Search Results (14,308)

The discharge of metal-complex dyes from textile industries poses significant environmental challenges due to their chemical stability and resistance to conventional biological treatment. This study examined the degradation of Acid Black 194 (AB–194), a 1:2 chromium-complex azo dye, using Co²⁺-activated peroxymonosulfate (PMS). A central composite design based on response surface methodology was used to evaluate the effects of Co²⁺ (5.93–20.07 µM), PMS (1.67–7.33 mM), and dye (13.79–56.21 mg L⁻¹) concentrations on decolorization and mineralization. The polynomial models demonstrated strong predictive accuracy (R² > 0.9896), identifying Co²⁺ and dye concentrations as the most influential factors. Under optimal conditions (18.0 µM Co²⁺, 6.5 mM PMS, 20.0 mg L⁻¹ dye), 99.19% decolorization was achieved at 30 min and 41.43% TOC removal at 240 min. Degradation kinetics were described by a mechanistic model incorporating 15 elementary reactions that comprise the Co²⁺/Co³⁺ redox cycle, radical generation, and dye oxidation, yielding a global R² of 0.9617. Estimated rate constants for dye oxidation (k₁₄ = 3.52 × 10⁹ M^–1 s^–1 for and k₁₅ = 2.00 × 10¹⁰ M^–1 s^–1 ) were consistent with values reported for aromatic compounds in sulfate radical systems. Radical contribution analysis confirmed sulfate radicals as the principal oxidizing species, accounting for 96.75% of the overall process. Full article

NanoArduSiPM represents a paradigm shift in the ArduSiPM (Architected Detection Unit for Silicon Photomultipliers) roadmap, evolving from a standalone instrument into a high-density modular building block (36 mm × 42 mm × 3 mm, 7 g). This revision does not merely pursue miniaturization; it re-engineers the signal-processing chain to maintain high performance within a scaled-down footprint, enabling the transition from single-unit detection to scalable, distributed multi-detector systems. NanoArduSiPM is based on a three-layer architecture comprising an external scintillator and Silicon Photomultiplier (SiPM) detection module, a dedicated high-speed discrete analog front-end, and a System-on-Chip (SoC) for embedded acquisition and processing. The physical implementation adopts high-integrity PCB routing and rigorous isolation techniques designed to suppress digital–analog coupling, a critical requirement in such a compact form factor. This deterministic layout strategy provides the architectural foundation for time-tagging capabilities, currently under quantitative characterization, by addressing the fundamental sources of signal interference at the hardware level. Beyond hardware integration, NanoArduSiPM introduces the capability for extended firmware functionality, including event tagging via external inputs and the implementation of coincidence and veto logic. This framework supports the acquisition of multiple correlated histograms and allows multiple units to be interconnected on a shared SPI bus. By shifting from standalone operation to a coordinated, hierarchical architecture, NanoArduSiPM enables distributed detection schemes where event selection and correlation are handled natively within the system, reducing the dependency on external data acquisition electronics. The compact modular architecture, together with the high-performance discrete analog front-end and embedded data handling, makes NanoArduSiPM suitable for applications where low mass and low power consumption are critical, targeting applications such as space-based payloads, laboratory instrumentation, remote sensing, and large-scale distributed multi-channel detection systems. While no radiation-tolerance qualification of the complete system has been performed in this work, the microcontroller family used in the design is also available in radiation-tolerant variants, which may support future implementations targeting more demanding radiation environments. Full article

Low-cost IoT-based air quality sensors enable dense monitoring networks but suffer from significant measurement noise and instability particularly in dynamic environments. Conventional fixed-window smoothing reduces noise but introduces a trade-off between signal stability and temporal responsiveness, often attenuating short-term pollution events. This paper proposes an adaptive filtering algorithm that dynamically adjusts the averaging window size based on short-term signal variability. The method relies on real-time variance estimation to balance noise suppression and sensitivity to rapid changes without increasing computational complexity. The approach is implemented within an IoT-based monitoring framework and evaluated using parallel measurements with a certified reference device. Comparative analysis against a certified reference device demonstrates strong agreement, with Pearson correlation coefficients reaching r = 0.88 for PM_2.5 and r = 0.86 for PM₁₀, and low error levels (RMSE ≈ 2.1–2.2 µg/m³). The proposed adaptive filtering approach preserves temporal dynamics while improving signal stability and robustness compared to raw and fixed-window filtering. In addition, this method improves event detection stability, achieving low false alarm rates and near real-time response (latency < 1 sampling interval), supporting RPA-based workflow triggering. The results show that the proposed adaptive filtering provides an efficient and lightweight solution for real-time signal processing on resource-constrained devices, making it suitable for large-scale deployment in environmental monitoring systems. Full article

This study evaluated the performance of thermochromic windows as dynamic envelopes for smart greenhouses, focusing on the light environment and cooling load under peak summer conditions. Four covering materials, glass, Low-E glass, polycarbonate, and thermochromic windows, were compared using EnergyPlus (v9.2.0) simulation for an 8-span greenhouse with a floor area of 1008 m² in Gwangju, South Korea, on a representative summer day of 21 July. Thermochromic properties were modeled with temperature-dependent SHGC variations from 0.521 at 25 °C to 0.425 at 85 °C. Results showed that thermochromic windows reduced noon illuminance by 75% compared to conventional glass, from 26,482 lux to 6628 lux, while maintaining adequate light levels above the compensation point for tomato and paprika cultivation. Simultaneously, peak cooling load decreased by 13.1%, from 537,929 W to 467,477 W, outperforming Low-E glass at 9.2% and polycarbonate at 7.0%. At peak hours of 1:00 p.m., when the glass surface temperature reached 60.5 °C, the thermochromic glazing reduced transmitted solar radiation by 37.8% per unit area compared to conventional glass. This study demonstrates that thermochromic windows effectively balance photosynthetic light provision and cooling energy reduction in smart greenhouses, offering a viable design solution for controlled environment agriculture under extreme summer conditions. Full article

For optimal growth and development, black soldier fly larvae require a balanced diet. This study focused on how nutrients other than protein, specifically fat, starch, fibre, and ash, affect larval growth, body composition, and the quality of the leftover material called frass. To isolate the effects of these nutrients, five types of organic byproducts: fast food (FF) waste, solid pig manure (PS), mushroom stems (MS), slaughter waste (SW) and poultry meal (PM), were used to create six different diets, all with similar protein levels (about 22% DM). The results showed that diets rich in fat and starch, such as those based on FF waste, produced the heaviest larvae (155.9 mg), which also had high fat (30.31% DM) and protein contents (52.74% DM). In contrast, diets based on PM, which were low in fat and starch but high in fibre and ash, resulted in lower larval weight, which had lower fat content but variable protein content depending on other diet ingredients. Similar dietary protein levels yielded different larval protein contents, indicating that other nutrients may have influenced how protein was stored. However, other components of the diet, especially fat and ash, were consistently reflected in both the larvae and the frass. Overall, the study shows that nutrients other than protein play important roles in larval development and should be considered when designing black soldier fly diets. Full article

Conventional memory machines often suffer from magnetic interference between high-coercive-force (HCF) and low-coercive-force (LCF) permanent magnets, which unintentionally alters the magnetization state and limits overload capability. To address this challenge, this paper proposes a novel axial parallel memory machine (DCB-AXMM) featuring a DC-bias-controlled variable-flux capability. Instead of a conventional structure, the proposed machine employs an axially segmented topology to spatially isolate the excitation sources, effectively shielding the LCF PMs from HCF PM interference and armature reaction. Furthermore, integrated windings are utilized to perform both armature excitation and pulse magnetization, thereby enhancing the overall space utilization. The flux-regulating mechanism is theoretically elucidated using a piecewise linear hysteresis model. To maximize electromagnetic performance, a two-step optimization framework based on a genetic algorithm (GA) is implemented. Comprehensive non-linear finite element analysis (FEA) is conducted to validate the proposed design. Quantitative results demonstrate that the DCB-AXMM achieves a wide flux regulation range, characterized by a 21.8% average torque reduction from 2.2 Nm at full magnetization to 1.72 Nm at zero magnetization, while maintaining a robust 1.5-times overload capability. These measurable outcomes confirm the topology’s effectiveness and reliability for high-performance variable-flux applications. Full article

This study evaluates the environmental performance of 34 single-engine light utility helicopters across five operational phases: ground idle departure, ground idle arrival, takeoff, approach, and landing-takeoff (LTO). A hybrid multi-criteria decision-making (MCDM) framework integrating interval type-2 fuzzy sets with the Analytic Hierarchy Process (AHP), VIKOR, and TOPSIS was applied to ensure robust and reliable assessment. Six criteria: shaft horsepower (SHP), fuel flow, hydrocarbon (HC), carbon monoxide (CO), particulate matter (PM), and nitrogen oxides (NOx) were considered to capture both engine performance and environmental impact, with relative importance determined through AHP. VIKOR generated a compromise ranking, while TOPSIS validated the results. The analysis revealed that the HUGHES 500 (DDA250-C18, A34), HUGHES 501 (DDA250-C20B, A29), and BELL 206B-1 (DDA250-C20, A32) engines achieved the best environmental performance due to low fuel consumption and reduced emissions across NOx, PM, HC, and CO. In contrast, engines such as K-1200 (T53 17A-1, A1) and BELL UH-1H (T53 L13, A2) performed the poorest, with high fuel flow and elevated emissions. Sensitivity analysis showed minimal changes in rankings when the NOx weight was varied, confirming the robustness of the framework. These results highlight that emissions and fuel efficiency are more critical than engine power in determining environmental sustainability. Full article

Amid rapid industrialization and urbanization, air pollution has emerged as a major public health concern linked to non-communicable diseases (NCDs), with older adults particularly vulnerable. Beyond its direct physiological effects, social participation could buffer environmental health risks by enhancing resilience, encouraging healthy behaviors, and reducing stress. Using data from the 2020 China Longitudinal Aging Social Survey (CLASS; 11,398 respondents aged 60 and above), linked with county-level air pollution indicators (PM_2.5, O₃, SO₂, NO₂, and CO), this study applied multilevel models to examine the association between air pollution and NCD prevalence among older adults, as well as the mediating role of social participation. Results show that higher NO₂ concentrations significantly increased NCD risk (OR = 1.27, 95% CI: 0.87–1.73), whereas higher SO₂ concentrations (mean = 9.96 µg/m³, ranged from 5.69 to 19.99 µg/m³) were unexpectedly associated with reduced risk (OR = 0.68, 95% CI: 0.58–0.8). This finding should be interpreted with caution and warrants further investigation; notably, the observed SO₂ levels were well below the World Health Organization air quality guideline values. CO exhibited an inverted U-shaped relationship with disease prevalence. Social participation functioned as a protective factor, lowering NCD risk (OR = 0.75, 95% CI: 0.66–0.84) and may partly explain the association between NO₂ exposure and NCDs. These findings highlight the complex and sometimes counterintuitive pathways through which air pollution and social participation jointly shape NCDs in later life. Policy interventions should integrate air quality improvements with initiatives that promote social participation to enhance resilience, reduce disparities, and foster healthy aging in polluted urban environments. For example, establishing well-ventilated indoor community centers equipped with air filtration systems in high-pollution areas could provide safer spaces for older adults to participate in social activities while minimizing exposure to harmful pollutants. Such interventions could simultaneously reduce environmental health risks and strengthen social participation, thereby offering a practical pathway for promoting healthy aging. Full article

Despite substantial improvement in air quality in China, winter PM_2.5 concentrations particularly in January show limited decline, especially in the central region. This study used statistical analysis and WRF-CMAQ to examine how typical meteorological years affect transport and pollution processes in Henan. The mean effect difference ranged from −22 to 33%. In January 2020, weak winds and a low planetary boundary layer increased PM_2.5 by 3–33%, whereas in January 2023, stronger northerly winds and a higher boundary layer reduced PM_2.5 by 12–22%. These differences altered transport pathways, leading to a shift in dominant source regions from Beijing–Tianjin–Hebei and Shandong to Anhui and Hubei, with primary PM_2.5 showing high sensitivity to transport pathways, whereas secondary PM_2.5 remained relatively stable due to its dependence on regional chemical formation. Typical meteorological years in Henan exhibit two distinct pollution regimes: The local accumulation regime (2020) showed faster growth (20–30 μg m⁻³ d⁻¹), a higher peak (107 μg m⁻³), longer persistence, and slower dissipation and was dominated by near-range transport. In contrast, the regional transport regime (2023) exhibited slower growth (<20 μg m⁻³ d⁻¹), a lower peak (99 μg m⁻³), shorter persistence, and more rapid dissipation and was sustained by multi-regional input from Anhui, Shandong, and Hubei. In both episodes, primary PM_2.5 dominated during the growth and peak stages, whereas secondary PM_2.5 played a more prominent role during dissipation. Full article

The use of entomopathogenic fungi as biological control agents has gained increasing relevance as a sustainable alternative to chemical insecticides in tropical agroecosystems. In this study, a naturally occurring isolate of Metarhizium brunneum infecting adults of Metamasius hemipterus was recovered from banana plantations in the Amazonas region, Peru, and evaluated for its potential as a biological control agent. Multilocus phylogenetic analysis based on tef1α, β-tubulin, rpb1, and rpb2 sequences confirmed its taxonomic identity within the M. brunneum clade. Physiological characterization revealed variability in growth and thermal response among isolates, while conidial production differed significantly depending on the substrate. Notably, isolate PM9 exhibited the highest conidial yield on rice substrate. Pathogenicity assays demonstrated high virulence against adult weevils, with an LC₅₀ of 2.91 × 10⁵ conidia·mL⁻¹ and mortality exceeding 90% at the highest concentration tested. These findings indicate that isolate PM9 combines desirable physiological and pathogenic traits for biological control. The natural occurrence of this entomopathogen in banana systems suggests ecological adaptation to local conditions and supports its potential incorporation into integrated pest management strategies, although further field-based evaluation is required. Full article

This preliminary study explored circadian variations in meridian-associated skin temperature using infrared thermal imaging (IRTI). Four healthy adults receive a two-hour IRTI measurement alternately over a 24 h period, with thermal images acquired every 15 min. Within the 24 h monitoring period, two-hour intervals corresponding to the predicted peak activity of each meridian according to the ziwu-liuzhu theory were selected for detailed analysis. Specifically, jing-well acupoints exhibited an early increase in temperature at the onset of their predicted active intervals, whereas terminal acupoints showed a decline in temperature, suggesting the initiation and completion of meridian activity. A progressive increase followed by a decrease was observed along both the spleen meridian (9:00–11:00 a.m.) and heart meridian (11:00–1:00 p.m.), suggesting a temporal trend that may be consistent with traditional Chinese medicine (TCM) predictions. These preliminary results indicate that IRTI may provide a non-invasive approach for visualizing circadian features of meridian function, offering potential to bridge TCM concepts with modern biomedical approaches. Full article

This study applies and evaluates established machine learning (ML) models for predicting monthly PM2.5 concentrations across the Greater Klang Valley (GKV), Malaysia using one year of data collected from 36 mobile monitoring stations between July 2022 and June 2023. Daily PM2.5 temperature (T), relative humidity (RH), and station location (L) were aggregated to form monthly datasets. Exploratory analysis showed substantial temporal variability, with elevated PM2.5 levels during the southwest monsoon and reduced concentrations during the northeast monsoon due to enhanced rainfall washout. Tree-based ML algorithms: decision tree (DT), random forest (RF), and Extreme Gradient Boosting (XGBoost) were developed following data cleaning, transformation, partitioning, and hyperparameter optimization via grid search. Model performance was evaluated using R², RMSE, MAE and NAE. Across all months, XGBoost consistently outperformed DT and RF, achieving the highest R² values (0.214–0.559) and generally lower error metrics. Model performance varied seasonally, with the highest accuracy observed in March 2023 (R² = 0.559) and February 2023 (R² = 0.552), whereas November 2022 showed the weakest predictive capability. Feature-importance analysis revealed that temperature exerted the strongest influence during the southwest monsoon, while station location dominated predictions in several months, reflecting spatial heterogeneity likely associated with land-use and emission patterns. RH was most influential in September 2022, when low humidity coincided with higher PM2.5 levels. Comparison of predicted and observed values showed strong alignment except during extreme pollution events, where the model tended to underperform. Overall, the findings demonstrate that XGBoost provides a robust modeling framework for monthly PM2.5 prediction in the GKV and highlights the importance of incorporating meteorological and spatial drivers to improve localized air-quality assessments. Full article

Background: Seasonal haze from biomass burning in northern Thailand frequently elevates PM2.5 above national and WHO standards, while evidence on short-term lung function changes in exposed populations remains limited. Method: This longitudinal study evaluated changes in lung function in 130 adults before and after the haze season from December 2023 to May 2024 in San Pa Thong District, Chiang Mai Province. Spirometry was conducted following ATS/ERS standards. Demographic and health-risk data were gathered using validated Thai questionnaires addressing diabetes, cardiovascular, and chronic obstructive pulmonary disease risk categories. Results: A significant reduction in the FEV₁/FVC ratio was observed, from 85.3% to 82.4% (p = 0.001) after the haze period, while the proportion of participants with FEV₁/FVC < 70% increased from 2.3% to 6.9% (p = 0.031). No statistically significant independent predictors were identified in multivariable analysis. Greater reductions were observed in older adults, low-income individuals, and those at moderate to high diabetes risk. Conclusions: These findings suggest modest changes in spirometry parameters during the seasonal haze period. The observed reduction in FEV₁/FVC should be interpreted cautiously and may reflect early functional variation rather than confirmed airway obstruction. Although the magnitude of change was relatively small, the findings highlight the potential value of ongoing respiratory monitoring and early detection strategies in haze-affected regions. Full article

The precise spatiotemporal monitoring of dopamine is critical for understanding neurotransmission and neurodegenerative pathologies. While traditional electrochemical methods offer excellent temporal resolution, they lack the spatial resolution required to map network-wide dynamic events. To address this, we adapted a wide-field plasmonic electrochemical microscopy (PEM) platform to spatially image localized electrochemical reactions. Specifically, we leveraged the anodic electropolymerization of dopamine into a surface-confined polydopamine nanofilm to enable label-free, pixel-level optical quantification. Bulk solution testing demonstrated highly uniform sensor sensitivity, yielding an estimated single-pixel limit of detection of 14 pM. Furthermore, utilizing a custom injection system, we successfully imaged the real-time localized delivery of micromolar dopamine concentrations and demonstrated qualitative responsiveness of the integrated optical signal to delivered dopamine as a proof-of-concept for the platform. The platform functions as a spatially resolved mass integrator while simultaneously decoupling this chemical signal from transient hydrodynamic mechanical deformations caused by dopamine injection flow. Ultimately, this platform establishes the fundamental methodology required for future high-throughput spatial monitoring of complex neurotransmitter release dynamics across cellular networks. Full article

Uncontrolled scrap tire fires represent high-intensity episodic emission events that pose severe toxicological threats to urban environments. This study employs atmospheric dispersion modelling to quantify the impact of a tire stockpile fire on a distal educational receptor, evaluating two distinct dynamic stages of the event: an initial high-intensity open flame scenario (E1, 4 h) and a prolonged smouldering/suppression scenario (E2, 6 h), induced by firefighting interventions. Results reveal extreme pollutant loading at the receptor site during E1, with PM₁₀ and SO₂ concentrations peaking at 23,766 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$ and 7821 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$ respectively, indicating an immediate risk of acute respiratory distress. The organic fraction was dominated by volatile organic compounds (VOCs) (8691 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$) and a ∑16 PAHs flux of 313.9 ${\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{{\mathrm{m}}^3}}$. Toxicological assessment identified Benzo[a]pyrene (BaP) as the primary driver of health hazards, contributing approximately 70% to the carcinogenic risk profile. A critical disparity was observed between Mutagenic Equivalency (MEQ) of 18.32 and Toxic Equivalency (TEQ) of 15.37, suggesting that standard monitoring significantly underestimates the biological threat to sensitive paediatric populations. These findings demonstrate that acute, oxygen-limited tire combustion creates a concentrated toxic slug of high-molecular-weight PAHs. The study underscores the necessity of integrating mutagenicity-based models into emergency response protocols to accurately safeguard vulnerable communities against the long-term toxicological legacy of elastomer thermolysis. Full article