(1) Background: University students, often constrained by time and influenced by socio-economic factors such as culture and religion, frequently adopt diets centred on ultra-processed foods (UPFs), increasing the risk of long-term non-communicable diseases. This study aimed to assess UPF consumption among Spanish university students and explore the potential impact of religion and the academic year on their eating habits. (2) Methods: In a cross-sectional study of 257 university students aged 18–31, UPF consumption was assessed using NOVA food classification at the academic year’s start and end. Chi-square and Wilcoxon tests analysed UPF consumption changes, while binary logistic regression identified associations between religion and weekly UPF consumption. (3) Results: Muslim students had a consumption of industrial bakery products almost five times [95% CI: 2.694–9.259] higher than that observed among Christians. Similar data were observed for artificial juice consumption (OR = 3.897, 95% CI = 2.291–6.627) and candy consumption (OR = 3.724, 95% CI = 2.051–6.762). Moreover, a greater percentage of calories and grams of saturated fats from UPFs was observed for Muslims at the end of the study. (4) Conclusions: Highlighting the impact of religion on UPF consumption among students underscores the necessity of monitoring and intervening in dietary habits to prevent undesirable long-term complications such as cardiovascular diseases. Full article

Efforts worldwide have been dedicated to developing strategies for reducing the environmental impacts arising from agricultural production. In developing countries, such as Brazil, where agricultural production stands as one of the most important economic sectors, meeting institutional and market requirements for sustainability is essential for ensuring the country’s competitiveness. This study investigated the intention of Brazilian dairy farmers to adopt environmental sustainability practices. The sample comprised 100 dairy farms in Paraná State, Brazil. The data were analyzed using structural equation models and discussed from the perspective of the Theory of Planned Behavior. The results showed that farmers’ intentions to adopt sustainability practices is not associated with socioeconomic or production characteristics. Structural equation modeling identified three constructs explaining farmers’ intentions to adopt sustainability practices, namely attitude (ATT), subjective norms (SN), and perceived behavioral control (PBC). ATT and SN had a positive and significant influence, explaining 90% (R² = 0.90) of the farmers’ intentions toward sustainability adoption. The lack of influence of the PBC construct suggests that farmers perceive themselves as having limited ability to adopt sustainability practices, mainly attributed to a lack of knowledge and financial resources, low self-confidence, and a heavy reliance on others for the implementation of sustainability actions. Full article

Abstract: Fibromyalgia (FM), a chronic disease with a high incidence in women, poses a significant challenge for diagnosis and treatment, especially due to the absence of specific biomarkers and the multifaceted nature of its symptoms, which range from neuromuscular pain to mood disorders and intestinal dysbiosis. While diagnosis currently relies on rheumatological clinical evaluations and treatment options mainly focus on symptom management, FM seems to have possible links with systemic metabolic dysfunctions with a common inflammatory root. In this context, a new therapeutic avenue emerges: could a therapeutic nutritional approach be the missing piece of the puzzle? Indeed, diet therapies employed particularly for metabolic syndromes proved recently to be efficacious for correcting systemic dysmetabolism and a high number of chronic inflammation conditions. In particular, the very-low-calorie ketogenic diet (VLCKD) demonstrated therapeutic benefits in many disorders. In the present study, we aimed to investigate the specific effects of two dietary interventions, namely the oloproteic VLCKD and the low-glycemic insulinemic (LOGI) diet, on two groups of female FM patients (FM1 and FM2) over a 45-day period. Utilizing clinical and laboratory tests, as well as non-invasive NMR metabolomic analysis of serum, urine, and saliva samples, we sought to uncover how these dietary regimens impact the metabolic dysfunctions associated with FM. Full article

Crown ethers are famous for the highly selectively grab Sr(II) from concentrated nitric acid solution due to the size match, but they suffer from the high leakage into the liquid phase caused by the presence of a large number of hydrophilic groups. To reduce their leakage, two novel porous silica-based adsorbents, (DtBuCH18C6 + Dodec)/SiAaC-g-ABSA and (DtBuCH18C6 + Dodec)/SiAaC-g-3-ABSA, were prepared by vacuum impregnation with organic contents of about 55.9 wt.% and 56.1 wt.%, respectively. The two adsorbents have good reusability and structural stability, and the total organic carbon leakage rates in 2 M HNO₃ solution are lower than 0.56 wt.% and 0.29 wt.%, respectively. Batch adsorption experiments revealed that the two adsorbents possessed good adsorption selectivity towards Sr, with SF_Sr/M over 40, except that of SF_Sr/Ba in 2 M HNO₃ solution. The adsorption equilibrium of Sr in 2 M HNO₃ solution was reached within 1 h, with saturated adsorption capacities of 36.9 mg/g and 37.5 mg/g, respectively. Furthermore, the XPS results indicate that the adsorption mechanism is the coordination of the crown ether ring with Sr. This work not only develops two novel adsorbents for the separation of Sr in nitric acid environments; it also provides a method for effectively reducing the water solubility of crown ethers. Full article

Contemporary architecture is shaped by the paradigm of sustainability and is characteristic of many solutions determined by a relevant set of principles related to shaping the environment based on the ecology of systems focused on the flow of energy. These design principles concern gaining energy from renewable resources, protection against the loss of thermal energy from buildings, protection against the excess of thermal energy in buildings, and proper distribution of thermal energy in buildings. This paper presents a proposal for a method to analyze some building components used as sustainability-related elements given their formal similarity to historic architectural details or some artworks integrated with buildings. It aims to emphasize the potential of a different perspective from which to perceive and assess buildings, and specifically their architectural details, given their spatial and aesthetic values associated with sustainable technical solutions. This study is based on a few differentiated examples. It proves the relations mentioned above true, given the sustainability paradigm epitomized in technical solutions to contemporary buildings and the related aesthetic features characterizing the relevant architectural detailing. Such a perception of buildings is intended to promote unconventional viewing and assessment of them by the public and professionals in the area of architecture and art. It would make them discover new types of aesthetic values, which are usually invisible. Full article

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity. Full article

This paper presents an efficient integrated multidisciplinary design optimization method for shaping a high-pressure cooling turbine blade in aero engines. This approach utilizes a novel regression/interpolation combination surrogate model (R/ICSM), facilitating comprehensive design optimization through collaborative coupling feature parameterization modeling and numerical simulation analysis across various disciplines. The optimized blade adjusts the load distribution on its surface, effectively eliminating flow separation at the tip and trailing edge. Notably, the optimized blade achieves a 0.69% increase in isentropic efficiency while satisfying aerodynamic, strength, and structural constraints. This highlights the effectiveness and progressiveness of the multidisciplinary design optimization method for a cooling turbine blade based on the R/ICSM in enhancing overall performance. It offers a novel and feasible approach for turbine blade design optimization and provides valuable insights for future research and applications. Full article

This article aims at addressing the future challenges in Sustainability and Information Technology (IT) by reversing the order of the conventional prioritization of social objectives and technology, and placing the aim first and the means second. In engineering and technology, historically, there has been greater focus on first developing the technologies (means) and then determining their potential (aim), and how to tame their unintended consequences. The greatest challenge confronting humanity in the coming decades is sustainability. Therefore, the question is how can IT design, develop, and assist in maintaining the ambitious, albeit difficult to grasp, sustainability agenda? This discussion is pertinent in order to avoid research programs and academic curriculum which dive into the intricacies of IT without viewing sustainability as a core value, which ultimately risks replicating the historical pattern that will generate even more unsustainability. Full article

Landscape occupation and green space reduction have decreased livability and hindered the sustainable development of cities. The urban landscape affects the quality of life and physical and mental state of the public, and urban underground space utilization is important for improving the urban landscape. Therefore, underground space utilization must be explored from a public perspective. Referring to typical underground municipal, transportation, and public space projects, an online questionnaire survey of 377 Nanjing residents was performed to construct a structural equation model investigating their perceptions and preferences regarding underground space usage to improve the landscape, focusing on the links between their preferences and opinions. Underground works that provide diverse open spaces were considered to have the most positive impact on the landscape (82.8%). The aesthetic value of the surface landscape (83.5%) and the vitality of historical sites (82.1%) were the most significantly affected, whereas stock underground space had no significant effect on landscape protection. In terms of age, profession, and place of work, the respondents demonstrated heterogeneous preferences. These findings indicate that targeted publicity and public participation are important to strengthen the cooperative utilization of space and realize the potential of the underground space, helping address actual requirements and develop sustainable cities. Full article

With the growing integration of the Internet of Things in smart buildings, it is crucial to ensure the precise implementation and operation of wireless sensor networks (WSNs). This paper aims to study the implementation aspect of WSNs in a commercial multi-story building, specifically addressing the difficulty of dealing with the variable environmental conditions on each floor. This research addresses the disparity between simulated situations and actual deployments, offering valuable insights into the potential to significantly improve the efficiency and responsiveness of building management systems. We obtain real-time sensor data to analyze and evaluate the system’s performance. Our investigation is grounded in the growing importance of incorporating WSNs into buildings to create intelligent environments. We provide an in-depth analysis for scrutinizing the disparities and commonalities between the datasets obtained from real-world deployments and simulation. The results obtained show the significance of accurate simulation models for reliable data representation, providing a roadmap for further developments in the integration of WSNs into intelligent building scenarios. This research’s findings highlight the potential for optimizing living and working conditions based on the real-time monitoring of critical environmental parameters. This includes insights into temperature, humidity, and light intensity, offering opportunities for enhanced comfort and efficiency in intelligent environments. Full article

Abstract: The care needs of children and adolescents with type 1 diabetes and their families are frequently approached as if they were identical to those of adults, overlooking the distinct challenges young people may face. It has been stated that children and adolescents often find conventional conversations with diabetes specialists tiresome and unpleasant. The present study focuses on familial experiences of an advanced carbohydrate counting program tailored to children and adolescents. The data encompass semi-structured interviews with families who participated in a group-based child-centered advanced carbohydrate counting program. The analysis revealed five themes: (1) peer-to-peer interaction is an essential determinant of sharing and learning; (2) illness perception significantly influences dietary intake; (3) normalization of diabetes in everyday life eases the disease burden; (4) repetition of dietary knowledge is important for retention; and (5) creating a safe and playful learning environment is crucial to engaging children and adolescents in their own treatment. The present findings suggest that it would be beneficial to explore and consider alternative teaching approaches that are adapted to a more interactive and engaging learning environment that is specifically tailored to children and adolescents. This entails moving away from traditional individual approaches. Full article

Object detection in computer vision requires a sufficient amount of training data to produce an accurate and general model. However, aerial images are difficult to acquire, so the collection of aerial image datasets is a priority issue. Building on the existing research on image generation, the goal of this work is to create synthetic aerial image datasets that can be used to solve the problem of insufficient data. We generated three independent datasets for ship detection using engine and generative model. These synthetic datasets are rich in virtual scenes, ship categories, weather conditions, and other features. Moreover, we implemented domain-adaptive algorithms to address the issue of domain shift from synthetic data to real data. To investigate the application of synthetic datasets, we validated the synthetic data using six different object detection algorithms and three existing real-world, ship detection datasets. The experimental results demonstrate that the methods for generating synthetic aerial image datasets can complete the insufficient data in aerial remote sensing. Additionally, domain-adaptive algorithms could further mitigate the discrepancy from synthetic data to real data, highlighting the potential and value of synthetic data in aerial image recognition and comprehension tasks in the real world. Full article

In order to gain insight into the influence of grain size on precipitation thermodynamics, bulk materials of coarse-grained (CG), ultrafine-grained (UFG) (with or without dislocations), and nanocrystalline (NC) 7075 Al alloy have been fabricated by solid solution treatment, equal-channel angular pressing (ECAP), or high-pressure torsion (HPT) processes. The precipitation behavior and the corresponding thermal phenomenon were studied by transmission electron microscopy (TEM) and differential scanning calorimetry (DSC) heating. The results indicated that there are significant differences in precipitation thermodynamics among the four bulk materials. In the CG and UFG materials without dislocations, homogeneous nucleation is the primary precipitation mechanism. However, the nucleation of the GP zones is suppressed at lower temperatures due to a reduction in the number of residual vacancies and the supersaturation in the UFG interiors. This is attributed to the absorption of vacancies and solute atoms by a greater volume of grain boundaries. It can be observed that the greater the excess of vacancies remaining in grain interiors, the lower the temperature at which nucleation of GP zones occurs. Defect-assisted heterogeneous nucleation was identified as the predominant precipitation mechanism in the UFG materials with dislocations and the NC materials. These defects encompass dislocations, lattice distortions, and grain boundaries. The decomposition processes of solid solutions were found to be almost complete at a lower temperature. The presence of dislocations, lattice distortions, and grain boundaries enables solute atoms to diffuse at a much faster rate, significantly enhancing the precipitation rate and reducing the nucleation and formation energies of various precipitate phases. Full article

The plant MADS-box transcription factor family is a major regulator of plant flower development and reproduction, and the AGAMOUS-LIKE11/SEEDSTICK (AGL11/STK) subfamily plays conserved functions in the seed development of flowering plants. Camellia japonica is a world-famous ornamental flower, and its seed kernels are rich in highly valuable fatty acids. Seed abortion has been found to be common in C. japonica, but little is known about how it is regulated during seed development. In this study, we performed a genome-wide analysis of the MADS-box gene the in C. japonica genome and identified 126 MADS-box genes. Through gene expression profiling in various tissue types, we revealed the C/D-class MADS-box genes were preferentially expressed in seed-related tissues. We identified the AGL11/STK-like gene, CjSTK, and showed that it contained a typical STK motif and exclusively expressed during seed development. We found a significant increase in the CjSTK expression level in aborted seeds compared with normally developing seeds. Furthermore, overexpression of CjSTK in Arabidopsis thaliana caused shorter pods and smaller seeds. Taken together, we concluded that the fine regulation of the CjSTK expression at different stages of seed development is critical for ovule formation and seed abortion in C. japonica. The present study provides evidence revealing the regulation of seed development in Camellia. Full article

Background: Liver cirrhosis (LC) is one of the most significant causes of morbidity and mortality in patients with chronic liver disease worldwide. Nutrition may be an important component of primary prevention of chronic liver disease. Diet–exercise patterns frame the eating behaviors and exercise habits of people through statistical methods related to nutritional epidemiology, which can explore the relationship between living habits and diseases among diverse populations. The purpose of this study was to explore the association between diet–exercise patterns and cirrhosis, and provide guidance on preventive diets for liver patients. Methods: This study identified diet–exercise patterns via clustering analysis of principal components and assessed their association with cirrhosis through the population samples of the National Health and Nutrition Examination Survey (NHANES) from 2017 to March 2020. Results: We identified two diet–exercise patterns that were named the “prudent pattern” (consumption of various staple foods, eggs, meat, fruits and vegetables; less sedentary) and the “dangerous pattern” (higher consumption of desserts, nuts, milk, meat, alcoholic beverages; recreational activities). The t-test demonstrated a significant relationship between patterns and multiple foods. The simple logistic regression test showed a lower risk of cirrhosis in those in the “prudent pattern” (OR = 0.73, 95%CI = 0.59–0.93). Conclusions: Two diet–exercise patterns associated with cirrhosis were identified: “prudent pattern” and “dangerous pattern”. The results of this study may be useful for suggesting preventive diets for people at risk of cirrhosis. Full article

Abstract: Semantic generation of network access control policies can help network administrators accurately implement policies to achieve desired security objectives. Current semantic generation research mainly focuses on semantic generation of single grammar and lacks work on automatically generating semantics for different grammatical strategies. Generating semantics for different grammars is a tedious, inefficient, and non-scalable task. Inspired by sequence labeling in the field of natural language processing, this article models automatic semantic generation as a sequence labeling task. We propose a semantic generation algorithm named ADLBiLSTM. The algorithm uses a self-attention mechanism and double-layer BiLSTM to extract the features of security policies from different aspects, so that the algorithm can flexibly adapt to policies of different complexity without frequent modification. Experimental results showed that the algorithm has good performance and can achieve high accuracy in semantic generation of access control list (ACL) and firewall data and can accurately understand and generate the semantics of network access control policies. Full article

The paper presents a method for determining the dynamic response of systems containing viscoelastic damping elements with uncertain design parameters. A viscoelastic material is characterized using classical and fractional rheological models. The assumption is made that the lower and upper bounds of the uncertain parameters are known and represented as interval values, which are then subjected to interval arithmetic operations. The equations of motion are transformed into the frequency domain using Laplace transformation. To evaluate the uncertain dynamic response, the frequency response function is determined by transforming the equations of motion into a system of linear interval equations. Nevertheless, direct interval arithmetic often leads to significant overestimation. To address this issue, this paper employs the element-by-element technique along with a specific transformation to minimize redundancy. The system of interval equations obtained is solved iteratively using the fixed-point iteration method. As demonstrated in the examples, this method, which combines the iterative solving of interval equations with the proposed technique of equation formulation, enables a solution to be found rapidly and significantly reduces overestimation. Notably, this approach has been applied to systems containing viscoelastic elements for the first time. Additionally, the proposed notation accommodates both parallel and series configurations of damping elements and springs within rheological models. Full article

To address the issues of high cost, low welding efficiency, and complex processes in vacuum brazing, we proposed a method of electromagnetic ultrasonic (EU)-assisted brazing with Al-12Si solder to join SiC ceramic and TC4 alloy. The results showed that the maximum magnetic induction strength (MIS) on the surface of the liquid solder was 0.629 T when subjected to a static and alternating magnetic field (MF). Additionally, the combined action of MF and eddy current generated a downward Lorentz force (LF) in the liquid solder, with the maximum LF in the horizontal and vertical directions being 48.91 kN m⁻³ and 60.93 kN m⁻³, respectively. Under the influence of an EU wave, the liquid solder exhibited capillary filling (CF) behavior. At 26 ms, the maximum length of CF was 12.21 mm. Full article

The opacity of the impact investment decision-making process is one of the main constraints hampering further growth in the impact investing ecosystem. This paper takes a differentiated view on why (investment motivation) and how (investment decision criteria) the major private impact investor types allocate funding to investees. We incorporate insights from 34 interviews with the five major impact investor types: social business angels, foundations, social banks, impact investment funds, and crowdvesting platforms. We find that motivation and decision-making significantly differ between the impact investor types, especially concerning strict vs. ambiguous impact definitions, active vs. passive investment approaches, and return requirements reaching from capital preservation to market-driven returns. By providing a differentiated overview of the investor type-specific motivations and most important investment criteria, our study offers social entrepreneurs a roadmap to identify the most appropriate impact investors for their business model. Full article

Biomass combustors provide space heating by converting chemical energy in woody biomass into low-temperature thermal energy. Thermoelectric generators (TEGs) can generate electricity from the heat flux without significantly reducing heating performance. However, most current TEGs are small (40 mm × 40 mm), requiring many TEG elements to generate useful power from a biomass combustion-based space heater. This work compares the electrical generation potential of an array of small TEGs with a larger (80 mm × 120 mm) TEG in a vertical configuration representative of a residential heating appliance. An experimental facility was developed for various representative cold-side ducts and controllable hot-side temperature and cooling airflows, and the Taguchi method was used to evaluate the impacts of temperature, airspeed, and ducting configurations. The results indicate that temperature and airspeed significantly influence TEG power, while ducting configurations have an insignificant influence. The large TEG achieved more consistent temperatures but produced lower power than an array of smaller TEGs with the same total area. The study emphasizes optimizing TEG design and operating conditions to enhance electricity generation efficiency in space heating combustors. Full article

There is a mutual causal relationship between population shrinkage and the level of regional social–economic–ecological development and their coordinated development. It is of great significance to reveal the correlation effect between population shrinkage and regional development for the adjustment and optimization of the relationship between regional population and social, economic and ecological development. Taking 142 counties in the three provinces of Northeast China as samples, the population contraction was identified and classified in different segments, and a comprehensive evaluation index system was constructed. The entropy method, coupled coordination model, grey correlation degree model, bivariate spatial autocorrelation model and other analysis methods were used. This paper measures the level of social, economic, ecological and synthetical development and the coordination degree among the three in different periods, and it analyzes the spatio-temporal correlation with population shrinkage. The obstacle degree model is used to analyze the main factors affecting the coordinated development under different population shrinkage levels. The results show that: (1) The number of counties with a shrinking population accounted for 57.04% from 2000 to 2010, showing a “Nearly half of the increase and half of the decrease” situation; from 2010 to 2020, the number of counties with population contraction type accounted for 99.3%, and the region entered a state of comprehensive contraction, and the contraction amplitude increased significantly. (2) From 2000 to 2010, the degree of population shrinkage was negatively correlated with the level of social, economic, synthetical and coordinated development but positively correlated with the level of ecological development. From 2010 to 2020, the degree of population shrinkage was still negatively correlated with the level of social, economic, synthetical and coordinated development, but it is not significantly correlated with the level of ecological development. During the study period, the correlation between population shrinkage and social development level was strong, while that between population shrinkage and ecological development level was weak. (3) During the study period, the social and economic system factors were the main obstacles in the process of coordinated development. From 2000 to 2010, the common important obstacle factors of the three types of population shrinkage level counties were the number of industrial enterprises above designated size, average night light index and gross regional product, and the common main obstacle factor was population density. From 2010 to 2020, the common important obstacle factors of the three types of population shrinking counties were the number of industrial enterprises above designated size and the per capita balance of loans from financial institutions at the end of the year, and the obstacle levels of indicators in different types of population shrinking counties are significantly different. Full article

Glaucoma refers to a spectrum of progressive optic neuropathies and remains the leading cause of irreversible blindness worldwide. Its insidious onset poses serious challenges to conventional diagnostic methods and clinicians striving to detect early-stage disease for timely and effective intervention. Artificial intelligence (AI) has demonstrated its ability to process and analyze large datasets which can help identify subtle changes in early glaucomatous clinical presentation. This study reviews the current state of AI utilization in glaucoma and elucidates the strengths and limitations of existing approaches. We dissect the role of AI in various domains: enhancing early detection and diagnosis, monitoring disease progression, and refining treatment strategies to optimize patient outcomes. Furthermore, we address the ethical, legal, and social implications, alongside the inherent limitations of AI in the clinical setting. Despite these challenges, AI holds transformative potential for glaucoma management. Future directions emphasize the need for interdisciplinary collaboration, advanced and explainable algorithm development, and equitable healthcare access to fully realize the promise of AI in combating this vision-threatening condition. Full article