Search Results (494,173)

Ischemia–reperfusion (I/R) injury is a complex pathological process underlying numerous acute organ failures and is a significant cause of morbidity and mortality in diseases such as myocardial infarction, stroke, thrombosis, and organ transplantation. Mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs) have demonstrated considerable therapeutic potential, but their broad tropism and general repair signaling may limit their efficacy. This review addresses the emerging paradigm of using organ-specific EVs for the treatment of I/R injury in the respective organs. We summarize the existing studies performed on experimental animals showing that these native EVs could possess tissue tropism and carry a specialized cargo of proteins, miRNAs, and lipids tailored to the unique regenerative needs of their organ of origin, enabling them to precisely modulate key processes, including inflammation, apoptosis, oxidative stress, and angiogenesis. However, their clinical translation faces challenges related to scalable production, standardization, and the dualistic nature of their effects, which can be either protective or detrimental, depending on the cellular source and pathophysiological context. Future developments need to focus on overcoming these obstacles through rigorous isolation protocols, engineering strategies such as cargo enrichment and hybrid vesicle creation, and validation in large-animal models. Overall, organ-specific EVs offer a novel, cell-free therapeutic strategy with the potential to significantly improve outcomes in I/R injury. Full article

As high-speed railway systems continue to develop toward intelligent operation, axle box bearings integrated with sensors have become key components for real-time condition monitoring. However, introducing sensor-embedded slots disrupts the structural continuity and thermal conduction paths of traditional bearing rings. This results in localized stress concentrations and thermal distortion, which compromise the bearing’s overall performance and service life. This study focuses on a double-row tapered roller bearing used in axle boxes and develops a multi-physics finite element model incorporating the effects of sensor-embedded grooves, based on Hertzian contact theory and the Palmgren frictional heat model. Both contact load verification and thermo-mechanical coupling analysis were performed to evaluate the influence of two key design parameters—groove depth and arc length—on equivalent stress, temperature distribution, and thermo-mechanical coupling deformation. The results show that the embedded slot structure significantly alters the local thermodynamic response. Especially when the slot depth reaches a certain value, both stress and deformation due to thermo-mechanical effects exhibit obvious nonlinear escalation. During the design process, the length and depth of the arc-shaped embedded slot, among other parameters, should be strictly controlled. The study of the stress and temperature characteristics under the thermos-mechanical coupling effect of the axle box bearing is of crucial importance for the design of the intelligent bearing body structure and safety assessment. Full article

Background: Globally, uncorrected refractive errors are recognized as the primary cause of visual impairment and blindness. According to a report by the World Health Organization (WHO), providing spectacle lenses at an affordable cost remains a significant challenge, particularly for underprivileged populations in developing countries. This challenge contributes to the low compliance with spectacle wear worldwide. However, the benefits of wearing spectacles are influenced by the perceptions of the population regarding spectacle use. Methods: A quantitative, cross-sectional survey-based study was conducted at a superior educative center in Oman, the University of Buraimi. Participants were recruited from the four major colleges, namely, the College of Health Sciences (COHS), College of Business (COB), College of Engineering (COE), and College of Law (COL), and the Center for Foundation Studies (CFS). This study was conducted over the period from 18 December 2022 to 18 December 2023. Essential data were collected using an electronic questionnaire facilitated by the Google platform. The initial section of the questionnaire outlines this study’s objectives and its benefits to the community. The digital survey comprises three sections: the first section addresses the sociodemographic profile of the participants; the second section explores perceptions related to spectacles; and the third section examines visual symptoms associated with spectacle wear. In this study, a pre-tested survey was administered following consultation with a panel of three subject matter experts who reviewed the clarity and content validity of the test items. Data analyses were performed using descriptive statistics, and linear regression was applied to assess the effect of socioeconomic profile on perceptions of spectacles. Additionally, data entry, processing, and analysis were conducted using SPSS 25 software. The overall mean score for spectacle-related visual symptoms was 2.51 ± 0.75, indicating a moderate level of symptom occurrence. Results: A total of 415 participants (N = 415) were included in this study, comprising 133 males (32.0%) and 282 females (68.0%). The most prominent symptoms related to spectacle perception were “light sensitivity” and “eye pain”, with mean values of 3.03 ± 1.30 and 3.04 ± 1.25, respectively. Additionally, 249 participants (60%) reported moderate concern regarding spectacle-related visual symptoms. Among female participants, 118 (41.8%) exhibited little concern about visual symptoms associated with spectacle wear, whereas this was observed in 25.6% of male participants. Descriptive statistics indicated the mean perceived spectacle-related disadvantages score measured on a scale of 0 to 4 was 2.88 ± 1.16 (57.69% ± 23.15% in percentages), reflecting a moderate perception of such disadvantages. The linear regression model demonstrated statistical significance, as indicated by the likelihood ratio chi-square = 199.194 (df = 15, p < 0.001). The most significant predictor was study major (χ² = 72.922, p < 0.001). Conclusions: The present study indicates that undergraduate students generally exhibit a low perception of the disadvantages associated with wearing spectacles. Randomized sampling should be preferred in future studies to the convenience sampling technique. The most frequently reported visual symptoms include “light sensitivity and eye pain” among spectacle wearers. Therefore, it is imperative to implement health education programs and foundational studies across colleges to address these issues among undergraduate university students. Full article

In this paper, the use of nilpotent Lie algebras as the basis for homomorphic encryption based on additive operations is explored. The $g$-setting is set up over $g{l}_n\left({\mathbb{Z}}_q\right)$) and the group $G=exp\left(g\right)$, and it is noted that the exponential and logarithm series are truncated by nilpotency in a natural way. From this, an additive symmetric conjugation scheme is constructed: given a message element $M$ and a central randomizer $U\in z\left(g\right),$ we encrypt $=Kexp\left(M+U\right)K^{-1}$ and decrypt to $M=log\left(K^{-1}CK\right)-U$. The scheme is additive in nature, with the security defined in the IND-CPA model. Integrity is ensured using an encrypt-then-MAC construction. These properties together provide both confidentiality and robustness while preserving the homomorphic functionality. The scheme realizes additive homomorphism through a truncated BCH-sum, so it is suitable for ciphertext summations. We implemented a prototype and took reproducible measurements (Python 3.11/NumPy) of the series $\{{10,10}^2,{10}^3,{10}^4,{10}^5\}$ over 10 iterations, reporting the medians and 95% confidence intervals. The graphs exhibit that the latency per operation remains constant at fixed values, and the total time scales approximately linearly with the batch size; we also report the throughput, peak memory usage, $\mid C\mid /\mid M\mid$ expansion rate, and achievable aggregation depth. The applications are federated reporting, IoT telemetry, and privacy-preserving aggregations in DBMS; the limitations include its additive nature (lacking general multiplicative homomorphism), IND-CPA (but not CCA), and side-channel resistance requirements. We place our approach in contrast to the standard FHE building blocks BFV/BGV/CKKS nd the emerging NIST PQC standards (FIPS 203/204/205), as a well-established security model with future engineering optimizations. Full article

An approximate optimal control issue for modular unmanned systems (MUSs) is presented via a cooperative differential game for solving the trajectory tracking problem. Initially, the modular unmanned system’s dynamic model is built with the joint torque feedback technique. The moment of inertia of the motor rotor has positive symmetry. Each MUS module is deemed as a participant in the cooperative differential game. Then, the MUS trajectory tracking problem is transformed into an approximate optimal control problem by means of adaptive critic design (ACD). The approximate optimal control is obtained by the critic network, approaching the joint performance index function of the system. The stability of the closed-loop system is proved through Lyapunov theory. The feasibility of the proposed control algorithm is verified by an experimental platform. Full article

This study presents an integrated petrophysical workflow for the comprehensive characterization of the Upper Dalan and Kangan carbonate gas reservoirs in the Shanul Field, southwest Iran. By combining advanced cross-plot techniques (including M-N, MID, and RHOma-Uma plots) with probabilistic porosity modeling calibrated to core data, this work achieves a higher-resolution discrimination of lithology and more robust estimation of fluid properties compared to conventional single-log approaches. The results reveal significant heterogeneity within both formations but demonstrate the superior reservoir quality of the Upper Dalan, particularly within the UD2 subzone, and in the Ka-2a subzone of the Kangan. The improved workflow enables more accurate zonation and identification of high-quality, productive intervals, supporting optimized field development strategies. These findings provide methodological advances for challenging and heterogeneous carbonate systems, offering a reference framework for similar reservoirs in the Zagros Basin and beyond. Full article

N-glycanase 1 (NGLY1) is a cytoplasmic glycoenzyme that removes N-linked glycans from misfolded glycoproteins. It plays an important role in the endoplasmic reticulum-associated degradation (ERAD) pathway in mammalian cells. NGLY1 dysfunction in humans causes NGLY1 deficiency as a rare autosomal recessive disorder that is characterized by neurodevelopmental delay, hypotonia, movement disorders, seizures, and multi-system involvement. In this review, we summarize recent advances in understanding the neural functions of NGLY1 and the neuropathological phenotypes associated with its deficiency. We discuss the molecular basis of NGLY1 deficiency in the central nervous system (CNS) and pathophysiological insights from animal and human induced pluripotent stem cell (iPSC)-based models. We also highlight emerging gene therapy approaches aimed at restoring NGLY1 activity and alleviating neurological symptoms. Full article

To date, the grinding behavior of saprolite and lateritic overburden mixtures remains poorly understood. The Bond Work Index (BWI) is the principal indicator used to determine the specific energy consumption during the grinding process. To establish the F₈₀ and P₈₀ values, granulometric distribution models—Rosin–Rammler (RR), Gates–Gaudin–Schuhmann (GGS), and the Swebrec function (SWEF)—were evaluated. The mineral phases of the feed samples were analyzed by X-ray powder diffraction. This study provides evidence that the RR function is the most suitable for simulating the particle size distribution of the feed material, with residual errors below 6.30% and a coefficient of determination (R²) exceeding 97%. After the grinding equilibrium cycle is reached, the SWEF model proves to be the most appropriate, exhibiting residual errors under 3.50% and R² values above 98%. BWI reveals that saprolite is the most difficult ore to grind, with specific energy consumption increasing from 16.38 kWh/t to 25.50 kWh/t as the proportion of saprolite in the mixture rises. This reflects a clear upward trend, as confirmed by a fitted model with an R² of 98.54%. In contrast, the grindability index (Gbp) decreases, indicating that the material becomes increasingly resistant to grinding as the saprolite content increases. This may be attributed to inherent material properties, such as hardness, or to physical phenomena related to fragmentation. The declining Gbp further suggests that greater energy input is required to achieve additional particle size reduction. Overall, the findings demonstrate that saprolite is inherently difficult to grind and behaves according to its own grinding characteristics, regardless of whether it is processed alone or in combination with lateritic overburden. Full article

The genetic material in living systems is mainly stored in DNA molecules, which in turn play a dominant biological role in relation to the coding and transfer of genetic information, the biosynthesis of proteins and RNA and the packaging and regulation of DNA expression and accessibility. These features, strictly dictated by the three-dimensional structure of DNA, are governed by non-covalent chemical interactions that drive the folding process of these biological macromolecules. The Main Mechanical Forces (MMFs) approach is a recently formulated calculation method, based on the accurate prediction of structural features of biomolecules through an in-depth assessment of the interplay between specific non-covalent chemical interactions and related mechanical forces developed during the folding process. By adopting the MMFs method in the context of nucleic acids, we report here the results obtained in terms of predicting three-dimensional DNA oligomer tertiary structures. To this end, we have developed tailored nucleic acid-specific equations, enabling to predict the torsion angles (with a relevant level of agreement with experimental values) of the phosphate-sugar backbone of the three model molecules A-, B- and Z- DNA used in this study. To increase the validity of this methodology, we have conducted RMSD measurements, indicating that there is a weak but rather acceptable match between the calculated vs. predicted A-DNA structure, whereas the prediction of the BII-DNA and Z-DNA tertiary structures was fully correct. Full article

To address low-frequency vibration and noise issues in ship grating structures, this study proposes a novel acoustic optimization design method based on modulating flexural wave bandgap characteristics. By establishing an equivalent periodic spring-mass coupled beam model to predict bandgap properties, its effectiveness is validated through numerical simulations and experimental testing. By selectively enhancing longitudinal stiffness while weakening transverse components, the bandgap characteristics are effectively tuned to target frequency bands. This approach achieves an 8.2 dB noise reduction at the 31.4 Hz natural frequency. The results demonstrate that bandgap-based design provides a numerically and experimentally validated solution for low-noise ship structures. Full article

The acoustic, thermal, and mechanical performances of sawdust-reinforced polyurethane (PU) foam are investigated for different thicknesses and varying mesh sizes. Acoustic properties are explored using a combination of impedance tube testing and mathematical modeling with the Johnson–Champoux–Allard–Lafarge (JCAL) model, a simplified JCAL model and a model of non-uniform cylindrical pores with a log-normal radius distribution (NUPSD). Thermal Insulation and mechanical properties are determined by measuring the effective thermal conductivity (K_eff) and by tensile strength tests, respectively. Compared with pure PU foam, the presence of sawdust matches noise reduction coefficients (NRC) and increases sound absorption averages (SAA) by nearly 10%. Increasing thickness and width of backing air gap have the usual effects of improving low- and mid-frequency absorption and shifting resonance peaks toward lower frequencies. As well as superior acoustic performance, samples with Mesh 16 sawdust reinforcement provide both useful insulation (K_eff = 0.044 W/mK) and tensile strength (~0.06 MPa), confirming their multifunctionality. Although the JCAL model provides reasonable fits to the sound absorption data, some of the fitted parameter values are unphysical. Predictions of the NUPSD model are relatively poor but improve with sample thickness and after fiber addition. Full article

Cultivated land quality is critical for soil productivity and scientific fertilization. This study analyzed its evolution and impact on soil productivity across three ecological regions (southern, central, and northern Shanxi) in Shanxi Province, China, from 1998 to 2021). Using data from 8 long-term experimental sites (1998–2021) and 50 monitoring stations (2016–2021), we employed random forest analysis to evaluate temporal trends in key soil indicators. The results show the following: (1) Northern Shanxi exhibited the greatest improvement in soil fertility, with organic matter increasing by 98.2%, total nitrogen by 57.2%, available phosphorus by 131.7%, and available potassium by 17.1%. (2) Nitrogen fertilizer application increased across all regions, while phosphorus and potassium inputs generally declined. (3) Crop yields improved substantially—southern Shanxi wheat and maize increased by 15.3% and 20.9%, respectively, while central and northern Shanxi maize yields rose by 30.9% and 75.4%. Random forest models identified regional characteristics (40%), nitrogen fertilization (20%), and available phosphorus (18%) as primary influencing factors. Although cultivated land quality improved overall, soil fertility remained medium to low. Region-specific management strategies are recommended: rational nitrogen use in all regions; nitrogen control with phosphorus supplementation in the south; focused improvement of available phosphorus and potassium in the center; and increased organic fertilizer in the north. These measures support scientific nutrient management and sustainable agricultural production. Full article

The Automated Building Information Modeling (BIM) reconstruction of existing building curtain walls is crucial for promoting digital Operation and Maintenance (O&M). However, existing 3D reconstruction technologies are mainly designed for general architectural scenes, and there is currently a lack of research specifically focused on the BIM reconstruction of curtain walls. This study proposes a BIM reconstruction method from unmanned aerial vehicle (UAV) images based on neural radiance field (NeRF) and deep learning-based semantic segmentation. The proposed method compensates for the lack of semantic information in traditional NeRF methods and could fill the gap in the automatic reconstruction of semantic models for curtain walls. A comprehensive high-rise building is selected as a case study to validate the proposed method. The results show that the overall accuracy (OA) for semantic segmentation of curtain wall point clouds is 71.8%, and the overall dimensional error of the reconstructed BIM model is less than 0.1m, indicating high modeling accuracy. Additionally, this study compares the proposed method with photogrammetry-based reconstruction and traditional semantic segmentation methods to further validate its effectiveness. Full article

This paper contains an analysis of methods for person classification based on signals from wearable IMU sensors during sports. While this problem has been investigated in prior work, existing approaches have not addressed it within the context of few-shot or minimal-data scenarios. A few-shot scenario is especially useful as the main use case for person identification in sports systems is to be integrated into personalised biofeedback systems in sports. Such systems should provide personalised feedback that helps athletes learn faster. When introducing a new user, it is impractical to expect them to first collect many recordings. We demonstrate that the problem can be solved with over 90% accuracy in both open-set and closed-set scenarios using established methods. However, the challenge arises when applying few-shot methods, which do not require retraining the model to recognise new people. Most few-shot methods perform poorly due to feature extractors that learn dataset-specific representations, limiting their generalizability. To overcome this, we propose a combination of an unsupervised feature extractor and a prototypical network. This approach achieves 91.8% accuracy in the five-shot closed-set setting and 81.5% accuracy in the open-set setting, with a 99.6% rejection rate for unknown athletes. Full article

Accurate aircraft trajectory prediction is fundamental to air traffic management, operational safety, and intelligent aerospace systems. With the growing availability of flight data, deep learning has emerged as a powerful tool for modeling the spatiotemporal complexity of 4D trajectories. This paper presents a comprehensive review of deep learning-based approaches for aircraft trajectory prediction, focusing on their evolution, taxonomy, performance, and future directions. We classify existing models into five groups—RNN-based, attention-based, generative, graph-based, and hybrid and integrated models—and evaluate them using standardized metrics such as the RMSE, MAE, ADE, and FDE. Common datasets, including ADS-B and OpenSky, are summarized, along with the prevailing evaluation metrics. Beyond model comparison, we discuss real-world applications in anomaly detection, decision support, and real-time air traffic management, and highlight ongoing challenges such as data standardization, multimodal integration, uncertainty quantification, and self-supervised learning. This review provides a structured taxonomy and forward-looking perspectives, offering valuable insights for researchers and practitioners working to advance next-generation trajectory prediction technologies. Full article