Oriented object detection (OOD) can precisely detect objects with arbitrary direction in remote sensing images (RSIs). Up to now, the two-stage OOD methods have attracted more attention because of their high detection accuracy. However, the two-stage methods only rely on the features of each proposal for object recognition, which leads to the misclassification problem because of the intra-class diversity, inter-class similarity and clutter backgrounds in RSIs. To address the above problem, an OOD model combining scene classification is proposed. Considering the fact that each foreground object has a strong contextual relationship with the scene of the RSI, a scene classification branch is added to the baseline OOD model, and the scene classification result of input RSI is used to exclude the impossible categories. To focus on the hard instances and enhance the consistency between classification and regression, a task-aligned focal loss (TFL) which combines the classification difficulty with the regression loss is proposed, and TFL assigns lager weights to the hard instances and optimizes the classification and regression branches simultaneously. The ablation study proves the effectiveness of scene classification branch, TFL and their combination. The comparisons with 15 and 14 OOD methods on the DOTA and DIOR-R datasets validate the superiority of our method. Full article

In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To address this issue, an adaptive PF-based tracking method (APF) with joint reverberation suppression is proposed. This method establishes the state space model under the Bayesian framework and implements it through particle filtering. To keep the weak target echoes, all the non-zero entries contained in the sparse matrix processed by the low-rank and sparsity decomposition (LRSD) are treated as the measurements. The prominent feature of this approach is introducing an adaptive measurement likelihood ratio (AMLR) into the posterior update step, which solves the problem of unstable tracking due to the strong fluctuation in the number of point measurements per frame. The proposed method is verified by four shallow water experimental datasets obtained by an active sonar with a uniform horizontal linear array. The results demonstrate that the tracking frame success ratio of the proposed method improved by over 14% compared with the conventional PF tracking method. Full article

Surface runoff is a major component of the hydrological cycle, and it is essential for supporting the ecosystem services provided by grassland and forest ecosystems. It is of practical importance to understand the mechanisms and the dynamic processes of runoff in a river’s basin, and in this study, we focused on the restored montane Pailugou Basin in the Qilian Mountains, Gansu Province, China, since its water status is extremely important for the large arid area and local economies therein. Our purpose was to determine the annual variation in the surface runoff in the Pailugou Basin because it is important to understand the influence of climate fluctuations on surface water resources and the economy of the basin. In addition, little is known about the annual variations in precipitation and runoff in this region of the world. Daily atmospheric precipitation, air temperature and runoff data from 2000 to 2019 were analyzed by the calculation of the uneven annual distribution of surface runoff, the calculation of the complete adjustment coefficient, and the vector accumulation expressed by the concentration degree. We also used the cumulative anomaly approach to determine the interannual variation trend of runoff, while the change trend was quantified by the sliding average method. Finally, we used the Mann–Kendall mutation test method and regression analysis to establish the time-series trend for precipitation and runoff and to determine the period of abrupt runoff changes. The results indicated concentrated and positive distributions of surface runoff on an annual basis, with a small degree of dispersion, and an explicit concentration of extreme flows. The relative variation ranges exhibited a decreasing trend, and the distribution of the surface runoff gradually was uniform over the year. The runoff was highest from July to September (85% of the annual total). We also determined that annual surface runoff in the basin fluctuated over the 20-year period but showed an overall increasing trend, increasing by 3.94 × 10⁵ m³, with an average increase rate of 0.42 × 10⁵ m³ every ten years. From 2005 to 2014, the annual runoff and the proportion of runoff in the flood season (July to September) to the annual runoff fluctuated greatly. The correlation between the runoff and precipitation was significant (r = 0.839, p < 0.05), whereas the correlation between air temperature and surface runoff was low (r = 0.421, p < 0.05). Full article

Bans on single-use plastic shopping bags (SUPBs) are a popular policy to tackle plastic pollution. However, their success has been evaluated solely based on reduced SUPBs consumption, ignoring the impacts of substitutes. This article addresses this gap by analyzing the Chilean plastic bag ban law. Results show a reduction of ~249 kilotons of SUPBs consumed and a change in the materiality of shopping bags (mainly toward paper), but also an increase of more than 50% of bin liners after the enactment of the ban. Despite some undesired effects, an improvement in the environmental performance of the bag market is obtained in fifteen of the eighteen categories studied. The environmental impacts are on average 38% lower than in the counterfactual scenario. This suggests that the law is being effective in protecting the environment. The strictness of the ban and its rapid enforcement were positive aspects of its design, but ignoring the end-of-life of the bags could be limiting its impact. To reduce the environmental impact of substitutes, it is recommended to create design guidelines for shopping bags and bin liners. Full article

This study explores the prediction of concrete compressive strength using machine learning models, aiming to overcome the time-consuming and complex nature of conventional methods. Four models—an artificial neural network (ANN), a multiple linear regression, a support vector machine, and a regression tree—are employed and compared for performance, using evaluation metrics such as mean absolute deviation, root mean square error, coefficient of correlation, and mean absolute percentage error. After preprocessing 1030 samples, the dataset is split into two subsets: 70% for training and 30% for testing. The ANN model, further divided into training, validation (15%), and testing (15%), outperforms others in accuracy and efficiency. This outcome streamlines compressive strength determination in the construction industry, saving time and simplifying the process. Full article

A rare case of an anomalous location of the orifice of the coronary artery was found in a 99-year-old male cadaver undergoing routine dissection. The presence of the right coronary artery (RCA), left coronary artery (LCA), and conus artery (conus branch) originating from the right Valsalva sinus are the characteristic findings of this case. Then, the LCA passed through the aorta and the pulmonary artery. The LCA and RCA branches were normal. These findings are useful for future surgical procedures, including cardiac catheterization. Full article

This paper addresses the critical need for precise thermal modeling in electronics, where temperature significantly impacts system reliability. We emphasize the necessity of accurate temperature measurement and uncertainty quantification in thermal imaging, a vital tool across multiple industries. Current mathematical models and uncertainty measures, such as Rényi and Shannon entropies, are inadequate for the detailed informational content required in thermal images. Our work introduces a novel entropy that effectively captures the informational content of thermal images by combining local and global data, surpassing existing metrics. Validated by rigorous experimentation, this method enhances thermal images’ reliability and information preservation. We also present two enhancement frameworks that integrate an optimized genetic algorithm and image fusion techniques, improving image quality by reducing artifacts and enhancing contrast. These advancements offer significant contributions to thermal imaging and uncertainty quantification, with broad applications in various sectors. Full article

Mild Cognitive Impairment (MCI) is a cognitive state frequently observed in older adults, characterized by significant alterations in memory, thinking, and reasoning abilities that extend beyond typical cognitive decline. It is worth noting that around 10–15% of individuals with MCI are projected to develop Alzheimer’s disease, effectively positioning MCI as an early stage of Alzheimer’s. In this study, a novel approach is presented involving the utilization of eXtreme Gradient Boosting to predict the onset of Alzheimer’s disease during the MCI stage. The methodology entails utilizing data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Through the analysis of longitudinal data, spanning from the baseline visit to the 12-month follow-up, a predictive model was constructed. The proposed model calculates, over a 36-month period, the likelihood of progression from MCI to Alzheimer’s disease, achieving an accuracy rate of 85%. To further enhance the precision of the model, this study implements feature selection using the Recursive Feature Elimination technique. Additionally, the Shapley method is employed to provide insights into the model’s decision-making process, thereby augmenting the transparency and interpretability of the predictions. Full article

The deformation and damage process of rocks is accompanied by crack extension and penetration. The rock strength criterion, as a macroscopic characterization of the rock strength microelement, is the basis for establishing the damage constitutive modeling of rock. Aiming at the problem of the Hoek–Brown (H–B) strength criterion having a large strength prediction value under high confining pressure, the H–B strength criterion is corrected by considering the influence of the initial cracks on the development of the rock strength, and its applicability is verified. Based on the damage theory, assuming that the rock strength microelement obeys the Weibull distribution and considering the influence of residual strength, the damage correction coefficient is introduced, and a thermal damage statistical constitutive model that can reflect the whole process of the development of initial cracks inside the rock is established. The degree of penetration up to the damage is established, and the method of determining the parameters of the model is given. The theoretical curves of the established model are compared and analyzed with the curves of a conventional triaxial compression test of rock samples, and the study shows that the statistical constitutive model of the thermal damage of rock, established based on the modified H–B strength criterion, can better simulate the stress–strain relationship of rock under a conventional triaxial test. It also verifies the reasonableness and applicability of the model, which is expected to provide a basis for the exploitation of deep resources and the safety assessment of underground engineering. Full article

This study investigates the potential of integrating multilayer animations and sophisticated shader technologies to enhance visitor social interactions within metaverse exhibition spaces. It is part of a broader initiative aimed at developing innovative digital museology strategies that foster social engagement through virtual reality (VR) experiences. The methodology adopted seeks to provide a more immersive and human-centric exploration of 3D digital environments by blending elements of physical spaces with the interactive dynamics common in video games. A virtual exhibition space themed around Mars was created as a testbed to facilitate social interactions among users, who navigate the environment via avatars. This digital space was developed using a specialized Unity template designed by the metaverse platform Spatial.io. Overcoming the programming constraints imposed by Spatial.io, which limits the use of external scripts for security and stability, posed a significant challenge. Nonetheless, by leveraging the ability to modify shader codes used for material creation and employing advanced animation techniques with layered effects, the authors of this work achieved dynamic material responses to lighting changes and initiated complex asset interactions beyond simple linear animations. Full article

Under extreme conditions such as high speed and heavy load, 18Cr2Ni4WA steel cannot meet the service requirements even after carburizing and quenching processes. In order to obtain better surface mechanical properties and tribological property, a hollow cathode ion source diffusion strengthening device was used to nitride the traditional carburizing and quenching samples. Unlike traditional ion carbonitriding technology, the low-temperature ion carbonitriding technology used in this article can increase the surface hardness of the material by 50% after 3 h of treatment, from the original 600 HV_0.1 to 900 HV_0.1, while the core hardness only decreases by less than 20%. The effect of post-ion carbonitriding treatment on mechanical properties and tribological properties of the carburized and quenched 18Cr2Ni4WA steel was investigated. Samples in different treatment are characterized using optical microscopy (OM), scanning electron microscopy (SEM), optimal SRV-4 high temperature tribotester, as well as Vickers hardness tester. Under two conditions of 6N light load and 60 N heavy load, compared with untreated samples, the wear rate of ion carbonitriding samples decreased by more than 99%, while the friction coefficient remained basically unchanged. Furthermore, the careful selection of ion nitrocarburizing and carburizing tempering temperatures in this study has been shown to significantly enhance surface hardness and wear resistance, while preserving the overall hardness of the carburized sample. The present study demonstrates the potential of ion carbonitriding technology as a viable post-treatment method for carburized gears. Full article

The analysis and simulation of water quality in distribution networks is a complex issue of great concern today. The analysis of the evolution of water age as a simple indicator of water quality in the network is of great interest in both the design and operation phases. Understanding the factors that have the strongest influence on water quality is key to developing adequate strategies aimed at preserving it. This paper first analyses the factors with the biggest influence on the tank’s water age to support the selection of the most appropriate configuration from the point of view of water quality during design phases. Then, the main considerations when modelling tanks following the different mixing models considered in Epanet are presented. Also, real tank behaviour is characterised through field measurements and Epanet simulations in order to determine the best-fitting mixing model. Full article

This study presents a data-driven model for identifying failure modes (FMs) and predicting the corresponding punching shear resistance of slab-column connections with shear reinforcement. An experimental database that contains 328 test results is used to determine nine input variables based on the punching shear mechanism. A comparison is conducted between three typical machine learning (ML) approaches: random forest (RF), light gradient boosting machine (LightGBM), extreme gradient boosting (XGBoost) and two hybrid optimized algorithms: grey wolf optimization (GWO) and whale optimization algorithm (WOA). It was found that the XGBoost classifier had the highest accuracy rate, precision, and recall values for FM identification. In testing, WOA-XGBoost has the best accuracy in predicting punching shear resistance, with R², MAE, and RMSE values of 0.9642, 0.087 MN, and 0.126 MN, respectively. However, a comparison between experimental values and calculated values derived from classical analytical methods clearly demonstrates that existing design codes need to be improved. Additionally, Shapley additive explanations (SHAP) were applied to explain the model’s predictions, with factors categorized according to their impact on failure modes and punching shear resistance. By modifying these parameters, punching resistance can be improved while reducing unpredictable failure. With the proposed hybrid algorithms, it is possible to determine the failure modes and the punching shear resistance of slabs during the preliminary stages of the construction. Full article

The author considers a nonlinear Caputo fractional-order delay differential equation (CFrDDE) with multiple variable delays. First, we study the existence and uniqueness of the solutions of the CFrDDE with multiple variable delays. Second, we obtain two new results on the Ulam–Hyers–Mittag–Leffler (UHML) stability of the same equation in a closed interval using the Picard operator, Chebyshev norm, Bielecki norm and the Banach contraction principle. Finally, we present three examples to show the applications of our results. Although there is an extensive literature on the Lyapunov, Ulam and Mittag–Leffler stability of fractional differential equations (FrDEs) with and without delays, to the best of our knowledge, there are very few works on the UHML stability of FrDEs containing a delay. Thereby, considering a CFrDDE containing multiple variable delays and obtaining new results on the existence and uniqueness of the solutions and UHML stability of this kind of CFrDDE are the important aims of this work. Full article

Investing in green hydrogen systems has become a global objective to achieve the net-zero emission goal. Therefore, it is seen as the primary force behind efforts to restructure the world’s energy, lessen our reliance on gas, attain carbon neutrality, and combat climate change. This paper proposes a power management for a net zero emission PV microgrid-based decentralized green hydrogen system. The hybrid microgrid combines a fuel cell, battery, PV, electrolyzer, and compressed hydrogen storage (CHSU) unit aimed at power sharing between the total components of the islanded DC microgrid and minimizing the equivalent hydrogen consumption (EHC) by the fuel cell and the battery. In order to minimize the EHC and maintain the battery SOC, an optimization-based approach known as the Equivalent Consumption Minimization Strategy (ECMS) is used. A rule-based management is used to manage the power consumed by the electrolyzer and the CHSU by the PV system in case of excess power. The battery is controlled by an inverse droop control to regulate the dc bus voltage and the output power of the PV system is maximized by the fuzzy logic controller-based MPPT. As the hybrid microgrid works in the islanded mode, a two-level hierarchical control is applied in order to generate the voltage and the frequency references. The suggested energy management approach establishes the operating point for each system component in order to enhance the system’s efficiency. It allows the hybrid system to use less hydrogen while managing energy more efficiently. Full article

Currently, more than 55 million people around the world suffer from dementia, and Alzheimer’s Disease and Related Dementias (ADRD) accounts for nearly 60–70% of all those cases. The spread of Alzheimer’s Disease (AD) pathology and progressive neurodegeneration in the hippocampus and cerebral cortex is strongly correlated with cognitive decline in AD patients; however, the molecular underpinning of ADRD’s causality is still unclear. Studies of postmortem AD brains and animal models of AD suggest that elevated endoplasmic reticulum (ER) stress may have a role in ADRD pathology through altered neurocellular homeostasis in brain regions associated with learning and memory. To study the ER stress-associated neurocellular response and its effects on neurocellular homeostasis and neurogenesis, we modeled an ER stress challenge using thapsigargin (TG), a specific inhibitor of sarco/endoplasmic reticulum Ca²⁺ ATPase (SERCA), in the induced pluripotent stem cell (iPSC)-derived neural stem cells (NSCs) of two individuals from our Mexican American Family Study (MAFS). High-content screening and transcriptomic analysis of the control and ER stress-challenged NSCs showed that the NSCs’ ER stress response resulted in a significant decline in NSC self-renewal and an increase in apoptosis and cellular oxidative stress. A total of 2300 genes were significantly (moderated t statistics FDR-corrected p-value ≤ 0.05 and fold change absolute ≥ 2.0) differentially expressed (DE). The pathway enrichment and gene network analysis of DE genes suggests that all three unfolded protein response (UPR) pathways, protein kinase RNA-like ER kinase (PERK), activating transcription factor-6 (ATF-6), and inositol-requiring enzyme-1 (IRE1), were significantly activated and cooperatively regulated the NSCs’ transcriptional response to ER stress. Our results show that IRE1/X-box binding protein 1 (XBP1) mediated transcriptional regulation of the E2F transcription factor 1 (E2F1) gene, and its downstream targets have a dominant role in inducing G1/S-phase cell cycle arrest in ER stress-challenged NSCs. The ER stress-challenged NSCs also showed the activation of C/EBP homologous protein (CHOP)-mediated apoptosis and the dysregulation of synaptic plasticity and neurotransmitter homeostasis-associated genes. Overall, our results suggest that the ER stress-associated attenuation of NSC self-renewal, increased apoptosis, and dysregulated synaptic plasticity and neurotransmitter homeostasis plausibly play a role in the causation of ADRD. Full article

Regarding organizational power, Salafism in France is a minority of dispersed groups emerging on the periphery of the Muslim French space. However, it can be regarded as a discursive force that has influenced significantly French discussions about Islam. Specifically, one of the most contentious positions in French political and intellectual discourse at the moment is Salafi vehement rejection of laïcité as a conspiracy against religion in general and Islam in particular. This article provides a close reading of three Salafi and neo-traditionalist discourses on secularism written by well-known theologians and intellectuals associated with this school of thought: Youssef Hindi, Kareem El Hidjaazi, and Aïssam Aït-Yahya. Investigative in nature, our aim is to comprehend the fundamental criticisms of French secularism and the rhetorical devices these Salafi and neo-traditionalist discourses have been using for the past ten years. Full article

(1) Background: With autistic children’s high pervasiveness of eating problems and inappropriate feeding behaviors by their caregivers, this study wanted to inspect the connection between caregivers’ pressure to eat and food neophobia in these children. (2) Methods: Cross-sectional overview of 160 guardians of kids aged 2 to 7 years. After one-on-one questioning by the researcher, the collected information on the socio-demographic characteristics of the children with autism, caregiver feeding behavior, and new food neophobia (FN) scores was entered into the Questionnaire Star system. (3) Results: The mean FN score was 25.56 ± 6.46. The caregiver’s pressure to eat positively related to children’s FN (β = 0.164 95% CI, 0.078, 2.163). In these children, we found a negative correlation between FN score and the frequency of vegetable intake (p ≤ 0.001), fruit intake (p ≤ 0.05), aquatic product intake (p ≤ 0.05), and dietary diversity score (p ≤ 0.01), and positively correlated with the frequency of snack intake (p ≤ 0.05). (4) Conclusions: Caregiver pressure to eat was positively associated with high levels of FN in Chinese kids with ASD, which in turn negatively impacted dietary quality. To improve eating habits, caregivers should reconsider their feeding strategies and avoid using forceful methods to ease food neophobia in these children. Full article

Point cloud-based detection focuses on land traffic, rarely marine, facing issues with ships: it struggles in bad weather due to reliance on adverse weather data and fails to detect ships effectively due to overlooking size and appearance differences. Addressing the above challenges, our work introduces point cloud data of marine scenarios under realistically simulated adverse weather conditions and a dedicated Ship Detector tailored for marine environments. To adapt to various maritime weather conditions, we simulate realistic rain and fog in collected marine scene point cloud data. Additionally, addressing the issue of losing geometric and height information during feature extraction for large objects, we propose a Ship Detector. It employs a dual-branch sparse convolution layer for extracting multi-scale 3D feature maps, effectively minimizing height information loss. Additionally, a multi-scale 2D convolution module is utilized, which encodes and decodes feature maps and directly employs 3D feature maps for target prediction. To reduce dependency on existing data and enhance model robustness, our training dataset includes simulated point cloud data representing adverse weather conditions. In maritime point cloud ship detection, our Ship Detector, compared to adjusted small object detectors, demonstrates the best performance. Full article

The relationship between epicardial adipose tissue (EAT) and atrial fibrillation (AF) has gained interest in recent years. The previous literature on the topic presents great heterogeneity, focusing especially on computed tomography imaging. The aim of the present study is to determine whether an increased volume of left atrial (LA) EAT evaluated at routine pre-procedural cardiac magnetic resonance imaging (MRI) relates to AF recurrences after catheter ablation. A total of 50 patients undergoing AF cryoballoon ablation and pre-procedural cardiac MRI allowing quantification of LA EAT were enrolled. In one patient, the segmentation of LA EAT could not be achieved. After a median follow-up of 16.0 months, AF recurrences occurred in 17 patients (34%). The absolute volume of EAT was not different in patients with and without AF recurrences (10.35 mL vs. 10.29 mL; p-value = 0.963), whereas the volume of EAT indexed on the LA volume (EATi) was lower, albeit non-statistically significant, in patients free from arrhythmias (12.77% vs. 14.06%; p-value = 0.467). The receiver operating characteristic curve testing the ability of LA EATi to predict AF recurrence after catheter ablation showed sub-optimal performance (AUC: 0.588). The finest identified cut-off of LA EATi was 10.65%, achieving a sensitivity of 0.5, a specificity of 0.82, a positive predictive value of 0.59 and a negative predictive value of 0.76. Patients with values of LA EATi lower than 10.65% showed greater survival, free from arrhythmias, than patients with values above this cut-off (84% vs. 48%; p-value = 0.04). In conclusion, EAT volume indexed on the LA volume evaluated at cardiac MRI emerges as a possible independent predictor of arrhythmia recurrence after AF cryoballoon ablation. Nevertheless, prospective studies are needed to confirm this finding and eventually sustain routine EAT evaluation in the management of patients undergoing AF catheter ablation. Full article

Dealing with and maintaining high-quality standards in the design and construction phases is challenging, especially for on-site construction. Issues like improper implementation of building components and poor communication can widen the gap between design specifications and actual conditions. To prevent this, particularly for energy-efficient buildings, it is vital to develop resilient, sustainable strategies. These should optimize resource use, minimize environmental impact, and enhance livability, contributing to carbon neutrality by 2050 and climate change mitigation. Traditional post-occupancy evaluations, which identify defects after construction, are impractical for addressing energy performance gaps. A new, real-time inspection approach is necessary throughout the construction process. This paper suggests an innovative guideline for prefabricated buildings, emphasizing digital ‘self-instruction’ and ‘self-inspection’. These procedures ensure activities impacting quality adhere to specific instructions, drawings, and 3D models, incorporating the relevant acceptance criteria to verify completion. This methodology, promoting alignment with planned energy-efficient features, is supported by BIM-based software and Augmented Reality (AR) tools, embodying Industry 4.0 principles. BIM (Building Information Modeling) and AR bridge the gap between virtual design and actual construction, improving stakeholder communication and enabling real-time monitoring and adjustments. This integration fosters accuracy and efficiency, which are key for energy-efficient and nearly zero-energy buildings, marking a shift towards a more precise, collaborative, and environmentally sensible construction industry. Full article

Reducing production costs, known as scaling, is a significant obstacle in the advancement of cultivated meat. The cultivation process hinges on several key components, e.g., cells, media, scaffolds, and bioreactors. This study demonstrates an innovative approach, departing from traditional stainless steel or glass bioreactors, by integrating food-grade plant-based scaffolds and thermoplastic film bioreactors. While thermoplastic films are commonly used for constructing fluidic systems, conventional welding methods are cost-prohibitive and lack rapid prototyping capabilities, thus inflating research and development expenses. The developed laser welding technique facilitates contamination-free and leakproof sealing of polyethylene films, enabling the efficient fabrication of macrofluidic systems with various designs and dimensions. By incorporating food-grade plant-based scaffolds, such as rice seeded with bovine mesenchymal stem cells, into these bioreactors, this study demonstrates sterile cell proliferation on scaffolds within macrofluidic systems. This approach not only reduces bioreactor prototyping and construction costs but also addresses the need for scalable solutions in both research and industrial settings. Integrating single-use bioreactors with minimal shear forces and incorporating macro carriers such as puffed rice may further enhance biomass production in a scaled-out model. The use of food-grade plant-based scaffolds aligns with sustainable practices in tissue engineering and cultured-meat production, emphasizing its suitability for diverse applications. Full article