Search Results (9,619)

The large yellow croaker (Larimichthys crocea) is an economically important marine fish in China, whose growth rate in aquaculture has yet to meet the industry’s demands. Understanding the mechanism underlying inter-individual growth differences will create a favorable condition for selective breeding. In combined transcriptome and metabolome analyses, this study collected muscle tissues from four groups of croakers categorized based on sex and growth rate: fast-growing males, slow-growing males, fast-growing females, and slow-growing females. We identified 2344 differentially expressed genes (DEGs) and 198 differentially expressed metabolites (DEMs). Three genes, bpgm, mstnb, and mylpfb, played a crucial role in the growth regulation of large yellow croaker. The pathway enrichment analysis showed that “Aminoacyl-tRNA biosynthesis”, “Alanine, aspartate and glutamate metabolism”, “Inositol phosphate metabolism” and “Retrograde endocannabinoid signaling” pathways were involved in growth regulation. This study provides new clues for future research on the molecular mechanisms of growth regulation in large yellow croaker and builds a theoretical basis for improving the growth quality of this species. Full article

High-precision spiral trajectory tracking for aquaculture net-cage inspection is hindered by uncertain hydrodynamics, strong coupling, and time-varying disturbances acting on an underactuated autonomous underwater vehicle. This paper adapts and validates a model–data-driven learning-aided adaptive robust control strategy for the specific challenge of high-precision spiral trajectory tracking for aquaculture net-cage inspection. At the kinematic level, a serial iterative learning feedforward compensator is combined with a line-of-sight guidance law to form a feedforward-compensated guidance scheme that exploits task repeatability and reduces systematic tracking bias. At the dynamic level, an integrated adaptive robust controller employs projection-based, rate-limited recursive least-squares identification of hydrodynamic parameters, along with a composite feedback law that combines linear error feedback, a nonlinear robust term, and fast dynamic compensation to suppress lumped uncertainties arising from estimation error and external disturbances. A Lyapunov-based analysis establishes uniform ultimate boundedness of all closed-loop error signals. Simulations that emulate net-cage inspection show faster convergence, higher tracking accuracy, and stronger robustness than classical adaptive robust control and other baselines while maintaining bounded control effort. The results indicate a practical and effective route to improving the precision and reliability of autonomous net-cage inspection. Full article

Stomata play a crucial role in plant immune responses, with their morphological characteristics closely linked to disease resistance. Accurate detection and analysis of stomatal phenotypic parameters are essential for soybean disease resistance research and variety breeding. However, traditional stoma detection methods are challenged by complex backgrounds and leaf vein structures in soybean images. To address these issues, we proposed a Soybean Stoma-YOLO (You Only Look Once) model (SS-YOLO) by incorporating large separable kernel attention (LSKA) in the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8 and Deformable Large Kernel Attention (DLKA) in the Neck part. These architectural modifications enhanced YOLOV8′s ability to extract multi-scale and irregular stomatal features, thus improving detection accuracy. Experimental results showed that SS-YOLO achieved a detection accuracy of 98.7%. SS-YOLO can effectively extract the stomatal features (e.g., length, width, area, and orientation) and calculate related indices (e.g., density, area ratio, variance, and distribution). Across different soybean rust disease stages, the variety Dandou21 (DD21) exhibited less variation in length, width, area, and orientation compared with Fudou9 (FD9) and Huaixian5 (HX5). Furthermore, DD21 demonstrated greater uniformity in stomatal distribution (SEve: 1.02–1.08) and a stable stomatal area ratio (0.06–0.09). The analysis results indicate that DD21 maintained stable stomatal morphology with rust disease resistance. This study demonstrates that SS-YOLO significantly improved stoma detection and provided valuable insights into the relationship between stomatal characteristics and soybean disease resistance, offering a novel approach for breeding and plant disease resistance research. Full article

Pleurotus ostreatus is among the most widely cultivated mushroom species on a global scale, valued for its relative ease of cultivation, excellent organoleptic qualities, and notable nutraceutical properties. P. ostreatus could use a wide range of by-products as growth substrates by excreting a potent array of hydrolytic and oxidative enzymes. In this study, a diverse range of agricultural residues and agro-industrial by-products, enriched (or not) with various supplements, was evaluated for the cultivation of five commercial P. ostreatus strains. Key cultivation parameters were assessed, including biological efficiency and productivity. A process analytical technology (PAT) approach, utilizing FTIR spectroscopy in combination with multivariate analysis, was employed to develop a predictive model for biological efficiency based solely on substrate’s spectral profile. Substrates based on wheat and barley straw supplemented with soybean demonstrated superior performance across most strains. The biological efficiency value reached 185% in some cases for a total cultivation period of only 35 days. The resulting model exhibited excellent predictive capability, with a coefficient of determination (R²) of 0.90 and low relative prediction error of just 6%. The developed innovative PAT tool will be beneficial for mushroom growers since it allows the fast and costless evaluation of agro-industrial by-products in respect to their potential exploitation as mushroom substrates. Full article

Background: Sarcopenia is characterized by a loss of muscle mass and strength, resulting in functional limitations and an increased risk of falls, injuries and fractures. The aim of this study was to obtain detailed information on skeletal muscle changes in patients with multiple myeloma (MM) during treatment. Methods: A total of 51 patients diagnosed with MM who had undergone whole-body low-dose computed tomography acquisition prior to induction therapy (T1) and post autologous stem cell transplantation (T2) were examined retrospectively. Total volume (TV), muscle volume (MV) and intramuscular adipose tissue volume (IMAT) of the autochthonous back muscles, the iliopsoas muscle and the gluteal muscles were evaluated on the basis of the resulting masks of the BOA tool with the fully automated combination of TotalSegmentator and a body composition analysis. An in-house trained artificial intelligence network was used to obtain a fully automated three-dimensional segmentation assessment. Results: Patients’ median age was 58 years (IQR 52–66), 38 were male and follow-up CT-scans were performed after a mean of 11.8 months (SD ± 3). Changes in MV and IMAT correlated significantly with Body-Mass-Index (BMI) (r = 0.7, p < 0.0001). Patients (n = 28) with a decrease in BMI (mean −2.2 kg/m²) during therapy lost MV (T1: 3419 cm³, IQR 3176–4000 cm³ vs. T2: 3226 cm³, IQR 3014–3662 cm³, p < 0.0001) whereas patients (n = 20) with an increased BMI (mean +1.4 kg/m²) showed an increase in IMAT (T1: 122 cm³, IQR 96.8–202.8 cm³ vs. T2: 145.5 cm³, IQR 115–248 cm³, p = 0.0002). Loss of MV varied between different muscle groups and was most prominent in the iliopsoas muscle (−9.8%) > gluteus maximus (−9.1%) > gluteus medius (−5.8%) > autochthonous back muscles (−4.3%) > gluteus minimus (−1.5%). Increase in IMAT in patients who gained weight was similar between muscle groups. Conclusions: The artificial intelligence-based three-dimensional segmentation process is a reliable and time-saving method to acquire in-depth information on sarcopenia in MM patients. Loss of MV and increase in IMAT were reliably detectable and associated with changes in BMI. Loss of MV was highest in muscles with more type 2 muscle fibers (fast-twitch, high energy) whereas muscles with predominantly type 1 fibers (slow-twitch, postural control) were less affected. This study provides valuable insight into muscle changes of MM patients during treatment, which might aid in tailoring exercise interventions more precisely to patients’ needs. Full article

Shipping in complex marine environments requires a balance between navigational safety, minimising travel time and optimising logistics management, which is particularly challenging in areas with geometric obstructions and Offshore Wind Farms (OWFs). This study focuses on the maritime route networks in the Croatian ports of Pula and Rijeka, including the main access routes to OWFs and zones characterised by multiple navigational challenges. The aim of the research is to develop an empirically based and practically applicable framework for the optimisation of sea routes that combines analytical precision with operational efficiency. The parallel application of Dijkstra and A* algorithms enables a comparative analysis between deterministic and heuristic approaches in terms of reducing navigation risk, optimising route costs and ensuring fast logistical access to OWFs. The applied methods include the analysis of real and simulated route networks, the evaluation of statistical route parameters and the visualisation of the results for the evaluation of logistical and operational efficiency. Adaptive heuristic modifications of the A* algorithm, combined with the parallel implementation of Dijkstra’s algorithm, enable dynamic route planning that takes into account real-world conditions, including variations in wind speed and direction. The results obtained provide a comprehensive framework for safe, efficient and logistically optimised navigation in complex marine environments, with direct applications in the maintenance, inspection and operational management of OWFs. Full article

The global textile industry has a significant environmental impact, driven by fast fashion and rising consumption, which leads to large amounts of waste. In Chile, this problem is especially visible, with thousands of tons of discarded clothing accumulating in open areas and landfills. This study explores how to design a practical textile revalorization system grounded in local reality. We used a qualitative mixed-methods approach, combining semi-structured interviews with six experts in textile circularity and an online survey completed by 328 people. Thematic analysis revealed low public awareness of textile recycling, limited consumer participation, and major structural barriers, including scarce infrastructure and unclear regulations. Experts emphasized the importance of coordinated action among government, industry, and grassroots recyclers, while survey respondents highlighted the need for education and easier recycling options. Based on these insights, we propose an integrated framework that combines education campaigns, better recycling systems, and formal recognition of informal recyclers’ work. While centered on Chile, the study offers ideas that could support textile circularity efforts in other countries facing similar challenges. By merging expert knowledge with everyday public perspectives, the approach helps design more realistic and socially grounded solutions for textile waste management. As with many exploratory frameworks, external validation remains a necessary step for future research to strengthen its robustness and applicability. Full article

Class 1 phytoglobins (Pgbs) are known for their multifunctional roles in plant stress responses, with recent studies suggesting broader interactions involving metabolic and transcriptional regulation. Interestingly, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) moonlights in many roles in colocalized spaces during cellular stress that are strikingly suitable for supporting Pgb function. This study investigates the molecular interactions of class 1 Pgb from sugar beet (Beta vulgaris), BvPgb 1.2, and an alanine-substituted mutant (C86A), focusing on their ability to bind GAPDH and DNA. Using dual-emission isothermal spectral shift (SpS) analysis, we report strong binding interactions with GAPDH, with dissociation constants (K_D) of 260 ± 50 nM for the recombinant wild-type protein (rWT) and a significantly stronger affinity for C86A (120 ± 40 nM), suggesting that the cysteine residue limits the interaction. Remarkably strong DNA-binding affinities were also observed for both variants, displaying biphasic binding. This behavior is characteristic of hexacoordinated globins and reflects the presence of two distinct species: a fast-reacting open pentacoordinated form and a slow-reacting closed hexacoordinated form with high apparent affinity. Here, the K_D in the open configuration was 120 ± 50 nm and 50 ± 20 nM for rWT and C86A, respectively. In the closed configuration, however, the cysteine appears to support the interaction, as the K_D was measured at 100 ± 10 pM and 230 ± 60 pM for rWT and C86A, respectively. Protein–protein docking studies reinforced these findings, revealing electrostatically driven interactions between BvPgb 1.2 and GAPDH, characterized by a substantial buried surface area indicative of a stable, biologically relevant complex. Protein–DNA docking similarly confirmed energetically favorable binding near the heme pocket without obstructing ligand accessibility. Together, these findings indicate a potential regulatory role for BvPgb 1.2 through its interaction with GAPDH and DNA. Full article

This work presents an analytical 2D model for estimating eddy current losses in the permanent magnets (PMs) of a coaxial magnetic gear (CMG), with a focus on loss minimization through magnet segmentation. The model is applied under various operating conditions, including different rotational speeds, load levels, and segmentation configurations, to derive empirical expressions for eddy current losses in both the inner and outer rotors. A 1D lumped-parameter thermal model is then used to predict the steady-state temperature of the PMs, incorporating empirical correlations for the thermal convection coefficient. Both models are validated against finite element analysis (FEA) simulations. The analytical eddy current loss model exhibits excellent agreement, with a maximum error of 2%, while the thermal model shows good consistency, with a maximum temperature deviation of 5%. The results confirm that eddy current losses increase with rotational speed but can be significantly reduced through magnet segmentation. However, achieving an acceptable thermal performance at high speeds may require a large number of segments, particularly in the outer rotor, which could influence the manufacturing cost and complexity. The proposed models offer a fast and accurate tool for the design and thermal analysis of CMGs, enabling early-stage optimization with minimal computational effort. Full article

This paper presents a CMOS-based hybrid system capable of noninvasively quantifying the total hemoglobin (tHb), the oxygen saturation (SpO₂), and the heart rate (HR) by utilizing five-wavelength (670, 770, 810, 850, and 950 nm) photoplethysmography. Conventional pulse oximeters are limited to the measurements of SpO₂ and heart rate, therefore hindering the real-time estimation of tHb that is clinically essential for monitoring anemia, chronic diseases, and postoperative recovery. Therefore, the proposed hybrid system enables us to distinguish between the concentrations of oxygenated (HbO₂) and deoxygenated hemoglobin (Hb) by using the absorption characteristics of five wavelengths from the visible to near-infrared range. This CMOS hybrid mixed-signal architecture includes a light emitting diode (LED) driver as a transmitter and an optoelectronic receiver with on-chip avalanche photodiodes, followed by a field-programmable gate array (FPGA) for a real-time signal processing pipeline. The proposed hybrid system, validated through post-layout simulations and algorithmic verification, achieves high precision with ±0.3 g/dL accuracy for tHb and ±1.5% for SpO₂, while the heart rate is extracted via 1024-point Fast Fourier Transform (FFT) with an error below ±0.2%. These results demonstrate the potential of a CMOS-based hybrid system as a feasible solution to achieve real-time, low-power, and high-accuracy analysis of bio-signals for clinical and home-use applications. Full article

This study aims to develop nutritionally improved alternative fast-food products by incorporating anchovy (Engraulis encrasicolus), a fish with high nutritional value, into three popular fast-food items (toast, burger, and pizza) frequently consumed by fast-food consumers. Anchovies, due to their rich content of omega-3 fatty acids, high-quality protein, vitamins A and D, and minerals, are a valuable food source for public health. Within the scope of this study, the nutritional compositions (crude protein, crude fat, crude ash, moisture, carbohydrate, energy) and sensory properties of the developed products were determined. According to the results of the analysis, the highest crude protein (18.64%) and crude ash (4.38%) content were found in anchovy-enriched toast, while the highest crude fat content (10.82%) was observed in anchovy burger (p < 0.05). Sensory analyses indicated that the panelists generally accepted all products. Specifically, the anchovy-enriched burger received the highest scores for appearance (90%) and aroma (40%). These findings demonstrate that anchovy-enriched fast-food products are both nutritionally rich and consumer-accepted, nutritionally improved food alternatives. Furthermore, this study identifies significant potential for utilizing aquatic products within the nutritionally enriched, seafood-based product sector. Full article

Due to the close association between gut microbiota and diabetes, probiotic dairy products have drawn a lot of attention in the development of functional foods with anti-diabetic activity. In this study, 28 type 2 diabetic patients received 10 g of camel milk powder supplemented with Bifidobacterium animalis A6 (BBA6) twice a day, taking camel milk powder as the placebo. After 4 weeks of intervention, there was a significant decrease in fasting blood glucose, serum content of total cholesterol, and pro-inflammatory cytokines (IL-6, MCP-1). And, in the CA group, the level of irisin and osteocrin increased significantly, while the level of osteonectin also increased, but with no significance. For the adipokines, the intervention of CA decreased the adiponectin, resistin, lipocalin-2, and adipsin levels significantly. Gut microbiota analysis suggested a significant enrichment in the relative abundance of Bifidobacterium when compared with patients supplemented with camel milk powder alone. Furthermore, elevated fecal concentrations of glucose-1-phosphate, conduritol b epoxide, D-Arabitol, dehydroascorbic acid, and dl-p-Hydroxyphenyllactic acid, accompanied with a decrease in glycine, N-Acetylisatin, hydroxylamine, caprylic acid, maltotriose, and guaiacol, were found in patients of group CA. Compared with camel milk alone, the adding of BBA6 can significantly decrease fasting blood glucose in type 2 diabetic patients, while also improving dyslipidemia, chronic inflammation, and skeletal muscle functions, indicating the possibility of probiotic camel milk powder as a dietary treatment that targets metabolic syndromes such as diabetes. Full article

The gut microbiome is strongly implicated in the development of obesity and type 2 diabetes mellitus (T2DM). A recent study demonstrated that 6-week oral supplementation of Anaerostipes rhamnosivorans (ARHAM) combined with the prebiotic myo-inositol (MI) reduced fasting glucose levels in mice. In the present study, we investigated the effects of a 13-week ARHAM-MI supplementation in high-fat diet-fed mice and examined the metabolic fate of MI, including its microbial conversion into short-chain fatty acids (SCFAs), using ¹³C-MI and stable isotope tracers in the cecum, portal vein, and peripheral blood. The results showed that the ARHAM-MI group gained less weight than the MI-only and placebo groups. Analysis of intestinal mRNA and stable isotope tracing revealed that MI is primarily absorbed in the upper gastrointestinal tract, whereas microbial conversion to SCFAs predominantly occurs in the cecum and is enhanced by ARHAM. ARHAM-MI mice also showed increased cecal Gpr43 mRNA expression, indicating enhanced SCFA-mediated signaling. Notably, SCFAs derived from MI displayed distinct distribution patterns: ¹³C-butyrate was detected exclusively in the cecum, ¹³C-propionate was present in the cecum and portal vein, whereas ¹³C-acetate was the only SCFA detected in peripheral blood. Collectively, ARHAM-MI co-supplementation confers modest metabolic benefits in high-fat diet-fed mice, underscoring the need to optimize the dosage and administration frequency of ARHAM-MI to enhance its therapeutic efficacy. Full article

The extraction of ocean wave wavelengths from optical imagery via Fast Fourier Transform (FFT) exhibits significant potential for Wave-Derived Bathymetry (WDB). However, in practical applications, this method frequently produces anomalously large wavelength estimates. To date, there has been insufficient exploration into the mechanisms underlying image spectral leakage to low wavenumbers and its suppression strategies. This study investigates three plausible mechanisms contributing to spectral leakage in optical images and proposes a subimage-based preprocessing framework: prior to executing two-dimensional FFT, the remote sensing subimages employed for wavelength inversion undergo three sequential steps: (1) truncation of distorted pixel values using a Gaussian mixture model; (2) application of a polynomial detrending surface; (3) incorporation of a two-dimensional Hann window. Subsequently, the dominant wavenumber peak is localized in the power spectrum and converted to wavelength values. Water depth is then inverted using the linear dispersion equation, combined with wave periods derived from ERA5. Taking 2 m-resolution WorldView-2 imagery of Sanya Bay, China as a case study, 1024 m subimages are utilized, with validation conducted against chart-sounding data. Results demonstrate that the proportion of subimages with anomalous wavelengths is reduced from 18.9% to 3.3% (in contrast to 14.0%, 7.8%, and 16.6% when the three preprocessing steps are applied individually). Within the 0–20 m depth range, the water depth retrieval accuracy achieves a Mean Absolute Error (MAE) of 1.79 m; for the 20–40 m range, the MAE is 6.38 m. A sensitivity analysis of subimage sizes (512/1024/2048 m) reveals that the 1024 m subimage offers an optimal balance between accuracy and coverage. However, residual anomalous wavelengths persist in near-shore subimages, and errors still increase with increasing water depth. This method is both concise and effective, rendering it suitable for application in shallow-water WDB scenarios. Full article

The fast and accurate calculation of the internal temperature rise in the oil-immersed transformer is the premise to realize the thermal health management and load energy evaluation of the in-service transformer. In view of the influence of nanofluids on the heat transfer process of transformer, a numerical simulation algorithm based on lattice Boltzmann method (LBM) and finite difference method (FDM) is proposed to study the heat and mass transfer process inside nano-modified oil-immersed transformer. Firstly, the D2Q9 lattice model is used to solve the fluid and thermal lattice Boltzmann equations inside the oil-immersed transformer at the mesoscopic scale, and the temperature field and velocity field are obtained by macroscopic transformation. Secondly, the electric field distribution inside the oil-immersed transformer is calculated by FDM. The viscous resistance in LBM analysis and the electric field force in FDM analysis, as well as the gravity and buoyancy of particles, are used to explore the motion characteristics of nanoparticles and metal particles. Finally, compared with the thermal ring method and the finite volume method (FVM), the relative error is less than 5%, which verifies the effectiveness of the numerical model and provides a method for studying the internal electrothermal convection of nano-modified oil-immersed transformers. Full article