Mica is a harmful substance in sand and occurs frequently. The application of super standard mica sand is a difficult problem in large-scale engineering. In this work, the effects of an interface modifier, mineral admixture, and a curing system on the properties of cement-based materials with super standard mica sand were studied. The strength of cement-based materials linearly decreases with the mica content in sand. When the mica content in sand exceeds 6%, the compressive strength of mortar and concrete at 28 d decreases by more than 22.3% and 33.5%, respectively. By adding the silane coupling agent (SCA) of 50% mica mass and curing in natural conditions, the compressive strength of mortar increases by 10.9%. The cement-based materials with the SCA are more suitable for curing in natural conditions, and the performance of the SCA will not be affected by adding appropriate amounts of mineral admixture. The drying shrinkage strain of the concrete, with the sand containing high mica content modified by SCA, is reduced by 10.5%, and the diffusion of chloride ions in concrete is reduced. The XRD results show that the addition of the interfacial agent does not change the hydration products. The MIP and SEM results show that the SCA can form a bridge structure between the hydration products and the mica, improve the bonding strength of the interface zone, and reduce the number of harmful pores. Full article

The emergence of illegal (gambling, pornography, and attraction) websites seriously threatens the security of society. Due to the concealment of illegal websites, it is difficult to obtain labeled data with high quantity. Meanwhile, most illegal websites usually disguise themselves to avoid detection; for example, some gambling websites may visually resemble gaming websites. However, existing methods ignore the means of camouflage in a single modality. To address the above problems, this paper proposes MEDAL, a multimodality-based effective data augmentation framework for illegal website identification. First, we established an illegal website identification framework based on tri-training that combines information from different modalities (including image, text, and HTML) while making full use of numerous unlabeled data. Then, we designed a multimodal mutual assistance module that is integrated with the tri-training framework to mitigate the introduction of error information resulting from an unbalanced single-modal classifier performance in the tri-training process. Finally, the experimental results on the self-developed dataset demonstrate the effectiveness of the proposed framework, performing well on accuracy, precision, recall, and F1 metrics. Full article

The retina, a tissue of the central nervous system, is vital for vision as its photoreceptors capture light and transform it into electrical signals, which are further processed before they are sent to the brain to be interpreted as images. The retina is unique in that it is continuously exposed to light and has the highest metabolic rate and demand for energy amongst all the tissues in the body. Consequently, the retina is very susceptible to oxidative stress. VDAC, a pore in the outer membrane of mitochondria, shuttles metabolites between mitochondria and the cytosol and normally protects cells from oxidative damage, but when a cell’s integrity is greatly compromised it initiates cell death. There are three isoforms of VDAC, and existing evidence indicates that all three are expressed in the retina. However, their precise localization and function in each cell type is unknown. It appears that most retinal cells express substantial amounts of VDAC2 and VDAC3, presumably to protect them from oxidative stress. Photoreceptors express VDAC2, HK2, and PKM2—key proteins in the Warburg pathway that also protect these cells. Consistent with its role in initiating cell death, VDAC is overexpressed in the retinal degenerative diseases retinitis pigmentosa, age related macular degeneration (AMD), and glaucoma. Treatment with antioxidants or inhibiting VDAC oligomerization reduced its expression and improved cell survival. Thus, VDAC may be a promising therapeutic candidate for the treatment of these diseases. Full article

The Advanced Encryption Standard (AES) is widely recognized as a robust cryptographic algorithm utilized to protect data integrity and confidentiality. When it comes to lightweight implementations of the algorithm, the literature mainly emphasizes area and power optimization, often overlooking considerations related to performance and security. This paper evaluates two of our previously proposed lightweight AES implementations using both profiled and non-profiled attacks. One is an unprotected implementation, and the other one is a protected version using Domain-Oriented Masking (DOM). The findings of this study indicate that the inclusion of DOM in the design enhances its resistance to attacks at the cost of doubling the area. Full article

Acute coronary thrombosis is a known, but rare, contributor to morbidity and mortality in patients with thermal and electrical injuries. The overall incidence of myocardial infarction among burn patients is 1%, with an in-hospital post-infarction mortality of approximately 67%, whereas the overall mortality rate of the general burn patient population is from 1.4% to 18%. As such, early detection and effective peri-operative management are essential to optimize patient outcomes. Here, we report the details of the management of an adult male patient with a 65% total body surface area severe thermal injury, who developed an ST-elevation myocardial infarction (STEMI) in the resuscitation period. The patient was found to have 100% occlusion of his left anterior descending coronary artery, for which prompt coronary artery stent placement with a drug-eluting stent (DES) was performed. Following stent placement, the patient required dual antiplatelet therapy. The ongoing dual antiplatelet therapy required the development of a detailed peri-operative protocol involving pooled platelets, packed red blood cells, desmopressin (DDAVP™) and intraoperative monitoring of the patient’s coagulation parameters with thromboelastography for three staged operative interventions to achieve complete debridement and skin grafting of his burn wounds. Full article

African swine fever (ASF) is a contagious viral disease affecting pigs and wild boars. It typically presents as a hemorrhagic fever but can also manifest in various forms, ranging from acute to asymptomatic. ASF has spread extensively globally, significantly impacting the swine industry. The complex and highly variable character of the ASFV genome makes vaccine development and disease surveillance extremely difficult. The overall trend in ASFV evolution is towards decreased virulence and increased transmissibility. Factors such as gene mutation, viral recombination, and the strain-specificity of virulence-associated genes facilitate viral variations. This review deeply discusses the influence of these factors on viral immune evasion, pathogenicity, and the ensuing complexities encountered in vaccine development, disease detection, and surveillance. The ultimate goal of this review is to thoroughly explore the genetic evolution patterns and variation mechanisms of ASFV, providing a theoretical foundation for advancement in vaccine and diagnostic technologies. Full article

The present paper investigates flaw strength distributions established using various flexural tests on batches of SiC bar test specimens, namely four-point bending as well as three-point bending tests with different span lengths. Flaw strength is provided by the elemental stress operating on the critical flaw at the fracture of a test specimen. Fracture-inducing flaws and their locations are identified using fractography. A single population of pores was found to dominate the fracture. The construction of diagrams of p-quantile vs. elemental strengths was aimed at assessing the Gaussian nature of flaw strengths. Then, empirical cumulative distributions of strengths were constructed using the normal distribution function. The Weibull distributions of strengths are then compared to the normal reference distributions. The parameters of the Weibull cumulative probability distributions are estimated using maximum likelihood and moment methods. The cumulative distributions of flexural strengths for the different bending tests are predicted from the flaw strength density function using the elemental strength model, and from the cumulative distribution of flexural strength using the Weibull function. Flaw strength distributions that include the weaker flaws that are potentially present in larger test pieces are extrapolated using the p-quantile diagrams. Implications are discussed regarding the pertinence of an intrinsically representative flaw strength distribution, considering failure predictions. Finally, the influence of the characteristics of fracture-inducing flaw populations expressed in terms of flaw strength interval, size, dispersion, heterogeneity, and reproducibility with volume change is examined. Full article

The automotive industries currently face challenges such as emission limits, traffic congestion, and limited parking, which have prompted shifts in consumer preferences and modern passenger vehicle requirements towards compact vehicles. However, given the inherent limited width of compact vehicles, the potential risk of vehicle rollover is greater than that of regular vehicles. This paper addresses the safety concerns associated with vehicle rollover, focusing on narrow tilting vehicles (NTVs). Quantifying stability involves numerical indicators such as the lateral load transfer ratio (LTR). Additionally, a unique approach is taken by applying ZMP (zero moment point), commonly used in the robotics field, as an indicator of vehicle stability. Effective roll control requires a detailed analysis of the vehicle’s characteristic model and the derivation of lateral and roll dynamics. The paper presents the detailed roll dynamics of an NTV with a MacPherson strut-type suspension. A stability-enhancing method is proposed using a cascade structure based on the internal robust position controller and outer roll stability controller, addressing challenges posed by disturbances. Experimental verification using Simscape Multibody and CarSim validates the dynamic model and controller’s effectiveness, ensuring the reliability of the proposed tilting control for NTVs in practical scenarios. Full article

Bayesian networks (BNs) are probabilistic graphical models that leverage Bayes’ theorem to portray dependencies and cause-and-effect relationships between variables. These networks have gained prominence in the field of health sciences, particularly in diagnostic processes, by allowing the integration of medical knowledge into models and addressing uncertainty in a probabilistic manner. Objectives: This review aims to provide an exhaustive overview of the current state of Bayesian networks in disease diagnosis and prognosis. Additionally, it seeks to introduce readers to the fundamental methodology of BNs, emphasising their versatility and applicability across varied medical domains. Employing a meticulous search strategy with MeSH descriptors in diverse scientific databases, we identified 190 relevant references. These were subjected to a rigorous analysis, resulting in the retention of 60 papers for in-depth review. The robustness of our approach minimised the risk of selection bias. Results: The selected studies encompass a wide range of medical areas, providing insights into the statistical methodology, implementation feasibility, and predictive accuracy of BNs, as evidenced by an average area under the curve (AUC) exceeding 75%. The comprehensive analysis underscores the adaptability and efficacy of Bayesian networks in diverse clinical scenarios. The majority of the examined studies demonstrate the potential of BNs as reliable adjuncts to clinical decision-making. The findings of this review affirm the role of Bayesian networks as accessible and versatile artificial intelligence tools in healthcare. They offer a viable solution to address complex medical challenges, facilitating timely and informed decision-making under conditions of uncertainty. The extensive exploration of Bayesian networks presented in this review highlights their significance and growing impact in the realm of disease diagnosis and prognosis. It underscores the need for further research and development to optimise their capabilities and broaden their applicability in addressing diverse and intricate healthcare challenges. Full article

Recently, the earth’s climate has changed considerably, leading to several hazards, including flash floods (FFs). This study aims to introduce an innovative approach to mapping and identifying FF exposure in the city of Tetouan, Morocco. To address this problem, the study uses different machine learning methods applied to remote sensing imagery within the Google Earth Engine (GEE) platform. To achieve this, the first phase of this study was to map land use and land cover (LULC) using Random Forest (RF), a Support Vector Machine (SVM), and Classification and Regression Trees (CART). By comparing the results of five composite methods (mode, maximum, minimum, mean, and median) based on Sentinel images, LULC was generated for each method. In the second phase, the precise LULC was used as a related factor to others (Stream Power Index (SPI), Topographic Position Index (TPI), Slope, Profile Curvature, Plan Curvature, Aspect, Elevation, and Topographic Wetness Index (TWI)). In addition to 2024 non-flood and flood points to predict and detect FF susceptibility, 70% of the dataset was used to train the model by comparing different algorithms (RF, SVM, Logistic Regression (LR), Multilayer Perceptron (MLP), and Naive Bayes (NB)); the rest of the dataset (30%) was used for evaluation. Model performance was evaluated by five-fold cross-validation to assess the model’s ability on new data using metrics such as precision, score, kappa index, recall, and the receiver operating characteristic (ROC) curve. In the third phase, the high FF susceptibility areas were analyzed for two-way validation with inundated areas generated from Sentinel-1 SAR imagery with coherent change detection (CDD). Finally, the validated inundation map was intersected with the LULC areas and population density for FF exposure and assessment. The initial results of this study in terms of LULC mapping showed that the most appropriate method in this research region is the use of an SVM trained on a mean composite. Similarly, the results of the FF susceptibility assessment showed that the RF algorithm performed best with an accuracy of 96%. In the final analysis, the FF exposure map showed that 2465 hectares were affected and 198,913 inhabitants were at risk. In conclusion, the proposed approach not only allows us to assess the impact of FF in this study area but also provides a versatile approach that can be applied in different regions around the world and can help decision-makers plan FF mitigation strategies. Full article

This study, utilizing high-throughput technologies and Machine Learning (ML), has identified gene biomarkers and molecular signatures in Inflammatory Bowel Disease (IBD). We could identify significant upregulated or downregulated genes in IBD patients by comparing gene expression levels in colonic specimens from 172 IBD patients and 22 healthy individuals using the GSE75214 microarray dataset. Our ML techniques and feature selection methods revealed six Differentially Expressed Gene (DEG) biomarkers (VWF, IL1RL1, DENND2B, MMP14, NAAA, and PANK1) with strong diagnostic potential for IBD. The Random Forest (RF) model demonstrated exceptional performance, with accuracy, F1-score, and AUC values exceeding 0.98. Our findings were rigorously validated with independent datasets (GSE36807 and GSE10616), further bolstering their credibility and showing favorable performance metrics (accuracy: 0.841, F1-score: 0.734, AUC: 0.887). Our functional annotation and pathway enrichment analysis provided insights into crucial pathways associated with these dysregulated genes. DENND2B and PANK1 were identified as novel IBD biomarkers, advancing our understanding of the disease. The validation in independent cohorts enhances the reliability of these findings and underscores their potential for early detection and personalized treatment of IBD. Further exploration of these genes is necessary to fully comprehend their roles in IBD pathogenesis and develop improved diagnostic tools and therapies. This study significantly contributes to IBD research with valuable insights, potentially greatly enhancing patient care. Full article

Traffic congestion caused by left-turning vehicles in a coordinated corridor is a multifaceted problem requiring tailored solutions. This study explores the impact of shared left-turn lanes within one-way couplets, particularly during peak hours, where high left-turn volumes, limited side street storage, and the overlapped green time between pedestrians and left-turners contribute to queue spillbacks, coordination interruption, and network congestion. The focus of this paper is on the solutions that can be easily analyzed by practitioners, here called “analyzable solutions”. This approach stands in contrast to solutions derived from “non-transparent” optimization tools, which do not allow for a clear assessment of the solution’s adequacy or the ability to predict its impact in real-world applications. This paper investigates the effects of employing two analyzable signal timing strategies: Lagging Pedestrian (LagPed) phasing and Left-Turn Progression (LTP) offsets. Using high-fidelity microsimulation, the authors evaluated different scenarios, assessing pedestrian delays, queue lengths, travel time index, area average travel time index, and environmental impacts such as Fuel Consumption (FC) and CO₂ emissions. The effectiveness of the proposed strategies was comprehensively evaluated against the base case scenario, demonstrating considerable improvements in various performance measures, including approximately a 5% reduction in FC and CO₂ emissions. Implementation of the LTP strategy alone yields substantial reductions in delays, the number of stops, the queue length for left-turning vehicles, travel times for all road users, and ultimately FC and CO₂ emissions. This study offers innovative approach to addressing the complex and multifaceted problem of left-turn-centered congestion in urban grid networks using efficient and down-to-earth analyzable solutions. Full article

The development of novel cathodic materials with tailored nanostructures is crucial for the advancement of electrochromic devices. In this study, we synthesized cobalt-doped titanium dioxide (Ti-Co) thin films using a facile hydrothermal method to investigate the effects of cobalt doping on their structural, morphological, and electrochromic properties. Comprehensive characterization techniques, including X-ray diffraction and Raman analysis, confirmed the highly crystalline nature of the Ti-Co thin films, with specific Raman bands indicating distinct modifications due to cobalt incorporation. The TiO₂ nanorods, optimally doped with cobalt (TC-3), demonstrated enhanced charge transport and mobility, significantly improving the electrochromic performance. Among the various compositions studied, the TC-3 sample exhibited superior lithium-ion accommodation, achieving an optical modulation of 73.6% and a high coloration efficiency of 81.50 cm²/C. It also demonstrated excellent electrochromic stability, maintaining performance for up to 5000 s of coloring/bleaching cycles. These results confirm the beneficial impact of cobalt doping on the structural and functional properties of the host material. Furthermore, the practical effectiveness of the TC-3 thin film was validated through the fabrication of an electrochromic device, which showed efficient coloration and bleaching capabilities. This comprehensive research enhances the understanding and functionality of Ti-Co nanorod architectures, highlighting their promising potential for advanced electrochromic applications. Full article

This study is based on a sample of 30 Sinitic languages spoken in the Hunan Province. Its first objective is to explore the types of dative markers, comparing the form of the dative with allative, passive, benefactive, and differential object markers in these languages. Five patterns are identified: (I) DAT = ALL (II) DAT = GIVE = OM ≠ PASS; (III) DAT = GIVE = OM = PASS; (VI) DAT = GIVE = PASS ≠ OM; (V) DAT = BEN. Then, we reveal three main possible grammaticalization pathways that motivate the five synchronic patterns: (a) Allative > Dative; (b) (TAKE >) GIVE > Dative; (c) Benefactive > Dative. It concerns two distinct developments for the second pathway. Based on the areal distribution of the various types of dative markers, we can observe how the dative markers are developed in Hunan Sinitic languages. Full article

Chronic inflammation drives the growth of colorectal cancer through the dysregulation of molecular pathways within the immune system. Infiltration of immune cells, such as macrophages, into tumoral regions results in the release of proinflammatory cytokines (IL-6; IL-17; TNF-α), fostering tumor proliferation, survival, and invasion. Tumors employ various mechanisms to evade immune surveillance, effectively ‘cloaking’ themselves from detection and subsequent attack. A comprehensive understanding of these intricate molecular interactions is paramount for advancing novel strategies aimed at modulating the immune response against cancer. Full article

The Modular Multilevel Converter (MMC) is a promising converter for medium-/high voltage applications due to its various features. The waveform quality could be enhanced further by expanding the number of generated voltage levels, which increases the number of submodules (SMs); however, this improvement enlarges the size and cost of the converter, posing a persistent challenge. Hence, there exists a trade-off between power quality and the size and complexity of the converter. To verify the performance of such a complex converter and to validate the effectiveness of the control system, especially in the absence of a physical system, Real-Time (RT) simulation becomes crucial. However, the large number of components of a MMC creates important numerical challenges and computational difficulties in RT simulation. This paper proposes a grid-connected MMC employing a Z Packed U-Cell converter as a SM to generate a higher number of voltage levels while minimizing the required number of SMs. The ZPUC-MMC is implemented on an FPGA-based RT simulation platform using Electric Hardware Solver to reduce computational burden and simulation time, while improving the accuracy of the obtained results. Conventional controllers of MMCs are applied to assess the effectiveness and robustness of the proposed system during steady-state and dynamic operations. Full article

In this paper, a unitary method for the solution of transient cavitating flow in viscoelastic pipes is proposed in the framework of the method of characteristics (MOC) and a Z-mirror numerical scheme (MOC-Z model). Assuming a standard form of the continuity equation allows the unified treatment of both viscoelasticity and cavitation. An extension of the MOC-Z is used for Courant numbers less than 1 to overcome a few cases with numerical instabilities. Four viscoelastic models were considered: a Kelvin–Voigt (KV) model without the instantaneous strain, and three generalised Kelvin–Voigt models with one, two, and three KV elements (GKV1, GKV2, and GKV3, respectively). The use of viscoelastic parameters of KV and GKV models calibrated for transient flow tests without cavitation allows good comparisons between experimental and numerical pressure versus time for transient tests with cavitation. Whereas for tests without cavitation, the mean absolute error (MAE) always decreases when the complexity of the model increases (from KV to GKV1, GKV2, and GKV3) for all the considered tests, this does not happen for tests with cavitation, probably because the decreasing capacity of parameter generalization for the increasing complexity of the model. In particular, in the examined cases, the KV model performs better than the GKV1 and the GKV3 models in three cases out of five, and the GKV2 model performs better than the GKV3 model in three cases out of five. Furthermore, the GKV2 model performs better than the KV model only in three cases out of five. Full article

Background: Pneumonia is a ubiquitous health condition with severe outcomes. The advancement of ultrasonography techniques allows its application in evaluating pulmonary diseases, providing safer and accessible bedside therapeutic decisions compared to chest X-ray and chest computed tomography (CT) scan. Because of its aforementioned benefits, we aimed to confirm the diagnostic accuracy of lung ultrasound (LUS) for pneumonia in adults. Methods: A systematic literature search was performed of Medline, Cochrane and Crossref, independently by two authors. The selection of studies proceeded based on specific inclusion and exclusion criteria without restrictions to particular study designs, language or publication dates and was followed by data extraction. The gold standard reference in the included studies was chest X-ray/CT scan or both. Results: Twenty-nine (29) studies containing 6702 participants were included in our meta-analysis. Pooled sensitivity, specificity and PPV were 92% (95% CI: 91–93%), 94% (95% CI: 94 to 95%) and 93% (95% CI: 89 to 96%), respectively. Pooled positive and negative likelihood ratios were 16 (95% CI: 14 to 19) and 0.08 (95% CI: 0.07 to 0.09). The area under the ROC curve of LUS was 0. 9712. Conclusions: LUS has high diagnostic accuracy in adult pneumonia. Its contribution could form an optimistic clue in future updates considering this condition. Full article

Octreotide is the first synthetic peptide hormone, consisting of eight amino acids, that mimics the activity of somatostatin, a natural hormone in the body. During the past decades, advanced instrumentation and crystallographic software have established X-Ray Powder Diffraction (XRPD) as a valuable tool for extracting structural information from biological macromolecules. The latter was demonstrated by the successful structural determination of octreotide at a remarkably high d-spacing resolution (1.87 Å) (PDB code: 6vc1). This study focuses on the response of octreotide to different humidity levels and temperatures, with a particular focus on the stability of the polycrystalline sample. XRPD measurements were accomplished employing an Anton Paar MHC-trans humidity-temperature chamber installed within a laboratory X’Pert Pro diffractometer (Malvern Panalytical). The chamber is employed to control and maintain precise humidity and temperature levels of samples during XRPD data collection. Pawley analysis of the collected data sets revealed that the octreotide polycrystalline sample is remarkably stable, and no structural transitions were observed. The compound retains its orthorhombic symmetry (space group: P2₁2₁2₁, a = 18.57744(4) Å, b = 30.17338(6) Å, c = 39.70590(9) Å, d ~ 2.35 Å). However, a characteristic structural evolution in terms of lattice parameters and volume of the unit cell is reported mainly upon controlled relative humidity variation. In addition, an improvement in the signal-to-noise ratio in the XRPD data under a cycle of dehydration/rehydration is reported. These results underline the importance of considering the impact of environmental factors, such as humidity and temperature, in the context of structure-based drug design, thereby contributing to the development of more effective and stable pharmaceutical products. Full article

Background: Abdominoperineal resection (APR)—the standard surgical procedure for low-lying rectal cancer (LRC)—leads to significant perineal defects, posing considerable reconstruction challenges that, in selected cases, necessitate the use of plastic surgery techniques (flaps). Purpose: To develop valuable decision algorithms for choosing the appropriate surgical plan for the reconstruction of perineal defects. Methods: Our study included 245 LRC cases treated using APR. Guided by the few available publications in the field, we have designed several personalized decisional algorithms for managing perineal defects considering the following factors: preoperative radiotherapy, intraoperative position, surgical technique, perineal defect volume, and quality of tissues and perforators. The algorithms have been improved continuously during the entire period of our study based on the immediate and remote outcomes. Results: In 239 patients following APR, the direct closing procedure was performed versus 6 cases in which we used various types of flaps for perineal reconstruction. Perineal incisional hernia occurred in 12 patients (5.02%) with direct perineal wound closure versus in none of those reconstructed using flaps. Conclusion: The reduced rate of postoperative complications suggests the efficiency of the proposed decisional algorithms; however, more extended studies are required to categorize them as evidence-based management guide tools. Full article

This study investigates the impacts of the Big Five personality traits and propensity to trust on the use and writing of online reviews. Additionally, this study examines how gender moderates these impacts. Results of a survey (n = 840) show that openness to experience and conscientiousness positively influence online review use, while openness to experience and extraversion positively influence online review writing. Moreover, gender moderates the impacts of extraversion, openness to experience, and agreeableness on online review writing, with no moderating effect observed for online review use. Our findings contribute to the electronic word-of-mouth (eWOM) literature and offer important practical insights for eWOM platforms. Full article

The soil response under the inherent cyclic loading conditions when dealing with offshore foundations can be considered by using contour plots. These plots are derived from several cyclic laboratory tests and characterize the general cyclic soil behaviour. In the design process with explicit numerical methods, such plots are needed in order to assess the soil behaviour under arbitrary loading conditions and hence estimate the cyclic foundation response. In the paper, excess pore pressure contour plots for a poorly graded medium sand are derived from numerous constant volume (CV) cyclic direct simple shear (DSS) tests and a new approach for parametrization of the plots is presented. Subsequently, the data are assessed regarding scaling for other sand soils, i.e., construction of contour plots with only a small number of test results by using the general trends observed. Full article