Search Results (1,653)

The building and construction sector accounts for approximately 37% of global CO₂ emissions and nearly 50% of material extraction, driving urgent demand for sustainable material alternatives. Bio-based composites derived from recycled waste and biomass offer a promising pathway toward a circular built environment, yet their production remains hampered by biomass batch variability, the absence of standardized process protocols, and sensitivity to environmental conditions. Digital twin (DT) technology, with its capacity for real-time monitoring, predictive simulation, and closed-loop optimization, has been widely applied in building operation and maintenance but has received scant attention at the material production end. This paper addresses this cross-disciplinary gap by proposing a five-layer DT conceptual framework for the standardized production of bio-based composites, developed using the Design Science Research paradigm. The framework comprises a physical layer, a data acquisition layer, a virtual model layer, a decision and control layer, and a lifecycle-circularity layer, mapped onto five production stages from raw material to recovery. An observe–simulate–decide–adjust (OSDA) closed-loop mechanism runs across all stages. A synthetic-data simulation of the OSDA closed-loop mechanism across 200 virtual production batches illustrates a 48.5% reduction in performance variability (95% CI: 42.9–53.7%) and a 99.0% reduction in the reject rate (95% CI: 96.9–100.0%) in a biochar–recycled-HDPE panel scenario; sensitivity analysis confirms robustness across a range of moisture penalty assumptions. These results are derived from a simplified regression model and constitute numerical proof-of-concept rather than empirical validation. The study contributes a structured, standards-aligned architecture that bridges digital twins and circular building materials, providing a methodological reference and conceptual justification for industry stakeholders. Full article

Lake Nasser represents Egypt’s principal strategic freshwater reservoir; however, its long-term phytoplankton dynamics at the basin scale remain insufficiently characterized. This study presents a detailed spatiotemporal investigation of chlorophyll-a (Chl-a) variability across the reservoir during the 2002–2020 period using exclusively MODIS-Aqua Level-3 satellite observations. As no concurrent in situ measurements were available for validation, the reported values are treated as satellite-derived Chl-a estimates rather than direct observations of phytoplankton biomass. A non-parametric statistical approach, incorporating the Mann–Kendall test, Theil–Sen slope estimator, coefficient of variation (CV), and relative anomaly analysis, was used to characterize pixel-level climatology and temporal trends. The findings demonstrate that the reservoir exhibits pronounced spatial heterogeneity and a well-defined bimodal seasonal pattern associated with the annual Blue Nile flood pulse during August–October and winter convective mixing processes between November and February. Although annual-scale analysis did not indicate a statistically significant monotonic trend, seasonal investigations revealed strongly contrasting temporal responses throughout the year. At the pixel level, significant increases dominated ten of the twelve calendar months, from September through June, with median slopes among significant pixels of +0.36 to +1.47 mg m⁻³ yr⁻¹. July and August reversed this pattern, combining significant declines along the northern and central main channel with the steepest increases in the record at the extreme southern inflow. The directional contrast was unaffected by control of the false discovery rate within each calendar month (q = 0.05), which retained 66% of the significant pixels. Summer conditions were additionally marked by substantial temporal variability (CV > 60%) and pronounced positive anomalies, reaching +274.51% during August. Notably, these anomalies were spatially concentrated within the central and southern sectors of the reservoir, rather than within the conventionally productive northern region. This spatial redistribution, together with the broad enrichment tendency indicated by the pixel-level trends, points to an intensification of the summer maximum within the southern inflow zone and to a possible emergence of localized eutrophication risk, a hypothesis that requires confirmation through concurrent nutrient, transparency, and dissolved-oxygen observations. Overall, the study provides valuable geospatial insights for the environmental management of Lake Nasser, emphasizing the importance of implementing targeted early-warning systems for harmful algal bloom monitoring. The results also demonstrate the critical role of satellite-based Earth observation technologies in supporting adaptive water resource management under evolving climatic and hydrological conditions. Full article

Spray application in spatially heterogeneous three-dimensional crop canopies is constrained by inadequate within-canopy deposition, off-target losses, and poor matching between operating parameters and target structure. This review synthesizes the technological evolution of intelligent agricultural spraying equipment from the perspectives of airflow-assisted transport, demand-based dose allocation, target sensing, actuation control, system integration, and performance evaluation. Air-assisted spraying has expanded transport regulation from hydraulic output alone to coordinated airflow–droplet–canopy interactions. Variable-rate and prescription approaches subsequently linked dose allocation to measurable spatial differences in canopy structure and target distribution. Ultrasonic sensing, light detection and ranging (LiDAR), red–green–blue depth (RGB-D) imaging, machine vision, and multimodal perception have increased the spatial and semantic resolution of target representation. Pulse width modulation (PWM), fuzzy control, and data-driven methods have improved nozzle-level actuation and compensation for nonlinear hydraulic dynamics. However, closed-loop actuator or navigation should not be conflated with closed-loop control of application quality: deposition, drift, and biological efficacy are still evaluated mainly after operation and are rarely used as real-time feedback variables. Current limitations arise less from the absence of individual sensing or control technologies than from weak coupling among canopy representation, spray transport, multivariable actuation, and performance feedback. Future development should prioritize transferable multiscale models and explicit coordination of liquid flow, airflow, droplet size, speed, and equipment state. Scenario-specific architectures must connect sensing, decision-making, actuation, and evaluation without sacrificing field robustness. Full article

Background: This study examined training-to-match transferability of positional coordination in semi-professional football players, comparing responses between defensive and midfield/offensive positional sectors. Methods: Twenty-nine players were monitored during the 2023–2024 season. Positional data and external load were collected using global positioning system (GPS) technology. Technical–tactical key performance indicators (KPI) were obtained from SportsBase. Internal training load was assessed using the rating of perceived exertion (RPE), and wellness status was evaluated using the Hooper Index (HI). Results: Official matches were associated with greater total distance, average and maximum speed, speed events, acceleration and deceleration events, and mechanical power outputs (p < 0.001), with the largest effects for maximum speed (d = 1.25), deceleration events (d = 1.14), speed events (d = 1.13), and relative mechanical power (d = 1.05). Positional responses showed distinct training-to-match patterns. In the defensive sector, the official matches showed higher spread rate (SR; p = 0.031, d = −1.83) and contraction time (CT; p = 0.007, d = −2.20). In the midfield/offensive sector, matches showed greater effective playing space, width, length, longitudinal synchronization, distance to sector centroid, and stretch index (p = 0.005–0.017; d = 1.73–2.61), whereas dyadic-distance variability was greater during training (p < 0.001, d = 4.46). Linear mixed-effects models confirmed greater locomotor and high-intensity demands during matches, while positional differences were more selective. No statistically robust tactical-sector differences were observed for KPIs, internal load, or wellness after adjustment for multiple comparisons. Conclusions: Training-to-match transferability was positional sector-dependent, with greater spatial expansion and longitudinal coordination in offensive players and higher overall locomotor demands during matches. Full article

China’s decentralized governance system relies partly on governance tournaments. We exploit the staggered award of the 5A Tourist Attraction Designation, China’s highest official rating for tourist attractions, as a quasi-natural experiment. We combine city-level designation records with panel data on Chinese A-share listed firms from 2000 to 2023. Difference-in-differences estimates suggests that 5A tourist attraction designation is associated with higher corporate green total factor productivity in affected cities. This result is robust to relaxing the parallel trends assumption, using bounds based on imperfect instrumental variables, and applying estimators that accommodate heterogeneous treatment effects. Evidence on mechanisms points to greater green innovation, substantive improvements in environmental practices, and higher investment efficiency. The effects are larger for non-state-owned firms, downstream firms, and firms located in the Two Control Zones or in cities with more developed green finance. Double machine learning estimates further indicate that the designation strengthens green technology spillovers. These findings identify an environmental governance benefit of tourism-based place designations and show how such policies can promote sustainable development by reshaping local government and firm incentives. Full article

The increasing global demand for sustainable energy has intensified interest in bioethanol as a renewable alternative to fossil fuels. While first- and second-generation bioethanol technologies have advanced considerably, challenges related to production cost, efficiency, and sustainability remain. Filamentous fungi have emerged as promising biocatalysts due to their ability to produce cellulolytic and hemicellulolytic enzymes that efficiently degrade lignocellulosic biomass into fermentable sugars. Genera including Trichoderma, Aspergillus, Fusarium, Neurospora, and Penicillium play significant roles in enhancing biomass saccharification and improving ethanol production. Co-cultivation strategies involving filamentous fungi and yeasts further enhance substrate utilization, ethanol yield, and process stability, although scalability and culture compatibility remain challenging. Recent advances in metabolic engineering, mutagenesis, and CRISPR-based genome editing have enabled the development of improved fungal strains with enhanced enzymatic performance and substrate conversion efficiency. Beyond bioethanol production, filamentous fungi are increasingly recognized as key components of integrated biorefinery systems through their capacity to utilize diverse feedstocks and generate value-added products, including organic acids, industrial enzymes, and bioactive compounds. Despite limitations such as variable growth rates, substrate heterogeneity, and inhibitory by-products, filamentous fungi represent versatile and sustainable platforms for advancing second-generation bioethanol production and supporting future circular bioeconomy and biorefinery development. Full article

Smart rings are emerging as a promising class of sensing devices that enable unobtrusive, always-available interaction with Internet of Things (IoT) ecosystems. These wearable devices support intuitive gesture-based control while minimizing user attention and preserving mobility. However, despite rapid advances in sensing hardware and gesture recognition algorithms, little is known about how users associate ring-based shared gestures with smart-home commands. To fill this gap, this paper presents Oringano, a framework for designing and evaluating a vocabulary of shared ring-based gestures for controlling IoT devices in a smart home. These gestures are original in that members of the same group can share the same gestures for the same actions, as well as gestures customized by each individual. The proposed approach combines (i) a synthesis of contemporary smart ring-based gesture interaction literature, (ii) a user-centered requirements elicitation identifying representative smart-home control actions, (iii) a gesture elicitation study involving $N=30$ participants to derive a vocabulary of shared ring-based gestures for 15 IoT control actions, (iv) an empirical analysis of gesture agreement and usability of Oringano, a smartphone prototype for managing shared ring-based gestures, and (v) a set of implications for designing shared gestures for future smart-ring systems. Experimental results demonstrate high agreement for concrete actions such as selection, navigation, and media control, whereas abstract actions exhibit greater variability, highlighting opportunities for personalized gestural interaction. The shared gestures benefit from a higher average agreement rate (+84%), a slightly lower goodness of fit (−13%), and a longer thinking time (+115%) than normal ring-based gestures. The subjective satisfaction resulting from the usability evaluation of Oringano, based on the elicited vocabulary, is overall positive (4.5/5). These results advance the design of next-generation ring-based systems by bridging user-centered gesture interaction with practical sensing technologies for IoT interaction. Full article

Two-stage anaerobic digestion (TSAD) is an alternative to single-stage anaerobic digestion, separating hydrolytic–acidogenic and methanogenic phases to improve stability, organic matter degradation, and methane production. This review examines TSAD for co-digestion of sewage sludge (SS) and the organic fraction of municipal solid waste (OFMSW), emphasizing performance, scale-up challenges, digestate intensification, and nutrient recovery. TSAD can increase methane production by 25–50% compared with single-stage systems, while volatile solids removal can reach 87–93% depending on substrate type, temperature regime, hydraulic retention time, and organic loading rate. However, improvement remains variable and depends on substrate biodegradability, reactor configuration, and process control. Beyond methane recovery, the review highlights valorizing digestate as a secondary resource. Digestate post-treatment technologies, including thermal hydrolysis and steam explosion, report methane improvements from 26% to more than 300%, although energy demand and economic feasibility remain constraints. Nitrogen recovery technologies, including ammonia stripping and membrane contactors, can achieve efficiencies above 80–95% under optimized conditions, while phosphorus may be recovered through struvite precipitation, calcium phosphate recovery, or biochar-based pathways. Future TSAD development should integrate biological conversion, digestate recirculation, nutrient recovery, techno-economic assessment, and life-cycle evaluation to support circular, resource-efficient organic waste treatment systems. Full article

Fetal magnetocardiography (fMCG) provides direct non-invasive assessment of fetal cardiac electrophysiology, enabling detailed evaluation of cardiac rhythm, conduction, and repolarization. However, the clinical adoption of conventional fMCG has been limited by its reliance on superconducting quantum interference device (SQUID) systems, which require cryogenic cooling and specialized infrastructure. Optically pumped magnetometers (OPMs) have emerged as a promising cryogen-free alternative with the potential to broaden access to fetal electrophysiological assessment. This review summarizes the technological evolution and early clinical evaluation of OPM-based fMCG through an analysis of original in vivo human studies published up to June 2026. Twelve eligible studies were identified and synthesized narratively. Advances in sensor design, magnetic shielding, acquisition strategies, and signal-processing algorithms have enabled SQUID-comparable signal quality and cardiac interval measurements while substantially reducing cryogenic and infrastructure requirements. OPM-fMCG has demonstrated the potential to assess fetal cardiac time intervals, heart rate variability, fetal movement, and clinically important arrhythmias, including congenital long QT syndrome, atrioventricular block, and supraventricular and ventricular tachyarrhythmias. However, the available evidence remains dominated by small, single-centre studies, with relatively few fetuses affected by clinically significant arrhythmias. Prospective multicenter clinical validation, protocol standardization, independent replication, and regulatory evaluation are therefore required before OPM-fMCG can be integrated into routine diagnostic pathways for pregnancies requiring advanced fetal electrophysiological assessment. Full article

To overcome the problems of poor durability and structural incompatibility inherent in conventional urban traffic monitoring technologies, this study develops a self-sensing asphalt concrete composite incorporating carbon fiber (CF) as a conductive functional filler to construct an internal conductive network. The effects of CF dosage and loading rate on the electrical and dynamic piezoresistive characteristics of the composite were systematically investigated. Furthermore, the evolution mechanism of the micro-conductive network was revealed via electrochemical impedance spectroscopy (EIS) coupled with equivalent circuit modeling. The results demonstrate that the electrical resistivity follows a two-stage percolation behavior (“sharp decline followed by stabilization”) with increasing CF content, yielding a percolation threshold of 0.2 wt%. As CF dosage increases, the Nyquist plots transition from quasi-linear profiles to a fully developed single semicircle, and eventually to an alternating pattern of high-frequency capacitive arcs and low-frequency diffusion impedance. Equivalent circuit analysis reveals that higher CF loadings reduce both contact and tunneling resistances while simultaneously elevating interfacial capacitance. Under monotonic loading, the developed conductive network enables enhanced piezoresistive responses, and the 0.2 wt% group achieves the most pronounced improvement relative to the 0.1 wt% group, with the maximum resistivity change rate and stress sensitivity increasing by 82.05% and 313.59%, respectively. Moreover, the specimens exhibit the optimum piezoresistive response under a dynamic loading rate of 250 N/s. This study clarifies the variable-frequency sensing mechanism of self-sensing asphalt concrete, providing scientific guidance for dynamic speed measurement and weigh-in-motion (WIM) monitoring in smart pavements. Full article

Carnot batteries are promising sustainable energy storage technologies for renewable electricity utilization and grid peak shaving. For broader applicability and flexible configurations, an electric-heater-assisted reversible heat pump–organic Rankine cycle Carnot battery was investigated under two charging modes using six working fluids. A thermo-economic model was developed, comprising segmented ε-NTU heat exchangers, a pressure-ratio off-design, and levelized cost of storage. Latin hypercube sampling, Gaussian process regression, global sensitivity analysis, NSGA-II, and entropy-weight TOPSIS were used for variable identification, Pareto optimization, and decision-making. The rated pressure ratio dominates round-trip efficiency under the electric-heater-first mode, whereas the evaporation temperature of the organic Rankine cycle dominates both objectives under the heat-pump-first mode. The heat-pump-first mode achieves higher round-trip efficiency and a lower levelized cost of storage for six working fluids. The R1234yf-electric-heater-first configuration is usually suitable for applications prioritizing high-temperature heat supply. However, considering environmental friendliness and sustainability, R1233zd(E)-heat-pump-first is recommended for the system, achieving 15.709% and 0.36562 $/kWh, respectively. Admittedly, the potential transient-response advantage was not quantified by the present steady-state model, which can be further investigated in the future. Full article

Background/Objectives: Diabetes management technologies—including continuous glucose monitors (CGM), insulin pumps (CSII), advanced hybrid closed-loop (AHCL) systems, and mobile health applications—have transformed diabetes care, yet gender-specific differences in ad-herence, clinical outcomes, and patient-reported outcomes remain inadequately char-acterised. Methods: We conducted a systematic literature review following PRISMA 2020 guide-lines, searching SciSpace, Google Scholar, and PubMed databases. From 852 identified records, 500 underwent title/abstract screening after duplicate removal; 16 studies were ultimately included in the qualitative synthesis. Results: Included studies examined insu-lin pumps (n = 7), CGM (n = 6), AHCL systems (n = 4), remote monitoring programmes (n = 2), and mobile health applications (n = 1); sample sizes ranged from 72 to 22,697 participants. In predominantly paediatric evidence, females demonstrated higher insu-lin pump discontinuation rates (discontinuation groups: 75% vs. 46%, p = 0.001), driv-en by body image concerns and device visibility (data from a single small predomi-nantly paediatric cohort; group sex compositions, not absolute discontinuation rates), whereas in a single small adult cohort (n = 72), males showed poorer adherence to in-termittently scanned CGM (approximately four fewer scans/day, p = 0.011). Glycaemic outcomes were modestly but consistently different: males achieved slightly higher time-in-range while females exhibited lower glycaemic variability; menstrual cycle effects on glycaemic control were partially mitigated by AHCL systems. Females con-sistently reported greater diabetes-related distress and a more negative perception of glycaemic control despite similar or better objective metrics. Conclusions: In conclusion, sex-based and gender-related differences are apparent across technology type, adherence, gly-caemic control, and psychosocial outcomes—albeit from a limited evidence base re-quiring cautious interpretation; sex-sensitive prescription, education, and technology design are warranted. Note: most included studies reported biological sex (male/female) rather than self-identified gender; conclusions should be interpreted primarily as sex-based differences. Full article

Wire Electrical Discharge Machining (WEDM) is highly significant for machining Inconel, which is widely used across industries for its excellent strength and heat resistance. Traditional machining of Inconel poses several difficulties; therefore, WEDM becomes a better option. One of the major challenges in WEDM is achieving optimal Material Removal Rate (MRR) and Surface Roughness (SR) simultaneously. In the present investigation, WEDM operation was conducted on Inconel 625 using a molybdenum wire as the electrode material, with three essential process variables: Pulse ON Time (P_ON), Pulse OFF Time (P_OFF), and peak current (I_P). Multi-response optimization was performed using Response Surface Methodology (RSM) with the Face-centred Central Composite (FCC) design, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Particle Swarm Optimization (PSO). The optimal values obtained using RSM were 45.71 µs for P_ON, 8.02 µs for P_OFF, and 4.78 A for I_P, providing an SR of 3.997 µm and an MRR of 5.612 mm³/min. PSO focused more on the quality of the processed surface and gave a better SR of 3.098 µm, but the resulting MRR was 4.437 mm³/min using 20 µs for P_ON, 12 µs for P_OFF, and 3 A for I_P. Conversely, the NSGA-II optimized for maximal machining productivity and generated the highest MRR of 5.907 mm³/min with an SR of 3.867 µm using 49.42 µs for P_ON, 8 µs for P_OFF, and 5 A for I_P. Novelty lies in the use of statistics and metaheuristics to compare the performance of optimization methods in nonlinear parameter response analysis. Although RSM demonstrated high predictive accuracy, both the NSGA-II and PSO improved the search for the trade-off between MRR and SR. Overall, the best compromise between MRR and SR was achieved using the solution based on the NSGA-II results. The obtained results will help in developing advanced machining technologies aimed at precision processing of superalloys that contribute to SDG 9—Industry, Innovation and Infrastructure. Full article

The growing deterioration of water resources and the energy requirements of conventional wastewater treatment technologies have increased interest in systems that combine organic matter removal with bioelectrochemical conversion. This study evaluated a laboratory-scale dual-chamber microbial fuel cell (MFC) operated with real wastewater using Scenedesmus acutus (S. acutus) and a native microbial consortium as anodic biocatalysts at 25 and 30 °C. The system was assessed through continuous monitoring of voltage, pH, temperature, and CH₄, H₂, and CO₂ signals in the anodic headspace, together with physicochemical characterization and chemical oxygen demand (COD) removal. COD removal efficiencies of 33.7 and 30.3% were obtained for S. acutus at 25 and 30 °C, respectively, whereas the native microbial consortium achieved 29.8 and 43.4% removal under the same conditions. The consortium at 30 °C showed the most favorable combination of COD removal and electrical response, whereas S. acutus at 30 °C reached the highest maximum voltage and stored energy, although with greater signal variability. The CH₄, H₂, and CO₂ signals differed among conditions and were consistent with the possible participation of fermentative and methanogenic processes alongside electrogenic activity, although gas production rates and the contribution of individual pathways were not quantified. Overall, the results demonstrate the operational feasibility of the proposed MFC for coupling wastewater treatment with a measurable electrical response and support further evaluation of native microbial consortia as anodic biocatalysts. Full article

Dynamic Facial Expression Recognition (DFER) has recently attracted significant interest due to its vital role in enabling empathetic and human-compatible technologies. Developing models that remain robust under in-the-wild variability is a key motivation for DFER research and its practical applications. Improving models through multimodal learning, which leverages audio and video data for richer, complementary representations, is one promising direction. However, existing methods still rely heavily on modality-specific encoders and coarse-grained content-level alignment, which hinders their ability to capture fine-grained emotional semantics and dynamic cross-modal interactions. To address this, we adopt parameter-efficient fine-tuning (PEFT) to facilitate audio-visual interaction. This strategy offers key advantages: (1) freezing parameters preserves upstream pretrained knowledge, ensuring that the model focuses solely on learning modules for audio-visual interaction and modal fusion; (2) a Mamba Fusion Adapter (MFAdapter) is inserted at each encoder layer to perform causal, audio-conditioned fusion over a frame-aligned token sequence, enabling efficient multi-level cross-modal injection with linear complexity; and (3) a Frame-level Feature Arrangement (FFA) strategy is introduced as a deterministic index-based arrangement scheme that arranges audio tokens at the video-frame rate, providing a frame-indexed temporal prior that supports the causal scan in MFAdapter; FFA reduces, but does not eliminate, coarse segment-level mismatch and is not claimed as verified frame-level synchronization. Notably, our method achieves competitive performance on DFEW and MAFW while updating 2.7% (4.7 million) of the model parameters, with the best WAR of 58.70% on MAFW among all compared methods and 76.62%/65.25% (WAR/UAR) on DFEW under the official five-fold cross-validation protocols. Full article