Search Results (13,879)

Sindbis virus (SINV) is a mosquito-borne alphavirus capable of causing neurological and immunological symptoms in humans, yet its effects on neural/immune systems remain insufficiently characterized. This study aimed to examine SINV replication, UV-C light inactivation, apoptosis induction, and immune gene modulation in human SH-SY5Y neuroblastoma cells. Following viral adaptation and infectious dose determination, SINV replication and inactivation were assessed using RT-qPCR and dsRNA immunofluorescence. Apoptotic markers (caspase-3, Bax, Bcl-2) were analyzed by immunofluorescence and immune genes expression kinetics (TLR3/7, RIGI, MDA5, IL-1β, IL-6, TNFα, IL-10, IFNβ and β-catenin) were measured at defined time points post-infection by RT-qPCR. SH-SY5Y cells supported productive SINV infection, with viral RNA detectable as early as 3 hpi and marked cytopathic effects by 24 hpi. A custom-built UV-C chamber achieved complete viral inactivation following 3 × 30 s exposures. We observed SINV time-course replication and UV-C inactivation with conspicuous morphological alterations in SH-SY5Y cells. Furthermore, SINV triggered caspase-dependent apoptosis and robust transcriptional upregulation of innate immune genes, peaking between 12–16 hpi and declining by 30 hpi. These findings elucidate the temporal dynamics of SINV replication, cell death mechanisms, and immune activation in a neuronal context, contributing to a better understanding of SINV neuropathogenesis. Full article

Visible near-infrared (VNIR) spectroscopy offers a cost-effective solution to quantify the spatiotemporal dynamics of soil organic carbon (SOC), especially in the context of rapid advances in spectra-based local modeling approaches using large-scale soil spectral libraries. And yet, direct temporal transferability of VNIR spectroscopic modeling (applying historical models to new spectral data) and its capability to monitor temporal changes in SOC remain underexplored. To address this gap, this study uses the LUCAS Soil dataset (2009 and 2015) from France to evaluate the effectiveness of localized spectral models in detecting SOC changes. Two local learning algorithms, memory-based learning (MBL) and GLOBAL-LOCAL algorithms, were adapted to integrate spectral and soil property similarities during local training set selection, while also incorporating LUCAS 2009 soil measurements (clay, silt, sand, CEC) as covariates. These adapted local learning algorithms were then compared against global partial least squares regression (PLSR). The results demonstrated that localized models substantially outperformed global PLSR, with MBL achieving the highest accuracy for croplands, grasslands, and woodlands (R² = 0.72–0.79, RMSE = 4.73–20.92 g/kg). Incorporating soil properties during the local learning procedure reduced spectral heterogeneity, leading to improved SOC prediction accuracy. This improvement was particularly pronounced after excluding organic soils from grasslands and woodlands, as evidenced by 13.3–21.1% decreases in the RMSE. Critically, for SOC monitoring, spectrally predicted SOC successfully identified over 70% of samples experiencing significant SOC changes (>10% loss or gain), effectively capturing the spatial patterns of SOC changes. This study demonstrated the potential of localized spectral modeling as a cost-effective tool for monitoring SOC dynamics, enabling efficient and large-scale assessments critical for sustainable soil management. Full article

Introduction: Exposure to violence is an adverse experience associated with the perpetration of violent future behaviors such as child-to-parent violence. Objective: The objectives were to analyze the psychometric properties of the Violence Exposure Scale (VES) in a sample of Ecuadorian adolescents as well as its measurement invariance by sex and age; analyze the differences in exposure to violence across four settings (home, school, street, and TV), in two time frames (last year and childhood), according to sex and age; and analyze the relationship between exposure to violence in the four settings and in both time frames with child-to-parent violence. Methods: A cross-sectional study was conducted using a probabilistic sample of 2150 Ecuadorian adolescents (55% female), aged 12 to 18 years (M = 14.53; SD = 1.55). Participants completed the adapted version of the VES and the Child-to-Parent Violence Questionnaire (CPV-Q). Confirmatory factor analyses, reliability testing, convergent and discriminant validity analyses, and measurement invariance assessments were performed. Results: The VES showed excellent model fit in both versions, VES¹ (last year) and VES² (before age 10), with strong goodness-of-fit indices (VES¹: CFI = 0.988; RMSEA = 0.055; VES²: CFI = 0.994; RMSEA = 0.044). Reliability was good (α_o and ω_o ≤ 0.80; G.6 and CR ≤ 0.70). Effect sizes ranged from 0.11 to 0.31 for violence by children toward parents and reached up to 0.83 among the different forms of victimization. Conclusions: The adaptation of the VES in Ecuadorian adolescents showed validity and reliability in assessing exposure to violence. Girls were more at risk at home, while boys were more exposed at school and in the community. Full article

Mikania micrantha, commonly known as mile-a-minute weed, is listed among the world’s top 10 worst weeds. Although native to humid regions of South America, it has recently been found to colonize arid habitats as well. Despite pronounced seasonal hydroclimatic variations in South China and increasing drought due to global climate change, the mechanisms underlying M. micrantha’s drought tolerance remain poorly understood. In this study, we compared the photosynthetic responses of M. micrantha leaves and stems between the dry (June) and wet (December) seasons through field experiments. We measured changes in phenotype, photosynthetic characteristics, and the content of antioxidant and osmotic adjustment substances, using the co-occurring native vine Paederia scandens as a control. The results revealed that during the dry season, M. micrantha leaves exhibited wilting, along with significant reductions in relative water content (RWC), chlorophyll (Chl), soluble sugar (SS), and soluble protein (SP). In contrast, the stems of M. micrantha maintained relatively stable phenotypes and chlorophyll levels compared to those of P. scandens. Notably, M. micrantha stems exhibited significant increases in vessel wall thickness, vessel density, total phenol content, and the activities of peroxidase (POD) and ascorbate peroxidase (APX). Furthermore, compared to P. scandens, M. micrantha stems displayed a greater increase in cortex proportion, flavonoid content, and soluble protein content. Expression analysis of bZIP transcription factors further revealed drought-responsive upregulation of specific genes (bZIP60, ZIP42-1), suggesting their potential involvement in drought response. These results indicate that although the leaves of M. micrantha are susceptible to prolonged drought, the stems exhibit considerable resilience, which may be attributed to a combination of traits including structural modifications in stem anatomy, enhanced antioxidant capacity, and osmotic adjustment. These insights suggest that stem-specific adaptations are key to its drought tolerance, providing a theoretical foundation for understanding the habitat distribution of M. micrantha and informing effective management strategies. Full article

As a critical technological foundation for electric vehicles, power battery state estimation primarily involves estimating the State of Charge (SOC), the State of Health (SOH) and the Remaining Useful Life (RUL). This paper systematically categorizes battery state estimation methods into three distinct generations, tracing the evolutionary progression from single-state to multi-state cooperative estimation approaches. First-generation methods based on equivalent circuit models offer straightforward implementation but accumulate SOC-SOH estimation errors during battery aging, as they fail to account for the evolution of microscopic parameters such as solid electrolyte interphase film growth, lithium inventory loss, and electrode degradation. Second-generation data-driven approaches, which leverage big data and deep learning, can effectively model highly nonlinear relationships between measurements and battery states. However, they often suffer from poor physical interpretability and generalizability due to the “black-box” nature of deep learning. The emerging third-generation technology establishes transmission mechanisms from microscopic electrode interface parameters via electrochemical impedance spectroscopy to macroscopic SOC, SOH, and RUL states, forming a bidirectional closed-loop system integrating estimation, prediction, and optimization that demonstrates potential to enhance both full-operating-condition adaptability and estimation accuracy. This progress supports the development of high-reliability, long-lifetime electric vehicles. Full article

US food regulatory agencies have adopted a preference for researchers and testing labs to use ‘acid adapted challenge cultures’ when performing inoculated validation studies of food processes that involve acidic treatments to accustom the cultures to acidic pH so that they will not be easily affected during processing. We evaluated acid adaptation in regard to the processing of South African style air-dried beef, notably biltong and droëwors, using a mixture of five serovars of Salmonella as well as a unique serovar isolated from dried beef (Salmonella Typhimurium 1,4,[5],12:i:-). Acid adaptation was obtained by growing cultures in tryptic soy (TS) broth containing 1% glucose. Non adapted cultures were obtained by growth in TS broth without glucose or in TS broth with 1% glucose but buffered with 0.2 M phosphate buffer. Processes included biltong (dried solid beef) and droëwors (ground, sausage-style). Each trial was performed twice and triplicate samples were examined at each sampling point (i.e., n = 6). Statistical analysis was applied using analysis of variance (ANOVA) or one-way repeated measures (RM-ANOVA) and the Holm–Sidak test for pairwise multiple comparisons to determine significant differences (p < 0.05). We observed that in all processes examined (eight trials), treatments using acid adapted cultures were more sensitive to the biltong and droëwors processes, giving greater reductions (5.3-log reduction) than when non-adapted cultures were used (3.8-log reduction). Acid adaptation leads to stressed conditions in Salmonella resulting in sensitization to the multiple hurdles found in biltong and droëwors processing (acid/vinegar, salt, desiccation). Based on our data, the use of non adapted Salmonella cultures to achieve desired challenge culture process lethality could result in more robust processing conditions and a greater level of safety in these products as intended by US regulatory guidance. Full article

Background: Mobility assessment is a crucial aspect of rehabilitation for individuals with lower limb amputation, as it directly influences their independence and quality of life. The objective of this study was to translate and cross-culturally adapt the Special Interest Group in Amputee Medicine (SIGAM) mobility grades questionnaire in the Persian language and to investigate its psychometric properties. Methods: The SIGAM mobility scale was translated into Persian according to international guidelines for cross-cultural adaptation of self-reported measures and was administered to forty Persian-speaking people with lower limb amputations. Measurement properties were evaluated following COSMIN (COnsensus-based Standards for the Selection of Health Measurement INstruments) recommendations and included internal consistency, test–retest reliability, and hypotheses testing for construct validity by comparing SIGAM mobility grades to the Locomotor Capabilities Index-5 (LCI-5), Houghton scale, Activities-specific Balance Confidence (ABC) scale, the 2-Minute Walk Test (2-MWT), and the Timed Up and Go (TUG). Results: SIGAM mobility scale demonstrated acceptable internal consistency (Kuder-Richardson 20 coefficient = 0.72) and excellent test–retest reliability (Cohen Kappa coefficient = 0.85). Hypothesis testing for construct validity confirmed the good to very good correlations of the Persian SIGAM mobility scale with the LCI-5 (r = 0.63, 0.55, and 0.63 for the general, basic, and advanced activities components, respectively), Houghton scale (r = 0.63), ABC scale (r = 0.73), 2-MWT (r = 0.50), and TUG test (r = −0.51). Conclusion: The Persian version of the SIGAM mobility scale demonstrated preliminary evidence of acceptable psychometric properties, supporting its clinical applicability. Full article

Background/Objectives: This cross-sectional study aimed to identify predictors of parent-reported health-related quality of life (HRQOL) in young children with early brain damage and severe motor dysfunction. It used baseline data from the PIH Multi Study, a randomized controlled trial evaluating an intensive, family-centered habilitation program for preschool children and their parents. Methods: Parent-reported HRQOL were measured using the CPCHILD questionnaire. Potential predictors included adaptive function (PEDI-CAT), gross motor function (GMFM-66), postural control and balance (ECAB), and communication function (FOCUS). These were selected to reflect the domains of the ICF-CY framework. Data were collected by professionals and by parents. Linear regression analyses were conducted to identify significant predictors. Results: Analyses included 65 children. Better adaptive skills, gross motor function, postural control, and communication all predicted higher parent-reported HRQOL. Adaptive skills—particularly in self-care and mobility—and gross motor function emerged as the strongest predictors. Conclusions: The study highlights the importance of targeting basic functional skills in early habilitation efforts for children with severe disabilities. The findings support a multidimensional understanding of health in line with the ICF-CY framework and underline the value of early, individualized, and family-centered interventions. Future research should investigate these predictors longitudinally and explore ways to integrate children’s own perspectives in assessment of HRQOL. Full article

Background: Breast cancer-related lymphedema (BCRL) is a common and debilitating treatment-related adverse event that can profoundly impact quality of life and financial well-being. Although prospective surveillance and early intervention for BCRL have been shown to reduce the incidence and severity of this chronic condition, diagnostic accuracy of screening, programmatic utilization and efficacy vary widely. We describe the protocol for the BCRL Prospective Surveillance Model (PSM) and Early Intervention Program at the Dana-Farber Brigham Cancer Center that aims to address these issues by augmenting arm measurements (standard of care) with use of patient-reported outcome metrics (PROMs). Methods: Women with newly diagnosed stage I-III breast cancer at high risk for developing BCRL based on tumor and treatment characteristics are eligible for inclusion in our PSM care pathway, which uses both the Breast Cancer and Lymphedema Symptom Experience Index PROMs and arm measurements for screening. Screening begins prior to the initiation of neoadjuvant therapy and continues at regular intervals postoperatively. A positive screen, defined as new patient-reported arm swelling/heaviness and/or relative volume change (RVC) ≥ 5% in the affected limb, triggers consideration for multidisciplinary early intervention. Analysis: The BCRL detection rate will be compared to years previous to protocol development. PSM feasibility will be determined according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Efficacy of the PSM will be gauged by comparing change in patient-reported outcomes of interest and arm volume measurement pre and post early intervention. Feasibility will be determined by calculating the percentage of PSM-eligible individuals who complete all PSM activities in a 1-year span. Characteristics of participants versus non-participants in the target population will be compared. Furthermore, 1:1 semi-structured interviews with enrolled patients will be performed to understand facilitators and barriers to implementation. Conclusions: The findings from this study will be used to develop a standardized approach to PSM and early intervention that can be adapted to both resource-modest and resource-abundant healthcare infrastructures. Full article

(1) Background: The global increase in life expectancy has generated growing interest in strategies that support functional independence and quality of life among older adults. Functional fitness—including strength, mobility, flexibility, and aerobic endurance—is essential for preserving autonomy during aging. In this context, physical exercise, particularly High-Intensity Interval Training (HIIT), has gained attention for its time efficiency and physiological benefits. This randomized controlled trial aimed to evaluate the effects of a group-based HIIT program on functional fitness in older adults; (2) Methods: Functional outcomes were assessed before, during, and after a 65-week intervention using standardized field tests, including measures of upper and lower body strength, flexibility, aerobic endurance, and agility. This study was prospectively registered at ClinicalTrials.gov (NCT07170579); (3) Results: Significant improvements were observed in the HIIT group across multiple domains of functional fitness compared to the control group, notably in upper body strength, lower limb flexibility, cardiorespiratory endurance, and mobility; (4) Conclusions: These results suggest that HIIT is an effective and adaptable strategy for improving functional fitness in older adults, with the potential to enhance performance in daily activities and support healthy aging in community settings. Full article

Cycling-induced vibration significantly affects riding comfort, with road surface conditions and vehicle type identified as primary contributing factors. This study developed a vibration measurement system based on ISO 2631-1, and proposed a method for generating cycling comfort maps grounded in vibration severity levels. Field measurements on 30 campus roads in Nanchang, China, used a Mountain Bike, Shared E-bike, and Shared Bicycle. Triaxial acceleration data were collected to evaluate vibration exposure, and comfort levels were classified to produce spatially resolved maps. Results show the proposed system has strong stability and adaptability across urban environments. The maps effectively captured vibration intensity variations along road segments. Among the three vehicle types, Mountain Bikes showed the lowest vibration exposure, with approximately 90% of segments rated as comfortable. Shared E-bike exhibited moderate vibration levels, with 42% of segments deemed uncomfortable, while Shared Bicycles experienced the highest vibration, with 80% of routes potentially inducing discomfort and only 1% meeting comfort standards. This study offers a framework for objective acquisition and visualization of cycling vibration data. The developed system and mapping method provide tools for assessing vehicle vibration, guiding route selection, and offer potential value for road quality monitoring. Full article

Fish species’ biological vocalizations serve as essential acoustic signatures for passive acoustic monitoring (PAM) and ecological assessments. However, limited availability of high-quality acoustic recordings, particularly for region-specific species like the brown croaker (Miichthys miiuy), hampers data-driven bioacoustic methodology development. In this study, we present a framework for reconstructing brown croaker vocalizations by integrating fk14 wavelet synthesis, PSO-based parameter optimization (with an objective combining correlation and normalized MSE), and deep learning-based validation. Sensitivity analysis using a normalized Bartlett processor identified delay and scale (length) as the most critical parameters, defining valid ranges that maintained waveform similarity above 98%. The reconstructed signals matched measured calls in both time and frequency domains, replicating single-pulse morphology, inter-pulse interval (IPI) distributions, and energy spectral density. Validation with a ResNet-18-based Siamese network produced near-unity cosine similarity (~0.9996) between measured and reconstructed signals. Statistical analyses (95% confidence intervals; residual errors) confirmed faithful preservation of SPL values and minor, biologically plausible IPI variations. Under noisy conditions, similarity decreased as SNR dropped, indicating that environmental noise affects reconstruction fidelity. These results demonstrate that the proposed framework can reliably generate acoustically realistic and morphologically consistent fish vocalizations, even under data-limited scenarios. The methodology holds promise for dataset augmentation, PAM applications, and species-specific call simulation. Future work will extend this framework by using reconstructed signals to train generative models (e.g., GANs, WaveNet), enabling scalable synthesis and supporting real-time adaptive modeling in field monitoring. Full article

In response to the inability to quickly assess wind noise performance during the early stages of automotive styling design, this paper proposes a method for predicting interior wind noise by integrating automotive point cloud models with the Gray Wolf Optimization Residual Network model (GWO-ResNet). Based on wind tunnel test data under typical operating conditions, the point cloud model of the test vehicle is compressed using an auto-encoder and used as input features to construct a nonlinear mapping model between the whole vehicle point cloud and the wind noise level at the driver’s left ear. Through adaptive optimization of key hyperparameters of the ResNet model using the gray wolf optimization algorithm, the accuracy and generalization of the prediction model are improved. The prediction results on the test set indicate that the proposed GWO-ResNet model achieves prediction results that are consistent with the actual measured values for the test samples, thereby validating the effectiveness of the proposed method. A comparative analysis with traditional ResNet models, GWO-LSTM models, and LSTM models revealed that the GWO-ResNet model achieved Mean Absolute Percentage Error (MAPE) and mean squared error (MSE) of 9.72% and 20.96, and 9.88% and 19.69, respectively, on the sedan and SUV test sets, significantly outperforming the other comparison models. The prediction results on the independent validation set also demonstrate good generalization ability and stability (MAPE of 10.14% and 10.15%, MSE of 23.97 and 29.15), further proving the reliability of this model in practical applications. The research results provide an efficient and feasible technical approach for the rapid evaluation of wind noise performance in vehicles and provide a reference for wind noise control in the early design stage of vehicles. At the same time, due to the limitations of the current test data, it is impossible to predict the wind noise during the actual driving of the vehicle. Subsequently, the wind noise during actual driving can be predicted by the test data of multiple working conditions. Full article

This paper presents a systematic approach to the development and validation of a monitoring and protection system based on the IEC 61850 standard, evaluated through hardware-in-the-loop (HIL) testing. The study utilized an already existing model of a modern power grid consisting of the IEEE 9-bus power system integrated with a large-scale wind power plant (LSWPP). The SEL-487B Relay was configured to protect the PCC using a low-impedance busbar differential monitoring and protection system equipped with adaptive setting group logic that automatically transitions between Group 1 and Group 2 based on system loading conditions. Significant steps were followed for selecting and configuring instrument transformers and implementing relay logic in compliance with IEEE and IEC standards. Real-time digital simulation using Real-Time Digital Simulator (RTDS) hardware and its software, Real-time Simulation Computer-Aided Design (RSCAD), was used to assess the performance of the overall monitoring and protection system, focusing on the monitoring and publishing of the selected electrical and mechanical measurements from a selected wind turbine generator unit (WTGU) on the LSWPP side through the IEC 61850 standard network, and on the behavior of the monitoring and protection system under initial and increased load conditions through monitoring of differential and restraint currents. The overall monitoring and protection system was tested under both initial and increased load conditions, confirming its capability to reliably publish analog values from WTGU13 for availability on the IEC 61850 standard network while maintaining secure protection operation. Quantitatively, the measured differential (operate) and restraint currents were 0.32 PU and 4.38 PU under initial loading, and 1.96 PU and 6.20 PU under increased loading, while total fault clearance times were 606.667 ms and 706.667 ms for faults under initial load and increased load demand conditions, respectively. These results confirm that the developed framework provides accurate real-time monitoring and reliable operation for faults, while demonstrating a practical and replicable solution for monitoring and protection at transmission-level PCCs within renewable-integrated networks. Full article

Cycle slips, abrupt discontinuities in carrier-phase measurements, pose a significant challenge for single-frequency GNSS receivers, particularly in real-time applications where rapid detection is critical. Unlike dual-frequency approaches, these receivers cannot rely on redundant combinations to isolate slips from other errors. This study proposes a real-time cycle slip detection algorithm for single-frequency GNSS receivers based solely on short-term differencing of pseudorange and carrier-phase observables. The method employs a two-step logic: first-order differencing of code-minus-carrier and second-order differencing of carrier phase. Both steps employ satellite elevation-dependent adaptive thresholds, enabling robust detection under diverse signal conditions. The method requires no user position, receiver-generated tracking flags, or additional sensor data. Experimental results reveal that the algorithm achieves over 98% detection accuracy for slips exceeding 10 cycles, with no false positives in artificial slip testing, and 87.93% agreement with Loss of Lock Indicators (LLI) during periods in which the receiver indicated signal instability. Full article