Search Results (4,016)

The high accessibility and interconnectedness of social media platforms have led to their increasing exploitation as tools for criminal activity. A notable example of such digital sexual offenses is the “Nth Room” case, in which sexually exploitative content and illegal recordings were unlawfully distributed on platforms such as X, Telegram, and Discord. Despite amendments to legislations, including the Sexual Violence Punishment Act and Youth Protection Act, aimed at preventing the recurrence of incidents, these crimes continue to persist. Perpetrators employ tactics such as the repeated creation and deletion of accounts, which complicate efforts to track and apprehend them. Consequently, there is an urgent need to develop advanced cyber investigation technologies capable of effectively monitoring sexual crimes posted on social media. This study aimed to propose a novel cyber investigation technology designed to trace criminal organizations by collecting tweets related to sexual crimes from X, which is the most frequently used social media platform for such content in Korea, and subsequently constructing a knowledge graph. Slang terms commonly associated with sexual crimes on X were employed as search keywords to collect relevant tweets. The knowledge graph is then generated based on three key elements extracted from the tweets: hashtags, words, and URL/invite codes. This graph serves as a tool for tracking the criminal networks involved in the distribution of sexually exploitative content and unauthorized recordings. Furthermore, to enhance tracking efficiency, an optimization model was developed to generate knowledge graphs from various analytical perspectives. In this study, to evaluate the performance of the proposed technology, a dataset of 3387 tweets was collected using an X crawler. Knowledge graphs were generated and optimized through both single and combined analyses of the three key elements, demonstrating the effectiveness of the proposed technology in tracking criminal organizations engaged in sexual crimes. Full article

Background/Objective: The poultry industry requires extensive vaccination of chickens against IBV in an effort to prevent the disease in animals and significant economic losses. Current vaccination strategies often lack effectiveness, and the continual emergence of new IBV variants makes disease control increasingly challenging. We have developed an inactivated vaccine for poultry containing nine different antigens (Nobilis Multriva), including two IBDV strains, two ARV strains, one NDV strain, one AMPV strain, one EDSV strain and two IBV strains: M41 (genotype GI-1) and 4–91 (genotype GI-13). In this study, the IB efficacy of this novel inactivated vaccine was investigated against homologous and heterologous IBV strains. Methods: Inactivated IBV vaccine containing the M41 and 4–91 strains (Nobilis Multriva) was administered intramuscularly, either alone or following vaccine priming, in SPF and commercial chickens. Birds were challenged with homologous and heterologous IBV strains at defined ages (peak of lay, mid-lay and end of lay). Vaccine efficacy was evaluated through serological assays, clinical observations, and monitoring of egg production post-challenge. Results: This vaccine provided excellent broad protection against different IBV strains circulating in different parts of the world, including IBV M41, 4–91, QX, Q1 and Var2. Furthermore, the vaccine provided long-lasting IBV serological response against IB M41 and IB 4–91 until at least 96 weeks of age in SPF and commercial layers and breeder birds. This vaccine will allow farmers to reduce the number of vaccination moments, thereby minimizing stress to the birds, while also decreasing labor demands and the risk of human error, ultimately contributing to lower overall vaccination costs. Conclusions: Given its demonstrated broad cross-protection and sustained serological responses, this nine-valent inactivated vaccine (Nobilis Multriva) represents a key component of an effective vaccination regimen for controlling IBV infections in the poultry industry. Full article

Background: Anterior cruciate ligament reconstruction (ACLR), one of the most frequently performed orthopedic procedures, has experienced rising demand and escalating costs, driving efforts to reduce expenses through shorter hospital stays and an increased shift toward outpatient settings. This study aims to evaluate how differing definitions of “outpatient” surgery influence the interpretation of outcomes following ACLR. Methods: ACS-NSQIP was queried for patients undergoing primary ACL reconstruction between 2014 and 2023. Patients ≥ 18 years with CPT code 29888 were included. Patients with missing hospital length of stay (LOS) data or a LOS > 2 days (≥99th percentile) were excluded. Two definitions of “outpatient” surgery were evaluated: hospital-defined outpatient (HDO) and same-day discharge (SDD, LOS = 0). Propensity score matching of baseline demographics and comorbidities was used to compare HDO and SDD cohorts to their respective inpatient counterparts. Primary outcomes analyzed included 30-day readmission, reoperation, and postoperative complications. Univariate and multivariate analyses were performed to compare risks of complications for HDO and SDD cohorts compared to their inpatient counterparts. Results: A total of 37,546 patients were included in this study, with 35,334 HDO (94.1%) and 34,801 (92.7%) SDD cases. 1021 (2.9%) of the 35,334 HDO patients had an inpatient hospital stay of at least 1 night. In propensity-matched cohorts, hospital-defined inpatient ACLR was associated with significantly greater risk of 30-day reoperation (odds ratio [OR] 3.167, 95% CI 1.267–7.915, p = 0.009) and superficial surgical site infection (SSI) (OR 5.0, 95% CI 1.712–14.604 p = 0.001), while HDO ACLR was associated with increased risk of deep vein thrombosis (DVT) (OR 0.333, 95% CI 0.121–0.916, p = 0.025). Compared to the propensity-matched SDD cohort, inpatient ACLR was significantly associated with greater rates of 30-day readmission (OR 1.988, 95% CI 1.088–3.630, p < 0.001), reoperation (OR 3.222, 95% CI 1.528–6.794, p = 0.001), and superficial SSI (OR 3.286, 95% CI 1.412–7.644, p = 0.003). Conclusions: This study found differences in readmission and deep vein thrombosis between HDO and SDD cohorts when compared to inpatient ACLR. A standardized definition of outpatient surgery should be created to clearly distinguish same-day discharge from other outpatient categories, considering discharge timing and patient monitoring practices. Full article

Urban trees provide essential environmental, health, social, and economic benefits. Consequently, researchers and stakeholders devote considerable effort to characterizing, mapping, and monitoring urban tree species. Traditional identification methods that rely on field surveys are labor-intensive and time-consuming. This study evaluated the potential of field hyperspectral spectroscopy to classify nine common urban tree species at the leaf level. Seven random forest classifiers, each using different combinations of spectral features, were compared for classification accuracy. The model that incorporated both first derivatives of spectral reflectance and vegetation indices achieved the highest overall accuracy (80.4%), whereas the model combining spectral reflectance and vegetation indices had the lowest predictive performance (70.1%). The most influential predictors were spectral bands and first derivatives in the red-edge and SWIR 1 regions; and the vegetation indices Red-edge Vegetation Stress Index (RVSI), Plant Senescence Reflectance Index (PSRI), and Blue Ratio (BR). These results support the use of hyperspectral remote sensing for identifying and classifying urban tree species. Full article

Forests are a critical component of global carbon sequestration, biodiversity, and ecosystem services, making accurate mapping essential for long-term monitoring. In North Korea, limited field access, rugged topography, and inconsistent national statistics necessitate reliable remote sensing–based observation. However, frequent cloud contamination challenges the use of optical time-series imagery for forest monitoring. This study introduces a framework that integrates a ConvLSTM-based autoencoder into a U-Net segmentation model to improve tree cover classification from Sentinel-2 time-series data. The autoencoder was pretrained to reconstruct cloud-contaminated or missing observations using multi-octave Perlin-noise perturbations, providing standardized inputs that enhanced segmentation robustness under noisy conditions. Results show that tree cover accuracy exceeded 96% when all five time steps were available and remained stable (94–95%) even with one missing step. Accuracy declined below 90% with three missing steps but remained above 80%, enabling draft classifications under limited data. Confidence analysis further indicated that model certainty is a practical quality-control metric. Annual mapping for 2019–2024 showed a general increase in tree cover, aligning with reported afforestation efforts in North Korea. Taken together, the framework advances long-term monitoring, carbon accounting, and risk assessment in North Korea, while also enabling robust, region-adapted monitoring in cloud-prone, data-limited settings. Full article

Precision medicine has reshaped the clinical management of prostate cancer by integrating comprehensive genomic profiling, biomarker-driven patient stratification, and the development of molecularly targeted therapeutics. Advances in next-generation sequencing have uncovered diverse genomic alterations—including homologous recombination repair defects, MSI-H/MMRd, PTEN loss, BRCA1/BRCA2 mutations, ATM alterations, SPOP mutations, and molecular hallmarks of neuroendocrine differentiation—that now inform individualized treatment decisions. This review synthesizes established clinical evidence with emerging translational insights to provide an updated and forward-looking overview of precision oncology in prostate cancer. Landmark trials of PARP inhibitors and PSMA-targeted radioligand therapy have redefined treatment standards for biomarker-selected patients. Concurrently, efforts to optimize immune checkpoint inhibition, AKT pathway targeting, and rational combinations with androgen receptor pathway inhibitors continue to expand therapeutic possibilities. Rapidly evolving investigational strategies—including bipolar androgen therapy (BAT), immunotherapeutic approaches for CDK12-altered tumors, targeted interventions for SPOP-mutated cancers, and epigenetic modulation such as EZH2 inhibition for neuroendocrine prostate cancer—further illuminate mechanisms of tumor evolution, lineage plasticity, and treatment resistance. Integrating multi-omics technologies, liquid biopsy platforms, and AI-assisted imaging offers new opportunities for dynamic disease monitoring and biology-driven treatment selection. By consolidating current clinical practices with emerging experimental directions, this review provides clinicians and researchers with a comprehensive perspective on the evolving landscape of precision medicine in prostate cancer and highlights future opportunities to improve patient outcomes. Full article

Ground settlement is readily induced by shield–tail gaps formed during tunneling, where soil loss must be compensated through backfill grouting. However, improper grouting control may trigger tunnel uplift, segment misalignment, and, after solidification, problems such as voids, cracking, and water ingress. Ensuring construction safety and long-term serviceability requires both reliable detection of grouting effectiveness and a mechanistic understanding of grout diffusion. This review systematically synthesizes sensing technologies, diffusion modeling, and intelligent data interpretation. It highlights their interdependence and identifies emerging trends toward multimodal joint inversion and real-time grouting control. Non-destructive testing techniques can be broadly categorized into geophysical approaches and sensor-based methods. For synchronous detection, vehicle-mounted GPR systems and IoT-based monitoring platforms have been explored, although studies remain sparse. Theoretically, grout diffusion has been investigated via numerical simulation and field measurement, including the spherical diffusion theory, columnar diffusion theory, and sleeve-pipe permeation grouting theory. These theories decompose the diffusion process of the slurry into independent movements. Nevertheless, oversimplified models and sparse monitoring data hinder the development of universally applicable frameworks capable of capturing diverse engineering conditions. Existing techniques are further constrained by limited imaging resolution, insufficient detection depth, and poor adaptability to complex strata. Looking ahead, future research should integrate complementary non-destructive methods with numerical simulation and intelligent data analytics to achieve accurate inversion and dynamic monitoring of the entire process, ranging from grout diffusion and consolidation to defect evolution. Such efforts are expected to advance both synchronous grouting detection theory and intelligent and digital-twin tunnel construction. Full article

Wild birds are relevant reservoirs and sentinels for zoonotic pathogens such as Chlamydia psittaci and West Nile virus (WNV), both of which can affect animal and public health. Wildlife rehabilitation centers (WRCs) offer unique opportunities for passive surveillance of emerging and re-emerging infectious diseases, particularly in urban and peri-urban settings. From 2013 to 2022, a total of 1024 bird samples were collected upon admission to WRCs in the Community of Madrid, Spain. Oropharyngeal and cloacal swabs, as well as tissue samples, were tested using real-time PCR targeting the ompA gene of C. psittaci and the 3’NC region of WNV. One sample tested positive for C. psittaci by real-time PCR in 2021, yielding a positivity rate of 0.22% (95% CI: 0.01–1.19). No positive cases were detected during the remaining years of the study. All samples tested negative for WNV over the nine-year period. The low detection rate suggests limited circulation of these pathogens among wild birds in central Spain, though it may partly reflect the variability inherent to passive surveillance and sample-type heterogeneity. However, continued surveillance is warranted, especially in high-risk avian species and personnel occupationally exposed in avian rehabilitation facilities using expanded sample sizes and complementary diagnostic tools. Extending monitoring beyond the typical vector season and increasing testing of sensitive tissues, particularly for WNV, may further enhance detection sensitivity and strengthen early-warning capacity. These efforts are essential to improve early detection and risk assessment within a One Health framework. Full article

The focus of this research is the automation of the synchronization process for track-recording vehicle signals in turnouts. Accurate synchronization of measurement signals is essential for assessing specific track sections—especially complex areas such as turnouts—and for enabling reliable time series for condition monitoring. Currently, the synchronization process is only partially automated, resulting in high levels of manual effort. With over 4000 turnouts on Austria’s main railways, full automation is important for ensuring efficiency and consistency of the synchronization process. Based on an analysis of 109 turnouts in the OeBB railways, the process begins with rough synchronization using mileage and curvature signals to eliminate invalid measurement runs. Subsequently, longitudinal level signals are synchronized within maintenance time blocks. These blocks include measurement runs with consistent signal characteristics between two maintenance interventions. The latest valid run then serves as reference for each block. Methods such as cumulative sum, Euclidean distance and cross-correlation are then employed to achieve fine synchronization. The results demonstrate the feasibility and efficiency of automated synchronization compared to manual methods, enabling more accurate condition assessment. This allows infrastructure managers to track turnout-specific quality indicators, integrate them into asset management systems, and develop predictive maintenance strategies. Full article

Background/Objectives: Workplace violence (WV) against healthcare workers (HCWs) is a major hazard all over the world. Prevention requires a reliable risk assessment. The rate of HCWs reporting a violent event varies considerably across multi-year retrospective studies compared to periodic surveys. We conducted a rapid observational study to demonstrate that data collection methods are more important than socio-cultural and healthcare organizational differences in determining the frequency of reported violence. Methods: In June 2025, in a cross-sectional observational comparison, we examined a total of 236 nurses divided into three groups: the first two were recruited online from Brescia (Italy) and Trollhättan (Sweden), while the third group was composed of Latium (Italy) nurses participating in a sleep health promotion program who answered the same questions on WV online. All the workers reported the frequency of violent incidents experienced in the previous 12 months using the Violent Incident Form (VIF), occupational stress using the Effort/Reward Imbalance questionnaire (ERI), and work ability via the Work Ability Score (WAS). Results: In the three samples, WV was correlated positively with stress and inversely with work ability (p < 0.01), while no significant difference was found between Italian and Swedish nurses in relation to the spot surveys. The nurses questioned directly about WV were significantly younger and reported significantly higher rates of physical aggression (28% vs. 5%, p < 0.001) and all forms of violence (73% vs. 20%, p < 0.001) than those questioned indirectly during the census of all the HCWs. In a multivariate linear regression model, the WV experienced and poor work ability were highly significant predictors of work-related stress (p < 0.001). Nurses who had experienced WV in the previous year had an increased odds ratio (OR = 8.94; Confidence Interval 95% = 4.43; 18.01) of reporting a state of distress. Conclusions: Experience has shown that specific questioning about violence—the commonest method used—encourages respondents to report violent events and may induce overreporting. This method also tends to involve younger workers who are more exposed to WV. On the other hand, prospective studies based on official reports may be influenced by underreporting. Monitoring WV during health promotion interventions included in occupational health surveillance could minimize both phenomena. Systematic studies and meta-analyses which rely mainly on “ad hoc” studies may be biased. Full article

The Semipalatinsk Test Site (STS), one of the most heavily contaminated nuclear test sites globally, presents critical challenges for ecological monitoring and restoration due to long-term radioactive pollution and soil degradation. This study applied the Remote Sensing Ecological Index (RSEI) model to systematically evaluate the spatiotemporal changes in ecological quality at STS from 2003 to 2023. The RSEI model integrated multi-indicator data, including NDVI (Normalized Difference Vegetation Index), LST (Land Surface Temperature), WET (Wetness), and NDBSI (Normalized Difference Built-up and Soil Index), enabling a comprehensive assessment of ecological dynamics. Results demonstrated a significant improvement in ecological quality, with the RSEI increasing by 29.59% (from 0.345 in 2003 to 0.447 in 2023). PCA results indicated that ecological recovery was primarily influenced by surface temperature, vegetation cover, and soil moisture, with radioactive residues further hindering recovery in severely contaminated zones. The proportion of “Poor” areas declined from 14.99% to 0.61%, while “Moderate” and “Good” areas expanded to 55.76% and 8.87%, respectively. Peripheral regions showed faster recovery due to effective natural and management interventions, while core high-contamination zones (Sary-Uzen) exhibited slower recovery due to persistent radioactive residues. This study highlights the applicability of RSEI for assessing ecological recovery in nuclear test sites and emphasizes the need for targeted remediation strategies. These findings provide valuable insights for global ecological management of nuclear test sites, supporting sustainable restoration efforts. Full article

Background: Tanzania is undergoing a rapid nutrition and epidemiological transition that has shifted dietary patterns and lifestyles toward more Westernised models, contributing to an increase in diet-related non-communicable diseases (NCDs), including obesity. Youth aged 15–35 years are particularly vulnerable to these shifts. Objectives: The objective of this scoping review was to map the available evidence on youth obesity in Tanzania, focusing on (1) data gaps in epidemiological reporting; (2) the ongoing nutrition transition; and (3) existing food system and health-related policies targeting youth. Methods: A targeted search was conducted in PubMed, Scopus, and the grey literature. The PCC (Population/Concept/Context) framework guided the study selection, focusing on youth and general young adults aged 15–35 years in Tanzania. Eligible studies published between 2000 and June 2025 were included. Results: The search yielded 247 peer-reviewed articles, of which 35 met the inclusion criteria. The findings reveal substantial gaps in epidemiological reporting, particularly limited regional data and inconsistent age disaggregation, which often obscures youth-specific patterns. Evidence on nutrition and lifestyle transitions is limited and fragmented, while available policies addressing obesity and related risk factors are broad in scope and rarely tailored to the youth population. Conclusions: This review demonstrates that evidence on obesity among Tanzanian youth is scarce, unevenly reported, and insufficiently specific to this age group. Clear gaps exist in epidemiological surveillance, research on nutrition transition, and youth-focused policy design. Strengthening age-specific monitoring systems, generating context-specific evidence, and developing targeted, measurable, and actionable strategies for youth could enhance Tanzania’s efforts to curb the rising burden of obesity and related NCDs. Full article

Frailty assessment and monitoring are essential for supporting independent living and preventing adverse outcomes among older adults. This study aimed to develop and evaluate the concurrent validity of a high-accuracy home-monitoring system for assessing and tracking frailty in older adults. The system integrated off-the-shelf, zero-effort technologies, including ultra-wideband (UWB) indoor positioning, a smart scale, a connected hand dynamometer, and a Bluetooth speakerphone, to measure the five components of Fried’s Frailty Phenotype criteria. Twenty-one participants (aged 21–90 years) completed frailty assessments using both traditional clinical measures and the sensor-based system within a simulated home environment within a major rehabilitation hospital. The developed system demonstrated very strong and statistically significant correlations between the sensor-based system and the Fried’s Frailty Phenotype criteria, strong correlations with the Clinical Frailty Scale, and moderate-to-strong correlations with the Edmonton Frailty Scale, confirming the system’s strong concurrent validity. These findings indicate that high-accuracy, home-based monitoring technologies can provide reliable, objective, and non-invasive assessment of frailty in older adults, supporting early detection and continuous monitoring. This approach shows promise for future integration into smart home environments to enhance proactive frailty management and aging-in-place strategies. Full article

To enhance the monitoring and conservation efforts for China’s Class II endangered species, specifically the wild giant salamander and its ecosystems, this study addresses the urgent need to counteract the rapid decline of its wild population caused by habitat loss and insufficient surveillance. We present an innovative localization system based on passive Ultra-High-Frequency Radio Frequency Identification (UHF RFID) technology, employing a Double-Transform (D-Tr) methodology that integrates an enhanced 3D LANDMARC algorithm with GAIN generative adversarial networks. This system effectively reconstructs missing Received Signal Strength Indicator (RSSI) data due to environmental barriers by applying a log-distance path loss model. The D-Tr framework simultaneously generates RSSI sequences alongside their first-order differential characteristics, allowing for a comprehensive analysis of spatiotemporal signal relationships. Field tests conducted in the Hubei Xianfeng Zhongjian River Giant Salamander National Nature Reserve reveal that the positioning error consistently remains within 10 cm, with average accuracy improvements of 20.075%, 15.331%, and 12.925% along the X, Y, and Z axes, respectively, compared to traditional time-series models such as long short-term memory (LSTM) and gated recurrent unit (GRU). This system, designed to investigate the behavioral patterns and movement paths of farmed giant salamanders, achieves centimeter-level tracking of their cave-dwelling activities. It provides essential technical support for quantitatively assessing their daily activity patterns, habitat choices, and population trends, thereby promoting a shift from passive oversight to proactive monitoring in the conservation of endangered species. Full article

Major depressive disorder (MDD) was long framed as a single clinical entity arising from a linear stress–monoamine–hypothalamic–pituitary–adrenal (HPA) axis cascade. This view was shaped by forced swim and learned helplessness tests in animals and by short-term symptom-based trials using scales such as the Hamilton Depression Rating Scale (HAM-D) and the Montgomery–Åsberg Depression Rating Scale (MADRS). This “unitary cascade” view has been dismantled by advances in neuroimaging, immune–metabolic profiling, sleep phenotyping, and plasticity markers, which reveal divergent circuit-level, inflammatory, and chronobiological patterns across anxiety-linked, pain-burdened, and cognitively weighted depressive presentations, all characterized by high rates of non-response and relapse. Translationally, face-valid rodent assays that equated immobility with despair have yielded limited bedside benefit, whereas cross-species bridges—electroencephalography (EEG) motifs, rapid eye movement (REM) architecture, effort-based reward tasks, and inflammatory/metabolic panels—are beginning to provide mechanistically grounded, clinically actionable readouts. In current practice, depression care is shifting toward systems psychiatry: inflammation-high and metabolic-high archetypes, anhedonia- and circadian-dominant subgroups, formal treatment-resistant depression (TRD) staging, connectivity-guided neuromodulation, esketamine, selected pharmacogenomic panels, and early digital phenotyping, as endpoints broaden to functioning and durability. A central gap is that heterogeneity is acknowledged but rarely built into trial design or implementation. This perspective advances a plasticity-centered systems psychiatry in which a testable prediction is that manipulating defined prefrontal–striatal and prefrontal–limbic circuits in sex-balanced, chronic-stress models will reproduce human network-defined biotypes and treatment response, and proposes hybrid effectiveness–implementation platforms that embed immune–metabolic and sleep panels, circuit-sensitive tasks, and digital monitoring under a shared, preregistered data standard. Full article