Search Results (8,744)

Family violence is a social issue that impacts families and communities every day in Canada and around the world. As family violence rates continue to increase there is an urgent need for cross-sectoral collaboration to codesign social work and social service systems, in partnership with those experiencing family violence. This article will share learnings from a two-year community-based participatory research study that worked alongside survivors and witnesses of family violence, community partners from diverse social service agencies, and researchers, to understand experiences of family violence in racialized communities in Peel region, Ontario, Canada. An intersectional-trauma-informed approach guided the work that included establishing a community advisory board, hiring peer research assistants, Photovoice, and holding a knowledge exchange event (KEE) with survivors and witnesses of family violence, researchers, and community partners to rapidly generate ideas for intervention areas through a 25/10 crowdsourcing activity and codesign preliminary solutions through a mini hackathon. Key findings from the photovoice highlighted systemic failures and gaps experienced by those facing family violence. As we shifted into ideation, this preliminary focus on systems solidified and top ideas identified included barrier-free, culturally aware provision of services ranging from mental health supports, safe housing, financial independence, and accessing wrap-around services. Our work concluded with the collaborative development of preliminary solutions to these ideas and emphasized the need for cross-sectoral partnerships and lived experience engagement to change systems. Centering the voices of those who have experienced FV in system-level change and advocacy is necessary to ensure services and supports meet the needs of service users. Full article

Metal-free C(sp³)–S bond cleavage of thioethers was achieved using NCS as a critical additive. A wide range of arylmethyl thioethers were successfully transformed into aryl aldehydes with satisfactory yields in chloroform. Meanwhile, employing fluorobenzene as the solvent enables the selective formation of dithioacetals from arylmethyl thioethers, achieving moderate to good yields. Notably, dithioacetals were first prepared through a metal-free C(sp³)–S bond cleavage and subsequent thioacetalization process. Furthermore, these simple and efficient approaches also provide complementary strategies for accessing important aryl aldehydes and dithioacetals. Full article

This work presents a novel dual-polarized antenna array tailored for Internet of Things (IoT) applications, specifically designed to operate in the millimeter-wave (mm-wave) spectrum within the frequency range of 30–60 GHz. Leveraging printed ridge gap waveguide (PRGW) technology, the antenna ensures robust performance by eliminating parasitic radiation from the feed network, thus significantly enhancing the reliability and efficiency required by IoT communication systems, particularly for smart cities, autonomous vehicles, and high-speed sensor networks. The proposed antenna achieves superior radiation characteristics through a cross-shaped magneto-electric (ME) dipole backed by an artificial magnetic conductor (AMC) cavity and electromagnetic bandgap (EBG) structures. These features suppress surface waves, reduce edge diffraction, and minimize back-lobe emissions, enabling stable, high-quality IoT connectivity. The antenna demonstrates a wide impedance bandwidth of 24% centered at 30 GHz and exceptional isolation exceeding 40 dB, ensuring interference-free dual-polarized operation crucial for densely populated IoT environments. Fabrication and testing validate the design, consistently achieving a gain of approximately 13.88 dBi across the operational bandwidth. The antenna’s performance effectively addresses the critical requirements of emerging IoT systems, including ultra-high data throughput, reduced latency, and robust wireless connectivity, essential for real-time applications such as healthcare monitoring, vehicular communication, and smart infrastructure. Full article

The stability of Cotinus coggygria extract-loaded liposomes (non-treated and UV-irradiated) was determined after 60 days through an investigation of the impact of storage on liposomal physical and antioxidant properties. The liposome size varied in a narrow range for 60 days; PDI was 0.273–0.313 (non-treated) and 0.829–0.911 (UV-irradiated). The zeta potential ranged from −28.2 to −29.6 mV (non-treated) and from −21.5 to −22.0 mV (UV-irradiated). The obtained liposomes with the extract neutralized 81.9% of free DPPH radicals before UV irradiation and 80.9% after irradiation. In the ABTS assay, UV irradiation also significantly reduced the antioxidant capacity, from 12.02 to 10.55 µmol Trolox equivalent (TE)/mL. The ABTS and DPPH radical scavenging activity of the UV-irradiated liposomes significantly decreased after the 60-day storage (8.93 µmol TE/mL and 75.4%, respectively), whereas in the non-treated sample, the mentioned drop in antioxidant capacity was not noticed. Liposomal formulations of C. coggygria extract can exhibit significant potential for further development as a functional food or dermo-cosmetic ingredient. Full article

As global energy grows short and environmental governance pressure increases, the automotive industry, a major energy consumer and pollution emitter, must enhance vehicle aerodynamics to cut energy use and emissions. This study creates an open-domain and virtual wind tunnel dual-computational-domain setup. It optimizes mesh refinement and boundary conditions, and evaluates the k-ε, k-ω, and Detached Eddy Simulation (DES) turbulence models. These models predict vehicle aerodynamic resistance, lift, and wake flow structure. The k-ε model best predicts the steady-state drag coefficient (Cd) (error 0.0009). DES excels in transient conditions (Cd error −0.4%, lift coefficient Cl matching experiments). The k-ω model, with its near-wall flow capture ability, has the lowest lift prediction error (−2.7%). Moreover, open-domain simulations align more closely with real free-flow environments and experimental data than virtual wind tunnel simulations. Overall, the study clarifies the varying applicability of turbulence models in complex flows, and offers a basis for model selection and technical support for vehicle aerodynamic optimization. It is highly significant for reducing fuel consumption, boosting the range of new-energy vehicles, and promoting sustainable industry development. Full article

Hexagonal ZnO nanowires were grown using the PLD/VLS technique on a SAW sensor active area for hydrogen sensing. The influence of different carbon and nitrogen surface contaminant concentrations on sensor output was investigated for three active area cases: a few weeks’ exposure to free ambient air contamination, 3 h at 600 °C thermal desorption of carbon, and (room temperature) plasma-activated nitrogen and carbon contamination. Correlations between sensing performance and contamination element concentration were established. To understand the adsorption versus absorption mechanisms, similar studies were further performed on circular ZnO nanowires morphology, which have a different surface-area-to-volume ratio. Comparative results show that, while a 20% carbon surface contamination variation generates a variation of 3–5% in nanostructure hydrogen sorption, nitrogen surface contamination influence depends on nanostructure morphology. Thus, in our comparative studies, for the case of a nanowire hexagonal cross-section a 12% nitrogen surface contamination variation generates a 5–7% increase in hydrogen adsorption and also an increase of 6–8% in hydrogen absorption. Consequently, the catalytic effect of nitrogen could enlarge the linear response of nanowire-based (SAW) sensors over a wider hydrogen concentration range. Full article

Mussel foot protein is a bioadhesive protein with potential biomedical applications, but its limited solubility and poor biological stability hinder its widespread use. In this study, highly soluble mussel foot protein (HMFP) was successfully extracted using a stepwise selective enzymatic digestion method, with a molecular weight in the range of 11–17 kDa. Furthermore, a dual-functional polyethylene glycol (PEG) derivative of HMFP, designated HMFP-PEG, was synthesized. FTIR analysis confirmed the successful modification of HMFP with PEG, while TGA analysis and SEM observations demonstrated that PEG modification significantly enhanced the stability of the protein. Both HMFP and HMFP-PEG effectively scavenged free radicals, enhanced antioxidant enzyme activity, and reduced MDA levels. Additionally, they activated the PI3K/Akt and Nrf2/HO-1 signaling pathways, inhibiting H₂O₂-induced cell apoptosis. Notably, HMFP-PEG exhibited superior antioxidant and cell-protective effects compared to HMFP, suggesting that PEG modification improves the functional stability of the protein. This study provides theoretical support for the potential application of HMFP in the biomedical and tissue engineering fields. Full article

Facial semantic segmentation, as a critical technology in high-level visual understanding, plays an important role in applications such as facial editing, augmented reality, and identity recognition. However, due to the complexity of facial structures, ambiguous boundaries, and inconsistent scales of facial components, traditional methods still suffer from significant limitations in detail preservation and contextual modeling. To address these challenges, this paper proposes a facial parsing network based on the Deeplabv3+ framework, named FP-Deeplab, which aims to improve segmentation performance and generalization capability through structurally enhanced modules. Specifically, two key modules are designed: (1) the Context-Channel Refine Feature Enhancement (CCR-FE) module, which integrates multi-scale contextual strip convolutions and Cross-Axis Attention and introduces a channel attention mechanism to strengthen the modeling of long-range spatial dependencies and enhances the perception and representation of boundary regions; (2) the Self-Modulation Attention Feature Integration with Regularization (SimFA) module, which combines local detail modeling and a parameter-free channel attention modulation mechanism to achieve fine-grained reconstruction and enhancement of semantic features, effectively mitigating boundary blur and information loss during the upsampling stage. The experimental results on two public facial segmentation datasets, CelebAMask-HQ and HELEN, demonstrate that FP-Deeplab improves the baseline model by 3.8% in Mean IoU and 2.3% in the overall F1-score on the HELEN dataset, and it achieves a Mean F1-score of 84.8% on the CelebAMask-HQ dataset. Furthermore, the proposed method shows superior accuracy and robustness in multiple key component categories, especially in long-tailed regions, validating its effectiveness. Full article

Obstructive sleep apnea (OSA) is characterized by frequent episodes of sleep-disordered breathing (SDB), which are often accompanied by leg movement (LM) events, especially periodic limb movements during sleep (PLMS). Traditional single-event detection methods often overlook the dynamic interactions between SDB and LM, failing to capture their temporal overlap and differences in duration. To address this, we propose Attention-enhanced CRF with U-Net (AttenCRF-U), a novel joint detection framework that integrates multi-head self-attention (MHSA) within an encoder–decoder architecture to model long-range dependencies between overlapping events and employs multi-scale convolutional encoding to extract discriminative features across different temporal scales. The model further incorporates a conditional random field (CRF) to refine event boundaries and enhance temporal continuity. Evaluated on clinical PSG recordings from 125 OSA patients, the model with CRF improved the average F1 score from 0.782 to 0.788 and reduced temporal alignment errors compared with CRF-free baselines. The joint detection strategy distinguished respiratory-related leg movements (RRLMs) from PLMS, boosting the PLMS detection F1 score from 0.756 to 0.778 and the SDB detection F1 score from 0.709 to 0.728. By integrating MHSA into a CRF-augmented U-Net framework and enabling joint detection of multiple event types, this study presents a novel approach to modeling temporal dependencies and event co-occurrence patterns in sleep disorder diagnosis. Full article

Fe₃O₄/H₂O nanofluid attracts many researchers’ attention due to its considerable potential for practical applications. This work is focused on the study of heat transfer efficiency in Fe₃O₄/H₂O nanofluids with nanoparticles (NPs) of mean diameter d_NPs in the nanosized range (13–50 nm) at volume fractions up to 2%. The Rayleigh–Bénard problem of free convection between plane-parallel plates corresponding to Rayleigh numbers 10³–10⁷ is numerically solved. It was shown that the addition of up to 2% of NPs with a diameter of 13 nm can increase the Prandtl number by up to 60% compared to pure water. A map of flow regimes is constructed, indicating the emerging convective patterns. It is demonstrated that as the volume fraction of NPs increases, the Prandtl number grows and the transition to more chaotic patterns with Rayleigh number slows down. It is observed that at a Rayleigh number of 10⁴, the heat flux through the nanofluid layer decreases by up to 25% relative to pure water. Conversely, at Ra ≈ 10⁵, the heat flux through the nanofluid layer increases by up to 18% when using a 2% volume fraction of 13 nm diameter NPs. Full article

Quantitative in vitro to in vivo extrapolation (QIVIVE) utilizes in vitro data to predict in vivo toxicity. However, there may be differences between reported nominal concentrations and the biologically effective free concentrations in media or cells. This study evaluated the performance of four in vitro mass balance models for predicting free media or cellular concentrations. Comparing model predictions to experimentally measured values for a wide range of chemicals and test systems, we found that predictions of media concentrations were more accurate than those for cells, and that the Armitage model had slightly better performance overall. Through sensitivity analyses, we found that chemical property-related parameters were most influential for media predictions, while cell-related parameters were also important for cellular predictions. Assessing the impact of these models on QIVIVE accuracy for a small dataset of 15 chemicals with both in vitro and regulatory in vivo points-of-departure, we found that incorporating in vitro and in vivo bioavailability resulted in at best modest improvements to in vitro–in vivo concordance. Based on these results, we conclude that a reasonable first-line approach for incorporating in vitro bioavailability into QIVIVE would be to use the Armitage model to predict media concentrations, while prioritizing accurate chemical property data as input parameters. Full article

Breast cancer is a prevalent malignancy worldwide. Human MutT homolog 1 (MTH1) is over expressed in breast tumors, and cancer cells rely on MTH1 for survival. This protein ensures the integrity of the nucleotide pool by preventing the integration of oxidized 2′-deoxynucleoside triphosphates (dNTPs) during DNA replication. Therefore, inhibiting MTH1 pharmacologically emerged as a valid target in treating breast cancer. In the present study, we screened biologically active phytochemicals from the NPACT database to discover potential inhibitors of MTH1. Molecular docking analysis was employed to identify the binding conformation and the interaction pattern. The top five compounds were selected for detailed analysis based on their superior binding affinity and interactions with crucial residues (Asn33, Gly36, Tyr7, Phe72, Trp117, Lys23, and Phe27, Glu100) of MTH1. Additionally, the ADMET profile of selected compounds highlighted the high intestinal absorption, low toxicity, and acceptable metabolic stability, exhibiting their potential as drug candidates. Furthermore, in silico validation of selected compounds was performed through molecular dynamics (MD) simulation, which revealed that the resultant complexes are appreciably stable. Compounds revealed RMSD values ranging between 1.0 and 1.5 Å, indicating strong and stable binding conformations. PCA analysis revealed restricted conformational sampling, highlighting stabilization, particularly with ZINC14727630, ZINC14819291, ZINC14781695, and ZINC95099417. MM-GBSA confirmed the stability of the ligand–protein complexes, with ZINC14819291, ZINC14727630, and ZINC95099417 demonstrating the most stable interactions with MTH1, with total binding free energies of −32.46, −45.06, and −33.44 kcal/mol, respectively. Our results support that these natural compounds could act as potential anti-MTH1 for ameliorating the breast cancer. However, experimental validation is required to validate the efficacy of these molecules and robustness of this anticancer approach. Full article

As an essential chemical raw material and a cost-effective energy product, fluctuations in propane price has garnered significant attention in the energy market. This paper processes the original time series using a coarse-grained method and employs symbolic representation combined with the sliding window technique to represent fluctuation modes as nodes within a network. The weight and direction of the edges among the nodes are determined by the number and direction of the conversions among the modes, thereby mapping the original sequence of the propane price into the propane price oriented weighted network (PPOWN) by the symbolic patterns, which is an asymmetric network that has evolved from the symmetric network based on symmetry theory. The results indicate that the core fluctuation state of the PPOWN is concentrated in the first 0.96% of the nodes, exhibiting scale-free network characteristics and dynamic asymmetry. Nodes with greater strength are more closely interconnected, but not all early-appearing nodes possess great strength. The PPOWN demonstrates a short-range correlation ($\overline{L}=8.5405$) and a highly linear growth trend in the cumulative time interval of the new nodes. Additionally, the nodes of the PPOWN display low betweenness, clustering coefficient, and strength, which significantly differ from the random and chaotic networks. The presence of these lower-strength nodes often signifies that the market is undergoing a transformation or transition period. By identifying and analyzing these nodes, subsequent propane price fluctuations can be predicted more effectively, enhancing market responsiveness. Full article

Background: Keratinocyte carcinomas, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), presents a growing concern. Electrochemotherapy (ECT), an emerging treatment modality, combines chemotherapy and electroporation to enhance drug delivery into cells. However, reviews evaluating ECT in keratinocyte carcinomas are lacking. Objectives: This study reviews the efficacy and toxicity of ECT in the treatment and palliation of keratinocyte carcinomas. Methods: A systematic search was conducted across PubMed, Cochrane, Embase, and Scopus databases. Patient, tumor, and treatment characteristics, tumor response, long-term disease outcomes, and toxicity data were extracted. Quality of studies was assessed using validated tools. Primary endpoints included tumor response; secondary endpoints included long-term disease outcomes and toxicity. Results: Twenty-one studies were included. Complete response (CR) rates ranged from 50 to 100% and from 10 to 100% for BCC and SCC, respectively. OS rates ranged from 95 (14 months) to 100 (1 year) % and from 64 (1 year) to 85.1 (8.6 months) % for BCC and SCC, respectively. One-year local disease-free survival (LDFS) rates were 89% and 87% for BCC and SCC, respectively. For BCC, local progression-free survival (LPFS) rates were 96% (1 year), 90% (2 year), and 70% (5 year). For SCC, 1-year LPFS rates were 80% on a per-patient basis and 49% on a per-lesion basis. Conclusions: ECT is effective and tolerable in the treatment and palliation of keratinocyte carcinomas. Future studies should focus on improving reporting quality, optimizing treatment protocols, and investigating long-term outcomes. Full article

Accurate monitoring of physical activity (PA) and sedentary behaviour (SB) is crucial for tailoring interventions aimed at improving movement behaviour. This study evaluated the validity of the pocket-worn RISE device for measuring movement behaviour in community-dwelling patients with stroke. Criterion validity was assessed in a laboratory setting using video recordings. Construct validity was assessed in a free-living setting using the thigh-affixed ActivPAL. In the laboratory setting (25 participants, 66 ± 11.8 years), the RISE device showed good criterion validity for SB and PA. In the free-living setting (19 participants, 73 ± 10.2 years), the RISE device showed good construct validity for SB and PA, though further improvements could enhance the accuracy of individual-level measurements of moderate to vigorous physical activity (MVPA) and prolonged sedentary bouts. The mean absolute percentage error and mean percentage error were below the predefined 20% threshold for SB and PA. Intraclass correlation coefficients (ICCs) for SB and PA showed good reliability, but ICC ranges for prolonged sedentary bouts and MVPA were too broad to draw firm conclusions. These findings indicate the RISE device is well-suited for measuring SB and PA in free-living conditions. With real-time feedback, app compatibility, and pocket-wear convenience, the RISE device shows potential for behavioural interventions targeting movement behaviour in stroke and other chronic conditions. Full article