Very little is known on high mountain tropical lakes of South America. Thus, the main motivation of this research was obtaining base bathymetric data of 119 tropical lakes of the Cajas National Park (CNP), Ecuador, that could be used in future geomorphological studies. Eleven interpolation methods were applied with the intention of selecting the best one for processing the scattered observations that were collected with a low-cost fishing echo-sounder. A split-sample (SS) test was used and repeated several times considering different proportions of available observations, selected randomly, for training of the interpolation methods and accuracy evaluation of the respective products. This accuracy was assessed through the use of empirical exceedance probability distributions of the mean absolute error (MAE). A single best interpolation method could not be identified. Instead, the study suggested six better-performing methods, including the complex methods Kriging (ordinary), minimum curvature (spline), multiquadric, and TIN with linear interpolation but also the much simpler methods natural neighbour and nearest neighbour. A sensitivity analysis (SA), considering several data error magnitudes, confirmed this. This advocated that sophisticated interpolation methods do not always produce the best products as geomorphological characteristics of the study site(s) together with observation data characteristics are likely to play important roles in their performance. As such, this type of assessment should be carried out in any terrestrial mapping of bathymetry that is based on the interpolation of scattered observations. Upon the analysis of the relative hypsometric curves of the 119 study lakes, they were classified into three average form categories: convex, concave, and mixed. The separated accuracy analysis of these three groups of lakes did not help in identifying a single best method. Finally, the interpolated bathymetries of 114 of the study lakes were incorporated into the best DEM of the study site by equalising their elevation reference systems. It is believed that the resulting enhanced DEM could be a very useful tool for a more appropriate management of these very beautiful but fragile high mountain tropical lakes. Full article

Dental anatomy education is traditionally structured into theoretical and practical modules to foster both cognitive and psychomotor development. The theoretical module typically involves didactic lectures where educators elucidate dental structures using visual aids. In contrast, practical modules utilize three-dimensional illustrations, extracted and plastic teeth, and tooth carving exercises on wax or soap blocks, chosen for their cost, ease of handling, and fidelity in replication. However, the efficacy of these traditional methods is increasingly questioned. The criticism in this concern is that oversized carving materials may distort students’ understanding of anatomical proportions, potentially affecting the development of necessary skills for clinical practice. Lecture-driven instruction, on the other hand, is also criticized for its limitations in fostering interactive learning, resulting in a gap between pre-clinical instruction and practical patient care. In this study, we review the various educational strategies that have emerged to enhance traditional dental anatomy pedagogy by describing the effectiveness of conventional didactic lectures, wax carving exercises, the use of real and artificial teeth, the flipped classroom model, and e-learning tools. Our review aims to assess each method’s contribution to improving clinical applicability and educational outcomes in dental anatomy, with a focus on developing pedagogical frameworks that align with contemporary educational needs and the evolving landscape of dental practice. We suggest that the optimal approach for teaching tooth morphology would be to integrate the digital benefits of the flipped classroom model with the practical, hands-on experience of using extracted human teeth. To address the challenges presented by this integration, the creation and standardization of three-dimensional tooth morphology educational tools, complemented with concise instructional videos for a flipped classroom setting, appears to be a highly effective strategy. Full article

Medical advocacy has continued to significantly impact quality of life and survivorship outcomes among Latina breast cancer survivors in the United States. However, little is known about the unique experiences of Latina survivors, including the perceived value, process, and context in which they practice medical advocacy. To help address this gap, we conducted a qualitative, secondary analysis of semi-structured focus groups with 18 Latina breast cancer survivors from Chicago, Illinois. Eligible women had to self-identify as (1) female, (2) Latina, (3) 18 years or older, and (4) having a breast cancer diagnosis 5 years ago or more. In total, 61% of participants were 50–59 years old, 83% were born in Mexico, and 100% spoke Spanish. The three emergent themes from the focus groups were (1) the cultural need for Latina advocates and support groups; (2) the process and experiences of becoming a community advocate within Latine culture; and (3) the cultural contexts for advocacy by Latina breast cancer survivors. Latina survivor advocates share strengths of receiving ongoing health education, peer support, and access to resources when being linked to a support group furthering their exposure to role models, increasing their awareness of opportunities in medical advocacy, and providing an entry to participate in medical advocacy. Full article

A cascaded pseudo-potential lattice Boltzmann model and refilling algorithms for moving boundary treatment were used to simulate the large density ratio cavitating flow in a two-dimensional nozzle with the periodic motion of the needle valve. The relationships between density variation at the cavitation zone, the evolution of force acting on the lower boundary of the sack wall region, and the surface of the needle valve with time under different needle valve motion frequencies were obtained. The results indicate that the inception and evolution of cavitation mainly exist in the vicinity of the lower boundary of the sack wall region. The density at cavitation decreases by approximately three orders of magnitude, while the force on the lower boundary of the sack wall region decreases by about one order of magnitude. Since cavitation does not exist in the vicinity of the needle valve, the forces are mainly influenced by the periodic motion of the needle valve and do not change significantly. Changes in the frequency of needle valve motion affect the time taken for cavitation evolution to reach a relatively steady state but do not significantly affect the forces acting on the different components. Full article

This study explores the effect of internal gas pressure (P) on closed-cell natural rubber (NR) foams. Three key factors are analyzed using a 3D model during uniaxial compression: (1) the initial gas pressure (P₀ = 1, 2, and 3 atm) inside the cells, (2) different cell sizes (D = 0.1, 0.2, 0.3, and 0.4 mm in diameter), and (3) the presence of defects (holes in the cell walls) in terms of their sizes (d = 0.07 to 0.1 mm). The findings reveal a negative relationship between the initial gas pressure and the relative internal gas pressure (α = P/P₀) and a direct correlation with stress during compression. For instance, a change from 1 to 3 atm of the initial internal gas pressure results in a 158% decrease in α with only a 3% increase in stress. Larger cell sizes contribute to higher α but lower stress levels during compression. Changing the cell size from 0.1 to 0.4 mm generates a 27% increase in α but a 45% drop in stress. An analysis of hole sizes (cell connection) indicates that larger holes result in higher relative internal gas pressure, while smaller holes lead to higher stress levels because of more flow restriction. For example, increasing the hole size from 0.07 to 0.1 mm leads to an 8% higher α but a 32% stress reduction. These findings highlight the significant effect of the internal gas pressure inside the cells in determining the mechanical properties of rubber foams, which are generally neglected. The results also provide useful insights for better material design and different industrial applications. This study also generates predictive models to understand the relationships between stress, strain, initial gas pressure, cell size, and defects (holes/connections), enabling the production of tailor-made rubber foams by controlling their mechanical behavior. Full article

We comparatively evaluated the antioxidant properties of key triterpenes from Centella asiatica, including asiatic acid (AA), asiaticoside, madecassic acid, and madecassoside, in several cell types, including skin fibroblasts, macrophages, hepatocytes, and endothelial cells, under conditions promoting oxidative stress. AA conferred the highest viability on Hs68 cells exposed to ultraviolet B (UVB) irradiation. Triterpene pretreatment attenuated the UVB-induced generation of reactive oxygen species (ROS) and malondialdehyde (MDA), as well as the UVB-induced depletion of glutathione (GSH) in skin fibroblasts. AA most potently inhibited UVB-induced MMP generation, resulting in increased intracellular collagen levels. Pretreatment with triterpenes, particularly AA, significantly improved cell viability and attenuated TBHP-induced levels of ROS, alanine aminotransferase, and aspartate aminotransferase in HepG2 cells. Triterpenes attenuated ROS levels and reduced MDA and GSH expression in EA.hy926 cells. In RAW264.7 macrophages, production of nitric oxide, tumor necrosis factor-α, and interleukin-6 (indicators of LPS-induced oxidative damage) was significantly reduced by treatment with any of the triterpenes. Statistical analyses of triterpene biological activities using principal component analysis and hierarchical clustering revealed that AA exerted the greatest overall influence and showed remarkable activity in Hs68 and HepG2 cells. Full article

This paper examines potential associations of loneliness with laboratory data and specific psychosocial and behavioral attitudes. The sample collection took place in an urban Primary Health Care unit between May and July 2023, consecutively, and once exclusion criteria were implemented. Participants were aged between 40 and 75 years. Routine laboratory test results upon study initiation and six months before were used. The University of California, Los Angeles (UCLA), Loneliness Scale (Version 3), blood glucose, serum lipids, Fibrosis-4 index, and Creatinine Clearance (CrCl) were assessed through hierarchical multiple logistic regression analysis. Based on full model (3rd) analysis, those who were engaged in an individual sport or activity or had contacts with more friends presented significantly lower odds for increased loneliness levels (odds ratio (OR): 0.28 [95% confidence interval (CI) 0.09–0.91], p = 0.034 and OR: 0.76 [95%CI 0.66–0.88], p < 0.001, respectively). The consumption of alcohol was associated with increased loneliness (OR: 5.55 [95%CI 1.42–21.63], p = 0.014). Elevated triglyceride levels were linked with moderate or no loneliness (OR: 0.20 [95%CI 0.05–0.83], p = 0.026), while an increased LDL/HDL atherosclerotic index was related to increased subjective loneliness (OR: 4.50 [95%CI 1.12–18.13], p = 0.035). The need for holistic approaches—involving primary care personnel—in understanding and addressing loneliness, recognizing its multifaceted nature as well as the diverse factors that contribute to this issue, is considered challenging. Full article

Two electrochemical sensors were developed in this study, with their preparations using two nanomaterials with remarkable properties, namely, carbon nanofibers (CNF) modified with Fe₃O₄ nanoparticles and multilayer carbon nanotubes (MWCNT) modified with Fe₃O₄ nanoparticles. The modified screen-printed electrodes (SPE) were thus named SPE/Fe₃O₄-CNF and SPE/Fe₃O₄-MWCNT and were used for the simultaneous detection of heavy metals (Cd²⁺, Pb²⁺, Cu²⁺ and Hg²⁺). The sensors have been spectrometrically and electrochemically characterized. The limits of detection of the SPE/Fe₃O₄-CNF sensor were 0.0615 μM, 0.0154 μM, 0.0320 μM and 0.0148 μM for Cd²⁺, Pb²⁺, Cu²⁺ and Hg²⁺, respectively, and 0.2719 μM, 0.3187 μM, 1.0436 μM and 0.9076 μM in the case of the SPE/ Fe₃O₄-MWCNT sensor (following optimization of the working parameters). Due to the modifying material, the results showed superior performance for the SPE/Fe₃O₄-CNF sensor, with extended linearity ranges and detection limits in the nanomolar range, compared to those of the SPE/Fe₃O₄-MWCNT sensor. For the quantification of heavy metal ions Cd²⁺, Pb²⁺, Cu²⁺ and Hg²⁺ with the SPE/Fe₃O₄-CNF sensor from real samples, the standard addition method was used because the values obtained for the recovery tests were good. The analysis of surface water samples from the Danube River has shown that the obtained values are significantly lower than the maximum limits allowed according to the quality standards specified by the United States Environmental Protection Agency (USEPA) and those of the World Health Organization (WHO). This research provides a complementary method based on electrochemical sensors for in situ monitoring of surface water quality, representing a useful tool in environmental studies. Full article

On 14 December 2021, the extraordinary event called “touching the Sun” has been heralded as a “monumental moment for solar science”, in which the Parker Solar Probe opened up a new frontier of research for Space exploration, proposing the challenge of reaching, studying, and even “touching” our Sun at close range. The consequences of this event are scientific but also metaphysical and transcendental, offering the opportunity to reflect on the complex reality and meaning of the “boundaries” as opportunities for relationships and then for ethics. In this paper, I would like to propose an attempt to develop a possible discussion for an extension of Space Sustainability as an ethical guide for humanity which, as it goes out into outer Space, is helped to rediscover new, expanded dimensions of perception along the path of mystery and humility, in order to return back to Earth enriched for new relationships in pursuit of the common good. Full article

The objectives of this study were to investigate (a) the relationship between the Yo-Yo intermittent recovery test level 1 (YYIR1) and a laboratory test for measuring maximal oxygen uptake (VO_2max), (b) the relationships between anthropometric characteristics and variables of the two aerobic tests (field and laboratory), and (c) differences in performance and anthropometric characteristics among five different playing positions. The study involved 27 U17 young soccer players (16.0 ± 0.6 years). They randomly underwent a maximal laboratory treadmill test to measure VO_2max and the YYIR1 test. Pearson correlation was used to find potential correlations, and a one-way ANOVA was used to find differences between playing positions. Statistical significance was set at p < 0.05. The results showed that height was moderately negatively correlated (r = −0.455, p = 0.017) as well as body mass (r = −0.395, p = 0.042). Significant positive correlation was observed between vVO_2max and the distance covered in YYIR1 (r = 0.393, p = 0.042). Finally, no differences were observed between playing positions in any anthropometric characteristic or in any variable of the two aerobic tests (laboratory or field) (p > 0.05). In conclusion, the YYIR1 test is not suitable for estimating VO_2max. Additionally, the lack of differences between playing positions may be due to the limited specialization of the training load received by the players until this age. Full article

Federated learning (FL) in mobile edge computing has emerged as a promising machine-learning paradigm in the Internet of Things, enabling distributed training without exposing private data. It allows multiple mobile devices (MDs) to collaboratively create a global model. FL not only addresses the issue of private data exposure but also alleviates the burden on a centralized server, which is common in conventional centralized learning. However, a critical issue in FL is the imposed computing for local training on multiple MDs, which often have limited computing capabilities. This limitation poses a challenge for MDs to actively contribute to the training process. To tackle this problem, this paper proposes an adaptive dataset management (ADM) scheme, aiming to reduce the burden of local training on MDs. Through an empirical study on the influence of dataset size on accuracy improvement over communication rounds, we confirm that the amount of dataset has a reduced impact on accuracy gain. Based on this finding, we introduce a discount factor that represents the reduced impact of the size of the dataset on the accuracy gain over communication rounds. To address the ADM problem, which involves determining how much the dataset should be reduced over classes while considering both the proposed discounting factor and Kullback–Leibler divergence (KLD), a theoretical framework is presented. The ADM problem is a non-convex optimization problem. To solve it, we propose a greedy-based heuristic algorithm that determines a suboptimal solution with low complexity. Simulation results demonstrate that our proposed scheme effectively alleviates the training burden on MDs while maintaining acceptable training accuracy. Full article

Effects of different phenolic compounds on the redox state of myoglobin and their potential for preserving the color and chemical quality of refrigerated longtail tuna (Thunnus tonggol) slices were studied. Purified myoglobin from dark muscle (15.83 kDa) was prepared. Catechin, EGCG, quercetin, and hyperoside affected the absorption spectra and redox state of metmyoglobin (metMb) at 4 °C for up to 72 h differently. Reduction of metMb to oxymyoglobin (oxyMb) was notably observed for two flavonols (EGCG and quercetin) at 50 and 100 ppm. Based on the reducing ability of metMb, EGCG and quercetin were selected for further study. Longtail tuna slices were treated with EGCG and quercetin at 200 and 400 mg/kg. Color (a* and a*/b*), proportion of myoglobin content, and quality changes were monitored over 72 h at 4 °C. Tuna slices treated with 200 mg/kg EGCG showed better maintenance of oxyMb and color as well as lower lipid oxidation (PV and TBARS) and protein oxidation (carbonyl content) than the remaining samples. Nevertheless, EGCG at 400 mg/kg exhibited lower efficacy in retaining the quality of tuna slices. Thus, EGCG at 200 mg/kg could be used to maintain the color and prolong the shelf life of refrigerated longtail tuna slices. Full article

As a natural satellite of the Earth, the moon is a prime target for planetary remote sensing exploration. However, lunar polarization studies are not popular in the planetary science community. Polarimetry of the lunar surface had not been carried out from a spacecraft until the Korean lunar exploration program was initiated. In previous polarization observations of the moon, images of different polarization states were obtained by a rotating linear polarizer. This method is not well suited for future polarization observations from space-based spacecraft. To this end, we present a new kind of polarized observation of the moon using a division of a focal-plane polarization camera and propose a pipeline on the processing method of the polarization observation of the moon. We obtain a map of the degree of white-light polarization on the nearside of the moon through polarization observation, data processing, and correction. The observation and data processing methods presented in this study have the potential to serve as a reference for analyzing polarization observation data from future orbiting spacecraft. These are expected to lead to new discoveries in the fields of astronomy and planetary science. Full article

This comprehensive review assessed the integration of robotics and artificial intelligence (AI) in dentistry, offering a transparent overview of developments across dental fields. Covering articles in prosthodontics, orthodontics, implantology, surgery, and radiology, the review included 39 articles on robotics and 16 on AI. Screening adhered to PRISMA guidelines, with searches conducted on Medline, Google Scholar, and IEEE. Incorporating the search strategy, the review used keywords related to dentistry, robotics, and AI. For robotics, 296 articles were screened, resulting in 39 qualifying for qualitative synthesis. A separate AI search on PubMed identified 142 studies within the last decade, with 16 studies selected for a detailed full-text analysis, offering a consolidated overview of the current state-of-the-art knowledge in the AI domain. Geographic distribution highlighted East Asia as a major research contributor. The findings indicate an increasing trend in dentistry robotics since 2000 and, particularly since 2016, in AI dentistry. The majority of the literature fell under the category of basic research. The technology readiness level did not cross “three” (proof of concept) in 41% of all articles. Therefore, the overall literature quality remains low, particularly regarding clinical validation. Full article

Nanoemulsions represent a remarkable class of colloidal systems that play a pivotal role in the encapsulation, protection, and targeted delivery of active ingredients to the skin. One of the primary objectives in skincare science is to maximize the interaction between the active ingredients and the skin. This can be achieved through various mechanisms, two of which are occlusion and extended contact of the formulation with the skin. Cosmetic masks can be used to improve the skin’s hydration by creating a barrier that minimizes transepidermal water loss while acting as a repository of the active ingredient, increasing the skin’s absorption of the formulation’s active ingredients. In order to diminish the environmental impact, natural-polymeric-material masks are being used, as an alternative to synthetic materials, for its biocompatibility and biodegradability. In this work pectin and tapioca starch were used to develop a polymeric mask to deliver a rice bran oil nanoemulsion and study some characteristics of the final product. The results show that the association of pectin and tapioca starch can be used to produce a film that can be molded and shows occlusive effects, besides being flexible and compatible with the skin. Full article

In patients with septic shock, compensatory tachycardia initially serves to maintain adequate cardiac output and tissue oxygenation but may persist despite appropriate fluid and vasopressor resuscitation. This sustained elevation in heart rate and altered heart rate variability, indicative of autonomic dysfunction, is a well-established independent predictor of adverse outcomes in critical illness. Elevated heart rate exacerbates myocardial oxygen demand, reduces ventricular filling time, compromises coronary perfusion during diastole, and impairs the isovolumetric relaxation phase of the cardiac cycle, contributing to ventricular-arterial decoupling. This also leads to increased ventricular and atrial filling pressures, with a heightened risk of arrhythmias. Ivabradine, a highly selective inhibitor of the sinoatrial node’s pacemaker current (I_f or “funny” current), mitigates heart rate by modulating diastolic depolarization slope without affecting contractility. By exerting a selective chronotropic effect devoid of negative inotropic properties, ivabradine shows potential for improving hemodynamics in septic shock patients with cardiac dysfunction. This review evaluates the plausible mechanisms and existing evidence regarding the utility of ivabradine in managing patients with septic shock. Full article

Inclusion of lysophospholipids (LPL) has been proposed to increase growth performance in broilers and pigs, acting as emulsifiers through mixed micelle formation. The aim of this study was to investigate the effect of feeding LPL in weanling pig diets on growth performance and intestinal morphology. Eight hundred pigs (weight 6.96 kg ± SD 1.58 kg) were assigned to one of two dietary treatments, i.e., a basal diet (CON) or a basal diet + 0.05% lysophospholipids (LPL). The experimental period lasted for 42 days, and on days 40 and 41, 32 pigs in total were euthanized for intestinal tissue samples. From days 14 to 21, feed intake and average daily gain increased, as well as FCR, from days 28 to 42, in the LPL group compared with the CON group. In the overall period, no differences in growth performance were present between the groups. However, females displayed increased ADG from days 21 to 28 compared with castrates. The villous height tended (p = 0.051) to be lower in LPL in the proximal jejunum compared with CON. In the proximal jejunum, villus was higher (p > 0.01) in females, and in the distal jejunum, higher crypt cell proliferation (p < 0.01) and a tendency to deeper crypts (p = 0.064) were observed in female pigs as well. In conclusion, lysophospholipids did not increase growth performance in this study; however, the rate of recovery from a poorer starting point was noted, as growth rates recovered and increased faster in the LPL group. In conclusion, unlike the first phase, the LPL group recovered the growth from days 14 to 21 through higher feed intake and weight gain than the CON group. Eventually, the LPL group displayed improved FCR compared with the CON group from days 28 to 42. Further studies are needed to investigate whether this effect continues into the grower–finisher phase. Full article

Chronic progressive lymphedema (CPL) is a prevalent and progressive disease in Rhenish German draught horses. The objective of our follow-up study was to evaluate the heritability of this disease in Rhenish German draught horses using pedigree-based and genomic relationship matrices. We employed linear and threshold animal models. Models included the random animal effect and effects of breeding association, coat colour, sex, and age within sex, and farm-related factors, on CPL scores. In addition, we estimated heritabilities in models assuming censoring for data when horses were below an age of 1–15 years. The heritabilities of CPL scores across all ages were 0.595 ± 0.131 and 0.482 ± 0.105 in the threshold and linear animal model with pedigree-based relationship matrices, respectively. The restriction of data to horses with a minimum age at examination or accounting for censored data in younger animals showed an increase in heritabilities of CPL scores up to 0.788 ± 0.168 (threshold model) and 0.752 ± 0.153 (linear model) at an age of 7–8 years. Analyses including genomic relationship matrices yielded very similar estimates, but with smaller standard errors than pedigree-based analyses. Heritabilities in threshold models for CPL prevalence (CPL-bin-score) and the number of affected limbs (CPL-bin-sum) were 0.176–0.189 ± 0.061–0.064 and 0.375–0.433 ± 0.164–0.170, respectively. We were able to show moderately to highly positive genetic correlations between the CPL score and cannon bone circumference (0.529–0.825), height at withers (0.338–0.555), and skinfold thickness (0.241–0.517). Using the dichotomous trait for the CPL score and the genomic relationship matrix resulted in corresponding estimates of 0.868, 0.793, and 0.784, respectively. This study showed the great importance of additive genetic variation influencing the expression of chronic progressive lymphedema in Rhenish German draught horses. Therefore, further research is warranted to implement breeding programmes in a small breeding population that exploit the potential of additive genetic differences among animals for reducing the prevalence and severity of lesions of this incurable disease. Full article

To address the problems of inadequate training and low precision in prediction models with small-sample-size and incomplete data, a novel SALGAN-CatBoost-SSAGA framework is proposed in this paper. We utilize the standard K-nearest neighbor algorithm to interpolate missing values in incomplete data, and employ EllipticEnvelope to identify outliers. SALGAN, a generative adversarial network with a self-attention mechanism of label awareness, is utilized to generate virtual samples and increase the diversity of the training data for model training. To avoid local optima and improve the accuracy and stability of the standard CatBoost prediction model, an improved Sparrow Search Algorithm (SSA)–Genetic Algorithm (GA) combination is adopted to construct an effective CatBoost-SSAGA model for risk warning, in which the SSAGA is used for the global parameter optimization of CatBoost. A UCI heart disease dataset is used for heart disease risk prediction. The experimental results show the superiority of the proposed model in terms of accuracy, precision, recall, and F1-values, as well as the AUC. Full article

Nowadays, machine learning (ML) is a useful technology due to its high accuracy in constructing non-linear models and algorithms that can adapt to the complexity and diversity of data. Thus, the current work aimed to predict the soil quality index (SQI) from extensive soil data, achieving high accuracy with the artificial neural networks (ANN) model. However, the efficiency of ANN depends on the accuracy of the data that is prepared for training. For this purpose, MATLAB programming language was used to enable the calculation, classification, and compilation of the results into databases within a few minutes. The proposed MATLAB program was highly efficient, accurate, and quick in calculating soil big data for training the machine compared with traditional methods. The database contains 306 vector sets, 80% of them are used for training and the remaining 20% are reserved for testing. The optimal model obtained comprises one hidden layer with 250 neurons and one output layer with a sigmoid function. The ANN achieved a high coefficient of determination (R²) values for SQI estimation, with around 0.97 and 0.98 for training and testing, respectively. The results indicate that 36.93% of the total soil samples belonged to the very high quality class (C1). In contrast, the high quality (C2), moderate quality (C3), low quality (C4), and very low quality (C5) classes accounted for 10.46%, 31.37%, 20.92%, and 0.33% of the samples, respectively. The high contents of CaCO₃, pH, sodium saturation, salinity, and clay content were identified as limiting factors in certain areas. The results of this study indicated high accuracy of soil quality assessment using physical, chemical, and fertility soil features in regression analysis with ANN. This method, which is suitable for arid zones, enhances agricultural productivity and decision-making by identifying critical soil quality categories and constraints. Full article

Solid brick masonry poses challenges in predicting compressive strength due to its non-homogeneous and anisotropic nature, compounded by variations in the properties of the constituent bricks and mortar. This research addresses this issue through secondary analysis and examining the interplay between brick-and-mortar compressive strengths. Contrary to existing empirical equations for predicting masonry compressive strength, regression analysis was conducted on test specimens categorized into two groups based on the relative strength of the constitutive materials: Group 1, masonry specimens with bricks stronger than mortar (f_b > f_j), and Group 2, specimens where the mortar has higher compressive strength than the bricks (f_j > f_b). Additionally, the calculated impact of factors like the slenderness ratio and mortar-to-brick joint thickness ratio on masonry compressive strength highlights the need for more precise compressive strength predictions. The results emphasize the importance of considering the individual contributions of bricks and mortar to the overall compressive strength, shedding light on how these components affect structural behavior. Full article

This article explores the integration of Digital Twins in Systems and Predictive Medicine, focusing on eye diagnosis. By utilizing the Digital Twin models, the proposed framework can support early diagnosis and predict evolution after treatment by providing customized simulation scenarios. Furthermore, a structured architectural framework comprising five levels has been proposed, integrating Digital Twin, Systems Medicine, and Predictive Medicine for managing eye diseases. Based on demographic parameters, statistics were performed to identify potential correlations that may contribute to predispositions to glaucoma. With the aid of a dataset, a neural network was trained with the goal of identifying glaucoma. This comprehensive approach, based on statistical analysis and Machine Learning, is a promising method to enhance diagnostic accuracy and provide personalized treatment approaches. Full article