Search Results (8,854)

This study presents a comprehensive bibliometric analysis of research trends in grain cleaning devices from 1998 to 2025. Grain cleaning equipment plays a critical role in post-harvest processing by improving grain quality, reducing losses, and enhancing overall efficiency in agricultural systems. The analysis is based on bibliographic data retrieved from the Scopus database. Various bibliometric tools and indicators, including publication trends, citation analysis, co-authorship networks, and keyword co-occurrence, were employed to identify patterns of development, major contributors, and emerging research themes in this field. The results reveal a significant growth in publications in recent years, reflecting increasing global interest in advanced cleaning technologies, including energy-efficient systems, intelligent sorting, and automation. Key research hotspots include vibration-based separation, pneumatic systems, and smart sensor-based cleaning technologies. This study provides a systematic overview of the intellectual structure and evolution of grain cleaning device research, offering valuable insights for researchers and practitioners. The findings also highlight existing research gaps and suggest future directions for the development of more efficient, sustainable, and intelligent grain processing technologies. Full article

Usnic acid (UA), a prominent lichen secondary metabolite, exhibits a unique dual therapeutic profile in dermatology, though its clinical translation is limited by systemic hepatotoxicity and poor solubility. This review comprehensively evaluates the topical efficacy, molecular mechanisms, and advanced formulation strategies of UA enantiomers and UA-rich extracts. A literature search across PubMed, Scopus, and Google Scholar identified 36 original publications focusing on anti-melanoma activity, photoprotection, and tissue regeneration. In vitro studies demonstrate that UA induces apoptosis in resistant melanoma cell lines (A375, HTB-140) via extrinsic/intrinsic pathways, with (−)-UA effectively overcoming doxorubicin resistance. Conversely, in non-cancerous models, low concentrations of UA accelerate wound and burn healing by upregulating vascular endothelial growth factor (VEGF), stimulating fibroblast proliferation, and optimizing extracellular matrix remodeling while preventing hypertrophic scarring. To mitigate skin sensitization and systemic risks, advanced drug delivery systems—including liposomes, nanoemulsions, chitosan nanogels, and electrospun scaffolds—have been developed, significantly enhancing skin permeability and localized dermal retention. Ultimately, the development of bio-functionalized smart dressings and targeted nano-formulations represents the most viable path toward unlocking the full clinical potential of UA in modern dermatological and oncological care. Full article

Cellular senescence is a state of stable cell cycle arrest triggered by various internal and external stressors. It represents an important tumor-suppressive mechanism that effectively prevents the proliferation of damaged cells. During tumor initiation and progression, cellular senescence plays a dual and paradoxical role. On one hand, it induces cell cycle arrest to inhibit the development of tumors in potentially malignant cells. On the other hand, it can promote tumor progression through the senescence-associated secretory phenotype (SASP), which enhances inflammation and extracellular matrix remodeling. This review outlines the definition and key characteristics of cellular senescence and analyzes different senescence-inducing stimuli along with their underlying molecular mechanisms. It further discusses the molecular basis for the maintenance of stable senescence, mechanisms to escape growth arrest, and how these cells contribute to tumor recurrence through dedifferentiation and acquisition of stemness properties. Additionally, the dual regulatory role of SASP in tumor progression is examined. In terms of cancer therapy, with a deeper understanding of the mechanisms of senescent cells, treatment strategies are gradually shifting from single senescence-inducing approaches to more comprehensive combinatorial strategies. Meanwhile, the integration of single-cell omics technologies with artificial intelligence and machine learning offers new prospects for personalized therapy. Full article

Selenium is an essential micronutrient for humans, underscoring its importance in enhancing the nutritional and physiological attributes of agricultural and horticultural crops through exogenous application. At low doses, selenium improves growth and development, and increases crop yield and quality, particularly under stress conditions. It is believed that abscisic acid and sucrose work together to regulate strawberry (Fragaria × ananassa Duch.) fruit ripening. This study aimed to provide comprehensive biochemical and molecular insights into the selenium mediated effects on ripening and quality changes in ‘Camarosa’ strawberry fruits. Selenium treatment increased chlorophyll levels in leaves, suggesting a positive impact on overall plant health. Foliar application of 1 mM selenium significantly accelerated ripening. Treated fruits exhibited higher levels of total soluble solids, along with a decrease in titratable acidity. About lipid peroxidation indices, foliar application of 1 mM selenium decreases hydrogen peroxide and malondialdehyde. Consistently, flavonoids, phenolic compounds, anthocyanins, ascorbic acid, and antioxidant capacity, as well as the activity of the enzymes SOD, CAT, APX and PAL, were increased by selenium treatment. Interestingly, the ABA content in strawberry fruits also increased with selenium treatment. The selenium treatment upregulated genes involved in abscisic acid biosynthesis, phenolic compound biosynthesis, and anthocyanin production, namely, FaNCED1, FaG2BD, FaCHS, FaPAL, and FaSUT1. This study highlights the potential of selenium as a biostimulant and quality-enhancing agent in strawberries, improving fruit biochemical composition and ripening dynamics while contributing to better nutritional value and market appeal. Full article

Low temperature is a major environmental factor influencing the reproductive performance of crustaceans, particularly during gonadal development. This review synthesizes current knowledge on the phenotypic, physiological, and molecular responses of crustaceans to cold stress, with a focus on its regulatory effects on gonadal development. Available evidence indicates that low temperature generally delays gonadal maturation, reduces the gonadosomatic index, impairs oocyte development and yolk deposition, and suppresses spawning. Mechanistically, cold stress induces energy limitation and triggers a growth–reproduction trade-off, in which resources are preferentially allocated to survival and somatic maintenance rather than reproductive investment. This process is closely associated with lipid metabolism remodeling, mitochondrial dysfunction, and altered ATP-dependent energy sensing. At the molecular level, several pathways and regulatory factors are involved, including PI3K–Akt–FoxO, AMPK/mTOR, heat shock proteins, vitellogenin and its receptor, cell cycle regulators, antioxidant defense systems, and neuroendocrine mediators such as MIH, MOIH, and ecdysteroids. Emerging evidence also suggests potential roles for epigenetic regulation and species- or population-specific adaptation in shaping reproductive responses to low temperatures. Overall, this review provides an integrated framework for understanding how cold stress modulates crustacean gonadal development and highlights key directions for future studies and aquaculture applications. However, a comprehensive framework integrating energy metabolism, neuroendocrine signaling, and molecular pathways to explain reproductive suppression under cold stress is currently lacking. Full article

This study aims to address the need to operationalize Industry 5.0 (I5.0) by developing a comprehensive Assessment Framework for the adoption of the Human Centricity, Environmental Sustainability, and Industrial Resilience pillars. While existing models largely focus on technological maturity, they fail to provide measurable tools for evaluating I5.0 adoption. To bridge this gap, the paper proposes an Assessment Framework based on a structured set of Key Performance Indicators (KPIs) developed within the EU-funded PROSPECTS 5.0 project. The methodology combines an extensive literature review, a workshop with relevant stakeholders, a Delphi survey with experts, and empirical refinement conducted through workshops involving 14 companies across multiple sectors and of varying sizes. The results highlight that organizations predominantly measure traditional indicators such as health and safety, energy consumption, and supply chain robustness, while underestimating emerging dimensions such as human empowerment, social inclusion, circularity, and advanced human–machine collaboration. The framework introduces a set of KPIs for each of the I5.0 pillars, supporting structured assessment across different industrial contexts while allowing sector-specific adaptation. The findings reveal a gap between the perceived importance of several sustainability and human-centric metrics and their actual implementation. This framework allows organizations to self-assess their practices, guide strategic decisions, and align technological growth with societal and environmental goals. Full article

The measurement and improvement of urban land use efficiency (ULUE) are crucial for sustainable development in China’s Canal Cities (CCCs). Drawing on the theories of production factors, spatial externalities, and agglomeration economy, this study proposes a framework that explicitly addresses the trade-offs and synergies of sustainable land use. A comprehensive ULUE evaluation index system was established. The super-SBM (Slack-Based Measure) and Global Malmquist–Luenberger (GML) index models were employed to assess the green efficiency of urban land use from 2002 to 2023, while Kernel Density Estimation (KDE) and the optimal parameters-based geographical detector (OPGD) model were used to investigate the spatiotemporal evolution and influencing factors of ULUE. The results reveal a distinctive V-shaped trend in efficiency, marked by significant spatial disequilibrium and predominantly technology-driven sustainable growth. Furthermore, ULUE exhibits a spatial distribution characterized by bipolar and multipolar differentiation, accompanied by concurrent concentration and dispersion, with high-value clusters dominating the spatial clustering type. Government regulation emerges as the dominant factor influencing ULUE, underscoring the pivotal role of policy intervention in guiding the sustainable development of land use. The interactions among pairs of influencing factors strengthened over time; notably, the interaction between government regulation and other factors is the strongest. Four-quadrant analysis profoundly reveals the underlying mechanism, distinguishing a high-quality, sustainable development model driven by technological innovation and a resource-dependent economic growth model. The findings provide valuable insights for promoting green development and formulating sustainable land use policies in CCCs. Full article

Citrus fruits are widely cultivated all over the world. Due to climatic conditions, citrus fruits are frequently exposed to periodic low temperatures, which poses a serious threat to their yield and quality. Cold not only restricts plant growth and deteriorates fruit quality but also leads to fruit abscission and tree mortality, posing severe constraints on large-scale citrus production. The TIFY family gene plays crucial roles in plant development and stress adaptation. However, the genome-wide identification and functional analysis of TIFY genes in cold stress adaptation of citrus plants remain largely unexplored. Here, we performed a systematic genome-wide analysis of the TIFY family in sweet orange (Citrus sinensis (L.) Osbeck) and identified 14 CsTIFY members. We conducted a comprehensive study on the protein characteristics, phylogenetic relationships, gene structure, chromosome distribution, promoter cis-acting elements, and subcellular localization of these genes. Phylogenetic analysis classified the CsTIFYs into ZML (ZML1–ZML4), JAZ (JAZ1–JAZ7), PPD (JAZ8, JAZ9), and TIFY (TIFY1) subfamilies, and they are distributed on seven chromosomes. Collinearity analysis revealed that segmental duplication is the primary driver for CsTIFY family expansion. Expression profiling under cold stress identified JAZ1, JAZ2, and JAZ3 as the most cold-inducible members. All three CsTIFY proteins are targeted to the nucleus, as confirmed by subcellular localization analysis. Overexpression of JAZ1, JAZ2, or JAZ3 in citrus calli significantly enhanced cold sensibility. Collectively, this study elucidates the gene function of CsTIFYs under cold stress and provides new insight for molecular breeding of cold-tolerant citrus varieties. Full article

The gut microbiota and its metabolites, as components of the gut–bone axis, play a pivotal role in regulating skeletal homeostasis through the bidirectional communication network. In this systematic review, evidence was collected from mainstream databases following standardized inclusion/exclusion criteria for screening, to comprehensively retrieve and screen eligible studies from multiple mainstream databases according to standardized inclusion and exclusion criteria, and systematically summarize current research progress on plant-derived bioactive compounds targeting the gut–bone axis for skeletal health regulation. This review systematically explores the underlying mechanisms of the gut–bone axis and critically evaluates the regulatory effects and therapeutic potential of plant-derived bioactive compounds. Particular attention is given to targeted interventions involving prebiotics, probiotics, synbiotics, and plant-rich diets or functional foods. Among these interventions, synbiotics represent the most successful strategy and show the most prominent therapeutic possibilities in bone-related disorders. Different from single prebiotics (only nourish endogenous intestinal microbes), individual probiotics (easy to be degraded in gastrointestinal tract with poor colonization) and ordinary plant-rich diets (unfixed effective dosage and weak targeting property), synbiotics combine prebiotic carriers and viable probiotic strains to produce complementary advantages, which is the core reason for its outstanding therapeutic prospect against bone diseases. Synbiotics exert synergistic effects on gut microecology, mineral absorption, and immune regulation, leading to more robust and consistent improvements in bone health than single prebiotics, probiotics, or general plant-rich diets. They have been verified in preclinical and clinical studies to ameliorate osteoporosis and related skeletal diseases via the gut–bone axis. These strategies offer novel insights into the prevention and treatment of bone metabolic disorders, such as osteoporosis, by targeting the gut–bone axis with phytochemicals. Key outcomes of this review include that synbiotics, soy isoflavones, naringin, curcumin, and resveratrol effectively improve bone mineral density, restore gut microbiota balance, and inhibit pathological bone resorption via the gut–bone axis. Collectively, the above bioactive substances realize bone protection mainly by reshaping gut flora, elevating mineral uptake and suppressing excessive osteoclast activity. Representative cases include soy isoflavones mitigating estrogen-deficient bone loss in OVX models, naringin improving the trabecular microarchitecture, and probiotic BL-11 promoting longitudinal bone growth in children. Future directions will focus on clarifying dose–response relationships, developing standardized synbiotic formulations, constructing microbiome-guided precision diets, and conducting large-sample randomized controlled trials to translate plant-derived compounds into clinical therapies. Full article

Although the Kazakh horse is a dual-purpose breed renowned for both milk and meat production, the extent to which surgical castration alters gene expression in its muscles has not yet been fully elucidated. In this study, left longissimus dorsi muscle (LDM) samples were obtained from six Kazakh stallions (W group) and six Kazakh geldings (S group) to comparatively evaluate meat quality parameters, examine histological characteristics in tissue sections, and apply transcriptomic profiling to comprehensively explore the principal regulatory pathways and candidate genes through which surgical castration modulates LDM growth. The results demonstrated that surgical castration did not induce significant alterations in meat color or pH-related parameters. However, cooking loss and shear force values were markedly diminished, accompanied by a marked decrease in muscle fiber cross-sectional area. Transcriptomic analysis identified 848 differentially expressed genes (DEGs) in total, comprising 415 upregulated and 433 markedly downregulated DEGs, which were predominantly enriched in key biological pathways, including actin cytoskeleton regulation. Moreover, eleven core candidate genes, including MYL2, MYL3, and TNNI1, were further screened and identified. Full article

Runway systems serve as the critical interface between airports and terminal airspace, and their efficient operation is essential for balancing air traffic demand and airport capacity. With the continuous growth of air traffic, intelligent runway demand and capacity management has become increasingly important for mitigating congestion and delays. This paper presents a comprehensive review of runway capacity–demand management from both supply-side and demand-side perspectives. On the supply side, runway configuration selection is reviewed, including runway configuration capacity envelopes, influencing factors, and existing optimization methodologies, such as prescriptive models, descriptive models, and reinforcement learning approaches. On the demand side, flight runway sequencing for arrivals, departures, and integrated arrival–departure operations is systematically analyzed. Problem analogies, operational characteristics, optimization objectives, and solution algorithms are discussed in detail. A critical comparison of existing methodologies is conducted from the perspectives of solution quality, real-time capability, human interpretability, technology readiness, trust requirements, and human–AI collaboration. Finally, future research directions are identified, including integrated runway management, multi-airport coordination, uncertainty-aware optimization, human–AI decision support, AI-enabled runway management, and integrated manned–unmanned operations. The review provides a reference for researchers, airport operators, air navigation service providers, and decision-support system developers seeking to improve runway operational efficiency and safety. Full article

The rapid growth of web-based services has intensified the need for reliable mechanisms to distinguish malicious Uniform Resource Locators (URLs) from legitimate ones. Phishing campaigns, malware distribution networks, and defacement operations increasingly rely on deceptive web addresses to compromise unsuspecting users and critical infrastructure. Accurate URL classification plays a critical role in mitigating phishing attacks, malware distribution, and other cyber threats. This study presents a machine learning framework for detecting malicious URLs in cybersecurity applications. This study presents a comprehensive empirical evaluation of multiple machine learning and deep learning approaches for URL classification under two experimental settings: training with the complete feature set and training with a reduced subset obtained through Particle Swarm Optimization (PSO). The framework incorporates advanced feature engineering techniques that capture domain-specific characteristics of malicious URLs. Seventeen classifiers, encompassing traditional ensemble methods, neural architectures, and hybrid stacking configurations, were evaluated on a publicly available dataset of 651,191 URL samples retrieved from Kaggle. The PSO reduced the original ten-feature space to seven discriminative features, representing a 30% dimensionality reduction. Experimental results demonstrate that all-feature models consistently outperformed their PSO-reduced counterparts, with Random Forest achieving the highest classification accuracy of 91.90% and an F1-score of 0.9165. The findings offer empirical grounding for the design of computationally efficient URL threat detection systems and provide actionable directions for future research in adversarial machine learning and real-time cybersecurity pipelines. Full article

Head and neck squamous cell carcinoma (HNSCC) remains one of the most aggressive and heterogeneous malignancies worldwide, characterized by high rates of locoregional recurrence, metastatic dissemination, and therapeutic resistance. Angiogenesis plays a central role in tumor progression by supporting vascular remodeling, hypoxia adaptation, invasion, immune evasion, and metastatic spread. In HNSCC, angiogenic activation is regulated through complex interactions involving hypoxia-inducible factors, vascular endothelial growth factor (VEGF) signaling, stromal remodeling, inflammatory pathways, and epigenetic mechanisms within the tumor microenvironment. Recent evidence has also highlighted the role of non-coding RNAs, particularly microRNAs, and exosome-mediated communication in modulating angiogenic and immune-related signaling pathways. Although antiangiogenic therapies, including monoclonal antibodies and tyrosine kinase inhibitors, have demonstrated biological activity in HNSCC, their clinical efficacy remains limited by tumor heterogeneity, adaptive resistance mechanisms, toxicity, and the lack of validated predictive biomarkers. Several emerging therapeutic strategies are under preclinical or early clinical investigation in HNSCC, including miRNA-based approaches, nanoparticle-assisted delivery systems, vascular normalization concepts, and combinations with immune checkpoint inhibitors; however, robust clinical evidence for most of these strategies remains limited, and their translation to routine practice requires further validation. This review provides a comprehensive overview of the molecular mechanisms regulating angiogenesis in HNSCC and critically discusses current and emerging pharmacological strategies targeting these pathways. Particular emphasis is placed on VEGF/VEGFR signaling, the integration of miRNA and exosome biology, resistance mechanisms, and translational perspectives for biomarker-guided personalized therapy. The novelty of this review lies in the systematic integration of miRNA- and exosome-mediated angiogenic regulation, therapeutic resistance pathways, and precision medicine strategies into a unified pharmacological framework, addressing gaps not fully covered by prior reviews focused primarily on VEGF-targeted agents. Full article

In the context of global population growth and intensifying climate change, ensuring food security remains a critical challenge. Orchards are more productive than arable crops, contributing significantly to the nutrition of a growing population. Ecologically, due to the absence of frequent soil tillage, orchards resemble natural forest ecosystems more closely than other agricultural systems. Irrigated orchards are particularly productive and enhance biodiversity in territories where water scarcity is the limiting factor for ecosystems. This review, the result of extensive reflection and a comprehensive analysis of the literature on orchard sustainability, synthesizes evidence on the diverse ecosystem services provided by these perennial systems. Due to their structural complexity, well-managed orchards contribute significantly to climate regulation through carbon sequestration, microclimate cooling, and soil erosion prevention. Furthermore, they support nutrient cycling and provide cultural value. This paper establishes an integrated scientific framework to inform evidence-based policies and reshape societal perceptions. It argues that recognizing orchards as multifunctional landscapes, rather than mere resource consumers, is critical for environmental resilience, supporting their fair valuation as essential components of a sustainable bioeconomy. Full article

Optical modules serve as the core transmission interfaces for artificial intelligence computing networks and digital communications. In recent years, demand for these modules has experienced explosive growth. During mass production, the requirements for the accuracy of surface defect detection and noise resistance have continued to rise. Existing POL detection models are susceptible to environmental noise interference; effective defect information is easily overwhelmed by noise entropy, and these models exhibit a high false negative rate for low-contrast and minute defects. This paper proposes a traditional image processing detection scheme that incorporates information entropy constraints. All experimental samples were collected from actual industrial mass production lines. The core process includes: noise suppression during the calibration stage using an entropy-weighted Hough transform; Canny edge detection combined with local entropy filtering for contour localization; and defect fusion recognition based on Hu similarity matching and entropy difference verification. Experimental results show that, compared to traditional POL methods, the proposed approach (WOMC) achieves an average improvement of 35.77% in image clarity and approximately a 2.25-fold increase in detection rate under Gaussian and salt-and-pepper noise conditions. According to statistical analysis of the experiments, this method achieved an accuracy of 96.67%, a recall rate of 97.32%, and a false positive rate of 3.31% in defect detection. In addition, the comprehensive performance score of this detection model reached 96.99%. Moreover, it does not require the deployment of deep-learning models, has a low computing power cost, and is suitable for the detection requirements of large-scale mass production. Full article