Search Results (663)

Solar energy continues to grow rapidly worldwide. Yet in the context of a ‘just transition’, recent research has found stark disparities in adoption across communities and sociodemographic groups. In Canada, where all levels of government have shown support for solar adoption, there is a clear lack of equity-centered research. For example, we can find no research that assesses the kinds of people that have invested in or developed solar PV. To begin to address this gap, we present the results from a pilot study set in the Halifax Regional Municipality (HRM), Nova Scotia—a municipality that has developed a novel financing support program called Solar City. This exploratory work focuses on analyzing the levels of participation, equity, and barriers experienced among homeowners who have adopted residential rooftop solar—via both Solar City and other non-local programs. After utilizing aerial imagery to locate a sample of solar installations in the HRM (n = 1315), we shared surveys that asked residents for their sociodemographic information as well as the barriers faced in the adoption of solar. We then compared the sociodemographic information to municipal-level characteristics provided by Statistics Canada. We center our analyses around variables such as age, education, gender, and income. Our paper closes with a discussion and conclusion which we hope will inform future research and practice around equitable pathways towards a just solar energy transition—in Halifax and beyond. Full article

Accurate prediction of regional sea level anomaly (SLA) is critical for coastal hazard early warning, navigation safety, and infrastructure protection in economically active marginal seas such as the East China Sea (ECS), yet complex multiscale air–sea dynamics still make SLA forecasting challenging. This study proposes a Local Spatial Attention Transformer Network (LSATrans-Net) for short-term regional SLA prediction in the ECS, which incorporates a Local Spatial Attention mechanism designed for regional ocean processes and employs a first-order difference preprocessing strategy to reduce error accumulation induced by data non-stationarity. The LSATrans-Net outperforms ConvLSTM, BiLSTM, and CNN-Transformer in 7-day prediction experiments, with an RMSE of 0.017 m and a PCC of 0.984, with particularly strong forecasting skill in the ECS-Kuroshio and eddy-active regions. LSATrans-Net provides an efficient and physically interpretable framework for high-precision short-term SLA forecasting in dynamically complex marine regions, and offers reliable technical support for coastal disaster prevention and operational ocean forecasting systems. Full article

Sustainable management of cultural heritage in mountainous regions requires effective strategies to mitigate natural hazards such as landslides. Landslide susceptibility mapping (LSM) provides a critical tool to support these conservation efforts. This study presents a hybrid framework that integrates probabilistic slope stability modeling with ensemble learning for LSM in the UNESCO World Heritage sites of Shirakawa-gō and Gokayama, Japan. The framework uses probabilities of failure from Bishop’s simplified method combined with Monte Carlo simulations to guide non-landslide sample selection. An enhanced tri-parametric optimization was applied to refine the slope unit segmentation process. SHAP analysis revealed that the hybrid framework emphasizes physically meaningful features such as rainfall. The proposed method results in AUC gains of 0.072 for XGBoost, 0.066 CatBoost for, and 0.063 for LightGBM compared to their buffer-based counterparts. Future landslide susceptibility was mapped based on the 2035 precipitation projections from ARIMA time-series modeling. By enhancing accuracy, interpretability, and geotechnical consistency, the proposed approach delivers a robust tool for sustainable risk management. The study further evaluates the exposure of Gasshō-style houses and other historic buildings to varying levels of landslide susceptibility, offering actionable insights for local planning and heritage conservation. Full article

Parvovirus B19 (B19V) is a human ssDNA virus with ample pathogenic potential. It is characterized by a selective tropism for erythroid progenitor cells (EPC), exerting a cytotoxic effect with blockade of erythropoiesis. In our work, we investigated both viral and cellular expression profile in the course of infection of EPCs cultures via mRNA high throughput sequencing technology (HTS) and a dedicated bioinformatic pipeline, reconstructing both the viral and cellular transcriptome and their variations. A productive infection was confirmed as restricted to EPCs expressing mature differentiation markers and the specific receptor for virus VP1u region. mRNA HTS reconstructed the viral transcriptome in terms of localization and abundance of the different mRNA species, detailing the differential expression profile of B19V among early or late times in the course of infection. Analysis of cellular transcriptome indicated that variation was mainly driven by the cellular differentiation process, with the virus impacting to a lesser level, but still clearly separating infected vs. non-infected profiles. At early times post-infection, variations were typical of cellular sensing of viral infection and aimed at the induction of an antiviral state. At later times in the course of infection, the cellular population showed induction of an inflammatory response, related to TNF and IL-10, and a transition to adaptive immunity with evidence of upregulation of genes involved in MHC-II presentation. This dual-transcriptome analysis on infected EPCs population can lay the ground for future research aimed at a better definition of the pathogenetic mechanisms of B19V. Full article

Current passive microwave satellites like SMAP still face limitations in observational frequency and responsiveness in regions with frequent cloud cover, dense vegetation, or complex terrain, making it difficult to achieve continuous global monitoring with high spatio-temporal resolution. To enhance global high-frequency monitoring capabilities, this study utilizes global reflectivity data provided by the Tianmu-1 (TM-1) constellation since 2023, combined with multiple auxiliary variables, including NDVI, VWC, precipitation, and elevation, to develop a 9 km resolution soil moisture retrieval model. Several spatial clustering and temporal partitioning strategies are incorporated for systematic evaluation. Additionally, since the publicly available TM-1 L1 reflectivity data does not provide separable polarization channels, this study uses DDM/specular point reflectivity as the primary observable quantity for modeling and mitigates non-soil factor interference by introducing multi-source priors such as NDVI, VWC, precipitation, terrain, and roughness. Unlike SMAP’s “single orbit daily fixed local time” observation mode, TM-1, leveraging multi-constellation and multi-orbit reflection geometry, offers more balanced temporal sampling and availability in cloudy, rainy, and mid-to-high latitude regions. This enables temporal gap filling and rapid event response (such as moisture transitions within hours after precipitation events) during periods of SMAP’s quality masking or intermittent data loss. Results indicate that the model combining LC-cluster with seasonal partitioning delivers the best performance at the cluster level, achieving a correlation coefficient (R) of 0.8155 and an unbiased RMSE (ubRMSE) of 0.0689 cm³/cm³, with a particularly strong performance in barren and shrub ecosystems. Comparisons with SMAP and ISMN datasets show that TM-1 is consistent with mainstream products in trend tracking and systematic error control, providing valuable support for global and high-latitude studies of dynamic hydrothermal processes due to its more balanced mid- and high-latitude orbital coverage. Full article

Rational allocation and coordinated operation of water resources in arid inland river basins are crucial for sustaining irrigated agriculture, maintaining ecological baseflow and ensuring reservoir safety. To address this need, this study develops and evaluates joint-operation schemes for the Jingou River-Hongshan Reservoir irrigation system in Xinjiang, northwestern China, to improve coordination among irrigation water supply, ecological baseflow maintenance and reservoir safety. A monthly reservoir-canal-irrigation operation model is formulated with irrigation demands, ecological flow constraints and key engineering limits. Using this model, operating schemes are generated to explore trade-offs among three objectives: shortages, reliability and non-beneficial reservoir releases. The non-dominated schemes obtained from multi-objective optimization are then ranked using an entropy-weighted TOPSIS framework, from which representative solutions are selected for further interpretation. The results indicate that the top-ranked schemes deliver comparable and relatively well-balanced performance across the objectives. Under the preferred compromise scheme, annual irrigation shortages amount to about 39% of total demand, the mean satisfaction level of irrigation and ecological requirements reaches roughly 57%, and the combined index of spill losses and end-of-year storage deviation remains low. Schemes that push shortage reduction or reliability enhancement to extremes tend to increase spill losses, compromise storage security or both, thereby degrading overall performance. The proposed optimization-ranking framework offers a transparent basis for identifying robust operating strategies that reflect local management priorities and is transferable to other reservoir-supported irrigation systems in arid regions. Full article

To address the issue of decreased localization accuracy and robustness in existing visual SLAM systems caused by imprecise identification of dynamic regions in complex dynamic scenes—leading to dynamic interference or reduction in valid static feature points, this paper proposes a dynamic visual SLAM method integrating instance-level motion classification, temporally adaptive super-pixel segmentation, and optical flow propagation. The system first employs an instance-level motion classifier combining residual flow estimation and a YOLOv8-seg instance segmentation model to distinguish moving objects. Then, temporally adaptive super-pixel segmentation algorithm SLIC (TA-SLIC) is applied to achieve fine-grained dynamic region partitioning. Subsequently, a proposed dynamic region missed-detection correction mechanism based on optical flow propagation (OFP) is used to refine the missed-detection mask, enabling accurate identification and capture of motion regions containing non-rigid local object movements, undefined moving objects, and low-dynamic objects. Finally, dynamic feature points are removed, and valid static features are utilized for pose estimation. The localization accuracy of the visual SLAM system is validated using two widely adopted datasets, TUM and BONN. Experimental results demonstrate that the proposed method effectively suppresses interference from dynamic objects (particularly non-rigid local motions) and significantly enhances both localization accuracy and system robustness in dynamic environments. Full article

This study investigates the aerodynamic and aeroacoustics behavior of automotive cooling modules in both conventional internal combustion engine (ICE) vehicles and electric vehicles (EVs), with a particular focus on installation effects. Numerical simulations based on the Lattice Boltzmann Method (LBM) are conducted to analyze noise generation mechanisms and flow characteristics across four configurations. The study highlights the challenges of adapting classical cooling module components to EV setups, emphasizing the influence of heat exchanger (HE) placement and duct geometry on noise levels and flow dynamics. The results show that the presence of the HE smooths the upstream flow, improves rotor loading distribution and disrupts long, coherent vortical structures, thereby reducing tonal noise. However, the additional resistance introduced by the HE leads to increased rotor loading and enhanced leakage flow through the shroud-rotor gap. Despite these effects, the overall sound pressure level (OASPL) remains largely unchanged, maintaining a similar magnitude and dipolar directivity pattern as the configuration without the HE. In EV modules, the inclusion of ducts introduces significant flow disturbances and localized pressure fluctuations, leading to regions of high flow rate and rotor loading. These non-uniform flow conditions excite duct modes, resulting in troughs and humps in the acoustic spectrum and potentially causing resonance at the blade-passing frequency, which increases the amplitude in the lower frequency range. Analysis of the loading force components reveals that rotor loading is primarily driven by thrust forces, while duct loading is dominated by lateral forces. Across all configurations, fluctuations at the leading and trailing edges of the rotor are observed, originating from the blade tip and extending to approximately mid-span. These fluctuations are more pronounced in the EV module, identifying it as the dominant source of pressure disturbances. The numerical results are validated against experimental data obtained in the anechoic chamber at the University of Sherbrooke and show good agreement. The relative trends are accurately predicted at lower frequencies, with slight over-prediction, and closely match the experimental data at mid-frequencies. Full article

Ensuring the integrity of medical images is essential to securing clinical workflows, telemedicine platforms, and healthcare IoT environments. Existing watermarking and reversible data-hiding approaches often modify pixel intensities, reducing diagnostic fidelity, introducing embedding constraints, or causing instability under compression and format conversion. This work proposes a distortion-free, non-embedding authentication framework that leverages the inherent stability of the most significant bit (MSB) patterns in the Non-Region of Interest (NROI) to construct a secure and tamper-sensitive reference for the diagnostic Region of Interest (ROI). The ROI is partitioned into fixed blocks, each producing a 256-bit SHA-256 signature. Instead of embedding this signature, each hash bit is mapped to an NROI pixel whose MSB matches the corresponding bit value, and only the encrypted coordinates of these pixels are stored externally in a secure database. During verification, hashes are recomputed and compared bit-by-bit with the MSB sequence extracted from the referenced NROI coordinates, enabling precise block-level tamper localization without modifying the image. Extensive experiments conducted on MRI (OASIS), X-ray (ChestX-ray14), and CT (CT-ORG) datasets demonstrate the following: (i) perfect zero-distortion fidelity; (ii) stable and deterministic MSB-class mapping with abundant coordinate diversity; (iii) 100% detection of intentional ROI tampering with no false positives across the six clinically relevant manipulation types; and (iv) robustness to common benign Non-ROI operations. The results show that the proposed scheme offers a practical, secure, and computationally lightweight solution for medical image integrity verification in PACS systems, cloud-based archives, and healthcare IoT applications, while avoiding the limitations of embedding-based methods. Full article

Airborne magnetic particles (AMPs) are associated with potentially toxic elements, and their size, mineralogy, and concentration can significantly impact both the environment and human health. However, their spatial analysis is often limited by small datasets, non-normality, and pronounced local variability. In this work, two sites with distinct demographic and geographic characteristics, the city of Mar del Plata (Argentina) and the Aburrá Valley region (Colombia), were analyzed using the fuzzy Magnetic Pollution Index (IMC) as an indicator of the concentration of AMPs. Moreover, an original methodological framework that explicitly incorporates measurement uncertainty through fuzzy numbers, combined with an approach modeling fuzzy semivariances via α-cuts, performs spatial prediction via ordinary kriging. This study produces maps that simultaneously reflect the magnitude of IMC and its associated uncertainty. Unlike classical geostatistics, the fuzzy-based model captures the inherent imprecision of magnetic measurements and reveals spatial patterns where uncertainty becomes informative about the type and origin of pollution. In particular, this approach demonstrates that areas with higher IMC levels are associated with high anthropic activity (near industrial zones, main avenues, slow traffic). In contrast, lower values were found in residential areas. Overall, the fuzzy-driven approach provides an additional layer of information not accessible through traditional methods, improving spatial interpretation and supporting the identification of priority areas for environmental monitoring. Full article

Recently, the environmental impact of halocarbons has become increasingly concerning, particularly due to the growing influence of non-regulated halocarbons on stratospheric ozone depletion and their adverse health effects in the troposphere. Previous model studies have highlighted the importance of halocarbon emissions from the YRD. However, only several reports have discussed the long-term pollution characteristics and health risks of halocarbons in the YRD based on observational data. The continuous observation of halocarbons was conducted in the central part of the YRD (Shanxi site) from 2018 to 2023. The result showed that rise in halocarbon levels was primarily driven by alkyl halides, including dichloromethane (1.194 ppb to 1.831 ppb), chloromethane (0.205 ppb to 1.121 ppb), 1,2-dichloroethane (0.399 ppb to 0.772 ppb), and chloroform (0.082 ppb to 0.300 ppb). The PMF and CBPF analysis revealed that pharmaceutical manufacturing (37.0% to 60.2%), chemical raw material manufacturing (8.0% to 19.9%), solvent use in machinery manufacturing (12.4% to 24.7%), solvent use in electronic industry, and background sources were the main sources of halocarbons at the Shanxi site. Among them, the contributions of chemical raw material manufacturing, as well as of solvent use in machinery manufacturing and electronic industry, are increasing. These aspects are all dominated by local emissions. Furthermore, the carcinogenic risks of chloroform and 1,2-dichloroethane, which rank first in this regard, are increasing. Also, attention should be paid to solvent use in the electronic industry and the background. The probabilities of these activities coming with health risks that exceed the acceptable levels are 94.8% and 94.9%. This study enriches the regional observation data in the YRD region, offering valuable insights into halocarbon pollution control measures for policy development. Full article

Understanding the processes that shape parasite community structure across spatial scales is essential for linking ecological theory with host–parasite dynamics. Using a metacommunity framework, we examined the metacommunity of helminth parasites infecting the freshwater fish Pseudoxiphophorus bimaculatus across 11 sites along the La Antigua River basin (Veracruz, Mexico). We combined β-diversity partitioning, local and species contributions to diversity, elements of metacommunity structure (EMS), and variance partitioning to identify the mechanisms underlying spatial variation in parasite composition. Helminth metacommunity was dominated by a few widespread taxa, with balanced variation in species abundances—indicative of turnover—emerging as the main driver of β-diversity at both host and site levels. Both rare and common species contributed disproportionately to regional diversity. EMS analyses revealed coherent, non-random community structures that varied from nested to quasi-Gleasonian and quasi-Clementsian types among sites and guilds, suggesting that species respond individually to shared environmental gradients. Variance partitioning indicated that environmental filtering, particularly through habitat structure, explained most of the variation in community composition, exceeding the effects of water quality and host size. Overall, our results demonstrate that turnover, species uniqueness, and environmental filtering interact to shape helminth parasite metacommunities in tropical freshwater systems, highlighting the integrative role of environmental heterogeneity and dispersal limitation in parasite community assembly. Full article

Background: Covering the defects around the calcaneus is still a largely debatable subject. In the classical view, the defects at the level of the foot can be treated only by a free flap. In a modern approach, it has been observed that for small or moderate foot defects, a local flap can be used. Methodology: In this case series, we have retrospectively selected the patients who were admitted to the orthopedic department for a calcaneal fracture and who presented soft-tissue complications during the treatment. The patients have been selected from the past five years if they have undergone reconstructive surgery with a local or regional flap. Results: By applying the inclusion and exclusion criteria, we found that out of 79 patients who have been admitted to the orthopedic department, only two patients met the criteria. Two flaps have been used to treat the defects that developed at the level of the calcaneus after traumatic injury of the foot. The reverse-flow sural flap, as a tunneled flap, had a good evolution, without vascular suffering of the flap. On the other hand, for defects at the medial level of the calcaneus, we have used the dorsalis pedis flap. The healing was fast, and the patient presented no complications at the level of the donor site. Conclusions: Both flaps presented a good evolution. We try to emphasize through this article that soft tissue defects around the non-weight-bearing area of the heel can also be treated through a non-microsurgical option. These two options can help the ortho-plastic team to manage difficult cases by avoiding a free flap or a split-thickness skin graft. Full article

Heavy metal contamination in agricultural soils poses serious threats to food safety, ecosystem integrity, and public health. This study investigates the concentrations, ecological risks, and human health impacts of nine heavy metals Cr, Mn, Co, Ni, Cu, Zn, Pb, As, and V in homestead agricultural soils collected from two depths, surface (0–20 cm) and subsurface (21–50 cm), across industrial and non-industrial regions of Bangladesh, using inductively coupled plasma mass spectrometry (ICP-MS). Results revealed that surface soils from industrial areas exhibited the highest metal concentrations in order of Mn > Zn > Cr > Pb > V > Ni > Cu > As > Co. However, maximum As levels were detected in non-industrial areas, suggesting combined influences of local geology, intensive pesticide application, and prolonged irrigation with As-contaminated groundwater. Elevated concentrations in surface soils indicate recent contamination with limited downward migration. Multivariate statistical analyses indicated that industrial and urban activities are the major sources of contamination, whereas Mn remains primarily geogenic, controlled by natural soil forming processes. Contamination factor (CF) and pollution load index (PLI) analyses identified Pb and As as the principal pollutants, with hotspots in Nairadi, Majhipara (Savar), Gazipur sadar, and Chorkhai (Mymensingh). Ecological risk (ER) assessment highlighted As and Pb as the dominant environmental stressors, though overall risk remained low. Human health risk analysis showed that ingestion is the primary exposure pathway, with children being more susceptible than adults. Although the hazard index (HI) values were within the acceptable safety limits, the estimated carcinogenic risks for As and Cr exceeded the USEPA thresholds, indicating potential long term health concerns. Therefore, the cumulative carcinogenic risk (CCR) results demonstrate that As is the primary driver of lifetime carcinogenic risk in homestead soils, followed by Cr, while contributions from other metals are minimal. These findings emphasize the urgent need for continuous monitoring, improved industrial waste management, and targeted mitigation strategies to ensure safe food production, a cleaner environment, and better public health. Full article

Spectroscopic techniques offer significant potential for investigating ligand–protein interactions, particularly for assessing conformational modifications and binding affinity. In the present study, a complementary approach combining near-UV circular dichroism (CD) and second-derivative fluorescence spectroscopy was applied to evaluate how two representative nonsteroidal anti-inflammatory drugs—phenylbutazone (PHB, a marker of Sudlow’s site I) and ketoprofen (KP, a marker of Sudlow’s site II)—influence the tertiary structure of human serum albumin in its native form (HSA) and after glycation by glucose (gHSA_GLC), fructose (gHSA_FRC), and glucose–fructose syrup (gHSA_syrup). The results demonstrate that glycation substantially modifies the tertiary structure of HSA and decreases its drug-binding capacity at Sudlow’s sites I and II, with the most pronounced conformational changes observed for gHSA_FRC, confirming fructose as the most reactive glycation agent. PHB induced distinct conformational rearrangements, including a characteristic increase in ellipticity near ~290 nm, indicating perturbations in the chiral microenvironment surrounding Trp214 within Sudlow’s site I. By contrast, KP induced weaker, site-specific structural changes, primarily within Phe-rich hydrophobic domains of site II. Glycation consistently increased the polarity and solvent exposure of aromatic residue microenvironments—particularly within Tyr-rich regions—while the local environment of Trp214 remained comparatively stable. These findings suggest that PHB and KP modulate the conformational flexibility of glycated HSA predominantly by reorganizing Tyr-rich regions rather than directly perturbing Trp214. Overall, the study shows that glycation heterogeneity significantly influences protein–drug interactions, with important implications for altered pharmacokinetics in diabetes and metabolic disorders. The combined application of near-UV CD and second-derivative fluorescence spectroscopy offers a sensitive and complementary strategy for distinguishing structural differences between non-glycated and glycated HSA and for characterizing drug–albumin interactions at the tertiary structural level of the macromolecule. Full article