Search Results (8,301)

Innovations in agricultural sciences have created opportunities for a multidisciplinary approach to explain the major reasons for yield reductions under low-cost production conditions. The aim of this review is to synthesize recent advances and explain the relationship between economic injury level (EIL) and economic threshold (ET) in the contexts of food security and agri-food value chain risk management, including pre- and post-harvest stages. Modern integrated pest management (IPM) frameworks show that pest density must never be evaluated in isolation. The presence, abundance, and effectiveness of natural enemies significantly alter the likelihood that a pest population will reach the EIL. Modern food-security strategies increasingly incorporate digital innovations that enhance ET accuracy. Results of cost-benefit analysis evaluated whether the economic value of preventing crop losses outweighs the costs associated with control actions. This information is important in that it involves comparing expected yield savings, derived from preventing pest populations from reaching damaging levels, with management of the expenses of intervention and potential environmental or ecological trade-offs. The study recommends the use of artificial intelligence (AI) models to coordinate climate and economic data to predict biological consequences associated with the main threats to sustainable food systems. Full article

The purpose of this review was to evaluate the current literature using plane-based analyses to describe open-chain proximal-to-distal sport motions and to clarify how these approaches can extend to other activities to advance biomechanical assessment. Open-chain sport motions typically rely on a coordinated rotational axis that allows momentum to be transferred efficiently through the kinetic chain. Although this directional organization is central to performance, most biomechanical studies have relied on discrete, event-based variables rather than modeling the continuous trajectory structure of the movement. This review summarizes applications of motion-plane models in sports and discusses how their conceptual foundations can apply to other movements. Four primary approaches for deriving optimal-fit planes from three-dimensional trajectories are described: Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Orthogonal Least Squares (OLS), and the Functional Swing Plane (FSP). These methods rely on different algebraic formulations to model kinematic trajectories. By comparing their mathematical foundations, strengths, and limitations, we highlight how plane-based models provide a meaningful perspective for examining movement efficiency, movement strategy, and potential injury risk across open-chain proximal-to-distal sports. Future research should apply these models across multiple sports to generate individualized trajectory planes, quantify plane deviation, and integrate measures of joint loading and performance, and may combine models to build motion planes. Full article

Nuclear Factor Y (NF-Y) transcription factors play pivotal roles in plant adaptation to abiotic stress, yet their genomic landscape and functional mechanisms in cabbage (Brassica oleracea var. capitata L.) remain underexplored. Here, we performed a genome-wide identification of the NF-Ys in cabbage, identifying 53 BoNF-Ys classified into three subfamilies: 20 BoNF-YAs, 22 BoNF-YBs, and 11 BoNF-YCs. Phylogenetic clustering revealed evolutionary conservation with their Arabidopsis orthologs. Domain analysis revealed that all BoNF-YA members contain the CBF_NF-YA domain, while all BoNF-YB and BoNF-YC members possess the CBFD_NFYB_HMF conserved domain. The BoNF-Y genes were named according to their chromosomal locations. Bioinformatic analysis showed that BoNF-Y proteins range in size from 131 to 642 amino acids, with molecular weights of 14.82–73.18 kDa, theoretical pI values of 4.57–9.96, instability indices between 33.02 and 73.48, aliphatic indices of 45.3–86.26, and grand average of hydropathicity (GRAVY) values ranging from −1.139 to −0.367. Promoter cis-element profiling uncovered stress- and hormone-responsive motifs, including abscisic acid-responsive elements (ABREs), TC-rich repeats, and ethylene-responsive elements (EREs). RNA sequencing (RNA-seq) and quantitative reverse transcription polymerase chain reaction (qRT-PCR) conducted under salt stress (256 mM) identified three salt-responsive candidate genes (BoNF-YA14, BoNF-YB9, and BoNF-YC8). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses highlighted significantly expressed genes’ roles in MAPK signaling, proline metabolism, and phytohormone transduction pathways. This study conducted a comprehensive survey of the BoNF-Y gene family in cabbage. It could serve as a theoretical foundation for further functional identification and utilization of BoNF-Y family members and their role in the interaction between cabbage and salt stress. Full article

This study investigates the predictability of Environmental, Social, and Governance (ESG) performance using financial fundamentals within the context of Taiwan, a prominent small open economy integrated into global value chains. As global markets transition toward mandatory sustainability reporting, identifying the financial ante-cedents of ESG outcomes is critical for risk management and regulatory oversight. Uti-lizing a decade of firm-level data (2014–2023) from the Taiwan Economic Journal (TEJ), we employ supervised machine learning (ML) architectures-including Decision Tree, Random Forest, and Extreme Gradient Boosting (XGBoost)-to classify firms into ESG performance tiers based on indicators such as profitability, valuation, and scale. Our empirical results provide robust support for the Slack Resources Hypothesis, identifying Return on Assets (ROA) and Firm Size (SIZE) as the most consistent predictors of ESG excellence across the semiconductor, cement, and steel sectors. Conversely, mar-ket-based indicators (Tobin’s Q) dominate predictive models for the financial industry. Methodologically, XGBoost delivers superior predictive calibration for the financial sector, while Decision Trees offer highly interpretable threshold-based logic for risk screening. Our study contributes a transparent “early-warning” framework, enabling investors and regulators to identify sustainability risks through auditable financial benchmarks. The findings suggest that while financial latitude is a structural prerequisite for ESG engagement, it is not its sole determinant, pointing toward a “virtuous circle” of financial health and managerial quality. Full article

Global demand for animal protein necessitates sustainable alternatives to soybean meal (SBM). This systematic review evaluated 177 peer-reviewed articles (2002–2023) across 12 categories to analyse the nutritional value of alternative protein sources for ruminant diets and to assess the associated environmental trade-offs. This was achieved through a targeted review, synthesising data from Life Cycle Assessments (LCAs) to create a multi-criteria matrix for ranking sustainability profiles. Results indicate that microalgae, insects, and single-cell proteins exhibit crude protein levels comparable to SBM. Moreover, insects, seaweeds, and animal by-products (ABPs) often present superior essential amino acid profiles and high intestinal digestibility. From an environmental perspective, insects, seaweeds and microalgae offer excellent land-use efficiency and significant enteric methane mitigation (17–74.6%), though current economic viability is hindered by high processing costs and emerging supply chains. Conversely, ABPs and agro-industrial by-products effectively embody circular economy principles, enhancing local system resilience. Ultimately, replacing SBM requires a multi-objective approach through a functional hybridisation model, carefully balancing metabolic efficiency with environmental sustainability. While microalgae, insects, and seaweeds demonstrate promising nutritional and mitigation potential, addressing economic barriers and ensuring biosecurity seems essential. Future LCA frameworks should prioritise bioavailable nutrient metrics to optimise the environmental impact of ruminant production. Full article

Heritage education is increasingly expected to connect past evidence with questions of responsibility, environmental change, and sustainable futures, yet primary learners often encounter heritage through fragmented, visually driven exposure with limited support for interpretation beyond factual recognition. This mixed-methods study applies an SRT framework (Supply–Response–Transformation) to examine early, sustainability-relevant meaning-making in primary heritage learning supported by a short animation-based digital story, with an industrial heritage site serving as the case context. Evidence includes stakeholder interviews (n = 39), a student pre-test (n = 399), a post-viewing survey (n = 452), student drawings (n = 12), and classroom observations. Findings indicate that narrative-visual mediation aligns with students’ reported curiosity and comprehension-related cues under classroom conditions, and that post-viewing responses cluster around four classroom-observable outcome signals: valued historical understanding, responsibility and care, change–consequence–restoration reasoning, and personal and cultural positioning. This study interprets digital storytelling as a classroom-feasible mediation format through which meaning-making signals become observable in early meaning-making beyond factual recall. It provides an interpretable chain for judging the visibility and elaboration of early meaning-making signals under real classroom constraints. Full article

Artificial intelligence is transforming global resource systems and reshaping the foundations of corporate governance. This paper develops the Architecture of Intelligent Governance (AIG), a hybrid governance framework that integrates AI-enabled analytical capabilities with human judgment, ethical reasoning, and strategic foresight. Drawing on evidence from energy systems, supply chains, critical mineral dependencies, agribusiness, and emerging quantum-computing infrastructures, the analysis demonstrates how AI enhances forecasting precision, strengthens transparency, and supports more adaptive decision-making in environments characterized by volatility and interdependence. At the same time, the paper introduces a criticality perspective to examine the systemic risks associated with AI, including energy intensity, technological concentration, and algorithmic opacity. These risks underscore the need for leadership models that extend beyond technical expertise to encompass interpretive judgment, ethical stewardship, cultural competence, and long-term strategic thinking. The unified leadership framework presented here positions leadership as the human anchor of intelligent governance, ensuring that AI-enabled decisions remain aligned with organizational values and societal expectations. The AIG model offers a comprehensive approach to governing AI-intensive systems, advancing a vision of corporate governance that is resilient, transparent, and oriented toward long-term sustainability. Full article

Background/Objectives: The 3-ketoacyl-CoA synthase (KCS) enzyme is a key and rate-limiting component in the biosynthesis of very long-chain fatty acids (VLCFAs). Through controlling VLCFA production, KCS plays an essential role in plant cuticle formation. The necrotrophic fungus Botrytis cinerea can infect all aboveground parts of rose plants (flowers, leaves, and stems), causing severe economic losses. KCS restricts pathogen invasion by influencing cuticle formation and enhances tolerance to environmental stresses. While the KCS gene family has been well-studied in some plants, it remains unexplored in rose (Rosa × hybrida Hort.), a species of significant ornamental and economic value. Methods: In this study, we conducted a genome-wide analysis of the RcKCS gene family in rose, identifying 18 non-redundant genes. Phylogenetic, structural, and synteny analyses were performed to investigate the evolutionary relationships, gene architecture, and duplication events. The expression patterns of RcKCS genes in rose petals during Botrytis cinerea infection were examined, and transient overexpression and silencing of RcKCS6 were used to study its function. Results: RcKCS6 was found to be upregulated during gray mold infection, and transient overexpression reduced lesion size on infected petals. Conclusions: Our study provides the first comprehensive analysis of the RcKCS gene family in rose and highlights RcKCS6 as a potential candidate for improving resistance to gray mold in rose through molecular breeding. Full article

Muscular fitness is a key component of health and athletic performance, and isometric strength is a widely used indicator. This study reports an agreement-based validation of the Isometric Strength Measurement Device (ISOMETRO) for upper-limb isometric tension measurements under controlled laboratory conditions. Twenty-one healthy young amateur rock climbers (11 men and 10 women) performed four upper-limb tensile tests (shoulder adduction at 90°, shoulder adduction at 60°, shoulder extension at 90°, and elbow extension at 90°). Agreement with an independent criterion device was evaluated using a force plate, while a series-connected load cell was used as an internal consistency check of the measurement chain. Linear mixed-effects models showed that ISOMETRO strongly predicted force plate values (β = 0.999, SE = 0.002, p < 0.001), with a marginal R² > 0.99. Bland–Altman analysis indicated negligible bias (−0.08 N) and narrow limits of agreement (−4.97 to 4.81 N), and concordance was excellent (CCC ≥ 0.996). The series-connected load cell comparison also showed near-unity agreement (β = 0.998, SE = 0.003, p < 0.001), supporting internal measurement chain integrity. These findings support excellent agreement between ISOMETRO and force plate measurements for upper-limb tensile isometric testing along the vertical axis in young amateur rock climbers under controlled laboratory conditions. However, given the specific sample characteristics and the strictly vertical laboratory configuration, these results should not be generalized to other populations, joint angles, force directions, or non-laboratory environments without further validation. Further studies are needed to confirm performance in more diverse contexts and to establish reliability for repeated-measurement applications. Full article

Biopolymers from renewable sources are increasingly explored to reduce the carbon footprint of materials and mitigate plastic pollution. This review synthesizes the last five years of progress across the biopolymer value chain, comparing plant, microbial/fermentation, fungal, and marine/algal resources and critically assessing greener extraction and fractionation routes (ultrasound and microwave intensification, subcritical water, supercritical CO₂ with co-solvents, ionic liquids, deep eutectic solvents including natural deep eutectic solvents, and enzymatic or bio-mediated processes). We emphasize yield-selectivity trade-offs, scalability, energy demand, and solvent recovery. Downstream, we summarize purification and performance tuning via crosslinking, derivatization, blending/plasticization, and nanocomposites, and we map advanced characterization to targeted functional properties to bridge processing choices with end-use performance. Applications are organized across food and agriculture, biomedical and pharmaceutical technologies, packaging, and cosmetics, with cross-cutting attention to safety and regulatory compliance, quality-by-design, techno-economics, and life-cycle assessment. Key bottlenecks are feedstock variability, viscosity and recyclability limitations of designer solvents, and persistent gaps in barrier and thermal properties versus petrochemical benchmarks, compounded by uneven composting and recycling infrastructure. Promising directions include low-viscosity or switchable solvents, data- and artificial intelligence (AI)-guided process optimization, engineered biopolymers, and circular end-of-life strategies that align material design with realistic recovery routes. Full article

Background/Objectives: Methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms may influence folate metabolism and DNA synthesis, potentially affecting disease characteristics and clinical outcomes in hematologic malignancies. This study investigated the associations of MTHFR C677T and A1298C polymorphisms with clinical features and survival outcomes in adult patients with acute lymphoblastic leukemia (ALL) or non-Hodgkin lymphoma (NHL). Methods: A total of 92 adult patients with ALL or NHL treated with standard chemotherapy were retrospectively analyzed. MTHFR C677T and A1298C genotypes were determined using real-time polymerase chain reaction. Associations between genotypes and baseline clinical features, treatment response, toxicity, overall survival (OS), and progression-free survival (PFS) were examined. Results: The C677T heterozygous genotype was significantly associated with the presence of B symptoms (p = 0.027). No significant differences were observed across genotypes with respect to other baseline clinical features, treatment response, or treatment-related toxicity. In the overall cohort (ALL + NHL), OS and PFS did not differ significantly by C677T or A1298C genotypes. However, in the NHL cohort, carriers of the C677T variant demonstrated significantly shorter PFS (p = 0.048) and a non-significant trend toward lower OS. This association was also observed in the DLBCL subgroup for PFS (p = 0.043), with a similar non-significant trend observed for OS. Conclusions: Although MTHFR genotyping appears to have limited value for broad clinical stratification, the observed association between the C677T polymorphism and PFS in NHL—particularly in the DLBCL subgroup—suggests a potential subtype-specific relevance that warrants further validation in larger, disease-specific cohorts. Full article

Objectives: The aim of this case report is to highlight the diagnostic challenges of carotid space masses, share clinical experience, and educate clinicians by presenting a case of a rare disease. Introduction: Accessory nerve schwannomas are rare, benign peripheral nerve sheath tumors. They make up only a small percentage of all cervical schwannomas. Given their rarity and varying appearance on imaging, these tumors can be difficult to accurately diagnose. Schwannomas may mimic other carotid space pathologies, such as metastatic lymphadenopathy, paragangliomas, or sympathetic chain tumors. Accurately identifying the nerve of origin before surgery is important for effective surgical planning and neurological function protection. Case Description: A 50-year-old woman presented with an asymptomatic left-sided neck mass. Computed tomography (CT) revealed a cystic lesion with a thick, contrast-enhancing capsule in the left carotid space, causing internal jugular vein compression and partial thrombosis. Subsequent MRI showed a 28 mm × 23 mm × 38 mm well-defined mass with characteristic schwannoma features, including T2/Short tau inversion recovery (STIR) hyperintensity, peripheral enhancement, central cystic degenerative components, and peripheral diffusion restriction with corresponding lower apparent diffusion coefficient (ADC) values. Split-fat sign and fascicular sign were also seen on the MRI. Despite these imaging findings, the radiological interpretation suggested a sympathetic chain schwannoma as the most likely diagnosis. The correct diagnosis of accessory nerve schwannoma was established intraoperatively when the mass was visualized to be attached to the accessory nerve. Conclusions: This case highlights that even with suggestive MRI features, the rarity of accessory nerve schwannomas can lead to misidentification of the nerve of origin. Accurate diagnosis may require intraoperative visualization, thus marking the importance of including accessory nerve involvement in the differential diagnosis of carotid space masses. Full article

Background/Objectives: Acinetobacter baumannii is a leading cause of healthcare-associated infections and is frequently associated with multidrug resistance, severely limiting therapeutic options. The increasing prevalence of carbapenem-resistant A. baumannii (CRAB) has intensified interest in novel antimicrobial agents such as cefiderocol, eravacycline, and imipenem–relebactam. Methods: A total of 80 multidrug-resistant (MDR) A. baumannii isolates recovered from various clinical specimens between April 2019 and October 2023 were included. Antimicrobial susceptibility testing was performed using disk diffusion, gradient test, and broth microdilution methods in accordance with EUCAST and CLSI recommendations. The minimum inhibitory concentrations (MIC’s) for cefiderocol were evaluated with broth microdilution using iron-depleted cation-adjusted Mueller–Hinton broth as the reference method. The presence of carbapenem resistance–associated genes (blaOXA-23, blaOXA-24, blaOXA-51, blaOXA-58, blaIMP, and tetA) was investigated by polymerase chain reaction. Results: All isolates were resistant to imipenem and meropenem. Colistin resistance was detected in 7.5% of isolates. According to EUCAST criteria, cefiderocol susceptibility was observed in 77.5% of isolates by microdilution and in 81.25% by disk diffusion. Eravacycline demonstrated low MIC values, with MIC₅₀ and MIC₉₀ of 0.25 mg/L and 0.75 mg/L, respectively. In contrast, all isolates were resistant to imipenem–relebactam. The blaOXA-23 gene was detected in 82.5% and blaOXA-24 in 17.5% of isolates, while no blaOXA-58, blaIMP, or tetA genes were identified. No statistically significant association was found between cefiderocol resistance and OXA-type carbapenemase genes. Conclusions: Cefiderocol and eravacycline demonstrated promising in vitro activity against MDR A. baumannii, including colistin-resistant isolates, whereas imipenem–relebactam showed no activity. These findings support the potential role of cefiderocol and eravacycline as alternative treatment options for CRAB infections and highlight the multifactorial nature of cefiderocol resistance beyond OXA-type carbapenemase production. Full article

The aim of the research was to assess changes in the bioactive status of organic yoghurts produced in the spring/summer season from Simmental cows’ bulk milk during 28-day refrigerated storage, including whey proteins, lipophilic vitamins, and free fatty acids, and to interpret these changes not only in terms of compositional stability but also regarding their nutritional significance, as evaluated using the IYQ (Index of Yoghurt Quality) for vitamins. Raw milk was found to be a significantly richer source of biologically active compounds compared with milk subjected to heat treatment. During the 28-day refrigerated storage of the yoghurts, unfavourable alterations were observed in the levels of selected bioactive components belonging to both the protein and lipid fractions. A reduction in the concentration of the analyzed proteins and vitamins was observed, ranging from 2% for vitamin D₃ to 38% for lactoferrin, while the content of free fatty acids increased, from 8% for monounsaturated free fatty acids (MUFFAs) to 39% for short-chain free fatty acids (SCFFAs). The most pronounced changes were observed in lactoferrin content (p ≤ 0.01), whereas vitamin D₃ exhibited the highest stability throughout the storage period. The stability of vitamin D₃ was further confirmed using the Index of Yoghurt Quality (IYQ). Despite the significant changes observed in the bioactive profile, the yoghurts retained high sensory quality throughout the entire storage period. This indicates that alterations in bioactive status did not compromise the sensory quality of the product, even after 28 days of storage (i.e., at the end of the shelf life). The obtained results indicate the feasibility of developing organic milk processing directly at the farm level while preserving the nutritional value of the products. The possibility of processing organic milk not only into cheese but also into fermented dairy beverages, particularly yoghurts, is of key importance for farmers aiming to diversify production, increase added value, and improve the economic sustainability of small-scale organic farms. Full article

This paper applies the reliability-based robust optimization (RBRO) technique to investigate the probabilistic structural design characteristics of the Fairlead Chain Stopper (FCS), a newly developed detachable mooring apparatus for installation on a 10 MW floating offshore wind turbine. The thickness dimensions of the FCS’s major structural members were considered as random design variables, including uncertainties such as manufacturing tolerances. The structural strength performance was defined as a probabilistic constraint function based on the allowable stresses specified by DNV classification rule. The structural strength performance of the FCS was evaluated through finite element analysis (FEA) using design load conditions for moored (LC1, LC2) and towed (LC3) conditions based on DNV classification rules. The RBRO design problem was formulated with weight minimization as the objective function, with probabilistic constraints on strength performance and 3-sigma robustness applied as side constraints. To evaluate reliability analysis methods suitable for probabilistic optimal design, the Mean Value Reliability Method (MVRM) and the Adaptive Importance Sampling Method (AISM) were applied during the RBRO process, and the results were compared and analyzed. The probabilistic optimal design using RBRO exhibited conservative design characteristics compared to the deterministic optimal design, ensuring robustness and reliability. After comprehensively considering the weight reduction rate and numerical computational cost (number of function evaluations), the RBRO method using MVRM was confirmed to be the most reasonable method for the probabilistic optimal structural design of the FCS. Full article