location and synteny show that the GsSRs are unevenly distributed on 15 chromosomes and are mainly under the purifying selection. The GsSR proteins can be phylogenetically classified into six sub-families and are conserved in evolution. Prediction of protein phosphorylation sites indicates that GsSR proteins are highly phosphorylated proteins. The protein–protein interaction network implies that there exist numerous interactions between GsSR proteins. We experimentally confirmed their physical interactions with the representative SR proteins of spliceosome-associated components such as U1-70K or U2AF35 by yeast two-hybrid assays. In addition, we identified various stress-/hormone-responsive cis-acting elements in the promoter regions of these GsSR genes and verified their expression patterns by RT-qPCR analyses. The results show most GsSR genes are highly expressed in root and stem tissues and are responsive to salt and alkali stresses. Splicing analysis showed that the splicing patterns of GsSRs were in a tissue- and stress-dependent manner. Overall, these results will help us to further investigate the biological functions of leguminous plant SR proteins and shed new light on uncovering the regulatory mechanisms of plant SR proteins in growth, development, and stress responses. [ABSTRACT FROM AUTHOR]

Identifying key genes involved in Cadmium (Cd) response pathways in plants and developing low-Cd-accumulating cultivars may be the most effective and eco-friendly strategy to tackle the problem of Cd pollution in crops. In our previous study, Stressseventy subfamily A 4 (SSA4) was identified to be associated with Cd tolerance in yeast. Here, we investigated the mechanism of SSA4 in regulating Cd tolerance in yeast. ScSSA4 binds to POre Membrane 34 (POM34), a key component of nuclear pore complex (NPC), and translocates from the cytoplasm to the nucleus, where it regulates the expression of its downstream gene, Viable in a Hal3 Sit4 background 1 (VHS1), resulting in reduced Cd accumulation in yeast cells. Additionally, we identified a Chinese cabbage SSA4 gene, BrSSA4c, which could enhance the Cd tolerance in Chinese cabbage. This study offers new insights into the regulatory mechanisms of Cd tolerance in yeast, a model organism, and paves the way for the genetic enhancement of Cd tolerance in Chinese cabbage. [ABSTRACT FROM AUTHOR]

The rising occurrence of erectile dysfunction related to diabetes mellitus (DMED) has led to the creation of new medications. Proanthocyanidins (PROs) is a potential agent for DMED. In this study, the DMED rat model was established using streptozotocin (STZ) and erectile function was assessed using apomorphine (APO) in rats. Following this, the rats were subjected to oral treatment with PRO. Then, we evaluated the influence of PROs on DMED rats. The findings suggest that PROs significantly enhance erectile function in DMED rats. PROs modulated glucose and lipid metabolism in DMED rats by decreasing blood glucose and lipid levels while increasing liver glycogen and serum insulin levels. Furthermore, PROs enhanced vascular endothelial function in DMED rats by augmenting nitric oxide (NO) levels and reducing the levels of endothelin-1 (ET-1) and lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1). Additionally, PROs have been shown to elevate testosterone (T) levels, mitigate pathological testicular damage, and enhance sperm concentration and survival rates. Finally, the core targets were screened using network pharmacology, followed by validation through molecular docking, enzyme-linked immunoassay (ELISA), and real-time PCR methodologies. Our findings imply that PROs may treat DMED by elevating AKT1 levels while concurrently diminishing CASP3 levels, thereby effectively regulating the PI3K-Akt signaling pathway. Overall, these results support using PROs as a potential candidate for the treatment of DMED. [ABSTRACT FROM AUTHOR]

Drought stress is one of the main abiotic stresses that limit plant growth and affect fruit quality and yield. Plants primarily lose water through leaf transpiration, and wax effectively reduces the rate of water loss from the leaves. However, the relationship between water loss and the wax formation mechanism in goji (Lycium barbarum) leaves remains unclear. 'Ningqi I' goji and 'Huangguo' goji are two common varieties. In this study, 'Ningqi I' goji and 'Huangguo' goji were used as samples of leaf material to detect the differences in the water loss rate, chlorophyll leaching rate, wax phenotype, wax content, and components of the two materials. The differences in wax-synthesis-related pathways were analyzed using the transcriptome and metabolome methods, and the correlation among the wax components, wax synthesis genes, and transcription factors was analyzed. The results show that the leaf permeability of 'Ningqi I' goji was significantly lower than that of 'Huangguo' goji. The total wax content of the 'Ningqi I' goji leaves was 2.32 times that of the 'Huangguo' goji leaves, and the epidermal wax membrane was dense. The main components of the wax of 'Ningqi I' goji were alkanes, alcohols, esters, and fatty acids, the amounts of which were 191.65%, 153.01%, 6.09%, and 9.56% higher than those of 'Huangguo' goji, respectively. In the transcriptome analysis, twenty-two differentially expressed genes (DEGs) and six transcription factors (TFs) were screened for wax synthesis; during the metabolomics analysis, 11 differential metabolites were screened, which were dominated by lipids, some of which, like D-Glucaro-1, 4-Lactone, phosphatidic acid (PA), and phosphatidylcholine (PE), serve as prerequisites for wax synthesis, and were significantly positively correlated with wax components such as alkanes by the correlation analysis. A combined omics analysis showed that DEGs such as LbaWSD1, LbaKCS1, and LbaFAR2, and transcription factors such as LbaMYB306, LbaMYB60, and LbaMYBS3 were strongly correlated with wax components such as alkanes and alcohols. The high expression of DEGs and transcription factors is an important reason for the high wax content in the leaf epidermis of 'Ningqi I' goji plants. Therefore, by regulating the expression of wax-synthesis-related genes, the accumulation of leaf epidermal wax can be promoted, and the epidermal permeability of goji leaves can be weakened, thereby reducing the water loss rate of goji leaves. The research results can lay a foundation for cultivating drought-tolerant goji varieties. [ABSTRACT FROM AUTHOR]

Background: There is growing evidence that diet and aging are associated; however, few studies have examined the relationship between macronutrient subtypes and phenotypic age acceleration, and the extent to which BMI (body mass index) mediates this association is unclear. Methods: This study included 6911 individuals who were 20 years or older and had participated in the National Health and Nutrition Examination Survey. Daily macronutrient intakes were calculated and classified by the quartile of their subtypes. PhenoAgeAccel was calculated as an aging index using nine chemistry biomarkers. Multivariable linear regression and isocaloric substitution effects were used to evaluate the association of macronutrients with PhenoAgeAccel. Mediation analyses were used to examine the mediation role of BMI in the association. Results: After adjusting for the potential covariates, the consumption of high-quality carbohydrates (β = −1.01, 95% CI: −1.91, −0.12), total protein (β = −2.00, 95% CI: −3.16, −0.84), and plant protein (β = −1.65, 95% CI: −2.52, −0.78) was negatively correlated with PhenoAgeAccel; the consumption of SFAs (β = 1.77, 95% CI: 0.72, 2.81) was positively correlated with PhenoAgeAccel. For every serving of low-quality carbohydrates/animal protein and other calories replaced by one serving of high-quality carbohydrates/plant protein, PhenoAgeAccel would be reduced by about 25 percent. The ratio between BMI-mediated high-quality carbohydrates and PhenoAgeAccel accounted for 19.76% of the total effect, while the ratio between BMI-mediated total fat and PhenoAgeAccel accounted for 30.78% of the total effect. Conclusions: Different macronutrient consumption subtypes are related to PhenoAgeAccel, which is partially mediated by BMI, depending on the quality of macronutrients. Replacing low-quality macronutrients with high-quality macronutrients might slow aging. [ABSTRACT FROM AUTHOR]

Mesoporous HZSM-5 zeolites with nanocrystal stacking morphology were directly synthesized via hydrothermal methods without mesoporous templates. The synthesized mesoporous HZSM-5 was subjected to hydrothermal–citric acid washing treatment. The structural and acidic properties of the samples before and after modification were characterized using various techniques. The catalytic performance for butene conversion to propylene was investigated under atmospheric pressure, 500 °C, and a butene weight hourly space velocity (WHSV) of 10 h−1 in a continuous-flow micro-fixed bed reactor. The results show that propylene selectivity increased significantly from 24.7% before modification to 44%, and propylene yield increased from 22% to 38%. After 2 h of hydrothermal–citric acid washing modification, the catalyst maintained a butene conversion rate of 76% and a selectivity of 47% at 525 °C and a WHSV of 10 h−1 after 130 h of continuous reaction, with a propylene yield of 37%. The results indicate that moderate hydrothermal–citric acid washing modification leads to the removal of aluminum from the zeolite framework, reducing the amount and strength of acid but increasing the mesopore quantity. This helps control the reaction pathways and diffusion of intermediate products, suppresses some side reactions, and improves the selectivity and yield of the desired product, propylene, while significantly enhancing catalytic stability. [ABSTRACT FROM AUTHOR]

Colorectal cancer remains a leading cause of cancer-related deaths worldwide, with early detection and removal of polyps being critical in preventing disease progression. Automated polyp segmentation, particularly in colonoscopy images, is a challenging task due to the variability in polyp appearance and the low contrast between polyps and surrounding tissues. In this work, we propose an edge-enhanced network (EENet) designed to address these challenges by integrating two novel modules: the covariance edge-enhanced attention (CEEA) and cross-scale edge enhancement (CSEE) modules. The CEEA module leverages covariance-based attention to enhance boundary detection, while the CSEE module bridges multi-scale features to preserve fine-grained edge details. To further improve the accuracy of polyp segmentation, we introduce a hybrid loss function that combines cross-entropy loss with edge-aware loss. Extensive experiments show that the EENet achieves a Dice score of 0.9208 and an IoU of 0.8664 on the Kvasir-SEG dataset, surpassing state-of-the-art models such as Polyp-PVT and PraNet. Furthermore, it records a Dice score of 0.9316 and an IoU of 0.8817 on the CVC-ClinicDB dataset, demonstrating its strong potential for clinical application in polyp segmentation. Ablation studies further validate the contribution of the CEEA and CSEE modules. [ABSTRACT FROM AUTHOR]

In this work, a series of electrical conductivities of pyrite-bearing dacite were measured under 10−1–106 Hz, 573–973 K, 1.0–3.0 GPa, and different pyrite contents ranging from 0 vol.% to 20 vol.%) using a Solartron–1260 A impedance analyzer. For the dacite sample with 5 vol.% pyrite, the electrical conductivity of the dacite increased with temperature but slightly decreased when the pressure was increased from 1.0 GPa to 3.0 GPa. In the temperature range of 573–973 K, the bulk electrical conductivity of the pyrite-bearing dacite gradually increased with increasing pyrite percentage from 0 vol.% to 20 vol.% at 1.0 GPa. Thus, a positive correlation between the electrical conductivity of the sample and the pyrite content was typically observed. In light of the significant enhancement in the electrical conductivity of the interconnected pyrite in the dacite, the value of the percolation threshold was determined as 7 vol.%. Furthermore, the dominant conduction mechanism of the small polaron for pyrite-bearing dacite was proposed from our obtained results on the chemical compositions and activation enthalpies under high-temperature and high-pressure conditions. A comprehensive consideration of our constructed electrical conductivity–depth profile based on the electrical conductivity of the pyrite-bearing dacite, can provide a good constraint on the volume of pyrite in dacite for high-conductivity Duobaoshan island arc. In conclusion, the presence of pyrite in dacite can provide a reasonable explanation for the high-conductivity anomaly observed in the region of Duobaoshan island arc. [ABSTRACT FROM AUTHOR]

Quaternary volcanoes from the southeastern Tibetan Plateau occur at the Tengchong volcanic field (TVF). The Daliuchong volcano is the largest volcano in the TVF, which has the most felsic compositions with explosive eruptions. The eruption history and origin of the Daliuchong volcano are a matter of debate. In the present paper, we report the groundmass K-Ar ages, whole-rock Sr-Nd-Pb-Hf isotopes, zircon U-Pb ages, and Hf-O isotopic compositions for the Daliuchong volcano to constrain its eruption history and petrogenesis. The groundmass K-Ar ages and zircon U-Pb ages indicate mid-Pleistocene (0.6 Ma to 0.3 Ma) eruptions. The presence of zircon phenocrysts with enriched mantle-like O-Hf isotopes (δ18O < 6‰, and εHf about −2) suggests the involvement of mantle-derived basaltic magmas. The whole-rock Pb isotope compositions and Sr-Nd isotope modeling reveal the involvement of magma from the lower crust. The zircon xenocrysts reveal previously unrecognized 20-Ma magmatic activity at the TVF and contamination of late Cretaceous (66–80 Ma) S-type granites during the formation of the Daliuchong dacites. The dacite magma at Daliuchong was formed by mixing of the mantle-derived magma and lower-crust-derived magma and subsequently contaminated by upper crustal materials, including late Cretaceous S-type granitic rocks. [ABSTRACT FROM AUTHOR]

Non-thermal plasma (NTP) synergistic anticancer strategies are a current hotspot of interest at the intersection of plasma biomedicine. Melittin (MEL) has been shown to inhibit cancer in many malignant tumors; however, its clinical application is controversial. Therefore, the transmembrane process and mechanism of MEL activity in different cell systems were studied and the combination of MEL and NTP was proposed in this paper. The results showed that the electrostatic attraction between MEL and the lipid bilayer contributes to the stable orientation of MEL on the membrane surface. In addition, sialic acid overexpression affects the degree to which MEL binds the membrane system and the stability of the membrane structure. The use of NTP to reduce the dosage of MEL and its related nonspecific cytolysis activity has certain clinical application value. The results of this study provide theoretical support for improving the clinical applicability of MEL and contribute to the further development of plasma biomedicine. [ABSTRACT FROM AUTHOR]

Axitinib (AXTN) is an oral tyrosine kinase inhibitor for the treatment of early to advanced renal cell carcinoma. In this work, solvates of AXTN were prepared in five solvents and subjected to desolvation treatment. The crystal form A of AXTN can form solvates in acetonitrile, DMF, acetic acid, acetic acid + water, and methanol. Different ratios of AXTN and acetic acid will form different products (solvate or directly crystallized into another crystal form (form IV)). The characterization results of thermal analyses confirmed the types of the five solvates. The obtained solvates were desolvated using methods of solid-phase desolvation (heating, exposure to solvent steam, microwave) and solvent-mediated phase transformation (SMPT). The desolvated solids were characterized by PXRD, TGA, DSC, FT-IR, and SEM, and it was ultimately inferred that a new crystal form (form Z) of AXTN could be formed after desolvation. In addition, the solvates obtained in this work experienced mutual transformation via SMPT, which depends on the type of solvents or mixed solvents. The phase transformations of different solid forms were summarized. This study is instructive for exploring solvates and polymorphs of AXTN and understanding phase transitions under different environments. [ABSTRACT FROM AUTHOR]

Prussian blue analogs (PBAs) are appealing cathode materials for sodium-ion batteries because of their low material cost, facile synthesis methods, rigid open framework, and high theoretical capacity. However, the poor electrical conductivity, unavoidable presence of [Fe(CN)6] vacancies and crystalline water within the framework, and phase transition during charge–discharge result in inferior electrochemical performance, particularly in terms of rate capability and cycling stability. Here, cobalt-free PBAs are synthesized using a facile and economic co-precipitation method at room temperature, and their sodium-ion storage performance is boosted due to the reduced crystalline water content and improved electrical conductivity via the high-entropy and component stoichiometry tuning strategies, leading to enhanced initial Coulombic efficiency (ICE), specific capacity, cycling stability, and rate capability. The optimized HE-HCF of Fe0.60Mn0.10-hexacyanoferrate (referred to as Fe0.60Mn0.10-HCF), with the chemical formula Na1.156Fe0.599Mn0.095Ni0.092Cu0.109Zn0.105 [Fe(CN)6]0.724·3.11H2O, displays the most appealing electrochemical performance of an ICE of 100%, a specific capacity of around 115 and 90 mAh·g−1 at 0.1 and 1.0 A·g−1, with 66.7% capacity retention observed after 1000 cycles and around 61.4% capacity retention with a 40-fold increase in specific current. We expect that our findings could provide reference strategies for the design of SIB cathode materials with superior electrochemical performance. [ABSTRACT FROM AUTHOR]

In this study, Fe, N co-doped biochar (Fe@N co-doped BC) was synthesized by the carbonization–pyrolysis method and used as a carbocatalyst to activate peroxymonosulfate (PMS) for sulfamethoxazole (SMX) removal. In the Fe@N co-doped BC/PMS system, the degradation efficiency of SMX (10.0 mg·L−1) was 90.2% within 40 min under optimal conditions. Radical quenching experiments and electron spin resonance (ESR) analysis suggested that sulfate radicals (SO4•−), hydroxyl radicals (•OH), and singlet oxygen (1O2) participated in the degradation process. After the reaction, the proportion of pyrrolic N decreased from 57.9% to 27.1%. Pyrrolic N served as an active site to break the inert carbon network structure and promote the generation of reactive oxygen species (ROS). In addition, pyrrolic N showed a stronger interaction with PMS and significantly reduced the activation energy required for the reaction (∆G = 23.54 kcal/mol). The utilization potentiality of Fe@N co-doped BC was systematically evaluated in terms of its reusability and selectivity to organics. Finally, the intermediates of SMX were also detected. [ABSTRACT FROM AUTHOR]

Simple Summary: The prevalence of indeterminate pulmonary nodule (IPN) findings in early lung cancer screening settings highlights the need for novel imaging biomarkers to assist clinicians in making informed therapeutic decisions. The surrounding vasculature of pulmonary nodules, termed "macro-vasculature", has been identified as a potential biomarker for evaluating nodule malignancy. However, the relationship between the macro-vasculature's arteries and veins surrounding an IPN and its malignancy remains unclear. This study aimed to investigate this association. Our findings indicate that arterial characteristics significantly outweigh venous characteristics in distinguishing malignant from benign nodules. Additionally, incorporating arterial information surrounding a nodule enhances the performance in differentiating malignant from benign nodules. Clarifying the relationship between macro-vasculature arteries and nodule malignancy may facilitate clinical follow-up procedures for screen-detected pulmonary nodules. Objective: This study aims to investigate the association between the arteries and veins surrounding a pulmonary nodule and its malignancy. Methods: A dataset of 146 subjects from a LDCT lung cancer screening program was used in this study. AI algorithms were used to automatically segment and quantify nodules and their surrounding macro-vasculature. The macro-vasculature was differentiated into arteries and veins. Vessel branch count, volume, and tortuosity were quantified for arteries and veins at different distances from the nodule surface. Univariate and multivariate logistic regression (LR) analyses were performed, with a special emphasis on the nodules with diameters ranging from 8 to 20 mm. ROC-AUC was used to assess the performance based on the k-fold cross-validation method. Average feature importance was evaluated in several machine learning models. Results: The LR models using macro-vasculature features achieved an AUC of 0.78 (95% CI: 0.71–0.86) for all nodules and an AUC of 0.67 (95% CI: 0.54–0.80) for nodules between 8–20 mm. Models including macro-vasculature features, demographics, and CT-derived nodule features yielded an AUC of 0.91 (95% CI: 0.87–0.96) for all nodules and an AUC of 0.82 (95% CI: 0.71–0.92) for nodules between 8–20 mm. In terms of feature importance, arteries within 5.0 mm from the nodule surface were the highest-ranked among macro-vasculature features and retained their significance even with the inclusion of demographics and CT-derived nodule features. Conclusions: Arteries within 5.0 mm from the nodule surface emerged as a potential biomarker for effectively discriminating between malignant and benign nodules. [ABSTRACT FROM AUTHOR]

The epoxy nanocomposites reinforced by MoS2 nanosheets and aligned multi-walled carbon nanotubes (MWCNTs) were fabricated by DC electric field inducement. The epoxy nanocomposites achieved improvement in the tribological properties with the addition of randomly dispersed MoS2 and MWCNTs compared to the pure epoxy. Furthermore, the epoxy nanocomposites exhibit anisotropic tribological and mechanical properties when the MWCNTs are aligned in the composites. The tribological properties of epoxy nanocomposites containing 1 wt% MoS2 and aligned 1.2 wt% MWCNTs achieved the maximum improvement when the sliding direction is perpendicular to the axial direction of MWCNTs. Compared to random MoS2 nanosheets and random MWCNTs reinforced epoxy nanocomposites, the friction coefficient and wear rate of random MoS2 and aligned MWCNTs reinforced epoxy nanocomposites decreased by 11.3 and 66.7% under a load of 5 N, respectively. The increased thermal conductivity and mechanical properties, higher surface content of nanoparticles, as well as unique alignment mode of MWCNTs are considered to be the main reasons for the improvement of tribological properties of epoxy nanocomposites. [ABSTRACT FROM AUTHOR]

China is one of the largest sugarcane industrial countries in the world, and the annual output of bagasse waste is abundant. Classical incineration, landfill, and other treatment methods are inefficient and seriously harmful to the environment, so it is urgent to develop a new comprehensive utilization of agricultural waste. In this work, the sugarcane waste residue is converted to biological activated carbon (BAC) through a simple pre-carbonization and KOH activation process, which is then mixed with perovskite oxide BaCo0.5Fe0.5O3−δ (BCF) to form BAC/BCF composite air electrode. BAC/BCF assembled rechargeable zinc–air battery (ZAB) exhibits a relatively good output maximum power density of 96 mW·cm−2 and considerable long-term charge–discharge cycle stability over 250 h operation. These results indicate that the BAC derived from sugarcane waste is a promising potential carbon material candidate for ZAB application, which can realize the high-value utilization of agricultural waste in the field of efficient and durable energy storage and conversion devices. [ABSTRACT FROM AUTHOR]

CO2 photoreduction into valuable hydrocarbons, such as CO, CH4, and C2H4, delivers a promising approach to address both environmental and energy challenges. Transition metal chalcogenides, particularly cadmium sulfide (CdS), have emerged as prominent candidates due to their tunable electronic properties and availability. This study delves into a comprehensive investigation of how CdS crystalline facets and sulfur-deficient surfaces modulate the product selectivity. Through employing density functional theory (DFT), we unravel the catalytic performance of various CdS crystal orientations and sulfur vacancy configurations. The results have shown that different CdS facets exhibit unique electronic characteristics and surface energetics, which influence the adsorption dynamics and reaction pathways. The introduction of sulfur vacancies further modulates the nature of active sites, leading to substantial shifts in product selectivity. A detailed investigation on the reaction mechanisms unveils that specific facets preferentially facilitate the formation of CO, while others are more conducive to the generation of hydrocarbons such as CH4 and C2H4, due to the variations in activation barriers and intermediate stabilities. These findings underscore the importance of crystal facet engineering and defect manipulation in tailoring catalyst performance thus providing valuable insights for the rational design of efficient and selective CO2 reduction metal catalysts. [ABSTRACT FROM AUTHOR]

The performance of the cathodic hydrogen evolution reaction (HER) in alkaline water electrolysis, an attractive hydrogen production technology, is highly dependent on efficient catalysts. Ruthenium (Ru), which is more affordable than platinum (Pt) and has a metal–hydrogen bond strength comparable to that of Pt, shows exceptional catalytic activity for the alkaline HER. Consequently, in recent years, research in the field of hydrogen production through alkaline water electrolysis has increasingly focused on Ru as a key element. This review first discusses the fundamentals of the alkaline HER, including principles, factors affecting its performance, and regulation strategies for its performance improvement. The research progress of ruthenium-based catalysts for the alkaline HER is then summarized with selected examples. The electronic structures of various ruthenium nanoparticles, ruthenium-M (M = noble metals and transition metals) heterogeneous catalysts, and ruthenium-based compounds are regulated by modulating the components and ligands of Ru atoms, aiming to achieve low water dissociation energies and optimal binding energies for hydrogen (H) and hydroxyl (−OH) groups, thereby enhancing the alkaline HER catalytic performance. Finally, the problems, challenges, and future development directions of the alkaline HER are proposed. [ABSTRACT FROM AUTHOR]

Joints in frame structures often fail before beams and columns in an earthquake and are a key part of reinforcement. In this study, to enhance the seismic performance of concrete frame structures, a steel-jacketed grouting composite reinforcement method is proposed by combining reinforcement technology, steel cladding technology, and eco-efficient materials from grouting technology. This method effectively utilizes the advantages of various materials, avoids major demolition and construction, and reduces waste and resource consumption. In order to verify the feasibility and effectiveness of the reinforcement method, one of the original joint specimens with a scale of 1:3 and one of the reinforced joint specimens were designed and tested. The experiments involved reversed cyclic testing of beam–column to measure its seismic behavior. The seismic performance indexes such as failure characteristics, hysteretic properties, and the energy dissipation capacity of the specimens were analyzed, and the corresponding finite element model was established. The influence of key parameters such as reinforcement range, steel plate thickness, and grout strength on its seismic performance was explored. The research shows that the method can effectively improve the seismic performance of the joints, and seismic performance indexes such as bearing capacity, ductility, and energy consumption of the specimens are significantly improved. The test results of the established finite element model are in good agreement. The variable parameter analysis of the finite element shows that the thickness of the steel plate has little influence on its bearing capacity. With the increase in the reinforcement range of the clad steel and the strength of the grouting material, the bearing capacity of the specimen increases. The research results can provide a reference for the reinforcement of frame structure joints. [ABSTRACT FROM AUTHOR]

As the popularity of fresh air systems (FAS) in residential buildings increases, exploring the behavioral characteristics of their use can help to provide a comprehensive understanding of the potential for demand flexibility in residential buildings. However, few studies in the past have focused on the personalized usage behavior of FAS. To fill this gap, this study proposes a method based on data mining techniques to reveal the behavioral patterns of FAS usage and the motivations behind them, including motivational patterns, operation duration patterns, and human–machine interaction patterns, for 13 households in Beijing. The simultaneously obtained behavioral patterns, in turn, form the basis of association rules, which can classify FAS usage behavior into two typical residential user profiles containing user behavioral characteristics. This study can not only provide more accurate assumptions and inputs for behavioral stochastic models but also provide data support for the development and optimization of demand response strategies. [ABSTRACT FROM AUTHOR]

By employing the hyperbolic tangent model of load transfer (LT), this paper establishes the thermo-mechanical (TM) coupling load transfer analysis approach for an energy pile (EP). By incorporating the control condition of the unbalance force at the null point, the method for determining the null point considering the temperature effect is enhanced. The viability of the presented method is validated through the measured outcomes from model experiments of energy piles. A parametric investigation is conducted to explore the impact of the soil shear strength parameters, upper load, temperature variation, head stiffness, and radial expansion on the axial force, strain, and displacement of the energy pile under thermo-mechanical coupling. The results suggest that the locations of the null point and the maximum axial force are dependent on the constraint boundary conditions of the pile side and the two ends. When the stiffness of the pile top increases, axial stress and displacement increase, while strain decreases. An increase in the drained friction angle leads to an increase in axial stress under thermal-load coupling, but strain and displacement decline. The radial expansion has a negligible influence on the thermo-mechanical interaction between the pile and the soil. [ABSTRACT FROM AUTHOR]

Underground spaces contain abundant geothermal energy, which can be recovered for building ventilation, reducing energy consumption. However, current research lacks a comprehensive quantitative assessment of its energy recovery. This research evaluates the energy recovery potential of the Xingfu Forest Belt Urban Underground Utility Tunnels. Field experiments revealed a 7 °C temperature difference in winter and a 2.5 °C reduction during the summer-to-autumn transition. A computational fluid dynamics (CFD) model was developed to assess the impact of design and operational factors such as air exchange rates on outlet temperatures and heat exchange efficiency. The results indicate that at an air change rate of 0.5 h−1, the tunnel outlet temperature dropped by 10.5 °C. A 200 m tunnel transferred 8.7 × 1010 J of heat over 30 days, and a 6 m × 6 m cross-sectional area achieved 1.1 × 1011 J of total heat transfer. Increasing the air exchange rate and cross-sectional area reduces the inlet–outlet temperature difference while enhancing heat transfer capacity. However, the optimal buried depth should not exceed 8 m due to cost and safety considerations. This study demonstrates the potential of shallow geothermal energy as an eco-friendly and efficient solution for enhancing building ventilation systems. [ABSTRACT FROM AUTHOR]

As a new type of pile, the bearing characteristics of stepped variable-section DX piles (multi-joint extruded and expanded piles) are quite complicated; thus, their design concepts and pile-forming processes are still in the exploration stage, and their application in actual engineering is not particularly mature. The settlement law and load transfer law of the variable section DX pile have not been studied deeply, and the values of the parameters of engineering design are not clear, which are the problems to be solved for the variable section DX pile. To solve the above problems, the present study on the bearing characteristics of stepped variable-section DX piles under vertical loading is of great scientific significance and engineering practical value. In this study, the bearing capacity of a DX pile with two variable steps was first analyzed experimentally. Then, the bearing capacity of variable cross-section DX piles and equal cross-section piles were simulated under the same soil conditions. Later, the numerical simulation results were compared with the experimental results to verify the validity and accuracy of the numerical models established in ABAQUS software. Finally, the bearing capacity of stepped variable-section DX piles in different soil layers was analyzed numerically to compare the effect of different soils on the compressive bearing capacity of piles. The results indicated that the load-bearing plates had a greater influence on the bearing capacity of the stepped variable-section DX piles. At the optimum variable section ratio, which was close to 0.9, DX piles had a good bearing capacity. The relative errors of the numerical simulation ultimate loads were below 10%, which verified the accuracy of the developed numerical model. The simulated ultimate load of the equal-section pile was the smallest. The vertical compressive bearing capacity and the effect of controlling settlement under the same level of load of the variable section DX pile in sandy soil were both better than those in silt soil. There was little difference between the bearing capacities of the piles with a load-bearing plate. The bearing capacity of the pile with two load-bearing plates was the best, which can be used in practical engineering. [ABSTRACT FROM AUTHOR]

Pavement maintenance and rehabilitation decision-making needs to weigh multiple strategic goals to achieve sustainable development through the pavement maintenance management system. Making decisions regarding pavement preventive maintenance is both intricate and costly. This study introduces a multi-criteria decision-making framework aimed at enhancing the scientific basis of such decisions. The framework first establishes an evaluation system for preventive maintenance strategies by considering three primary evaluation criteria—service functionality, pavement performance, and economic benefits, and then identifies nine specific evaluation indicators to influence these criteria, with a comparison matrix constructed to determine the weight of each indicator in relation to the maintenance decision hierarchy. Following this, the technique for order preference by similarity to ideal solution (TOPSIS) is employed to prioritize four commonly utilized preventive maintenance strategies. The results reveal that pavement condition and maintenance costs are the most influential factors in determining the appropriate preventive maintenance strategies for national highways. The priority rankings for the four strategies—slurry seal, micro-surfacing, chip seal, and ultra-thin overlays—are found to be 56.12%, 63.86%, 12.12%, and 83.52%, respectively, with ultra-thin overlays identified as the optimal choice for second-class highways. The decision-making model utilized in this study enables a multi-dimensional analysis, reducing the subjectivity inherent in expert evaluations and facilitating the prompt identification of the most suitable maintenance strategy. [ABSTRACT FROM AUTHOR]

Nucleation and growth during the crystallization process are crucial steps that determine the crystal structure, size, morphology, and purity. A thorough understanding of these mechanisms is essential for producing crystalline products with consistent properties. This study investigates the solubility of tacrolimus (FK506) in an ethanol–water system (1:1, v/v) and examines its crystallization kinetics using batch crystallization experiments. Initially, the solubility of FK506 was measured, and classical nucleation theory was employed to analyze the induction period to determine interfacial free energy ( γ ) and other nucleation parameters, including the critical nucleus radius ( r * ), critical free energy ( ∆ G * ), and the molecular count of the critical nucleus ( i * ). Crystallization kinetics under seeded conditions were also measured, and the parameters of the kinetic model were analyzed to understand the effects of process states such as temperature on the crystallization process. The results suggested that increasing temperature and supersaturation promotes nucleation. The surface entropy factor ( f ) indicates that the tacrolimus crystal growth mechanism is a two-dimensional nucleation growth. The growth process follows the particle size-independent growth law proposed by McCabe. The estimated kinetic parameters reveal the effects of supersaturation, temperature, and suspension density on the nucleation and growth rates. [ABSTRACT FROM AUTHOR]

Helium ions implanted into metals can form ordered bubbles that are isomorphic to the host lattice. While long-range elastic interactions are generally believed to drive bubble superlattice formation, the interactions between individual helium solutes are not yet fully understood. Our first-principles calculations reveal that in molybdenum, Friedel oscillations induced by individual helium atoms generate potential barriers and wells that influence helium pairing and clustering at short He-He distances. These repulsive and attractive interactions at high concentrations provide thermodynamic driving forces that align randomly distributed helium atoms into Mo-He superlattices. Friedel oscillations may have broad impacts on solute–solute interactions in alloys. [ABSTRACT FROM AUTHOR]

Raw lacquer, known for its superior performance as a natural liquid coating, boasts excellent physical and mechanical properties as well as durability, making it widely used in manufacturing. However, the high hardness of the lacquer film upon complete curing poses challenges for carving and mechanical engraving. Therefore, it is necessary to study the curing process of lacquer films to obtain films suitable for carving or mechanical engraving. This study involves the preparation of raw lacquer with varying amounts of tung oil added, followed by the measurement of film drying time, surface roughness, glossiness, hardness, and adhesion on substrates to determine the optimal drying conditions. Additionally, SEM analysis of the carved surfaces and FT-IR analysis were used to investigate the impact of tung oil addition on lacquer carving performance and its variation. The results indicate that tung oil, to a certain extent, contributes to a smoother lacquer film but adversely affects film hardness and adhesion to Prunus serotina. However, with an increase in the amount of refined tung oil to 15%, the film exhibits improved glossiness, smoother carving tool marks, and reduced debris, thereby validating the feasibility of mechanical carving of tung oil-modified raw lacquer to some extent. [ABSTRACT FROM AUTHOR]

Macrophages, known for their phenotypic plasticity, play a critical role in maintaining homeostasis and inflammation-related pathogenesis. Although identifying diverse macrophage phenotypes holds promise for enhancing diagnoses and treatments of diseases mediated by macrophages, existing methodologies for differentiating macrophages often lack precision. They are limited by the cumbersome procedures that require large-scale equipment, such as flow cytometry and transcriptomic analysis. In this context, we have engineered fluorescent polyadenine (polyA)-mediated sticky flares that enable practical visualization of macrophages. This technology facilitates the highly sensitive detection of macrophage phenotypes through the specific recognition of intracellular mRNAs, permitting in situ imaging. Our approach demonstrates the potential for determining macrophage polarization status at the single-cell level within dynamic immune microenvironments, thereby providing crucial diagnostic and prognostic information that could guide the development of tailored treatments for macrophage-related diseases in personalized medicine. [ABSTRACT FROM AUTHOR]