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Sintering is a common phenomenon, which often takes place during the oxidation roasting process of molybdenite concentrate in multiple-hearth furnaces. The occurrence of sintering phenomena has detrimental effects on the product quality and the service life of the furnace. In this work, the influence of two key factors (roasting temperature and K content) on the sintering behavior is investigated using molybdenite concentrate as the raw material. Different technologies such as XRD, FESEM-EDS, and phase diagrams are adopted to analyze the experimental data. The results show that the higher the roasting temperature is, the greater the mass loss and the more serious the sintering degree will be. The results also show that with the increase in K content, the mass loss of the raw material is first increased and then decreased, while its sintering degree is still gradually increased. The sintering products obtained during the oxidation roasting process are often tightly combined with the bottom of the used crucible with a smooth and dense surface structure, while their internal microstructures are very complicated, which not only includes numerous MoO 3 species, but also unoxidized MoS 2 , Mo sub-oxide, SiO 2 , and a variety of molybdates. Among them, both MoO 3 and molybdates can be easily dissolved into the ammonia solution, leading to a residue mainly composed of SiO 2 and CaMoO 4 . This study also finds that the sintering phenomenon is caused by the increase in local temperature and the formation of various low-melting-point eutectics. It is suggested that decreasing the roasting temperature and K content, especially the K content, are effective methods for reducing the sintering degree of molybdenite concentrate during the oxidation roasting process.

A series of β-carboline derivatives containing nitrogen heterocycles were designed and synthesized. All compounds were screened for their antitumor activity against four human tumor cell lines (A549, K562, PC-3, T47D). Notably, compound N -(4-(morpholinomethyl)phenyl)-2-((5-(1-(3,4,5-trimethoxyphenyl)-9 H -pyrido[3,4-b]indol-3-yl)-1,3,4-oxadiazol-2-yl)thio)acetamide ( 8q ) exhibited significant inhibitory activity against PC-3 cells with an IC 50 value of 9.86 µM. Importantly, compound 8q effectively suppressed both the proliferation and migration of PC-3 cells. Mechanistic studies revealed that compound 8q induced cell apoptosis and caused the accumulation of reactive oxygen species (ROS), leading to cell cycle arrest in the G0/G1 phase in PC-3 cells.

This paper reports on the novel composite membrane electrolytes used in Zn/MnO 2 , Al/MnO 2 , Al/air, and zinc/air electrochemical devices. The composite membranes were made using poly(vinyl alcohol), poly(acrylic acid), and a sulfonated polypropylene/polyethylene separator to enhance the electrochemical characteristics and dimensional stability of the solid electrolyte membranes. The ionic conductivity was improved significantly by the amount of acrylic acid incorporated into the polymer systems. In general, the ionic conductivity was also enhanced gradually as the testing temperature increased from 20 to 80 °C. Porous zinc gel electrodes and pure aluminum plates were used as the anodes, while porous carbon air electrodes or porous MnO 2 electrodes were used as the cathodes. The cyclic voltammetry properties and electrochemical impedance characteristics were investigated to evaluate the cell behavior and electrochemical properties of these prototype cells. The results showed that these prototype cells had a low bulk resistance, a high cell power density, and a unique device stability. The Al/MnO 2 cell achieved a density of 110 mW cm -2 at the designated current density for the discharge tests, while the other cells also exhibited good values in the range of 70-100 mW cm -2 . Furthermore, the Zn/air cell consisting of the PVA/PAA = 10:5 composite membrane revealed an excellent discharge capacity of 1507 mAh. This represented a very high anode utilization of 95.7% at the C/10 rate.

Defects in photovoltaic (PV) panels can significantly reduce the power generation efficiency of the system and may cause localized overheating due to uneven current distribution. Therefore, adopting precise pixel-level defect detection, i.e., defect segmentation, technology is essential to ensuring stable operation. However, for effective defect segmentation, the feature extractor must adaptively determine the appropriate scale or receptive field for accurate defect localization, while the decoder must seamlessly fuse coarse-level semantics with fine-grained features to enhance high-level representations. In this paper, we propose a Progressive Deformable Transformer (PDeT) for defect segmentation in PV cells. This approach effectively learns spatial sampling offsets and refines features progressively through coarse-level semantic attention. Specifically, the network adaptively captures spatial offset positions and computes self-attention, expanding the model's receptive field and enabling feature extraction across objects of various shapes. Furthermore, we introduce a semantic aggregation module to refine semantic information, converting the fused feature map into a scale space and balancing contextual information. Extensive experiments demonstrate the effectiveness of our method, achieving an mIoU of 88.41% on our solar cell dataset, outperforming other methods. Additionally, to validate the PDeT's applicability across different domains, we trained and tested it on the MVTec-AD dataset. The experimental results demonstrate that the PDeT exhibits excellent recognition performance in various other scenarios as well.

In recent years, with the rapid construction of a safe, clean, efficient and sustainable modern energy system, the intelligence of coal mining has become the inevitable direction of the development of the coal mining industry. The intelligence of coal mining system and equipment is the core of intelligent mining, and the positioning technology of mining equipment is the key to underground intelligent mining. The strapdown inertial navigation system can make up for the shortcomings of traditional GPS positioning systems and laser positioning because of its strong anti-interference, high precision and real-time monitoring, and ability to carry out real-time dynamic positioning of mining equipment in underground coal mines. This paper briefly introduces the basic principle of the strapdown inertial navigation system, analyzes the application of the existing strapdown inertial navigation system in mining equipment, and lists and analyzes the research status of the improvement strategy of the inertial navigation system, such as zero speed correction and integrated navigation technology. Finally, by analyzing the application and future development trend of inertial navigation systems in mining equipment, this paper provides more data and method support for the positioning of mining equipment in the future.

The material properties and structural characteristics of ballistic composites are crucial to their ballistic performance. A numerical model of a 1.1 g FSP penetrating a UHMWPE target plate was established in this paper. The numerical results show that the failure process of the body armor target plate primarily involves shear failure, interlayer delamination, and tensile failure. Based on this, further research was conducted on the influence of material properties and structural characteristics on the ballistic limit velocity of the UHMWPE armor plate. Furthermore, the study evaluates the effects of elastic modulus, tensile strength, shear strength, number of layers, and interlayer strength on the ballistic limit velocity of UHMWPE body armor. The findings reveal that the ballistic limit velocity is most sensitive to changes in shear strength, with variation rates ranging from -18% to +11%, showing an approximate positive correlation, while the elastic modulus has the smallest impact on ballistic limit velocity, with variation rates ranging from -2% to +4%. Additionally, appropriate interlayer strength can improve the ballistic limit velocity of the body armor to a certain extent. This study provides theoretical methods and recommendations for optimizing anti-penetration performance of UHMWPE body armor.

In smart classroom environments, accurately recognizing students' facial expressions is crucial for teachers to efficiently assess students' learning states, timely adjust teaching strategies, and enhance teaching quality and effectiveness. In this paper, we propose a student facial expression recognition model based on multi-scale and deep fine-grained feature attention enhancement (SFER-MDFAE) to address the issues of inaccurate facial feature extraction and poor robustness of facial expression recognition in smart classroom scenarios. Firstly, we construct a novel multi-scale dual-pooling feature aggregation module to capture and fuse facial information at different scales, thereby obtaining a comprehensive representation of key facial features; secondly, we design a key region-oriented attention mechanism to focus more on the nuances of facial expressions, further enhancing the representation of multi-scale deep fine-grained feature; finally, the fusion of multi-scale and deep fine-grained attention-enhanced features is used to obtain richer and more accurate facial key information and realize accurate facial expression recognition. The experimental results demonstrate that the proposed SFER-MDFAE outperforms the existing state-of-the-art methods, achieving an accuracy of 76.18% on FER2013, 92.75% on FERPlus, 92.93% on RAF-DB, 67.86% on AffectNet, and 93.74% on the real smart classroom facial expression dataset (SCFED). These results validate the effectiveness of the proposed method.

With the rapid development of wearable biosensor technology, the combination of head-mounted displays and augmented reality (AR) technology has shown great potential for health monitoring and biomedical diagnosis applications. However, further optimizing its performance and improving data interaction accuracy remain crucial issues that must be addressed. In this study, we develop smart glasses based on augmented reality and eye tracking technology. Through real-time information interaction with the server, the smart glasses realize accurate scene perception and analysis of the user's intention and combine with mixed-reality display technology to provide dynamic and real-time intelligent interaction services. A multi-level hardware architecture and optimized data processing process are adopted during the research process to enhance the system's real-time accuracy. Meanwhile, combining the deep learning method with the geometric model significantly improves the system's ability to perceive user behavior and environmental information in complex environments. The experimental results show that when the distance between the subject and the display is 1 m, the eye tracking accuracy of the smart glasses can reach 1.0° with an error of no more than ±0.1°. This study demonstrates that the effective integration of AR and eye tracking technology dramatically improves the functional performance of smart glasses in multiple scenarios. Future research will further optimize smart glasses' algorithms and hardware performance, enhance their application potential in daily health monitoring and medical diagnosis, and provide more possibilities for the innovative development of wearable devices in medical and health management.

Fusarium solani KMZW-1 is recognized for its potential as a biocontrol agent against agricultural and forestry pests, particularly due to its compatibility with integrated pest management (IPM) strategies. This study aimed to investigate the complete genome of F. solani KMZW-1 and assess its pathogenicity against Bactrocera dorsalis . Whole-genome sequencing revealed a genome size of 47,239,278 bp, comprising 27 contigs, with a GC content of 51.16% and fungus identified as F. solani KMZW-1. The genome completeness was assessed as 97.93% using BUSCO analysis, the DFVF sequence identifier was Fusarium 0G092560.1, and AntiSMASH analysis identified 35 gene clusters associated with secondary metabolite biosynthesis, providing insights into the genetic basis of its pathogenic mechanisms and biocontrol potential. Comparative genomic analysis found 269 unique genes for F. solani KMZW-1, and collinearity analysis exhibited a high degree of synteny with Fusarium solani-melongenae . The pathogenicity of F. solani KMZW-1 was assessed using concentrations ranging from 1 × 10 4 to 1 × 10 11 conidia/mL. Higher concentrations (1 × 10 10 to 1 × 10 11 conidia/mL) resulted in significantly increased cumulative mortality rates of B. dorsalis adults compared to the control group. Notably, the pathogenicity was higher in male adults than in females. Probit analysis yielded LC 50 (50% lethal concentration) values of 5.662 for female and 4.486 for male B. dorsalis adults. In summary, F. solani , KMZW-1 exhibits strong insecticidal activity against B. dorsalis and shows potential as a biocontrol agent with IPM strategies. These findings provide robust genomic evidence supporting the use of F. solani KMZW-1 in managing against B. dorsalis populations.

Camellia luteoflora is a rare and endangered plant endemic to China. It has high ornamental and potential economic and medicinal value, and is an important germplasm resource of Camellia. To understand the distributions and differences in metabolites from different parts of C. luteoflora , in this study, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to examine the types and contents of chemical constituents in five organs of C. luteoflora : roots, stems, leaves, flowers, and fruits. The results showed that a total of 815 metabolites were identified in the five organs and were classified into 18 main categories, including terpenoids (17.1%), amino acids (10.4%), flavonoids (10.3%), sugars and alcohols (9.8%), organic acids (9.0%), lipids (7.1%), polyphenols (4.8%), alkaloids (4.8%), etc. A total of 684 differentially expressed metabolites (DEMs) in five organs were obtained and annotated into 217 KEGG metabolic pathways, among which metabolic pathways, ABC transporters, the biosynthesis of cofactors, and the biosynthesis of amino acids were significantly enriched. In DEMs, flowers are rich in flavonoids, polyphenols, organic acids, and steroids; fruits are rich in amino acids, alkaloids, vitamins, and xanthones; stems are rich in lignans; and leaves have the highest relative content of phenylpropanoids, ketoaldehydic acids, quinones, sugars and alcohols, terpenoids, coumarins, lipids, and others; meanwhile, the metabolite content is lower in roots. Among the dominant DEMs, 58 were in roots, including arachidonic acid, lucidone, isoliquiritigenin, etc.; 75 were in flowers, including mannose, shikimic acid, d-gluconic acid, kaempferol, etc.; 45 were in the fruit, including pterostilbene, l-ascorbic acid, riboflavin, etc.; 27 were in the stems, including salicylic acid, d-(-)-quinic acid, mannitol, (-)-catechin gallate, etc.; there was a maximum number of 119 dominant metabolites in the leaves, including oleanolic acid, l-glucose, d-arabitol, eugenol, etc. In sum, the rich chemical composition of C. luteoflora and the significant differences in the relative contents of metabolites in different organs will provide theoretical references for the study of tea, flower tea, edible oil, nutraceuticals, and the medicinal components of C. luteoflora .

Trigger-action programming (TAP) enables users to automate Internet of Things (IoT) devices by creating rules such as "IF Device1.TriggerState is triggered, THEN Device2.ActionState is executed". As the number of IoT devices grows, the combination space between the functions provided by devices expands, making manual rule creation time-consuming for end-users. Existing TAP recommendation systems enhance the efficiency of rule discovery but face two primary issues: they ignore the association of rules between users and fail to model collaborative information among users. To address these issues, this article proposes a graph contrastive learning-based recommendation system for TAP rules, named GCL4TAP. In GCL4TAP, we first devise a data partitioning method called DATA2DIV, which establishes cross-user rule relationships and is represented by a user-rule bipartite graph. Then, we design a user-user graph to model the similarities among users based on the categories and quantities of devices that they own. Finally, these graphs are converted into low-dimensional vector representations of users and rules using graph contrastive learning techniques. Extensive experiments conducted on a real-world smart home dataset demonstrate the superior performance of GCL4TAP compared to other state-of-the-art methods.

Background/Objectives: Induced pluripotent stem cells (iPSCs) reprogrammed from somatic cells into cells with most of the ESC (embryonic stem cell) characteristics show promise toward solving ethical problems currently facing stem cell research and eventually yield clinical grade pluripotent stem cells for therapies and regenerative medicine. In recent years, an increasing body of research suggests that the chemical induction of pluripotency (CIP) method can yield iPSCs in vitro, yet its application in avian species remains unreported. Methods: Herein, we successfully obtained stably growing chicken embryonic fibroblasts (CEFs) using the tissue block adherence method and employed 12 small-molecule compounds to induce chicken iPSC formation. Results: The final optimized iPSC induction system was bFGF (10 ng/mL), CHIR99021 (3 μM), RepSox (5 μM), DZNep (0.05 μM), BrdU (10 μM), BMP4 (10 ng/mL), vitamin C (50 μg/mL), EPZ-5676 (5 μM), and VPA (0.1 mM). Optimization of the induction system revealed that the highest number of clones was induced with 8 × 10 4 cells per well and at 1.5 times the original concentration. Upon characterization, these clones exhibited iPSC characteristics, leading to the development of a stable compound combination for iPSC generation in chickens. Concurrently, employing a deletion strategy to investigate the functionality of small-molecule compounds during induction, we identified CHIR99021 and BrdU as critical factors for inducing chicken iPSC formation. Conclusions: In conclusion, this study provides a reference method for utilizing small-molecule combinations in avian species to reprogram cells and establish a network of cell fate determination mechanisms.

Ceramic slurry is the raw material used in stereolithography, and its performance determines the printing quality. Rheological behavior, one of the most important physical factors in stereolithography, is critical in ceramic printing, significantly affecting the flow, spreading, and printing processes. The rheological behavior of SiO 2 slurry used in stereolithography technology is investigated in the current research using different powder diameters and temperatures. The results present the apparent non-Newtonian behavior. The yielding characteristics occur in all cases. For single-powder cases, the viscosity decreases when the powder diameter is increased. When the nano-sized and micro-sized powders are mixed in different proportions, a more significant proportion of micron-sized powders will decrease the viscosity. With an increase in the nano-sized powders, the slurry exhibits the shear thinning behavior; otherwise, the shear thickening behavior is observed. Thus, the prediction model is built based on the use of the pelican optimization algorithm-deep extreme learning machine (POA-DELM), and the model in then compared with the fitted and traditional models to validate the effectiveness of the method. A more accurate viscosity prediction model will contribute to better fluid dynamic simulation in future work.

Mobile Edge Computing (MEC) is crucial for reducing latency by bringing computational resources closer to the network edge, thereby enhancing the quality of services (QoS). However, the broad deployment of cloudlets poses challenges in efficient network slicing, particularly when traffic distribution is uneven. Therefore, these challenges include managing diverse resource requirements across widely distributed cloudlets, minimizing resource conflicts and delays, and maintaining service quality amid fluctuating request rates. Addressing this requires intelligent strategies to predict request types (common or urgent), assess resource needs, and allocate resources efficiently. Emerging technologies like edge computing and 5G with network slicing can handle delay-sensitive IoT requests rapidly, but a robust mechanism for real-time resource and utility optimization remains necessary. To address these challenges, we designed an end-to-end network slicing approach that predicts common and urgent user requests through T distribution. We formulated our problem as a multi-agent Markov decision process (MDP) and introduced a multi-agent soft actor-critic (MAgSAC) algorithm. This algorithm prevents the wastage of scarce resources by intelligently activating and deactivating virtual network function (VNF) instances, thereby balancing the allocation process. Our approach aims to optimize overall utility, balancing trade-offs between revenue, energy consumption costs, and latency. We evaluated our method, MAgSAC, through simulations, comparing it with the following six benchmark schemes: MAA3C, SACT, DDPG, S2Vec, Random, and Greedy. The results demonstrate that our approach, MAgSAC, optimizes utility by 30%, minimizes energy consumption costs by 12.4%, and reduces execution time by 21.7% compared to the closest related multi-agent approach named MAA3C.

Semen cryopreservation results in the differential remodeling of the molecules presented in sperm, and these alterations related to reductions in sperm quality and its physiological function have not been fully understood. Given this, this study aimed to investigate the cryoinjury mechanism of goat sperm by analyzing changes of the metabolic characteristics in sperm during the cryopreservation process. The ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) technique was performed to explore metabolite profiles of fresh sperm (C group), equilibrated sperm (E group), and frozen-thawed sperm (F group). In total, 2570 metabolites in positive mode and 2306 metabolites in negative mode were identified, respectively. After comparative analyses among these three groups, 374 differentially abundant metabolites (DAMs) in C vs. E, 291 DAMs in C vs. F, and 189 DAMs in E vs. F were obtained in the positive mode; concurrently, 530 DAMs in C vs. E, 405 DAMs in C vs. F, and 193 DAMs in E vs. F were obtained in the negative mode, respectively. The DAMs were significantly enriched in various metabolic pathways, including 31 pathways in C vs. E, 25 pathways in C vs. F, and 28 pathways in E vs. F, respectively. Among them, 65 DAMs and 25 significantly enriched pathways across the three comparisons were discovered, which may be tightly associated with sperm characteristics and function. Particularly, the functional terms such as TCA cycle, biosynthesis of unsaturated fatty acids, sphingolipid metabolism, glycine, serine and threonine metabolism, alpha-linolenic acid metabolism, and pyruvate metabolism, as well as associated pivotal metabolites like ceramide, betaine, choline, fumaric acid, L-malic acid and L-lactic acid, were focused on. In conclusion, our research characterizes the composition of metabolites in goat sperm and their alterations induced by the cryopreservation process, offering a critical foundation for further exploring the molecular mechanisms of metabolism influencing the quality and freezing tolerance of goat sperm. Additionally, the impacts of equilibration at low temperature on sperm quality may need more attentions as compared to the freezing and thawing process.

Designing efficient electrode materials is necessary for supercapacitors but remains highly challenging. Herein, cobalt sulfide with crystalline/amorphous heterophase (denoted as Co(Al)S) derived from an Al metal-organic framework was constructed by ion exchange/acid etching and subsequent sulfidation strategy. It was found that rational sulfidation by adjusting the sulfur source concentration to a suitable level was favorable to form a 3D nanosheet-interconnected network architecture with a large specific surface area, which promoted ion/electron transport and charge separation. Benefiting from the features of the unique network structure and heterophase accompanied by aluminum, nitrogen and carbon coordinated in amorphous phase, the optimal Co(Al)S (10) exhibited a high specific capacity (1791.8 C g -1 at 1 A g -1 ), an outstanding rate capability and an excellent cycling stability. Furthermore, the as-assembled Co(Al)S//AC device afforded an energy density of 72.3 Wh kg -1 at a power density of 750 W kg -1 , verifying that the Co(Al)S was a promising material for energy storage devices. The developed scheme is expected to promote the application of MOF-derived electrode materials in electrochemical energy storage and conversion fields.

With the rapid development of the Industrial Internet of Things in rotating machinery, the amount of data sampled by mechanical vibration wireless sensor networks (MvWSNs) has increased significantly, straining bandwidth capacity. Concurrently, the safety requirements for rotating machinery have escalated, necessitating enhanced real-time data processing capabilities. Conventional methods, reliant on experiential approaches, have proven inefficient in meeting these evolving challenges. To this end, a fault detection method for rotating machinery based on mobileNet in MvWSNs is proposed to address these intractable issues. The small and light deep learning model is helpful to realize nearly real-time sensing and fault detection, lightening the communication pressure of MvWSNs. The well-trained deep learning is implanted on the MvWSNs sensor node, an edge computing platform developed via embedded STM32 microcontrollers (STMicroelectronics International NV, Geneva, Switzerland). Data acquisition, data processing, and data classification are all executed on the computing- and energy-constrained sensor node. The experimental results demonstrate that the proposed fault detection method can achieve about 0.99 for the DDS dataset and an accuracy of 0.98 in the MvWSNs sensor node. Furthermore, the final transmission data size is only 0.1% compared to the original data size. It is also a time-saving method that can be accomplished within 135 ms while the raw data will take about 1000 ms to transmit to the monitoring center when there are four sensor nodes in the network. Thus, the proposed edge computing method shows good application prospects in fault detection and control of rotating machinery with high time sensitivity., Competing Interests: The authors declare no conflict of interest.

Physic nut ( Jatropha curcas L.) has attracted extensive attention because of its fast growth, easy reproduction, tolerance to barren conditions, and high oil content of seeds. SWEET (Sugar Will Eventually be Exported Transporter) family genes contribute to regulating the distribution of carbohydrates in plants and have great potential in improving yield and stress tolerance. In this study, we performed a functional analysis of the homology of these genes from physic nut, JcSWEET12 and JcSWEET17a . Subcellular localization indicated that the JcSWEET12 protein is localized on the plasma membrane and the JcSWEET17a protein on the vacuolar membrane. The overexpression of JcSWEET12 (OE12) and JcSWEET17a (OE17a) in Arabidopsis leads to late and early flowering, respectively, compared to the wild-type plants. The transgenic OE12 seedlings, but not OE17a, exhibit increased salt tolerance. In addition, OE12 plants attain greater plant height and greater shoot dry weight than the wild-type plants at maturity. Together, our results indicate that JcSWEET12 and JcSWEET17a play different roles in the regulation of flowering time and salt stress response, providing a novel genetic resource for future improvement in physic nut and other plants.

A talented endophytic Streptomyces sp. PH9030 is derived from the medicinal plant Kadsura coccinea (Lem.) A.C. Smith. The undescribed naphthoquinone naphthgeranine G ( 5 ) and seven previously identified compounds, 6 - 12 , were obtained from Streptomyces sp. PH9030. The structure of 5 was identified by comprehensive examination of its HRESIMS, 1D NMR, 2D NMR and ECD data. The inhibitory activities of all the compounds toward α-glucosidase and their antibacterial properties were investigated. The α-glucosidase inhibitory activities of 5 , 6 , 7 and 9 were reported for the first time, with IC 50 values ranging from 66.4 ± 6.7 to 185.9 ± 0.2 μM, as compared with acarbose (IC 50 = 671.5 ± 0.2 μM). The molecular docking and molecular dynamics analysis of 5 with α-glucosidase further indicated that it may have a good binding ability with α-glucosidase. Both 9 and 12 exhibited moderate antibacterial activity against methicillin-resistant Staphylococcus aureus , with minimum inhibitory concentration (MIC) values of 16 μg/mL. These results indicate that 5 , together with the naphthoquinone scaffold, has the potential to be further developed as a possible inhibitor of α-glucosidase.

The identification of accurate gene insertion sites on chicken sex chromosomes is crucial for advancing sex control breeding materials. In this study, the intergenic region NC_006127.4 on the chicken Z chromosome and the non-repetitive sequence EE0.6 on the W chromosome were selected as potential gene insertion sites. Gene knockout vectors targeting these sites were constructed and transfected into DF-1 cells. T7E1 enzyme cleavage and luciferase reporter enzyme analyses revealed knockout efficiencies of 80.00% (16/20), 75.00% (15/20), and 75.00% (15/20) for the three sgRNAs targeting the EE0.6 site. For the three sgRNAs targeting the NC_006127.4 site, knockout efficiencies were 70.00% (14/20), 60.00% (12/20), and 45.00% (9/20). Gel electrophoresis and high-throughput sequencing were performed to detect potential off-target effects, showing no significant off-target effects for the knockout vectors at the two sites. EdU and CCK-8 proliferation assays revealed no significant difference in cell proliferation activity between the knockout and control groups. These results demonstrate that the EE0.6 and NC_006127.4 sites can serve as gene insertion sites on chicken sex chromosomes for gene editing without affecting normal cell proliferation.

Metro stray currents flowing into transformer-neutral points cause the high neutral DC and a transformer to operate in the DC bias state.Because neutral DC caused by stray current varies with time, the neutral DC value cannot be used as the only characteristic indicator to evaluate the DC bias risk level. Thus, unified characteristic extraction and assessment methods are proposed to evaluate the DC bias risk of a transformer caused by stray current, considering the signals of transformer-neutral DC and vibration. In the characteristic extraction method, the primary characteristics are obtained by comparing the magnitude and frequency distributions of transformer-neutral DC and vibration with and without metro stray current invasion. By analyzing the correlation coefficients, the final characteristics are obtained by clustering the primary characteristics with high correlation. Then, the magnitude and frequency characteristics are extracted and used as indicators to evaluate the DC bias risk. Moreover, to avoid the influence of manual experience on indicator weights, the entropy weight method (EWM) is used to establish the assessment model. Finally, the proposed methods are applied based on the neutral DC and vibration test data of a certain transformer. The results show that the characteristic indicators can be extracted, and the transformer DC bias risk can be evaluated by using the proposed methods.

When using traditional 3D printing equipment to manufacture overhang models, it is often necessary to generate support structures to assist in the printing of parts. The post-processing operation of removing the support structures after printing is time-consuming and wastes material. In order to solve the above problems, a support-free five-degree-of-freedom additive manufacturing (SFAM) method is proposed. Through the homogeneous coordinate transformation matrix, the forward and inverse kinematics equations of the five-degree-of-freedom additive manufacturing device (FAMD) are established, and the joint variables of each axis are solved to realize the five-axis linkage of the additive manufacturing (AM) device. In this research work, initially, the layered curve is obtained through the structural lines of the overhang model, and a continuous path planning of the infill area is performed on it, and further, the part printing experiments are conducted on the FAMD. Compared with the traditional three-axis additive manufacturing (TTAM) method, the SFAM method shortens the printing time by 23.58% and saves printing materials by 33.06%. The experimental results show that the SFAM method realizes the support-free printing of overhang models, which not only improves the accuracy of the parts but also the manufacturing efficiency of the parts.

Craniopharyngioma patients often suffer from a diminished quality of life after surgery, which is usually associated with metabolic disorders and hypothalamic obesity. However, the precise etiology of these conditions remains elusive. To identify the metabolic changes after surgery, we conducted a cross-sectional study using metabolomic and lipidomic analysis to profile metabolic alterations in adult-onset craniopharyngioma patients with postoperative obesity. A cohort of 120 craniopharyngioma patients who had undergone surgery were examined. Differential analyses, including clinical characteristics, serum metabolome, and lipidome, were conducted across distinct body mass index (BMI) groups. Our findings indicated no statistically significant differences in age, sex, and fasting blood glucose among postoperative craniopharyngioma patients when stratified by BMI. However, a noteworthy difference was observed in uric acid and blood lipid levels. Further investigation revealed that alterations in metabolites and lipids were evidently correlated with increased BMI, indicating that postoperative obesity of craniopharyngioma patients affected their whole-body metabolism. Additionally, the multi-omics analysis identified specific metabolites and lipids, including uric acid and DG(18:2/20:4), as contributors to the metabolic disorders associated with postoperative obesity of craniopharyngioma patients. This work provides valuable insight into the involvement of metabolites and lipids in metabolic disorders subsequent to craniopharyngioma surgery.

This paper delves into enhancing the performance of ScAlN-based Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) through the implementation of Polydimethylsiloxane (PDMS) acoustic lenses. The PMUT, encapsulated in PDMS, underwent thorough characterization through the utilization of an industry-standard hydrophone calibration instrument. The experimental results showed that the ScAlN-based PMUT with the PDMS lenses achieved an impressive sensitivity of -160 dB (re: 1 V/μPa), an improvement of more than 8 dB compared to the PMUT with an equivalent PDMS film. There was a noticeable improvement in the -3 dB main lobe width within the frequency response when comparing the PMUT with PDMS encapsulation, both with and without lenses. The successful fabrication of high-performance PDMS lenses proved instrumental in significantly boosting the sensitivity of the PMUT. Comprehensive performance evaluations underscored that the designed PMUT in this investigation surpassed its counterparts reported in the literature and commercially available transducers. This encouraging outcome emphasizes its substantial potential for commercial applications.

Rapid corrosion in aqueous solutions of magnesium alloys is one of the major obstacles to their wide application, and coating plays a crucial role in their corrosion protection. Recently, protection- and function-integrated coatings have attracted much attention in the research field of magnesium alloys. In this work, a simple chemical conversion process is proposed to fabricate a composite coating on a magnesium-neodymium alloy through immersion in an aqueous solution made of Ca(OH) 2 and NaHCO 3 . After the immersion process, a coating consisting of two spontaneously formed layers is acquired. The top flower-like layer is composed of Mg 5 (OH) 2 (CO 3 ) 4 ∙4H 2 O, Mg(OH) 2 and CaCO 3 , and the inner dense layer is speculated to be Mg(OH) 2 . Electrochemical impedance spectroscopy, polarization tests, and hydrogen evolution are combined to evaluate the corrosion resistance in simulated body fluid, simulated seawater solution, and simulated concrete pore solution, which reveals that the coated sample has better corrosion resistance than the uncoated one. After the coated sample is modified with fluorinated silane, a water-repellent surface can be achieved with an average water contact angle of 151.74° and a sliding angle of about 4°. Therefore, our results indicate that effective corrosion protection and potential self-cleaning ability have been integrated on the surface of the magnesium alloy in this study. In addition, the formation mechanism of the self-layered coating is discussed from the viewpoint of the interaction between the substrate and its external solution.

To better assess the practical value and avoid potential risks of the traditionally medicinal and edible basidiomycete Schizophyllum commune , which may arise from undescribed metabolites, a combination of elicitors was introduced for the first time to discover products from cryptic and low-expressed gene clusters under laboratory cultivation. Treating S. commune NJFU21 with the combination of five elicitors led to the upregulated production of a class of unusual linear diterpene-derived variants, including eleven new ones ( 1 - 11 ), along with three known ones ( 12 - 14 ). The structures and stereochemistry were determined by 1D and 2D NMR, HRESIMS, ECD, OR and VCD calculations. Notably, the elongation terminus of all the diterpenes was decorated by an unusual butenedioic acid moiety. Compound 1 was a rare monocyclic diterpene, while 2 - 6 possessed a tetrahydrofuran moiety. The truncated metabolites 4 , 5 and 13 belong to the trinorditerpenes. All the diterpenes displayed approximately 70% scavenging of hydroxyl radicals at 50 μM and null cytotoxic activity at 10 μM. In addition, compound 1 exhibited potent antifungal activity against the plant pathogenic fungi Colletotrichum camelliae , with MIC values of 8 μg/mL. Our findings indicated that this class of diterpenes could provide valuable protectants for cosmetic ingredients and the lead compounds for agricultural fungicide development.

Keratins are the main structural protein components of wool fibres, and variation in them and their genes ( KRTs ) is thought to influence wool structure and characteristics. The PCR-single strand conformation polymorphism technique has been used previously to investigate genetic variation in selected coding and intron regions of the type II sheep keratin gene KRT81 , but no variation was identified. In this study, we used the same technique to explore the 5' untranslated region of KRT81 and detected three sequence variants ( A , B and C ) that contain four single nucleotide polymorphisms. Among the 389 Merino × Southdown cross sheep investigated, variant B was linked to a reduction in clean fleece weight, while C was associated with an increase in both greasy fleece weight and clean fleece weight. No discernible effects on staple length or mean-fibre-diameter-related traits were observed. These findings suggest that variation in ovine KRT81 might influence wool growth by changing the density of wool follicles in the skin, the density of individual fibres, or the area of the skin producing fibre, as opposed to changing the rate of extrusion of fibres or their diameter.

Magnesium hydroxide, as a green inorganic flame-retardancy additive, has been widely used in polymer flame retardancy. However, magnesium hydroxide is difficult to disperse with epoxy resin (EP), and its flame-retardancy performance is poor, so it is difficult to use in flame-retardant epoxy resin. In this study, an efficient magnesium hydroxide-based flame retardant (MH@PPAC) was prepared by surface modification of 2-(diphenyl phosphine) benzoic acid (PPAC) using a simple method. The effect of MH@PPAC on the flame-retardancy properties for epoxy resins was investigated, and the flame-retardancy mechanism was studied. The results show that 5 wt% MH@PPAC can increase the limiting oxygen index for EP from 24.1% to 38.9%, achieving a V-0 rating. At the same time, compared to EP, the peak heat release rate, peak smoke production rate, total smoke production rate, and peak CO generation rate for EP/5 wt% MH@PPAC composite material decreased by 53%, 45%, 51.85%, and 53.13% respectively. The cooperative effect for PPAC and MH promotes the formation of a continuous and dense char layer during the combustion process for the EP-blend material, significantly reducing the exchange for heat and combustible gases, and effectively hindering the combustion process. Additionally, the surface modification of PPAC enhances the dispersion of MH in the EP matrix, endowing EP with superior mechanical properties that meet practical application requirements, thereby expanding the application scope for flame-retardant EP-blend materials.

The production of municipal solid waste incineration bottom ash (MSWIBA) is substantial and has the potential to replace cement, despite challenges such as complex composition, uneven particle size distribution, and low reactivity. This paper employs sodium silicate activation of MSWIBA composite Ground-granulated Blast Furnace slag (GGBS) to improve the reactivity in preparing composite cementitious materials. It explores the hydration performance of the composite cementitious materials using isothermal calorimetric analysis, Fourier-transform infrared (FTIR) spectroscopy, XRD physical diffraction analysis, and SEM tests. SEM tests were used to explore the hydration properties of the composite gelling. The results show that with an increase in MSWIBA doping, the porosity between the materials increased, the degree of hydration decreased, and the compressive strength decreased. When the sodium silicate concentration increased from 25% to 35%, excessive alkaline material occurred, impacting the alkaline effect. This inhibited particle hydration, leading to a decrease in the degree of hydration and, consequently, the compressive strength. The exothermic process of hydration can be divided into five main stages; quartz and calcite did not fully participate in the hydration reaction, while aluminum did. The vibrational peaks of Si-O-Ti (T = Si and Al) were present in the material. The vibrational peaks of XRD, FTIR, and SEM all indicate the presence of alumosilicate network structures in the hydration products, mainly N-A-S-H and C-A-S-H gels.

Background: Neddylation, a post-translational modification process, plays a crucial role in various human neoplasms. However, its connection with kidney renal clear cell carcinoma (KIRC) remains under-researched., Methods: We validated the Gene Set Cancer Analysis Lite (GSCALite) platform against The Cancer Genome Atlas (TCGA) database, analyzing 33 cancer types and their link with 17 neddylation-related genes. This included examining copy number variations (CNVs), single nucleotide variations (SNVs), mRNA expression, cellular pathway involvement, and methylation. Using Gene Set Variation Analysis (GSVA), we categorized these genes into three clusters and examined their impact on KIRC patient prognosis, drug responses, immune infiltration, and oncogenic pathways. Afterward, our objective is to identify genes that exhibit overexpression in KIRC and are associated with an adverse prognosis. After pinpointing the specific target gene, we used the specific inhibitor MLN4924 to inhibit the neddylation pathway to conduct RNA sequencing and related in vitro experiments to verify and study the specificity and potential mechanisms related to the target. This approach is geared towards enhancing our understanding of the prognostic importance of neddylation modification in KIRC., Results: We identified significant CNV, SNV, and methylation events in neddylation-related genes across various cancers, with notably higher expression levels observed in KIRC. Cluster analysis revealed a potential trade-off in the interactions among neddylation-related genes, where both high and low levels of gene expression are linked to adverse prognoses. This association is particularly pronounced concerning lymph node involvement, T stage classification, and Fustat score. Simultaneously, our research discovered that PSMB10 exhibits overexpression in KIRC when compared to normal tissues, negatively impacting patient prognosis. Through RNA sequencing and in vitro assays, we confirmed that the inhibition of neddylation modification could play a role in the regulation of various signaling pathways, thereby influencing the prognosis of KIRC. Moreover, our results underscore PSMB10 as a viable target for therapeutic intervention in KIRC, opening up novel pathways for the development of targeted treatment strategies., Conclusion: This study underscores the regulatory function and potential mechanism of neddylation modification on the phenotype of KIRC, identifying PSMB10 as a key regulatory target with a significant role in influencing the prognosis of KIRC.

In this study, the rolling process of the warm-rolled duplex-phase Mg-8.3Li-3.1Al-1.09Si alloy and the strengthening mechanism of as-rolled Mg-Li alloy were investigated. The highest ultimate tensile strength (UTS, 323.66 ± 19.89 MPa) could be obtained using a three-pass rolling process with a 30% thickness reduction for each pass at 553 K. The strength of the as-rolled LAS831 alloy is determined by a combination of second-phase strengthening, grain refinement strengthening, dislocation strengthening, and load-transfer reinforcement. Of these factors, dislocation strengthening, which is caused by strain hardening of the α-Mg phase, can produce a good strengthening effect but also cause a decrease in plasticity. The Mg 2 Si phase is broken up into particles or strips during the rolling process. After three passes, the AlLi particles were transformed into an AlLi phase, and the Mg 2 Si particles and nanosized AlLi particles strengthened the second phase to form a hard phase. The average size of the DRXed β-Li grains decreased with each successive rolling pass, and the average size of recrystallized grains in the three-pass-rolled LAS831 alloy became as low as 0.27 μm. The interface between the strip-like Mg 2 Si phase and the α-Mg phase is characterized by semicoherent bonding, which can promote the transfer of tensile and shear forces from the matrix to the strip-like Mg 2 Si phase, thereby improving the strength of the matrix and thus strengthening the LAS831 alloy.

In this report, micro-patterned silicon semiconductor photovoltaic cells have been proposed to improve the efficiency in various incident sunlight angles, using homeotropic liquid crystal polymers. The anisotropic liquid crystal precursor solution based on a reactive mesogen has good flowing characteristics. It can be evenly coated on the silicon solar cells' surface by a conventional spreading technique, such as spin coating. Once cured, the polymers exhibit asymmetric transmittance properties. The optical retardation characteristics of the coated polymer films can be eventually determined by the applicable coating and curing parameters during the processes. The birefringence of light then influences the optical path and the divergence of any encountered sunlight. This allows more photons to enter the active semiconductor layers for optical absorption, resulting in an increase in the photon-to-electron conversion, and thus improving the photovoltaic cell efficiency. This new design is straightforward and could allow various patterns to be created for scientific development. The experimental results have evidenced that the energy conversion efficiency could be improved by 2-3% for the silicon photovoltaic cells, under direct sunlight or at no inclination, when the liquid crystal polymer precursor solution is prepared at 5%. In addition, the efficiency could be much more significantly improved to 14-16% when the angle is inclined to 45°. The unique patterned liquid crystal polymer thin films provide enhanced energy conversion efficiency for silicon photovoltaic cells. The design could be further evaluated for other solar cell applications.

This study aims to investigate the effects of different hydroxy-terminated silicones on the properties of polycarbonate-silicone copolymers (ICS-PC) by introducing flexible and hydrophobic silicone into isosorbide-based polycarbonate through melt transesterification- polycondensation method. Through compatibility and transesterification experiments, it is confirmed that the alcohol-hydroxyl polydimethylsiloxane ( a -PDMS) has higher reactivity and silicone conversion than the phenol-hydroxyl polydimethylsiloxane ( p -PDMS), but the conversion does not exceed 81%. Polyether-modified silicone (PEMS) exhibits better compatibility and higher reactivity, thus resulting in higher conversion that can reach 86%. Effects of the type and content of silicone on the glass transition temperature ( T g ), optical transparency, saturated water absorption, and mechanical strength of ICS-PCs were also discussed. It is found that p -PDMS has higher T g , hydrophobicity, and mechanical strength with similar silicone content, but the total transmittance does not exceed 60%. In contrast, the PEMS system exhibits better optical transparency due to its improved compatibility with the PC matrix, with a total transmittance of up to 73%, T g exceeding 150 °C while maintaining excellent flexibility and hydrophobicity. These results are helpful to further improve the comprehensive properties of bio-based polycarbonates.

The tiger nut ( Cyperus esculentus L.) is a usable tuber and edible oil plant. The size of the tubers is a key trait that determines the yield and the mechanical harvesting of tiger nut tubers. However, little is known about the anatomical and molecular mechanisms of tuber expansion in tiger nut plants. This study conducted anatomical and comprehensive transcriptomics analyses of tiger nut tubers at the following days after sowing: 40 d (S1); 50 d (S2); 60 d (S3); 70 d (S4); 90 d (S5); and 110 d (S6). The results showed that, at the initiation stage of a tiger nut tuber (S1), the primary thickening meristem (PTM) surrounded the periphery of the stele and was initially responsible for the proliferation of parenchyma cells of the cortex (before S1) and then the stele (S2-S3). The increase in cell size of the parenchyma cells occurred mainly from S1 to S3 in the cortex and from S3 to S4 in the stele. A total of 12,472 differentially expressed genes (DEGs) were expressed to a greater extent in the S1-S3 phase than in S4-S6 phase. DEGs related to tuber expansion were involved in cell wall modification, vesicle transport, cell membrane components, cell division, the regulation of plant hormone levels, signal transduction, and metabolism. DEGs involved in the biosynthesis and the signaling of indole-3-acetic acid (IAA) and jasmonic acid (JA) were expressed highly in S1-S3. The endogenous changes in IAA and JAs during tuber development showed that the highest concentrations were found at S1 and S1-S3, respectively. In addition, several DEGs were related to brassinosteroid (BR) signaling and the G-protein, MAPK, and ubiquitin-proteasome pathways, suggesting that these signaling pathways have roles in the tuber expansion of tiger nut. Finally, we come to the conclusion that the cortex development preceding stele development in tiger nut tubers. The auxin signaling pathway promotes the division of cortical cells, while the jasmonic acid pathway, brassinosteroid signaling, G-protein pathway, MAPK pathway, and ubiquitin protein pathway regulate cell division and the expansion of the tuber cortex and stele. This finding will facilitate searches for genes that influence tuber expansion and the regulatory networks in developing tubers.

The various wastes generated by silkworm silk textiles that are no longer in use are increasing, which is causing considerable waste and contamination. This issue has attracted widespread attention in countries that use a lot of silk. Therefore, enhancing the mechanical properties of regenerated silk fibroin (RSF) and enriching the function of silk are important directions to expand the comprehensive utilization of silk products. In this paper, the preparation of RSF/Al 2 O 3 nanoparticles (NPs) hybrid fiber with different Al 2 O 3 NPs contents by wet spinning and its novel performance are reported. It was found that the RSF/Al 2 O 3 NPs hybrid fiber was a multifunctional fiber material with thermal insulation and UV resistance. Natural light tests showed that the temperature rise rate of RSF/Al 2 O 3 NPs hybrid fibers was slower than that of RSF fibers, and the average temperature rose from 29.1 °C to about 35.4 °C in 15 min, while RSF fibers could rise to about 40.1 °C. UV absorption tests showed that the hybrid fiber was resistant to UV radiation. Furthermore, the addition of Al 2 O 3 NPs may improve the mechanical properties of the hybrid fibers. This was because the blending of Al 2 O 3 NPs promoted the self-assembly of β-sheets in the RSF reaction mixture in a dose-dependent manner, which was manifested as the RSF/Al 2 O 3 NPs hybrid fibers had more β-sheets, crystallinity, and a smaller crystal size. In addition, RSF/Al 2 O 3 NPs hybrid fibers had good biocompatibility and durability in micro-alkaline sweat environments. The above performance makes the RSF/Al 2 O 3 NPs hybrid fibers promising candidates for application in heat-insulating and UV-resistant fabrics as well as military clothing.

In the last twenty years, three deadly zoonotic coronaviruses (CoVs)-namely, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2-have emerged. They are considered highly pathogenic for humans, particularly SARS-CoV-2, which caused the 2019 CoV disease pandemic (COVID-19), endangering the lives and health of people globally and causing unpredictable economic losses. Experiments on wild-type viruses require biosafety level 3 or 4 laboratories (BSL-3 or BSL-4), which significantly hinders basic virological research. Therefore, the development of various biosafe CoV systems without virulence is urgently needed to meet the requirements of different research fields, such as antiviral and vaccine evaluation. This review aimed to comprehensively summarize the biosafety of CoV engineering systems. These systems combine virological foundations with synthetic genomics techniques, enabling the development of efficient tools for attenuated or non-virulent vaccines, the screening of antiviral drugs, and the investigation of the pathogenic mechanisms of novel microorganisms.

Partial discharge detection is considered a crucial technique for evaluating insulation performance and identifying defect types in cable terminals of high-speed electric multiple units (EMUs). In this study, terminal samples exhibiting four typical defects were prepared from high-speed EMUs. A cable discharge testing system, utilizing high-frequency current sensing, was developed to collect discharge signals, and datasets corresponding to these defects were established. This study proposes the use of the convolutional neural network (CNN) for the classification of discharge signals associated with specific defects, comparing this method with two existing neural network (NN)-based classification models that employ the back-propagation NN and the radial basis function NN, respectively. The comparative results demonstrate that the CNN-based model excels in accurately identifying signals from various defect types in the cable terminals of high-speed EMUs, surpassing the two existing NN-based classification models.

Two α-pyrone analogs were isolated from the endophytic fungus Diaporthe sp. CB10100, which is derived from the medicinal plant Sinomenium acutum . These analogs included a new compound, diaporpyrone F ( 3 ), and a known compound, diaporpyrone D ( 4 ). The structure of 3 was identified by a comprehensive examination of HRESIMS, 1D and 2D NMR spectroscopic data. Bioinformatics analysis revealed that biosynthetic gene clusters for α-pyrone analogs are common in fungi of Diaporthe species. The in vitro α-glucosidase inhibitory activity and antibacterial assay of 4 revealed that it has a 46.40% inhibitory effect on α-glucosidase at 800 μM, while no antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA), Mycolicibacterium ( Mycobacterium ) smegmatis or Klebsiella pneumoniae at 64 μg/mL. Molecular docking and molecular dynamics simulations of 4 with α-glucosidase further suggested that the compounds are potential α-glucosidase inhibitors. Therefore, α-pyrone analogs can be used as lead compounds for α-glucosidase inhibitors in more in-depth studies.

With the rapid development of 3D reconstruction, especially the emergence of algorithms such as NeRF and 3DGS, 3D reconstruction has become a popular research topic in recent years. 3D reconstruction technology provides crucial support for training extensive computer vision models and advancing the development of general artificial intelligence. With the development of deep learning and GPU technology, the demand for high-precision and high-efficiency 3D reconstruction information is increasing, especially in the fields of unmanned systems, human-computer interaction, virtual reality, and medicine. The rapid development of 3D reconstruction is becoming inevitable. This survey categorizes the various methods and technologies used in 3D reconstruction. It explores and classifies them based on three aspects: traditional static, dynamic, and machine learning. Furthermore, it compares and discusses these methods. At the end of the survey, which includes a detailed analysis of the trends and challenges in 3D reconstruction development, we aim to provide a comprehensive introduction for individuals who are currently engaged in or planning to conduct research on 3D reconstruction. Our goal is to help them gain a comprehensive understanding of the relevant knowledge related to 3D reconstruction.

Tomato brown rugose fruit virus (ToBRFV) is a newly-emerging tobamovirus which was first reported on tomatoes in Israel and Jordan, and which has now spread rapidly in Asia, Europe, North America, and Africa. ToBRFV can overcome the resistance to other tobamoviruses conferred by tomato Tm-1 , Tm-2 , and Tm-2 2 genes, and it has seriously affected global crop production. The rapid and comprehensive transcription reprogramming of host plant cells is the key to resisting virus attack, but there have been no studies of the transcriptome changes induced by ToBRFV in tomatoes. Here, we made a comparative transcriptome analysis between tomato leaves infected with ToBRFV for 21 days and those mock-inoculated as controls. A total of 522 differentially expressed genes were identified after ToBRFV infection, of which 270 were up-regulated and 252 were down-regulated. Functional analysis showed that DEGs were involved in biological processes such as response to wounding, response to stress, protein folding, and defense response. Ten DEGs were selected and verified by qRT-PCR, confirming the reliability of the high-throughput sequencing data. These results provide candidate genes or signal pathways for the response of tomato leaves to ToBRFV infection.

Members of the abscisic acid (ABA)-responsive element (ABRE) binding factor (ABF) and ABA-responsive element binding protein (AREB) families play essential roles in the regulation of ABA signaling pathway activity and shape the ability of plants to adapt to a range of stressful environmental conditions. To date, however, systematic genome-wide analyses focused on the ABF/AREB gene family in wheat are lacking. Here, we identified 35 ABF/AREB genes in the wheat genome, designated TaABF1 - TaABF35 according to their chromosomal distribution. These genes were further classified, based on their phylogenetic relationships, into three groups (A-C), with the TaABF genes in a given group exhibiting similar motifs and similar numbers of introns/exons. Cis-element analyses of the promoter regions upstream of these TaABFs revealed large numbers of ABREs, with the other predominant elements that were identified differing across these three groups. Patterns of TaABF gene expansion were primarily characterized by allopolyploidization and fragment duplication, with purifying selection having played a significant role in the evolution of this gene family. Further expression profiling indicated that the majority of the TaABF genes from groups A and B were highly expressed in various tissues and upregulated following abiotic stress exposure such as drought, low temperature, low nitrogen, etc., while some of the TaABF genes in group C were specifically expressed in grain tissues. Regulatory network analyses revealed that four of the group A TaABF s ( TaABF2 , TaABF7 , TaABF13 , and TaABF19 ) were centrally located in protein-protein interaction networks, with 13 of these TaABF genes being regulated by 11 known miRNAs, which play important roles in abiotic stress resistance such as drought and salt stress. The two primary upstream transcription factor types found to regulate TaABF gene expression were BBR/BPC and ERF, which have previously been reported to be important in the context of plant abiotic stress responses. Together, these results offer insight into the role that the ABF/AREB genes play in the responses of wheat to abiotic stressors, providing a robust foundation for future functional studies of these genes.

Fenugreek (Trigonella foenum-graecum L.) is a traditional medicinal plant for treating human diseases that is widely cultivated in many countries. However, the component and related metabolic pathways are still unclear. To understand the changes in expression of the component and related genes during seed development, this study employed metabolomic and transcriptomic analyses and integrative analysis to explore the metabolites and pathways involved in the growth of fenugreek. The antifungal activity of the fenugreek seeds was also analyzed. A total of 9499 metabolites were identified in the positive ion mode, and 8043 metabolites were identified in the negative ion mode. Among them, the main components were fatty acyls, prenol lipids, steroids, steroid derivatives, flavonoids, and isoflavonoids. Among these enriched pathways, the top 20 pathways were "flavone and flavonol biosynthesis", "isoflavonoid biosynthesis", and "flavonoid biosynthesis". 3,7-Di-O-methylquercetin, flavonoids, pseudobaptigenin, isoflavonoids, methylecgonine, alkaloids, and derivatives were the most significantly upregulated metabolites. There were 38,137 differentially expressed genes (DEGs) identified via transcriptomic analysis. According to the KEGG pathway enrichment analysis, 147 DEGs were significantly enriched in "flavonoid biosynthesis". Ten DEGs of the six key enzymes were found to be involved in three pathways related to flavonoid and alkaloid synthesis in fenugreek. The antifungal activity test revealed the inhibitory effect of the ethanol extract of fenugreek seeds on Alternaria tenuissima (Kunze)Wiltshire and Magnaporthe oryzae . These findings further prove that the use of botanical pesticides in fenugreek fruit has research value.

Bi-based YbMg 2 Bi 1.98 Zintl compounds represent promising thermoelectric materials. Precise composition and appropriate doping are of great importance for this complex semiconductor. Here, the influence of Zn substitution for Mg on the microstructure and thermoelectric properties of p -type YbMg 1.85- x Zn x Bi 1.98 ( x = 0, 0.05, 0.08, 0.13, 0.23) was investigated. Polycrystalline samples were prepared using induction melting and densified with spark plasma sintering. X-ray diffraction confirmed that the major phase of the samples possesses the trigonal CaAl 2 Si 2 -type crystal structure, and SEM/EDS indicated the presence of minor secondary phases. The electrical conductivity increases and the lattice thermal conductivity decreases with more Zn doping in YbMg 1.85- x Zn x Bi 1.98 , whereas the Seebeck coefficient has a large reduction. The band gap decreases with increasing Zn concentration and leads to bipolar conduction, resulting in an increase in the thermal conductivity at higher temperatures. Figure of merit ZT values of 0.51 and 0.49 were found for the samples with x = 0 and 0.05 at 773 K, respectively. The maximum amount of Zn doping is suggested to be less than x = 0.1.

Medium- and long-chain triacylglycerol (MLCT), as a novel functional lipid, is valuable due to its special nutritional properties. Its low content in natural resources and inefficient synthesis during preparation have limited its practical applications. In this study, we developed an effective Pickering emulsion interfacial catalysis system (PE system) for the enzymatic synthesis of MLCT by trans-esterification. Lipase NS 40086 served simultaneously as a catalyst and a solid emulsifier to stabilize the Pickering emulsion. Benefitting from the sufficient oil-water interface, the obtained PE system exhibited outstanding catalytic efficiency, achieving 77.5% of MLCT content within 30 min, 26% higher than that of a water-free system. The K m value (0.259 mM) and activation energy (14.45 kJ mol - 1 ) were 6.8-fold and 1.6-fold lower than those of the water-free system, respectively. The kinetic parameters as well as the molecular dynamics simulation and the tunnel analysis implied that the oil-water interface enhanced the binding between substrate and lipase and thus boosted catalytic efficiency. The conformational changes in the lipase were further explored by FT-IR. This method could give a novel strategy for enhancing lipase activity and the design of efficient catalytic systems to produce added-value lipids. This work will open a new methodology for the enzymatic synthesis of structured lipids.

Multi-view stereo methods utilize image sequences from different views to generate a 3D point cloud model of the scene. However, existing approaches often overlook coarse-stage features, impacting the final reconstruction accuracy. Moreover, using a fixed range for all the pixels during inverse depth sampling can adversely affect depth estimation. To address these challenges, we present a novel learning-based multi-view stereo method incorporating attention mechanisms and an adaptive depth sampling strategy. Firstly, we propose a lightweight, coarse-feature-enhanced feature pyramid network in the feature extraction stage, augmented by a coarse-feature-enhanced module. This module integrates features with channel and spatial attention, enriching the contextual features that are crucial for the initial depth estimation. Secondly, we introduce a novel patch-uncertainty-based depth sampling strategy for depth refinement, dynamically configuring depth sampling ranges within the GRU-based optimization process. Furthermore, we incorporate an edge detection operator to extract edge features from the reference image's feature map. These edge features are additionally integrated into the iterative cost volume construction, enhancing the reconstruction accuracy. Lastly, our method is rigorously evaluated on the DTU and Tanks and Temples benchmark datasets, revealing its low GPU memory consumption and competitive reconstruction quality compared to other learning-based MVS methods.

In crowded fluids, polymer segments can exhibit anomalous subdiffusion due to the viscoelasticity of the surrounding environment. Previous single-particle tracking experiments revealed that such anomalous diffusion in complex fluids (e.g., in bacterial cytoplasm) can be described by fractional Brownian motion (fBm). To investigate how the viscoelastic media affects the diffusive behaviors of polymer segments without resolving single crowders, we developed a novel fractional Brownian dynamics method to simulate the dynamics of polymers under confinement. In this work, instead of using Gaussian random numbers ("white Gaussian noise") to model the Brownian force as in the standard Brownian dynamics simulations, we introduce fractional Gaussian noise (fGn) in our homemade fractional Brownian dynamics simulation code to investigate the anomalous diffusion of polymer segments by using a simple "bottle-brush"-type polymer model. The experimental results of the velocity autocorrelation function and the exponent that characterizes the subdiffusion of the confined polymer segments can be reproduced by this simple polymer model in combination with fractional Gaussian noise (fGn), which mimics the viscoelastic media.

Tube-like outgrowths from root epidermal cells, known as root hairs, enhance water and nutrient absorption, facilitate microbial interactions, and contribute to plant anchorage by expanding the root surface area. Genetically regulated and strongly influenced by environmental conditions, longer root hairs generally enhance water and nutrient absorption, correlating with increased stress resistance. Wheat, a globally predominant crop pivotal for human nutrition, necessitates the identification of long root hair genotypes and their regulatory genes to enhance nutrient capture and yield potential. This study focused on 261 wheat samples of diverse genotypes during germination, revealing noticeable disparities in the length of the root hair among the genotypes. Notably, two long root hair genotypes (W106 and W136) and two short root hair genotypes (W90 and W100) were identified. Transcriptome sequencing resulted in the development of 12 root cDNA libraries, unveiling 1180 shared differentially expressed genes (DEGs). Further analyses, including GO function annotation, KEGG enrichment, MapMan metabolic pathway analysis, and protein-protein interaction (PPI) network prediction, underscored the upregulation of root hair length regulatory genes in the long root hair genotypes. These included genes are associated with GA and BA hormone signaling pathways, FRS/FRF and bHLH transcription factors, phenylpropanoid, lignin, lignan secondary metabolic pathways, the peroxidase gene for maintaining ROS steady state, and the ankyrin gene with diverse biological functions. This study contributes valuable insights into modulating the length of wheat root hair and identifies candidate genes for the genetic improvement of wheat root traits.

A polysaccharide from Artocarpus heterophyllus Lam. (jackfruit) pulp (JFP-Ps) is known for its excellent bioactivities. However, its impact on small intestinal barrier function is still largely unexplored. The study aimed to examine the protection effect of JFP-Ps against dextran sodium sulfate-induced enteritis and its underlying mechanism. This research revealed that JFP-Ps mitigated small intestinal tissue damage by reducing the expression of pro-inflammatory cytokines and promoting the expression of the anti-inflammatory cytokine interleukin-10 in the small intestine. JFP-Ps diminished oxidative stress by bolstering the activity of antioxidant enzymes and reducing the concentration of malondialdehyde in the small intestine. In addition, JFP-Ps may restore the mechanical barrier and inhibit intestinal structure damage by augmenting the expression of short-chain fatty acids (SCFAs) receptors (GPR41/43) and up-regulating the expression of tight junction proteins (occludin). In conclusion, JFP-Ps may positively influence intestinal health by relieving oxidative stress in the small intestine, improving mechanical barrier function, activating the SCFA-GPR41/GPR43 axis, and inhibiting TLR4/MAPK pathway activation. The results augment our comprehension of the bioactivities of JFP-Ps, corroborating its great potential as a functional food.

In natural kaolinite lattices, Al3+ can potentially be substituted by cations such as Mg2+, Ca2+, and Fe3+, thereby influencing its adsorption characteristics towards rare earth elements like Sc3+. Density functional theory (DFT) has emerged as a crucial tool in the study of adsorption phenomena, particularly for understanding the complex interactions of rare earth elements with clay minerals. This study employed DFT to investigate the impact of these three dopant elements on the adsorption of hydrated Sc3+ on the kaolinite (001) Al-OH surface. We discerned that the optimal adsorption configuration for hydrated Sc3+ is Sc(H2O)83+, with a preference for adsorption at the deprotonated O u sites. Among the dopants, Mg doping exhibited superior stability with a binding energy of -4.311 eV and the most negative adsorption energy of -1104.16 kJ/mol. Both Mg and Ca doping enhanced the covalency of the Al-O bond, leading to a subtle shift in the overall density of states towards higher energies, thereby augmenting the reactivity of the O atoms. In contrast, Fe doping caused a pronounced shift in the density of states towards lower energies. Compared to the undoped kaolinite, Mg and Ca doping further diminished the adsorption energy of hydrated Sc3+ and increased its coordination number, while Fe doping elevated the adsorption energy. This study offers profound insights into understanding the role of dopant elements in the adsorption of hydrated Sc3+ on kaolinite.

The emerging field of flexible tactile sensing systems, equipped with multi-physical tactile sensing capabilities, holds vast potential across diverse domains such as medical monitoring, robotics, and human-computer interaction. In response to the prevailing challenges associated with the limited integration and sensitivity of flexible tactile sensors, this paper introduces a versatile tactile sensing system capable of concurrently monitoring temperature and pressure. The temperature sensor employs carbon nanotube/graphene conductive paste as its sensitive material, while the pressure sensor integrates an ionic gel containing boron nitride as its sensitive layer. Through the application of cost-effective screen printing technology, we have successfully manufactured a flexible dual-mode sensor with exceptional performance, featuring high sensitivity (804.27 kPa-1), a broad response range (50 kPa), rapid response time (17 ms), and relaxation time (34 ms), alongside exceptional durability over 5000 cycles. Furthermore, the resistance temperature coefficient of the sensor within the temperature range of 12.5 °C to 93.7 °C is -0.17% °C -1 . The designed flexible dual-mode tactile sensing system enables the real-time detection of pressure and temperature information, presenting an innovative approach to electronic skin with multi-physical tactile sensing capabilities.