Search Results (29,520)

The species Psychotria densicostata Müll.Arg. is a shrub belonging to the Rubiaceae family, endemic to Brazil. So far, there are reports neither of phytochemical work on nor of biological evaluation of it. This study investigated its alkaloid profile and evaluated the inhibitory effects of extracts, alkaloid-enriched fractions and one of its major constituents on human neutrophil elastase (HNE). The monoterpene indole alkaloids (MIAs) strictosidine (1), (3α,5α)-5-carboxystrictosidine (2), strictosidine lactam (3), lyaloside (4), lyalosidic acid (5), 5-carboxystrictosamide (6), 3,4-dehydrostrictosidinic acid (7), and N-glucopyranosyl vincosamide (8) were characterized in mixture, in its leaves, and/or stems by using an integrated approach combining nuclear magnetic resonance (NMR) techniques, high performance liquid chromatography coupled to a tandem mass spectrometer with an electrospray ionization source (HPLC-ESI-MS/MS), and molecular networks. The crude leaf extract and an alkaloid-enriched fraction derived from it showed inhibitory activity against HNE. These results contribute to the chemical knowledge of the species and suggest its potential biological property. Full article

Drought stress significantly constrains crop productivity and yield stability. Sorghum (Sorghum bicolor L. Moench), a C4 cereal widely cultivated in arid and semi-arid regions, exhibits high water-use efficiency and remarkable drought tolerance. Understanding both the impacts of drought and the plant’s response mechanisms is essential for enhancing drought resilience in this crop. In this study, physiological changes and differential protein accumulation were analyzed in leaves of the sorghum inbred line BT × 623 under 10% PEG-6000-induced drought stress. The physiological adaptation to drought was characterized by improved water retention and mitigation of oxidative damage through the synergistic action of antioxidant enzymes. Using two-dimensional electrophoresis (2-DE) and MALDI-TOF-TOF mass spectrometry, 43 protein spots were successfully identified, corresponding to 38 unique proteins differentially expressed under osmotic stress. These proteins function in diverse biological processes, including protein synthesis, processing, and degradation; photosynthesis; carbohydrate and energy metabolism; transcriptional regulation; stress and defense; lipid and membrane metabolism; and amino acid metabolism. Proteomic profiling revealed that the coordinated modulation of multiple functional groups, such as those involved in photosynthesis, energy metabolism, transcriptional adjustment, ROS scavenging, and protein turnover, underpins sorghum’s osmotic stress adaptation. These findings provide key insights into the drought resistance mechanisms of sorghum at both physiological and proteomic levels. Full article

RNA interference (RNAi) provides a sequence-specific strategy for pest management, but efficient and stable double-stranded RNA (dsRNA) delivery remains a key challenge. Here, we established a plant-probiotic-based gene silencing system using the endophytic fungus Fusarium commune G3-29 as a dsRNA delivery vector against western flower thrips (WFTs, Frankliniella occidentalis). Recombinant G3-29 strains expressing dsRNA targeting the essential WFT genes ACT and SNF were constructed and confirmed to colonize kidney bean leaves without pathogenicity. Bioassays showed that feeding on leaves colonized by dsRNA-expressing G3-29 significantly decreased survival and downregulated target gene expression in both WFT larvae and adults. Within 4 days, survival of both larvae and adults fell below 10%. In larvae, target gene expression decreased by 63% (ACT) and 33% (SNF), while in adults, reductions of 74% (ACT) and 65% (SNF) were observed. In contrast, in vitro-synthesized dsRNA failed to induce significant gene silencing or mortality in larvae, and its control efficacy against adults was also inferior to that of endophytic fungus-mediated dsRNA delivery. Our findings establish endophytic fungus F. commune G3-29 as an effective and sustainable dsRNA delivery vehicle for RNAi-based pest control, offering distinct advantages over existing strategies such as HIGS and SIGS. This approach provides a promising new direction for managing WFTs and other insect pests. Full article

Smart vehicles integrated with the Internet of Things (IoT) provide rich data for traffic management, safety, and liability services; however, existing blockchain-enabled vehicular architectures still struggle with consensus scalability, heavy centralized validation, limited interaction-based corroboration, incomplete attack coverage, and rapid ledger growth. In particular, many schemes either optimize single-layer consensus or embed detailed reputation information into every transaction, while pushing most validation to central servers. This leads to bottlenecks under dense traffic and leaves replay, Sybil-assisted 51% attacks on roadside units (RSUs), and man-in-the-middle tampering only partially addressed. In this context, this paper proposes a novel hierarchical blockchain for vehicular IoT (HBV-IoT) model to address the above challenges. An independent transaction for periodic vehicle status reporting and an interaction-based transaction for corroborating data between vehicles in proximity are presented. Three smart contracts are designed to automate the validation and processing of transactions, and to identify compromised or malicious vehicles within the HBV-IoT network. Algorithms for distributed consensus to accept transactions into the blockchain and for vehicle reputation management to enforce edge-level filtering and down-weighting of malicious nodes are implemented. Simulation results demonstrate significant improvements compared to conventional vehicular blockchain approaches, with performance gains validated by 95% confidence intervals. The model supports practical applications, including real-time traffic monitoring, automated e-challan issuance, intelligent insurance claim processing, and blockchain-based vehicle registration. Full article

Background: The systematic identification of transcriptional repressors remains challenging, as current inference frameworks are predominantly optimized for accessible chromatin, leaving regulatory signals embedded within repressive domains undercharacterized. Methods: Here, we present NuRepress, a computational framework that predicts candidate transcriptional repressors by integrating repressive chromatin architecture, functional signatures, and transcriptional outcomes. NuRepress first identifies well-phased nucleosome arrays within repressive chromatin. These arrays are treated as discrete structural units that capture characteristic local chromatin organization associated with regulatory activity. Since distinct Tn5 cut signal patterns often imply divergent regulatory functions, the framework stratifies these arrays into potential functional subtypes. By synthesizing the quantified repressive efficacy of each subtype with spatial motif enrichment and observed transcriptional dynamics, NuRepress systematically prioritizes and ranks candidate repressors. Results: Our analysis indicated that well-phased nucleosome arrays exhibited accessibility-defined organizational patterns with distinct repressive efficacies, and that these patterns were also observed across species, suggesting that the structural principles captured by NuRepress might extend beyond one specific biological system. Positional motif analysis revealed that distinct TFs exhibited different spatial preferences relative to well-phased nucleosome arrays, suggesting scale-specific preferences for their interactions with these organized chromatin structures. When applied to pancreatic cancer progression, NuRepress identified changes in nucleosome organization associated with stage-specific transcriptional remodeling, highlighting candidate repressors of key oncogenic drivers. Conclusions: NuRepress establishes a structure-aware strategy for repressor inference that extends regulatory genomics beyond accessibility-centered paradigms. By linking well-phased nucleosome organization to transcriptional outcomes, it provides a principled framework for dissecting transcriptional repression across diverse biological settings. Full article

The necrotrophic pathogen Sclerotinia sclerotiorum compromises the physiological and anatomical integrity of cotton, leading to substantial economic losses due to rapid tissue necrosis, stem blight, boll rot, and leaf wilting. In this context, the use of endophytic microorganisms emerges as a promising strategy for the biocontrol of white mold. This study tested the hypothesis that endophytic fungal strains isolated from the roots of Butia purpurascens, a palm tree endemic to the Cerrado biome, could mitigate disease symptoms in Gossypium hirsutum L. To evaluate this, cotton plants were subjected to biotic stress imposed by S. sclerotiorum to assess the effectiveness of seven fungal strains in attenuating disease. The impact of the pathogen was monitored through growth variables, gas exchange, leaf temperature, chlorophyll a fluorescence, antioxidant enzyme activity, proline and malondialdehyde (MDA) levels, and the incidence of rot in petioles, leaves, and flower buds. Overall, inoculation with endophytic fungi significantly alleviated the effects of the phytopathogen, promoting vegetative growth and optimizing physiological performance. Treated plants exhibited alleviated stress in primary photochemistry, reduced non-photochemical energy dissipation, and stable carbon fixation. Additionally, efficient modulation of the antioxidant system and preservation of anatomical structures were observed, minimizing the severe symptoms of white mold. Notably, the non-pathogenic strains BP10EF (Gibberella moniliformis), BP16EF (Penicillium purpurogenum), and BP33EF (Hamigera insecticola) acted as potent physiological modulators, yielding responses similar to those of healthy plants. These results highlight the biotechnological potential of these endophytic strains, which can be explored as both growth promoters and resistance inducers in cotton against white mold. Full article

While direct current (DC) ice-melting is currently adopted for some transmission lines, its application to 10 kV distribution transformers—often located in remote and rugged terrain—presents significant operational challenges. Disconnecting these transformers prior to ice-melting is a complex procedure that incurs substantial labor, material, and financial costs. Leaving transformers connected risks DC current flowing into idle windings, potentially causing damage. Furthermore, existing mobile DC ice-melting power supplies are bulky and impose stringent transportation requirements, rendering them unsuitable for use on mountain roads. To overcome these limitations, this paper proposes a compact, lightweight variable-frequency ice-melting device. The operating principle and output characteristics of the variable-frequency method are investigated in detail. Using Simulink, system modeling and simulation analyses are performed to obtain the voltage and current output characteristics, along with harmonic spectra. Simulation results demonstrate that the proposed device achieves significant miniaturization compared with conventional solutions: within the typical parameter range of conventional devices, the volume can be reduced by 44–58% and the weight by 43–52%. In addition, the selected LC filter parameters (L = 10.39 mH, C = 86.62 μF) represent an optimized compromise solution that effectively suppresses input harmonics while maintaining the output current total harmonic distortion (THD) within an acceptable limit of 3.6%. Experimental results further validate the feasibility of the variable-frequency ice-melting current. Based on a matrix converter topology, the proposed device enables flexible adjustment of the output melting voltage and frequency, exhibits excellent low-frequency performance and dynamic response, and maintains low output harmonic content—fully meeting the application requirements for variable-frequency ice-melting. The key novelty lies in a compact matrix-converter-based de-icing device with systematic low-frequency performance analysis, offering superior portability and adaptability over traditional DC solutions. Full article

Background/Objectives: With the acceleration of global industrialization and continuous population growth, the world is increasingly confronted with the dual challenges of food insecurity and cultivated land contamination. The screening and breeding of rice varieties with superior agronomic traits and low heavy metal accumulation have therefore become important strategies for ensuring food safety and sustainable agricultural production. Methods: In this study, rice varieties carrying the Gn1a-i gene and exhibiting specific cadmium (Cd) accumulation characteristics were screened using a combination of molecular marker detection and cadmium accumulation evaluation. Specific loop-mediated isothermal amplification (LAMP) primers targeting the Gn1a-i gene were designed and combined with a lateral flow dipstick (LFD) assay to enable rapid genetic screening of rice varieties. A six-day hydroponic experiment under cadmium stress was conducted across three temperature ranges (15–20 °C, 22–27 °C, and 30–35 °C), and cadmium accumulation in different plant organs (roots, stem sheath, and leaves) was analyzed. Results: Seven varieties carrying the Gn1a-i gene, including Xiangwanxian 12, were identified among ten tested rice varieties. Xiangwanxian 12 was subsequently selected for further evaluation, with the high-cadmium-accumulating variety Yuzhenxiang used as a control. At 144 h, the total Cd content in the measured organs of Xiangwanxian 12 was 9.6%, 4.0%, and 23.2% lower than that of Yuzhenxiang under low, medium, and high temperatures, respectively (one-tailed t-test, p < 0.01 for all three temperatures). Conclusions: The integration of LAMP-based genotyping and physiological evaluation provides a novel and reliable strategy for identifying low-Cd rice germplasm. Xiangwanxian 12, which carries the Gn1a-i allele and exhibits consistently lower Cd accumulation than Yuzhenxiang, suggests potential as a candidate for breeding high-yield, low-Cd rice cultivars. Full article

Cadmium (Cd) contamination is widely recognized as a major risk factor affecting the security and quality of crop production. Watermelon (Citrullus lanatus) is a globally cultivated fruit that is susceptible to Cd stress. 24-Epibrassinolide (EBR), an active brassinosteroid, is essential for plant growth and abiotic stress responses. However, its protective role in watermelon under Cd stress remains unclear. This study elucidates the physiological and molecular processes underlying EBR-mediated alleviation of Cd toxicity in watermelon seedlings. The results showed that exogenous EBR application effectively mitigated Cd-induced growth inhibition through decreased Cd deposition, reduced the accumulation of reactive oxygen species (ROS), lowered membrane lipid peroxidation, and increased antioxidant capacity in watermelon leaves under Cd treatment. Transcriptome (RNA-Seq) analysis revealed that EBR triggered substantial reprogramming of gene expression patterns, identifying 530 differentially expressed genes (DEGs) in Cd + EBR co-treatment compared with Cd treatment alone, including 204 down-regulated genes and 326 up-regulated genes. These DEGs are vital for controlling several physiological processes, including phenylpropane metabolism, phenylpropanoid biosynthesis, endoplasmic reticulum’s protein production, cell wall organization, and others. Further physiological assays confirmed that EBR increased the activities of PAL and 4CL, the core enzymes driving phenylpropanoid biosynthesis, leading to a significant accumulation of total phenols and flavonoids. Together, the above results give concrete proof of the powerful functions of 24-EBR, acting as an enhancer of plant performance under Cd stress by enhancing the antioxidant system and by activating the phenylpropanoid pathway and its derived metabolic networks. Full article

Contemporary emergency systems operate at the intersection of climate volatility, digital interdependence, and cascading institutional disruptions. Despite growing research on resilience, adaptive governance, and digital transformation, these fields remain largely disconnected, leaving a theoretical gap in explaining how emergency systems perform under compound uncertainty. This integrative review synthesizes 32 peer-reviewed articles (post-2020) using structured narrative methodology and VOSviewer bibliometric analysis to map the field’s intellectual architecture and identify its structural gaps. The analysis reveals six thematic clusters organized around resilience as the central construct, yet characterized by three recurring disconnections: the weak integration between digital transformation and governance theory, the operational underdevelopment of polycentric governance frameworks, and the temporal separation between emergency response and climate adaptation. Drawing on this structural diagnosis, the study advances the Complex Adaptive Governance (CAG) model—a three-layer framework encompassing systemic architecture, adaptive mechanisms, and operational resilience—in which digital interoperability functions as a cross-cutting accelerator. The CAG model reconceptualizes resilience as a relational property of governance ecosystems, enhanced by digital interoperability, and offers design principles for climate-resilient emergency systems aligned with SDG 9, SDG 11, SDG 13, and SDG 16. Full article

Liu Mu 劉牧 inaugurated the diagram-based paradigm of Yijing 易經 interpretation in the Song dynasty and restored the Hetu and Luoshu 河圖洛書 to the center of Yi studies 易學. Existing scholarship has approached his system primarily through the lens of xiang-shu 象數 structure or semiotics, frameworks that illuminate how his numerical diagrams function as interpretive tools while leaving unaddressed a more fundamental question: what grounds their authority. This article argues that attending to the religious dimensions of Liu Mu’s system opens a new line of inquiry by revealing how his numerological framework could function as a substantive ground of political and moral order in the intellectual culture of the Renzong 宋仁宗 reign. Liu Mu’s system operates on two interconnected religious levels. First, by anchoring moral and political norms in the objective order of cosmic numerology rather than in human convention, it furnishes a sacred foundation for ethical and political life that transcends arbitrary agreement. Second, by deliberately withholding Heaven’s One (tianyi 天一) from the yarrow-stalk method, it carves out, within an otherwise calculable rational order, an irreducible space for genuine encounter with cosmic mystery. The article further demonstrates that this strategy was shaped by the specific historical and institutional contexts of the early Song. Liu Mu’s enduring contribution lies in constructing a numerological system in which sacred authority and rational order are not opposed but mutually constitutive. Full article

Domestic and family violence (DFV) is a key driver of women’s homelessness and financial insecurity. In Australia, Safe at Home (SAH) programs have emerged as an innovative, wrap-around service response that increases victim-survivors’ safety by implementing a range of strategies and tools that enables them to remain in their home or a home of their choice. SAH responses represent one strategy that effectively prevents homelessness and mitigates the financial, social, and emotional disruption associated with housing relocation after leaving a violent and abusive relationship. This paper examines the implementation of SAH responses in Australia through a critical synthesis of national policy documents and published literature. The paper outlines the four nationally endorsed pillars of SAH (maximising safety, integrated responses, homelessness prevention, and economic security) and examines how these pillars shape service design and outcomes. Evidence from evaluations and outcome studies indicate that SAH can enhance women’s sense of safety, support housing stability, and reduce the financial burden of leaving a violent partner. Access and effectiveness vary depending on the design of the response and location. Challenges include limited affordable housing supply, inconsistent perpetrator accountability, and structural barriers to long-term economic security. Sustained investment in SAH programs, robust data collection mechanisms, and stronger integration of housing and economic supports are ultimately needed to ensure SAH can fulfil its potential as a core component of Australia’s DFV service system. Full article

Pedestrian interaction remains a central safety challenge for autonomous driving, particularly under non-compliant or adversarial pedestrian behavior. Existing research and evaluations predominantly test against rule-following pedestrians, leaving a gap in understanding how learning-based agents handle worst-case interactions. We introduce the Jaywalkers Library, a novel configurable benchmark in CARLA with three adversarial pedestrian archetypes (Intruder, Indecisive Crosser, and Protester). We evaluate a DreamerV3 agent trained with sparse rewards, where the only pedestrian-specific signal is a terminal collision penalty. Evaluation employs a frozen-policy protocol with explicit train–test separation. Safety behavior is decomposed into endpoint outcomes, evasion dynamics, and efficiency costs. Under nominal conditions, the agent achieves high route completion and generalizes to an unseen town, whereas under adversarial exposure, an archetype-sensitive evasion strategy emerges. The agent swerves at speed against dynamic pedestrians but decelerates against the slow-moving Protester. Collision rates reveal a counterintuitive difficulty ordering in which the Protester is the hardest, followed by the Intruder, with the Indecisive Crosser as the most survivable. These findings show that a sparse terminal penalty suffices for emergent pedestrian avoidance in a world-model agent, but that effectiveness is bounded by the world model’s ability to predict pedestrian persistence. Full article

Wheat productivity and grain quality are strongly influenced by nutrient management and soil moisture availability. Nitrogen (N) and potassium (K) regulate biomass production, physiological stability and grain protein development. However, their efficiency varies under water-limited conditions. This study aimed to evaluate how soil moisture modulates nitrogen–potassium efficiency, nutrient partitioning, physiological responses and grain quality development in wheat. The current experiment was planned to assess the impact of varying but combined levels of N and K fertilizers on wheat crop growth and yield components as well as nutrient uptake and grain quality under different irrigation levels (i.e., normal irrigation Field Capacity (FC) 100%, partial water deficit FC75%, moderate water deficit FC50%, severe water deficit FC25%). The results of the study showed that increasing N-K supply enhanced biomass, chlorophyll contents, nutrient accumulation and grain quality under full irrigation, with N2K2 showing the highest growth, yield and quality traits. Under moderate deficit, N2K1 maintained a relatively stable yield and physiological performance, whereas severe moisture limitation markedly reduced nutrient uptake, grain development and fertilizer efficiency despite a higher NK application. Progressive reductions in irrigation also altered nutrient distribution among leaves, straw and grain, indicating moisture-regulated remobilization during grain filling. Maximum increments in values for plant height (27%), total biomass (108%), grain yield (183%), grain NPK content (38%, 6.3%, 26%), grain protein (38%) and wet gluten (38%) were noted in the N2K2 treatment at FC100%, but these parameters showed up to 80% reduction under the same treatment of N-K at FC25%. It is concluded that wheat response to N–K fertilization was moisture dependent and fertilizer rate alone did not ensure productivity under severe water deficit. Therefore, integrating nutrient supply with irrigation management is essential to sustain productivity and grain quality. Full article

The Changbai Mountain Forest Region contains one of the best-preserved mountain forest ecosystems in eastern Asia and serves as a critical ecological barrier in China. Using the Baihe Forestry Bureau as the study area, this research quantified forest surface fire behavior, and based on the historical wildfire occurrence data and the forest fire spread trends, proposed targeted strategies for fire prevention and emergency resource allocation. Forest fires in the coniferous and broad-leaved mixed near-mature forest pose the greatest threat to the region. The establishment of five supply storages in five strategic locations and the construction of new firebreak roads are essential for effective fire management in the Baihe Forestry Bureau. Full article