Search Results (1,438)

We evaluated the inclusion of hydrolyzed feather meal (HFM) as a partial replacement for fishmeal in diets for Macrobrachium rosenbergii post-larvae (PL) over a 32-day nursery feeding trial. Five experimental diets with increasing HFM levels (control, 1.5%, 3.0%, 4.5%, and 6.0%) were tested. Survival rates ranged from 73.3 ± 5.44% to 83.3 ± 3.84% without significant differences among groups. Dietary HFM inclusion levels above 3.0% significantly improved prawn performance, including final weight (up to 2.18-fold higher than control), length (1.13-fold), antenna length (1.18-fold), biomass gain (2.14-fold), and feed conversion ratio (1.59-fold lower). Prawn-fed diets at 6.0% HFM showed the highest performance among all experimental groups. No significant effects were observed on antioxidant biomarkers or digestive enzymes in prawns hepatopancreas, which suggests no imbalance in the antioxidant system or impairment of digestive function. Likewise, carcass proximate composition remained stable across experimental groups. These findings suggest that HFM at 3.0–6.0% dietary inclusion levels is a potential alternative to fishmeal in nursery-phase diets for M. rosernbergii PL, promoting prawn growth and welfare and maintaining health and carcass quality. Notably, to the best of our knowledge, this is the first study demonstrating the potential effective use of HFM in feeding the nursery phase of M. rosernbergii. Full article

Banana de-handing is a critical yet labor-intensive step in postharvest processing, with current manual methods resulting in high costs and occupational risks. This study addresses the automation of de-handing point localization by integrating high-resolution 3D scanning and morphometric analysis of banana crowns with machine learning techniques. A total of 210 crown samples were analyzed to extract key morphological features, including inner arc length (L_i), inner arc radius (R_i), outer arc radius (R_o), and the distance between inner and outer arcs (D_oi), among others. Four machine learning algorithms, namely, Multi-Layer Perceptron (MLP), Gradient Boosted Decision Trees (GBDT), Extreme Gradient Boosting (XGBoost), and Random Forest (RF), were developed to predict the target radius (R_t) and target distance (D_ti) of the de-handing point. The RF models achieved the optimal predictive performance on the testing set, with the following results: for R_t, R² = 0.95, MAE = 1.50, and RMSE = 1.94; for D_ti, R² = 0.91, MAE = 1.33, and RMSE = 1.66. A Shapley Additive Explanations (SHAP) analysis revealed that L_i, R_i, and R_o were the most influential features for R_t, while D_oi was the most important for D_ti. Notably, feature threshold effects were observed, with limited gains in prediction accuracy beyond specific morphological values. These results provide a quantitative foundation for vision-guided automated de-handing systems, advancing intelligent and efficient banana postharvest management. Full article

Deep coalbed methane (CBM) reservoirs are characterized by high hydrocarbon content and are considered an important strategic resource. Due to their inherently low permeability and porosity, horizontal well drilling is commonly employed to enhance production, with the length of the horizontal section playing a critical role in determining CBM output. However, during extended horizontal drilling, wellbore instability frequently occurs as a result of drilling fluid invasion into the coal formation, posing significant safety challenges. This instability is primarily caused by the physical intrusion of drilling fluids and their interactions with the coal seam, which alter the mechanical integrity of the formation. To address these challenges, interpenetrating and semi-interpenetrating network (IPN/s-IPN) hydrogels have gained attention due to their superior physicochemical properties. This material offers enhanced sealing and support performance across fracture widths ranging from micrometers to millimeters, making it especially suited for plugging applications in deep CBM reservoirs. A self-degradable interpenetrating double-network hydrogel particle plugging agent (SSG) was developed in this study, using polyacrylamide (PAM) as the primary network and an ionic polymer as the secondary network. The SSG demonstrated excellent thermal stability, remaining intact for at least 40 h in simulated formation water at 120 °C with a degradation rate as high as 90.8%, thereby minimizing potential damage to the reservoir. After thermal aging at 120 °C, the SSG maintained strong plugging performance and favorable viscoelastic properties. A drilling fluid containing 2% SSG achieved an invasion depth of only 2.85 cm in an 80–100 mesh sand bed. The linear viscoelastic region (LVR) ranged from 0.1% to 0.98%, and the elastic modulus reached 2100 Pa, indicating robust mechanical support and deformation resistance. Full article

The search for artificial blood substitutes that are suitable for safe transfusion in clinical conditions and in extreme situations has gained increasing interest during recent years. Most of the problems related to donor blood could be overcome with hemoglobin sub-micron particles (HbMPs) that are able to bind and deliver oxygen. On the other hand, the length of the circulation time of HbMPs in the bloodstream strongly depends on their surface properties and can be improved with biopolymer coatings. The redox potential of HbMPs and HbMPs coated with biopolymers using the layer-by-layer technique (LbL-HbMPs) is related to the energy required for electron transfer upon transition from an oxidized to a reduced state. It can be used as a measure of the stability of Hb against oxidation, which is directly connected with its function as an oxygen carrier. The redox potential of Hb, HbMPs, and LbL-HbMPs was determined by a spectroelectrochemical method utilizing the shift of the Soret peak of Hb upon oxidation/reduction of the iron in the heme. The obtained results showed a slight shift in the redox potential of both particle types of about 17 mV towards more negative values compared to the free Hb in the solution. It was demonstrated that the free Hb and the cross-linked Hb in HbMPs and LbL-HbMPs undergo transitions from an oxidized to a reduced state and vice versa several times without Hb destruction. The LbL coating does not affect the redox properties of HbMPs. This ability, as well as the proximity of the obtained redox potentials of Hb, HbMPs, and LbL-HbMPs, indicates that the eventual oxidation of HbMPs in the bloodstream is reversible; thus, HbMPs can be active as artificial oxygen carriers for a longer period of time. Full article

Intelligent driving is a key technology in the field of automotive manufacturing due to its advantages in environmental protection, energy efficiency, and economy. However, since the intelligent driving model is an uncertain multi-input multi-output dynamic system, especially in an interactive environment, it faces uncertainties such as non-uniform trial lengths, unknown nonlinear parameters, and unknown control direction. In this paper, an adaptive iterative learning control method is proposed for vehicle systems with non-uniform trial lengths and asymmetric control gain matrices. Unlike the existing research on adaptive iterative learning for non-uniform test lengths, this paper assumes that the elements of the system’s control gain matrix are asymmetric. Therefore, the assumption made in traditional adaptive iterative learning methods that the control gain matrix of the system is known or real, symmetric, and positive definite (or negative definite) is relaxed. Finally, to prove the convergence of the system, a composite energy function is designed, and the effectiveness of the adaptive iterative learning method is verified using vehicle systems. This paper aims to address the challenges in intelligent driving control and decision-making caused by environmental and system uncertainties and provides a theoretical basis and technical support for intelligent driving, promoting the high-quality development of intelligent transportation. Full article

The newly developed automorphism ensemble decoder (AED) leverages the rich automorphisms of Reed–Muller (RM) codes to achieve near maximum likelihood (ML) performance at short code lengths. However, the performance gain of AED comes at the cost of high complexity, as the ensemble size required for near ML decoding grows exponentially with the code length. In this work, we address this complexity issue by focusing on the factor graph permutation group (FGPG), a subgroup of the full automorphism group of RM codes, to generate permutations for AED. We propose a uniform partitioning of FGPG based on the affine bijection permutation matrices of automorphisms, where each subgroup of FGPG exhibits permutation invariance (PI) in a Plotkin construction-based information set partitioning for RM codes. Furthermore, from the perspective of polar codes, we exploit the PI property to prove a subcode estimate convergence (SEC) phenomenon in the AED that utilizes successive cancellation (SC) or SC list (SCL) constituent decoders. Observing that strong SEC correlates with low noise levels, where the full decoding capacity of AED is often unnecessary, we perform path pruning to reduce the decoding complexity without compromising the performance. Our proposed SEC-aided path pruning allows only a subset of constituent decoders to continue decoding when the intensity of SEC exceeds a preset threshold during decoding. Numerical results demonstrate that, for the FGPG-based AED of various short RM codes, the proposed SEC-aided path pruning technique incurs negligible performance degradation, while achieving a complexity reduction of up to 67.6%. Full article

Integrated rice–crayfish (Oryza sativa–Procambarus clarkii) co-culture (RC) systems have gained prominence due to their economic benefits and ecological sustainability; however, the interactions between soil properties and microbial communities in such systems remain poorly understood. This study evaluated the effects of the RC systems on soil physicochemical characteristics and microbial dynamics in paddy fields of southern Henan Province, China, over the 2023 growing season and subsequent fallow period. Using a randomized complete design, rice monoculture (RM, as the control) and RC treatments were compared across replicated plots. Soil and water samples were collected post-harvest and pre-transplanting to assess soil properties, extracellular enzyme activity, and microbial community structure. Results showed that RC significantly enhanced soil moisture by up to 30.2%, increased soil porosity by 9.6%, and nearly tripled soil organic carbon compared to RM. The RC system consistently elevated nitrogen (N), phosphorus (P), and potassium (K) throughout both the rice growth and fallow stages, indicating improved nutrient availability and retention. Elevated extracellular enzyme activities linked to carbon, N, and P cycling were observed under RC, with enzymatic stoichiometry revealing increased microbial nutrient limitation intensity and a shift toward P limitation. Microbial community composition was significantly altered under RC, showing increased biomass, a higher fungi-to-bacteria ratio, and greater relative abundance of Gram-positive bacteria, reflecting enhanced soil biodiversity and ecosystem resilience. Further analyses using the Mantel test and Random Forest identified extracellular enzyme activities, PLFAs, soil moisture, and bulk density as major factors shaping microbial communities. Redundancy analysis (RDA) confirmed that total potassium (TK), vector length (VL), soil pH, and total nitrogen (TN) were the strongest environmental predictors of microbial variation, jointly explaining 74.57% of the total variation. Our findings indicated that RC improves soil physicochemical conditions and microbial function, thereby supporting sustainable nutrient cycling and offering a promising, environmentally sound strategy for enhancing productivity and soil health in rice-based agro-ecosystems. Full article

Breeding programs often overlook the use of root traits. Therefore, we investigated the relevance of sorghum root traits in explaining its adaptation to combined drought and heat stress (CDHS). Six (i.e., three pre-release lines + three checks) sorghum genotypes were established at two low-altitude (i.e., <600 masl) locations with a long-term history of averagely very high temperatures in the beginning of the summer season, under two management (i.e., CDHS and well-watered (WW)) regimes. At each location, the genotypes were laid out in the field using a randomized complete block design (RCBD) replicated two times. Root trait data, namely root diameter (RD), number of roots (NR), number of root tips (NRT), total root length (TRL), root depth (RDP), root width (RW), width–depth ratio (WDR), root network area (RNA), root solidity (RS), lower root area (LRA), root perimeter (RP), root volume (RV), surface area (SA), root holes (RH) and root angle (RA) were gathered using the RhizoVision Explorer software during the pre- and post-flowering stage of growth. RSA traits differentially showed significant (p < 0.05) correlations with grain yield (GY) at pre- and post-flowering growth stages and under CDHS and WW conditions also revealing genotypic variation estimates exceeding 50% for all the traits. Regression models varied between pre-flowering (p = 0.013, R² = 47.15%, R² Predicted = 29.32%) and post-flowering (p = 0.000, R² = 85.64%, R² Predicted = 73.30%) growth stages, indicating post-flowering as the optimal stage to relate root traits to yield performance. RD contributed most to the regression model at post-flowering, explaining 51.79% of the 85.64% total variation. The Smith–Hazel index identified ICSV111IN and ASAREACA12-3-1 as superior pre-release lines, suitable for commercialization as new varieties. The study demonstrated that root traits (in particular, RD, RW, and RP) are linked to crop performance under CDHS conditions and should be incorporated in breeding programs. This approach may accelerate genetic gains not only in sorghum breeding programs, but for other crops, while offering a nature-based breeding strategy for stress adaptation in crops. Full article

The two-stage proportional valve is a key control component in heavy-duty equipment, where its signal-flow characteristics critically influence operational performance. This study proposes an innovative flow characteristic regulation method using variable-gain feedback grooves. Unlike conventional throttling notch optimization, the core mechanism actively adjusts pilot–main valve mapping through feedback groove shape and area gain adjustments to achieve the desired flow curves. This approach avoids complex throttling notch issues while retaining the valve’s high dynamics and flow capacity. Mathematical modeling elucidated the underlying mechanism. Subsequently, trapezoidal and composite feedback grooves are designed and investigated via simulation. Finally, composite feedback groove spools tailored to construction machinery operating conditions are developed. Comparative experiments demonstrate the following: (1) Pilot–main mapping inversely correlates with area gain; increasing gain enhances micro-motion control, while decreasing gain boosts flow gain for rapid actuation. (2) This method does not significantly increase pressure loss or energy consumption (measured loss: 0.88 MPa). (3) The composite groove provides segmented characteristics; its micro-motion flow gain (2.04 L/min/0.1 V) is 61.9% lower than conventional valves, significantly improving fine control. (4) Adjusting groove area gain and transition point flexibly modifies flow gain and micro-motion zone length. This method offers a new approach for high-performance valve flow regulation. Full article

Background/Objectives: Burned tissue has traditionally been removed surgically, but the effectiveness of enzymatic debridement with NexoBrid has been reported in burn patients and has gained attention in recent years. This agent was approved for use in Japan in 2023. However, even in Japan, there have been few studies examining its effectiveness in patients with extensive burns. The purpose of this study was to analyze the association of combined NexoBrid and surgical excision with clinical outcomes in extensive burn patients. Methods: Between January 2020 and December 2024, seventeen flame burn patients requiring surgical excision were divided into two groups based on whether NexoBrid was used. Clinical outcomes between the two groups were compared using the propensity score overlap weighting method to adjust for baseline differences. Results: Seven of the patients received combined NexoBrid and surgical excision. After weighting, NexoBrid was significantly associated with a shorter time to complete debridement of burned tissue (difference −4 days, 95% CI −5 to −2) and lower percentage of bacteremia (odds ratio 0.06, 95% CI 0.00 to 0.96). However, no significant differences were observed in the length of ICU stay, the amount of blood transfusion required for complete tissue removal, hospitalization costs, and in-hospital mortality. Conclusions: Combining conventional surgical excision with enzymatic debridement may reduce the time required to complete debridement of burned tissue and decrease the rate of bacteremia. Further studies are needed to evaluate the effectiveness of NexoBrid combined with surgical excision in patients with extensive burns. Full article

The scaphoid is the most commonly fractured carpal bone. Headless compression screws became the gold standard for fixation, but the ideal screw diameter remains debated. This study investigates the relative benefit of using a larger screw diameter to improve stability in typical scaphoid fractures. It also examines the effects of preload and screw length on mechanical behaviour. A finite element (FE) model of a mid-waist scaphoid fracture was created. Screws from Medartis (1.7 mm, 2.2 mm, and 3.0 mm diameter; 23 mm length) were placed along the longitudinal axis. Boundary and loading conditions matched prior studies. Interfragmentary displacement (IFD) and von Mises stress were compared across screw sizes. The effects of screw length and preload were also evaluated. Maximum in-plane IFD was 2.08 mm (1.7 mm screw), 0.53 mm (2.2 mm), and 0.27 mm (3.0 mm). The 1.7 mm screw exceeded the scaphoid’s average ultimate stress (60.51 MPa). Increasing preload reduced IFD, especially above 60 N. Screws longer than 1.5 times the mid-waist diameter offered no added benefit. Larger screws provide better biomechanical fracture stability. However, the gain from 2.2 mm to 3.0 mm is minor, while 1.7 mm screws lack sufficient strength. The 2.2 mm screw offers a good balance of stability and bone preservation, making it the preferred choice. Full article

To address the challenges of model uncertainty, strong nonlinearities, and controller tuning in high-precision trajectory tracking for hydraulic servo systems, this paper proposes a hierarchical GA-PID-MPC fusion strategy. The architecture integrates three functional layers: a Genetic Algorithm (GA) for online parameter optimization, a Model Predictive Controller (MPC) for future-oriented planning, and a Proportional–Integral–Derivative (PID) controller for fast feedback correction. These modules are dynamically coordinated through an adaptive cost-aware blending mechanism based on real-time performance evaluation. The MPC module operates on a linearized state–space model and performs receding-horizon control with weights and horizon length $\theta =[q,r,T_p]$ tuned by GA. In parallel, the PID controller is enhanced with online gain projection to mitigate nonlinear effects. The blending coefficient $\sigma \left(t\right)$ is adaptively updated to balance predictive accuracy and real-time responsiveness, forming a robust single-loop controller. Rigorous theoretical analysis establishes global input-to-state stability and $H_{\infty }$ performance under average dwell-time constraints. Full article

The rising global demand for food, including potatoes, necessitates increased crop production. To achieve higher yields, farmers frequently depend on regular applications of nitrogen and phosphate fertilizers. As people seek more environmentally friendly alternatives, biofertilizers are gaining popularity as a potential replacement for synthetic fertilizers. This study aimed to determine how Glomus iranicum affects the growth of potatoes (Solanum tuberosum L.) and the nutritional value of potato tubers when grown alongside broad beans (Vicia faba L.). An experiment was conducted using potatoes tested at five dosage levels of G. iranicum, ranging from 0 to 4 g, to see its impact on the plants and soil. Inoculation with G. iranicum produced variable results in associated potato and bean crops, with significant effects on some variables. In particular, inoculation with 3 g of G. iranicum produced an increase in plant height (24%), leaf dry weight (90%), and tuber dry weight (57%) of potatoes. Similarly, 4 g of G. iranicum produced an increase in the foliar fresh weight (115%), root length (124%), root fresh weight (159%), and root dry weight (243%) of broad beans compared to no inoculation. These findings suggest that G. iranicum could be a helpful biological tool in Andean crops to improve the productivity of potatoes associated with broad beans. This could potentially reduce the need for chemical fertilizers in these crops. Full article

To address the modeling complexity and multi-objective collaborative optimization challenges in multi-depot and multiple unmanned aerial vehicle (UAV) delivery task planning, this paper proposes a bi-layer planning framework, which comprehensively considers resource constraints, multi-depot coordination, and the coupling characteristics of path execution. The novelty of this work lies in the seamless integration of an enhanced genetic algorithm and tailored swarm optimization within a unified two-tier architecture. The upper layer tackles the task assignment problem by formulating a multi-objective optimization model aimed at minimizing economic costs, delivery delays, and the number of UAVs deployed. The Enhanced Non-Dominated Sorting Genetic Algorithm II (ENSGA-II) is developed, incorporating heuristic initialization, goal-oriented search operators, an adaptive mutation mechanism, and a staged evolution control strategy to improve solution feasibility and distribution quality. The main contributions are threefold: (1) a novel ENSGA-II design for efficient and well-distributed task allocation; (2) an improved PSO-based path planner with chaotic initialization and adaptive parameters; and (3) comprehensive validation demonstrating substantial gains over baseline methods. The lower layer addresses the path planning problem by establishing a multi-objective model that considers path length, flight risk, and altitude variation. An improved particle swarm optimization (PSO) algorithm is proposed by integrating chaotic initialization, linearly adjusted acceleration coefficients and maximum velocity, a stochastic disturbance-based position update mechanism, and an adaptively tuned inertia weight to enhance algorithmic performance and path generation quality. Simulation results under typical task scenarios demonstrate that the proposed model achieves an average reduction of 47.8% in economic costs and 71.4% in UAV deployment quantity while significantly reducing delivery window violations. The framework exhibits excellent capability in multi-objective collaborative optimization. The ENSGA-II algorithm outperforms baseline algorithms significantly across performance metrics, achieving a hypervolume (HV) value of 1.0771 (improving by 72.35% to 109.82%) and an average inverted generational distance (IGD) of 0.0295, markedly better than those of comparison algorithms (ranging from 0.0893 to 0.2714). The algorithm also demonstrates overwhelming superiority in the C-metric, indicating outstanding global optimization capability in terms of distribution, convergence, and the diversity of the solution set. Moreover, the proposed framework and algorithm are both effective and feasible, offering a novel approach to low-altitude urban logistics delivery problems. Full article

Global warming raises surface water temperatures, impacting fish alongside pollutants, such as ubiquitous xenoestrogens. Combined stressor effects are poorly studied but likely to worsen impacts and hinder biota adaptation, warranting further research. Unadapted fish face heightened risks. The liver is a vital metabolic organ, sensitive to temperature and xenoestrogens, eventually adjusting hepatocyte size and number to ensure survival, growth, and reproduction. This study assessed, for the first time, the impact of exposure (45 days) to thermal stress (29 °C versus 26 °C) and ethinylestradiol (EE2, 5 ng/L) on male guppies, primarily on body and quantitative liver morphology. Higher temperature reduced body mass (14%) and standard length (3.6%) gain. EE2 exposure reduced body mass increase (14%), hepatosomatic index (20%), and the volumes of the liver (32%), hepatocytes (16%), and their nuclei (17%). The nucleus-to-cytoplasm ratio and total hepatocyte number remained stable. No histopathological lesions existed. Guppies appear to have adapted to stressors by reducing hepatocyte size and utilizing lipid reserves, yet they exhibited deficits in body growth and hepatosomatic index. Gonadal maturation was unaffected. Only under EE2 at 29 °C did hepatocytes show minimal lipid droplet content (less vacuolation). This indicated exhausted reserves, reinforcing how heat and toxicants interact to exacerbate impacts. Full article