Search Results (7,258)

Soil salinity is a major constraint to wheat production worldwide. Efficient screening of salt-tolerant cultivars is essential for breeding programs, yet a rapid and reliable evaluation system based on full-life-cycle salt stress treatment is lacking. To address this, we conducted a hydroponic experiment encompassing the entire growth cycle of 37 wheat cultivars under control and salt stress (85.5 mM NaCl). Using principal component and stepwise regression analyses on 15 agronomic and yield-related traits, we identified five key indicators—total dry weight, root dry weight, plant height, thousand-grain weight, and number of grains per spike—that effectively represent overall salt tolerance. Based on a comprehensive evaluation value (D-value), the cultivars were classified into five distinct categories: highly salt-tolerant, salt-tolerant, moderately salt-tolerant, weakly salt-tolerant, and salt-sensitive. Notably, the highly salt-tolerant cultivar ‘Yangfumai 8′ and the salt-sensitive cultivar ‘Yangmai 22’ were selected as representative extremes. A subsequent pot experiment confirmed significant physiological differences between them in antioxidant enzyme activities (SOD, POD, CAT) and proline accumulation under salt stress. This study establishes a practical and efficient screening framework, providing breeders with a simplified index set for high-throughput evaluation and offering ideal contrasting materials for in-depth physiological research on salt tolerance mechanisms in wheat. Full article

Biomass ashes represent a promising secondary phosphorus (P) source, yet their agronomic performance depends on feedstock origin, processing, and crop-specific interactions. This study evaluated the P fertilizer efficacy of raw and processed biomass ashes derived from cereal straw and paludiculture biomass, compared with triple superphosphate (TSP), using two sequential greenhouse pot experiments with maize, amaranth, and blue lupine. Processed ash products, particularly compacted ashes and ash–straw mixtures, increased plant biomass and P uptake to levels comparable to or exceeding those achieved with TSP. The cumulative P uptake of the three crops reached up to 250–300 mg pot⁻¹ under processed ash treatments, exceeding the uptake under TSP (≈150–180 mg pot⁻¹) and the unfertilized control (≤80 mg pot⁻¹). However, crop-specific differences were observed: amaranth benefited most from the ash products, whereas combinations of ashes with lupine were less favorable. Beside acting as a P source, processed biomass ashes also increased soil pH by about 0.5 units, improved soil aggregation by increasing macroaggregates (>2 mm) to up to 20% compared with only about 7% in TSP and the control, and promoted favorable shifts in Hedley P fractions. Soil enzyme activities were governed primarily by crop species, with amaranth stimulating phosphatase activity the most. Further research should aim to refine crop-specific application strategies for processed biomass ashes and to elucidate their impacts on soil structure and P dynamics. Full article

Planning in robotics represents an ongoing research challenge, as it requires the integration of sensing, reasoning, and execution. Although large language models (LLMs) provide a high degree of flexibility in planning, they often introduce hallucinated goals and actions and consequently lack the formal reliability of deterministic methods. In this paper, we address this limitation by proposing a hybrid Sense–Plan–Code–Act (SPCA) framework that combines perception, LLM-based reasoning, and symbolic planning. Within the proposed approach, sensory information is first transformed into a symbolic description of the world in Planning Domain Definition Language (PDDL) using an LLM. A heuristic planner is then used to generate a valid plan, which is subsequently converted to code by a second LLM. The generated code is first validated syntactically through compilation and then semantically in simulation. When errors are detected, local corrections can be applied and the process is repeated as necessary. The proposed method is evaluated in the OpenAI Gym MiniGrid reinforcement learning environment and in a Gazebo simulation on a UR5 robotic arm using a curriculum of tasks with increasing complexity. The system successfully completes approximately 71–75% of tasks across environments with a relatively low number of simulation iterations. Full article

Deep reinforcement learning policies are hard to deploy in safety-critical settings, because they fail to explain why a sequence of actions is taken. We introduce an intrinsically interpretable framework that learns compact summaries of recurring behavior and uses them for case-based decision making. Our method (i) discovers global regimes by grouping trajectories into a small set of recurrent patterns and (ii) learns a prototype-conditioned local policy that maps the current short-horizon pattern to an action (“this matches prototype X → take action Y”). Each action is accompanied by a similarity score to relevant prototypes, which provide the explanations. We evaluate our approach on two domains: (1) CarRacing (pixel-based continuous control) and (2) a real voltage-control problem in low-voltage distribution networks. Our results indicate that the method provides clear pre hoc explanations while keeping task performance close to the reference policy. Full article

Recently, the EU approved RENURE-criteria materials to be used as substitutes for synthetic N fertilisers. Several studies have been performed on the agronomic efficacy and potential environmental impacts of different bio-based fertilisers (BBFs) from biomass recovery, including the RENURE-criteria materials. But information is lacking about their effectiveness under abiotic stress conditions like salinity and drought. The predictions for climate change-induced increased drought and soil salinisation for the European soils have also increased, making it inevitable to understand BBF performance in these impending situations. Two RENURE-criteria top-priority materials (ammonium nitrate (AN) and ammonium sulphate (AS) and another commercially used BBF—an evaporator concentrate (CaE)) were evaluated in a pot trial growing spinach under salinity and drought stress with a reference ‘no stress’ condition to examine crop growth, nutrient uptake, and nitrogen fertiliser replacement value (NFRV). Agronomically, BBFs performed at par with the synthetic fertiliser (SF) under unstressed and salt-stressed conditions, whereas, under drought stress, BBFs outperformed the SF treatment. AS exhibited the highest yield and nutrient uptake, displaying an NFRV of 3.1 and 1.8 under no-stress and salt-stress conditions, respectively. Salt stress did not negatively impact the crops grown in this trial, potentially due to the higher potassium content in the system, which alleviated the possible negative impacts of high sodium. This study delves into the agronomic response, without evaluating crop physiological changes, and, hence, should be taken as a preliminary step into further investigation of observed elemental interactions (that could be potentially driving stress mitigation) while also examining the crop physiology during the duration of stress. Full article

Background: Infections caused by the protozoan Trichomonas vaginalis affect millions of people worldwide and are responsible for one of the most common sexually transmitted diseases. Despite the efficacy of 5-nitroimidazoles like metronidazole, concerns regarding widespread resistance and the absence of viable alternatives for specific patient populations necessitate the development of structurally diverse pharmacological agents. In this study, we investigated the antiparasitic activity of 1,3-thiazolidin-4-one derivatives against T. vaginalis. Methods: Thiazolidines were synthesized via multicomponent reaction (MCR) using one-pot methodology and tested in vitro against the parasite and mammalian cell lines. Results: Seventy percent of the compounds showed more than 80% antiparasitic activity at 100 μM, with compounds 4a, 4b, and 4f exhibiting IC₅₀ ≤ 20 µM. None of the molecules exhibited cytotoxic against Vero CCL-81 and HeLa cells. Evaluation of the structure–activity relationship (SAR) indicates that the substituent at the nitrogen position of the heterocycle may be involved in the antiparasitic effect of these compounds. In silico studies also revealed that the three compounds possess adequate oral bioavailability and do not present mutagenic, tumorigenic or irritating risks. Finally, molecular docking predicted strong interactions of compounds 4a, 4b, and 4f with T. vaginalis enzymes lactate dehydrogenase and purine nucleoside phosphorylase; compound 4f also interacted with methionine Ƴ-lyase. Conclusions: These preliminary results suggest that 1,3-thiazolidin-4-ones are promising scaffolds for developing new trichomonacidal agents. Full article

In this study, a novel Bi₂O₃/BiOBr_0.9I_0.1 (BO0.9−BBI0.1) composite photocatalyst was successfully synthesized via a single-pot solvothermal method for the efficient degradation of 2,4-dichlorophenoxyacetic acid (2,4-D) under visible light. The structure, morphology, and optical properties of the photocatalyst were characterized through X-ray diffraction (XRD), Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), UV–vis diffuse reflectance spectra (DRS), Steady-state photoluminescence (PL), and Electrochemical Impedance Spectroscopy (EIS). The composite exhibits a 3D hierarchical morphology with increased specific surface area and optimized pore structure, enhancing pollutant adsorption and providing more active sites. Under visible light irradiation, BO0.9−BBI0.1 achieved a 92.4% removal rate of 2,4-D within 2 h, with a reaction rate constant 5.3 and 4.6 times higher than that of pure BiOBr and BiOI, respectively. Mechanism studies confirm that photogenerated holes (h⁺) and superoxide radicals (·O₂⁻) are the primary active species, and the Z-scheme charge transfer pathway significantly promotes the separation of electron-hole pairs while maintaining strong redox capacity. The catalyst also demonstrated good stability over multiple cycles. This work provides a feasible dual-modification strategy for designing efficient bismuth-based photocatalysts for pesticide wastewater treatment. Full article

Accurate assessment of rice resistance to Sogatella furcifera (Horváth) is essential for breeding insect-resistant cultivars. Traditional assessment methods rely on manual scoring of damage severity, which is subjective and inefficient. To overcome these limitations, this study proposes an automated resistance evaluation approach based on multi-view 3D reconstruction and deep learning–based point cloud segmentation. Multi-view videos of rice materials with different resistance levels were collected over time and processed using Structure from Motion (SfM) and Multi-View Stereo (MVS) to reconstruct high-quality 3D point clouds. A well-annotated “3D Rice WBPH Damage” dataset comprising 174 samples (15 rice materials, three replicates each, 45 pots) was established, where each sample corresponds to a reconstructed 3D point cloud from a video sequence. A comparative study of various point cloud semantic segmentation models, including PointNet, PointNet++, ShellNet, and PointCNN, revealed that the PointNet++ (MSG) model, which employs a Multi-Scale Grouping strategy, demonstrated the best performance in segmenting complex damage symptoms. To further accurately quantify the severity of damage, an adaptive point cloud dimensionality reduction method was proposed, which effectively mitigates the interference of leaf shrinkage on damage assessment. Experimental results demonstrated a strong correlation (R² = 0.95) between automated and manual evaluations, achieving accuracies of 86.67% and 93.33% at the sample and material levels, respectively. This work provides an objective, efficient, and scalable solution for evaluating rice resistance to S. furcifera, offering promising applications in crop resistance breeding. Full article

Background/Objectives: Dizziness is a symptom of many disorders across a wide range of etiologies. If dizzy patients are seen for vestibular evaluation with an audiologist and no vestibular reason for the patient’s dizziness is found, the medical referral pathway can become convoluted. This can leave patients feeling discouraged and unable to manage their symptoms. Clinically symptomatic chronic respiratory alkalosis (CSCRA) is an acid–base disorder that typically presents with dizziness but is unfamiliar to practitioners in vestibular and balance care settings. Methods: In a retrospective chart review deemed exempt by the Mayo Clinic Institutional Review Board, 74 patients at Mayo Clinic Arizona were included. All had consultations with both Audiology and Aerospace Medicine to assess their dizzy symptoms. Results: After completing vestibular testing, arterial blood gas (ABG) testing, and a functional test developed at Mayo Clinic Arizona called the Capnic Challenge test, 40% of patients were found to have CSCRA contributing to their dizzy symptoms. Many of these patients also had common comorbidities of CSCRA, like postural orthostatic tachycardia syndrome (POTS), migraines, and sleep apnea. Fewer than one-fourth of these patients had measurable vestibulopathies causing their dizziness. Half of the patients referred by the vestibular audiologist to Aerospace Medicine had a diagnosis of CSCRA. Conclusions: Assessment for CSCRA should be considered as a next step for patients presenting with dizziness without a vestibular component. Being aware of the prevalence of CSCRA and its comorbidities may help balance providers offer quality interprofessional referrals and improve patient quality of life. Full article

(1) Background: Improving nitrogen use efficiency in peanuts is essential for achieving a high yield with reduced nitrogen fertilizer input. This study investigates the role of the fungal endophyte Phomopsis liquidambaris in regulating nitrogen utilization throughout the entire growth cycle of peanuts. (2) Methods: Field pot experiments and a two-year plot trial were conducted. The effects of Ph. liquidambaris colonization on the rhizosphere microbial community, soil nitrogen forms, and peanut physiology were analyzed. (3) Results: Colonization by Ph. liquidambaris significantly suppressed the abundance of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in the rhizosphere at the seedling stage. This led to a transient decrease in nitrate and an increase in ammonium availability, which enhanced nodulation-related physiological responses. Concurrently, the peanut-specific rhizobium Bradyrhizobium sp. was enriched in the rhizosphere, and the root exudates induced by the fungus further stimulated nodulation activity. These early-stage effects promoted the establishment of peanut–Bradyrhizobium symbiosis. During the mid-to-late growth stages, the fungus positively reshaped the composition of key functional microbial groups (including diazotrophs, AOA, and AOB), thereby increasing rhizosphere nitrogen availability. (4) Conclusions: Under low nitrogen fertilization, inoculation with Ph. liquidambaris maintained yield stability in long-term monocropped peanuts by enhancing early nodulation and late-stage rhizosphere nitrogen availability. This study provides a promising microbe-based strategy to support sustainable legume production with reduced nitrogen fertilizer application. Full article

Modulating the electronic structure and surface properties of graphitic carbon nitride (g-C₃N₄) by chemically phosphorus doping is an effective strategy for improving its photocatalytic performance. However, in order to benefit from practical applications, the cost-effectiveness, efficiency, and optimization of the doping level need to be investigated further. Herein, we report a structural doping of P into g-C₃N₄ by in situ polymerization of the mixture of dicyandiamide (DCDA) and phosphorus pentoxide (P₂O₅). As an alternative to previous studies that used complex organic phosphorus precursors or post-treatment strategies, this work proposed a one-pot thermal polycondensation method that is low-cost, scalable, and enables controlled phosphorus substitutions at carbon sites of the g-C₃N₄ heptazine structure. Most of the structural features of g-C₃N₄ were well retained after doping, but the electronic structures and light harvesting capacity had been effectively altered, which provided not only a much better charge separation but also an improvement in photocatalytic activity toward H₂ evolution under irradiation of a simulated sunlight. The optimized sample with P-doping content of 9.35 at.% (0.5PGCN) exhibited an excellent photocatalytic performance toward H₂ evolution, which is over 5 times higher than that of bulk g-C₃N₄. This work demonstrates a facile one-step in situ route for producing high-yield photocatalysts using low-cost commercial precursors, offering practical starting materials for studies in solar cells, polymer batteries, and photocatalytic applications. Full article

To elucidate the potential of integrated multi-omics approaches for studying systemic mechanisms of mycorrhizal fungi in mediating plant-microbe interactions, this study employed the Tuber-inoculated Corylus system as a model to demonstrate how high-throughput profiling can investigate how fungal inoculation reshapes the rhizosphere microbial community and correlates with host metabolism. A pot experiment was conducted comparing inoculated (CTG) and non-inoculated (CK) plants, followed by integrated multi-omics analysis involving high-throughput sequencing (16S/ITS), functional prediction (PICRUSt2/FUNGuild), and metabolomics (UPLC-MS/MS). The results demonstrated that inoculation significantly restructured the fungal community, establishing Tuber as a dominant symbiotic guild and effectively suppressing pathogenic fungi. Although bacterial alpha diversity remained stable, the functional profile shifted markedly toward symbiotic support, including antibiotic biosynthesis and environmental adaptation. Concurrently, root metabolic reprogramming occurred, characterized by upregulation of strigolactones and downregulation of gibberellin A5, suggesting a potential “symbiosis-priority” strategy wherein carbon allocation shifted from structural growth to energy storage, and plant defense transitioned from broad-spectrum resistance to targeted regulation. Multi-omics correlation analysis further revealed notable associations between microbial communities and root metabolites, proposing a model in which Tuber acts as a core regulator that collaborates with the host to assemble a complementary micro-ecosystem. In summary, the integrated approach successfully captured multi-level changes, suggesting that Tuber-Corylus symbiosis constitutes a fungus-driven process that transforms the rhizosphere from a competitive state into a mutualistic state, thereby illustrating the role of mycorrhizal fungi as “ecosystem engineers” and providing a methodological framework for green agriculture research. Full article

In an effort to evaluate the performance of a 5-gallon pot still in separating yeast-derived congeners during the distillation of a grain-based distiller’s beer, the distillates of a fermented mash of cracked corn, malted barley, and wheat were characterized using ¹H NMR spectroscopy and GC-MS. A quantitative comparison using these two techniques is uncommon. Results revealed significant variation in congener concentrations across runs, with a notable discrepancy in the third run possibly due to bacterial contamination, as indicated by high 1-propanol levels. Key congeners, such as acetaldehyde, ethyl acetate, furfural, phenylethanol, and 1,1-diethoxyethane, showed expected distillation behavior across ten fractions, based on their respective boiling points. However, methanol and 1-propanol showed a fairly flat concentration profile across all ten fractions, while those for ethyl octanoate and ethyl hexanoate decreased rapidly and were undetected at fraction 5. White dog (unaged whiskey) fractions from column and combination stills were also analyzed, and the results demonstrate that the small 5-gallon still separates congeners as well as these stills. Finally, a comparison of congener concentrations demonstrates that NMR and GC-MS do not yield identical concentrations of congeners, despite exhibiting similar trends in congener concentrations in the fractions from the still, with GC-MS suggesting higher levels. Full article

Fire-retardant intumescent coatings offer an effective means of enhancing the fire resistance of combustible substrates such as wood. These coatings have a complex chemical composition and, when exposed to temperatures above 200 °C, undergo an intumescent reaction accompanied by the release of non-flammable gases, forming an expanded, charred layer with low thermal conductivity. This provides thermal insulation and acts as a physical barrier against heat, oxygen, and flammable volatiles. In this study, the applicability of several thermoanalytical techniques for evaluating the performance of three different intumescent coatings applied to spruce wood was investigated. Simultaneous thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) showed that coating No. 3 was the most efficient, initiating substrate protection at the lowest temperature and reducing the combustion enthalpy by approximately 50% compared to uncoated wood. DSC-microscopy visualization enabled direct observation of the intumescent expansion, degradation of the carbonized protective layer, and delayed thermal decomposition of coated wood. Furthermore, a comparison between TGA-MS and TGA-IST16-GC-MS demonstrated the superiority of chromatographic separation for identifying evolved gaseous products. While TGA-MS is effective for detecting small gaseous species (e.g., H₂O, CO₂, formaldehyde), TGA-IST16-GC-MS enables the deconvolution of many degradation products evolving simultaneously, allowing for distinction between flame-retardant-related species, polymer backbone fragments, nitrogen-rich heterocycles, and small oxygenated molecules in the most effective coating. Full article

The canopy temperature of winter jujube serves as a direct indicator of plant water status and transpiration efficiency, making its accurate prediction a critical prerequisite for effective water management and optimized growth conditions in greenhouse environments. This study developed a data-driven model to forecast canopy temperature. The model serially integrates a Long Short-Term Memory (LSTM) network and a Random Forest (RF) algorithm, leveraging their complementary strengths in capturing temporal dependencies and robust nonlinear fitting. A three-stage framework comprising temporal feature extraction, multi-source feature fusion, and direct prediction was implemented to enable reliable nowcasting. Data acquisition and preprocessing were tailored to the greenhouse environment, involving multi-sensor data and thermal imagery processed with Robust Principal Component Analysis (RPCA) for dimensionality reduction. Key environmental variables were selected through Spearman correlation analysis. Experimental results demonstrated that the proposed LSTM–RF model achieved superior performance, with a determination coefficient (R²) of 0.974, mean absolute error (MAE) of 0.844 °C, and root mean square error (RMSE) of 1.155 °C, outperforming benchmark models including standalone LSTM, RF, Transformer, and TimesNet. SHAP (SHapley Additive exPlanations)-based interpretability analysis further quantified the influence of key factors, including the “thermodynamic state of air” driver group and latent temporal features, offering actionable insights for irrigation management. The model establishes a reliable, interpretable foundation for real-time water stress monitoring and precision irrigation control in protected winter jujube production systems. Full article