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By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time–domain Gaussian fitting method is proposed in this paper. The concept of a time–domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time–domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time–domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms. [ABSTRACT FROM AUTHOR]

The rapid development of mobile communication technologies and Internet of Things (IoT) devices has introduced new challenges for multi-access edge computing (MEC). A key issue is how to efficiently manage MEC resources and determine the optimal offloading strategy between edge servers and user devices, while also protecting user privacy and thereby improving the Quality of Service (QoS). To address this issue, this paper investigates a privacy-preserving computation offloading scheme, designed to maximize QoS by comprehensively considering privacy protection, delay, energy consumption, and the task discard rate of user devices. We first formalize the privacy issue by introducing the concept of privacy entropy. Then, based on quantified indicators, a multi-objective optimization problem is established. To find an optimal solution to this problem, this paper proposes a computation offloading algorithm based on the Twin delayed deep deterministic policy gradient (TD3-SN-PER), which integrates clipped double-Q learning, prioritized experience replay, and state normalization techniques. Finally, the proposed method is evaluated through simulation analysis. The experimental results demonstrate that our approach can effectively balance multiple performance metrics to achieve optimal QoS. [ABSTRACT FROM AUTHOR]

Co-based catalysts have shown great promise for propane dehydrogenation (PDH) reactions due to their merits of environmental friendliness and low cost. In this study, ordered mesoporous molecular sieve-supported CoOx species (CoOx/Al-SBA-15 catalyst) were prepared by one-step organometallic complexation. The catalysts show worm-like morphology with regular straight-through mesoporous pores and high external specific surface area. These typical features can substantially enhance the dispersion of CoOx species and mass transfer of reactants and products. Compared with the conventional impregnation method, the 10CSOC (10 wt.% Co/Al-SBA-15 prepared by the organometallic complexation method) sample presents a smaller CoOx size and higher Co2+/Co3+ ratio. When applied to PDH reaction, the 10CSOC delivers higher propane conversion and propylene selectivity. Under the optimal conditions (625 °C and 4500 h−1), 10CSOC achieves high propane conversion (43%) and propylene selectivity (83%). This is attributed to the smaller and better dispersion of CoOx nanoparticles, more suitable acid properties, and higher content of Co2+ species. This work paves the way for the rational design of high-performance catalysts for industrially important reactions. [ABSTRACT FROM AUTHOR]

With the continuous advancement of the economy and technology, the number of cars continues to increase, and the traffic congestion problem on some key roads is becoming increasingly serious. This paper proposes a new vehicle information feature map (VIFM) method and a multi-branch convolutional neural network (MBCNN) model and applies it to the problem of traffic congestion detection based on camera image data. The aim of this study is to build a deep learning model with traffic images as input and congestion detection results as output. It aims to provide a new method for automatic detection of traffic congestion. The deep learning-based method in this article can effectively utilize the existing massive camera network in the transportation system without requiring too much investment in hardware. This study first uses an object detection model to identify vehicles in images. Then, a method for extracting a VIFM is proposed. Finally, a traffic congestion detection model based on MBCNN is constructed. This paper verifies the application effect of this method in the Chinese City Traffic Image Database (CCTRIB). Compared to other convolutional neural networks, other deep learning models, and baseline models, the method proposed in this paper yields superior results. The method in this article obtained an F1 score of 98.61% and an accuracy of 98.62%. Experimental results show that this method effectively solves the problem of traffic congestion detection and provides a powerful tool for traffic management. [ABSTRACT FROM AUTHOR]

Aqueous zinc−ion batteries (ZIBs) are widely recognized as highly promising energy storage devices because of their inherent characteristics, including superior safety, affordability, eco−friendliness, and various other benefits. However, the significant corrosion of the zinc metal anode, side reactions occurring between the anode and electrolyte, and the formation of zinc dendrites significantly hinder the practical utilization of ZIBs. Herein, we utilized an electrodeposition method to apply a unique hydrous molybdenum oxide (HMoOx) layer onto the surface of the zinc metal anode, aiming to mitigate its corrosion and side reactions during the process of zinc deposition and stripping. In addition, the HMoOx layer not only improved the hydrophilicity of the zinc anode, but also adjusted the migration of Zn2+, thus facilitating the uniform deposition of Zn2+ to reduce dendrite formation. A symmetrical cell with the HMoOx−Zn anode displayed reduced−voltage hysteresis (80 mV at 2.5 mA/cm2) and outstanding cycle stability after 3000 cycles, surpassing the performance of the uncoated Zn anode. Moreover, the HMoOx−Zn anode coupled with a γ−MnO2 cathode created a considerably more stable rechargeable full battery compared to the bare Zn anode. The HMoOx−Zn||γ−MnO2 full cell also displayed excellent cycling stability with a charge/discharge−specific capacity of 129/133 mAh g−1 after 300 cycles. In summary, this research offers a straightforward and advantageous approach that can significantly contribute to the future advancements in rechargeable ZIBs. [ABSTRACT FROM AUTHOR]

This study investigated the impact of different preheat treatments on the emulsifying and gel textural properties of soy protein with varying 11S/7S ratios. A mixture of 7S and 11S globulins, obtained from defatted soybean meal, was prepared at different ratios. The mixed proteins were subjected to preheating (75 °C, 85 °C, and 95 °C for 5 min) or non-preheating, followed by spray drying or non-spray drying. The solubility of protein mixtures rich in the 7S fraction tended to decrease significantly after heating at 85 °C, while protein mixtures rich in the 11S fraction showed a significant decrease after heating at 95 °C. Surprisingly, the emulsion stability index (ESI) of protein mixtures rich in the 7S fraction significantly improved twofold during processing at 75 °C. This study revealed a negative correlation between the emulsifying ability of soy protein and the 11S/7S ratio. For protein mixtures rich in either the 7S or the 11S fractions, gelling proprieties as well as emulsion activity index (EAI) and ESI showed no significant changes after spray drying; however, surface hydrophobicity was significantly enhanced following heating at 85 °C post-spray drying treatment. These findings provide insights into the alterations in gelling and emulsifying properties during various heating processes, offering great potential for producing soy protein ingredients with enhanced emulsifying ability and gelling property. They also contribute to establishing a theoretical basis for the standardized production of soy protein isolate with specific functional characteristics. [ABSTRACT FROM AUTHOR]

Background: Although several epidemiological studies have identified an inverse association between healthy dietary patterns and metabolic dysfunction-associated steatotic liver disease (MASLD)/non-alcoholic fatty liver disease (NAFLD), little is known about the contribution of the food component to MASLD risk and the association between dietary patterns and severity of MASLD. This study aimed to investigate the association between healthy eating patterns and MASLD risk and severity of MASLD. Methods: A case–control study including 228 patients diagnosed with MASLD and 228 controls was conducted. The modified Alternate Healthy Eating Index (AHEI), Dietary Approaches to Stop Hypertension (DASH) score, and Alternative Mediterranean Diet (AMED) score were evaluated based on information collected via a validated food-frequency questionnaire. MASLD was confirmed if participants presented with ultrasound-diagnosed fatty liver diseases along with at least one of five cardiometabolic risk factors and no other discernible cause. The logistic regression models were applied to estimate the odds ratio (OR) and 95% confidence interval (95% CI) of MASLD for dietary scores. Results: Compared with participants in the lowest tertile, those in the highest tertile of AHEI had a 60% reduced risk of MASLD (OR: 0.40; 95% CI: 0.25–0.66). Similar associations were also observed for DASH and AMED, with ORs comparing extreme tertiles of 0.38 (95% CI: 0.22–0.66) and 0.46 (95% CI: 0.28–0.73), respectively. Further Stratified analysis revealed that the inverse associations between AHEI and DASH with MASLD risks were stronger among women than men, and the inverse associations between AMED and MASLD risks were more pronounced among participants with normal weight (OR: 0.22; 95% CI: 0.09–0.49). For components within the dietary score, every one-point increase in vegetable score and whole grain score within the AHEI was associated with an 11% (95% CI: 5–16%) and a 6% (95% CI: 0–12%) lower MASLD risk, respectively. Similar inverse associations with those scores were observed for the DASH and AMED. Conclusion: Greater adherence to healthy eating patterns was associated with reduced risk of MASLD, with vegetables and whole grains predominately contributing to these associations. These findings suggested that healthy eating patterns should be recommended for the prevention of MASLD. [ABSTRACT FROM AUTHOR]

Plants photoreceptors perceive changes in light quality and intensity and thereby regulate plant vegetative growth and reproductive development. By screening a γ irradiation-induced mutant library of the soybean (Glycine max) cultivar "Dongsheng 7", we identified Gmeny, a mutant with elongated nodes, yellowed leaves, decreased chlorophyll contents, altered photosynthetic performance, and early maturation. An analysis of bulked DNA and RNA data sampled from a population segregating for Gmeny, using the BVF-IGV pipeline established in our laboratory, identified a 10 bp deletion in the first exon of the candidate gene Glyma.02G304700. The causative mutation was verified by a variation analysis of over 500 genes in the candidate gene region and an association analysis, performed using two populations segregating for Gmeny. Glyma.02G304700 (GmHY2a) is a homolog of AtHY2a in Arabidopsis thaliana, which encodes a PΦB synthase involved in the biosynthesis of phytochrome. A transcriptome analysis of Gmeny using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed changes in multiple functional pathways, including photosynthesis, gibberellic acid (GA) signaling, and flowering time, which may explain the observed mutant phenotypes. Further studies on the function of GmHY2a and its homologs will help us to understand its profound regulatory effects on photosynthesis, photomorphogenesis, and flowering time. [ABSTRACT FROM AUTHOR]

Uncovering the trade-offs and synergy relationship of multiple ecosystem services (ESs) is important for scientific ecosystem management and the improvement of ecological service functions. In this study, we investigated the spatiotemporal changes of four typical ES types (i.e., water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ)) from 2001 to 2020 in the Han River Basin (HRB). Meanwhile, the trade-offs and synergies between paired ESs and the socioecological drivers of these ESs were further explored. The results showed that grassland, cropland, and bare land decreased by 12,141.3 km2, 624.09 km2, and 22.1 km2 during the study period, respectively, which can be attributed to their conversion to forests in the HRB. Temporally, the WY, CS, and SC all showed a continuously increasing trend. Spatially, WY and HQ exhibited bipolar clustering characteristics, with WY exhibiting low-value clustering in the upstream and high-value clustering in the downstream, while CS showed the clustering characteristics of a scattered distribution of cold and hot spots from 2001 to 2020. The spatial patterns of aggregation locations in CS and HQ were relatively similar, with clusters of higher ES values mainly distributed in the western and central regions and clusters of lower ES values mainly located in the eastern and southeastern regions, while the aggregation of WY was spatially concentrated. Overall, the CS showed a significant positive correlation with HQ, but a significant negative correlation with WY. Spatially, WY and HQ, CS, and SC showed a substantial trade-off relationship in the northwest and southeast parts of the study area, while HQ, CS, and SC mainly exhibited a synergistic relationship in most parts of the study area. Slope and temperature had high influencing factor coefficients on multiple ESs; the mixed effect of terrain and natural factors was significantly greater than the impact of a single factor on ESs, and terrain factors played an essential role in the changes in ESs. The findings can provide technical and theoretical support for integrated scientific ecosystem management and sustainable development at the local scale. [ABSTRACT FROM AUTHOR]

Binary transition metal selenides (BTMSs) are more promising than single transition metal selenides (TMS) as anode materials of sodium-ion batteries (SIBs). However, it is still very challenging to prepare high-performance BTMSs in the pure phase, instead of a mixture of two TMSs. In this study, a binary metal center-based MOF derived selenization strategy was developed to prepare iron–cobalt selenide (Fe2CoSe4@NC) and iron–nickel selenide (Fe2NiSe4@NC) nanocomposites in the single phase and when wrapped with carbon layers. As the anode material of SIBs, Fe2CoSe4@NC exhibits higher long-term cycling performance than Fe2NiSe4@NC, maintaining a capacity of 352 mAh g−1 after 2100 cycles at 1.0 A g−1, which is ascribed to the higher percentage of the nanopores, larger lattice spacing, and faster Na+ diffusion rate in the electrode materials of the former rather than the latter. [ABSTRACT FROM AUTHOR]

This study subjected nuclear-grade 20# pipeline steel to cyclic freeze–thaw ice plugging tests, simulating the plastic deformation experienced by pipes during ice plug removal procedures. Subsequently, the dislocation morphology and mechanical properties of the specimens post cyclic ice plugging were examined. The cyclic ice plugging process led to an increase in the dislocation density within the specimens. After 20 and 40 cycles of ice plugging, the internal dislocation structures evolved from individual dislocation lines and dislocation tangles to high-density dislocation walls and dislocation cells. These high-density dislocation walls and cells hindered dislocation motion, giving rise to strain hardening phenomena, thereby resulting in increased strength and hardness of the specimens with an increasing number of ice plugging cycles. In addition, a large stress field was generated around the dislocation buildup, which reduced the pipe material's plastic toughness. The findings elucidate the effects of cyclic ice plugging on the microstructure and properties of nuclear-grade 20# pipeline steel, aiming to provide a theoretical basis for the safe and stable application of ice plugging technology in nuclear piping systems. [ABSTRACT FROM AUTHOR]

The detection of the amount of aflatoxin M1 (AFM1) in milk is crucial for food safety. Here, we utilize a fiber optic (FO) localized surface plasmon resonance (LSPR) biosensor by constructing gold nanoparticle (AuNP) multimers, in which the nanogaps amplified the LSPR signal by the hot spot effect, and achieved a highly sensitive detection of f AFM1. Through the optimization of parameter conditions for the fabrication of the sensor and detection system, a high performance result from the FO LSPR biosensor was obtained, and the method for AFM1 detection was established, with a wide detection range of 0.05–100 ng/mL and a low limit of detection (LOD) of 0.04 ng/mL, and it has been successfully validated with the actual sample milk. Therefore, it is a good strategy to fabricate highly sensitive FO LSPR sensors for detecting AFM1 by constructing AuNP multimers, and this approach is suitable for developing other biosensors. [ABSTRACT FROM AUTHOR]

To accurately evaluate the skidding resistance of asphalt pavements, a texture imaging device was developed to realize the standardized acquisition of pavement images. Based on the gray-level co-occurrence matrix and multifractal theory of texture structure, the influence of segregation degree and gradation type on the texture properties of asphalt pavement was studied. Meanwhile, a comprehensive evaluation index of skidding resistance was proposed for asphalt pavement. Furthermore, the attenuation characteristics of the anti-skidding performance for asphalt mixture were explored, and the corresponding attenuation model of asphalt pavement was established. The results show that the segregation degree and gradation type significantly affected the texture parameters and anti-skidding performance of asphalt mixture. Specially, with an increase in the segregation degree of coarse aggregate, the parameters of energy, entropy, and multifractal spectrum width gradually increased, whereas the inertial moment gradually decreased. The variation range of the multifractal spectrum difference initially increased and subsequently decreased. For the texture parameters such as energy, entropy, inertial moment, and multifractal spectrum width Δα, the values of the asphalt mixture with larger nominal maximum particle were higher than those of the mixture with smaller nominal maximum particle, whereas the multifractal spectrum difference value showed the opposite law. In addition, the texture parameters of energy, entropy, and multifractal spectrum width exhibited good linear correlation with the texture depth (TD) of asphalt mixtures with various segregation levels and gradation types. The index based on the texture parameters of energy, entropy, and multifractal spectrum width effectively evaluated the skidding resistance of asphalt pavements, which showed the same trend as the TD with the increase of the abrasion number. The achievement provides an effective solution for the evaluation of skidding resistance and attenuation characteristics of asphalt mixtures. [ABSTRACT FROM AUTHOR]

Radical reactions are powerful in the synthesis of diverse molecular scaffolds bearing functional groups. In previous review articles, we have presented 1,2-difunctionalizations, remote 1,3-, 1,4-, 1,5-, 1,6- and 1,7-difunctionalizations, and addition followed by cyclization reactions. Presented in this paper is radical cyclization followed by the second functionalization reaction. The second functionalization could be realized by atom transfer reactions, radical or transition metal-assisted coupling reactions, and reactions with neutral molecules, cationic and anionic species. [ABSTRACT FROM AUTHOR]

To address the challenge of quickly and efficiently accessing relevant management experience for a wide range of ground engineering construction projects, supporting project management with information technology is crucial. This includes the establishment of a case database and an application platform for intelligent search and recommendations. The article leverages Optical Character Recognition (OCR) technology, knowledge graph technology, and Natural Language Processing (NLP) technology. It explores the mechanisms for classifying construction cases, methods for constructing a case database, structuring case data, intelligently retrieving and matching cases, and intelligent recommendation methods. This research forms a complete, feasible, and scalable method for deconstructing, storing, intelligently retrieving, and recommending construction cases, providing a theoretical basis for the establishment of a construction case database. It aims to meet the needs of digital project management and intelligent decision-making support in the oil and gas sector, thereby enhancing the efficiency and accuracy of project construction. This work offers a theoretical foundation for the development of an intelligent management platform for ground engineering projects in the oil and gas industry, supporting the sector's digital transformation and intelligent development. [ABSTRACT FROM AUTHOR]

In this study, a Long Short-Term Memory (LSTM) network approach is employed to evaluate the prediction performance of PM2.5 in the Beijing–Tianjin–Hebei region (BTH). The proposed method is evaluated using the hourly air quality datasets from the China National Environmental Monitoring Center, European Center for Medium-range Weather Forecasts ERA5 (ECMWF-ERA5), and Multi-resolution Emission Inventory for China (MEIC) for the years 2016 and 2017. The predicted PM2.5 concentrations demonstrate a strong correlation with the observed values (R2 = 0.871–0.940) in the air quality dataset. Furthermore, the model exhibited the best performance in situations of heavy pollution (PM2.5 > 150 μg/m3) and during the winter season, with respective R2 values of 0.689 and 0.915. In addition, the influence of ECMWF-ERA5's hourly meteorological factors was assessed, and the results revealed regional heterogeneity on a large scale. Further evaluation was conducted by analyzing the chemical components of the MEIC inventory on the prediction performance. We concluded that the same temporal profile may not be suitable for addressing emission inventories in a large area with a deep learning method. [ABSTRACT FROM AUTHOR]

In most silent speech research, continuously observing tongue movements is crucial, thus requiring the use of ultrasound to extract tongue contours. Precisely and in real-time extracting ultrasonic tongue contours presents a major challenge. To tackle this challenge, the novel end-to-end lightweight network DAFT-Net is introduced for ultrasonic tongue contour extraction. Integrating the Convolutional Block Attention Module (CBAM) and Attention Gate (AG) module with entropy-based optimization strategies, DAFT-Net establishes a comprehensive attention mechanism with dual functionality. This innovative approach enhances feature representation by replacing traditional skip connection architecture, thus leveraging entropy and information-theoretic measures to ensure efficient and precise feature selection. Additionally, the U-Net's encoder and decoder layers have been streamlined to reduce computational demands. This process is further supported by information theory, thus guiding the reduction without compromising the network's ability to capture and utilize critical information. Ablation studies confirm the efficacy of the integrated attention module and its components. The comparative analysis of the NS, TGU, and TIMIT datasets shows that DAFT-Net efficiently extracts relevant features, and it significantly reduces extraction time. These findings demonstrate the practical advantages of applying entropy and information theory principles. This approach improves the performance of medical image segmentation networks, thus paving the way for real-world applications. [ABSTRACT FROM AUTHOR]

Paclitaxel, a microtubule-stabilizing chemotherapy drug, can cause severe paclitaxel-induced peripheral neuropathic pain (PIPNP). The roles of transient receptor potential (TRP) ion channel vanilloid 1 (TRPV1, a nociceptor and heat sensor) and melastatin 8 (TRPM8, a cold sensor) in PIPNP remain controversial. In this study, Western blotting, immunofluorescence staining, and calcium imaging revealed that the expression and functional activity of TRPV1 were upregulated in rat dorsal root ganglion (DRG) neurons in PIPNP. Behavioral assessments using the von Frey and brush tests demonstrated that mechanical hyperalgesia in PIPNP was significantly inhibited by intraperitoneal or intrathecal administration of the TRPV1 antagonist capsazepine, indicating that TRPV1 played a key role in PIPNP. Conversely, the expression of TRPM8 protein decreased and its channel activity was reduced in DRG neurons. Furthermore, activation of TRPM8 via topical application of menthol or intrathecal injection of WS-12 attenuated the mechanical pain. Mechanistically, the TRPV1 activity triggered by capsaicin (a TRPV1 agonist) was reduced after menthol application in cultured DRG neurons, especially in the paclitaxel-treated group. These findings showed that upregulation of TRPV1 and inhibition of TRPM8 are involved in the generation of PIPNP, and they suggested that inhibition of TRPV1 function in DRG neurons via activation of TRPM8 might underlie the analgesic effects of menthol. [ABSTRACT FROM AUTHOR]

The lack of efficient ways to dispose of lignocellulosic agricultural residues is a serious environmental issue. Low temperatures greatly impact the ability of organisms to degrade these wastes and convert them into nutrients. Here, we report the isolation and genomic characterization of a microbial consortium capable of degrading corn straw at low temperatures. The microorganisms isolated showed fast cellulose-degrading capabilities, as confirmed by scanning electron microscopy and the weight loss in corn straw. Bacteria in the consortium behaved as three diverse and functionally distinct populations, while fungi behaved as a single population in both diversity and functions overtime. The bacterial genus Pseudomonas and the fungal genus Thermoascus had prominent roles in the microbial consortium, showing significant lignocellulose waste-degrading functions. Bacteria and fungi present in the consortium contained high relative abundance of genes for membrane components, with amino acid breakdown and carbohydrate degradation being the most important metabolic pathways for bacteria, while fungi contained more genes involved in energy use, carbohydrate degradation, lipid and fatty acid decomposition, and biosynthesis. [ABSTRACT FROM AUTHOR]

Intercropping is a vital cropping system that can create a conducive growth environment for crops and enhance land productivity. Tiger nuts (Cyperus esculentus L.) have high oil content and are adaptable to various soil types, making them a promising new oil crop with significant development potential. This study evaluated the plant height, leaf area, tiller numbers, biomass, land equivalent ratio (LER), and root morphological characteristics of tiger nuts. The agronomic traits and root distribution of tiger nuts and other crops were further investigated to achieve the goal of high yield for tiger nuts. Seven intercropping systems were implemented in the experiment: maize–tiger nut intercropping (MT), soybean–tiger nut intercropping (ST), cotton–tiger nut intercropping (CT), monoculture tiger nut (T), monoculture maize (M), monoculture soybean (S), and monoculture cotton (C). The results indicated that under different planting systems, the agronomic traits of tiger nuts in MT and ST modes were superior, with plant height and tiller numbers increasing by 7.6% to 11.6%. However, the plant height and Soil Plant Analysis Development (SPAD) values in CT mode were slightly lower than in T mode. Additionally, intercropping reduced the leaf area by 6.2% to 37.9%. Root development was more pronounced in intercropping modes, with the ST mode showing the most significant improvement, increasing the 0–20 cm root length density (RLD) by 12.2% to 45.7%. Therefore, each of the three intercropping modes demonstrated distinct advantages. The LER of the intercropping systems ranged from 1.10 to 1.24, enhancing land utilization, with tiger nuts being the dominant species. Compared to monoculture, the ST mode exhibited the best overall effect. Understanding the impact of different planting systems on tiger nuts provides valuable insights for developing tiger nut cultivation in Xinjiang. [ABSTRACT FROM AUTHOR]

The construction of an appropriate cropping pattern is crucial for the improvement of regional agricultural economic efficiency and sustainable development. Despite previous efforts, there remains a gap in optimizing cropping patterns that fully leverage climate resources to enhance production efficiency. This study addresses this gap by systematically comparing the differences in climate resource allocation, production efficiency and crop response among models by constructing four new triple-maturing cropping models at typical ecological sites in the hilly areas of southwest China. To solve the above problems, we constructed eight cropping patterns and classified them to three as follows: the Traditional Double Cropping System, the Traditional Triple Cropping System, the Novel Triple Cropping System. The results showed that the new multi-maturing planting pattern was significantly better than the traditional two-maturing netting pattern and the traditional three-maturing planting pattern in terms of light, temperature and water productivity. Compared with the traditional two-maturity net cropping model and the traditional three-maturity cropping model, the new cropping model increased light energy productivity by 97.88% and 50.00%, respectively; light energy use by an average of 0.48% and 0.31%; cumulative temperature productivity by an average of 84.70% and 49.14%; and rainfall productivity by an average of 101.04% and 49.61%. An assessment of the light, temperature and water meteorological resource use efficiency of the different treatments showed that the resource use efficiency of the new multi-maturing planting pattern was on average 111.58% and 74.78% higher than that of the traditional two-maturing net planting pattern and the traditional three-maturing planting pattern, with the T6 pattern having the highest resource use efficiency. The new multi-ripening cropping pattern has demonstrated production stability in response to changes in light, temperature and water resources, better adapting to weekly climate changes, stabilizing yields and improving efficiency. In summary, the results of this study can provide a theoretical basis for optimizing cropping patterns and promoting the use of climate resources in agriculture and sustainable development. Future research should focus on further refining these models, exploring their adaptability to various climatic conditions, and evaluating their long-term economic and environmental impacts. [ABSTRACT FROM AUTHOR]

The speed of sound in seawater plays a crucial role in determining the accuracy of multibeam bathymetric measurements. In deep-sea multibeam measurements, the challenge of inadequate longitudinal coverage of sound speed profiles arises from variations in seafloor topography, meteorological conditions, measurement equipment, and operational efficiency, resulting in diminished measurement precision. Building upon the EOF (Empirical Orthogonal Function), a method employed to analyze spatiotemporal data such as sound speeds, this paper addresses the limitations of the EOF method caused by the shallowest sampling depth of the sound speed profile samples. It proposes two methods for EOF reconstruction of measured sound speed profiles extended to full water depth by splicing measured sound speed profiles at non-full water depths with historical average sound speed profiles of the surveyed sea area. Specially, Method 2 introduces the latest metaheuristic optimization algorithm, CPO (Crested Porcupine Optimizer), which exhibited superior performance on multiple standard test functions in 2024. The study reconstructs randomly sampled measured sound speed profiles using the two proposed methods and commonly employed substitution and splicing methods, followed by a comparative analysis of the experimental outcomes. At a sampling depth of 200 m, Method 2 demonstrates performance superior to other methods, with RMSE, MAE, MAPE, and R2 values of 0.9511 m/s, 0.8492 m/s, 0.0566%, and 0.9963, respectively. Method 1 yields corresponding values of 0.9594 m/s, 0.8492 m/s, 0.0568%, and 0.9962, respectively. Despite its slightly inferior performance compared with Method 2, it offers substantial advantages over the substitution and splicing methods. Varying the sampling depth of measured sound speed profiles reveals that Methods 1 and 2 exhibit inferior reconstruction performance in shallow water compared with the substitution and splicing methods. Nevertheless, when the sampling depth surpasses the depth range of initial spatial modes with abrupt variations, both methods achieve notably higher reconstruction accuracy compared with the substitution and splicing methods, reaching a stabilized state. Sound ray tracing reveals that the reconstructed sound speed profiles from both methods meet the stringent accuracy standards for bathymetric measurements, achieving an effective beam ratio of 100%. The proposed methods not only provide rapid reconstruction of sound speed profiles, thereby improving the efficiency of multibeam bathymetric surveys, but also provide references for the reasonable determination of sampling depths of sound speed profiles to ensure reconstruction accuracy, demonstrating practical application value. [ABSTRACT FROM AUTHOR]

In this paper, the aging characterization of a kind of insulating paper modified by magnetron sputtering MgO particles based on a microstrip resonant sensor was presented. Firstly, the modified insulating paper with 0, 15 and 30 min MgO particle sputtering times was prepared by a magnetron sputtering device. After that, the properties of the modified insulating paper with different sputtering times were analyzed through microscopic characterization, infrared spectrum, polymerization degree, dielectric constant, AC breakdown strength and thermal aging experiments. The results show that the dielectric constant of the modified insulating paper decreased obviously, the AC breakdown strength increased and the thermal aging resistance was better after 15 min of sputtering. The overall performance of the modified insulating paper after 30 min of sputtering is reduced due to excessive sputtering. In addition, microstrip resonant sensors are introduced to characterize the thermal aging degree of the modified insulating paper, and two microstrip resonant sensors are prepared: a complementary split ring resonator (CSRR) and an interdigital-capacitor-shaped defected ground structure resonator (IDCS-DGS). The resonance frequency deviation of the modified insulating paper samples after aging was measured by microstrip resonance sensors to show the influence of aging temperature on aging degree. The experimental results show that the test results of the microstrip resonance sensors are in good agreement with the traditional characterization methods and can characterize the various aging stages of the modified insulating paper to a certain extent, which proves the feasibility of the characterization method. [ABSTRACT FROM AUTHOR]

Chronic migraine is a disabling disorder without effective therapeutic medicine. AMPA receptors have been proven to be essential to pathological pain and headaches, but the related regulatory mechanisms in chronic migraine have not yet been explored. In this study, we found that the level of surface GluA2 was reduced in chronic migraine rats. Tat-GluR23Y (a GluA2 endocytosis inhibitor) reduced calcium inward flow and weakened synaptic structures, thus alleviating migraine-like pain sensitization. In addition, the inhibition of GluA2 endocytosis reduced the calcium influx and alleviated mitochondrial calcium overload and ROS generation in primary neurons. Furthermore, our results showed that ROS can induce allodynia and GluA2 endocytosis in rats, thus promoting migraine-like pain sensitization. In our previous study, the dopamine D2 receptor was identified as a potential target in the treatment of chronic migraine, and here we found that dopamine D2 receptor activation suppressed chronic-migraine-related pain sensitization through blocking the GluA2/ROS positive feedback loop in vivo and in vitro. Additionally, ligustrazine, a core component of ligusticum chuanxiong, was shown to target the dopamine D2 receptor, thereby alleviating ROS production and abnormal nociception in CM rats. This study provides valuable insight into the treatment of chronic migraine. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa (PA) is an opportunistic pathogen frequently isolated from cutaneous chronic wounds. How PA, in the presence of oxidative stress (OS), colonizes chronic wounds and forms a biofilm is still unknown. The purpose of this study is to investigate the changes in gene expression seen when PA is challenged with the high levels of OS present in chronic wounds. We used a biofilm-forming PA strain isolated from the chronic wounds of our murine model (RPA) and performed a qPCR to obtain gene expression patterns as RPA developed a biofilm in vitro in the presence of high levels of OS, and then compared the findings in vivo, in our mouse model of chronic wounds. We found that the planktonic bacteria under OS conditions overexpressed quorum sensing genes that are important for the bacteria to communicate with each other, antioxidant stress genes important to reduce OS in the microenvironment for survival, biofilm formation genes and virulence genes. Additionally, we performed RNAseq in vivo and identified the activation of novel genes/pathways of the Type VI Secretion System (T6SS) involved in RPA pathogenicity. In conclusion, RPA appears to survive the high OS microenvironment in chronic wounds and colonizes these wounds by turning on virulence, biofilm-forming and survival genes. These findings reveal pathways that may be promising targets for new therapies aimed at disrupting PA-containing biofilms immediately after debridement to facilitate the treatment of chronic human wounds. [ABSTRACT FROM AUTHOR]

Despite the rapid development of vehicle intelligent technology, the aerodynamic noise problem of internal combustion engine vehicles and pure electric vehicles at high speed has always been a growing problem. In this study, the effects of the car body fender shape on the aerodynamic noises of the rearview mirror and wheel region were investigated, and a noise reduction method was also proposed by optimizing the fender shape. To realize the parametric modeling of the fender, five positional variables were selected to define the fender configuration; the free-form deformation (FFD) method was used to establish the response fender model according the DOE schemes, and computational fluid dynamics (CFD) simulations are used to obtain the noise results. Then, with the help of the radial basis function (RBF) model and the adaptive simulated annealing (ASA) algorithm, the aerodynamic shape of the fender was optimized to reduce aerodynamic noise. Comparative analysis was then employed to assess flow field characteristics of the optimized model against the original model and elucidate the fender configuration's contribution to aerodynamic noise reduction and its realization mechanism. [ABSTRACT FROM AUTHOR]

With the development of the petroleum industry, the demand for materials for oilfield equipment is becoming increasingly stringent. The strength increase brought about by time strengthening is limited in meeting the needs of equipment development. The GH3625 alloy with different strength levels can be obtained through cold deformation and heat treatment processes. A study should be carried out to further develop the potential mechanical properties of GH3625. In this study, the GH3625 alloy was cold drawn with different reductions in area (0–30%) and heat treated, and its mechanical properties were tested. The microstructure of the alloy during deformation and heat treatment was characterized by methods such as optical microscopy (OM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) based on the principles of physical metallurgy. The strength increase caused by dislocation strengthening was calculated from the dislocation density, tested by X-ray diffraction (XRD). The calculated value was compared to the measured value, elucidating the strengthening effect of cold deformation and heat treatment. The results showed that the yield strength and yield ratio of the cold-drawn alloy significantly reduced after aging at 650 °C and 760 °C. Heat treatment can make a cold-deformed material recover, ablate dislocations, and greatly reduce the dislocation density in the microstructure of the GH3625 alloy, which was the main factor in the decrease in yield strength. The work-hardening gradient of the cold-drawn material varied greatly with different reductions in area. When the reduction in area was small (10%), the hardness gradient was obvious. When it increased to 30%, the alloy was uniformly strengthened as the deformation was transmitted to the axis. This study can provide more mechanical performance options for GH3625 alloy structural components in the petrochemical industry. [ABSTRACT FROM AUTHOR]

Instance segmentation is pivotal in remote sensing image (RSI) analysis, aiding in many downstream tasks. However, annotating images with pixel-wise annotations is time-consuming and laborious. Despite some progress in automatic annotation, the performance of existing methods still needs improvement due to the high precision requirements for pixel-level annotation and the complexity of RSIs. With the support of large-scale data, some foundational models have made significant progress in semantic understanding and generalization capabilities. In this paper, we delve deep into the potential of the foundational models in automatic annotation and propose a training-free automatic annotation method called DiffuPrompter, achieving pixel-level automatic annotation of RSIs. Extensive experimental results indicate that the proposed method can provide reliable pseudo-labels, significantly reducing the annotation costs of the segmentation task. Additionally, the cross-domain validation experiments confirm the powerful effectiveness of large-scale pseudo-data in improving model generalization performance. [ABSTRACT FROM AUTHOR]

The use of solar interface evaporation for seawater desalination or sewage treatment is an environmentally friendly and sustainable approach; however, achieving efficient solar energy utilization and ensuring the long-term stability of the evaporation devices are two major challenges for practical application. To address these issues, we developed a novel ceramic fiber@bioderived carbon composite aerogel with a continuous through-hole structure via electrospinning and freeze-casting methods. Specifically, an aerogel was prepared by incorporating perovskite oxide (Ca0.25La0.5Dy0.25)CrO3 ceramic fibers (CCFs) and amylopectin-derived carbon (ADC). The CCFs exhibited remarkable photothermal conversion efficiencies, and the ADC served as a connecting agent and imparted hydrophilicity to the aerogel due to its abundant oxygen-containing functional groups. After optimizing the composition and microstructure, the (Ca0.25La0.5Dy0.25)CrO3 ceramic fiber@biomass-derived carbon aerogel demonstrated remarkable properties, including efficient light absorption and rapid transport of water and solutes. Under 1 kW m−2 light intensity irradiation, this novel material exhibited a high temperature (48.3 °C), high evaporation rate (1.68 kg m−2 h−1), and impressive solar vapor conversion efficiency (91.6%). Moreover, it exhibited long-term stability in water evaporation even with highly concentrated salt solutions (25 wt%). Therefore, the (Ca0.25La0.5Dy0.25)CrO3 ceramic fiber@biomass-derived carbon aerogel holds great promise for various applications of solar interface evaporation. [ABSTRACT FROM AUTHOR]

The development of immobilized enzymes with high activity and stability is critical. Metal–organic frameworks (MOFs) have attracted much academic and industrial interest in the field of enzyme immobilization due to their unique properties. In this study, the amino-functionalized ionic liquid (NIL)-modified metal–organic framework (UiO-66-NH2) was prepared to immobilize Candida rugosa lipase (CRL), using dialdehyde starch (DAS) as the cross-linker. The results of the Fourier transform infrared (FT-IR) spectra, X-ray powder diffraction (XRD), and scanning electronic microscopy (SEM) confirmed that the NIL was successfully grafted to UiO-66-NH2. The CRL immobilized on NIL-modified UiO-66-NH2 (UiO-66-NH2-NIL-DAS@CRL) exhibited satisfactory activity recovery (79.33%), stability, reusability, and excellent organic solvent tolerance. The research results indicated that ionic liquid-modified UiO-66-NH2 had practical potential for application in enzyme immobilization. [ABSTRACT FROM AUTHOR]

Simple Summary: The aim of this study was to detect the copy number variations in 25 Wannan spotted pigs and 10 Asian wild boars with whole genome sequencing data. The selection signatures of Wannan spotted pigs compared to those of Asian wild boars were calculated with fixation index (Fst). A total of 195 selected CNVs were under selected, harboring 80 genes. The selected genes were associated with reproduction, fatty acid composition, immune system, ear size, and feed efficiency. This study provides a new insight for understanding the characteristics of Wannan spotted pigs based on copy number variations. Copy number variation (CNV) is an important structural variation used to elucidate complex economic traits. In this study, we sequenced 25 Wannan spotted pigs (WSPs) to detect their CNVs and identify their selection signatures compared with those of 10 Asian wild boars. A total of 14,161 CNVs were detected in the WSPs, accounting for 0.72% of the porcine genome. The fixation index (Fst) was used to identify the selection signatures, and 195 CNVs with the top 1% of the Fst value were selected. Eighty genes were identified in the selected CNV regions. Functional GO and KEGG analyses revealed that the genes within these selected CNVs are associated with key traits such as reproduction (GAL3ST1 and SETD2), fatty acid composition (PRKG1, ACACA, ACSL3, UGT8), immune system (LYZ), ear size (WIF1), and feed efficiency (VIPR2). The findings of this study contribute novel insights into the genetic CNVs underlying WSP characteristics and provide essential information for the protection and utilization of WSP populations. [ABSTRACT FROM AUTHOR]

Recently, community detection has emerged as a prominent research area in the analysis of complex network structures. Community detection models based on non-negative matrix factorization (NMF) are shallow and fail to fully discover the internal structure of complex networks. Thus, this article introduces a novel constrained symmetric non-negative matrix factorization with deep autoencoders (CSDNMF) as a solution to this issue. The model possesses the following advantages: (1) By integrating a deep autoencoder to discern the latent attributes bridging the original network and community assignments, it adeptly captures hierarchical information. (2) Introducing a graph regularizer facilitates a thorough comprehension of the community structure inherent within the target network. (3) By integrating a symmetry regularizer, the model's capacity to learn undirected networks is augmented, thereby facilitating the precise detection of symmetry within the target network. The proposed CSDNMF model exhibits superior performance in community detection when compared to state-of-the-art models, as demonstrated by eight experimental results conducted on real-world networks. [ABSTRACT FROM AUTHOR]

The Yellow River, a critical water resource, faces challenges stemming from increasing water demand, which has led to detrimental effects on hydropower generation and ecological balance. This paper will address the complex task of balancing the interests of hydropower generation, water supply, and ecology within the context of cascade reservoirs, specifically Longyangxia and Liujiaxia reservoirs. Employing a systemic coupling coordination approach, we constructed a multi-objective synergetic model of the upper Yellow River in order to explore synergies and competitions among multiple objectives. The results reveal that there is a weak competitive relationship between hydropower generation and water supply, a strong synergy between hydropower generation and ecology, and a strong competitive relationship between water supply and ecology. The Pareto solution set analysis indicates a considerable percentage (59%, 20%, and 8% in wet, normal, and dry years, respectively) exhibiting excellent coordination. The probability of excellent coordination decreases with diminishing inflow. The optimization scheme with the highest coupling coordination demonstrates significant improvements in power generation, water supply, and ecological benefits in the upper Yellow River without compromising other objectives, fostering the sustainable operation of hydropower generation, water supply, and ecology in the upper Yellow River. [ABSTRACT FROM AUTHOR]

Chromium slag is a solid waste of chromium salt production, which contains highly toxic Cr(VI) and significant amounts of valuable metals, such as Fe and Cr. Recycling chromium slag as a raw sintering material in sintering–ironmaking processes can simultaneously reduce toxic Cr(VI) and recover valuable metals. A micro-sintering experiment, compressive strength test, microhardness test, and first-principles calculation are performed to investigate the influence of Cr2O3 on the sintering microstructure and mechanical properties of the silico-ferrite of calcium and aluminum (SFCA) in order to understand the basis of the sintering process with chromium slag addition. The results show that the microstructure of SFCA changes from blocky to interwoven, with further increasing Cr2O3 content from 0 wt% to 3 wt%, and transforms to blocky with Cr2O3 content increasing to 5 wt%. Cr2O3 reacts with Fe2O3 to form (Fe1−xCrx)2O3 (0 ≤ x ≤ 1), which participates in forming SFCA. With the increase in Cr doping concentrations, the hardness of SFCA first decreases and then increases, and the toughness increases. When Cr2O3 content increases from 0 wt% to 3 wt%, the SFCA microhardness decreases and the compressive strength of the sintered sample increases. Further increasing Cr2O3 contents to 5 wt%, the SFCA microhardness increases, and the compressive strength of sintered sample decreases. [ABSTRACT FROM AUTHOR]

Tomatoes are annual herbaceous plants of the family Solanaceae. They have very stringent requirements for their growing environment and climate conditions. To precisely control the greenhouse environment for tomato growth, this project designed and implemented a monitoring system utilizing programmable logic controllers and a data acquisition system for monitoring. Sensors are installed at key locations in the greenhouse, such as near the ground, in the plant canopy, and under the roof, to monitor environmental parameters such as temperature, humidity, light intensity, and carbon dioxide concentration in real time. A three-layer feedforward GA-BP neural network model was established using soil temperature, soil humidity, air humidity, and illumination as predictive parameters. This technology predicts optimal environmental parameters and performs real-time monitoring and intelligent control, overcoming the traditional BP neural network's drawbacks of slow convergence, susceptibility to disturbance, and poor generalization ability, with the current model's average prediction error being less than 5%. It provides a theoretical basis and decision support for precision control and related environmental forecasting in agricultural projects. Based on the growth characteristics, physiological and morphological features of tomatoes, and the comprehensive impact of planting conditions, the technology enhances tomato yield and quality while reducing production costs and labor inputs. It mainly includes the establishment of tomato growth models, measurement and control of environmental parameters, and the design and optimization of intelligent decision control systems. Research outcomes in this field are significant for improving agricultural production efficiency, ensuring food security, and promoting sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Black spot, caused by Alternaria brassicicola (Ab), poses a serious threat to crucifer production, and knowledge of how plants respond to Ab infection is essential for black spot management. In the current study, combined transcriptomic and metabolic analysis was employed to investigate the response to Ab infection in two cabbage (Brassica oleracea var. capitata) genotypes, Bo257 (resistant to Ab) and Bo190 (susceptible to Ab). A total of 1100 and 7490 differentially expressed genes were identified in Bo257 (R_mock vs. R_Ab) and Bo190 (S_mock vs. S_Ab), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that "metabolic pathways", "biosynthesis of secondary metabolites", and "glucosinolate biosynthesis" were the top three enriched KEGG pathways in Bo257, while "metabolic pathways", "biosynthesis of secondary metabolites", and "carbon metabolism" were the top three enriched KEGG pathways in Bo190. Further analysis showed that genes involved in extracellular reactive oxygen species (ROS) production, jasmonic acid signaling pathway, and indolic glucosinolate biosynthesis pathway were differentially expressed in response to Ab infection. Notably, when infected with Ab, genes involved in extracellular ROS production were largely unchanged in Bo257, whereas most of these genes were upregulated in Bo190. Metabolic profiling revealed 24 and 56 differentially accumulated metabolites in Bo257 and Bo190, respectively, with the majority being primary metabolites. Further analysis revealed that dramatic accumulation of succinate was observed in Bo257 and Bo190, which may provide energy for resistance responses against Ab infection via the tricarboxylic acid cycle pathway. Collectively, this study provides comprehensive insights into the Ab–cabbage interactions and helps uncover targets for breeding Ab-resistant varieties in cabbage. [ABSTRACT FROM AUTHOR]

Ice plug technology is an effective method for isolating the pipeline system, which are promising methods utilized in the nuclear, chemical, and power industries. To reduce the cold energy consumption and temperature stress, the multi-stage (1–10) of time-dependent thermal boundary conditions was proposed for the formation of ice plug, while the gradient cooling wall temperature of multi-stage was applied. A numerical model considering the liquid–solid phase change, heat transfer, and time-dependent thermal boundary condition has been established. The effects of the ratio of length and diameter of the cooling wall lc/d (1–9) on the formation rate and heat flux of ice plug in the pipe has been investigated. The fastest formation rate of ice plug with 800 mm in the axial direction (7.47 cm3/s) was observed in the pipe with the lc/d of 5. The formation rate of ice plug and the ice formation volume under unit energy consumption VE under various stages (1–10) of cooling wall temperature have been compared. The VE of eight temperature stages (1.45 cm3/kJ) was 1.16 times than the VE of one temperature stage, which satisfied the freezing rate at the same time. This investigation provides insight for proposing an energy-saving system for the formation of ice plug. [ABSTRACT FROM AUTHOR]

Tunnel–interchange connecting sections pose significant safety challenges on mountainous expressways due to their high incidence of accidents. Improving road safety necessitates a comprehensive understanding of driver behavior in such areas. This study explores the influences of road characteristics, signage information volume, and traffic conditions on drivers' car-following and lane-changing behavior in tunnel–interchange diverging areas. Utilizing driving data from 25 subjects of 72 simulated road models, driving performance is assessed using the Friedman rank test and multivariate variance analysis. The results highlight the significant influence of both connection distance and signage information load on driving behavior. In tunnel–interchange scenarios, the reduction in velocity increased by 62.61%, and speed variability surged by 61.11%, indicating potential adverse effects on driving stability due to the environmental transitions. Decreased connection distances are associated with reduced lane-changing durations, larger steering angles, and increased failure rates. Furthermore, every two units of increase in signage information leads to a 13.16% rise in maximum deceleration and a 5% increase in time headway. Notably, the signage information volume shows a significant interaction with connection distance (F > 1.60, p < 0.045) for most car-following indicators. Hence, the study recommends a maximum connection distance of 700 m and signage information not exceeding nine units for optimal safety and stability. [ABSTRACT FROM AUTHOR]

Several commonly used opioid analgesics, such as fentanyl, sufentanil, alfentanil, and hydrocodone, are by report primarily metabolized by the CYP3A4 enzyme. The concurrent use of ritonavir, a potent CYP3A4 inhibitor, can lead to significant drug interactions. Using physiologically based pharmacokinetic (PBPK) modeling and simulation, this study examines the effects of different dosing regimens of ritonavir on the pharmacokinetics of these opioids. The findings reveal that co-administration of ritonavir significantly increases the exposure of fentanyl analogs, with over a 10-fold increase in the exposure of alfentanil and sufentanil when given with ritonavir. Conversely, the effect of ritonavir on fentanyl exposure is modest, likely due to additional metabolism pathways. Additionally, the study demonstrates that the steady-state exposure of hydrocodone and its active metabolite hydromorphone can be increased by up to 87% and 95%, respectively, with concurrent use of ritonavir. The extended-release formulation of hydrocodone is particularly affected. These insights from PBPK modeling provide valuable guidance for optimizing opioid dosing and minimizing the risk of toxicity when used in combination with ritonavir-containing prescriptions. [ABSTRACT FROM AUTHOR]

Silicon carbide (SiC) is utilized in the automotive, semiconductor, and aerospace industries because of its desirable characteristics. Nevertheless, the traditional machining method induces surface microcracks, low geometrical precision, and severe tool wear due to the intrinsic high brittleness and hardness of SiC. Femtosecond laser processing as a high-precision machining method offers a new approach to SiC processing. However, during the process of femtosecond laser ablation, temperature redistribution and changes in geometrical morphology features are caused by alterations in carrier density. Therefore, the current study presented a multi-physics model that took carrier density alterations into account to more accurately predict the geometrical morphology for femtosecond laser ablating SiC. The transient nonlinear evolutions of the optical and physical characteristics of SiC irradiated by femtosecond laser were analyzed and the influence of laser parameters on the ablation morphology was studied. The femtosecond laser ablation experiments were performed, and the ablated surfaces were subsequently analyzed. The experimental results demonstrate that the proposed model can effectively predict the geometrical morphology. The predicted error of the ablation diameter is within the range from 0.15% to 7.44%. The predicted error of the ablation depth is within the range from 1.72% to 6.94%. This work can offer a new way to control the desired geometrical morphology of SiC in the automotive, semiconductor, and aerospace industries. [ABSTRACT FROM AUTHOR]

The increasing adoption of cutting-edge technologies, such as cloud computing and machine learning by robots that replace human workers, has posed serious challenges to employees' career sustainability (CS), affecting their innovative work behavior (IWB). As the digitalization of the workplace continues to progress as normal, further investigations into the relationship between CS and IWB are urgently required. In response, we investigate the relationships among CS, IWB, human capital (HC), and user resistance (UR). Using data collected from 537 employees in Chinese high-tech enterprises, structural equation and regression analyses were performed. Our results reveal that (1) three dimensions of CS (career renewability, career flexibility, and career integrity) are positively related to IWB, while the fourth dimension of CS (career resourcefulness) exerts inverted U-shaped influences on IWB, and (2) there is a significant dual moderating effect between UR and HC on the four dimensions of CS and IWB, with the former demonstrating a negative effect and the latter showing a positive effect. These findings offer valuable insights for global managers and policymakers to more appropriately implement HR practices in this highly competitive international market. Adopting a conservation of resources theory (COR) framework and the Job Demands–Resources model (JD-R), we theoretically elucidate how different dimensions of CS serve as personal resources for IWB in the digitalized context, thereby enriching the literature on innovative behavior and career development. [ABSTRACT FROM AUTHOR]

The temperature and strain fields monitoring during the preparation process of buoyancy materials, as well as the health status after molding, are important for mastering the mechanical properties of buoyancy materials and ensuring the safety of operators and equipment. This paper proposes a short and high-density femtosecond fiber Bragg grating (fs-FBG) array based on different temperature coefficients fibers. By optimizing the parameters of femtosecond laser point-by-point writing technology, high-performance fs-FBG arrays with millimeter level gating length and millimeter level spatial resolution were prepared on two types of fibers. These were successfully embedded in buoyancy materials to achieve in-situ online monitoring of the curing process and after molding. The experimental results show that the fs-FBG array sensor has good anti-chirp performance and achieves online monitoring of millimeter-level spatial resolution. Intelligent buoyancy materials can provide real-time feedback on the health status of equipment in harsh underwater environments. The system can achieve temperature monitoring with an accuracy of 0.56 °C and deformation monitoring with sub-millimeter accuracy; the error is in the order of micrometers, which is of great significance in the field of deep-sea exploration. [ABSTRACT FROM AUTHOR]

The goal of this study was to understand the effect of light intensity on the chlorogenic acid content and biosynthesis-related gene expression in Marsdenia tenacissima. In this study, M. tenacissima plants were treated with different light intensities; the chlorogenic acid content was determined by high-performance liquid chromatography; and transcriptome sequencing was performed. The amount of chlorogenic acid in the control was the highest and differed significantly from that under three different shading treatments. With a decrease in light intensity, the content of chlorogenic acid also showed a decreasing trend. A total of 1149 differentially expressed genes were identified by transcriptome sequencing, and most of the genes were down-regulated under the 90% shading treatment. A weighted gene co-expression network analysis identified the differentially expressed genes associated with light-induced chlorogenic acid biosynthesis. The different shading treatments down-regulated the expression of the chlorogenic acid biosynthesis pathway structural genes (HCTs). The MIKC family genes were the main transcription factors regulating light-induced chlorogenic acid biosynthesis, but the MYB and SBP family genes were also involved. In summary, combined physiological and transcriptome analysis, candidate structural genes, and transcription factors in the biosynthesis pathway of chlorogenic acid were identified in M. tenacissima. [ABSTRACT FROM AUTHOR]

A stratigraphic complex composed of mass transport deposits (MTDs), where the gas occurrence allows for the formation of a gas chimney and pipe structure, is identified based on seismic interpretation in the QiongDongNan area of the northern South China Sea. During the Fifth Gas Hydrate Drilling Expedition of the Guangzhou Marine Geological Survey, this type of complex morphology that has close interaction with local gas hydrate (GH) distribution was eventually confirmed. A flow-reaction model is built to explore the spatial–temporal matching evolution process of massive GH reservoirs since 30 kyr before the present (BP). Five time snapshots, including 30, 20, 10, and 5 kyr BP, as well as the present, have been selected to exhibit key strata-evolving information. The results of in situ tensile estimation imply fracturing emergence occurs mostly at 5 kyr BP. Six other environmental scenarios and three cases of paleo-hydrate existence have been compared. The results almost coincide with field GH distribution below the bottom MTD from drilling reports, and state layer fracturing behaviors always feed and probably propagate in shallow sediments. It can be concluded that this complex system with 10% pre-existing hydrates results in the exact distribution and occurrence in local fine-grained silty clay layers adjacent to upper MTDs. [ABSTRACT FROM AUTHOR]

Genetic variation facilitates the evolution, environmental adaptability, and biodiversity of organisms. Danish Large White (LW) pigs have more desirable phenotypes compared with local Chinese pigs, which have difficulty adapting to the modern swine industry. However, the genome-wide mutational differences between these pig breeds are yet to be evaluated. Therefore, this study aimed to evaluate genomic variation and identify breed-specific SNPs in Danish LW pigs. Here, 43 LW, 15 Diqing Tibetan (DQZ), and 15 Diannan small-ear (DN) pigs whose genomes were re-sequenced with 5× depth were selected. This was followed by a conjoined analysis of our previous resequencing data of 24 Anqing six-end white (AQ) and six Asian wild (SS) pigs. In total, 39,158,378 SNPs and 13,143,989 insertion–deletions were obtained in all breeds. The variation number of LW pigs was the lowest, with 287,194 breed-specific and 1289 non-synonymous SNPs compared with Chinese breeds. Functional analysis of the breed-specific non-synonymous SNPs indicated that these mutations were mainly associated with the reproductive performance, feed intake, and feed conversion ratio of LW pigs. These findings provide a theoretical basis for genetic improvements in the Chinese swine industry. [ABSTRACT FROM AUTHOR]

Accurate estimation of soil water content (SWC) is crucial for effective irrigation management and maximizing crop yields. Although dielectric property-based SWC measurements are widely used, their accuracy is still affected by soil variability, soil–sensor contact, and other factors, making the development of convenient and accurate soil-specific calibration methods a major challenge. This study aims to propose a plate compression filling technique for soil-specific calibrations and to monitor the extent of soil biomass degradation using dielectric properties. Before and after biodegradation, dielectric measurements of quartz sand and silt loam were made at seven different water contents with three different filling techniques. A third-order polynomial fitting equation explaining the dependence of the dielectric constant on the volumetric water content was obtained using the least-squares method. The suggested plate compression filling method has a maximum mean bias error (MBE) of less than 0.5%, according to experimental results. Depending on the water content, silt loam's dielectric characteristics change significantly before and after biodegradation. The best water content, measured in gravimetric units, to encourage the decomposition of biomass was discovered to be 24%. It has been demonstrated that the plate compression filling method serves as a simple, convenient, and accurate alternative to the uniform compaction method, while the dielectric method is a reliable indicator for evaluating biomass degradation. This exploration provides valuable insights into the complex relationship between SWC, biomass degradation, and soil dielectric properties. [ABSTRACT FROM AUTHOR]

The emerging technology of rotating synthetic aperture (RSA) presents a promising solution for the development of lightweight, large-aperture, and high-resolution optical remote sensing systems in geostationary orbit. However, the rectangular shape of the primary mirror and the distinctive imaging mechanism involving the continuous rotation of the mirror lead to a pronounced decline in image resolution along the shorter side of the rectangle compared to the longer side. The resolution also exhibits periodic time-varying characteristics. To address these limitations and enhance image quality, we begin by analyzing the imaging mechanism of the RSA system. Subsequently, we propose a single-image super-resolution method that utilizes a rotated varied-size window attention mechanism instead of full attention, based on the Vision Transformer architecture. We employ a two-stage training methodology for the network, where we pre-train it on images masked with stripe-shaped masks along the shorter side of the rectangular pupil. Following that, we fine-tune the network using unmasked images. Through the strip-wise mask sampling strategy, this two-stage training approach effectively circumvents the interference of lower confidence (clarity) information and outperforms training the network from scratch using the unmasked degraded images. Our digital simulation and semi-physical imaging experiments demonstrate that the proposed method achieves satisfactory performance. This work establishes a valuable reference for future space applications of the RSA system. [ABSTRACT FROM AUTHOR]

Seed germination represents a multifaceted biological process influenced by various intrinsic and extrinsic factors. In the present study, our investigation unveiled the regulatory role of OsSCYL2, a gene identified as a facilitator of seed germination in rice. Notably, the germination kinetics of OsSCYL2-overexpressing seeds surpassed those of their wild-type counterparts, indicating the potency of OsSCYL2 in enhancing this developmental process. Moreover, qRT-PCR results showed that OsSCYL2 was consistently expressed throughout the germination process in rice. Exogenous application of ABA on seeds and seedlings underscored the sensitivity of OsSCYL2 to ABA during both seed germination initiation and post-germination growth phases. Transcriptomic profiling following OsSCYL2 overexpression revealed profound alterations in metabolic pathways, MAPK signaling cascades, and phytohormone-mediated signal transduction pathways, with 15 genes related to the ABA pathways exhibiting significant expression changes. Complementary in vivo and in vitro assays unveiled the physical interaction between OsSCYL2 and TOR, thereby implicating OsSCYL2 in the negative modulation of ABA-responsive genes and its consequential impact on seed germination dynamics. This study elucidated novel insights into the function of OsSCYL2 in regulating the germination process of rice seeds through the modulation of ABA signaling pathways, thereby enhancing the understanding of the functional significance of the SCYL protein family in plant physiological processes. [ABSTRACT FROM AUTHOR]

Olibanum, a golden oleo-gum resin from species in the Boswellia genus (Burseraceae family), is a famous traditional herbal medicine widely used around the world. Previous phytochemical studies mainly focused on the non-polar fractions of olibanum. In this study, nine novel diterpenoids, boswellianols A–I (1–9), and three known compounds were isolated from the polar methanolic fraction of the oleo-gum resin of Boswellia carterii. Their structures were determined through comprehensive spectroscopic analysis as well as experimental and calculated electronic circular dichroism (ECD) data comparison. Compound 1 is a novel diterpenoid possessing an undescribed prenylmaaliane-type skeleton with a 6/6/3 tricyclic system. Compounds 2–4 were unusual prenylaromadendrane-type diterpenoids, and compounds 5–9 were new highly oxidized cembrane-type diterpenoids. Compounds 1 and 5 showed significant transforming growth factor β (TGF-β) inhibitory activity via inhibiting the TGF-β-induced phosphorylation of Smad3 and the expression of fibronectin and N-cadherin (the biomarker of the epithelial–mesenchymal transition) in a dose-dependent manner in LX-2 human hepatic stellate cells, indicating that compounds 1 and 5 should be potential anti-fibrosis agents. These findings give a new insight into the chemical constituents of the polar fraction of olibanum and their inhibitory activities on the TGF-β/Smad signaling pathway. [ABSTRACT FROM AUTHOR]

Cerebral ischemia has a high morbidity and disability rate. Clinical diagnosis is mainly made by radiologists manually reviewing cerebral perfusion images to determine whether cerebral ischemia is present. The number of patients with cerebral ischemia has risen dramatically in recent years, which has brought a huge workload for radiologists. In order to improve the efficiency of diagnosis, we develop a neural network for segmenting cerebral ischemia regions in perfusion images. Combining deep learning with medical imaging technology, we propose a segmentation network, UTAC-Net, based on U-Net and Transformer, which includes a contour-aware module and an attention branching fusion module, to achieve accurate segmentation of cerebral ischemic regions and correct identification of ischemic locations. Cerebral ischemia datasets are scarce, so we built a relevant dataset. The results on the self-built dataset show that UTAC-Net is superior to other networks, with the mDice of UTAC-Net increasing by 9.16% and mIoU increasing by 14.06% compared with U-Net. The output results meet the needs of aided diagnosis as judged by radiologists. Experiments have demonstrated that our algorithm has higher segmentation accuracy than other algorithms and better assists radiologists in the initial diagnosis, thereby reducing radiologists' workload and improving diagnostic efficiency. [ABSTRACT FROM AUTHOR]