Asthma is a debilitating disease, and its diagnosis and disease management remain imprecise. It continues to impose a major global burden on public health, medicine, and the economy. Asthma exhibits marked heterogeneity in clinical phenotypes, and environmental and genetic risk factors remain incompletely defined. Moreover, its significant geographical and ethnic variation limits diagnostic precision. They also hinder effective risk stratification and accurate prediction of disease exacerbations. To date, most asthma research and therapeutic development have focused on allergen-mediated immune responses. Conversely, the adverse effects of environmental chemical pollutants have received less attention. This imbalance has limited the development of a comprehensive understanding of asthma pathogenesis. It has also slowed progress toward truly precision-based therapies. Simultaneously, growing experimental and clinical evidence highlights causal links between environmental exposures and disease. The concepts of the exposome and exposomics have also emerged. These provide useful frameworks to study disease development and progression. In this review, we summarize recent multicenter studies on asthma. These studies show that environmental determinants of asthma are not uniform, as different asthma phenotypic clusters have distinct environmental exposure profiles. Moreover, environmentally driven metabolic reprogramming plays an important role, resulting in bioactive metabolites that also deserve careful attention. These factors are crucial for advancing precision environmental medicine.
Cyclospora cayetanensis is an important foodborne parasite worldwide, with fresh produce and contaminated irrigation water as major transmission vehicles. In South Asia, environmental surveillance data remain limited. We investigated the occurrence of C. cayetanensis DNA in fresh produce and irrigation water across peri-urban areas of Khyber Pakhtunkhwa, Pakistan, and assessed environmental and farm-level factors associated with contamination. A cross-sectional study was conducted in Peshawar and Kohat districts from April to September 2025. A total of 420 samples were collected, including 300 fresh produce samples (six commonly consumed vegetables and herbs) and 120 irrigation water samples from canal, tube-well, and mixed sources. Samples were processed using concentration techniques, and detection was performed by nested PCR targeting the 18 S rRNA gene. Structured field questionnaires were used to capture farm-level practices, and logistic regression was applied to identify risk factors. We detected C. cayetanensis DNA in 6.0% of produce (18/300) and 12.5% of irrigation water (15/120; p = 0.028). Canal water (20.0%) was more frequently contaminated than tube-well water (5.0%; OR 4.75; 95% CI: 1.01-22.3). Leafy vegetables and herbs had higher contamination than smooth-surfaced produce (8.0% vs. 2.0%; p = 0.009). In multivariable analysis, canal irrigation (aOR 3.41), proximity to drainage channels ≤ 50 m (aOR 3.98), and use of untreated rinsing water (aOR 2.91) remained independently associated with contamination (all p < 0.05). This study provides among the first molecular evidence of C. cayetanensis contamination at the produce-water interface in peri-urban Khyber Pakhtunkhwa, Pakistan, identifying surface irrigation and poor water management as key risk factors. However, because PCR detects DNA rather than viable organisms, these findings indicate environmental contamination and potential exposure pathways rather than direct infection risk. Sequencing confirmation is needed to exclude cross-amplification of related coccidia.
Heterogeneous agro-ecological factors, insect breeding, and climate change are serious challenges to sustainable agricultural management. The study proposes a graph-enhanced meta-adaptive federated learning framework (GNN-ML-FRL) to address the challenges in precision agriculture. The proposed framework integrates Federated Learning (FL) for collaborative training of models in a decentralized manner across geographically distributed farms, Meta-Learning (ML) for rapid adaptation to changing environmental factors, and Graph Neural Networks (GNNs) for capturing spatial dependencies among agricultural entities. A comprehensive multivariate IoT environmental dataset with 52.56 million time-series observations gathered from 500 dispersed sensors over a 12-month period, the IP102 insect pest recognition benchmark (75,222 images across 102 species), and curated genomic datasets from MaizeGDB and the Rice Annotation Project Database for genotype-informed modeling are the three standardized datasets used to assess the framework. Experimental results show statistically significant improvements (p < 0.01) over CNN and graph-based baselines, achieving 89.3% Top-1 accuracy, 7.8% higher generalization performance, and 12.4% reduction in prediction loss across geographically unseen farms. SHAP-based explainability further indicate that environmental accuracy-related features contributed nearly 63% positive influence, while loss-related factors contributed 37% negative influence, validating model robustness. Geographic generality is confirmed by site-out validation using IoT data, and resilience is improved under varied crop conditions by genotype-informed graph modeling. The findings show that a scalable and statistically sound framework for data-driven pest identification and environmental modeling in precision agriculture may be achieved by combining spatial graph reasoning, meta-adaptive learning, and decentralized training.
Skin cancer carries a significant global health concern; the incidence is further rising due to environmental exposure and genetic predisposition. In this chapter, nanotechnology is explored in the context of its practical and clinical importance for skin cancer diagnosis, treatment, and prevention. It discusses, through real-world applications and case-based insights, how nanotechnology played a role in precise drug delivery, improved immunohistochemistry (i.e., for diagnosis and marking cells), and the manufacture of diagnostic tools for early detection. The manuscript emphasizes the use of nano enabled strategies like nanovaccines that modulate the immune system against tumor antigens, nano biosensors/ biomarker detectors, nano photothermal and photodynamic therapies. Furthermore, preventive nano-devices for high-risk people are presented in terms of wearable nano-devices that monitor ultraviolet exposure. Current literature and clinical outcomes allow this to be supported for each application, showcasing the integration of advanced materials science with oncology and how this benefits patient care. The chapter bridges theoretical innovation to clinical utility in dermatologic oncology through the example of these translational advances.
Global climate change is rapidly impacting biodiversity and threatening the sustainable use of medicinal plant species by reducing their availability and increasing harvest uncertainty. Understanding the adaptive genetic variation and genetic vulnerability of medicinal plants under climate change is crucial for effective germplasm management, cultivation, and breeding efforts. In this study, we assessed the genetic differentiation, local adaptation, and genomic vulnerability of the medicinal plant Isodon rubescens (Hemsl.) H. Hara, with the goals of elucidating the impacts of geographic and environmental factors on its genetic structure and identifying at-risk populations for informed conservation and breeding under climate change. We applied restriction site-associated DNA sequencing (RAD-seq) to 17 populations of I. rubescens spanning its central and peripheral ranges, including the Taihang and Qinling-Funiu Mountains. The analysis revealed two distinct genetic groups: one in the Taihang Mountains and the other in the Qinling-Funiu Mountains. Significant patterns of isolation by distance (IBD), environment (IBE), and resistance (IBR) were detected, alongside high niche differentiation. We identified 456 candidate adaptive SNPs, some linked to genes involved in stress responses and biosynthesis. Precipitation was a key environmental driver of local adaptation. Populations in the northern Taihang Mountains and southern Funiu Mountains showed higher genomic vulnerability, indicating a greater risk of maladaptation. Our findings demonstrate that geographic isolation and environmental factors, particularly precipitation, are key drivers of genetic differentiation and local adaptation in I. rubescens. The identified genomic vulnerability pinpoints specific populations at high risk under climate change. These insights provide a crucial genetic basis for formulating targeted conservation strategies and developing climate-resilient breeding programs for this medicinal species.
Variation in plant functional traits reflects environmental adaptation. Understanding how traits shift along elevational gradients can clarify mechanisms by which species respond to environmental change. Here, we used white birch (Betula platyphylla) in the Niyang River Basin (left bank of the Yarlung Tsangpo River, Xizang) as a model species to quantify leaf trait variation along an elevational gradient and to identify key environmental drivers. Leaf functional traits were analyzed using one-way ANOVA, redundancy analysis (RDA), Pearson correlation, and principal component analysis (PCA). Coefficients of variation ranged from 5.52% to 26.14%, with leaf area showing the greatest variation and leaf water content the lowest. Most traits differed significantly among elevations: leaf area (LA), leaf length (LL), leaf width (LW), petiole length (PL), petiole base width (PBW) and leaf phosphorus content (LPC) declined with increasing elevation, whereas leaf nitrogen content (LNC) and leaf N: P ratio increased. Total chlorophyll content (TChl) and leaf water content (LWC) exhibited a hump-shaped pattern along the elevational gradient. In contrast, leaf dry matter content (LDMC) exhibited a unimodal pattern along the elevational gradient, whereas specific leaf area (SLA) and leaf mass per area (LMA) showed no significant trends with elevation. RDA indicated that soil factors were the primary drivers of leaf trait variation, explaining 50.90% of the total variance; soil total nitrogen (TN), pH, and available potassium (AK) were the most influential variables. Trait patterns suggest contrasting resource acquisition strategies across elevations: high-elevation individuals enhanced photosynthetic efficiency and shifted toward a more acquisitive "fast investment-return" strategy to cope with harsher conditions. Our findings contribute to understanding the adaptive responses of montane tree species to climate warming and improve our understanding of plant trait variation along environmental gradients.
Monolithic zirconia has become increasingly popular in clinical dentistry as an indirect restorative material fabricated using computer-aided design/computer-aided manufacturing (CAD/CAM) technology. It is widely used due to its favorable combination of mechanical strength, aesthetic potential, and biocompatibility. Its monolithic design reduces the risk of veneer chipping, thereby improving restoration longevity. To narratively review the mechanical and adhesive properties of monolithic zirconia and discuss their clinical implications. This narrative review was based on a comprehensive, non-systematic literature search conducted using PubMed/MEDLINE, Scopus, and Web of Science. English-language publications addressing monolithic zirconia, mechanical behavior, surface treatments, adhesive strategies, and clinical performance were considered. Additional studies were identified through manual screening of reference lists. Study selection was guided by relevance to the review topic rather than predefined inclusion or exclusion criteria. Monolithic zirconia demonstrates high flexural strength and fracture toughness, supporting its use in posterior load-bearing restorations. However, direct exposure to the oral environment may promote low-temperature degradation (LTD), potentially affecting long-term mechanical stability. Despite improvements in translucency, aesthetic performance remains a consideration. Adhesive durability depends largely on appropriate surface conditioning and the use of functional primers, particularly those containing 10-methacryloyloxydecyl dihydrogen phosphate (MDP), which enhance chemical bonding to zirconia. Monolithic zirconia offers a reliable balance between strength and clinical durability. Nevertheless, its long-term performance is influenced by environmental exposure and adhesive protocols. Further research is needed to optimize the resin-zirconia interface while maintaining both mechanical reliability and aesthetic outcomes.
With coral reefs increasingly threatened by rapid environmental changes, understanding genetic diversity at microgeographic scale is critical for assessing their capacity to respond to local stress regimes. Theory for continuous populations predicts that brooding corals with restricted dispersal should exhibit fine-scale genetic structure and isolation-by-distance, yet such patterns remain poorly resolved in marginal and environmentally extreme reef ecosystems. Here, we investigated the genetic structure of the catch bowl coral, Isopora cf. palifera, across 11 sites within ~ 14 km in Kenting National Park (KNP), southern Taiwan, a reefscape characterized by strong small-scale environmental heterogeneity, including chronic thermal influence from a nuclear power plant and tidally driven upwelling. We genotyped 466 colonies (six microsatellite loci yielding 302 unique multilocus genotypes) and sequenced nuclear PaxC 46/47-intron from 322 colonies of I. cf. palifera. Microsatellite data revealed strong genetic structure (K = 2, K = 5): principal coordinate analyses identified four geographic groupings, and Bayesian clustering (STRUCTURE) supported two major clusters separating Nanwan (plus Tantzei Bay) from the remaining coastal sites, with one site (Shiaowan) showing admixture. The PaxC marker resolved ten haplotypes, with H1 widespread, H2 concentrated along Nanwan, and H3 dominant at thermally influenced sites near the nuclear power plant outfall. Overall, populations showed high site differentiation, significant isolation-by-distance, and high self-recruitment (68-92%), indicating limited effective dispersal. A temporal comparison (2000-2015) at Tantzei Bay indicated stable genetic structure through time despite repeated regional disturbances. Generalized estimating equation (GEE) models showed that site-level seawater temperature was positively associated with both host haplotype composition (GEE; coefficient = 0.0479, p < 0.001) and Symbiodiniaceae genera (GEE; coefficient = 0.0462, p < 0.001, symbiont data from a previous work in KNP), suggesting non-random host-symbiont-environment associations at microgeographic scale. Together, these results indicate that I. cf. palifera in KNP exhibits pronounced fine-scale genetic structure consistent with restricted dispersal and possible microgeographic adaptation of the holobiont to local thermal regimes. While such structuring may enhance local resilience by maintaining diverse, site-specific host-symbiont combinations, it also implies limited scope for rescue via gene flow if future warming pushes populations beyond their adapted tolerances. Our findings underscore the importance of accounting for microgeographic genetic structure and local adaptation when designing management and conservation strategies for reefscape such as those in KNP.
Paddy soils derived from basalt weathering contain high levels of Fe-Mn oxides, along with elevated nickel (Ni) and chromium (Cr), posing threats to rice safety. Unlike Fe oxides, Mn oxides exhibit both adsorption and oxidation capabilities, creating complex regulatory mechanisms for Ni and Cr. The environmental impacts of these oxides depend on their spatial distribution, though the mechanisms remain unclear. This study investigates the synergistic regulation of δ-MnO2 on the speciation transformation and bioavailability of Ni and Cr. Pot experiments were setup using δ-MnO2 distributed either in the rhizosphere or sub-root layers, combined with continuous or intermittent flooding water management. Results show that δ-MnO2 spatial distribution critically influences the distinct environmental behaviors of Ni and Cr. For Ni, δ-MnO2 exhibits adsorption and immobilization effect, but these effects are strongly dependent on the position: distribution in the rhizosphere reduces the concentration of available forms and decreases Ni accumulation in rice grains, while distribution in the sub-root layer hinders downward Ni migration and increases grain Ni accumulation. For Cr, δ-MnO2 primarily converts inert Cr(III) into highly reactive Cr(VI) through oxidation, resulting in increased Cr accumulation in grains. Water management and the spatial distribution of δ-MnO2 show significant synergistic effects: continuous flooding promotes Ni release and Cr(VI) reduction, while intermittent flooding favors Ni adsorption and immobilization. This study challenges the conventional understanding that "metal oxides universally exhibit immobilization effects on heavy metals", clarifying the differential regulatory roles of Mn oxide spatial distribution in paddy soil profiles on the environmental behaviors of Ni and Cr. It reveals the "double-edged sword effect" of Mn oxides in adsorbing/immobilizing Ni while oxidizing/activating Cr, and elucidates the core principle that neglecting their vertical distribution would lead to counterproductive heavy metal control measures. The findings not only provide new insights into the mechanisms by which Mn oxides regulate Ni and Cr accumulation in rice within basalt weathering zones, but also offer scientific and theoretical support for precise management of rice safety production in geologically high-background regions based on the differential properties of heavy metals.
Radioactive cesium-rich microparticles (CsMPs) released from the Fukushima Daiichi Nuclear Power Plant (FDNPP) in 2011 pose a persistent environmental concern, yet their initial atmospheric dispersion has remained poorly constrained. Here we quantify CsMP abundance and radioactive fraction (RF) in 100 surface soil samples collected across Fukushima Prefecture in July 2011 and integrate the results with WSPEEDI atmospheric simulations. CsMP abundance ranged from 0 to 52.3 particles g⁻¹ (dry weight), with RF values of 0-61.85%. The combined analysis identifies a major CsMP formation and release event at ∼03:00 JST on 15th March 2011, producing a plume strongly enriched in CsMPs. Plumes released after 00:00 JST on 16th March contained no detectable CsMPs, indicating that particle formation had ceased by that time. The widespread distribution of CsMPs across Fukushima is therefore attributed primarily to this single plume. Directional variations in CsMP abundance reflect temporal changes in plume composition, with peak concentrations of ∼2070 particles m⁻³ toward the southwest and ∼4700 particles m⁻³ toward the northwest. These findings constrain CsMP formation mechanisms and improve reconstruction of radiological dispersion relevant to the long-term environmental risk assessment of nuclear power plants.
As the primary living environment for disabled older adults, families play a crucial role in disease prevention and maintaining their health. However, research has found that both disabled older adults and their family members experience numerous physiological, psychological, and social adaptation problems when adjusting to the changes brought by disability, severely impacting the overall health status of the family. Therefore, guided by the ERG (Existence-Relatedness-Growth) theory, this study aims to understand the family health needs of families with disabled older adults in the community, providing a basis for improving the health level of these families and developing targeted intervention programs. From December 2024 to February 2025, this study employed purposive and snowball sampling to select 12 pairs of disabled older adults and their primary caregivers from communities under the jurisdiction of Zhengzhou City, Henan Province for semi-structured interviews. Thematic analysis was applied to organize and analyze the interview data. Deductive analysis indicated that the famliy health needs of families with disabled older adults in the community can be summarized into the following three themes: existence needs (daily living needs, economic support needs, environmental modification needs), relatedness needs (family communication needs, social resource connection needs, social participation needs), and growth needs (autonomy and dignity maintenance needs, family development needs, demand for technology-enabled solutions). The results show that the family health needs of families with disabled older adults in the community are unique and diverse. Community health workers and social workers can develop and implement effective strategies based on the different levels of family needs to promote the health level of families with disabled older adults and improve the overall quality of life of these families.
Medicinal plants are widely used for applications in agriculture, food, medicine, and cosmetics due to their abundant bioactive secondary metabolites (SMs) such as terpenoids, phenylpropanoids, and alkaloids. The biosynthesis and accumulation of SMs are highly associated with multiple environmental factors. Among these abiotic stresses, drought plays a pivotal role in regulating the quality of medicinal plants. Understanding the regulatory mechanisms of medicinal plants in response to drought is beneficial for (i) cultivating high-quality traditional Chinese medicinal plants via targeted water management strategies; (ii) screening candidate marker genes to breed high-quality novel cultivars with enhanced bioactive compound accumulation under drought conditions, thereby addressing the adverse impacts of drought induced by global climate change; (iii) mining dual-functional genes that confer drought tolerance while maintaining high bioactive compound content, thus ensuring both the yield and quality of medicinal plants. To summarize the latest advances in the transcriptional regulation of SM biosynthesis with a focus on terpenoids, phenylpropanoids, and alkaloids in medicinal plants under drought conditions. A comprehensive literature search was conducted in three electronic databases including PubMed, Scopus, and Web of Science using the search terms "regulatory mechanism", "secondary metabolites", "medicinal plants", "drought stress", "transcription factor", "bioactive compound", "synthetic biology", "smart irrigation", "terpenoid biosynthesis", "phenylpropanoid biosynthesis", "phenolic biosynthesis" and "alkaloid biosynthesis". All the retrieved data were then critically reviewed and summarized. Drought affects secondary metabolite biosynthesis via a complex molecular regulatory network, including shifts in microbial community composition, epigenetic remodeling, changes in global gene expression profiles, altered catalytic activity of core biosynthetic enzymes, as well as modifications of transcription factors. This review offers novel insights into unraveling the underlying transcriptional regulatory networks, and practical implications for researchers in the fields of medicinal plant biology, natural product chemistry, and crop stress physiology.
Exogenous halide ions in aquatic environments can generate highly toxic halogenated disinfection byproducts during the advanced oxidation process, posing new environmental risks. However, the release of halide ions from widely utilized halide-containing catalysts and subsequent formation of these highly toxic byproducts have largely been overlooked. Herein, in this study, metallic Bi deposited onto BiOI to promote peroxydisulfate (PDS) activation for the degradation of bisphenol A (BPA). The results showed that the degradation rate constant of BPA on Bi/BiOI (0.323 min-1) was 8.97 times higher than that on pristine BiOI (0.036 min-1). Mechanism studies revealed that the active sites (Bi/Bi(III)) of Bi/BiOI undergo strong covalent hybridization with the p-orbitals of oxygen in PDS. This interaction disrupted the local structure of Bi/BiOI, thereby liberating iodide ions (∼0.11 mM). Quenching experiments and electron paramagnetic resonance (EPR) analysis demonstrated that the released iodide ions were locally oxidized by surface-adsorbed sulfate (Bi-*SO4·-) into reactive iodine species. Consequently, these reactive iodine species attacked BPA to form highly toxic iodinated byproducts and dimers, as identified via high-performance liquid chromatography-high-resolution mass spectrometry (HPLCHRMS). This study provides new insights into the activation mechanism of PDS by Bi/BiOI and highlights potential environmental risks of deploying BiOX-based catalysts to activate oxidants for pollutants degradation.
Wastewater treatment has become a hot topic of research in the field of environmental catalysis in recent years. However, traditional catalytic treatment methods often depended on noble-metal components or harsh reaction conditions, which were costly and difficult to meet the requirements of green and large-scale applications. To address these challenges, the core@shell structure micromotors (MMs) composed of a spherical Co3O4 core and an environmentally friendly MnO2 nanosheet shell were prepared through a solvothermal method. Under neutral pH conditions, the Co3O4@MnO2 MMs could efficiently drive the Fenton-like reaction, achieving rapid degradation of tetracycline hydrochloride with a degradation efficiency of up to 92% within 1 h under neutral conditions, thus overcoming the limitation of the conventional Fenton process that required strongly acidic media. Mechanistic studies revealed that abundant singlet oxygen was generated during the catalytic process of the Co3O4@MnO2-H2O2 system. The Co3O4@MnO2 MMs offer a promising strategy for constructing cost-effective, highly stable, and sustainable wastewater remediation systems owing to their self-propulsion capability, simple preparation, and favorable catalytic performance.
The sustainable production of silver nanoparticles (AgNPs) from renewable biowaste would reduce environmental burden and expand green nanotechnology applications. This study reports a hydrothermal extraction route that avoids external chemical reductants, thereby enabling duck-feather keratin to function intrinsically as both a reducing and capping agent in the synthesis of stable, bioactive AgNPs. Extraction was verified using the Lowry assay and SDS-PAGE, confirming preservation of protein content needed for metal coordination. One-factor-at-a-time optimization identified pH 11, 70 °C, 30 mL extract per 1 mM Ag⁺ reaction, and a 24 h duration as optimal conditions, producing uniform spherical nanoparticles having an average (11 nm) with excellent dispersion and long-term optical stability. Characterization by UV-Vis, FTIR, XRD, and SEM-EDX confirmed Ag⁺ reduction, keratin capping, and crystalline face-centered cubic Ag formation. TGA-DTA showed improved thermal stability, while BET surface area increased from 1.55 to 6.32 m2·g⁻1 after nanoparticle incorporation, indicating enhanced mesoporosity. The synthesized duck-feather keratin silver nanoparticles (DFKSN) demonstrated strong antioxidant activity and potent antibacterial performance, with DDT, MIC, and MBC assays confirming both bacteriostatic and bactericidal effects against Gram-positive and Gram-negative bacteria. The nanoparticles also promoted cytocompatibility in human skin fibroblasts cell (HSF1184) at a dose of 3.0 mg.mL-1. These findings highlight hydrothermally processed keratin as a scalable, waste-valorizing route for sustainable and eco-friendly nanomaterial production.
Catalysis was an effective method for uranium recovery and environmental remediation. However, the weak flexoelectric response, despite being universal in dielectric materials, greatly limited its appeal for research and catalytic applications. Here, we proposed a strategy to enhance the flexoelectric response by bridging inorganic chains with metal-organic chains within the structure. The resulting hybrid material, Co[C4H4N2]V2O6, demonstrated excellent uranyl removal performance, surpassing that of state-of-the-art piezocatalysts. Co[C4H4N2]V2O6 showed flexocatalytic uranyl activity across a broad pH range and under high-salinity conditions. Under a dynamic experimental setup, Co[C4H4N2]V2O6 showed strong potential for practical flexocatalytic applications. Co[C4H4N2]V2O6 could efficiently separate uranyl in contaminated potable water, reducing the uranium concentration (~2.0 ppm) to below the drinking water standard (30 ppb). It could also lower the uranium concentration (~5.6 ppm) in mining wastewater to below the discharge limit (300 ppb). Its intrinsic anisotropic mechanical properties and cantilever-like morphology endowed high deformability, which, together with a large dielectric constant, enhanced its flexoelectric polarization. The revealed flexocatalytic mechanism confirmed that uranyl was converted into insoluble (UO2)O2·2H2O by active species generated through dynamic polarization. This work provided a promising avenue for the design of advanced flexocatalysts and offered an effective strategy for uranium recovery and environmental remediation.
This study focuses on evaluating the thermoregulatory performance of a graphene-based electric heating cape and determining its optimal temperature for use in cool indoor environments during winter. Through controlled experiments with 30 participants in a climate chamber maintained at 15.5 °C, five heating conditions (no heating, 35 °C, 40 °C, 45 °C, and 50 °C) were systematically tested. Skin temperature and heart rate were continuously monitored, and subjective thermal sensation and comfort votes were collected using 7-point scales. Results demonstrated that the electric heating cape significantly improved thermal comfort, with 40 °C identified as the optimal temperature setpoint: overall thermal sensation shifted from slightly cool to slightly warm, and overall thermal comfort state attained 'slightly comfortable' level on the adaptive comfort scale. Repeated-measures ANOVA revealed that heating temperature had a highly significant effect on both overall thermal sensation and overall thermal comfort. Post-hoc tests identified 40 °C as the optimal temperature setpoint under these environmental conditions (15.5 °C). At this temperature, the overall thermal sensation vote improved significantly from - 1.23 (no heating) to -0.13 (p < 0.01), approaching a neutral sensation, while overall thermal comfort increased significantly from - 1.08 to 0.35, reaching a "slightly comfortable" level. The most significant improvements were observed in the abdomen and lumbar regions. While skin temperature showed a positive correlation with thermal perception, heart rate remained stable (± 5 bpm), indicating a low physiological burden. Marked individual differences in temperature preference underscore the importance of personalized thermal regulation. This study provides empirical evidence to guide the application and control of localized heating devices in cool indoor office settings during winter.
Accurate detection and segmentation of moving objects constitute a fundamental challenge in computer vision, particularly for intelligent video surveillance systems operating under variable illumination, dynamic backgrounds, and environmental noise. This paper presents a fully unsupervised dual-phase motion analysis framework that effectively combines statistical independence modeling and geometric contour evolution to achieve high-precision motion detection and segmentation. In the first phase, an enhanced Fast Independent Component Analysis (Fast-ICA) algorithm is employed to perform statistical decomposition of video sequences, exploiting temporal independence to distinguish moving foregrounds from static backgrounds. This process generates an initial motion mask with strong robustness to illumination variation and noise artifacts. In the second phase, a hybrid level set segmentation model integrating the global Chan-Vese formulation and a locally adaptive Yezzi-based energy function refines object boundaries through an adaptive energy minimization process. A stabilization term and a self-regulating convergence criterion are further incorporated to ensure contour smoothness, numerical stability, and resilience to topological changes. Comprehensive experiments conducted on the CDNet-2014 benchmark dataset demonstrate that the proposed method achieves an average recall of 0.9613, precision of 0.9089, and F-measure of 0.9310, outperforming several state-of-the-art supervised, semi-supervised and unsupervised background subtraction algorithms. The proposed Fast-ICA-Level Set fusion framework thus provides a robust, adaptive, and computationally efficient solution for real-world intelligent surveillance and autonomous visual monitoring applications.
The sulfidation is widely adopted for treatment of arsenic-contained solution. Within the copper smelting industry, multivalent arsenic hazards primarily arise from copper smelting waste acid (CSWA) and electrolytic refining purification solution (ERPS), also containing valuable copper resources. Due to the diversified competitive sulfidations of multivalent arsenic, the conventional mixed treatment process of Cu(Ⅱ)-As(Ⅲ) and Cu(Ⅱ)-As(Ⅴ) solutions is difficult to achieve efficient copper recovery and arsenic removal. According to Avrami kinetics, the sulfidation reaction rates for Cu(Ⅱ), As(Ⅲ), and As(Ⅴ) are 35.0339 M-1 s-1, 34.7333 M-1 s-1, and 0.05551 M-1 s-1, respectively. Thus, Cu/As separation causes 72.02% arsenic content in the Cu(Ⅱ)-As(Ⅲ) sulfide precipitates, and less than 6.45% arsenic content in the Cu(Ⅱ)-As(Ⅴ) sulfide precipitates. Interestingly, the rapid nucleation of As(Ⅲ) sulfide provides a heterogeneous nucleation and secondary growth platform for As(Ⅴ) sulfide, facilitating rapid settling of As(Ⅲ)-As(Ⅴ) sulfide. Therefore, based on the difference in sulfidation rates, a novel process for Cu/As separation in CSWA and ERPS is proposed, involving copper split recovery and arsenic mixed removal. Value assessment of this process suggests that arsenic reuse can be diminished by approximately 645 tons annually through copper split recovery, and the particle size of As(Ⅲ)-As(Ⅴ) sulfide increases at least 44.3% via arsenic mixed removal. This study improves the sulfidation process of Cu/As separation in the copper smelting industry, which is significant for environmental protection and resource recovery.
ConspectusEnzymatic catalysis represents a sustainable and selective approach to chemical synthesis, yet its practical implementation is frequently limited by the instability of enzymes under cell-free conditions. Confinement─a principle fundamental to early biochemical evolution─has emerged as a key strategy for maintaining enzymatic activity in non-native environments. This has motivated the design of robust biocatalysts through the encapsulation of enzymes within synthetic porous scaffolds. Crystalline porous frameworks (CPFs), which exhibit ultrahigh porosity, tunable pore architectures, and programmable compositions, offer an ideal platform for such confinement. In this context, the in situ growth of CPFs using enzymes as nucleation sites (biotemplates) constitutes a cutting-edge strategy to fabricate enzyme-confined CPF (E@CPF) biocatalysts. Nevertheless, this approach has been constrained by two formidable challenges: the incompatibility of conventional CPF crystallization conditions with fragile enzymes and the pervasive stability-activity trade-off in the resulting heterogeneous biocatalysts.This Account outlines our strategies to overcome these barriers through the synergistic integration of molecular linkage design, pore-channel optimization, and host-guest interface engineering. We detail a biocompatible in situ synthetic methodology enabled by moderately energetic linkages─specifically Zn-N coordination and carboxylic acid dimer hydrogen bonds─which facilitate enzyme-templated crystallization of metal-organic and hydrogen-bonded organic frameworks under aqueous ambient conditions. We further illustrate how reticular chemistry can be leveraged to precisely tailor pore channels and interfacial interactions between the enzyme guest and the CPF host. Such control not only facilitates substrate diffusion but also can predispose the enzyme into a catalytically favorable conformation, providing a viable pathway to overcome the classic stability-activity trade-off in heterogeneous biocatalysis. Translating these fundamental insights, we showcase functional E@CPFs systems for biocatalytic sensing, therapeutic nanodrugs, and photoenzyme coupled catalysis for environmental remediation. Finally, we discuss enduring challenges and future directions, advocating for advanced characterization, predictive design, and increased functional complexity to fully harness the potential of CPF-confined enzymes for multidisciplinary applications. This body of work offers both a strategic blueprint for hybrid biocatalyst design and a deeper understanding of enzymatic behavior under nanoconfinement.