Search Results (3,151)

Fiber-based and fabric batteries signify a groundbreaking development in energy storage, allowing for the straightforward incorporation of power sources into wearable fabrics, intelligent apparel, and adaptable electronics. In this study, we introduce a novel strategy for one-step fabrication of a flexible lithium titanate oxide (Li₄Ti₅O₁₂, LTO) anode directly on a copper current collector via electrospinning, eliminating the need for high-temperature post-processing. Based on our previous work with electrospun nanofiber cathodes and carbon-based current collector, we prepared the LTO electrode using polyethylene oxide (PEO) as a binder and carbon additives to enhance mechanical integrity and conductivity. LTO fiber mats detached from the current collector were found to endure multiple instances of bending, twisting, and folding without any structural damage. LTO/Li cells incorporating electrospun fiber LTO electrodes with 72 wt% active material loading deliver a high capacity of 170 mAh g⁻¹ at 0.05 C. In addition, they demonstrate excellent cycling stability with a capacity loss of only 0.01% per cycle over 200 cycles and maintain a capacity of 160 mAh g⁻¹ at 0.1 C. The scalability of the heat-treatment-free method for fabricating flexible LTO anodes, together with the improved mechanical durability and electrochemical performance, offers a promising route toward the development of next-generation flexible and wearable energy storage devices. Full article

Efficient composting is essential for sustainable organic waste management, yet conventional monitoring approaches are limited by single-parameter measurements and delayed response. This study presents an integrated sensor–AI framework designed to capture the interaction between thermal, chemical, and environmental factors governing composting. A distributed in-pile sensor network continuously measured temperature, moisture, and pH, while ambient parameters and gaseous emissions (O₂, CO₂, CH₄) were recorded to validate process dynamics. Statistical analyses, including correlation and regression modeling, were applied to quantify parameter interdependencies and the influence of external conditions. Results showed strong positive associations between temperature, moisture, and CO₂, and an inverse relationship with O₂, indicating active microbial respiration and accelerated decomposition. The validated sensors maintained high accuracy (±0.5 °C, ±3%, ±0.1 pH units) and supported real-time feedback control, leading to improved nutrient enrichment (notably N, P, and K) in the final compost. The framework demonstrates a transition from static measurement to intelligent, feedback-driven management, providing a scalable and reliable platform for optimizing compost quality and advancing sustainable waste-to-resource applications. Full article

Cladophora glomerata is a species of green algae from the Cladophoraceae family belonging to the class Ulvophyceae. This filamentous macroalga is generally associated with freshwater habitats, especially in nutrient-rich ecosystems. It produces high biomass and occupies large areas of freshwater. The robust filaments of Cladophora glomerata form dense mats that are easy to harvest. It is also rich in proteins, macro- and micronutrients, and other bioactive compounds. Therefore, its biomass could be used in various fields of sustainable agriculture, for example, promoting plant growth and yield, purifying soil, improving crop properties against biotic and abiotic stress, or it could be used in husbandry as a feed supplement. It is also becoming increasingly attractive for use in sustainable farming. This review provides an update with the latest information on the use of freshwater Cladophora glomerata in sustainable farming and suggests the most promising fields of research. Full article

Highly sensitive flexible pressure sensors are crucial for wearable health monitoring and human–machine interaction. While the emerging iontronic sensors inherently offer high sensitivity, this can be further improved by engineering microstructured interfaces. In this study, we employ four different types of common fiber materials as substrates for fabricating ionic dielectric layers by a simple impregnation of ionic liquid (IL). A comparative study reveals that the porosity and microstructural architecture (e.g., fiber diameter) of the substrate material directly influences the amount of adsorbed IL and consequent sensing performance. We achieved the highest sensitivity by using a thin electrospun TPU/IL nanofiber mat (33 μm), which exhibited high sensitivities of 3.10 kPa⁻¹, 1.85 kPa⁻¹, and 1.02 kPa⁻¹ in the pressure ranges of 0–200 kPa, 200–400 kPa, and 400–700 kPa, respectively. Furthermore, the sensor exhibited an excellent fast response (2.71 ms) and recovery time (8.71 ms), along with outstanding cyclic stability. This work provides valuable guidance for selecting and utilizing common fiber materials to develop high-sensitivity iontronic pressure sensors, paving the way for their practical application in next-generation wearable electronics. Full article

Background/Objectives: According to the World Drug Report 2025, cannabis is the most abused drug in the world, being sold in illicit markets in various physical forms ranging from herbal cannabis to cannabis resin and liquid cannabis. Currently, the methods used for cannabis identification are largely based on the morphological features and chemical content of the product. In this respect, identification could be severely impacted if the product is highly fragmented or pulverised. As such, DNA-based molecular techniques offer a viable alternative detection approach. In this study, we have developed a robust DNA testing method for cannabis identification, with high sensitivity and specificity. Methods/Results: Two plant DNA barcode regions, rbcL and matK, were successfully amplified in a cohort of 54 cannabis plant samples. DNA sequences obtained from these samples were blast-searched against GenBank and resulted in returned matched identity of at least 99% compared to their corresponding Cannabis sativa reference sequences. In addition, the amplification of two cannabis-unique markers, the tetrahydrocannabinolic acid synthase (THCAS) and cannabidiolic acid synthase (CBDAS) genes, produced amplicons with expected sizes only in cannabis samples; these amplicons were not detected in those plants closely related to cannabis. Sequence comparison of the majority of samples yielded at least 97% matched identity against C. sativa reference sequences in GenBank. The THCAS and CBDAS markers detected only the cannabis DNA in varying levels of cannabis–hops and cannabis–tobacco DNA mixtures. Lastly, the use of the four markers could effectively differentiate between cannabis and non-cannabis in 27 blinded samples, including 18 actual casework samples. Conclusions: In conclusion, these four genetic markers can be used to discriminate cannabis from other plant species at the genus level, especially in challenging forensic samples lacking morphological features which therefore cannot be determined by traditional detection methods. As such, this method can complement existing techniques to identify a myriad of cannabis samples. Full article

Landscape character assessment (LCA) is a systematic approach used to classify, describe, and analyze the physical and cultural attributes that define the landscape. The traditional approaches to LCA are fundamentally subjective and descriptive, relying on human evaluations of aesthetic value, and they often show inconsistencies in results when assessed by different observers for the same landscape. This research aims to establish a spatial and quantitative methodology through GIS for evaluating the landscape character of King Khalid University (KKU)’s campus in the Southern Province of Saudi Arabia, which is considered crucial for designing a sustainable and context-sensitive landscape. To identify the feasible developed areas and their sustainable characteristics, three key landscape variables were measured and spatially expressed, subsequently averaged to categorize landscape character. The variables include land use and land cover, which were obtained from Sentinel 2 remote sensing data through supervised classification, as well as landforms and hydrological settings derived from a digital elevation model (DEM) utilizing GIS functionalities. The findings revealed three distinct landscape characters, each characterized by quantifiable landscape attributes. The landscapes exhibiting the most significant character encompass approximately 20% (1074 ha) of the study area, whereas those with the least significance account for 6.5% (342 ha). The remaining 73.5% (3884 ha) is classified as landscapes with an average significance character. The results provide a solid scientific basis for choosing locations in the campus’s study area that promote environmentally friendly and sustainable landscape development. This method improves objectivity in LCA and offers a reproducible framework for implementation in arid and semi-arid areas. Full article

PM_2.5 is the primary source of urban atmospheric pollution, as it not only damages the ecological environment but also poses a threat to human health. Taking the Yangtze River Economic Belt as the research object, this study analyzes the spatiotemporal variation characteristics of PM_2.5 concentrations in the region from 2005 to 2020. Furthermore, by combining the Geodetector model with Geographically and Temporally Weighted Regression (GTWR) model, the spatiotemporal heterogeneity of its influencing factors is revealed at three scales: municipal, watershed, and grid. The results show that, from 2005 to 2020, the annual average PM_2.5 concentration in the Yangtze River Economic Belt exhibited an inverted U-shaped trend with 2013 as the inflection point, showing distinct spatial clustering characteristics. Overall, the spatiotemporal variation in annual average PM_2.5 concentration demonstrated a significant downward trend during this period, with slower decline rates in the western region and faster rates in the central and eastern regions. Spatial differentiation of annual average PM_2.5 concentrations within the region was primarily influenced by three factors: PFA, PISA, and PD. NDVI and PWA exerted their effects mainly at large scales, while MAT and SDE primarily acted at small scales. Within the region, NDVI and CVO predominantly suppressed PM_2.5 concentrations, whereas MAT, PFA, PD, and SDE primarily promoted PM_2.5 pollution. The spatial distribution of effects for factors within the same category is broadly consistent across the three scales, though details vary. This study overcomes previous limitations of administrative-scale research, yielding more refined results. It provides new methodologies and insights for future research while offering more precise scientific support for regional PM_2.5 governance. Full article

In this paper, different physiochemical and biological indicators were tested to determine and compare the water quality of the Zaalklapspruit ecologically engineered wetland before and after a veldfire. Five sampling sites and a reference site 2.2 km upstream of an acid mine drainage (AMD)-decanting coal mine were selected and sampled before and after the veldfire. The “black box” method was also employed to determine the percentage change in the selected in- and outflow variables before and after the veldfire. After the veldfire, Al was reduced by 97.43%. The same trend was observed for Fe, which decreased by 99.65% at the outflow, and Mn and sulphate levels decreased by 98.41% and 68.16%. Possible pathways of the reduction in acid mine drainage impacts on the wetland were identified after the veldfire, including the increase in waterflows during the wet season causing a dilution factor, and phycoremediation by macroalgae drifting mats that accumulate metals and ash slurry from the burned-out macrophyte plant material that may have increased the wetland’s alkalinity. A comprehensive framework for the digital twinning and monitoring of the effects of natural disasters on wetlands is also presented. Full article

[Objectives]: By performing genome assembly, annotation, comparative characterization, and phylogenetic analysis on the complete chloroplast genomes of E. tubulosa and E. japonica—two medicinal plants belonging to the genus Euchresta—this study aims to identify their differential genes, thereby providing fundamental research for screening candidate genes as DNA barcodes for species identification and facilitating the conservation of these endangered species. [Methods]: Illumina PE150 sequencing was performed. Chloroplast genomes (plastomes) were assembled and annotated with GetOrganelle/SPAdes. Comparative analyses assessed gene content, IR/LSC/SSC structure, repeat profiles, and codon-usage bias. Using related Fabaceae as references, we conducted mVISTA alignments and sliding-window nucleotide diversity (Pi) analyses to identify candidate DNA barcodes. Phylogenies from whole-plastome sequences were inferred with Maximum Likelihood, Bayesian Inference, and Maximum Parsimony. [Results]: The plastomes measured 153,960 bp (E. japonica) and 150,146 bp (E. tubulosa), with GC contents of 36.30% and 36.20%, respectively, each exhibiting a typical quadripartite structure. IR/SC boundaries were highly conserved without evident expansion or contraction. Repeat statistics were 20/30 palindromic repeats, 57/64 tandem repeats, and 156/159 simple sequence repeats (SSRs) in E. japonica/E. tubulosa, respectively. Leucine was the most frequently encoded amino acid, cysteine the least, and codon usage favored A/U at third positions. Five hypervariable loci—rps19, psbA, trnK, matK, and rps16 (Pi > 0.03)—were identified as candidate DNA barcodes. All trees consistently placed both species within Papilionoideae (Fabaceae) and recovered the closest relationship to Sophora macrocarpa. [Conclusions]: This study provides, for the first time, complete plastomes and candidate barcoding regions for two protected Euchresta species, supplying foundational resources for species identification, resource assessment, and conservation planning. Full article

Thermally activated building systems (TABS) rely on high thermal mass materials, such as concrete, which perform well thermally but have a high carbon footprint. This study systematically investigates the thermal behavior of bio-based materials—spruce, pine, beech, and oak—in TABS using numerical simulations, comparing them with conventional and hybrid materials like concrete and clay. A total of 120 variants were simulated with different pipe diameters, spacing, embedment depths, and inlet temperatures. Thermal properties, particularly thermal conductivity and specific heat capacity, significantly influenced component activation efficiency. Concrete exhibited a characteristic cooling time of 71 h at an inlet temperature of 26 °C (pipe diameter 16 mm), while pine reached 80 h under the same conditions. The use of capillary tube mats extended the cooling times to 75 h for concrete and 92 h for pine. Although concrete provides the best thermal performance, certain bio-based materials achieve comparable results under optimized conditions. Hybrid systems with mineral components offer additional potential for improvement. These findings demonstrate that ecologically sustainable component activation using bio-based materials is feasible with only moderate efficiency losses compared to mineral-based systems, provided system parameters are appropriately adapted. Full article

The development of advanced wound dressings that integrate favorable physico-mechanical properties with the ability to support physiological healing processes remains a critical challenge in biomaterials science. An ideal dressing should modulate the wound microenvironment, prevent infection, maintain hydration, and possess adequate strength and elasticity. This study aimed to fabricate and characterize electrospun chitosan (CS)-based 3D scaffolds dual-reinforced with halloysite nanotubes (HNTs) and cerium oxide nanoparticles (CeONPs) to enhance material properties and biological performance. HNTs were incorporated to improve electrospinnability and provide mechanical reinforcement, while CeONPs were added for their redox-modulating and anti-inflammatory activities. Composite mats were fabricated via non-capillary electrospinning. The individual and synergistic effects of HNTs and CeONPs were systematically evaluated using physico-chemical methods (SEM, EDX, WAXS, TGA, mechanical testing) and biological assays (in vitro cytocompatibility with mesenchymal stem cells, in vivo biocompatibility, and wound healing efficacy in a rat model). Scaffolds containing only HNTs exhibited defect-free nanofibers with an average diameter of 151 nm, whereas the dual-filler (CS-PEO-HNT-CeONP) composites showed less uniform fibers with a rough surface and a larger average diameter of 233 nm. The dual-filler system demonstrated significantly enhanced mechanical properties, with a Young’s modulus nearly double that of pure CS mats (881 MPa vs. 455 MPa), attributed to strong interfacial interactions. In vivo, the CS-PEO-HNT-CeONP scaffolds degraded more slowly, promoted earlier formation of a connective tissue capsule, and elicited a reduced inflammatory response compared to single-filler systems. Although epithelialization was temporarily delayed, the dual-filler composite ultimately facilitated superior tissue regeneration, characterized by a more organized, native-like collagen architecture. The synergistic combination of HNTs and CeONPs within a CS matrix yields a highly promising scaffold for wound management, offering a unique blend of tailored biodegradability, enhanced mechanical strength, and the ability to guide healing towards a regenerative rather than a fibrotic outcome, particularly for burns and traumatic injuries. Full article

Environmental and ancient DNA are mostly present in degraded forms in nature. Plant forensics is necessary for plants like Taxus (Taxaceae), which is a medicinal, as well as poisonous, endangered plant. We designed a study to develop high-efficiency PCR mini-barcoding primers for the identification of Taxus. We collected environmental materials, fresh and old Taxus specimens from natural habitats, herbaria, and ex situ propagation sites. Taxon-specific mini-barcoding primers were prepared through primer3. All the primers were amplified onto Taxus specimens and environmental samples having Taxus DNA, while no amplification on fresh and herbarium specimens other than Taxus was noted. DNA sequencing of amplified regions of matK, ITS, and rbcL yielded lengths of 117, 175, and 200 bp. Blast taxonomy showed 100% identification power at the genus level, while 75–93% at the species level, and identified a total of 30 taxa within the genus Taxus, comprising 16 species, 5 varieties, 2 hybrids, and 7 variants. ITS was the most specific for genus identification, followed by matK and rbcL. Environmental, trade, socio-economic, and toxicological crimes were also identified. Our high-efficiency PCR mini-barcoding method can be useful in the prevention of Taxus illegal trade and habitat degradation to mitigate climate change in the Himalayan region of Pakistan. Full article

Chronic pain is a serious health issue, often irrationally managed by conventional analgesics. Duloxetine, a serotonin–norepinephrine reuptake inhibitor (SNRI), also effective in neuropathic and musculoskeletal pain, but the molecular mechanism of its analgesic action is still unclear. Here, we examined whether Duloxetine exerts pleiotropic effects by directly targeting phosphorylated STAT3 (pSTAT3), a key regulator of neuroinflammation and pain sensitization. Molecular docking showed that Duloxetine binds with pSTAT3 with binding energy −5.83 kcal/mol. Ruxolitinib, a JAK/STAT inhibitor used as reference, showed binding energy of −6.19 kcal/mol. Molecular dynamics (MD) simulations confirmed stable Duloxetine–pSTAT3 complexes, while MM-PBSA free energy analysis revealed more favorable binding for Duloxetine (ΔG = −15.17 kJ·mol⁻¹) than Ruxolitinib (ΔG = −12.98 kJ·mol⁻¹) for pSTAT3. In-vitro analyses, Western blot showed that Duloxetine significantly reduced IL-6–induced STAT3 and pSTAT3 expression in C2C12 cells in a dose-dependent manner (6.4 and 12.8 μM, *** p < 0.0001), although Ruxolitinib produced a stronger suppression. Transcriptomic analysis revealed Duloxetine-specific enrichment of mitochondrial, oxidative phosphorylation, and synaptic pathways, distinct from the immune-suppressive influence of Ruxolitinib. RNA-seq further revealed that STAT3 transcript abundance remains constant under all treatment conditions, indicating that post-transcriptional or post-translational mechanisms, such as phosphorylation-dependent activation, may be involved rather than transcriptional modulation of STAT3 in action of Ruxolitinib and Duloxetine and the formation of novel STAT3 indicating enhanced transcript diversity. The rMATS splicing analysis confirmed dose-dependent modulation, with Duloxetine promoting mild exon skipping at 6.4 μM (IncLevel 0.90 → 0.80) and recovery at 12.8 μM (0.85 → 0.86), while Ruxolitinib induced stronger exon inclusion (0.85 → 1.00,0.94), with broader transcript suppression at 6.4 μM and 12.8 μM, respectively. These findings establish Duloxetine as a dual-action therapeutic that combines neurotransmitter reuptake inhibition with pSTAT3 suppression and isoform-level transcriptomic modulation. This pleiotropic mechanism provides a rationale for its durable analgesic effects and supports repurposing in STAT3-associated disorders. Full article

Historic floors, including mosaics, stone slabs, and decorated pavements, are fragile elements that can be easily damaged during restoration works. Risks arise from falling tools, concentrated loads of scaffolding or equipment, and the repeated passage of workers. Traditional protection methods, such as plywood sheets, mats, multilayer systems, or modular plastic panels, have been applied in different sites but often present limitations in adaptability to irregular surfaces, in moisture control, and in long-term reversibility. This paper introduces an innovative approach developed within the 3D-EcoCore project. The proposed solution consists of a bio-inspired modular sandwich system manufactured by 3D printing with biodegradable polymers. Each module contains a Voronoi-inspired cellular core, shaped to match the geometry of the floor obtained from digital surveys, and an upper flat skin that provides a safe and resistant surface. The design ensures mechanical protection, adaptability to uneven pavements, and the possibility to integrate ventilation gaps, cable pathways, and monitoring systems. Beyond heritage interventions, the system also supports routine architectural maintenance by enabling safe, reversible protection during inspections and minor repairs. The solution is strictly temporary and non-substitutive, fully aligned with conservation principles of reversibility, recognizability, and minimal intervention. The Ninfeo Ponari in Cassino is presented as a guiding example, showing how multilevel knowledge and thematic mapping become essential inputs for the tailored design of the modules. The paper highlights both the technical innovation of the system and the methodological contribution of a knowledge-based design process, opening future perspectives for durability assessment, pilot installations, and the integration of artificial intelligence to optimise core configurations. Full article

The mesh size significantly affects the accuracy and computational efficiency of finite-element analysis (FEA) simulations. This study investigates mesh regularization to mitigate mesh dependency, align numerical results with experimental data, and optimize the computational time for carbon/epoxy composites. Mesh regularization was implemented using the ^∗MAT_ADD_GENERALIZED_DAMAGE (MAGD) model in LS-DYNA, which incorporates a scaling factor based on the ply orientation and stress triaxiality to adjust the material failure criterion. To address the limitations of trial-and-error methods for determining scaling factors, four analytical models were developed to predict these factors as functions of element size. These predictions were validated against experimentally derived scaling factors for unidirectional carbon/epoxy composites across three ply orientations (0°, 45°, and 90°) and three stress triaxiality conditions (tension, compression, and shear) using mesh sizes ranging from 0.5 mm to 1.5 mm. The scaling factor effectively reduced the mesh dependency in the tested configurations. A clear relationship between ply orientation and mesh regularization was established; however, no definitive correlation was observed with stress triaxiality. Among the theoretical approaches, the stress degradation model yielded the most consistent predictions, although discrepancies with the experimental results indicate the need for further refinement. This study proposes integrating scaling factors into a material model as a practical approach to mesh regularization for orthotropic materials and evaluates existing theoretical models for predicting these factors. Full article