The present study aims to explore rowshans as essential vernacular architectural elements in designing houses in very hot-dry climates such as Jeddah, Saudi Arabia, to determine their most significant effects on air movement, ventilation, and mitigating cooling loads. A comprehensive combination of building performance simulation and computational fluid dynamics (CFD) analysis was used to model a room with six different sizes of rectangular openings and quantify rowshans’ potential as passive elements in providing occupants with comfort and reducing energy use. Analysis of the passive element revealed the thermal performance and natural ventilation in single-family homes for the Jeddah climate, created by outdoor and indoor temperature, airspeed, and pressure differences in the room model, were improved, lowering sensation temperature for inhabitants’ comfort. The results highlight the beneficial effects of rowshans in lowering a house’s temperature during the daytime: from November to April, at noon, indoor air temperature (IAT) could reach a 15% to 22% reduction in the north orientation. The findings also show that rowshans with 5 × 5 cm opening grids can keep the air volume flow rate within an acceptable range and keep the room in the comfort zone range for 42.3% of hours annually, equal to 3704 h. An implication of these results is the possibility of establishing housing design criteria that can enhance efficiency and thermal comfort conditions, lower the cost of operations, provide occupants with satisfaction, and reduce emissions to regenerate the environment, leading to affordability and sustainability in the Jeddah region. Full article

In this work we suggest that the common cause for the development of various power laws is the existence of a suitable exchangeable quantity between the agents of a set. Examples of such exchangeable quantities, leading to eponymous power laws, include money (Pareto’s Law), scientific knowledge (Lotka’s Law), people (Auerbach’s Law), and written or verbal information (Zipf’s Law), as well as less common cases like bullets during deadly conflicts, recognition in social networks, heat between the atmosphere and sea-ice floes, and, finally, mass of water vapors between pores in solids. This last case is examined closely in the present article based on extensive experimental data. It is shown that the transferred mass between pores, which eventually grow towards a power law distribution, may be expressed using different parameters, either transferred surface area, or transferred volume, or transferred pore length or transferred pore anisotropy. These distinctions lead to different power laws of variable strength as reflected by the corresponding exponent. The exponents depend quantitatively on the spread of frequency distribution of the examined parameter and tend to zero as the spread of distribution tends to a single order of magnitude. A comparison between the energy and the entropy of different kinds of pore distributions reveals that these two statistical parameters are linearly related, implying that the system poise at a critical state and the exchangeable quantities are the most convenient operations helping to keep this balance. Full article

Aminopyrazoles represent interesting structures in medicinal chemistry, and several derivatives showed biological activity in different therapeutic areas. Previously reported 5-aminopyrazolyl acylhydrazones and amides showed relevant antioxidant and anti-inflammatory activities. To further extend the structure–activity relationships in this class of derivatives, a novel series of pyrazolyl acylhydrazones and amides was designed and prepared through a divergent approach. The novel compounds shared the phenylamino pyrazole nucleus that was differently decorated at positions 1, 3, and 4. The antiproliferative, antiaggregating, and antioxidant properties of the obtained derivatives 10–22 were evaluated in in vitro assays. Derivative 11a showed relevant antitumor properties against selected tumor cell lines (namely, HeLa, MCF7, SKOV3, and SKMEL28) with micromolar IC₅₀ values. In the platelet assay, selected pyrazoles showed higher antioxidant and ROS formation inhibition activity than the reference drugs acetylsalicylic acid and N-acetylcysteine. Furthermore, in vitro radical scavenging screening confirmed the good antioxidant properties of acylhydrazone molecules. Overall, the collected data allowed us to extend the structure–activity relationships of the previously reported compounds and confirmed the pharmaceutical attractiveness of this class of aminopyrazole derivatives. Full article

In recent years, most research on bearing fault diagnosis has assumed that the source domain and target domain data come from the same machine. The differences in equipment lead to a decrease in diagnostic accuracy. To address this issue, unsupervised domain adaptation techniques have been introduced. However, most cross-device fault diagnosis models overlook the discriminative information under the marginal distribution, which restricts the performance of the models. In this paper, we propose a bearing fault diagnosis method based on envelope spectrum and conditional metric learning. First, envelope spectral analysis is used to extract frequency domain features. Then, to fully utilize the discriminative information from the label distribution, we construct a deep Siamese convolutional neural network based on conditional metric learning to eliminate the data distribution differences and extract common features from the source and target domain data. Finally, dynamic weighting factors are employed to improve the convergence performance of the model and optimize the training process. Experimental analysis is conducted on 12 cross-device tasks and compared with other relevant methods. The results show that the proposed method achieves the best performance on all three evaluation metrics. Full article

Thermodynamic theory was employed in this study to investigate the feasibility of separating antimony (Sb) from crude arsenic (As) using vacuum sublimation. Ab initio molecular dynamics simulations are used to calculate the structure, stability, and diffusion properties of AsmSbn (m + n ≤ 6) clusters. As₄, As₃Sb, As₂Sb₂, and AsSb₃ are the possible clusters in this thermodynamic calculation, and the molecular dynamics results confirmed their structural stability and stabilization in the gas phase. As₄ had the largest diffusion coefficients, which is the reason it separates from the Sb-containing clusters (As₃Sb, As₂Sb₂, and AsSb₃) during gas-phase diffusion and condensation processes. The experimental results show that As vapor was transformed from crystalline to amorphous with increasing subcooling, and the Sb-containing clusters that enter the gas phase were mainly condensed and deposited at the proximal end of the heating zone. Not considering the volatilization rate, the removal rate of Sb in products can reach 99.35% by increasing the condensation disk and expanding the condensation zone; thus, experiments confirmed that industrial crude arsenic can realize deep Sb removal after vacuum sublimation. Full article

Bio-inspired gyroid triply periodic minimum surface (TPMS) lattice structures have been the focus of research in automotive engineering because they can absorb a lot of energy and have wider plateau ranges. The main challenge is determining the optimal energy absorption capacity and accurately capturing plastic plateau areas using finite element analysis (FEA). Using nTop’s Boolean subtraction method, this study combined walled TPMS gyroid structures with a normal TPMS gyroid lattice. This made a composite TPMS gyroid lattice (CTG) with relative densities ranging from 14% to 54%. Using ideaMaker 4.2.3 (3DRaise Pro 2) software and the fused deposition modeling (FDM) Raise3D Pro 2 3D printer to print polylactic acid (PLA) bioplastics in 1.75 mm filament made it possible to slice computer-aided design (CAD) models and fabricate 36 lattice samples precisely using a layer-by-layer technique. Shimadzu 100 kN testing equipment was utilized for the mechanical compression experiments. The finite element approach validates the results of mechanical compression testing. Further, a composite CTG was examined using a field emission scanning electron microscope (FE-SEM) before and after compression testing. The composite TPMS gyroid lattice showed potential as shock absorbers for vehicles with relative densities of 33%, 38%, and 54%. The Gibson–Ashby model showed that the composite TPMS gyroid lattice deformed mainly by bending, and the size effect was seen when the relative densities were less than 15%. The lattice’s relative density had a significant impact on its ability to absorb energy. The research also explored the use of these innovative foam-like composite TPMS gyroid lattices in high-speed crash box scenarios to potentially enhance vehicle safety and performance. The structures have tremendous potential to improve vehicle safety by acting as advanced shock absorbers, which are particularly effective at higher relative densities. Full article

Ice plug technology is an effective method for isolating the pipeline system, which are promising methods utilized in the nuclear, chemical, and power industries. To reduce the cold energy consumption and temperature stress, the multi-stage (1–10) of time-dependent thermal boundary conditions was proposed for the formation of ice plug, while the gradient cooling wall temperature of multi-stage was applied. A numerical model considering the liquid–solid phase change, heat transfer, and time-dependent thermal boundary condition has been established. The effects of the ratio of length and diameter of the cooling wall l_c/d (1–9) on the formation rate and heat flux of ice plug in the pipe has been investigated. The fastest formation rate of ice plug with 800 mm in the axial direction (7.47 cm³/s) was observed in the pipe with the l_c/d of 5. The formation rate of ice plug and the ice formation volume under unit energy consumption VE under various stages (1–10) of cooling wall temperature have been compared. The VE of eight temperature stages (1.45 cm³/kJ) was 1.16 times than the VE of one temperature stage, which satisfied the freezing rate at the same time. This investigation provides insight for proposing an energy-saving system for the formation of ice plug. Full article

As bilingual families increase, the phenomenon of language mixing among children in mixed-language environments has gradually attracted academic attention. This study aims to explore the impact of language mixing on vocabulary acquisition in bilingual children and whether language distance moderates this impact. We recruited two groups of bilingual children, Chinese–English bilinguals and Chinese–Japanese bilinguals, to learn two first-language new words in a monolingual environment and a mixed-language environment, respectively. The results showed that the participants could successfully recognize the novel words in the code-switching sentences. However, when we compared the performance of the two groups of bilingual children, we found that the gaze time proportion of the Chinese–English bilingual children under the code-switching condition was significantly higher than that of the Chinese–Japanese bilingual children, while there was no significant difference under the monolingual condition. This suggests that language mixing has an inhibitory effect on vocabulary acquisition in bilingual children and that this inhibitory effect is influenced by language distance, that is, the greater the language distance, the stronger the inhibitory effect. This study reveals the negative impact of language mixing on vocabulary acquisition in bilingual children and also implies that there may be some other influencing factors, so more research is needed on different types of bilingual children. Full article

Agar, as a seaweed polysaccharide mainly extracted from Gracilariopsis lemaneiformis, has been commercially applied in multiple fields. To investigate factors indicating the agar accumulation in G. lemaneiformis, the agar content, soluble polysaccharides content, and expression level of 11 genes involved in the agar biosynthesis were analysed under 4 treatments, namely salinity, temperature, and nitrogen and phosphorus concentrations. The salinity exerted the greatest impact on the agar content. Both high (40‰) and low (10‰, 20‰) salinity promoted agar accumulation in G. lemaneiformis by 4.06%, 2.59%, and 3.00%, respectively. The content of agar as a colloidal polysaccharide was more stable than the soluble polysaccharide content under the treatments. No significant correlation was noted between the two polysaccharides, and between the change in the agar content and the relative growth rate of the algae. The expression of all 11 genes was affected by the 4 treatments. Furthermore, in the cultivar 981 with high agar content (21.30 ± 0.95%) compared to that (16.23 ± 1.59%) of the wild diploid, the transcriptional level of 9 genes related to agar biosynthesis was upregulated. Comprehensive analysis of the correlation between agar accumulation and transcriptional level of genes related to agar biosynthesis in different cultivation conditions and different species of G. lemaneiformis, the change in the relative expression level of glucose-6-phosphate isomerase II (gpiII), mannose-6-phosphate isomerase (mpi), mannose-1-phosphate guanylyltransferase (mpg), and galactosyltransferase II (gatII) genes was highly correlated with the relative agar accumulation. This study lays a basis for selecting high-yield agar strains, as well as for targeted breeding, by using gene editing tools in the future. Full article

The aim of the work was to investigate the influence of the surface texture of composite based on PA6, intended for wet painting, on the stability of the colour and gloss parameters. The stability of the paint coating was required to be maintained despite exposure to mechanical stress resulting from attempts to manually remove graffiti stains. The study examined the influence of surface texture on the effectiveness of cleaning. In the case of painted surfaces from which graffiti stains were effectively removed, the roughness, colour parameters and gloss of the paint coating were measured. During the research, it was found that roughness after painting decreased to the value of Ra < 2.00 µm meets aesthetic expectations and at the same time ensures the effective removal of graffiti stains. For this surface, there were no negative effects of the mechanical impact on the textures or quality parameters of the coating as a result of manual graffiti removal. As a result of the conducted research, the recommended maximum values of roughness and textures of the surfaces to be painted were determined in order to ensure a sufficiently low amount of work necessary to effectively remove traces of graffiti. Full article

In the architecture, engineering, and construction (AEC) industry, the positioning technology for a mobile construction platform (MCP) is critical to achieve on-site, continuous, large-scale construction. During construction, MCP movement and construction actions seldom occur simultaneously. Therefore, this paper categorizes the MCP into stationary and moving states for positioning studies, respectively. When the platform is stationary, it is positioned using an improved ultra-wideband (UWB) sensor. When the platform is in motion, a single UWB positioning technique cannot meet the required accuracy for positioning, and fusion positioning using both UWB and an inertial measurement unit (IMU) is considered. The experimental results show that compared with only UWB positioning, the improved UWB positioning algorithm improves the positioning accuracy by 53% in the stationary state, and the fused UWB/IMU positioning improves the positioning accuracy by 46% in the moving state. As a result, the positioning accuracy of the MCP is significantly improved regardless of whether it is in a stationary or moving state. Furthermore, this paper integrates the positioning technique with the robotic arm construction technique to successfully simulate an on-site continuous construction of a wooden cabin, which provides the potential for large-scale continuous construction in real-world scenarios in the future. Full article

Objectives: Internet addiction is a behavioral addiction characterized by excessive and compulsive use of the internet. The risk of internet addiction among adolescents has risen recently due to an increase in technological advancement and globalization. However, previous studies have focused on the precipitating factors triggering the internet addiction without looking at the exogenous factors and boundary conditions, such as family functioning, that can either sustain or weaken such behavior. Thus, the present study aimed to examine the moderating role of family functioning in the relationship between personality traits and internet addiction among adolescents. Methods: This study is a cross-sectional study consisting of 3150 adolescent students in the grade/class level of JSS1-SS3 who were assessed with standardized measures of the Big-Five Personality Inventory, Internet Addictive Test, and Family APGAR Index. Pearson correlation was used to explore the bivariate relationships between the demographic variable and other variables of interest, while Hayes regression-based PROCESS macro for SPSS was used to test the Hypotheses. Results: (1) Openness to experience, conscientiousness, extraversion, and neuroticism positively correlated with internet addiction, whereas agreeableness was negatively associated with internet addiction. (2) Positive family functioning correlated negatively with internet addiction. (3) Positive family functioning moderated the relationships of extraversion and agreeableness with internet addiction but not on openness to experience, conscientiousness, and neuroticism with internet addiction. Conclusions: Positive family functioning correlated negatively with internet addiction among adolescents, suggesting that improving family functioning would be a valuable tactic for reducing adolescents’ susceptibility to personality-related internet addiction. Full article

This article presents a comprehensive evaluation of traditional machine learning and deep learning models in analyzing sentiment trends within the SENT-COVID Twitter corpus, curated during the COVID-19 pandemic. The corpus, filtered by COVID-19 related keywords and manually annotated for polarity, is a pivotal resource for conducting sentiment analysis experiments. Our study investigates various approaches, including classic vector-based systems such as word2vec, doc2vec, and diverse phrase modeling techniques, alongside Spanish pre-trained BERT models. We assess the performance of readily available sentiment analysis libraries for Python users, including TextBlob, VADER, and Pysentimiento. Additionally, we implement and evaluate traditional classification algorithms such as Logistic Regression, Naive Bayes, Support Vector Machines, and simple neural networks like Multilayer Perceptron. Throughout the research, we explore different dimensionality reduction techniques. This methodology enables a precise comparison among classification methods, with BETO-uncased achieving the highest accuracy of 0.73 on the test set. Our findings underscore the efficacy and applicability of traditional machine learning and deep learning models in analyzing sentiment trends within the context of low-resource Spanish language scenarios and emerging topics like COVID-19. Full article

The study focused on examining the relationship between well-being and various psychological factors such as loneliness, anxiety, depression, and stress, whilst also considering changes in lifestyle. A total of 108 elderly participants, with an average age of 70.38 years, were enrolled in this quantitative cross-sectional study. The research employed a battery of assessment tools including a Sociodemographic Data Questionnaire, Mini-Mental State Examination, Positive Mental Health Scale, Stress Perception Scale, Geriatric Anxiety Inventory, Geriatric Depression Scale (reduced version), Loneliness Scale, and International Physical Activity Questionnaire. Descriptive analysis was conducted in order to understand the distribution of scores across these variables, followed by the categorization of participants based on the reported alterations in eating and physical activity behaviors. Correlations between variables were assessed using Spearman correlation and an EBIC-LASSO network analysis. The findings indicated a potential detriment to the well-being of elderly individuals practicing social distancing, evidenced by heightened symptoms of loneliness, depression, anxiety, and stress, alongside the reported changes in dietary patterns and physical activity. The study underscores the importance of understanding the pandemic’s impact on the well-being of older adults and advocates for longitudinal investigations to delineate the evolving effects of social distancing measures across different phases of the pandemic. Full article

With the advent of big data science, the field of geoscience has undergone a paradigm shift toward data-driven scientific discovery. However, the abundance of geoscience data distributed across multiple sources poses significant challenges to researchers in terms of data compilation, which includes data collection, collation, and database construction. To streamline the data compilation process, we present GeoKnowledgeFusion, a publicly accessible platform for the fusion of text, visual, and tabular knowledge extracted from the geoscience literature. GeoKnowledgeFusion leverages a powerful network of models that provide a joint multimodal understanding of text, image, and tabular data, enabling researchers to efficiently curate and continuously update their databases. To demonstrate the practical applications of GeoKnowledgeFusion, we present two scenarios: the compilation of Sm-Nd isotope data for constructing a domain-specific database and geographic analysis, and the data extraction process for debris flow disasters. The data compilation process for these use cases encompasses various tasks, including PDF pre-processing, target element recognition, human-in-the-loop annotation, and joint multimodal knowledge understanding. The findings consistently reveal patterns that align with manually compiled data, thus affirming the credibility and dependability of our automated data processing tool. To date, GeoKnowledgeFusion has supported forty geoscience research teams within the program by processing over 40,000 documents uploaded by geoscientists. Full article

This work investigated the impact of temperature on the diffusion of lithium ions within cells. To achieve this, electrochemical impedance spectroscopy (EIS) analysis was conducted at various temperatures across three distinct cells. These cells utilized an electrode composed of corn starch meringue and were paired with three different electrolytes. Notably, one electrolyte included an additional 5% of starch. The objective of this study extends beyond merely determining resistance from graphical representations; it also entails performing a kinetic analysis of specific systems, with a particular emphasis on elucidating the significance of the lithium-ion diffusion coefficient as a critical parameter. The cell with 1 M LiPF₆ in the EC/DMC/DEC electrolyte and corn starch-based electrode exhibited the most horizontally oriented Warburg curve, representing the smallest angle. Full article

Skeleton editing has rapidly advanced as a synthetic methodology in recent years, significantly streamlining the synthesis process and gaining widespread acceptance in drug synthesis and development. This field encompasses diverse ring reactions, many of which exhibit immense potential in skeleton editing, facilitating the generation of novel ring skeletons. Notably, reactions that involve the cleavage of two distinct rings followed by the reformation of new rings through ring insertion play a pivotal role in the construction of novel ring skeletons. This article aims to compile and systematize this category of reactions, emphasizing the two primary reaction types and offering a thorough exploration of their associated complexities and challenges. Our endeavor is to furnish readers with comprehensive reaction strategies, igniting research interest and injecting fresh impetus into the advancement of this domain. Full article

Traffic accidents represent a major problem worldwide. Public and private entities launch communication campaigns in order to educate the population about this problem. The aim of this study is to analyze the evolution of the presence of road safety in the Spanish media and its influence on the reduction of road accidents. A content analysis of six major Spanish newspapers between 2000 and 2008 (an important period in the reduction of the accident rate in Spain) was carried out in which the presence of news related to traffic accidents and the intensity of them were quantified using a set of criteria designed for this study. Furthermore, the correlation between the accident rates and the presence and intensity of news in the same time frame was measured. There has been an evident increase in the news related to traffic accidents during the analyzed period, both in terms of the presence of such news in general and in terms of intensity. The correlation analysis also shows a strong relationship between the increase in news presence and intensity and a sharp fall in accident rates in Spain. Although correlation analysis is not enough to establish a causal relationship between the variables studied here, the findings suggest that informative campaigns had a positive effect on encouraging pro-social behavior, were successful in disseminating related information, and, therefore, contributed significantly to lowering accident rates, although that was not the only reason. Full article

Understanding sustainable food choices is key to shifting consumer behavior toward sustainable food consumption. This study aimed to determine the validity and reliability of the Sustainable Food Choice Questionnaire (SUS-FCQ) in 602 Turkish adults. The linguistic equivalence of the SUS-FCQ was provided using the standard translation–back translation method, content validity, and pilot testing. Then, the convergent, discriminant, and construct (exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)) validity and reliability (test–retest and internal consistency) were evaluated. Cronbach’s alpha coefficient was found to be excellent (0.961) and the intraclass correlation coefficient was found to be moderate (0.689) using the test–retest method. As a result of the EFA, two-factor structures were found, and the factor loadings of the items were 0.651 and 0.878. These factors explained 79.17% of the total variance, and discriminant and convergent validity was provided for both factors. The results of this study suggest that the adapted SUS-FCQ is valid and reliable for determining sustainable food choice motives in the Turkish population. Therefore, the SUS-FCQ can be a useful instrument to encourage people to shift toward and adhere to sustainable food consumption. Full article

The selection of the optimal methodology for the 3D geometric documentation of cultural heritage is a subject of high concern in contemporary scientific research. As a matter of fact, it requires a multi-source data acquisition process and the fusion of datasets from different sensors. This paper aims to demonstrate the workflow for the proper implementation and integration of geodetic, photogrammetric and laser scanning techniques so that high-quality photorealistic 3D models and other documentation products can be generated for a complicated, large-dimensional architectural monument and its surroundings. As a case study, we present the monitoring of the Mehmet Bey Mosque, which is a landmark in the city of Serres and a significant remaining sample of the Ottoman architecture in Greece. The surveying campaign was conducted in the context of the 2022–2023 annual workshop of the Interdepartmental Program of Postgraduate Studies “Protection Conservation and Restoration of Cultural Monuments” of the Aristotle University of Thessaloniki, and it served as a geometric background for interdisciplinary cooperation and decision-making on the monument restoration process. The results of our study encourage the fusion of terrestrial laser scanning and photogrammetric datasets for the 3D modeling of the mosque, as they supplement each other as regards geometry and texture. Full article

(1) Background: The aim of this study was to analyze the impact of pharmacogenetic-guided antidepressant therapy on the 12-month evolution of the intensity of depressive symptoms in patients with recurrent depressive disorder (RDD) in comparison to a control group of depressive subjects who were treated conventionally. (2) Methods: This prospective longitudinal study was conducted between 2019 and 2022, and the patients were evaluated by employing the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A) and the Clinical Global Impressions Scale: Severity and Improvement. We followed them up at 1, 3, 6, and 12 months. (3) Results: Of the 76 patients with RDD, 37 were tested genetically (Group A) and 39 were not (Group B). Although the patients from Group A had statistically significantly more severe MDD at baseline than those from Group B (p < 0.001), by adjusting their therapy according to the genetic testing, they had a progressive and more substantial reduction in the severity of RDD symptoms [F = 74.334; η² = 0.674; p < 0.001], indicating a substantial association with the results provided by the genetic testing (67.4%). (4) Conclusions: In patients with RDD and a poor response to antidepressant therapy, pharmacogenetic testing allows for treatment adjustment, resulting in a constant and superior reduction in the intensity of depression and anxiety symptoms. Full article

The current study delves into a fuzzy matrix decision-making problem involving fuzzy sets of states. It establishes that a maximum guaranteed payoff constitutes a type-2 fuzzy set defined on the real line. Additionally, it provides the associated type-2 membership function. Moreover, the paper illustrates that the maximum guaranteed payoff type-2 fuzzy set of the decision-making problem can be broken down, based on the secondary membership grades, into a finite collection of fuzzy numbers. Each of these fuzzy numbers represents the maximum guaranteed payoff of the corresponding decision-making problem with a crisp set of states. This set corresponds to a specific cut of the original fuzzy set of states. Some properties of the maximum guaranteed payoff type-2 fuzzy set are investigated, and illustrative examples are provided. Since the problem formulation is symmetrical with respect to alternatives and states of nature, the results obtained can be used in the case of a fuzzy set of alternatives. Full article