Search Results (2,265)

Heavy metals are widespread environmental contaminants from natural and anthropogenic sources, posing risks to human health and ecosystems. In urban areas, levels are elevated due to industrial activity, traffic emissions, and building materials. Camden, New Jersey, a city with a history of industry and illegal dumping, faces increased risk due to aging sewer and stormwater systems. These systems frequently flood neighborhoods and parks, heightening residents’ exposure to heavy metals. Despite this, few studies have examined metal distribution in Camden, particularly during storm events. This study analyzes stormwater metal concentrations across residential and commercial areas to assess contamination levels, potential sources, and land use associations. Stormwater samples were collected from 33 flooded street locations after four storm events in summer 2023, along with samples from a flooded residential basement during three storms. All were analyzed for total lead, cadmium, and arsenic using inductively coupled plasma–mass spectrometry (ICP-MS, (Department of Chemistry and Biochemistry, Rowan University, Glassboro, NJ, USA)). Concentration data were visualized using geographic information system (GIS)-based mapping in relation to land use, socioeconomic, and public health factors. In Camden’s stormwater, lead levels (1–1164 µg L⁻¹) were notably higher than those of cadmium (0.1–3.3 µg L⁻¹) and arsenic (0.2–8.6 µg L⁻¹), which were relatively low. Concentrations varied citywide, with localized hot spots shaped by environmental and socio-economic factors. Principal component analysis indicates lead and cadmium likely originate from shared sources, mainly industries and illegal dumping. Notably, indoor stormwater samples showed higher heavy metal concentrations than outdoor street samples, indicating greater exposure risks in flooded homes. These findings highlight the spatial variability and complex sources of heavy metal contamination in stormwater, underscoring the need for targeted interventions in vulnerable communities. Full article

The conventional reactive cooling strategy, which relies on static thresholds, has become inadequate for managing dynamically changing heat loads, often resulting in energy inefficiency and increased risk of local hot spots. In this study, we develop a data center cooling optimization system that integrates distributed sensor arrays for predictive analysis. By deploying high-density temperature and humidity sensors both inside and outside server racks, a real-time, high-fidelity three-dimensional digital twin of the data center’s thermal environment is constructed. Time-series analysis combined with Long Short-Term Memory algorithms is employed to forecast temperature and humidity based on the extensive environmental data collected, achieving high predictive accuracy with a root mean square error of 0.25 and an R² value of 0.985. Building on these predictions, a proactive cooling control strategy is formulated to dynamically adjust fan speeds and the opening degree of chilled-water valves in computer room air conditioning units, changing the cooling approach from passive to preemptive prevention of overheating. Compared with conventional proportional–integral–differential control, the developed system significantly reduces overall energy consumption and maintains all equipment within safe operating temperatures. Specifically, the framework has reduced the energy consumption of the cooling system by 37.5%, lowered the overall power usage effectiveness of the data center by 12% (1.48 to 1.30), and suppressed the cumulative hotspot duration (temperature 27 °C) by nearly 96% (from 48 to 2 h). Full article

The aim of the presented research was to conduct a spatial analysis of the progress of energy transition in countries of the European Union. The energy transition is understood as replacing fossil fuels with renewable energy sources, reducing greenhouse gas emissions, and improving the energy efficiency of the EU economy. The analysis used statistical data obtained from Eurostat. These data were subjected to spatial analysis, enabling the identification of hot spots and clusters representing spatial variations in the degree of transformation progress. This allowed for the identification of countries with similar dynamics of change, as well as the differences between clusters. The weights of the explanatory variables and the energy transition progress index (ETPI) were also determined. The results obtained allowed the proposal of strategies and energy policies for individual clusters. The ETPI clearly shows that more than half of the EU countries have values of this index below their average. The maximum value of the index is 67% (for Denmark), and only two countries achieved an index of 50%. Therefore, even the leaders of the transition did not achieve their goals completely. There are still areas that need improvement, such as the decarbonization of transportation, industry, and construction. Countries that are lagging behind in their transition should implement measures to accelerate the achievement of decarbonization goals, both in the short term and strategically. Full article

Crime in Seattle, WA (USA), has long been concentrated in a few discrete geographic areas. This study examines the impact of a one-year place-based soft policing intervention to reduce crime and disorder in these two acutely affected areas: The Blade and Little Saigon. Employing Bayesian Structural Time Series (BSTS) to estimate the treatment effect of the intervention on several crimes and calls for service measures, we find mixed results with important implications. One area responded with significant reductions in crime and community-driven calls for service. The second treatment area did not reflect these effects, suggesting that key contextual variations may influence performance of Problem-Oriented Policing treatments. Additionally, treatment effects in the first location were observed to partially diminish over time, indicating a point of diminishing returns. This study suggests that a multi-partner soft policing approach to crime reduction is effective; however, treatment must be tailored to local context, and treatment areas should be expected to adjust, necessitating programed variability to maintain treatment efficacy. A “test-as-you-go” approach is critical to optimal performance. Implications for future place-based interventions are discussed. Full article

Heavy metal enrichment in agricultural soils can affect crop safety, ecosystem functioning, and long-term land productivity, yet farm-scale screening is often constrained by limited routine monitoring data. This study develops a GIS-based framework that combines field-scale spatial analysis with explainable machine learning to characterize and predict heavy metal enrichment on an intensively managed cereal farm in eastern Kazakhstan. Topsoil samples (0 to 20 cm) were collected from 34 fields across eight campaigns between 2020 and 2023, yielding 241 composite field–campaign observations for eight metals (Pb, Cu, Zn, Ni, Cr, Mo, Fe, and Mn) and routine soil properties (humus, pH in H₂O, and pH in KCl). Concentrations were generally low but spatially heterogeneous, with wide observed ranges for several elements (for example, Pb 0.06 to 2.20 mg kg⁻¹, Zn 0.38 to 7.00 mg kg⁻¹, and Mn 0.20 to 38.0 mg kg⁻¹). We synthesized multi-metal structure using an HMI defined as the unweighted mean of z-standardized metal concentrations, which supported field-level screening of persistent enrichment and emerging hot spots. We then trained Extreme Gradient Boosting models using only humus and pH predictors and evaluated performance with field-based spatial block cross-validation. Predictive skill was modest but nonzero for several targets, including HMI (mean R² = 0.20), indicating partial spatial transferability under conservative validation. SHAP analysis identified humus content and soil acidity as dominant contributors to HMI prediction. Overall, the workflow provides a transparent approach for field-scale screening of heavy metal enrichment and establishes a foundation for future integration with satellite-derived covariates for broader monitoring applications. Full article

The interaction between laser irradiation and energetic materials is critically influenced by microstructural void defects that determine local energy deposition and initiation sensitivity. In this work, a three-dimensional finite-difference time-domain (3D-FDTD) method was employed to investigate the modulation effects of void defects on optical field distributions and hot spot formation in RDX energetic crystals. The influences of void geometry, spatial position, and void number on the modulation of the incident laser beam were systematically analyzed. It reveals that void defects exhibit strong focusing and scattering behavior, leading to localized high-intensity regions both inside RDX bulk crystals and in void defects. For a single void defect, increasing either the width or depth can significantly enhance the peak electric field and thus the laser sensitivity of RDX crystals. When two voids are present, the number of high-intensity spots first increases and then decreases with increasing separation distance, and the strongest modulation effects are obtained at separations of 0.75λ–3λ. Furthermore, as the number of void defects increases, the modulation effect intensifies, promoting the formation of more hot spots. These findings provide quantitative insight into how void structures govern laser–matter interactions in energetic crystals, offering guidance for understanding and controlling laser initiation behavior. Full article

Adversarial patch attacks threaten the reliability of modern vision models. We present PatchMap, the first spatially exhaustive benchmark of patch placement, built by evaluating over $1.5\times {10}^8$ forward passes on ImageNet validation images. PatchMap reveals systematic “hot-spots” where small patches (as little as 2% of the image) induce confident misclassifications and large drops in model confidence. To demonstrate its utility, we propose a simple segmentation-guided placement heuristic that leverages off-the-shelf masks to identify vulnerable regions without any gradient queries. Across five architectures-including adversarially trained ResNet-50-our method boosts attack success rates by 8–13 percentage points compared to random or fixed placements. Full article

Traditional colloid SERS substrates are mostly based on metal nanoparticles (MNPs), which have complex and time-consuming fabrication processes, poor structural control, and are susceptible to oxidation. As a result, solid-state SERS substrates have emerged as an effective alternative. Here, we propose using two-step mild and hard anodization to fabricate ordered anodic aluminum oxide (AAO) substrates with high total pore circumference for SERS detection. Hybrid pulse anodization (HPA) enables the fabrication of AAO at room temperature using 40 V in the first step and 40, 110, and 120 V in the second step of anodization. The different voltages applied in the second step effectively control the pore diameter, thereby achieving various nanostructures. The enhancement mechanism primarily originates from the high total pore circumference of nanostructures, which generates abundant hot spots around the pore peripherals, thereby significantly amplifying the SERS signal. Sorbic acid is a common preservative widely used in food products and employed as a test substance on high regularity AAO substrates at concentrations of 1000 ppm to 10 ppb. The resulting SERS spectra exhibited distinct characteristic peaks at 1640–1645 cm⁻¹. The analytical enhancement factor is calculated as 1.02 × 10⁵ at the AAO substrate prepared by 110 V with the Si substrate as the reference. By appropriately tuning the process parameters, a limit of detection (LOD) as low as 10 ppb of sorbic acid was achieved. Full article

The 2025 International Technology Roadmap for Photovoltaics (ITRPV) projects that bifacial modules will dominate the photovoltaic (PV) market, reaching roughly 60–80% global share between 2024 and 2035, while monofacial PV modules will steadily decline. Current industry practice is to route the cable bundles along structural members such as main beams or torque tubes, thereby preventing rear-side shading but resulting in two key drawbacks: increased cable length and decreased system reliability due to cable proximity with rotating members and pinch points. Both effects contribute to higher system costs and reduced cable reliability. An alternative method involves suspending cable bundles directly behind the modules using hangers. While this approach mitigates excess length and risk of cable snags, it introduces the possibility of partial rear-side shading, which could possibly cause performance loss and hot-spot formation due to shade-induced electrical mismatch. Experimental evidence indicates that this risk is minimal, as albedo irradiance typically represents only 10–30% of front-side irradiance as reported in the literature and is largely diffuse, thereby limiting the likelihood of significant directional shading. This study evaluates the performance and reliability impacts of hanger-supported cable bundles under varying experimental conditions. Performance metrics assessed include maximum power output (Pmax), short-circuit current (Isc), open-circuit voltage (Voc), and fill factor (FF), while hot-spot risk was evaluated through measurements of module temperature uniformity using infrared imaging. Each cable (1X) was 6 AWG with a total outer diameter of approximately 9 mm. Experiments covered different cable bundle counts/sizes (2X, 6X, 16X), mounting configurations (fixed-tilt and single-axis tracker), and albedo conditions (snow-covered and snow-free ground). Measurements were conducted hourly on clear days between 8:00 and 16:00 from June to September 2025. The results consistently show that hanger-supported cable bundles have a negligible shading impact across all hours of the day and throughout the measurement period. This indicates that rear-side cable shading can be safely and practically disregarded in performance modeling and energy-yield assessments for the tested configurations, including fixed-tilt systems and single-axis trackers with or without torque tube shading and with various hanger sizes and cable-bundle counts. Therefore, hanging cables behind modules is a cost- and reliability-friendly, safe and recommended practice. Full article

In this study we employed nanopore whole genome sequencing to analyze the resistance genes, genomic islands and prophage DNA in two multidrug resistant E. rhusiopathiae strains, i.e., 670 and 147, isolated from domestic geese. MLST profiles and core-genome phylogeny were determined to assess strain relatedness. In strain 670 (serotype 8, ST 113), a novel 53 kb prophage φEr670 carrying the lnuB and lsaE resistance genes was identified. Regions highly homologous to the φEr670 prophage were detected in 36 of 586 (6.14%) publicly available E. rhusiopathiae genomes, as well as in some other Gram-positive bacteria, and usually contained resistance genes. E. rhusiopathiae strain 147 (serotype 5, ST 243) was found to contain a composite 98 kb genomic island (GI_Er147) carrying the ant(6)-Ia and spw genes, as well as gene encoding a putative lincosamide nucleotidyltransferase designated lnu(J) and a vat family gene encoding a putative streptogramin A O-acetyltransferase. The lnu(J) gene exhibited 83.6% homology to the lnu(D) gene, and lnu(J)-positive E. rhusiopathiae strains displayed intermediate susceptibility to lincomycin. Vat-positive strain 147 and vat-negative E. rhusiopathiae strains showed similar susceptibility to quinupristin/dalfopristin. The presence of the Tn916 transposon carrying the tetM gene was confirmed in the genomes of both E. rhusiopathiae strains; in strain 147, however, Tn916 was located within ICEEr1012. Based on analyses of additional E. rhusiopathiae genomes, the integration sites of Tn916, ICEEr1012, and GI_Er147 were identified as genomic “hot spots,” contributing to the genome plasticity of E. rhusiopathiae. Prophage φEr670 and GI_Er147 as well as the Tn916 transposon and ICEEr1012 are most likely responsible for the dissemination of resistance genes in E. rhusiopathiae. Prophages highly homologous to φEr670 act as carriers of resistance genes in various Gram-positive bacteria. However, the transferability of the identified genetic elements and the functional role of the lnu(J) gene require further investigation. This study provides new insights into the diversity of MGEs in E. rhusiopathiae and advances understanding of the genomic mechanisms driving antimicrobial resistance in Gram-positive bacteria. Full article

We examine how the Arctic Oscillation (AO) shapes winter sea-surface-temperature (SST) variability in the East/Japan Sea, with a focus on sub-seasonal SST memory (how long anomalies persist) and air–sea coupling (where SST and atmospheric anomalies co-vary). Using daily OISST v2.1 and ERA5 reanalysis for 1993–2022, we first analyze winter persistence of SST and key atmospheric drivers and identify East Korea Bay and the Subpolar Front as hotspots of long-lived SST anomalies. A rank-reduced multivariate maximum covariance analysis then extracts the leading coupled mode between SST and a set of atmospheric fields under positive and negative AO phases; in both phases the coupled mode is front-anchored, but its amplitude and spatial focus differ. Finally, to quantify the mixed-layer memory, we construct Ornstein–Uhlenbeck-like time-integrated responses of the atmospheric principal components. The effective integration timescales, determined by maximizing zero-lag correlations with the SST mode, cluster at approximately 2–3 weeks for wind-stress curl and near-surface variables and 4–7 weeks for sea-level pressure and meridional wind, with longer timescales during negative AO. The time-integrated atmospheric responses exhibit SST-like persistence, confirming the mixed layer’s role as a stochastic integrator. These AO-conditioned memory windows define practical lead times over which integrated atmospheric indices can act as predictors of winter marine heatwaves and cold-surge-impacted SST anomalies. Full article

Background: Electromagnetic compatibility (EMC) challenges in 2.5D/3D semiconductor packaging arise from the complex coupling between device, interposer, board, and cable domains, which are insufficiently captured by conventional board-level analysis. Method: This study proposes HiPAC-EMC, a packaging-aware EMC workflow that integrates the device, package, PCB, cable harness, line impedance stabilization network (LISN), and receiver elements into an isomorphic co-model. The model mirrors the entire measurement chain and links simulation to real conducted and radiated tests. Validation: The workflow was verified using CISPR-25-compliant conducted measurements, magnetic near-field mapping, and key-point radiated checks at 3 m and 10 m, ensuring model–measurement consistency within ±2–3 dB (1σ ≈ 3.1 dB). Results: Two quantitative indices—the mitigation efficiency (η) and the common-mode hot-spot headroom (CMH)—enabled the traceable evaluation of suppression effectiveness, achieving up to 22–25 dB reduction across dominant 300–800 MHz bands. Significance: The HiPAC-EMC workflow establishes a traceable, reproducible, and measurement-faithful design methodology, providing a practical tool to de-risk EMC during early design and reduce full-band chamber time for advanced semiconductor packaging. Full article

Harvest-disrupting rain events (HDREs) are prolonged cloudy–rainy spells during winter wheat maturity that impede harvesting and drying, induce pre-harvest sprouting and grain mould, and threaten food security in the Huang–Huai–Hai Plain (HHHP), China’s core winter wheat region. Using daily meteorological records (1960–2019), remote sensing-derived land-use data and topography, we develop a hazard–exposure–vulnerability framework to quantify HDRE risk and its drivers at 1 km resolution. Results show that HDRE risk has increased markedly over the past six decades, with the area of medium-to-high risk rising from 26.9% to 73.1%. The spatial pattern evolved from a “high-south–low-north” structure to a concentrated high-risk belt in the central–northern HHHP, and the risk centroid migrated from Fuyang (Anhui) to Heze (Shandong), with an overall displacement of 124.57 km toward the north–northwest. GeoDetector analysis reveals a shift from a “humidity–temperature dominated” mechanism to a “sunshine–humidity–precipitation co-driven” mechanism; sunshine duration remains the leading factor (q > 0.8), and its interaction with relative humidity shows strong nonlinear enhancement (q = 0.91). High-risk hot spots coincide with low-lying plains and river valleys with dense winter wheat planting, indicating the joint amplification of meteorological conditions and underlying surface features. The results can support regional decision-making for harvest-season early warning, risk zoning, and disaster risk reduction in the HHHP. Full article

This work describes an innovative three-dimensional model of a proton exchange membrane electrolyzer. For the first time, a multi-phase model has captured segregated channel flow together with multiphase flow in a porous medium, as well as heat transfer and phase change employing an Eulerian multiphase model. The novel electrolyzer design investigated employs a symmetrical, interdigitated flow field to facilitate even water distribution. In the current case, a hot spot is predicted with a temperature increase of 7 °C at a current density of 1.0 A/cm². The flow field plates are horizontally oriented, and it is shown that gravity plays an important role in the electrolyzer design and orientation. A parametric study shows, for the first time, the effect of operating a PEM electrolyzer at sub-ambient anode pressure to favorably adjust the concentration ratio between water vapor and oxygen in the anode compartment. This ratio is increased by a factor of 5.6 when the pressure is decreased from one bar to 500 mbar. Full article

Intensity–Frequency–Duration Curves (IDF curves) are a tool applied in hydraulic and hydrology engineering to design infrastructure for rainfall management. They express how precipitation, with a defined duration (D) and intensity (I), is frequent in a certain area. They are built from past recorded rainfall series, applying the extreme value statistics, and they are considered invariant in time. However, the current climate change projections are showing a detectable positive trend in temperatures, which, according to Clausius–Clapeyron, is expected to intensify extreme precipitation (higher temperatures bring more water vapour available for precipitation). According to the IPCC (Intergovernmental Panel on Climate Change) reports, rainfall events are projected to intensify their magnitude and frequency, becoming more extreme, especially across “climatic hot-spot” areas such as the Mediterranean basin. Therefore, a sensible modification of IDF curves is expected, posing some challenges for future hydraulic infrastructure design (i.e., sewage networks), which may experience damage and failure due to extreme intensification. In this paper, a methodology for reconstructing IDF curves by analysing the EURO-CORDEX climate model outputs is presented. The methodology consists of the analysis of climatic rainfall series (that cover a future period up to 2100) using GEV (Generalised Extreme Value) techniques. The future anomalies of rainfall height (H) and their return period (RP) have been evaluated and then compared to the currently adopted IDF curves. The study is applied in Lombardy (Italy), a region characterised by strong orographic precipitation gradients due to the influence of Alpine complex orography. The future anomalies of H evaluated in the study show an increase of 20–30 mm (2071–2100 ensemble median, RCP 8.5) in rainfall depth. Conversely, a significant reduction in the return period by 40–60% (i.e., the current 100-year event becomes a ≈40–60-year event by 2071–2100 under RCP 8.5) is reported, leading to an intensification of extreme events. The former have been considered to correct the currently adopted IDF curves, taking into account climate change drivers. A series of applications in the field of hydraulic infrastructure (a stormwater retention tank and a sewage pipe) have demonstrated how the influence of IDF curve modification may change their design. The latter have shown how future RP modification (i.e., reduction) of the design rainfall may lead to systematic under-design and increased flood risk if not addressed properly. Full article