Search Results (90,108)

Micropropagated plantlets, after removal from controlled laboratory conditions, require an acclimatization period. Adaptation to the new environment induces anatomical and physiological changes controlled by cellular processes. This study investigated the involvement of the primary proton transport systems of total membranes in pineapple root colonization by diazotrophic bacteria and in the development of plantlets treated with different nitrogen doses, allowing an understanding of nutrient absorption and accumulation dynamics. The experiment followed a randomized block design (RBD) in a factorial scheme (2 × 3 × 2), with two inocula (a mixture of diazotrophic bacteria containing Burkholderia sp. UENF 114111, Burkholderia silvatlantica UENF 117111, and Herbaspirillum seropedicae HRC 54, and another without bacteria), three urea doses (0, 5, and 10 g L⁻¹), and two evaluation (90 and 150 days) and bacterial counting times (30 and 150 days), with three blocks. Diazotrophic bacterial populations were lower in older plantlets. H⁺ transport mediated by P H⁺-ATPases changed with acclimatization time. Inoculation did not induce transport; however, the F_max of V H⁺-ATPase was lower without nitrogen fertilization. Nitrogen fertilization affected V H⁺-ATPase proton transport activity in root membranes. The presence of diazotrophic bacteria did not induce proton transport. On the other hand, nitrogen fertilization and acclimatization time affected the proton transport activity mediated by H⁺-ATPases isolated from roots of micropropagated pineapple. Full article

Arsenic (As) contamination of soils is a critical environmental and geochemical concern, with its mobility and bioavailability largely controlled by molecular-scale interactions with soil minerals. This study investigates the adsorption behavior of arsenate [As(V)] and arsenious acid [As(III)] on major clay minerals to elucidate fundamental controls on As retention in soil and sediment systems. Molecular modeling approaches were employed to investigate these interactions. Density functional theory (DFT) calculations were performed on cluster models of illite, chlorite, montmorillonite, and kaolinite to evaluate adsorption configurations and binding energies of arsenate and arsenious acid. In addition, semiempirical (PM6) and classical force-field (UFF) methods were used to examine the influence of vermicompost-derived organic matter on arsenate-mineral interactions. Multiple adsorption configurations, including atop atom, bridge, three-fold filled, and three-fold hollow sites, were evaluated, and binding energies were calculated with correction for basis set superposition error. The results indicate that three-fold hollow sites are the most favorable, with As(V) binding energies of 60–65 kcal mol⁻¹ on illite, chlorite, and montmorillonite, reaching 75 kcal mol⁻¹ on kaolinite at a surface distance of 2.7 Å. In contrast, As(III) shows weaker and energetically flatter adsorption, with binding energies of 28–54 kcal mol⁻¹ and larger equilibrium distances of 3.2–4.0 Å. Modeling of vermicompost addition suggests a substantial reduction in arsenate binding on most clay minerals, except illite, indicating competitive or disruptive interactions at mineral surfaces. These findings provide quantitative, atomistic insight into mineral- and amendment-specific controls on As stabilization and mobility in soil and sediment systems. Full article

China is one of the world’s major lychee producers, and the fruit’s soft texture, small size, and thin peel make non-destructive robotic harvesting particularly challenging. Accurate fruit detection, branch segmentation, and precise picking-point localization are critical for enabling automated harvesting in complex natural orchard environments. This study proposes an integrated perception framework for lychee harvesting that combines object detection, density-based clustering, and semantic segmentation. An improved YOLO11s-based detection network incorporating SimAM attention, CMUNeXt feature enhancement, and MPDIoU loss is developed to enhance robustness under illumination variation, occlusion, and scale changes. The proposed detector achieves a precision of 84.3%, recall of 73.2%, and mAP of 81.6%, outperforming baseline models. Density-based clustering is employed to group individual detections into fruit clusters. Comparative experiments demonstrate that MeanShift achieves the highest clustering consistency, with an average Adjusted Rand Index (ARI) of 0.768, outperforming k-means and other baselines. An improved DeepLab v3+ semantic segmentation network with a ResDenseFocal backbone and Focal Loss is designed for accurate branch extraction under complex backgrounds. Finally, a rule-based geometric picking-point localization algorithm is formulated in the image coordinate system by integrating detection, clustering, and branch segmentation results. Experimental validation demonstrates that the proposed framework can reliably localize picking points in two-dimensional images under natural orchard conditions. The proposed method provides a practical perception solution for intelligent lychee harvesting and establishes a foundation for future 3D robotic manipulation and field deployment. Full article

Interlayer-sliding ferroelectricity in van der Waals bilayers enables ultralow-power switching, but practical devices are often limited by contact/interface scattering and weak coupling between polarization and transport. We propose homophase lateral architectures based on bilayer Janus MoSSe: a 1T/2H/1T ferroelectric tunnel homojunction and an H-phase lateral p–i–n photodetector (artificially doped electrode). Metallic 1T electrodes largely eliminate contact barriers and maximize polarization-driven tunneling modulation. Using non-equilibrium Green’s function–density functional theory (Perdew–Burke–Ernzerhof approximation, without explicit spin–orbit coupling), we find that AB to BA sliding reduces the current from the nA range to the pA range, with the minimum current of|I_OFF|_min = 2.83 pA, yielding giant tunneling electroresistance up to 5.3 × 10⁴%. Projected local density of states reveals a non-rigid long-range potential redistribution that reshapes the tunneling barrier and opens high-transmission channels. In the p–i–n photodetector, the response is strongly anisotropic and stacking-dependent: AB reaches photocurrent density J_ph ≈ 7.2 µA·mm⁻² at 2.6 eV for in-plane light versus ≈2.9 µA·mm⁻² at 3.5 eV for out-of-plane, and exceeds BA by 1.5–1.8 times due to density of states advantages and Mo-d orbital selection rules. Bilayer Janus MoSSe therefore provides a reconfigurable platform for high-contrast memory and polarization-sensitive photodetection. Full article

One of the gaps in green building research in European and Mediterranean countries is the assessment of Leadership in Energy and Environmental Design (LEED)-certified projects in the context of the LEED rating system’s ongoing transition from a prescriptive to a performance-based approach. This study evaluates LEED certification strategies by analyzing the statistical association between five independent performance indicators and the overall LEED score for LEED for Existing Office Buildings version 4.1 (LEED-EB v4.1) gold-certified office projects in Sweden, Italy, Israel, Spain, Germany, and Ireland using simple linear regression. The results showed that each of the six above-mentioned countries demonstrated a unique LEED certification strategy for LEED-EB v4.1 gold-certified office projects. Linear regression revealed an unexpected result: the statistical association between the independent indicator (energy) and the dependent indicator (overall LEED) score was statistically insignificant (R² = 0.04 and p = 0.359; R² = 0.13 and p = 0.112, respectively) in LEED-EB v4.1 gold-certified office projects in Germany and Ireland. However, in Sweden, Italy, Israel, and Spain, this association was statistically significant (R² = 0.38, 0.46, 0.53, and 0.40 at p < 0.001 in all cases, respectively). Full article

Background: Cavity disinfection is commonly performed in pediatric restorative dentistry to reduce residual bacterial contamination. Although boric acid has been proposed as a potential antimicrobial agent, its effect on marginal integrity and adhesive performance in primary teeth remains unclear. This study evaluated the effects of 3% and 5% boric acid, compared with 2% chlorhexidine (CHX), on microleakage and microshear bond strength of composite restorations in primary teeth bonded with a two-step self-etch adhesive system. Methods: Seventy-two extracted primary second molars were allocated to four groups (n = 18) for microleakage assessment: control, 2% CHX, 3% boric acid, and 5% boric acid. Standardized Class V cavities were prepared, disinfectants were applied for 60 s, and restorations were completed using Clearfil SE Bond and resin composite. Microleakage at occlusal and gingival margins was evaluated using dye penetration. For microshear bond strength testing, 60 primary molars (n = 15 per group) were treated similarly, and shear force was applied to bonded composite microcylinders. Data were analyzed at the p < 0.05 significance level. Results: Both boric acid groups showed significantly higher occlusal and gingival microleakage than the control and CHX groups (p < 0.05). Gingival microleakage was greater than occlusal microleakage in the boric acid groups (p < 0.05). Microshear bond strength was significantly reduced in the boric acid groups compared with the control (p < 0.05), whereas CHX had no significant effect. Failure modes did not differ significantly. Conclusions: While 2% CHX did not adversely affect adhesive performance, 3% and 5% boric acid increased microleakage and reduced bond strength. Caution is advised when using boric acid with self-etch adhesive systems in primary teeth. Full article

Objective: The objective of this study was to choose the optimal anesthesia method for gastric cancer patients undergoing surgery with lymph node dissection. Materials and Methods: The study included 53 patients with stage T1-4aN0-3M0 gastric cancer, who underwent radical surgery with xenon and dexmedetomidine (DMM) anesthesia in combination with epidural analgesia (main group, 27 patients) or with sevorflurane anesthesia in combination with epidural analgesia (comparison group, 26 patients). All patients underwent monitoring of hemodynamic parameters, blood coagulation system, thromboelastometry, and inflammation and metabolic parameters (interleukins, hormones and glucose levels), with an assessment of complications according to the Clavien-Dindo classification and the intensity of postoperative pain. Results: Awakening and extubation times, narcotic analgesic consumption, and Numeric Rating Scale pain scores were lower in the xenon + DMM group than in the sevoflurane group (p < 0.05). The overall number of patients experiencing complications did not differ significantly between anesthesia types; however, significant differences were found in the total number of complications (p = 0.003), the number of complications according to Clavien-Dindo I (p = 0.043) and II (p = 0.019), and the incidence of postoperative nausea and vomiting (p = 0.042). Conclusions: The BIS monitoring data obtained showed a sufficient level of anesthesia depth during surgery in both groups; however, post-anesthesia depression persisted longer in patients in sevoflurane group. Mathematical models for predicting Clavien-Dindo IIIb-V complications and severe postoperative pain syndrome are characterized by high sensitivity and specificity. They include simple clinical and laboratory parameters as well as type of anesthesia as predictors. The limitations of predictive models are also discussed in the article. Full article

Liquid vermicompost fertilizer (LVF) represents a valuable organic resource in the promotion of sustainable crop production. This study assessed how LVF at four different dilution rates (0, 0.5:1000, 1:1000, and 1.5:1000, v/v) impacted the growth, yield, and quality parameters of Thai basil (Ocimum basilicum L.) grown in greenhouse conditions. The study was carried out from September 2023 to January 2024 at Ton Duc Thang University, Vietnam. Measurements and statistical analyses were conducted on growth and yield traits, which included plant height, leaf area (LA), leaf number, and fresh biomass. Additionally, quality parameters such as total phenolic content, total flavonoid content, and antioxidant activity were also assessed. The application of LVF had a notable impact on all of the assessed parameters (p < 0.05). The highest LVF rate (1.5:1000) led to the most substantial increases in plant height, LA, leaf number, and fresh weight, while also significantly boosting phenolic and flavonoid content in comparison to the control. The antioxidant activity demonstrated a distinct upward trend as the concentration of LVF was increased. Full article

Long COVID is the disease entity triggered and potentially driven by SARS-CoV-2 infection. It is an heterogeneous condition characterized by dozens of different symptoms, signs and sequelae, which can affect all organs and body systems and evolve over the disease course. Clinical manifestations of Long COVID can vary from individual to individual and across the broader patient population. Pathology can range from asymptomatic and subclinical manifestations to fatal outcomes. Over 400 million people worldwide are estimated to suffer, or have suffered, from Long COVID, making the sequelae of SARS-CoV-2 infection one of the greatest public health challenges of the 21st century. This article provides an updated overview of epidemiology, definitions, main concepts and terminology for Long COVID. It also summarizes key evidence of pathology and disease mechanisms in major organs and body systems, such as the immune system, cardiovascular system, endothelium, heart, lungs, central nervous system, peripheral nervous system, gastrointestinal system, hapatobiliary system, pancreas and kidney. Heterogeneity in manifestations, potential risk of death and the degree of disability in several disease subsets call for timely diagnosis of each Long COVID types and a fuller understanding of their pathophysiological underpinnings. Further research is recommended to better understand pathobiology, develop effective clinical trials, and identify treatments and scalable biomarkers. Full article

Hypocrellin A (HA) represents a pharmaceutically important perylenequinone photosensitizer produced by Shiraia bambusicola. However, submerged fermentation remains constrained by filamentous morphological characteristics and inherent mass transfer limitations. Although microparticle-enhanced cultivation (MPEC) has demonstrated efficacy in filamentous fungal systems, the molecular mechanisms by which physical cues, such as microparticle-induced shear stress, reprogram fungal metabolism remain largely unexplored. This work systematically optimizes SiO₂-based MPEC parameters for S. bambusicola GDMCC 60438, including particle dimensions, temporal addition protocols, and solid loading. Mechanistic investigations integrated pellet morphology analysis, membrane lipid composition, intracellular redox status, energy/precursor markers, and RNA-seq transcriptomic profiling with qRT-PCR validation. Under optimized conditions (10% w/v SiO₂, 30 mesh, added at 6 h), HA yield reached 41.76 ± 5.02 mg/L, representing a 3.65-fold increase over controls. MPEC shifted morphology toward smaller, more porous pellets with denser internal structure, accompanied by increased membrane fluidity (unsaturated/saturated fatty acid ratio from 1.54 to 2.63), elevated ROS levels with antioxidant enzyme activation, and enhanced acetyl-CoA and ATP accumulation. Transcriptomic analysis identified 206 differentially expressed genes enriched in oxidative phosphorylation, carbon metabolism, and stress responses, with upregulation of PKS-related biosynthetic genes and major facilitator superfamily transporters. This work establishes an integrated mechanistic framework linking particle-induced morphological changes to metabolic reprogramming through oxidative stress and subsequent transcriptional activation of the HA biosynthetic pathway, providing rational design principles for MPEC strategies in filamentous fungi. Full article

This study proposes Advisory Board Reinforcement Learning (AdvB-RL), a cooperative reinforcement-learning framework that integrates multiple advisory neural networks to guide policy optimization. Unlike conventional single-agent architectures, AdvB-RL maintains a set of independently trained advisory networks that contribute to action selection through a dynamic aggregation mechanism. This design preserves diverse experiential knowledge while improving learning stability and the exploration–exploitation balance. The framework is evaluated on three benchmark control tasks, namely LunarLander-v2, CartPole-v1, and MountainCar-v0, using advisory board sizes of 1, 5, and 10 members against a Double Deep Q-Network (DDQN) baseline. The best-performing configuration, 10 AdvB, achieved 270.02 ± 24.74 on LunarLander-v2 versus 227.92 ± 86.02 for DDQN, 497.79 ± 5.18 on CartPole-v1 versus 304.37 ± 144.04, and −103.16 ± 15.46 on MountainCar-v0 versus −130.71 ± 31.64, indicating higher returns together with markedly lower variability. Across the three environments, these results show that increasing the number of advisory members improves both reward consistency and overall robustness, with the 10-member setting providing the strongest performance. Within the tested configurations, the advisory board mechanism remains computationally feasible, while preliminary experiments beyond 10 advisors show diminishing returns relative to added complexity. Overall, AdvB-RL provides a robust and modular alternative to single-policy reinforcement learning for adaptive cooperative control. Full article

Oil leakage in oil-immersed power transformers poses a significant threat to grid reliability, potentially causing severe electrical accidents and environmental pollution if not detected in time. Detecting oil leakage outdoors, however, remains challenging due to the impact of weather conditions such as fog, humidity, and rain, which obscure the leakage signs and complicate real-time detection. To address these challenges, we propose a solution that integrates infrared thermal imaging with a CNN-SVM hybrid architecture. The core of this approach lies in shifting from traditional Softmax-cross-entropy-based empirical risk minimization (ERM) to maximum-margin-based structural risk minimization (SRM). A fully fine-tuned MobileNetV3 transforms low-contrast, boundary-softened infrared thermal images—often affected by fog and moisture—into a more discriminative high-dimensional feature space, where positive and negative samples become linearly separable. This is followed by replacing Softmax with a linear SVM and using hinge loss to enforce a margin constraint, which maximizes the classification margin and improves robustness to input perturbations. Experimental results show that our proposed method outperforms all compared models, achieving an accuracy of 0.990, significantly higher than ResNet50_BCE (0.908), EfficientNetB0 (0.925), YOLOv11n-CLS (0.930), and ViT (0.929). In terms of F1-Score (0.989) and AUC (0.995), MobileNetV3-SVM also demonstrates excellent performance, ensuring outstanding classification capability. Additionally, the model achieves an inference latency of only 6.3 ms, demonstrating excellent real-time inference performance, highlighting its potential for transformer oil monitoring applications. This research contributes to SDG 6 by preventing industrial water pollution resulting from transformer oil runoff, thereby protecting vital water sources in remote environments. Full article

Thin wall composite fan blades in aircraft engines demand designs that ensure structural integrity under operational loads while resisting foreign object damage and bird strikes. This study presents a finite element investigation of thin wall composite blades with metal leading edge caps, modeled through parametric coupon analyses under static flexure loading using ANSYS APDL. Three metallic leading edge caps, Ti-6Al-4V, Inconel 718, and 15-5 PH stainless steel, were combined with IM7/8551-7 carbon fiber composites. Parametric variations included changes in metal cap material, geometric designs of the joint, and other things. Performance was evaluated in terms of failure stress, interlaminar shear strains, interface integrity, and failure margins. Results reveal that cap design and cap material critically govern structural response, with distinct interchanges between strength-to-weight efficiency, interface stresses, and interlaminar shear strain. Optimal designs reduced interlaminar shear strain levels in thin wall composite blades, while retaining adequate stiffness and strength. The results underscore the importance of interface design for effective load transfer and provide design guidelines for lightweight, damage-tolerant thin wall composite fan blade structures. Full article

Prior molecular docking and dynamics studies indicated a pyrazolopyridine–sulfonamide derivative (L87/PPS2, or simply PPS2) as a potential interactant with SARS-CoV-2 protein targets. The in vitro anti-SARS-CoV-2 activity and cytotoxicity profile of PPS2 were screened alongside a series of pyrazolopyrimidine (PZP) and triazolopyrimidine (TZP) derivatives. PPS2 demonstrated only partial inhibition of SARS-CoV-2 growth in Vero E6 cells at 100 µM. Crucially, however, four out of five PZPs and eight out of fourteen TZPs exhibited potent in vitro inhibitory activity against SARS-CoV-2 at 100 µM, with none of the tested compounds displaying cytotoxicity against Vero E6 cells at this concentration. Further characterization of one compound, PZP25, revealed an inhibitory concentration (IC50) of 8.2 µM, combined with low cytotoxicity (CC50 > 800 µM), yielding a selectivity index greater than 100. Time of addition assays indicated that PZP25’s antiviral effects were most pronounced when administered post-infection. While cellular pre-treatment provided a partial reduction in virus growth, modest virucidal activity was also observed at warmer temperatures (20 °C and 37 °C). Collectively, our findings demonstrate that PZP and TZP derivatives possess potent inhibitory activity of SARS-CoV-2 replication in vitro and highlight such compounds as promising chemical scaffolds for the development of novel antiviral agents targeting coronaviruses. Full article

With the increasing penetration of distributed energy resources, distribution networks face elevated risks of power disruptions, which call for rapid and flexible emergency response mechanisms. There are not enough traditional emergency generator vehicles, and they are not highly adaptable when it comes to operations, which makes it hard to meet changing dispatching needs. Electric vehicles (EVs), on the other hand, can be used as distributed emergency resources that can be dispatched through vehicle-to-grid (V2G) interaction. Electric vehicle charging stations (EVCSs), on the other hand, are integrated energy storage units that use existing charging infrastructure to provide on-site grid support. To address this gap, this study proposes a comprehensive V2G-powered pre- and post-disaster coordination framework for enhancing distribution network resilience, with three core novelties: first, a refined individual EV model considering dual power and energy constraints is developed, and the Minkowski summation method is applied to accurately quantify the real-time aggregate regulation potential of EVCSs for the first time; second, a two-stage robust optimization model is formulated for pre-event strategic planning, which jointly optimizes EVCS participant selection and distribution network topology to address photo-voltaic (PV) power generation uncertainties; third, a multi-source collaborative dynamic scheduling model is constructed for post-disaster recovery, which explicitly incorporates the spatiotemporal dynamics of EVs and coordinates EVCSs, gas turbine generators (GTGs) and other resources for the first time. We carried out simulations on a modified IEEE 33-bus system with a 10 h extreme fault scenario. The results show that the proposed strategy raises the average critical load recovery ratio to 97.7% (2% higher than traditional deterministic optimization), lowers the total load shedding power by 0.2 MW and the load reduction cost by 19,797.63 CNY, and gives a net V2G power output of 3.42 MW (86.9% higher than the comparison strategy). The proposed V2G-enabled coordinated pre- and post-disaster fault recovery strategy significantly improves the resilience of distribution networks compared to traditional methods. This makes it easier and faster to recover from extreme disaster scenarios, with the overall load recovery rate reaching 91.8% and the critical load restoration rate staying above 85% throughout the recovery process. Full article