Pulmonary manifestations of vasculitis are associated with significant morbidity and mortality in affected individuals. They result from a complex interplay between immune dysregulation, which leads to vascular inflammation and tissue damage. This review explored the underlying pathogenesis of pulmonary involvement in vasculitis, encompassing various forms such as granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), eosinophilic granulomatosis with polyangiitis (EGPA), and anti-GBM disease. Mechanisms involving ANCA and anti-GBM autoantibodies, neutrophil activation, and neutrophil extracellular trap (NETs) formation are discussed, along with the role of the complement system in inducing pulmonary injury. Furthermore, the impact of genetic predisposition and environmental factors on disease susceptibility and severity was considered, and the current treatment options were presented. Understanding the mechanisms involved in the pathogenesis of pulmonary vasculitis is crucial for developing targeted therapies and improving clinical outcomes in affected individuals. Full article

This study proposes a vessel position prediction method using attention spatiotemporal graph convolutional networks, which addresses the issue of low prediction accuracy due to less consideration of inter-feature dependencies in current vessel trajectory prediction methods. First, the method cleans the vessel trajectory data and uses the Time-ratio trajectory compression algorithm to compress the trajectory data, avoiding data redundancy and providing feature points for vessel trajectories. Second, the Spectral Temporal Graph Neural Network (StemGNN) extracts the correlation matrix that describes the relationship between multiple variables as a priori matrix input to the prediction model. Then the vessel trajectory prediction model is constructed, and the attention mechanism is added to the spatial and temporal dimensions of the trajectory data based on the spatio-temporal graph convolutional network at the same time as the above operations are performed on different time scales. Finally, the features extracted from different time scales are fused through the full connectivity layer to predict the future trajectories. Experimental results show that this method achieves higher accuracy and more stable prediction results in trajectory prediction. The attention-based spatio-temporal graph convolutional networks effectively capture the spatio-temporal correlations of the main features in vessel trajectories, and the spatio-temporal attention mechanism and graph convolution have certain interpretability for the prediction results. Full article

This study introduces a novel process identification method aimed at overcoming the challenge of accurately estimating process models when faced with deterministic disturbances, a common limitation in conventional identification methods. The proposed method tackles the difficult modeling problems due to deterministic disturbances by representing the disturbances as a linear combination of Laguerre polynomials and applies an integral transform with frequency weighting to estimate the process model in a numerically robust and stable manner. By utilizing a least squares approach for parameter estimation, it sidesteps the complexities inherent in iterative optimization processes, thereby ensuring heightened accuracy and robustness from a numerical analysis perspective. Comprehensive simulation results across various process types demonstrate the superior capability of the proposed method in accurately estimating the model parameters, even in the presence of significant deterministic disturbances. Moreover, it shows promising results in providing a reasonably accurate disturbance model despite structural disparities between the actual disturbance and the model. By improving the precision of process models under deterministic disturbances, the proposed method paves the way for developing refined and reliable control strategies, aligning with the evolving demands of modern industries and laying solid groundwork for future research aimed at broadening application across diverse industrial practices. Full article

Land use/land cover (LULC) changes significantly impact spatiotemporal groundwater levels, posing a challenge for sustainable water resource management. This study investigates the long-term (2000–2022) influence of LULC dynamics, particularly urbanization, on groundwater depletion in Kabul, Afghanistan, using geospatial techniques. A time series of Landsat imagery (Landsat 5, 7 ETM+, and 8 OLI/TIRS) was employed to generate LULC maps for five key years (2000, 2005, 2010, 2015, and 2022) using a supervised classification algorithm based on Support Vector Machines (SVMs). Our analysis revealed a significant expansion of urban areas (70%) across Kabul City between 2000 and 2022, particularly concentrated in Districts 5, 6, 7, 11, 12, 13, 15, 17, and 22. Urbanization likely contributes to groundwater depletion through increased population growth, reduced infiltration of precipitation, and potential overexploitation of groundwater resources. The CA-Markov model further predicts continued expansion in built-up areas over the next two decades (2030s and 2040s), potentially leading to water scarcity, land subsidence, and environmental degradation in Kabul City. The periodic assessment of urbanization dynamics and prediction of future trends are considered the novelty of this study. The accuracy of the generated LULC maps was assessed for each year (2000, 2005, 2010, 2015, and 2022), achieving overall accuracy values of 95%, 93.8%, 85%, 95.6%, and 93%, respectively. These findings provide a valuable foundation for the development of sustainable management strategies for Kabul’s surface water and groundwater resources, while also guiding future research efforts. Full article

In this study, the tribological properties of nanocomposites based on ultra-high molecular weight polyethylene (UHMWPE) filled with nano-CuO and 2-mercaptobenzothiazole (CuO/MBT) in mass ratios of 1:1 and 2:1 were investigated. In the supramolecular structure of UHMWPE nanocomposites, spherulites of several hundred micrometers in size are formed. The density of UHMWPE nanocomposites slightly increases relative to the pure polymer, reaching a maximum at 2 wt.% CuO/MBT in both ratios. The Shore D hardness and compressive stress of the UHMWPE nanocomposites showed an improvement of 5–6% and 23–35%, respectively. The wear resistance and coefficient of friction of UHMWPE nanocomposites were tested using a pin-on-disk configuration under dry friction conditions on #45 steel and on P320 sandpaper. It was shown that the wear rate of UHMWPE nanocomposites filled with 2 wt.% CuO/MBT decreased by ~3.2 times compared to the pure polymer, and the coefficient of friction remained at the level of the polymer matrix. Abrasive wear showed an improvement in UHMWPE nanocomposites filled with 1 wt.% CuO/MBT compared to the polymer matrix and other samples. The worn surfaces of the polymer composites after dry friction were examined by scanning electron microscopy and IR spectroscopy. The formation of secondary structures in the form of tribofilms that protect the material from wear was demonstrated. Due to this, the wear mechanism of UHMWPE nanocomposites is transformed from adhesive to fatigue wear. The developed materials, due to improved mechanical and tribological properties, can be used as parts in friction units of machines and equipment. Full article

The estimated ultimate recovery (EUR) of a single well must be predicted to achieve scale-effective shale gas extraction. Accurately forecasting EUR is difficult due to the impact of various geological, engineering, and production factors. Based on data from 200 wells in the Weiyuan block, this paper used Pearson correlation and mutual information to eliminate the factors with a high correlation among the 31 EUR influencing factors. The RF-RFE algorithm was then used to identify the six most important factors controlling the EUR of shale gas wells. XGBoost, RF, SVM, and MLR models were built and trained with the six dominating factors screened as features and EUR as labels. In this process, the model parameters were optimized, and finally the prediction accuracies of the models were compared. The results showed that the thickness of a high-quality reservoir was the dominating factor in geology; the high-quality reservoir length drilled, the fracturing fluid volume, the proppant volume, and the fluid volume per length were the dominating factors in engineering; and the 360−day flowback rate was the dominating factor in production. Compared to the SVM and MLR models, the XG Boost and the RF models based on integration better predicted EUR. The XGBoost model had a correlation coefficient of 0.9 between predicted and observed values, and its standard deviation was closest to the observed values’ standard deviation, making it the best model for EUR prediction among the four types of models. Identifying the dominating factors of shale gas single-well EUR can provide significant guidance for development practice, and using the optimized XGBoost model to forecast the shale gas single-well EUR provides a novel idea for predicting shale gas well production. Full article

In recent years the world has seen an increase in the popularity of farmer’s markets, short food supply chains and local food systems. This growth can be attributed to the public’s growing consciousness of the impracticality of the global food system, globalization’s waste of fossil fuels, the fear of food chemicals, and small farmers’ desire to directly sell their products, among other things. Although there are a wealth of farmer’s market surveys and research on this topic that has been conducted over the past decades around the world, scant data have been collected about farmer’s markets in the south of Spain. This study focuses on the organic farmer’s market in Granada (Spain) and consists of five surveys developed in 8 years which are analyzed to help better understand this market that was first established in the Spring of 2013. It will also consider research on farmer’s markets in Europe and beyond in order to compare the situation of the Granada market as well as bringing in some new ideas of how it can be improved. Full article

The myostatin (MSTN) gene also regulates the developmental balance of skeletal muscle after birth, and has long been linked to age-related muscle wasting. Many rodent studies have shown a correlation between MSTN and age-related diseases. It is unclear how MSTN and age-associated muscle loss in other animals are related. In this study, we utilized MSTN gene-edited bovine skeletal muscle cells to investigate the mechanisms relating to MSTN and muscle cell senescence. The expression of MSTN was higher in older individuals than in younger individuals. We obtained consecutively passaged senescent cells and performed senescence index assays and transcriptome sequencing. We found that senescence hallmarks and the senescence-associated secretory phenotype (SASP) were decreased in long-term-cultured myostatin inactivated (MT-KO) bovine skeletal muscle cells (bSMCs). Using cell signaling profiling, MSTN was shown to regulate the SASP, predominantly through the cycle GMP-AMP synthase-stimulator of antiviral genes (cGAS-STING) pathway. An in-depth investigation by chromatin immunoprecipitation (ChIP) analysis revealed that MSTN influenced three prime repair exonuclease 1 (TREX1) expression through the SMAD2/3 complex. The downregulation of MSTN contributed to the activation of the MSTN-SMAD2/3-TREX1 signaling axis, influencing the secretion of SASP, and consequently delaying the senescence of bSMCs. This study provided valuable new insight into the role of MSTN in cell senescence in large animals. Full article

Having a comprehensive knowledge of phase equilibrium is advantageous for industrial simulation and design of chemical processes. For further acquisition of primary data to facilitate the separation and purification of waste oil biodiesel systems, a liquid–liquid equilibrium (LLE) tank is deployed for the ternary system of waste oil biodiesel + methanol + glycerin, thereby enhancing the precision and efficiency of the process. The phase equilibrium system was constructed under the influence of atmospheric pressure at precise temperatures of 303.15 K, 313.15 K, and 323.15 K. The equilibrium components of each substance were analyzed by employing high-temperature gas chromatography, a sophisticated analytical method that enables the identification and quantification of individual components of a sample. Moreover, the ternary liquid–liquid equilibrium data were correlated by implementing the NRTL and UNIQUAC activity coefficient models. Subsequently, the binary interaction parameters of the ternary system were derived by conducting regression analysis. The experimental data demonstrated that the presence of lower methanol content in the system resulted in nearly immiscible biodiesel and glycerol phases, which ultimately facilitated the separation of biodiesel and glycerol. Conversely, with the increase in methanol content, the mutual solubility of biodiesel and glycerol was observed to increase gradually. The results showed that the calculated values of the NRTL and UNIQUAC models aligned well with the experimental values. The root-mean-square deviations of the NRTL and UNIQUAC models at 313.15 K were 2.76% and 3.56%, respectively. Full article

Peripheral nerve injuries (PNI) impact millions of individuals in the United States, prompting thousands of nerve repair procedures annually. Nerve conduits (NC) are commonly utilized to treat nerve injuries under 3 cm but larger gaps still pose a challenge for successful peripheral nerve regeneration (PNR) and functional recovery. This is partly attributed to the absence of bioactive agents such as stem cells or growth factors in FDA-approved conduits due to safety, harvesting, and reproducibility concerns. Therefore, curcumin, a bioactive phytochemical, has emerged as a promising alternative bioactive agent due to its ability to enhance PNR and overcome said challenges. However, its hydrophobicity and rapid degradation in aqueous solutions are considerable limitations. In this work, a nanoscale delivery platform with tannic acid (TA) and polyvinylpyrrolidone (PVP) was developed to encapsulate curcumin for increased colloidal and chemical stability. The curcumin nanoparticles (CurNPs) demonstrate significantly improved stability in water, reduced degradation rates, and controlled release kinetics when compared to free curcumin. Further, cell studies show that the CurNP is biocompatible when introduced to neuronal cells (SH-SY5Y), rat Schwann cells (RSC-S16), and murine macrophages (J774 A.1) at 5 μM, 5 μM, and 10 μM of curcumin, respectively. As a result of these improved physicochemical properties, confocal fluorescence microscopy revealed superior delivery of curcumin into these cells when in the form of CurNPs compared to its free form. A hydrogen peroxide-based oxidative stress study also demonstrated the CurNP’s potential to protect J774 A.1 cells against excessive oxidative stress. Overall, this study provides evidence for the suitability of CurNPs to be used as a bioactive agent in NC applications. Full article

Urban natural spaces provide important ecosystem services and a wide range of health- and well-being-related benefits for their visitors. They are also essential spaces for biodiversity protection and promotion in a world of rising urbanisation rates and worsening impacts of climate change. However, these spaces are often underutilised by urban residents. When they are utilised, this usage often leads to some level of environmental degradation and biodiversity loss. Hence, understanding how to promote both use and biodiversity levels in urban natural spaces is critical. While various reports have studied the broad factors associated with urban natural space use, the specific relationship between biodiversity and use remains to be explored. This paper uses a Systems Thinking approach to unpack the complex relationship between urban natural space use and biodiversity and to help guide the design and management of these spaces in a way that promotes both use and biodiversity. With data collected from a systematic literature review, a causal loop diagram (CLD) was constructed and analysed. The CLD construction and analysis highlighted various key factors that play an important role in relating urban natural space use and biodiversity. Among these is the role of individual and social perceptions and values in determining how biodiversity levels will affect usage, and vice versa. The results were applied to a case study: the Thamesmead regeneration project undertaken by the social housing association Peabody. We made recommendations regarding Peabody’s biodiversity and green infrastructure plans for Thamesmead, presenting new design and maintenance techniques and assessing various existing techniques mentioned in the documents. Through the CLD analysis, we uncovered various unintended consequences from common design and maintenance techniques and discuss these trade-offs and relationships. Full article

The charge/discharge operation of the prosumer’s energy storage and the energy interaction between prosumers and MGs are chaotic from the overall point of the MG’s operation. It causes considerable resource waste and reduces the overall benefits of the MG with multi-prosumers. Therefore, a game theory-based optimal scheduling strategy for the MG with multi-prosumers combined into a PRCO is proposed in this paper. According to the prosumers’ complementary characteristics of ES utilization and energy production, prosumers can be integrated into the PRCO to obtain energy reciprocity by sharing ES with an ordered charge–discharge operation. Meanwhile, to improve the collaboration of prosumers and the overall efficiency of the MG, a game scheduling model is established with the MG as the leader and the PRCO as the follower. The ToU price incentive policy is implemented in the MG to maximize the operational benefits and reduce the difference between the valley and peak load. Meanwhile, the PRCO responds to the price policy and implements an ordered charge–discharge strategy of ES to optimize each member’s energy scheduling strategy and minimize the total costs. The PRCO revenues are distributed to prosumers based on the Shapley value method. The uniqueness and existence of Stackelberg equilibrium in the game model are proved. The simulations of a community MG show that the ordered charge–discharge operation of ES is achieved and the overall benefits of the system are improved. Full article

Ermp1 is a putative metalloprotease from Schizosaccharomyces pombe and a member of the Fxna peptidases. Although their function is unknown, orthologous proteins from rats and humans have been associated with the maturation of ovarian follicles and increased ER stress. This study focuses on proposing the first prediction of PPI by comparison of the interologues between humans and yeasts, as well as the molecular docking and dynamics of the M28 domain of Ermp1 with possible target proteins. As results, 45 proteins are proposed that could interact with the metalloprotease. Most of these proteins are related to the transport of Ca²⁺ and the metabolism of amino acids and proteins. Docking and molecular dynamics suggest that the M28 domain of Ermp1 could hydrolyze leucine and methionine residues of Amk2, Ypt5 and Pex12. These results could support future experimental investigations of other Fxna peptidases, such as human ERMP1. Full article

In this paper, experimental results about the performance of a Takagi–Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration of the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. In this work, following the Takagi–Sugeno (TS) fuzzy control design methodology, the Parallel Distributed Compensation (PDC) approach is used in the design of the TSFC. The EV3BRS’s TS Fuzzy Model (TSFM) design comes from linearization of the nonlinear model around two operation points near the upright position of EV3BRS’s body. The Linear Matrix Inequality (LMI) approach was used to obtain the feedback gains for every local linear controller, guaranteeing, via a conservative stability condition, the global asymptotic stability of the overall fuzzy control system. The main goal of the control task consists of maintaining the EV3BRS’s body at its upright position. Measurement and control data from and to the EV3BRS are transferred via telecontrol and telemetry. The appropriate performance of the controller design is corroborated via experimentation. Full article

LOX-1, ORL-1, or lectin-like oxidized low-density lipoprotein receptor 1 is a transmembrane glycoprotein that binds and internalizes ox-LDL in foam cells. LOX-1 is the main receptor for oxidized low-density lipoproteins (ox-LDL). The LDL comes from food intake and circulates through the bloodstream. LOX-1 belongs to scavenger receptors (SR), which are associated with various cardiovascular diseases. The most important and severe of these is the formation of atherosclerotic plaques in the intimal layer of the endothelium. These plaques can evolve into complicated thrombi with the participation of fibroblasts, activated platelets, apoptotic muscle cells, and macrophages transformed into foam cells. This process causes changes in vascular endothelial homeostasis, leading to partial or total obstruction in the lumen of blood vessels. This obstruction can result in oxygen deprivation to the heart. Recently, LOX-1 has been involved in other pathologies, such as obesity and diabetes mellitus. However, the development of atherosclerosis has been the most relevant due to its relationship with cerebrovascular accidents and heart attacks. In this review, we will summarize findings related to the physiologic and pathophysiological processes of LOX-1 to support the detection, diagnosis, and prevention of those diseases. Full article

The paper presents a critical review and new accomplishments on the equivalence of the first-order displacement-based zigzag theories for laminated composite and sandwich structures. Zigzag theories (ZZTs) have widely spread among researchers over the last few decades thanks to their accuracy in predicting the response of multilayered composite and sandwich structures while retaining the simplicity of their underlying equivalent single-layer (ESL) theory. The displacement field consists of two main contributions: the global one, able to describe the overall structural behaviour, and the local layer-wise one that considers the transverse shear continuity at the layer interfaces that describe the “zigzag” displacement pattern typical of multilayered structures. In the framework of displacement-based linear ZZTs, various assumptions have been made on the local contribution, and different theories have been deduced. This paper aims to provide a unified formulation for first-order ZZTs, highlighting some common aspects and underlying equivalencies with existing formulations. The mathematical demonstrations and the numerical examples prove the equivalence of the approaches to characterising local zigzag enrichment. Finally, it is demonstrated that the kinematic assumptions are the discriminants of the ZZTs’ accuracy. Full article

Osteoporosis is a complex endocrine disease characterized by a decline in bone mass and microstructural integrity. It constitutes a major global health problem. Recent progress in the field of artificial intelligence (AI) has opened new avenues for the effective diagnosis of osteoporosis via radiographs. This review investigates the application of AI classification of osteoporosis in radiographs. A comprehensive exploration of electronic repositories (ClinicalTrials.gov, Web of Science, PubMed, MEDLINE) was carried out in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement (PRISMA). A collection of 31 articles was extracted from these repositories and their significant outcomes were consolidated and outlined. This encompassed insights into anatomical regions, the specific machine learning methods employed, the effectiveness in predicting BMD, and categorizing osteoporosis. Through analyzing the respective studies, we evaluated the effectiveness and limitations of AI osteoporosis classification in radiographs. The pooled reported accuracy, sensitivity, and specificity of osteoporosis classification ranges from 66.1% to 97.9%, 67.4% to 100.0%, and 60.0% to 97.5% respectively. This review underscores the potential of AI osteoporosis classification and offers valuable insights for future research endeavors, which should focus on addressing the challenges in technical and clinical integration to facilitate practical implementation of this technology. Full article

The current study presents a non-random, quantitative experimental investigation detailing the steps required to accredit a non-regulated test method (referred to as its own) under the ISO/IEC 17025:2017 standard and the criteria set by the Mexican Accreditation Entity (EMA). The focus is on the methodology employed to validate the test method, particularly emphasizing the precision of the measurement system, along with the total variation in and tolerance of its components. For the measurement analysis, repeatability and reproducibility (r&R) studies were conducted using a variance analysis method variant (ANOVA). This variant is highlighted for its ability to estimate deviations more accurately. Furthermore, the chosen model incorporates random effect measurements for all factors or components of system variation (operators, parts, interaction, and instrument). This approach demonstrates the reliability, accuracy, and precision of the proposed measurement system within the test method, leading to its subsequent accreditation under ISO/IEC 17025:2017 as a conformity assessment body. Full article

In this paper, we provide a blow-up criterion for the density-dependent incompressible magnetohydrodynamic system with zero viscosity. The proof uses the $L^p$-method and the Kato–Ponce inequalities in the harmonic analysis. The novelty of our work lies in the fact that we deal with the case in which the resistivity $\eta$ is positive. Full article

This paper presents an enhanced ground vehicle localization method designed to address the challenges associated with state estimation for autonomous vehicles operating in diverse environments. The focus is specifically on the precise localization of position and orientation in both local and global coordinate systems. The proposed approach integrates local estimates generated by existing visual–inertial odometry (VIO) methods into global position information obtained from the Global Navigation Satellite System (GNSS). This integration is achieved through optimizing fusion in a pose graph, ensuring precise local estimation and drift-free global position estimation. Considering the inherent complexities in autonomous driving scenarios, such as the potential failures of a visual–inertial navigation system (VINS) and restrictions on GNSS signals in urban canyons, leading to disruptions in localization outcomes, we introduce an adaptive fusion mechanism. This mechanism allows seamless switching between three modes: utilizing only VINS, using only GNSS, and normal fusion. The effectiveness of the proposed algorithm is demonstrated through rigorous testing in the Carla simulation environment and challenging UrbanNav scenarios. The evaluation includes both qualitative and quantitative analyses, revealing that the method exhibits robustness and accuracy. Full article

Mitochondrial DNA (mtDNA) exhibits distinct characteristics distinguishing it from the nuclear genome, necessitating specific analytical methods in genetic studies. This comprehensive review explores the complex role of mtDNA in a variety of genetic studies, including genome-wide, epigenome-wide, and phenome-wide association studies, with a focus on its implications for human traits and diseases. Here, we discuss the structure and gene-encoding properties of mtDNA, along with the influence of environmental factors and epigenetic modifications on its function and variability. Particularly significant are the challenges posed by mtDNA’s high mutation rate, heteroplasmy, and copy number variations, and their impact on disease susceptibility and population genetic analyses. The review also highlights recent advances in methodological approaches that enhance our understanding of mtDNA associations, advocating for refined genetic research techniques that accommodate its complexities. By providing a comprehensive overview of the intricacies of mtDNA, this paper underscores the need for an integrated approach to genetic studies that considers the unique properties of mitochondrial genetics. Our findings aim to inform future research and encourage the development of innovative methodologies to better interpret the broad implications of mtDNA in human health and disease. Full article

Plate heat exchangers are widely used in the Heating, Ventilation, and Air Conditioning (HVAC) field. Cross-corrugated triangular ducts are commonly employed in plate heat exchangers. Inserting baffles into the cross-corrugated triangular ducts can improve the heat transfer performance of the plate heat exchangers. This study focuses on intricate interdependencies among the flow channel apex angle, the trapezoidal baffle inclination angle, baffle position, and Reynolds number (Re) on heat transfer and pressure drop using response surface methodology (RSM) and computational fluid dynamic (CFD). To identify the factors that maximize the Nusselt number (Nu) and minimize friction factor (f), the RSM is used to design factors, conduct numerical studies, and establish regression equations. The results show that the apex angle, baffle angle, X-direction position, and Re have significantly affected Nu and f. Compared to a non-baffled channel with the same apex angle and Re conditions, the optimized channel enhances heat transfer by 1.54 times and has an almost identical pressure drop. The inclined baffle significantly enhances comprehensive performance at low Re. The synergistic effect of the heat transfer and pressure drop is most optimal when the apex angle of the flow channel is 90°, the trapezoidal baffle inclination angle is 52.5°, and the Re is 1000, with the baffle position at 0.625H in the X-direction. Full article