Search Results (14,720)

The actomyosin complex—nature’s dynamic engine composed of actin filaments and myosin motors—is emerging as a versatile tool for bio-integrated nanotechnology. This review explores the growing potential of actomyosin-powered systems in biosensing and actuation applications, highlighting their compatibility with physiological conditions, responsiveness to biochemical and physical cues and modular adaptability. We begin with a comparative overview of natural and synthetic nanomachines, positioning actomyosin as a uniquely scalable and biocompatible platform. We then discuss experimental advances in controlling actomyosin activity through ATP, calcium, heat, light and electric fields, as well as their integration into in vitro motility assays, soft robotics and neural interface systems. Emphasis is placed on longstanding efforts to harness actomyosin as a biosensing element—capable of converting chemical or environmental signals into measurable mechanical or electrical outputs that can be used to provide valuable clinical and basic science information such as functional consequences of disease-associated genetic variants in cardiovascular genes. We also highlight engineering challenges such as stability, spatial control and upscaling, and examine speculative future directions, including emotion-responsive nanodevices. By bridging cell biology and bioengineering, actomyosin-based systems offer promising avenues for real-time sensing, diagnostics and therapeutic feedback in next-generation biosensors. Full article

Antibiotic resistance remains one of the most formidable challenges to modern medicine, threatening to outpace therapeutic innovation and undermine decades of clinical progress. While resistance was once viewed narrowly as a clinical phenomenon, it is now understood as the outcome of complex ecological and molecular interactions that span soil, water, agriculture, animals, and humans. Environmental reservoirs act as silent incubators of resistance genes, with horizontal gene transfer and stress-induced mutagenesis fueling their evolution and dissemination. At the molecular level, advances in genomics, structural biology, and systems microbiology have revealed intricate networks involving plasmid-mediated resistance, efflux pump regulation, integron dynamics, and CRISPR-Cas interactions, providing new insights into the adaptability of pathogens. Simultaneously, the environmental dimensions of resistance, from wastewater treatment plants and aquaculture to airborne dissemination, highlight the urgency of adopting a One Health framework. Yet, alongside this growing threat, novel therapeutic avenues are emerging. Innovative β-lactamase inhibitors, bacteriophage-based therapies, engineered lysins, antimicrobial peptides, and CRISPR-driven antimicrobials are redefining what constitutes an “antibiotic” in the twenty-first century. Furthermore, artificial intelligence and machine learning now accelerate drug discovery and resistance prediction, raising the possibility of precision-guided antimicrobial stewardship. This review synthesizes molecular insights, environmental drivers, and therapeutic innovations to present a comprehensive landscape of antibiotic resistance. By bridging ecological microbiology, molecular biology, and translational medicine, it outlines a roadmap for surveillance, prevention, and drug development while emphasizing the need for integrative policies to safeguard global health. Full article

Structural variation (SV) serves as a fundamental driver of phenotypic diversity and environmental adaptation in plants and animals, significantly influencing key agronomic traits in crops. Common wheat (Triticum aestivum L.), an allohexaploid species, harbors extensive chromosomal SVs and distant hybridization-induced recombination events that provide critical resources for genetic improvement. This study utilizes non-denaturing fluorescence in situ hybridization (ND-FISH) and oligonucleotide multiplex probe-based FISH (ONPM-FISH) to analyze the karyotypes of 153 BC₁F₄–BC₁F₆ lines derived from the hybrid line Xiaoyan 7430 and common wheat Yannong 1212. The results revealed that Xiaoyan 7430 carries 8 alien chromosome pairs and 20 wheat chromosome pairs (lacking 6B), and Yannong 1212 contains 21 pairs of wheat chromosomes. The parental lines exhibited presence/absence variations (PAVs) on chromosomes 2A, 6A, 5B, 1D, and 2D. Chromosomal variations, including numerical chromosomal variation (NCV), structural chromosomal variation (SCV), and complex chromosomal variation (CCV), were detected in the progeny lines through ONPM-FISH analysis. The tracking of alien chromosomes over three consecutive generations revealed a significant decrease in transmission frequency, declining from 61.82% in BC₁F₄ to 26.83% in BC₁F₆. Telosomes were also lost during transmission, declining from 21.82% in BC₁F₄ to 9.76% in BC₁F₆. Alien chromosome 1J^S, 4J, and 6J exhibited the highest transmission stability and were detected across all three generations. Association analysis showed that YN-PAV.2A significantly affected the length/width ratio (LWR) and grain diameter (GD); YN-PAV.6A, XY-PAV.6A, and PAV.5B increased six grain traits (+2.25%~15.36%); YN-PAV.1D negatively affected grain length (GL) and grain circumference (GC); and XY-PAV.2D exerted positive effects on thousand-grain weight (TGW). Alien chromosomes differentially modulated grain characteristics: 1J^S and 6J both reduced grain length and grain circumference; 1J^S increased LWR; and 4J negatively impacted TGW, grain width (GW), GD, and grain area (GA). Meanwhile, increasing alien chromosome numbers correlated with progressively stronger negative effects on grain traits. These findings elucidate the genetic mechanisms underlying wheat chromosomal variations induced by distant hybridization and their impact on wheat grain traits, and provide critical intermediate materials for genome design breeding and marker-assisted selection in wheat improvement. Full article

Background: Greenhouses are pivotal to sustainable agriculture as they provide suitable conditions to support the growth of crops in unusable land such as arid areas. However, conventional greenhouse cover materials such as glass, polycarbonate (PC), and polyethylene (PE) sheets are limited in regulating internal conditions in the greenhouses based on environmental changes. Quantum and nonlinear metamaterials are emerging materials with the potential to optimize the covers and ensure appropriate regulation. Objective: This comprehensive review investigated the performance optimization of greenhouse covers through the potential application of nonlinear and quantum metamaterials as nano-additives, examining their effects on electromagnetic radiation management, crop growth enhancement, and temperature regulation within greenhouse systems. Method: The scoping review method was used, where 39 published articles were examined. Results: The review revealed that integrating nano-additives ensured that the greenhouse covers would block harmful near-infrared (NIR) radiation that generated heat while also optimizing for photosynthetically active radiation (PAR) to promote crop yields. Conclusions: The insights also indicated that the high sensitivity of the metamaterials would facilitate the regulation of the internal conditions within the greenhouses. However, challenges such as complex production processes that were not commercially scalable and the recyclability of the metamaterials were identified. Future work should further investigate pathways to produce hybrid greenhouse covers that integrate metamaterials with conventional materials to enhance scalability. Full article

In this study, four types of Fe₃O₄-based magnetic nanospheres were functionalized with distinct surface groups to examine how surface chemistry influences their co-transport with tetracycline (TC) in porous media. The functional groups investigated are carboxyl (−COOH), epoxy (−EPOXY), silanol (−SiOH), and amino (−NH₂). Particles bearing −COOH, −EPOXY, or −SiOH are negatively charged, facilitating their transport through porous media, whereas −NH₂-modified particles acquire a positive charge, leading to strong electrostatic attraction to the negatively charged TC and quartz sand, and consequently substantial retention with reduced mobility. Adsorption of TC onto Fe₃O₄-MNPs is predominantly chemisorptive, driven by ligand exchange and the formation of coordination complexes between the ionizable carboxyl and amino groups of TC and the surface hydroxyls of Fe₃O₄-MNPs. Additional contributions arise from electrostatic interactions, hydrogen bonding, hydrophobic effects, and cation–π interactions. Moreover, the carboxylate moiety of TC can coordinate to surface Fe centers via its oxygen atoms. Molecular dynamics simulations reveal a hierarchy of adsorption energies for TC on the differently modified surfaces: Fe₃O₄-NH₂ > Fe₃O₄-EPOXY > Fe₃O₄-COOH > Fe₃O₄-SiOH, consistent with experimental findings. The results underscore that tailoring the surface properties of engineered nanoparticles substantially modulates their environmental fate and interactions, offering insights into the potential ecological risks associated with these nanomaterials. Full article

Soil organic matter (SOM) is essential for ecosystem health and agricultural productivity. Accurate prediction of SOM content is critical for modern agricultural management and sustainable soil use. Existing digital soil mapping (DSM) models, when processing temporal data, primarily focus on modeling the changes in input data across successive time steps. However, they do not adequately model the relationships among different input variables, which hinders the capture of complex data patterns and limits the accuracy of predictions. To address this problem, this paper proposes a novel deep learning model, 2-Channel Network (2C-Net), leveraging sequential multi-temporal remote sensing images to improve SOM prediction. The network separates input data into temporal and spatial data, processing them through independent temporal and spatial channels. Temporal data includes multi-temporal Sentinel-2 spectral reflectance, while spatial data consists of environmental covariates including climate and topography. The Multi-sequence Feature Fusion Module (MFFM) is proposed to globally model spectral data across multiple bands and time steps, and the Diverse Convolutional Architecture (DCA) extracts spatial features from environmental data. Experimental results show that 2C-Net outperforms the baseline model (CNN-LSTM) and mainstream machine learning model for DSM, with R² = 0.524, RMSE = 0.884 (%), MAE = 0.581 (%), and MSE = 0.781 (%)². Furthermore, this study demonstrates the significant importance of sequential spectral data for the inversion of SOM content and concludes the following: for the SOM inversion task, the bare soil period after tilling is a more important time window than other bare soil periods. 2C-Net model effectively captures spatiotemporal features, offering high-accuracy SOM predictions and supporting future DSM and soil management. Full article

Power systems are undergoing a transformative transition as consumers seek greater participation in managing electricity systems. This shift has given rise to the concept of “prosumers,” individuals who both consume and produce electricity, primarily through renewable energy sources. While renewables offer undeniable environmental benefits, they also introduce significant energy management challenges. One major concern is the variability in energy consumption patterns within households, which can lead to inefficiencies. Also, improper energy management can result in economic losses due to unbalanced energy control or inefficient systems. Home Energy Management Systems (HEMSs) have emerged as a promising solution to address these challenges. A well-designed HEMS enables users to achieve greater efficiency in managing their energy consumption, optimizing asset usage while ensuring cost savings and system reliability. This paper presents a comprehensive systematic review of optimization techniques applied to HEMS development between 2019 and 2024, focusing on key technical and computational factors influencing their advancement. The review categorizes optimization techniques into two main groups: conventional methods, emerging techniques, and machine learning methods. By analyzing recent developments, this study provides an integrated perspective on the evolving role of HEMSs in modern power systems, highlighting trends that enhance the efficiency and effectiveness of energy management in smart grids. Unifying taxonomy of HEMSs (2019–2024) and integrating mathematical, heuristic/metaheuristic, and ML/DRL approaches across horizons, controllability, and uncertainty, we assess algorithmic complexity versus tractability, benchmark comparative evidence (cost, PAR, runtime), and highlight deployment gaps (privacy, cybersecurity, AMI/HAN, and explainability), offering a novel synthesis for AI-enabled HEMS. Full article

This study aims to explore the intersection of Artificial Intelligence (AI), Environmental, Social, and Governance (ESG) factors, and Open Innovation (OI) within the context of mergers and acquisitions (M&A). As ESG considerations increasingly influence corporate strategy and valuation, integrating AI offers powerful tools for enhancing due diligence, reducing risks, and creating long-term value. Building on the ARCTIC framework, an extension of the VRIO framework and real options theory, this paper introduces a new method for measuring AI-ESG-OI-driven synergies in mergers and acquisitions. It highlights the crucial role of Open Innovation in facilitating cross-boundary knowledge exchange, federated learning, and collaborative ESG data analysis. Based on recent advances in AI-ESG-enabled OI practices, such as multi-agent systems, synthetic data, and decentralized innovation, this paper shows how companies can address ESG complexity and cultural integration challenges. The findings indicate that incorporating OI principles into AI-ESG strategies not only enhances decision-making but also aligns M&A activities with evolving investor expectations and sustainability goals. The study concludes with practical insights and directions for future research in AI-driven, ESG-aligned corporate innovation. Full article

Metal contamination poses serious environmental and human health risks, which results in the need for low-cost remediation approaches. The utilization of agricultural byproducts for the removal of metal contaminants is considered cost-effective and environmentally sustainable. Garlic byproducts are rich in sulfur-containing compounds, and various functional groups contribute to metal binding. This study aimed to evaluate the potential of garlic stem and peel for the removal of cadmium (Cd), lead (Pb), and arsenic (As) from aqueous solutions and for their immobilization in contaminated soils. Batch sorption experiments conducted at pH 7 for 24 h showed that garlic stem removed 71.5% of Cd and 70.8% of Pb, while garlic peel achieved 65.4% and 79.4% removal, respectively. The higher Pb removal by garlic peel might be attributed to its higher sulfur content. However, both byproducts were less effective in removing As(III) and showed negligible removal of As(V), as these species predominantly occur in neutral or negatively charged species at neutral pH, resulting in weak interactions with negatively charged surface functional groups. Soil incubation experiments were conducted using 1% and 5% amendments of garlic stem and peel in Pb- and As-contaminated soils. Extractable Pb concentrations significantly increased in soils treated with 1% garlic peel because of the formation of labile complexes of Pb with dissolved organic carbon. However, a column experiment to evaluate the impact on Pb mobility under saturated and unsaturated conditions showed that Pb concentration in soil pore water decreased with garlic stem. Pb concentration was lower under saturated conditions, possibly due to the precipitation of Pb as PbS. Although the short-term application of raw agricultural byproducts increased extractable metal concentrations, long-term incubation reduced Pb levels in pore water. These findings suggest that unmodified garlic stem is a promising, cost-effective amendment for Pb immobilization in soil. Nevertheless, caution is needed in its application to prevent unintended metal mobilization in soil. Full article

Introduction: Dry Eye Syndrome (DES) is a multifactorial disorder of the ocular surface, characterized by complex interactions between environmental factors, immune dysregulation, and potential genetic predispositions. Vitamin D deficiency, known for its immunomodulatory properties, has increasingly been implicated in the pathogenesis of DES; however, the underlying mechanisms remain insufficiently elucidated. Of particular interest is the vitamin D receptor (VDR) gene, whose polymorphisms may influence the bioavailability and biological activity of vitamin D. Objective: The aim of this study was to investigate the association between serum 25-hydroxyvitamin D [25(OH)D₃] levels and selected polymorphisms in the VDR gene (Taq, Fok, Apa, and Bsm) in patients with DES and to analyze their potential clinical and genetic interactions. Methods: This prospective observational study included 60 patients with a confirmed diagnosis of DES. Serum 25(OH)D₃ levels were measured, and genotyping of four VDR single-nucleotide polymorphisms (SNPs) was performed using PCR followed by restriction fragment length polymorphism analysis. Genotype distributions were assessed in relation to vitamin D status using appropriate statistical tests and Hardy–Weinberg equilibrium analysis. Results: Over 85% of patients exhibited insufficient or deficient vitamin D levels. Among the analyzed SNPs, only the ApaI polymorphism (rs7975232) showed a statistically significant association with vitamin D status (p = 0.0384), with the homozygous AA genotype being more prevalent among patients with hypovitaminosis. The remaining polymorphisms (TaqI, FokI, BsmI) did not reach statistical significance; however, potential trends were observed that may warrant further investigation in larger cohorts. Conclusion: The findings suggest a potential role for VDR gene variability in the regulation of systemic vitamin D levels in patients with DES. Identification of specific genotypes may contribute to the development of personalized diagnostic and therapeutic strategies, particularly for patients with treatment-resistant forms of the disease. These results support the integration of genetic biomarkers and nutritional parameters into modern ophthalmologic practice. Full article

Hybrid marine energy platforms that integrate wave energy converters (WECs) and hydrokinetic turbines (HKTs) offer potential to improve energy yield and system stability in marine environments. This study identifies a compatible WEC–HKT integrated system concept through a structured concept selection framework based on multi-criteria decision analysis (MCDA). The framework follows a two-stage process: individual technology assessment using eight criteria (efficiency, TRL, self-starting capability, structural simplicity, integration feasibility, environmental adaptability, installation complexity, and indicative cost) and pairing evaluation using five integration-focused criteria (structural compatibility, PTO feasibility, mooring synergy, co-location feasibility, and control compatibility). Criterion weights were assigned through a four-level importance framework based on expert judgment from 11 specialists, with unequal weights for the individual evaluation and equal weights for the integration stage. Four WEC types (oscillating water column, point absorber, overtopping wave energy converter, and oscillating wave surge converter) and four HKT types (Darrieus, Gorlov, Savonius, and hybrid Savonius–Darrieus rotor) are assessed using literature-derived scoring and weighted ranking. The results show that the oscillating water column achieved the highest weighted score among the WECs with 4.05, slightly ahead of the point absorber, which scored 3.85. For the HKTs, the Savonius rotor led with a score of 4.05, surpassing the hybrid Savonius–Darrieus rotor, which obtained 3.50, by 0.55 points. In the pairing stage, the OWC–Savonius configuration achieved the highest integration score of 4.2, surpassing the PA–Savonius combination, which scored 3.4, by 0.8 points. This combination demonstrates favorable structural layout, PTO independence, and mooring simplicity, making it the most promising option for early-stage hybrid platform development. Full article

The conceptual design phase in architecture establishes the foundation for subsequent design decisions and influences up to 80% of a building’s lifecycle environmental impact. While Building Information Modeling (BIM) demonstrates transformative potential for sustainable design, its application during conceptual design remains constrained by perceived technical complexity and limited support for abstract thinking. This research examines how BIM tools can facilitate conceptual design through diagrammatic reasoning, thereby bridging technical capabilities with creative exploration. A mixed-methods approach was employed to develop and validate a Diagrammatic BIM (D-BIM) framework. It integrates diagrammatic reasoning, parametric modeling, and performance evaluation within BIM environments. The framework defines three core relationships—dissection, articulation, and actualization—which enable transitions from abstract concepts to detailed architectural forms in Revit’s modeling environments. Using Richard Meier’s architectural language as a structured test case, a 14-week quasi-experimental study with 19 third-year architecture students assessed the framework’s effectiveness through pre- and post-surveys, observations, and artifact analysis. Statistical analysis revealed significant improvements (p < 0.05) with moderate to large effect sizes across all measures, including systematic design thinking, diagram utilization, and academic self-efficacy. Students demonstrated enhanced design iteration, abstraction-to-realization transitions, and performance-informed decision-making through quantitative and qualitative assessments during early design stages. However, the study’s limitations include a small, single-institution sample, the absence of a control group, a focus on a single architectural language, and the exploratory integration of environmental analysis tools. Findings indicate that the framework repositions BIM as a cognitive design environment that supports creative ideation while integrating structured design logic and performance analysis. The study advances Education for Sustainable Development (ESD) by embedding critical, systems-based, and problem-solving competencies, demonstrating BIM’s role in sustainability-focused early design. This research provides preliminary evidence that conceptual design and BIM are compatible when supported with diagrammatic reasoning, offering a foundation for integrating competency-based digital pedagogy that bridges creative and technical dimensions of architectural design. Full article

Seawater intrusion into coastal river systems poses increasing challenges for freshwater availability and estuarine ecosystem integrity, especially under evolving climatic and anthropogenic pressures. This study presents a multidisciplinary investigation of marine intrusion dynamics within the Magra River estuary (Northwest Italy), integrating field monitoring, isotopic tracing (δ¹⁸O; δD), and multivariate statistical modeling. Over an 18-month period, 11 fixed stations were monitored across six seasonal campaigns, yielding a comprehensive dataset of water electrical conductivity (EC) and stable isotope measurements from fresh water to salty water. EC and oxygen isotopic ratios displayed strong spatial and temporal coherence (R² = 0.99), confirming their combined effectiveness in identifying intrusion patterns. The mass-balance model based on δ¹⁸O revealed that marine water fractions exceeded 50% in the lower estuary for up to eight months annually, reaching as far as 8.5 km inland during dry periods. Complementary δD measurements provided additional insight into water origin and fractionation processes, revealing a slight excess relative to the local meteoric water line (LMWL), indicative of evaporative enrichment during anomalously warm periods. Multivariate regression models (PLS, Ridge, LASSO, and Elastic Net) identified river discharge as the primary limiting factor of intrusion, while wind intensity emerged as a key promoting variable, particularly when aligned with the valley axis. Tidal effects were marginal under standard conditions, except during anomalous events such as tidal surges. The results demonstrate that marine intrusion is governed by complex and interacting environmental drivers. Combined isotopic and machine learning approaches can offer high-resolution insights for environmental monitoring, early-warning systems, and adaptive resource management under climate-change scenarios. Full article

Fujian Tulou, a UNESCO World Heritage Site, is highly vulnerable to environmental and anthropogenic stresses, with its earthen walls prone to surface cracking that threatens both structural stability and cultural value. Traditional manual inspection is inefficient, subjective, and may disturb fragile surfaces, highlighting the need for non-destructive and automated solutions. This study proposes a dual-path framework that integrates lightweight crack detection with independent physical simulation. On the detection side, an improved YOLOv12 model is developed to achieve lightweight and accurate recognition of multiple crack types under complex wall textures. On the simulation side, a two-layer RFPA^3D model was employed to parameterize loading conditions and material thickness, reproducing the four-stage crack evolution process, and aligning well with field observations. Quantitative validation across paired samples demonstrates improved consistency in morphology, geometry, and topology compared with baseline models. Overall, the framework offers an effective and interpretable solution for standardized crack documentation and mechanistic interpretation, providing practical benefits for the preventive conservation and sustainable management of Fujian Tulou. Full article

In recent years, corporate perceptions of environmental sustainability have shifted from viewing it as a compliance burden to recognizing it as a strategic driver of innovation and competitive advantage, prompting a demand for effective sustainable design tools. Traditionally, tools like the Life Cycle Assessment (LCA) tool have been used to evaluate environmental impacts, yet their complexity, cost, and retrospective focus make them impractical for driving early-stage, disruptive innovation. Although biomimicry has emerged as a promising approach, adopting this novel interdisciplinary design practice within a corporate setting requires significant resources and time, disrupting established processes. Therefore, the biomimicry Life Principles (LPs) tool, a guiding sustainable design tool of the practice, provides an opportunity to lower the barrier to the entry of biomimicry within a corporate setting and potentially increases adoption of the broader practice. This comparative study seeks to explore the creative potential, and practical value of the biomimicry LPs tool compared to the traditional LCA approach while exploring the intrinsic motivation of R&D practitioners to implement these tools within a virtual product redesign workshop. To derive our conclusions, we employed a mixed-methods approach comprising a 23-item survey designed to assess practitioners’ intrinsic motivation and perceived practical value of the implemented tool alongside an external evaluation of the creativity of all generated design concepts. Together, these methods provide empirical evidence of the biomimicry LPs tool’s potential to enhance creative output, require minimal adoption effort, and act as a catalyst for whole-systems thinking in sustainable innovation. These findings offer compelling evidence to support their strategic addition to existing R&D toolkits and workflows. By highlighting the efficacy, accessibility, and intrinsic motivation of R&D professionals to use biomimicry LPs, the results underscore the viability of this tool to streamline the integration of biomimicry design thinking into real-world workflows. As such, they represent a pragmatic and scalable pathway to catalyze broader and deeper engagement with biomimicry across corporate contexts. Full article