Search Results (20,379)

As wearable electronic products have been integrated into daily life, flexible pressure sensors, which convert pressure into electrical signals, have become a research focus because of their cross-industry application potential. Despite an increasing number of related studies, the systematic integration of discussions on sensing mechanisms, performance regulation, and multiscenario adaptability remains to be explored. In this paper, core sensing mechanisms such as piezoresistive, capacitive, piezoelectric, and triboelectric mechanisms are systematically reviewed; key performance indicators, including sensitivity, response time, and linearity, are analyzed; construction strategies for diverse substrates and conductive functional materials are explored; and applications in healthcare, human–computer interaction, and electronic skin are elaborated on. The aim of these analyses is to provide practical insights into the development and design of flexible pressure sensors, thus providing a useful reference for advancing these technologies and expanding their cross-domain use. Full article

As an elite indigenous poultry breed under national protection in China, the Xupu goose is renowned for its large body size, superior fatty liver production, premium meat quality, and high tolerance to roughage. To elucidate its genomic architecture, genetic diversity, and evolutionary selection signatures, we conducted whole-genome resequencing on 15 purposively selected, unrelated male Xupu geese. An average of 6.79 Gb of high-quality sequence data was generated per individual, yielding approximately 4.27 million single-nucleotide polymorphisms (SNPs) with a transition/transversion (Ti/Tv) ratio of 2.49. Population genomic analyses revealed that while the population retains a moderate genetic reservoir (H_E = 0.298), it exhibits a distinct heterozygote deficit (Ho = 0.217) and a moderate genomic inbreeding coefficient (F_roh = 0.204). This structural pattern underscores the genetic impact of historical ex situ closed-flock conservation and the consequent formation of cryptic family lineages. Furthermore, genome-wide integrated haplotype score (iHS) scans detected distinct regions under recent positive selection. Functional annotation of these regions highlighted candidate genes tightly associated with the breed’s hallmark traits, specifically lipid metabolism and hepatic fat deposition (ACSS2, ACSS3, PECR), alongside muscle development (CMYA5, MTPN, LEPR). Conclusively, this study delineates a comprehensive genomic landscape of the Xupu goose, providing a robust foundational resource for future germplasm conservation, molecular marker development, and precision breeding programs. Full article

Fixed-wing unmanned aerial vehicles, with their advantages of long endurance and substantial payload capacity, are poised to be a key platform for the future low-altitude economy. However, the challenge of achieving precise attitude tracking control under unknown time-varying disturbances persists. To tackle this difficulty, this article introduces a soft-sign function-based active disturbance rejection control (SSADRC) method, and develops a hybrid grey wolf optimizer (HGWO) with balanced exploration–exploitation mechanisms for intelligent parameter tuning. Specifically, SSADRC utilizes a novel smooth nonlinear function with saturation constraints to reconstruct the nonlinear feedback controller and the extended state observer, ensuring smooth and stable control output. Subsequently, HGWO integrates the good point set-based initialization strategy, the fitness-based dynamic-weight strategy, the diversity-based adaptive-mutation strategy, and the logistic chaotic map-based survival-of-the-fittest strategy, addressing the tuning of multiple coupled parameters in SSADRC. Additionally, the SSADRC-based pitch attitude controller is designed for a fixed-wing unmanned aerial vehicle, and an HGWO and seven other swarm optimization algorithms are employed to tune the parameters. The results demonstrate that the HGWO exhibits the best convergence accuracy in the SSADRC parameter optimization task, and SSADRC illustrates better command tracking performance and state estimation accuracy than typical ADRC. Full article

Fungal endophytes are microorganisms that inhabit plant tissues without causing disease and emerge as critical mediators of plant stress tolerance, nutrient acquisition, and ecosystem resilience under diverse climate change scenarios. Their unique position within the host allows them to modulate physiological responses more closely than external microbiota. This review explores how endophytic fungi contribute to plant adaptation under climate-induced stresses such as heat, salinity, drought, pollution, and nutrient limitation, with a focus on molecular crosstalk, functional trait modules, and metabolic trade-offs. Key findings emphasize multilayered signaling systems, including MAMP/DAMP recognition, phytohormone regulation, immune tuning, ROS dynamics, and effector deployment, while emerging mechanisms such as cross-kingdom RNA and extracellular vesicle (EV)-mediated exchange are discussed as promising but currently limited in empirical validation within many endophytic systems. Endophytes also enhance nutrient exchange through conditional carbon-for-benefit trade and may shape rhizosphere microbiota and soil activities through plant-mediated inputs. Integrative multi-omics approaches provide predominantly correlational insights into the mechanistic basis of these effects, linking molecular function to ecosystem and community outcomes. These insights have potential applications in climate-resilient agriculture, phytoremediation, and ecosystem restoration; however, their large-scale implementation requires further field-based validation and context-specific assessment. Future priorities should focus on trait-based selection, ecological modeling, and biosafety evaluation to translate microbial functions into reliable field-level strategies that support sustainable crop performance under accelerating environmental stress. Full article

Total factor productivity (TFP) is crucial for evaluating technological innovation, yet its accurate measurement remains challenging due to diverse methodologies. Notably, the selection of proxy variables in control function approach (CFA) significantly influences TFP estimation, yet existing studies have failed to clarify the criteria for proxy variable selection, particularly at meso and macro levels. This study employs a comprehensive methodological framework integrating significance, robustness, and comparative analyses to assess TFP estimation methods, addressing prevalent misconceptions. We utilize data sourced from 30 Chinese provinces across three major industries over the period 1998–2022, and conduct TFP calculations employing theoretically comparable methods. Our findings reveal significant discrepancies among methods, emphasizing the impact of proxy variable selection on TFP outcomes. This study finds that while CFA shows comparable performance to traditional production function approach (PFA) in terms of goodness-of-fit and significance (it does not verify the first level of Hypothesis 1 set forth in this study), it excels in reducing TFP estimation volatility (it verifies the second level of Hypothesis 1 set forth in this study). Crucially, proxy variable selection significantly impacts TFP results. We provide empirical norms for proxy variable selection at macro and meso levels, although Hypothesis 2 was not fully validated, offering a standardized framework to enhance TFP measurement accuracy and robustness: energy input is superior for lowly heterogeneous subjects, whereas intermediate input is preferable for those with high heterogeneity, offering valuable implications for policymakers and researchers. Full article

Industrialization has caused extensive environmental change, including a global surge in plastic production and pollution. This has resulted in the accumulation of microplastics (MPs; <5 mm) and nanoplastics (NPs; <1 μm) in ecosystems worldwide. MPs originate from both primary sources, such as cosmetics and industrial applications, and secondary sources, through the degradation of larger plastic debris. As a result, MPs and NPs have become ubiquitous contaminants, posing significant toxicological risks to living organisms. These persistent pollutants are diverse polymers that vary in size, shape, and chemical composition, making their impacts on organism physiology complex and difficult to disentangle. Plastic pollution is particularly severe in aquatic environments, where particles accumulate from terrestrial sources such as urban dust, agricultural runoff, industrial discharges, and wastewater effluents. Although most research has centered on marine ecosystems, emerging evidence indicates that freshwater environments may contain comparable or even higher concentrations of MPs. Once inside the body, MPs can translocate into tissues and exert toxic effects on multiple organ systems. Collectively, plastic pollution poses not only physiological but also neurological and behavioral risks to aquatic life, with potential consequences for ecosystem stability and trophic interactions. Both MPs and NPs are sufficiently small to cross the blood–brain barrier, raising concerns about their potential impacts on the nervous system by interfering with neuronal function and brain development. Plastic particles can accumulate in neural tissues, inducing oxidative stress, neuroinflammation, and disruption of neurotransmitter signaling. Such neurotoxic effects are linked to altered locomotion, feeding, predator avoidance, and social behaviors across multiple species. This review examines current evidence on the neurotoxic effects of plastic pollution in aquatic organisms and underscores the urgent need for further research and action to mitigate its impact. In light of escalating plastic production and inadequate waste management, the growing evidence that MPs and NPs disrupt aquatic nervous systems, behavior, and ecosystem stability underscores an urgent need for intensified research, improved mitigation strategies, particularly for nanoplastics, and the accelerated development of truly safe and sustainable alternatives. Full article

Current literature on baseline voiding function in gender-diverse patients assigned male at birth (AMAB) is limited. We conducted a retrospective analysis of patients presenting for gender-affirming orchiectomy consultation between 2021 and 2024 who completed the American Urological Association symptom score (AUA-SS) questionnaire to characterize baseline urinary symptoms and identify factors associated with symptom-related bother. Demographics, hormone therapy characteristics, and comorbidities were collected. Bother score was analyzed as both an ordinal variable (score 0 = “delighted” to 6 = “terrible”) and dichotomized (no bother = “delighted” or “pleased” and some bother = “mostly satisfied” to “terrible”). Twenty-six patients met the inclusion criteria, with a median age of 28 years. Overall symptom burden was low (median AUA-SS 4, IQR 2–7.3), with frequency and nocturia reported most commonly. Despite mild symptoms, most patients did not select the lowest possible bother score (“delighted”). Total AUA-SS and bother were not significantly associated with hormone therapy type or duration. In contrast, those with a documented history of anxiety, depression, or bipolar disorder had significantly higher bother score compared to those without (mean rank 15.3 vs. 9.6, p = 0.04). In this single-center cohort, urinary symptoms were generally mild among AMAB patients seeking gender-affirming orchiectomy. Psychiatric history was associated with a higher bother score, though this relationship was no longer significant when bother was dichotomized. These findings suggest behavioral factors may influence how urinary symptoms are experienced and reported in this population. These findings are exploratory and warrant validation in larger cohorts. Full article

This paper examines the philosophy and practice of interfaith dialogue (IFD) developed by Daisaku Ikeda (1928–2023), a prominent religious leader and peace philosopher. It explores how his dialogical approach can contribute to the United Nations’ Sustainable Development Goals (SDGs) and pathways to global peace. Ikeda’s dialogue is not confined to doctrinal debate or temporary reconciliation among faith communities. Rather, it is framed as a transformative process in which participants from diverse religious and civilizational traditions rebuild relationships through mutual respect and understanding, thereby contributing to personal transformation and broader societal change. Focusing on Ikeda’s core concepts—humanism, the dignity of life, and human revolution—this study first clarifies the philosophical foundations of his interfaith dialogue rooted in Nichiren Buddhism and a life-affirming worldview. It then examines major dialogues with global thinkers and leaders (e.g., Arnold J. Toynbee, Linus Pauling, Mikhail Gorbachev, and Johan Galtung) and selected institutional practices associated with Soka Gakkai International (SGI), the Institute of Oriental Philosophy (IOP), and the Ikeda Center for Peace, Learning, and Dialogue. These cases illustrate how Ikeda’s IFD functions as praxis for civilizational understanding, social cohesion, conflict transformation, and solidarity for the public good. The paper further analyzes the linkages between Ikeda’s IFD and SDG 16 (Peace, Justice and Strong Institutions), SDG 17 (Partnerships for the Goals), SDG 4 (Quality Education—especially Target 4.7 on Global Citizenship Education), and SDG 10 (Reduced Inequalities). It argues that IFD can operate as both a normative and practical resource for mitigating religious conflict, strengthening inclusion, enhancing global citizenship education and education for sustainable development (ESD), and fostering multistakeholder partnerships. The paper also reflects on the challenges of translating an approach grounded in a particular religious tradition into broader SDG governance contexts. Full article

Lichens represent a fundamental symbiotic association between fungi and photosynthetic organisms, such as algae or cyanobacteria, and are widely regarded as sensitive indicators of environmental change. Lichens’ capacity to colonize a wide range of ecological niches is attributed to their distinctive physiological characteristics, notably, their lack of protective cuticles and ability to uptake water and nutrients directly from the atmosphere. Concurrently, lichens are highly vulnerable to airborne contaminants, making them critical bioindicators of air quality. However, the survival of lichens is increasingly influenced by intensifying global change via agriculture, industrial activities, and vehicular emissions. Organic and inorganic pollutants can adversely affect lichen physiology by inducing pigment degradation, disrupting membranes, and altering lichen diversity. The synergistic stressors associated with global change, such as increasing temperatures and shifts in precipitation regimes, exacerbate the effects of atmospheric deposition and oxidative stress on lichens. Here, we present existing knowledge on lichens’ ecological functions, elucidate the mechanisms underlying their sensitivity to air pollution, and assess their utility for environmental monitoring amid accelerating global change. By recognizing lichens as dynamic ecological indicators, we underscore their dual role in sustaining ecosystem processes amidst rapid global change. Full article

Alginate, a naturally occurring polysaccharide derived from brown algae, has emerged as a versatile cornerstone in the field of biomedical materials. Its widespread adoption is driven by its exceptional biocompatibility and the unique cation-dependent gelation defined by the “egg-box” model. This review examines the fundamental chemistry of alginate, detailing how its crosslinking mechanisms dictate the physicochemical properties essential for clinical performance. The discussion bridges the gap between polymer structure and diverse biomedical applications, including drug delivery, tissue engineering, and the clinical management of gastrointestinal reflux and wound care. Furthermore, the article evaluates the role of alginate-based systems in the biomedical and metabolic management of obesity and diabetes. By analyzing how alginate influences satiety, glycemic index modulation, and lipid absorption through biophysical mechanisms, this review highlights the transition from fundamental chemical architecture to practical clinical utility. By integrating structural chemistry with physiological impact, this work underscores the evolving potential of alginate-based materials as supportive and functional strategies in modern clinical care. Full article

Gut microbiota dysbiosis is implicated in metabolic disorders, yet taxonomic and functional alterations in canine diabetes remain incompletely defined. Here, we performed shotgun metagenomic sequencing of fecal samples from 38 diabetic dogs and 37 healthy controls under controlled conditions (no recent antibiotic/probiotic exposure and stable commercial diets). Alpha-diversity indices did not differ between groups, whereas beta-diversity revealed significant separation of community structure at both genus and species levels (p < 0.05). Linear discriminant analysis effect size (LEfSe) identified enrichment of opportunistic-associated taxa in diabetic dogs, including Enterobacterales/Enterobacteriaceae (e.g., Escherichia coli, Klebsiella pneumoniae, Salmonella enterica) and Enterococcus faecalis. In contrast, healthy dogs were enriched for putatively beneficial taxa linked to bile acid and short-chain fatty acid (SCFA) metabolism, including Turicibacter spp. and Romboutsia spp. Functional profiling showed higher abundances of pathways related to carbohydrate/energy metabolism, membrane transport, and virulence/colonization in diabetic dogs; 17 KEGG level-3 pathways and 320 KOs differed at FDR < 0.05, with enriched modules including bacterial secretion systems, lipopolysaccharide biosynthesis, chemotaxis/flagellar assembly, and biofilm formation. Collectively, canine diabetes is associated with a remodeled gut microbiome characterized by expansion of opportunistic pathogens and elevated virulence and metabolic potential, supporting exploration of microbiota-targeted strategies as a complement to conventional management. Full article

This longitudinal study investigates the development of alphabetic skills from kindergarten to third grade and the contribution of the three different executive function (EF) abilities—working memory (WM), cognitive flexibility, and inhibition—to these skills among children from diverse SES. A comprehensive battery of early literacy, reading, and EF tasks was administered individually to assess reading abilities and various EF facets at three time points (kindergarten, first grade, and third grade). The results revealed significant differences in alphabetic skills and reading abilities (reading fluency) from kindergarten to third grade among children from different SES backgrounds, with children from higher SES backgrounds exhibiting better alphabetic and reading skills than those from lower SES backgrounds. These differences decreased in the third grade. The various EF components contributed differently at each age and SES level to the alphabetic and reading abilities. Auditory WM (AWM) was a significant predictor of reading ability in all SES groups, especially the low SES group. Among the high and medium SES groups in first grade, AWM and cognitive flexibility emerged as significant predictors, while visual WM was significant in the low SES group. EF abilities contributed less to reading in all SES groups in the third grade as compared to earlier ages. This trend suggests a gradual narrowing of the SES-related gap in reading development, associated with the role of school exposure in reducing disparities rooted in varied home environments. These findings suggest that early screening in kindergarten, particularly among low SES populations, could identify children at risk for reading difficulties and inform targeted interventions that support the development of critical executive function skills alongside literacy instruction. Full article

Water is fundamental to structural integrity, stability, and functional properties of food systems, biomaterials, and biobased industries. The dynamics of hydration, including hydrogen bonding, hydration shell formation, plasticization, and phase transitions, dictate molecular behavior and exert broad influence on energy consumption, shelf life, biodegradability, and resource efficiency. However, the nonlinear and multiscale characteristics of hydration have constrained the predictive capabilities of conventional empirical methods. This study introduces a comprehensive framework that integrates foundational hydration science with advanced computational intelligence to model, predict, and optimize hydration-driven phenomena across diverse biopolymer classes. Leveraging classical insights into carbohydrate stereochemistry, protein hydrophobic hydration, and phospholipid-bound water, we demonstrate how computational approaches can reduce resource use in bioprocessing by 30–50% and optimize drying curves to lower energy consumption by 25%. By establishing hydration as a strategic design parameter, this work charts a pathway toward a resilient and sustainable economy where predictive error rates for hydration dynamics are significantly minimized through data-driven calibration. Full article

Topological graph theory provides a quantitative approach to understanding the structural complexities of sulfonamide compounds, which are prominent for their therapeutic importance in cancer treatment. A new computational scheme to predict the physicochemical and biological functions of sulfonamide derivatives, based on connection numbers and connection-based topological indices as alternatives to the theoretically overt degree-based index, is proposed. A set of structurally diverse sulfonamide compounds as chemical graphs is considered, and the relevant graph descriptors are computed using different connection numbers. Due to the complexity of the calculations involved in connectivity and other such indices, algorithms were developed in Python 3.12.12 to automate the extraction and calculation of these indices. QSPR analysis, with the help of supervised machine learning models like linear regression, among others, and various statistical techniques, was employed to obtain insight into the relationships existing between the structural properties and the molecular properties measured, such as melting point, molecular weight, etc. These results demonstrate the great predictive capability of connection-based indices in assessing pharmacologic efficacy or molecular behavior. The holistic setting thus links topological modeling to data-driven prediction and provides a window into the rational design and optimization of sulfonamide-based cancer therapeutics. Full article

The mitogen-activated protein kinase (MAPK) cascade constitutes a core component of signal transduction pathways in eukaryotic organisms. With its precise, efficient, and specific mechanism of action, this cascade pathway integrates, amplifies, and rapidly transmits signals. Among them, the specificity and functional diversity of the MPK3 cascade depend on the phosphorylation interaction between MKK and MPK3, as well as the specific interaction between MPK3 and its substrates. MPK3 targets an extremely diverse array of substrates, including transcription factors, RNA-binding proteins, enzymes, and transporters. The summary of the regulatory role of the MPK3 signal mainly focuses on three functional mechanisms: The most well-known regulatory mechanism is to recognize and phosphorylate substrate proteins or transcription factors, thereby affecting the stability and transcriptional activity of downstream substrates, and thus regulating the transcriptional regulatory activity and expression of downstream genes. MPK3 can also participate in downstream functional regulation by triggering the MAPKKK-MKK4/5-MPK3/6 signaling pathways or feedback mechanisms. MPK3 can exert regulatory effects independently or together with MPK6. The redundancy of the MPK3/6 function is related to the synergistic effect of the component cascade reaction, as well as the dose-dependent activation effect. This article presents a comprehensive synthesis of the latest research progress on the regulatory role of MPK3, in plant growth, development, and stress adaptation and defence. Moreover, it provides critical evaluations and forward-looking perspectives on the future investigation of the underlying molecular mechanisms governing MPK3-mediated regulation. Full article