The research aimed to observe the influence of the storage conditions of silver colloidal solutions prepared by biological (green) and chemical methods on their long-term stability. Green methods for reducing and stabilizing silver nanoparticles (AgNPs) use natural substances. The rosemary leaf extract was used for AgNPs synthesis, and prepared nanoparticles were spherical (average size of 12 nm). In the chemical method, commercial chemicals (NaBH₄, TSC, PVP, and H₂O₂) were used, and two colloids were prepared; the first contained spherical nanoparticles with an average size of 8 nm, and the second triangular prisms with an average size of 35 nm. The prepared colloids were stored under four conditions: at room temperature in the light and the dark, and at a temperature of 5 °C (refrigerator) in the light and the dark. The results confirmed the influence of storage conditions on the stability of nanoparticles. Colloids stored at 5 °C in the dark show the best stability. However, differences in stability dependent on the shape of nanoparticles prepared by chemical method were also observed; triangular nanoparticles showed the least stability. Methods such as UV–vis spectrophotometry, TEM, and EDX were used to analyze the nanoparticles before and after storage. Full article

To investigate the ameliorative effects and mechanism of Lycium barbarum polysaccharide (LBP) on growth performance, oxidative stress, and lipid deposition in common carp (Cyprinus carpio) fed with high-fat diets, fish with an initial weight of 5.29 ± 0.12 g were divided into five experimental groups—including normal-fat diets, high-fat diets, and high-fat diets—supplemented with LBP (0.5, 1.0, and 2.0 g/kg) for 8 weeks. The results showed that high-fat diets resulted in significant decreases in final body weight, weight gain rate, and specific growth rate of fish, as well as causing a significant decrease in hepatic total antioxidant capacity, catalase, and glutathione peroxidase activities. These changes were accompanied by a significant decrease in lipase activity and ATP level and a significant increase in malondialdehyde content. The expression levels of lipid metabolism-related genes (acetyl coenzyme A carboxylase 1, stearoyl coenzyme A desaturase 1, fat synthase, peroxisome proliferator-activated receptor-γ, fructofuranose bisphosphatase, and glucose-6-phosphatase) were also markedly elevated by high-fat diets. Supplementation with 0.5–2.0 g/kg LBP in high-fat diets improved the reduced growth performance, increased hepatic total antioxidant enzymes, catalase, and glutathione peroxidase activities, and lowered malondialdehyde level in fish fed with high-fat diets. Additionally, dietary supplementation with LBP significantly downregulated hepatic gene expression levels of acetyl coenzyme A carboxylase 1, stearoyl coenzyme A desaturase 1, fat synthase, sterol regulatory element-binding protein 1, peroxisome proliferator-activated receptor-γ, fructofuranose bisphosphatase, and glucose-6-phosphatase. In conclusion, fish fed with high-fat diets demonstrated impaired growth performance, antioxidant capacity, and lipid metabolism, and dietary supplementation with 0.5–2.0 g/kg LBP ameliorated the impairments induced by high-fat diets. Full article

Background: Popular movement-based injury risk screens were shown to lack predictive precision, leading to interest in multifactorial models. Furthermore, there is a lack of research regarding injury risk assessment for those currently or planning to be recreationally active. This study aims to provide injury risk insights by analyzing multifactorial injury risk models and associated clinical measures in the U.S. population. Methods: Data related to injury, inflammatory markers, physical functioning, body composition, physical activity, and other variables from 21,033 respondents were extracted from NHANES. Odds ratios for self-reported injury were calculated for single predictors and risk models. Case–control and principal component analyses (PCA) were conducted to elucidate confounders and identify risk factor clusters, respectively. Receiver operating characteristic analysis was used to test the precision of a risk factor cluster to identify pain points and functional difficulties. Results: Sociodemographic, individual, and lifestyle factors were strongly associated with higher odds of injury. Increases in fibrinogen and C-reactive protein were significantly associated with all risk groups. Membership to the high-risk group (age over 40, obesity, no muscle-strengthening activities, sedentary lifestyle, and low back pain) predicted at least one functional difficulty with 67.4% sensitivity and 87.2% specificity. In the injury group, bone turnover markers were higher, yet confounded by age, and there was a significantly higher prevalence of self-reported osteoporosis compared to the control. In males, low testosterone was associated with injury, and high estradiol was associated with pain and functional difficulties. In females, high follicle-stimulating hormone was associated with functional difficulties. PCA revealed four high-risk profiles, with markers and activities showing distinct loadings. Conclusions: A comprehensive approach to injury risk assessment should consider the nexus of aging, lifestyle, and chronic disease to enhance tailored injury prevention strategies, fostering safe and effective physical activity participation and reducing the burden of musculoskeletal disorders. Full article

In recent years, there has been an increasing amount of research analyzing open government initiatives that enable access to the information held by public bodies, promoting accountability and the fight against corruption. As there are few studies on intermediate governments to date, this research focuses on this level of government in Spain, one of the most decentralized countries in the world. The autonomous communities in Spain manage over 35% of consolidated public spending and are responsible for providing most social services, including health, education, and social services. To achieve this goal, the perceptions of the seventeen heads of open government in Spain’s autonomous communities were collected through a questionnaire. This approach fills a research gap as individuals outside of public administration have made the previous assessments. By allowing for a comparison with the conclusions reached by prior research, this study contributes to the creation of new knowledge. The study’s results are consistent with previous research and suggest that the open government in Spain is positively regarded, not falling below the European or global averages, and has a promising future despite significant obstacles, such as a resistance to change. Transparency is the most developed aspect of open government, while citizen collaboration ranks last. The autonomous communities of the Basque Country, Aragon, Castile Leon, and Catalonia have been identified as the most advanced in terms of open government. The analysis did not reveal any gender-based differences in opinion. Still, it did show variations based on age, the size of the autonomous community, or membership to the most developed group. Therefore, it is evident that promoting open government in the autonomous communities of Spain should continue. Full article

Mitochondria are the energy factories of a cell, and depending on the metabolic requirements, the mitochondrial morphology, quantity, and membrane potential in a cell change. These changes are frequently assessed using commercially available probes. In this study, we tested the suitability of three commercially available probes—namely 5′,6,6′-tetrachloro-1,1′,3,3′-tetraethylbenzimidazolo-carbocyanine iodide (JC-1), MitoTracker Red CMX Rox (CMXRos), and tetramethylrhodamine methyl ester (TMRM)—for assessing the mitochondrial quantity, morphology, and membrane potential in living human mesoangioblasts in 3D with confocal laser scanning microscope (CLSM) and scanning disk confocal microscope (SDCM). Using CLSM, JC-1, and CMXRos—but not TMRM—uncovered considerable background and variation. Using SDCM, the background signal only remained apparent for the JC-1 monomer. Repetitive imaging of CMXRos and JC-1—but not TMRM—demonstrated a 1.5–2-fold variation in signal intensity between cells using CLSM. The use of SDCM drastically reduced this variation. The slope of the relative signal intensity upon repetitive imaging using CLSM was lowest for TMRM (−0.03) and highest for CMXRos (0.16). Upon repetitive imaging using SDCM, the slope varied from 0 (CMXRos) to a maximum of −0.27 (JC-1 C1). Conclusively, our data show that TMRM staining outperformed JC-1 and CMXRos dyes in a (repetitive) 3D analysis of the entire mitochondrial quantity, morphology, and membrane potential in living cells. Full article

This study aims to reveal the long-term station-based characteristics of precipitation in Istanbul, a mega city located on the continents of Europe and Asia, with complex topography and coastline along the Marmara and Black Seas. Using data from five different stations, three located in the European continent and two in the Asian continent, with measurement periods ranging from 72 to 93 years, wet and dry days have been identified, statistics on precipitation conditions during the warm and cold seasons have been generated, categorization based on precipitation intensities has been performed, and analyses have been conducted using extreme precipitation indices. At stations located in the northern part of the city, higher annual total precipitation has been observed compared to those in the south. A similar situation applies to the number of wet days. While during the cold season, the wet and dry day counts are nearly the same across all stations, this condition exhibits significant differences in favor of dry days during the warm season. Apart from dry conditions, “moderate” precipitation is the most frequently observed type across all stations. However, “extreme” events occur significantly more often (6%) during the warm season compared to the cold season (2%). Long-term anomalies in terms of annual precipitation totals have shown similarity between stations in the north and south, which has also been observed in longitudinally close stations. Despite the longer duration of the cold season and stronger temperature gradients, extreme rainfall events are more frequent during the warm season, primarily due to thunderstorm activity. While trend analyses revealed limited significant trends in precipitation intensity categories and extreme indices, the study highlights the importance of comprehensive examination of extreme rainfall events on both station-based and regional levels, shedding light on potential implications for regional climate change. Lastly, during the cold season, the inter-station correlation in terms of annual total precipitation amounts has been considerably higher compared to the warm season. Full article

E-leadership (i.e., remotely leading employees) has become a new normal in the public sector during the pandemic. However, practices of e-leadership differ due to legal, national and even organisational conditions. A deeper analysis is needed to understand what has happened with leadership practices in municipalities after the COVID-19 pandemic. The aim of the article is to reveal the main challenges of e-leadership in the post-pandemic municipal administrations and to identify e-leaders’ approaches (how they should act) in this context. A qualitative method of online focus groups was used to analyze specifics of the post-pandemic e-leadership in municipal administrations. The research was conducted in Lithuanian, Latvian and German municipal administrations. It was revealed that the use of remote work and e-leadership in municipal administrations after the pandemic heavily depends on the attitudes of supervisors toward work productivity. In addition, ensuring effective digital communication as well as managing social contacts and maintaining team spirit become challenges for e-leadership in municipalities after the pandemic also when remote work is reduced. Full article

Since about 1997, the realisation that the finite Reynolds number (FRN) effect needs to be carefully taken into account when assessing the behaviour of small-scale statistics came to the fore. The FRN effect can be analysed either in the real domain or in the spectral domain via the scale-by-scale energy budget equation or the transport equation for the energy spectrum. This analysis indicates that the inertial range (IR) is established only when the Taylor microscale Reynolds number $R{e}_{\lambda }$ is infinitely large, thus raising doubts about published power-law exponents at finite values of $R{e}_{\lambda }$, for either the second-order velocity structure function $\overline{{\left(\delta u\right)}^2}$ or the energy spectrum. Here, we focus on the transport equation of $\overline{{\left(\delta u\right)}^2}$ in decaying grid turbulence, which represents a close approximation to homogeneous isotropic turbulence. Regarding small-scale effects, the large-scale forcing term associated with streamwise advection decreases as $R{e}_{\lambda }$ increases and finally disappears when $R{e}_{\lambda }$ is sufficiently large. An approach based on the dual scaling of $\overline{{\left(\delta u\right)}^2}$, i.e., a scaling based on the Kolmogorov scales (when the separation r is small) and another based on the integral scales (when r is large), yields $\overline{{\left(\delta u\right)}^2}\sim r^{2/3}$ when $R{e}_{\lambda }$ is infinitely large. This approach also yields $\overline{{\left(\delta u\right)}^n}\sim r^{n/3}$ when $R{e}_{\lambda }$ is infinitely large. These results seem to be supported by the trend as $R{e}_{\lambda }$ increases according to the available experimental data. Overall, the results for decaying turbulence strongly suggest that a tendency towards the predictions of K41 cannot be dismissed at least at Reynolds numbers that are currently beyond the reach of experiments and direct numerical simulations. Full article

It is necessary to develop a health monitoring system (HMS) for complex systems to improve safety and reliability and prevent potential failures. Time-series signals are collected from multiple sensors installed on the equipment that can reflect the health condition of them. In this study, a novel interpretable recurrent variational state-space model (IRVSSM) is proposed for time-series modeling and anomaly detection. To be specific, the deterministic hidden state of a recursive neural network is used to capture the latent structure of sensor data, while the stochastic latent variables of a nonlinear deep state-space model capture the diversity of sensor data. Temporal dependencies are modeled through a nonlinear transition matrix; an automatic relevance determination network is introduced to selectively emphasize important sensor data. Experimental results demonstrate that the proposed algorithm effectively captures vital information within the sensor data and provides accurate and reliable fault diagnosis during the steady-state phase of liquid rocket engine operation. Full article

Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital image correlation (DIC) system. Numerical simulations were performed on egg-shaped, U-shaped, and straight-walled arched tunnels based on the mesoscopic parameters of the elliptical tunnel and following the principle of an equal cross-sectional area. The meso-crack evolution and stress conditions of the four types of tunnels were compared. The results show that (1) fractures around an elliptical tunnel were mainly distributed at the end of the long axis and mainly induce slabbing failure, and the failure mode is similar to a V-shaped notch; (2) strain localization is an important characteristic of rock fracturing, which forebodes the initiation, propagation, and coalescence paths of macro-cracks; and (3) the peak loads of tunnels with egg-shaped, U-shaped, and straight-walled arched cross-sections are 98.76%, 97.56%, and 90.57% that of an elliptical cross-section. The elliptical cross-section shows the optimal bearing capacity. Full article

Oil/air two-phase flow distribution in the bearings is the basis for bearing lubrication status identification and precise thermal analysis of the bearing. In order to understand the fluid behavior inside the under-race lubrication ball bearing and obtain an accurate oil volume fraction prediction model. A numerical study of ball bearing with under-race lubrication is carried out to study oil-gas two-phase distribution inside the bearing, and the influence of several parameters is quantified, like bearing rotating speed, oil flow rate, oil viscosity, and oil density. The results indicate that the oil fraction in the bearing cavity between the inner and outer ring shows a periodic distribution along the circumference direction, and the period is the same as the number of under-race oil supply holes. Oil distribution alone radial direction is affected by the outer-ring-guiding cage and centrifugal force, leading to oil accumulation near the outer ring. Different bearing running conditions and oil characteristics do not change the oil distribution trend alone in circumference and radial direction, but the difference ratio. Finally, based on the numerical simulation results, a formula for the average oil volume fraction prediction in the bearing ring cavity is constructed. Full article

The separation of rare earth ions (RE³⁺) from aqueous solutions poses a significant challenge due to their similar chemical and physical characteristics. This study presents a method for synthesizing hematite nanoparticles (Fe₂O₃ NPs) through the high-temperature phase transition of natural pyrite for adsorbing RE³⁺ from mine wastewater. The characteristics of Fe₂O₃ NPs were studied using XRD, SEM, BET, XPS, FTIR, and Zeta potential. The optimal condition for RE³⁺ adsorption by Fe₂O₃ NPs was determined to be at pH 6.0 with an adsorption time of 60 min. The maximum adsorption capacities of Fe₂O₃ NPs for La³⁺, Ce³⁺, Pr³⁺, Nd³⁺, Sm³⁺, Gd³⁺, Dy³⁺, and Y³⁺ were 12.80, 14.02, 14.67, 15.52, 17.66, 19.16, 19.94, and 11.82 mg·g⁻¹, respectively. The experimental data fitted well with the Langmuir isotherm and pseudo-second-order models, suggesting that the adsorption process was dominated by monolayer chemisorption. Thermodynamic analysis revealed the endothermic nature of the adsorption process. At room temperature, the adsorption of RE³⁺ in most cases (La³⁺, Ce³⁺, Pr³⁺, Nd³⁺, Sm³⁺, and Y³⁺) onto Fe₂O₃ NPs was non-spontaneous, except for the adsorption of Gd³⁺ and Dy³⁺, which was spontaneous. The higher separation selectivity of Fe₂O₃ NPs for Gd³⁺ and Dy³⁺ was confirmed by the separation factor. Moreover, Fe₂O₃ NPs exhibited excellent stability, with an RE³⁺ removal efficiency exceeding 94.70% after five adsorption–desorption cycles, demonstrating its potential for the recovery of RE³⁺ from mine wastewater. Full article

As technology evolves, more complex non-affine systems are created. These complex systems are hard to model, whereas most controllers require information on systems to be designed. This information is hard to obtain for systems with varying control directions. Therefore, this study introduces a novel data-driven estimator and controller tailored for single-input single-output non-affine discrete-time systems. This approach focuses on cases when the control direction varies over time and the mathematical model of the system is completely unknown. The estimator and controller are constructed using a Multiple-input Fuzzy Rules Emulated Network framework. The weight vectors are updated through the gradient descent optimization method, which employs a unique cost function that multiplies the error by a hyperbolic tangent. The stability analyses demonstrate that both the estimator and controller converge to uniformly ultimately bounded (UUB) functions of Lyapunov. To validate the results, we show experimental tests of force control that were executed on the z-axis of a drive-controlled 3D scanning robot. This system has a varying control direction, and we also provide comparison results with a state-of-the-art controller. The results show a mean absolute percentage tracking error smaller than one percent on the steady state and the expected variation in the system’s control direction. Full article

Black trumpet (Craterellus cornucopioides) is a mushroom present in many countries but underestimated. The aim of this publication is to present the latest state of knowledge about the chemical composition and bioactivity of C. cornucopioides and the possibility of its application in food. According to researchers, black trumpet is very rich in nutritional compounds, including unsaturated fatty acids (mainly oleic and linoleic acids), β-glucans, minerals, and vitamins as well as polyphenols and tannins. It also contains compounds influencing the sensory properties, like free amino acids and nucleotides as well as sugars and polyols, mainly mannitol. Many of the described components show high nutritional and bioactive properties. Therefore, C. cornucopioides shows antioxidant activity and immunostimulating, anti-inflammatory, and anticancer effects as well as antibacterial, antifungal, antiviral, and antihyperglycemic effects. This makes black trumpet, also called horn of plenty, a mushroom with great potential for use both in medicine and directly in food. So far, black trumpet is not widely used in food, especially processed food. There are only a few studies on the use of dried black trumpet in sausages, but there is great potential for its use in food. Full article

Geogenic arsenic (As)-rich groundwater poses a significant environmental challenge worldwide, yet our understanding of the interplay between dissolved organic matter (DOM) transformation and arsenic mobilization during microbial sulfate reduction remains limited. This study involved microcosm experiments using As-rich aquifer sediments from the Singe Tsangpo River basin (STR) and Jianghan Plain (JHP), respectively. The findings revealed that microbial sulfate reduction remarkably increased arsenic mobilization in both STR and JHP sediments compared to that in unamended sediments. Moreover, the mobilization of As during microbial sulfate reduction coincided with increases in the fluorescence intensity of two humic-like substances, C2 and C3 (R = 0.87/0.87 and R = 0.73/0.66 in the STR and JHP sediments, respectively; p < 0.05), suggesting competitive desorption between DOM and As during incubation. Moreover, the transformations in the DOM molecular characteristics showed significant increases in CHOS molecular and low-O/C-value molecular intensities corresponding to the enhancement of microbial sulfate reduction and the possible occurrence of methanogenesis processes, which suggests a substantial bioproduction contribution to DOM components that is conducive to As mobilization during the microbial sulfate reduction. The present results thus provide new insights into the co-evolution between As mobilization and DOM transformations in alluvial aquifer systems under strong microbial sulfate reduction conditions. Full article

Brain tumors necessitate swift detection and classification for optimal patient outcomes. Deep learning has been extensively utilized to recognize complex tumor patterns in magnetic resonance imaging (MRI) images, aiding in tumor diagnosis, treatment, and prognostication. However, model complexity and limited generalizability with unfamiliar data hinder appropriate clinical integration. The objective of this study is to develop a clean-energy cloud-based deep learning platform to classify brain tumors. Three datasets of a total of 2611 axial MRI images were used to train our multi-layer convolutional neural network (CNN). Our platform automatically optimized every transfer learning and data augmentation feature combination to provide the highest predictive accuracy for our classification task. Our proposed system identified and classified brain tumors successfully and efficiently with an overall precision value of 96.8% [95% CI; 93.8–97.6]. Using clean energy supercomputing resources and cloud platforms cut our workflow to 103 min, $0 in total cost, and a negligible carbon footprint (0.0014 kg eq CO₂). By leveraging automated optimized learning, we developed a cost-effective deep learning (DL) platform that accurately classified brain tumors from axial MRI images of different levels. Although studies have identified machine learning tools to overcome these obstacles, only some are cost-effective, generalizable, and usable regardless of experience. Full article

Sarcoidosis is a multisystem granulomatous disease of an unknown aetiology. It can exist in many organs. Pulmonary and intrathoracic lymph nodes are most commonly involved. Lung sarcoidosis is uncommon in Asia. However, due to the large population of our country and the development of bronchoscopy, percutaneous lung puncture, and other medical technologies, the number of pulmonary sarcoidosis patients is on the rise. Pulmonary sarcoidosis patients have no obvious symptoms in the early stage, and the clinical manifestations in the later stage may vary from person to person. Eventually, the disease progresses to life-threatening pulmonary fibrosis. Therefore, patients with pulmonary sarcoidosis should receive a timely diagnosis. In recent years, the imaging features and serologic biomarkers of pulmonary sarcoidosis have been continuously studied. The diagnostic value of imaging and serologic biomarkers for pulmonary sarcoidosis is summarized below. Full article

Surgical aortic valve replacement (SAVR) with a biological heart valve prosthesis (BHV) is often used as a treatment in elderly patients with symptomatic aortic valve disease. This age group is also at risk for the development of dementia in the years following SAVR. The research question is “what are the predictors for the development of dementia?”. In 1500 patients undergoing SAVR with or without an associated procedure, preoperative (demographic, cardiac and non-cardiac comorbid conditions), perioperative (associated procedures, cross-clamp and cardiopulmonary bypass time) and postoperative 30-day adverse events (bleeding, thromboembolism, heart failure, conduction defects, arrhythmias, delirium, renal and pulmonary complications) were investigated for their effect on the occurrence of dementia by univariate analyses. Significant factors were entered in a multivariate analysis. The sum of the individual follow-up of the patients was 10,182 patient-years, with a mean follow-up of 6.8 years. Data for the development of dementia could be obtained in 1233 of the 1406 patients who left the hospital alive. Dementia during long-term follow-up developed in 216/1233 (17.2%) of the patients at 70 ± 37 months. Development of dementia reduced the mean survival from 123 (119–128) to 109 (102–116) months (p < 0.001). Postoperative delirium was the dominant predictor (OR = 3.55 with a 95%CI of 2.41–4.93; p < 0.00), followed by age > 80 years (2.38; 1.78–3.18; p < 0.001); preoperative atrial fibrillation (1.47; 1.07–2.01; p = 0.018); cardiopulmonary bypass time > 120 min (1.34; 1.02–1.78; p = 0.039) and postoperative thromboembolism (1.94; 1.02–3.70; p = 0.044). Postoperative delirium, as a marker for poor condition, and an age of 80 or more were the dominant predictors. Full article

This article examines the emergence of new representations of Byzantium in early Arabic literature, with a focus on the Sīra, the biography of the Prophet Muḥammad. This historical investigation leads to a dual conclusions that the Arab perception of Byzantium not only forged an “imaginary Byzantium” but also marked the emergence of Arab self-consciousness. This process significantly influenced the Arab historical and cultural narratives, framing them within the context of the Arabic identity that emerged in late antiquity. Nevertheless, this relationship between the early Islamic community and Byzantium does little to confirm accurate knowledge about Byzantium, rendering the emerging representations as not truly reflective of “reality”, but rather presenting us with an “imaginary Byzantium”. This applies whether related to events in the 1st/7th century or the transition from oral to written texts during the 2nd/8th and 3rd/9th centuries. Furthermore, these representations reveal more about the creators of this imaginary than the other itself, shedding light on the motives of early Muslim writers who used the Sīra as a vehicle for these imaginaries. Ultimately, the article identifies, through the textual analysis and historical contextualization of Sīra, two narrative layers therein that are related to the imaginary Byzantium. The first layer reflected a pervasive fear of Byzantium, while the second layer represented an attitude of challenge and rivalry. Full article

Myocardial remodeling is developed by increased stress in acute or chronic pathophysiologies. Stressed heart morphology (SHM) is a new description representing basal septal hypertrophy (BSH) caused by emotional stress and chronic stress due to increased afterload in hypertension. Acute stress cardiomyopathy (ASC) and hypertension could be together in clinical practice. Therefore, there are some geometric and functional aspects regarding this specific location, septal base under acute and chronic stress stimuli. The findings by our and the other research groups support that hypertension-mediated myocardial involvement could be pre-existed in ASC cases. Beyond a frequently seen predominant base, hyperkinetic tissue response is detected in both hypertension and ASC. Furthermore, hypertension is the responsible factor in recurrent ASC. The most supportive prospective finding is BSH in which a hypercontractile base takes a longer time to exist morphologically than an acutely developed syndrome under both physiologic exercise and pressure overload by transaortic binding in small animals using microimaging. However, cardiac decompensation with apical ballooning could mask the possible underlying hypertensive disease. In fact, enough time for the assessment of previous hypertension history or segmental analysis could not be provided in an emergency unit, since ASC is accepted as an acute coronary syndrome during an acute episode. Additional supportive findings for SHM are increased stress scores in hypertensive BSH and the existence of similar tissue aspects in excessive sympathetic overdrive like pheochromocytoma which could result in both hypertensive disease and ASC. Exercise hypertension as the typical form of blood pressure variability is the sum of physiologic exercise and pathologic increased blood pressure and results in increased mortality. Hypertension is not rare in patients with a high stress score and leads to repetitive attacks in ASC supporting the important role of an emotional component as well as the potential danger due to multiple stressors at the same time. In the current review, the impact of multiple stressors on segmental or global myocardial remodeling and the hazardous potential of multiple stressors at the same time are discussed. As a result, incidentally determined segmental remodeling could be recalled in patients with multiple stressors and contribute to the early and combined management of both hypertension and chronic stress in the prevention of global remodeling and heart failure. Full article

Steel-fiber reinforced polymer (FRP) composite bars (SFCBs) can enhance the controllability of damage in concrete structures; thus, studying the interfacial bonding between them is fundamental and a prerequisite for achieving deformation coordination and collaboration. However, research on the interfacial bonding performance between SFCBs and concrete remains inadequate. This study conducted central pullout tests on SFCB-concrete specimens with different concrete strengths (C30, C50, and C70), bar diameters (12, 16 and 20 mm), and hoop reinforcement constraints, analyzing variations in failure modes, bond-slip curves, bond strength, etc. Additionally, finite element simulations were performed using ABAQUS software to further validate the bonding mechanism of SFCB-concrete. The results showed that the failure mode of the specimens was related to the confinement effect on the bars. Insufficient concrete cover and lack of hoop restraint led to splitting failure, whereas pullout failure occurred otherwise. For the specimens with pullout failure, the interfacial damage between the SFCB and concrete was mainly caused by the surface fibers wear of the bar and the shear of the concrete lugs, which indicated that the bond of the SFCB-concrete interface consisted mainly of mechanical interlocking forces. In addition, the variation of concrete strength as well as bar diameter did not affect the bond-slip relationship of SFCB-concrete. However, the bond strength of SFCB-concrete increased with the increase of concrete strength. For example, compared with C30 concrete, when the concrete strength was increased to C70, the bond strength of the specimens under the same conditions was increased to 50–101.6%. In contrast, the bond strength of the specimens decreased by 13.29–28.71% when the bar diameter was increased from 12 to 14 mm. These discoveries serve as valuable references for the implementation of sustainable SFCB-reinforced concrete structures. Full article

Datasets used in AI applications for human health require careful selection. In healthcare, machine learning (ML) models are fine-tuned to reduce errors, and our study focuses on minimizing errors by generating code snippets for cost-sensitive learning using water potability datasets. Water potability ensures safe drinking water through various scientific methods, with our approach using ML algorithms for prediction. We preprocess data with ChatGPT-generated code snippets and aim to demonstrate how zero-shot learning prompts in ChatGPT can produce reliable code snippets that cater to cost-sensitive learning. Our dataset is sourced from Kaggle. We compare model performance metrics of logistic regressors and gradient boosting classifiers without additional code fine-tuning to check the accuracy. Other classifier performance metrics are compared with results of the top 5 code authors on the Kaggle scoreboard. Cost-sensitive learning is crucial in domains like healthcare to prevent misclassifications with serious consequences, such as type II errors in water potability assessment. Full article