Search Results (74)

Crimean–Congo Hemorrhagic Fever Virus (CCHFV) is a tick-borne bunyavirus with widespread and growing geographic distribution that causes severe hemorrhagic fever and death. Vaccine candidates targeting the viral nucleoprotein (NP) have shown efficacy in both mouse and non-human primate models but the mechanism of protection is unclear. Here we employ the closely related Hazara virus (HAZV) to investigate how the intracellular antibody receptor TRIM21 uses anti-NP antibodies to neutralize infection. We show that TRIM21 can detect incoming NP particles within hours of infection and that this results in a potent block to infection. Electroporated-antibody-dependent neutralization assay (EDNA) experiments reveal that TRIM21 inhibits viral transcription, protein expression and genome synthesis and reduces the production of infectious virions. Mutations and domain deletions within TRIM21 reveal that neutralization requires antibody-binding by the PRYSPRY domain but is only partially dependent on the E3 ubiquitin ligase RING domain. The data suggest a dual restriction mechanism in which NP cross-linking by TRIM21 physically interferes with NP function whilst parallel ubiquitination labels the protein for degradation. This dual mechanism is similar to that used by TRIM5 against retroviruses and suggests that antiviral TRIMs may utilize their capacity for self-assembly both for catalytic activation and viral caging. Full article

Vehicle crash boxes are elements that protect the integrity of vehicles and ensure the safety of occupants in potential vehicle accidents. These crash boxes are mounted on the chassis of vehicles. In this study, composite crash boxes fabricated from aluminum, which is known for its lightweight properties, as well as denim and ultra-high-molecular-weight polyethylene, both of which are widely available on the market, were investigated experimentally. Composite crash boxes composed of an epoxy resin matrix reinforced with denim fabric (DenimFRP) and ultra-high-molecular-weight polyethylene (UHMWPEFRP) fibers, as well as aluminum (Al), were produced. The crash boxes were manufactured using a vacuum infusion method. This combination was produced by wrapping these fibers around an aluminum core. The energy absorption values, peak force values, and specific energy absorption values of the manufactured crash boxes were obtained through quasi-static compression tests and then compared. The best energy absorption value was achieved with the Al+denimFRP composite crash box manufactured by wrapping denim around aluminum at a workload of 1645.22 J, and its specific energy absorption value was also calculated as 15.52 J/g. The difference between the highest and lowest energy absorption was determined to be 244.61%. The highest peak strength value was obtained with the Al+denim+UHMWPEFRP sample, which contained a combination of aluminum on the inside, denim fabric in the middle, and UHMWPE fabric on the outside. Among the individually produced samples, the Al+denimFRP composite crash box manufactured with denim fiber exhibited higher results compared with the UHMWPEFRP composite box manufactured with ultra-high-molecular-weight polyethylene. Full article

This study investigates the mechanical behavior and anisotropy of cellular structures fabricated using PolyJet Matrix (PJM) technology from RGD 720 photopolymer resin. Standard ISO 527 specimens were produced at build orientations of 0°, 45°, and 90° to evaluate the influence of printing direction on tensile properties. Based on these results, the optimal 0° orientation was selected for further analysis of cellular structures, including hexagonal, spiral, and quasi-self-similar geometries, manufactured in both unfilled and silicone-filled configurations. Static tensile tests were performed to determine load–displacement characteristics, maximum load, and deformation behavior. The results reveal a strong dependence of mechanical properties on build orientation, with the highest strength observed at 0° and the lowest at 90°, confirming significant material anisotropy. This behavior was further quantified using first- and second-order anisotropy coefficients derived from experimental data. The introduction of silicone filling improved load-bearing capacity, reduced variability, and promoted a more ductile failure mechanism. Among the analyzed geometries, quasi-self-similar structures exhibited the best mechanical performance, while unfilled structures showed lower strength and higher deformation. The findings demonstrate that both build orientation and structural design are critical factors in optimizing the mechanical properties of additively manufactured components and provide a basis for designing tailored cellular structures for engineering applications. Full article

Battery locomotives used in underground coal mining operations require continuous maintenance, and failures occurring during these operations pose significant occupational safety and health (OSH) risks. Traditional Risk Assessment Methods (TRAMs), particularly the Risk Matrix Method (RMM), often fail to capture the uncertainty and subjectivity inherent in complex mining environments. This study develops a fuzzy logic-based risk assessment framework to improve the evaluation of accident risks associated with maintenance and repair activities in battery locomotive workshops of an underground coal mine in Turkey. Two fuzzy inference models (FL-Basic and FL-Advanced) based on expert knowledge and linguistic variables were designed using Mamdani-type inference with centroid defuzzification. The mathematical formulation of the fuzzy inference and defuzzification steps is presented explicitly, and a six-step algorithm formalises the proposed framework. The rule base of FL-Advanced systematically upweights the severity dimension relative to RMM through reassignment of 16 of the 25 consequent categories. The outputs of these models were compared with RMM to analyse their effectiveness in identifying critical hazards. Application results from Karadon Hard Coal Company show that the proposed FL-Advanced model significantly reduces ambiguity, prioritises high-severity risks more realistically, and provides a more consistent decision-making structure for OSH specialists. The study highlights the advantages of fuzzy logic for modelling uncertain, incomplete, and human-dependent data in hazardous underground mining conditions. Full article

Wheelchair users face significant mobility limitations related to both medical issues (e.g., musculoskeletal strain, pressure ulcers) and urban accessibility challenges. This pilot study introduces a sensor system integrating an inertial measurement unit (IMU), GPS (Global Positioning System), and a pressure-measuring seat to monitor distance travelled, speed, and posture in relation to real-world conditions. Seven participants navigated an approximately 800-metre outdoor course, divided into 13 sections, while real-time data were recorded. The results showed an average speed of 1.24 ± 0.41 m/s with peak speeds of up to 2.67 m/s. The centre of pressure on the seat fluctuated by an average of 25 mm in the x and y directions (left-right: COPx, back-forward: COPy). The data for average speed, COPx, and COPy showed significant differences between most of the 13 sections, with large, very large, and huge effect sizes. Comparing the speed, COPx, and COPy data with respect to distance travelled, and correlating them between the seven participants by applying the rank-sum method to the mean R² and calculating Kendall’s W, revealed that speed, COPx, and COPy were influenced by course conditions (R² medians between 0.013 and 0.499; W = 0.7857, strong agreement; χ²p = 0.0281). Small R² values indicate more individualised participant behaviour, while large R² values highlight the stronger influence of course conditions on the parameters. This non-invasive and cost-effective system provides objective motion data that can be used for future research in wheelchair design and rehabilitation strategies. Despite its advantages, this study was limited to able-bodied participants, so further clinical trials with individuals with mobility impairments are needed. Full article

Reliable tool-wear monitoring is essential for maintaining machining quality and preventing unscheduled downtime in manufacturing. This investigation presents a sound-based classification framework for identifying wear states in the turning of AISI 316L stainless steel using advanced gradient-boosting models. Acoustic signals were recorded under constant cutting parameters to eliminate process-induced variability, and each recording was divided into standardized 2 s segments. A total of 540 multidomain features—including RMS, ZCR, spectral descriptors, Mel-spectrogram statistics, MFCCs and their derivatives, and discrete wavelet energies—were extracted to capture both stationary and transient characteristics of tool–workpiece interactions. Feature selection was performed using a three-stage pipeline comprising Boruta, LASSO, and SHAP analysis, resulting in a compact subset of highly informative descriptors. LightGBM, XGBoost, and CatBoost classifiers were trained using stratified 10-fold cross-validation across three wear states: Unworn, Slight wear, and Severe wear. LightGBM and XGBoost achieved the best performance, with mean accuracies above 0.96 and strong PRC–AUC and ROC–AUC values (0.98–1.00). Although Slight wear remained the most difficult class due to its transitional acoustic characteristics, all models showed clear separability for Unworn and Severe wear conditions. The results confirm that boosted decision-tree methods combined with SHAP-enhanced feature selection provide an effective, low-cost, and non-contact solution for tool-wear classification in 316L turning. Full article

Background and Objectives: Glioblastoma (GBM) is the most aggressive form of primary brain tumor, characterised by high recurrence rates and poor patient prognosis. This study aimed to identify gene-expression signatures and molecular networks associated with primary and recurrent GBM to better understand the biological mechanisms underlying tumor progression. Materials and Methods: Gene expression analysis of TCGA data was conducted to identify differentially expressed genes across tumor, recurrent, and normal brain tissues. Analysis of overlapping differentially expressed gene sets revealed both common and specific gene-expression profiles across the groups, highlighting genes potentially involved in GBM recurrence. Gene network and canonical pathway analyses were performed using Ingenuity Pathway Analysis (IPA) to identify key pathways and cellular functions altered in GBM. Results: Our data identified distinct molecular signatures in tumor, recurrent, and normal brain samples, highlighting dysregulated genes associated with cellular growth, proliferation, and movement. Transcriptomic stratification revealed progressive tumor- and recurrence-adapted states, with composite Tumor Scores (TS) and Recurrence Scores (RS) classifying samples into four classes: normal-like, proliferative, transitional, and recurrence-adapted tumor states. Conclusions: These findings provide insights into the signaling networks and biological mechanisms underlying GBM recurrence and may guide the identification of potential therapeutic targets to improve the management of this malignancy. Full article

Background: Mobile health (mHealth) applications are widely used for lifestyle monitoring and health promotion; however, their psychological impact on mental health outcomes remains insufficiently understood. Beyond usage frequency, the perceived usefulness of mHealth tools and underlying psychological mechanisms play a critical role in explaining their association with psychological distress. The present study examined perceived health competence as a potential mediator linking mHealth use to symptoms of depression, anxiety, and stress. Methods: This cross-sectional study included 255 adult participants who completed an online survey assessing frequency of mHealth use, perceived usefulness of mHealth applications, perceived health competence (PHCS), and psychological distress (DASS-21). Separate mediation models were tested for depression, anxiety, and stress, with perceived health competence specified as the mediator. Analyses were conducted using bootstrapped mediation procedures. Results: Perceived usefulness of mHealth applications was strongly and positively associated with perceived health competence, which in turn was consistently associated with lower levels of depression, anxiety, and stress. Mediation analyses indicated significant indirect effects of perceived usefulness on all three distress outcomes through perceived health competence. In contrast, frequency of mHealth use showed weaker and less consistent associations, with primarily small direct effects and no significant indirect effects through perceived health competence. Conclusions: The findings indicate perceived health competence is a plausible explanatory pathway statistically consistent with the association between perceived usefulness and psychological distress. The psychological benefits of mHealth applications appear to depend less on how frequently they are used and more on whether users perceive them as useful and empowering. These results underscore the importance of incorporating psychological process indicators into the design and evaluation of mHealth interventions. Full article

Vehicle crush boxes are one of the safety elements used in vehicles to minimize damage that may occur during an accident. The task of crush boxes is to absorb the energy which is generated during an accident. In this study, peak force, energy absorption and specific energy absorption values of cylindrical composite crush boxes, to which 0.25% and 0.50% graphene was added, were experimentally investigated with hydrothermal aging. The composite crush boxes were produced with vacuum infusion method. Glass, aramid and carbon fibers and their hybridizations were used as fibers. During hybridization, the winding order of the fibers was changed from inside to outside. The parameters for hydrothermal aging were selected as 500 h and 1000 h at 60 °C. The highest energy absorption value was obtained in the carbon fiber-reinforced sample CFRPG1H2 with 0.25% graphene-added epoxy resin matrix, aged for 1000 h. The lowest peak strength was observed in the aramid fiber-reinforced sample AFRPG2H2 with 0.50% graphene-added epoxy resin matrix, hydrothermally aged for 1000 h. It was observed that increasing the graphene addition rate reduced the negative effects on aging. It was determined that increasing the graphene ratio by 0.25% had an effect on aging. Full article

Background: Human adenovirus type 4 (HAdV-4), the sole member of species Human mastadenovirus E (HAdV-E), is of zoonotic origin and has established stable human transmission through recombination, conferring distinctive host adaptation and pathogenicity. It causes respiratory and ocular diseases, with a significant risk of severe pneumonia in children. No targeted antivirals are approved for routine use, leaving supportive care as the primary management. China bears a relatively high HAdV-4 disease burden in Asia. Methods: To generate neutralizing nanobodies (Nbs) against HAdV-4, we employed an alpaca immunization strategy using hexon protein from Ad4-RI67 strain, followed by the isolation of hexon-specific nanobodies. The epitope competition and molecular docking was employed to analysis the binding site of the Nbs’. We engineered VHH-Fc fusions by conjugating VHH domains to human IgG1 Fc. The lead candidate, NVA17, showed efficacy in both in vitro and in vivo (Stat1^+/− mouse model). Flow cytometric analysis was employed to assess the downstream immune effects of NVA17 in vivo. Its intracellular neutralization mechanism was further investigated through confocal microscopy by examining co-localization in TRIM21-overexpressing and knockdown cells. Results: The isolated nanobodies revealed epitopes distinct from those targeted by known antibodies. The lead candidate NVA17 demonstrated potent neutralizing activity in vitro (IC₅₀ < 10 ng/mL). In the Stat1^+/− mouse model, NVA17 provided complete protection against lethal challenge, significantly reduced viral load in the lungs, and ameliorated pathological damage. NVA17 treatment dose-dependently reversed the virus-induced reduction in immune cell counts and enhanced cytotoxicity, suggesting a systemic immunomodulatory effect. Mechanistic studies indicated that the antiviral activity of NVA17 partly depends on the TRIM21-mediated antibody-dependent intracellular neutralization (ADIN) pathway, whereby TRIM21 terminates the viral life cycle by promoting viral degradation via K48-linked ubiquitination. Conclusions: We have identified multiple antibody candidates, particularly NVA17, with significant therapeutic potential for developing antibody-based treatments against HAdV-4. This offers a targeted intervention strategy to counter the current lack of specific antiviral therapies. Full article

In this paper, we present the results of a comprehensive study on how excited-state absorption and concentration effects influence fiber laser efficiency and the optimization of the laser cavity’s output coupler reflection. The concentration effects discussed include the cooperative interaction between two closely spaced active ions and the pair-induced quenching typically observed in heavily doped gain fibers. The laser is simulated using a model based on the laser, pump, and spontaneous emission waves propagating along the gain fiber, where the intensities of these waves determine their absorption or amplification. The model considers the radial distributions of optical fields and populations of the energy levels of the active ions, which is crucial to comply with the law of conservation of energy. The results discussed in this paper are essential for applications related to the optimization of heavily doped fiber lasers. The physics behind the reported results is discussed. Full article

Mixed legume–grass pastures may enhance nitrogen recycling via litter and excreta compared to unfertilized grass monocultures. This study evaluated litter biomass, litter deposition rate, and the chemical and isotopic composition of Urochloa decumbens litter in monoculture and mixed pasture intercropped with Arachis pintoi cv. Belmonte at five planting spacings (0.40, 0.50, 0.60, 0.70, and 0.80 m) in a Ferralsol. Additionally, isotopic analysis of sheep feces under grazing was conducted across the dry season. The experiment was conducted according to a split-plot scheme, with spacings in the plots and the periods or years in the subplots, in a randomized block design, with four replications. Litter biomass was not significantly influenced by planting spacing; however, the litter deposition rate was substantially greater in mixed pastures, reaching up to 77.2 kg ha⁻¹ day⁻¹ in the second year. Isotopic analysis revealed that up to 39% of the litter carbon was derived from C3 plants (Arachis pintoi), while nitrogen concentration ranged from 8.3 g kg⁻¹ in monoculture to 12.9 g kg⁻¹ at 0.40 m spacing. Spatial arrangement was critical for optimizing nutrients dynamic. Narrower planting spacings (0.40–0.50 m) increased the proportion of Arachis pintoi and enhanced litter deposition rates, improving nitrogen inputs and cycling within mixed Urochloa decumbens. Full article

To ensure the safety of nuclear power production, nuclear power plants deploy numerous sensors to monitor various physical indicators during production, enabling the early detection of anomalies. Efficient anomaly detection relies on complete sensor data. However, compared to conventional energy sources, the extreme physical environment of nuclear power plants is more likely to negatively impact the normal operation of sensors, compromising the integrity of the collected data. To address this issue, we propose an anomaly detection method for nuclear power data: Neural Normal Stochastic Process (NNSP). This method does not require imputing missing sensor data. Instead, it directly reads incomplete monitoring data through a sequentialization structure and encodes it as continuous latent representations in a neural network. This approach avoids additional “processing” of the raw data. Moreover, the continuity of these representations allows the decoder to specify supervisory signals at time points where data is missing or at future time points, thereby training the model to learn latent anomaly patterns in incomplete nuclear power monitoring data. Experimental results demonstrate that our model outperforms five mainstream baseline methods—ARMA, Isolation Forest, LSTM-AD, VAE, and NeutraL AD—in anomaly detection tasks on incomplete time series. On the Power Generation System (PGS) dataset with a 15% missing rate, our model achieves an F1 score of 83.72%, surpassing all baseline methods and maintaining strong performance across multiple industrial subsystems. Full article

Background/Objectives: While anterior lumbar interbody fusion (ALIF) is a well-established treatment for degenerative lumbar spine pathology, the timing and pace of postoperative recovery remain poorly defined. Understanding these temporal trends is clinically important for setting patient expectations and optimizing postoperative care. Methods: This retrospective single-institution study evaluated functional recovery in patients undergoing primary, single-level stand-alone (SA) ALIF, or with percutaneous posterior instrumentation (PI). Patient-reported outcome measures (PROMs), including the Oswestry Disability Index (ODI), the Visual Analog Scale (VAS) for back and leg pain, and the SF-12 Physical Component Score (PCS), were assessed preoperatively and at 2 weeks, 6 weeks, 3 months, 6 months, 1 year, and 2 years postoperatively. Achievement of minimum clinically important difference (MCID), global rating change (GRC), and return-to-activity milestones were also analyzed. Results: A total of 143 patients were included (90 SA; 53 PI). PROMs showed significant improvement through 1 year. VAS-back improved by 2 weeks, while ODI and SF12 PCS initially worsened but improved after 6 weeks. By 6 months, over half of the cohort achieved MCID, with continued gains through 1 year. Most patients returned to driving and work, and over 90% discontinued narcotics. Recovery trajectories were comparable between groups, despite early delays in the instrumented cohort. Conclusions: These findings provide time-specific recovery benchmarks that can guide surgical decision-making, patient education, and expectations around functional milestones. Full article

This study demonstrates that effervescent denture cleansers can influence the electrochemical behavior of cobalt–chromium (Co-Cr) alloys, with a particular focus on their corrosion resistance. The findings underscore the importance for dental professionals of selecting cleansers compatible with Co-Cr prostheses to minimize material degradation and enhance clinical durability. Corrosion resistance was evaluated using open-circuit potential (OCP), corrosion current density (i_corr), and passivation current density (i_pass). Surface morphology and elemental composition were analyzed through scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). Forty specimens (n = 5 per group) were individually immersed in one of ten test solutions: distilled water (DW), artificial saliva (AS), and eight commercial denture cleansers—Polident 3 minutes™ (P3M), Steradent™ (St), Polident for Partials™ (PP), Efferdent™ (Ef), Corega Tabs™ (CT), NitrAdine™ (Ni), Fixodent™ (Fi), and Kukident™ (Ku). Each specimen was exposed a single solution to avoid cross-contamination. Results showed St, Ef, and Ku had higher OCP values than DW and Ni (p < 0.05), indicating better corrosion resistance. AS exhibited lower OCP values compared to St (p = 0.034), Ku (p = 0.023), and P3M (p = 0.050). DW had higher i_corr than PP (p = 0.030), CT (p = 0.005), and P3M (p = 0.003). For i_pass, DW had lower values than Ef (p = 0.025) and Ku (p = 0.016). SEM and EDS revealed no significant surface alterations. Understanding the underlying corrosion mechanisms in different solutions provides valuable insights into optimizing material performance and ensuring durability in clinical applications. The corrosion resistance of Co-Cr depends on the stability of the passive oxide layer, which can be degraded by chloride ions, reinforced by sulfate ions, and influenced by active ingredients in denture cleansers. Overall, the Co-Cr alloy demonstrated acceptable corrosion resistance, underscoring the importance of selecting suitable cleansers for prosthesis longevity. Full article