Search Results (911)

Diffuse speckle contrast analysis (DSCA), also called speckle contrast optical spectroscopy (SCOS), has emerged as a groundbreaking optical imaging technique for tracking dynamic biological processes, including blood flow and tissue perfusion. Recent advancements in single-photon avalanche diode (SPAD) cameras have unlocked exceptional sensitivity, time resolution, and high frame-rate imaging capabilities. Despite this, the application of large-format SPAD arrays in speckle contrast analysis is still relatively uncommon. This study introduces a pioneering use of a large-format SPAD camera for DSCA. By harnessing the camera’s high temporal resolution and photon-detection efficiency, we significantly enhance the accuracy and robustness of speckle contrast measurements. Our experimental results demonstrate the system’s remarkable ability to capture rapid temporal variations over a broad field of view, enabling detailed spatiotemporal analysis. Through simulations, phantom experiments, and in vivo studies, we validated the proposed approach’s potential for cerebral blood flow and functional tissue monitoring. This work highlights the transformative impact of large SPAD cameras on DSCA, setting the stage for breakthroughs in optical imaging. Full article

Slow-release nitrogen fertilizers enhance crop production and reduce environmental pollution, but their slow nitrogen release may cause insufficient nitrogen supply in the early stages of crop growth. Mixed nitrogen fertilization (MNF), combining slow-release nitrogen fertilizer with urea, is an effective way to increase yield and income and improve nitrogen fertilizer efficiency. This study used urea alone (Urea) and slow-release nitrogen fertilizer alone (C/SRF) as controls and employed meta-analysis and a random forest model to assess MNF effects on crop yield and nitrogen partial factor productivity (PFPN), and to identify key influencing factors. Results showed that compared with urea, MNF increased crop yield by 7.42% and PFPN by 8.20%, with higher improvement rates in Northwest China, regions with an average annual temperature ≤ 20 °C, and elevations of 750–1050 m; in soils with a pH of 5.5–6.5, where 150–240 kg·ha⁻¹ nitrogen with 25–35% content and an 80–100 day release period was applied, and the blending ratio was ≥0.3; and when planting rapeseed, maize, and cotton for 1–2 years. The top three influencing factors were crop type, nitrogen rate, and soil pH. Compared with C/SRF, MNF increased crop yield by 2.44% and had a non-significant increase in PFPN, with higher improvement rates in Northwest China, regions with an average annual temperature ≤ 5 °C, average annual precipitation ≤ 400 mm, and elevations of 300–900 m; in sandy soils with pH > 7.5, where 150–270 kg·ha⁻¹ nitrogen with 25–30% content and a 40–80 day release period was applied, and the blending ratio was 0.4–0.7; and when planting potatoes and rapeseed for 3 years. The top three influencing factors were nitrogen rate, crop type, and average annual precipitation. In conclusion, MNF should comprehensively consider crops, regions, soil, and management. This study provides a scientific basis for optimizing slow-release nitrogen fertilizers and promoting the large-scale application of MNF in farmland. Full article

The increasing penetration of distributed renewable energy and the emergence of large-scale, flexible loads such as data centers pose significant challenges to the economic and secure operation of distribution systems. Traditional static pricing mechanisms are often inadequate, leading to inefficient resource dispatch and curtailment of renewable generation. To address these issues, this paper proposes a hierarchical pricing and dispatch framework modeled as a tri-level Stackelberg game that coordinates interactions among an upstream grid, a distribution system operator (DSO), and multiple virtual power plants (VPPs). At the upper level, the DSO acts as the leader, formulating dynamic time-varying purchase and sale prices to maximize its revenue based on upstream grid conditions. In response, at the lower level, each VPP acts as a follower, optimally scheduling its portfolio of distributed energy resources—including microturbines, energy storage, and interruptible loads—to minimize its operating costs under the announced tariffs. A key innovation is the integration of a schedulable data center within one VPP, which responds to a specially designed wind-linked incentive tariff by shifting computational workloads to periods of high renewable availability. The resulting high-dimensional bilevel optimization problem is solved using a Kriging-based surrogate methodology to ensure computational tractability. Simulation results verify that, compared to a static-pricing baseline, the proposed strategy increases DSO revenue by 18.9% and reduces total VPP operating costs by over 28%, demonstrating a robust framework for enhancing system-wide economic and operational efficiency. Full article

Deep drilling and horizontal wells, as important means of unconventional oil and gas development, face problems with the high energy consumption but low removal efficiency of traditional well washing equipment, the uneven cleaning of horizontal well intervals, and an insufficient degree of automation. This paper proposes a novel hydraulic drive well washing device which consists of two main units. The wellbore cleaning unit comprises a hydraulic drive cutting–flushing module, a well cleaning mode-switching module, and a filter storage module. The unit uses hydraulic and mechanical forces to perform combined cleaning to prevent mud and sand from settling. By controlling the flow direction of the well washing fluid, it can directly switch between normal and reverse washing modes in the downhole area, and at the same time, it can control the working state of corresponding modules. The assembly control unit includes the chain lifting module and the arm assembly module, which can lift and move the device through the chain structure, allow for the rapid assembly of equipment through the use of a mechanical arm, and protect the reliability of equipment through the use of a centering structure. The device converts some of the hydraulic power into mechanical force, effectively improving cleaning and plugging removal efficiency, prolonging the downhole continuous working time of equipment, reducing manual operation requirements, and comprehensively improving cleaning efficiency and energy utilization efficiency. Full article

Acute hepatopancreatic necrosis disease (AHPND), caused by the bacterium Vibrio parahaemolyticus, is a major threat to global shrimp aquaculture. In this study, we evaluated the therapeutic effects of phage therapy in Litopenaeus vannamei challenged with AHPND-causing Vibrio parahaemolyticus. Phage application at various concentrations significantly improved shrimp survival, with the 1 ppm group demonstrating the highest survival rate. Enzymatic assays revealed that phage-treated shrimp exhibited enhanced immune enzyme activities, including acid phosphatase (ACP), alkaline phosphatase (AKP), and lysozyme (LZM). In addition, antioxidant defenses such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-PX), and total antioxidant capacity (T-AOC) significantly improved, accompanied by reduced malondialdehyde (MDA) levels. Serum biochemical analyses demonstrated marked improvements in lipid metabolism, particularly reductions in triglyceride (TG), total cholesterol (TC), and low-density lipoprotein (LDL), alongside higher levels of beneficial high-density lipoprotein (HDL). Transcriptomic analysis identified 2274 differentially expressed genes (DEGs), notably enriched in pathways involving fatty acid metabolism, peroxisome functions, lysosomes, and Toll-like receptor (TLR) signaling. Specifically, phage treatment upregulated immune and metabolic regulatory genes, including Toll-like receptor 4 (TLR4), myeloid differentiation primary response protein 88 (MYD88), interleukin-1β (IL-1β), nuclear factor erythroid 2-related factor 2 (Nrf2), and peroxisome proliferator-activated receptor (PPAR), indicating activation of innate immunity and antioxidant defense pathways. These findings suggest that phage therapy induces protective immunometabolic adaptations beyond its direct antibacterial effects, thereby providing an ecologically sustainable alternative to antibiotics for managing bacterial diseases in shrimp aquaculture. Full article

This review comprehensively examines the application of deep learning technologies across the entire soybean production chain, encompassing areas such as disease and pest identification, weed detection, crop phenotype recognition, yield prediction, and intelligent operations. By systematically analyzing mainstream deep learning models, optimization strategies (e.g., model lightweighting, transfer learning), and sensor data fusion techniques, the review identifies their roles and performances in complex agricultural environments. It also highlights key challenges including data quality limitations, difficulties in real-world deployment, and the lack of standardized evaluation benchmarks. In response, promising directions such as reinforcement learning, self-supervised learning, interpretable AI, and multi-source data fusion are proposed. Specifically for soybean automation, future advancements are expected in areas such as high-precision disease and weed localization, real-time decision-making for variable-rate spraying and harvesting, and the integration of deep learning with robotics and edge computing to enable autonomous field operations. This review provides valuable insights and future prospects for promoting intelligent, efficient, and sustainable development in soybean production through deep learning. Full article

The objective of this experiment was to investigate the effects of tartary buckwheat flavonoids (TBF) and 25-hydroxyvitamin D₃ (25-OHD) on fatty liver syndrome (FLS) in laying hens. A total of 450 35-wk-old Lohmann laying hens were selected and randomly divided into five groups, with six replicates per treatment and 15 laying hens in each replicate. The control group was fed a corn-soybean meal basal diet. The FLS group was fed a high- energy–low-protein (HELP) diet, and the other three experimental groups were fed HELP diets supplemented with 60 mg/kg TBF, 69 μg/kg 25-OHD, and 60 mg/kg TBF plus 69 μg/kg 25-OHD, respectively. The experiment lasted 8 weeks. The results demonstrated that feeding laying hens with a HELP diet led to a significant accumulation of fat in their livers, liver enlargement and yellowing, as well as a decline in liver antioxidant capacity and an aggravation of inflammation. TBF alone, 25-OHD alone, and their combination had no effect on the laying performance of laying hens fed with a HELP diet. However, 25-OHD significantly enhanced the albumin content, eggshell strength, and eggshell thickness of eggs (p < 0.05). Compared with the HELP group, TBF, 25-OHD, or their combination reduced serum LDL-C and TG (p < 0.05). The combined treatment further lowered serum NEFA and MDA, enhanced liver SOD activity (p < 0.05), and unlike TBF alone (which reduced hepatic TG) or 25-OHD alone (which decreased liver index), reduced both liver index and hepatic TG (p < 0.05). Liver gene expression analysis showed that combined TBF and 25-OHD significantly inhibited the expression of fat synthesis-related genes (ACC, FAS, GPAT1, ChREBP1, LXRα, SREBP-1C, SREBP-2, FABP) as well as inflammation-related genes (IL-6, TNF-α, NF-κB, TLR4) (p < 0.05). At the phylum level of the cecal microbiota, TBF increased the abundance of Bacteroidota (p < 0.05), and combined TBF and 25-OHD tended to increase the abundance of Firmicutes_D. At the genus level, TBF increased the abundance of Phocaeicola_A (p < 0.05). Furthermore, TBF, 25-OHD, or their combination reduced the abundance of Faecalibacterium (p < 0.05). These findings suggest that combined TBF and 25-OHD mitigates FLS in laying hens potentially through remodeling gut microbiota and maintaining lipid metabolic homeostasis. Full article

Investigating the factors influencing rice grain yield (GY) is critical for optimizing nitrogen (N) management and enhancing resource use efficiency in rice cultivation. However, few studies have comprehensively investigated the factors affecting rice GY, considering an entire influence chain encompassing rice N uptake, growth indicators, and GY components. In this study, field experiment with six different N fertilizer rates (0, 60, 120, 180, 225, and 300 kg N ha⁻¹, i.e., N0, N60, N120, N180, N225, and N300) was conducted in the Jianghan Plain in the Middle Reaches of the Yangtze River, China, to comprehensively elucidate the factors influencing rice GY from aspects of rice N uptake, growth indicators, and GY components and determine the optimal N fertilizer rate. The results showed that rice GY and N uptake initially increased and then either stabilized or declined with higher N fertilizer rate, while apparent N loss escalated with increased N fertilizer rate. The application of N fertilizer significantly promoted the increase in straw N uptake, which was significantly positively correlated with growth indicators (p < 0.05). Among all GY components, panicle number per hill was the most significant positive factor influencing rice GY, and it was significantly positively correlated with all rice growth indicators (p < 0.05). In addition, N180 was the optimal N fertilizer rate, ensuring more than 95% of maximum GY and reducing N loss by 74% and 39% compared to N300, respectively. Meanwhile, the average N balance for N180 remained below 60 kg N ha⁻¹. In conclusion, optimizing the N fertilizer application in paddy fields can effectively maintain stable rice GY and minimize environmental pollution. Full article

Precise estimation of the remaining available energy in batteries is not only key to improving energy management efficiency, but also serves as a critical safeguard for ensuring the safe operation of battery systems. To address the challenges associated with energy state estimation under dynamic operating conditions, this study proposes a method for predicting the remaining available energy of energy storage batteries based on an interpretable generalized additive neural network (IGANN). First, considering the variability in battery operating conditions, the study designs a battery working voltage threshold that accounts for safety margins and proposes an available energy state assessment metric, which enhances prediction consistency under different discharge conditions. Subsequently, 12 features are selected from both direct observation and statistical characteristics to capture the operating condition information of the battery, and a dataset is constructed using actual operational data from an energy storage station. Finally, the model is trained and validated on the feature dataset. The validation results show that the model achieves an average absolute error of 2.39%, indicating that it effectively captures the energy variation characteristics within the 0.2 C to 0.6 C dynamic current range. Furthermore, the contribution of each feature is analyzed based on the model’s interpretability, and the model is optimized by utilizing high-contribution features. This optimization improves both the accuracy and runtime efficiency of the model. Finally, a dynamic prediction is conducted for a discharge cycle, comparing the predictions of the IGANN model with those of three other machine learning methods. The IGANN model demonstrates the best performance, with the average absolute error consistently controlled within 3%, proving the model’s accuracy and robustness under complex conditions. Full article

The utilization of iron tailings in road construction poses significant environmental risks due to the complex release mechanisms of pollutants and varying regional conditions. This study integrates an exponential decay model with an instantaneous pollutant transport model, employing Monte Carlo simulations to assess risks and regional characteristics. Results show high Potential Hazard Indices (PHIs) for arsenic, manganese, barium, nickel, and lead, with PHI values between 4.2 and 22.7. Simulations indicate that manganese and nickel concentrations may exceed groundwater standards, particularly in humid areas. The study recommends controlling the iron tailings mixing ratio based on climate, suggesting limits of 35% in humid, 60% in semi-humid, and more lenient ratios in arid and semi-arid regions. It also underscores the need for improved risk assessment methodologies and region-specific management strategies at the national level. Full article

Hilbert proved in 1888 that a positive semi-definite (PSD) homogeneous quartic polynomial of three variables always can be expressed as the sum of squares (SOS) of three quadratic polynomials, and a psd homogeneous quartic polynomial of four variables may not be sos. Only after 87 years, in 1975, Choi gave the explicit expression of such a psd-not-sos (PNS) homogeneous quartic polynomial of four variables. An $m\times n$ biquadratic polynomial is a homogeneous quartic polynomial of $m+n$ variables. In this paper, we show that an $m\times n$ biquadratic polynomial can be expressed as a tripartite homogeneous quartic polynomial of $m+n-1$ variables. Therefore, by Hilbert’s theorem, a $2\times 2$ PSD biquadratic polynomial can be expressed as the sum of squares of three quadratic polynomials. This improves the result of Calderón in 1973, who proved that a $2\times 2$ biquadratic polynomial can be expressed as the sum of squares of nine quadratic polynomials. Furthermore, we present a necessary and sufficient condition for an $m\times n$ psd biquadratic polynomial to be sos, and show that if such a polynomial is sos, then its sos rank is at most $mn$. Then we give a constructive proof of the sos form of a $2\times 2$ psd biquadratic polynomial in three cases. Full article

The integration of forestry and agriculture has promoted edible fungi cultivation in forest understory spaces. However, the impact of spent mushroom substrates on forest soils remains unclear. This study explored the use of seafood mushroom spent substrates (SMS) and grass substrates to cultivate Dictyophora indusiata. After cultivation, soil pH stabilized, organic carbon increased by 34.02–62.24%, total nitrogen rose 1.1–1.9-fold, while soil catalase activity increased by 43.78–100.41% and laccase activity surged 3.3–11.2-fold. The 49% Cenchrus fungigraminus and 49% SMS treatment yielded the highest 4-coumaric acid levels in the soil, while all treatments reduced maslinic and pantothenic acid content. SMS as padding material with C. fungigraminus enhanced soil bacterial diversity in the first and following years. Environmental factors and organic acids influenced the recruitment of genus of Latescibacterota, Acidothermus, Rokubacteriales, Candidatus solibacter, and Bacillus, altering organic acid composition. In conclusion, cultivating D. indusiata understory enhanced environmental characteristics, microbial dynamics, and organic acid profiles in forests’ soil in short time. Full article

In this study, a terahertz microfluidic multi-band sensor was designed. Unlike previous microfluidic absorption sensors that rely on dipole resonance, the proposed sensor uses a physical mechanism for absorption by exciting higher-order lattice resonances in microfluidic structures. With a Fabry–Perot cavity, the sensor can form an absorption peak with a high quality factor (Q) and narrow full width at half maximum (FWHM). A high Q value and a narrow FWHM are valuable in the field of sensing and provide strong support for high-precision sensing. On this basis, the sensing performance of the device was investigated. The simulation results clearly show that the absorption sensor has ultra-high sensitivity, which reaches 400 GHz/Refractive Index Unit (RIU). In addition, the sensor generates three absorption peaks, overcoming the limitations of a single frequency band in a composite resonance mode and multidimensional frequency response, which has potential application value in the field of volatile organic compound (VOC) sensing. Full article

Background: The reproductive ability of equine species is a critical component of equine breeding programs, with sperm quality serving as a primary determinant of reproductive success. In this study, we perform an integrative analysis of proteomics and metabolomics in seminal plasma to identify proteins and metabolites associated with sperm quality and reproductive ability in equine species. Methods: We utilized the CEROS instrument to assess the morphology and motility of sperm samples from three horses and three donkeys. Additionally, we statistically analyzed the mating frequency and pregnancy rates in both species. Meanwhile, the 4D-DIA high-throughput proteomic and metabolomic profiling of seminal plasma samples from horses and donkeys revealed a complex landscape of proteins and metabolites. Results: Our findings reveal a certain degree of correlation between seminal plasma proteins and metabolites and sperm quality, as well as overall fertility. Notably, we found that the proteins B3GAT3, XYLT2, CHST14, HS2ST1, GLCE, and HSPG2 in the glycosaminoglycan biosynthesis signaling pathway; the metabolites D-glucose, 4-phosphopantetheine, and 4-hydroxyphenylpyruvic acid in the tyrosine metabolism, starch, and source metabolisms; and pantothenate CoA biosynthesis metabolism present unique characteristics in the seminal plasma of equine species. Conclusions: This comprehensive approach provides new insights into the molecular mechanisms underlying sperm quality and has identified potential proteins and metabolites that could be used to indicate reproduction ability. The findings from this study could be instrumental in developing novel strategies to enhance equine breeding practices and reproductive management. Future research will focus on exploring their potential for clinical application in the equine industry. Full article

This study assessed the environmental risks and regional variations associated with using titanium gypsum in road construction. It revealed that the conventional HJ/T299-2007 leaching method underestimates heavy metal leaching rates from titanium gypsum by approximately 1%, potentially leading to an underestimation of environmental risks. Further analysis indicated that Pb, Ni, As, Cd, and Zn leach from titanium gypsum road materials to varying extents, while Mn poses a notable exceedance risk with an 11% probability of surpassing limits and a maximum exceedance factor of 1.8. Significant disparities in regulatory thresholds for titanium gypsum pollutants were observed among 11 provinces along the Yangtze River, with the highest threshold (Qinghai) nearly five times greater than the lowest (Jiangxi). Rainfall was identified as a key contributor to these regional differences. The findings suggest that traditional assessment methods underestimate titanium gypsum risks and highlight the need for enhanced national solid waste evaluation frameworks. Additionally, given the substantial regional risk variations, differentiated management strategies are recommended. Full article