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22 pages, 314 KiB  
Article
Informal Home Care in the Digital Transformation: Platform Design and Work Ethics of Care
by Anna Katharina Korn
Soc. Sci. 2025, 14(4), 225; https://doi.org/10.3390/socsci14040225 (registering DOI) - 3 Apr 2025
Abstract
With the aging society in Germany, the demand for informal care in private households is rising. This has led to a growing market for digital platforms that broker informal care services. Research shows that workers in elderly care, as a sub-sector of care [...] Read more.
With the aging society in Germany, the demand for informal care in private households is rising. This has led to a growing market for digital platforms that broker informal care services. Research shows that workers in elderly care, as a sub-sector of care work, often embody a work ethic centered on caring and helpfulness. However, this strong ethic can result in self-exploitation. Despite prior insights, the mediating role of digital platforms and their repercussions on work ethics remain underexplored. Therefore, this article asks how workers’ ethics of care unfold within the design of platforms in platform-mediated care. Ten narrative-oriented, in-depth interviews with platform workers on two platforms were conducted. Findings reveal that care workers in this field of platform work have a work ethic of care strongly oriented towards identification with the role of caregiver and the needs of the client. The open and unstructured design of these platforms—where worker qualifications are rarely verified to attract large numbers—devalues and informalizes care work. The lack of recognition as a legitimate profession perpetuates the perception of care work as unskilled, diminishing its professional status and fostering feelings of unprofessionalism and self-exploitation. Full article
(This article belongs to the Special Issue Informal Care in the Digital Space)
19 pages, 1643 KiB  
Review
The Role of Bacteria-Derived Hydrogen Sulfide in Multiple Axes of Disease
by Aleksandr Birg and Henry C. Lin
Int. J. Mol. Sci. 2025, 26(7), 3340; https://doi.org/10.3390/ijms26073340 (registering DOI) - 3 Apr 2025
Abstract
In this review article, we discuss and explore the role of bacteria-derived hydrogen sulfide. Hydrogen sulfide is a signaling molecule produced endogenously that plays an important role in health and disease. It is also produced by the gut microbiome. In the setting of [...] Read more.
In this review article, we discuss and explore the role of bacteria-derived hydrogen sulfide. Hydrogen sulfide is a signaling molecule produced endogenously that plays an important role in health and disease. It is also produced by the gut microbiome. In the setting of microbial disturbances leading to disruption of intestinal homeostasis (dysbiosis), the concentration of available hydrogen sulfide can also vary leading to pathologic sequelae. The brain–gut axis is the original studied paradigm of gut microbiome and host interaction. In recent years, our understanding of microbial and host interaction has expanded greatly to include specific pathways that have branched into their own axes. These axes share a principal concept of microbiota changes, intestinal permeability, and an inflammatory response, some of which are modulated by hydrogen sulfide (H2S). In this review, we will discuss multiple axes including the gut–immune, gut–heart, and gut–endocrine axes. We will evaluate the role of H2S in modulation of intestinal barrier, mucosal healing in intestinal inflammation and tumor genesis. We will also explore the role of H2S in alpha-synuclein aggregation and ischemic injury. Finally, we will discuss H2S in the setting of metabolic syndrome as int pertains to hypertension, atherosclerosis and glucose-like peptide-1 activity. Majority of studies that evaluate hydrogen sulfide focus on endogenous production; the role of this review is to examine the lesser-known bacteria-derived source of hydrogen sulfide in the progression of diseases as it relates to these axes. Full article
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38 pages, 6239 KiB  
Article
Computational Intelligence Approach for Fall Armyworm Control in Maize Crop
by Alex B. Bertolla and Paulo E. Cruvinel
Electronics 2025, 14(7), 1449; https://doi.org/10.3390/electronics14071449 (registering DOI) - 3 Apr 2025
Abstract
This paper presents a method for dynamic pattern recognition and classification of one dangerous caterpillar species to allow for its control in maize crops. The use of dynamic pattern recognition supports the identification of patterns in digital image data that change over time. [...] Read more.
This paper presents a method for dynamic pattern recognition and classification of one dangerous caterpillar species to allow for its control in maize crops. The use of dynamic pattern recognition supports the identification of patterns in digital image data that change over time. In fact, identifying fall armyworms (Spodoptera frugiperda) is critical in maize production, i.e., in all of its growth stages. For such pest control, traditional agricultural practices are still dependent on human visual effort, resulting in significant losses and negative impacts on maize production, food security, and the economy. Such a developed method is based on the integration of digital image processing, multivariate statistics, and machine learning techniques. We used a supervised machine learning algorithm that classifies data by finding an optimal hyperplane that maximizes the distance between each class of caterpillar with different lengths in N-dimensional spaces. Results show the method’s efficiency, effectiveness, and suitability to support decision making for this customized control context. Full article
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21 pages, 5625 KiB  
Article
Characteristics and Influencing Factors of Cropland Function Trade-Off in Highly Urbanized Areas: Insights from the Yangtze River Delta Region in China
by Jieyi Tao, Jinhe Zhang, Ping Dong, Yuqi Lu, Xiaobin Ma, Zipeng Zhang, Yingjia Dong and Peijia Wang
Agronomy 2025, 15(4), 894; https://doi.org/10.3390/agronomy15040894 (registering DOI) - 3 Apr 2025
Abstract
Exploring the characteristics of changes in cropland function trade-off and the influencing factors in highly urbanized areas can promote the synergistic development of urbanization and fine cropland management. Taking the Yangtze River Delta region as the study area, this paper developed a cropland [...] Read more.
Exploring the characteristics of changes in cropland function trade-off and the influencing factors in highly urbanized areas can promote the synergistic development of urbanization and fine cropland management. Taking the Yangtze River Delta region as the study area, this paper developed a cropland function evaluation system from the production–ecology–living perspective, identified the spatial and temporal changes in cropland function trade-offs through Wavelet analysis and Root mean square error, and explored the driving factors of the trade-offs by using GeoDetector. The results indicated the following: (1) The cropland function in the Yangtze River Delta region has undergone a transition from a single production function to a composite function integrating ecology and life in conjunction with urbanization. The trade-offs between cropland functions are weakened, and the rate of decline from 2010 to 2023 is significantly higher than that from 2000 to 2010, and the characterization of cropland in different types of cities is revealed. (2) The turning points of cropland function trade-off changes in cities of different scales diverge, with the inflection points of small and medium-sized cities and large cities shrinking toward the center (decreasing from 42–48 km to 30–36 km), and metropolises showing an obvious trend of outward expansion (expanding from 42 km to 60 km). (3) The influence of natural and socioeconomic factors on cropland function trade-off intensity generally increases over time, with socioeconomic factors increasingly becoming significant drivers of the trade-off intensities. It is recommended that the study area focus on developing cropland characterization in different types of cities in the future, and continue to improve the degree of sharing the integration of profits from cropland functions, so as to promote optimal development. Full article
(This article belongs to the Section Farming Sustainability)
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23 pages, 3342 KiB  
Case Report
A Novel Approach to Engaging Communities Through the Use of Human Behaviour Change Models to Improve Companion Animal Welfare and Reduce Relinquishment
by Natalie Powdrill-Wells, Chris Bennett, Fiona Cooke, Suzanne Rogers and Jo White
Animals 2025, 15(7), 1036; https://doi.org/10.3390/ani15071036 (registering DOI) - 3 Apr 2025
Abstract
Experts consider tackling companion animal ownership problems, such as delayed veterinary treatment and a lack of appropriate care provision, to be key in striving towards improved animal welfare. Additionally, every year, millions of companion animals are relinquished to rescue centres globally; a process [...] Read more.
Experts consider tackling companion animal ownership problems, such as delayed veterinary treatment and a lack of appropriate care provision, to be key in striving towards improved animal welfare. Additionally, every year, millions of companion animals are relinquished to rescue centres globally; a process that can be distressing for both people and animals. By adapting traditional shelter model activity, it is possible to develop proactive community interventions to provide support for companion animal owners prior to crisis points and therefore, prevent suffering. This case report shares a novel approach to improving companion animal welfare and reducing avoidable relinquishment in communities. As part of a three-stage process, a mixed-method approach was applied to build an understanding of the needs of owners of potentially vulnerable companion animals in the target community. The research stages revealed that the lack of timely veterinary treatment for pets within the target community represented a welfare concern. Based upon this understanding, a co-creation approach was deployed to design targeted interventions to improve companion animal welfare in the community through the application of human behaviour change theories. The process revealed the operational effectiveness of a co-creation approach to intervention design in the context of improving animal welfare. This novel approach has demonstrated significant value in addressing the needs of pet-owning communities. Full article
(This article belongs to the Section Companion Animals)
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14 pages, 2334 KiB  
Article
Brain Volume Measures in Adults with MOG-Antibody-Associated Disease: A Longitudinal Multicenter Study
by Riccardo Orlandi, Sara Mariotto, Francesca Gobbin, Francesca Rossi, Valentina Camera, Massimiliano Calabrese, Francesca Calabria and Alberto Gajofatto
J. Clin. Med. 2025, 14(7), 2445; https://doi.org/10.3390/jcm14072445 (registering DOI) - 3 Apr 2025
Abstract
Background/Objectives: Little is known about the impact of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) on brain atrophy. This multicenter longitudinal study compares brain MRI volumes and T2 lesion volume between MOGAD patients, relapsing-remitting MS (RRMS) patients and a healthy control (HC) group [...] Read more.
Background/Objectives: Little is known about the impact of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) on brain atrophy. This multicenter longitudinal study compares brain MRI volumes and T2 lesion volume between MOGAD patients, relapsing-remitting MS (RRMS) patients and a healthy control (HC) group with brain MRI scans available from an online repository. Methods: In total, 16 adult MOGAD patients (9 F) were age- and sex-matched with 44 RRMS patients (17 F) recruited in Verona MS Center and 14 HC subjects. The availability of two brain MRI scans performed 18 ± 6 months apart was mandatory for each patient. Annual percentage brain volume change (PBVC/y), baseline global brain, white matter (WM), gray matter (GM) regional brain volumes and T2 lesion volume were compared between groups. Results: PBVC/y was lower in MOGAD than in RRMS patients (p = 0.014) and lower in HC subjects than in MS patients (p = 0.005). Overall, MOGAD showed higher mean global brain (p = 0.012) and WM volume (p = 0.024) but lower median T2 lesion volume at timepoint 1 (p < 0.001); T2 lesion volume increased over time in the RRMS (p < 0.001) but not in the MOGAD cohort (p = 0.262). Conclusions: The structural brain MRI features of MOGAD show higher global brain and WM volumes and lower brain volume loss over time compared to RRMS, suggesting different underlining pathogenetic mechanisms. Full article
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17 pages, 4041 KiB  
Article
Characterization and Biological Evaluation of Composite Nanofibrous Membranes Prepared from Hemp Salmon (Oncorhynchus keta) Skin Collagen
by Yu Liu, Mochi Zhu, Rui Duan and Junjie Zhang
Cells 2025, 14(7), 537; https://doi.org/10.3390/cells14070537 (registering DOI) - 3 Apr 2025
Abstract
Aquatic collagen, a natural macromolecule protein with excellent biocompatibility, has attracted attention in the field of medical materials. Compared to mammalian collagen, aquatic collagen offers unique advantages, including the absence of zoonotic disease risks and religious concerns. In this study, salmon skin collagen [...] Read more.
Aquatic collagen, a natural macromolecule protein with excellent biocompatibility, has attracted attention in the field of medical materials. Compared to mammalian collagen, aquatic collagen offers unique advantages, including the absence of zoonotic disease risks and religious concerns. In this study, salmon skin collagen nanofiber membrane (GS) was prepared by electrostatic spinning. Then, skin collagen was combined with silk sericin (SS) and sodium hyaluronate (HA) to fabricate composite collagen nanofiber membrane (GF) using electrostatic spinning technology. GF membranes were further cross-linked (GFL) for use in a mouse wound healing model. The physicochemical properties and biocompatibility of GS, GF, and GFL were evaluated. FTIR analysis revealed that GFL exhibited a more stable secondary structure compared to GS and GF. DSC and TGA results indicated that GFL had the highest thermal stability, followed by GF. Cytotoxicity tests confirmed that GS, GF, and GFL were non-cytotoxic, with GF showing the highest cell viability rate of 175.23 ± 1.77%. In the wound healing model, GFL group achieved nearly complete healing by day 14 (98 ± 0.1%), compared to 76.04 ± 0.01% in the blank group. Measurement of TGF-β1 and VEGF levels in the healing tissue on day 14 indicated that the GFL group had progressed to the late stage of healing, whereas the blank group remained in the early stage. These results suggest that GFL holds significant potential as a medical biomaterial for wound healing applications. Full article
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22 pages, 8528 KiB  
Article
MSEA-Net: Multi-Scale and Edge-Aware Network for Weed Segmentation
by Akram Syed, Baifan Chen, Adeel Ahmed Abbasi, Sharjeel Abid Butt and Xiaoqing Fang
AgriEngineering 2025, 7(4), 103; https://doi.org/10.3390/agriengineering7040103 (registering DOI) - 3 Apr 2025
Abstract
Accurate weed segmentation in Unmanned Aerial Vehicle (UAV) imagery remains a significant challenge in precision agriculture due to environmental variability, weak contextual representation, and inaccurate boundary detection. To address these limitations, we propose the Multi-Scale and Edge-Aware Network (MSEA-Net), a lightweight and efficient [...] Read more.
Accurate weed segmentation in Unmanned Aerial Vehicle (UAV) imagery remains a significant challenge in precision agriculture due to environmental variability, weak contextual representation, and inaccurate boundary detection. To address these limitations, we propose the Multi-Scale and Edge-Aware Network (MSEA-Net), a lightweight and efficient deep learning framework designed to enhance segmentation accuracy while maintaining computational efficiency. Specifically, we introduce the Multi-Scale Spatial-Channel Attention (MSCA) module to recalibrate spatial and channel dependencies, improving local–global feature fusion while reducing redundant computations. Additionally, the Edge-Enhanced Bottleneck Attention (EEBA) module integrates Sobel-based edge detection to refine boundary delineation, ensuring sharper object separation in dense vegetation environments. Extensive evaluations on publicly available datasets demonstrate the effectiveness of MSEA-Net, achieving a mean Intersection over Union (IoU) of 87.42% on the Motion-Blurred UAV Images of Sorghum Fields dataset and 71.35% on the CoFly-WeedDB dataset, outperforming benchmark models. MSEA-Net also maintains a compact architecture with only 6.74 M parameters and a model size of 25.74 MB, making it suitable for UAV-based real-time weed segmentation. These results highlight the potential of MSEA-Net for improving automated weed detection in precision agriculture while ensuring computational efficiency for edge deployment. Full article
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20 pages, 1701 KiB  
Review
Translational Regulators in Pulmonary Fibrosis: MicroRNAs, Long Non-Coding RNAs, and Transcript Modifications
by Sumeen Kaur Gill and Richard H. Gomer
Cells 2025, 14(7), 536; https://doi.org/10.3390/cells14070536 (registering DOI) - 3 Apr 2025
Abstract
Fibrosing disorders including idiopathic pulmonary fibrosis (IPF) are progressive irreversible diseases, often with poor prognoses, characterized by the accumulation of excessive scar tissue and extracellular matrix. Translational regulation has emerged as a critical aspect of gene expression control, and the dysregulation of key [...] Read more.
Fibrosing disorders including idiopathic pulmonary fibrosis (IPF) are progressive irreversible diseases, often with poor prognoses, characterized by the accumulation of excessive scar tissue and extracellular matrix. Translational regulation has emerged as a critical aspect of gene expression control, and the dysregulation of key effectors is associated with disease pathogenesis. This review examines the current literature on translational regulators in IPF, focusing on microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and RNA transcript modifications including alternative polyadenylation and chemical modification. Some of these translational regulators potentiate fibrosis, and some of the regulators inhibit fibrosis. In IPF, some of the profibrotic regulators are upregulated, and some of the antifibrotic regulators are downregulated. Correcting these defects in IPF-associated translational regulators could be an intriguing avenue for therapeutics. Full article
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17 pages, 852 KiB  
Review
A Review of Multimodal Interaction in Remote Education: Technologies, Applications, and Challenges
by Yangmei Xie, Liuyi Yang, Miao Zhang, Sinan Chen and Jialong Li
Appl. Sci. 2025, 15(7), 3937; https://doi.org/10.3390/app15073937 (registering DOI) - 3 Apr 2025
Abstract
Multimodal interaction technology has become a key aspect of remote education by enriching student engagement and learning results as it utilizes the speech, gesture, and visual feedback as various sensory channels. This publication reflects on the latest breakthroughs in multimodal interaction and its [...] Read more.
Multimodal interaction technology has become a key aspect of remote education by enriching student engagement and learning results as it utilizes the speech, gesture, and visual feedback as various sensory channels. This publication reflects on the latest breakthroughs in multimodal interaction and its usage in remote learning environments, including a multi-layered discussion that addresses various levels of learning and understanding. It showcases the main technologies, such as speech recognition, computer vision, and haptic feedback, that enable the visitors and learning portals to exchange data fluidly. In addition, we investigate the function of multimodal learning analytics in order to measure the cognitive and emotional states of students, targeting personalized feedback and refining instructional strategies. Though multimodal communication may bring a historical improvement to the mode of online education, the platform still faces many issues, such as media synchronization, higher computational demand, physical adaptability, and privacy concerns. These problems demand further research in the fields of algorithm optimization, access to technology guidance, and the ethical use of big data. This paper presents a systematic review of the application of multimodal interaction in remote education. Through the analysis of 25 selected research papers, this review explores key technologies, applications, and challenges in the field. By synthesizing existing findings, this study highlights the role of multimodal learning analytics, speech recognition, gesture-based interaction, and haptic feedback in enhancing remote learning. Full article
(This article belongs to the Special Issue Current Status and Perspectives in Human–Computer Interaction)
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16 pages, 4555 KiB  
Article
Statistical Approach for the Imputation of Long-Term Seawater Data Around the Korean Peninsula from 1966 to 2021
by Myeong-Taek Kwak, Kyunghwan Lee, Hyi-Thaek Ceong and Seungwon Oh
Water 2025, 17(7), 1066; https://doi.org/10.3390/w17071066 (registering DOI) - 3 Apr 2025
Abstract
Climate change is a global phenomenon that significantly impacts the ocean environment around the Korean Peninsula. These changes in climate can lead to rising sea temperatures, thereby significantly affecting marine life and ecosystems in the region. In this study, four statistical approaches were [...] Read more.
Climate change is a global phenomenon that significantly impacts the ocean environment around the Korean Peninsula. These changes in climate can lead to rising sea temperatures, thereby significantly affecting marine life and ecosystems in the region. In this study, four statistical approaches were employed to analyze ocean characteristics around the Korean Peninsula: layer classification, imputation for replacing missing values, evaluation using statistical tests, and trend analysis. The trend model we used was a deep learning-based seasonal-trend decomposition using Loess, a piecewise regression module with change points in 2000 and 2009, and Fourier transform to calculate the seasonality of one year. In addition, the water temperature was considered to have a Gaussian distribution so that anomalous water temperatures could be detected through confidence intervals. The ocean was first classified into three layers (surface layer, middle layer, and bottom layer) to characterize the sea area around Korea, after which multiple imputation methods were employed to replace missing values for each layer. The imputation method exhibiting the best performance was then selected by comparing the replaced missing values with high-quality data. Additionally, we compared the slope of the water temperature change around the Korean Peninsula based on two temporal inflection points (2000 and 2009). Our findings demonstrated that the long-term change in water temperature aligns with previous studies. However, the slope of the water temperature change has tended to accelerate since 2009. Full article
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21 pages, 1243 KiB  
Article
Unveiling Dynamic Capabilities in Public Procurement: Myths, Realities, and Strategic Transformation
by Vera Ndrecaj, Issam Tlemsani and Mohamed Ashmel Mohamed Hashim
Adm. Sci. 2025, 15(4), 134; https://doi.org/10.3390/admsci15040134 (registering DOI) - 3 Apr 2025
Abstract
This study explores the application of the dynamic capabilities (DCs) sensing, seizing, and transforming in strategic public sector procurement (SPSP) and examines whether these capabilities represent a tangible reality or a conceptual myth. Drawing on qualitative data from six Welsh local authorities (WLAs), [...] Read more.
This study explores the application of the dynamic capabilities (DCs) sensing, seizing, and transforming in strategic public sector procurement (SPSP) and examines whether these capabilities represent a tangible reality or a conceptual myth. Drawing on qualitative data from six Welsh local authorities (WLAs), this research investigates the extent to which DCs enable organizations to navigate complex procurement environments and achieve strategic transformation. The findings reveal significant variations in the operationalization of DCs. Larger authorities demonstrated robust sensing and seizing capabilities, leveraging market intelligence, collaborative initiatives, and innovative procurement strategies to align with broader organizational objectives. Conversely, smaller authorities faced institutional barriers, such as resource limitations and leadership turnover, which hindered their ability to implement and sustain DCs effectively. While transformative initiatives, including category management and innovative service models, were evident in some cases, challenges in leadership stability and cultural adaptability limited their widespread application. This study highlights the gap between theoretical frameworks and practical implementation, emphasizing the need for tailored approaches to building DCs in diverse public sector contexts. By mapping procurement DCs and proposing an integrated conceptual framework, this research contributes to the literature on strategic management in public procurement and offers actionable insights for policymakers and practitioners. Future research should explore DCs in broader public sector settings. Full article
(This article belongs to the Section Strategic Management)
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22 pages, 8594 KiB  
Article
Prediction of Friction Torque in Paired Tapered Roller Bearings of Disc Cutter Under Tri-Axial Rock-Breaking Loads and Preload
by Gang Hu, Chaoyu Yang, Huanqiang Li, Haiming Zhao and Zhihao Zhang
Lubricants 2025, 13(4), 160; https://doi.org/10.3390/lubricants13040160 (registering DOI) - 3 Apr 2025
Abstract
The disc cutter is a key rock-breaking component of tunnel boring machines, and during operation, improper assembly preload often leads to uneven wear of the cutter. To study the effect of preload force on the friction torque of paired tapered roller bearings during [...] Read more.
The disc cutter is a key rock-breaking component of tunnel boring machines, and during operation, improper assembly preload often leads to uneven wear of the cutter. To study the effect of preload force on the friction torque of paired tapered roller bearings during rock-breaking, the transmission of preload and rock-breaking loads within the disc cutter structure is first analyzed, and a bearing load distribution model is established. Based on this model, a method for calculating the friction torque of the tapered roller bearings in the disc cutter, considering both external loads and preload force, is proposed. Next, finite element analysis is conducted to investigate the impact of preload displacement on preload force, and a relationship equation is derived using polynomial fitting. Finally, experiments on bearing preload displacement and friction torque are carried out under no-load conditions. The results show that the simulation results for the relationship between preload force and preload displacement are in good agreement with the experimental results. Additionally, the experimental results for the friction torque of the tapered roller bearings are close to the theoretical calculation results, with the overall trend matching, thus verifying the reliability of both the simulation and theoretical models. Full article
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13 pages, 1584 KiB  
Article
Managing Expectations and Predicting Willingness to Pay in Novel Healthy Foods Development in East Africa
by Alexander Mirzaei-Fard, Jesper Clement, John H. Muyonga, Olivia Janet Natocho, Josephine Kisakye, Susan Nchimbi-Msolla, Rashid Suleiman, Fulgence Mishili, Dasel Wambua Mulwa Kaindi and Sophia Ngala
Foods 2025, 14(7), 1258; https://doi.org/10.3390/foods14071258 (registering DOI) - 3 Apr 2025
Abstract
This study explores the factors influencing consumer willingness to pay (WTP) for novel, healthy, and locally produced food products in East Africa, focusing on sensory experiences and packaging design. Conducted in Tanzania, Uganda, and Kenya, the research includes two complementary studies: Study A [...] Read more.
This study explores the factors influencing consumer willingness to pay (WTP) for novel, healthy, and locally produced food products in East Africa, focusing on sensory experiences and packaging design. Conducted in Tanzania, Uganda, and Kenya, the research includes two complementary studies: Study A examines sensory evaluations (taste, texture, aroma, color, and general acceptance) as predictors of WTP, while Study B assesses the impact of visual packaging features (e.g., typography, illustrations, and product windows) on consumer perceptions and WTP. Study A highlights that general acceptance (GA) is the strongest predictor of WTP, driven primarily by taste, texture, and aroma, while visual sensory cues play a secondary role. In contrast, Study B demonstrates that packaging design features, such as product visibility and ingredient-focused imagery, significantly influence WTP, with health messaging increasing perceived value but locality cues reducing it, likely due to cultural biases against packaged local products. The results reveal a critical difference: WTP is more stable and predictable in sensory evaluations but more volatile in response to packaging designs, driven by consumer expectations. These findings underscore the importance of aligning sensory and visual attributes to understand consumer expectations and enhance WTP for innovative food products in emerging markets. Full article
(This article belongs to the Section Sensory and Consumer Sciences)
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13 pages, 277 KiB  
Article
A Preliminary Study on the Effect of an Intervention Based on Green Exercise on Mental Health and Physical Fitness of Adolescents
by Santiago Gómez-Paniagua, Carmen Galán-Arroyo, Antonio Castillo-Paredes and Jorge Rojo-Ramos
Healthcare 2025, 13(7), 809; https://doi.org/10.3390/healthcare13070809 (registering DOI) - 3 Apr 2025
Abstract
Background: The latest data on physical inactivity and mental health among adolescents raise concerns about the quality of life and development of young people. The expert scientific community in this field has focused its efforts on researching tools that facilitate the improvement [...] Read more.
Background: The latest data on physical inactivity and mental health among adolescents raise concerns about the quality of life and development of young people. The expert scientific community in this field has focused its efforts on researching tools that facilitate the improvement of these variables, such as self-perceived physical condition and life satisfaction, with evidence supporting the effects of green spaces on health. Objective: The aim of this study is to analyze the effects of a physical activity intervention in the natural environment on life satisfaction and self-perceived physical condition in adolescents. Methods: For this purpose, a 12-day quasi-experimental study was carried out, consisting of nature activities (such as canyoning or canoeing) twice a day in an adolescent population that attended camps in the region. Results: The results showed improvements in both variables, with increasing levels of life satisfaction and self-perceived physical condition after the intervention. Conclusions: Physical activity in natural environments is an effective strategy to improve the physical and mental health of young people, acquiring vital importance as a protective factor against numerous psychological and social disorders. Interventions that promote physical activity in the natural environment have proven successful in improving life satisfaction and self-perceived physical condition among young people, simultaneously addressing issues of inactivity, quality of life, and healthy habits in this demographic group. Full article
26 pages, 1409 KiB  
Article
Is the Energy Transition of Housing Financially Viable? Unlocking the Potential of Deep Retrofits with New Business Models
by Ezio Micelli, Giulia Giliberto and Eleonora Righetto
Buildings 2025, 15(7), 1175; https://doi.org/10.3390/buildings15071175 (registering DOI) - 3 Apr 2025
Abstract
The transition to energy-efficient buildings is a priority of the European EPBD (Energy Performance Building Directive) and requires deep retrofits to reduce consumption and emissions. However, their financial viability remains underexplored. This research assesses the financial feasibility of deep retrofit interventions through innovative [...] Read more.
The transition to energy-efficient buildings is a priority of the European EPBD (Energy Performance Building Directive) and requires deep retrofits to reduce consumption and emissions. However, their financial viability remains underexplored. This research assesses the financial feasibility of deep retrofit interventions through innovative business models, focusing on the Managed Energy Services Agreement (MESA), which is considered the most effective for residential buildings. Additionally, we integrate off-site production from the Energiesprong model, which optimizes costs and time through long-term contracts and industrialized retrofit technologies. The analysis targets two investment profiles—owner/tenant and developer/entrepreneur—in Italian urban contexts with different market dynamics. A static analysis evaluates retrofits based on existing costs and technologies, while a dynamic analysis considers future profitability improvements because of cost reductions enabled by off-site production. The results indicate that, under current conditions, residential retrofitting is not financially sustainable without public subsidies. However, cost reductions driven by off-site technologies improve profitability, making large-scale retrofits feasible. Moreover, real estate market characteristics affect financial sustainability: in smaller cities, deeper cost reductions are necessary for retrofit interventions to become viable. Full article
(This article belongs to the Special Issue Study on Building Energy Efficiency Related to Simulation Models)
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14 pages, 1326 KiB  
Article
Maximizing Tax Revenue for Profit Maximizing Monopolist with the Cobb-Douglas Production Function and Linear Demand as a Bilevel Programming Problem
by Zrinka Lukač, Krunoslav Puljić and Vedran Kojić
AppliedMath 2025, 5(2), 37; https://doi.org/10.3390/appliedmath5020037 (registering DOI) - 3 Apr 2025
Abstract
Optimal taxation and profit maximization are two very important problems, naturally related to one another since companies operate under a given tax system. However, in the literature, these two problems are usually considered separately, either by studying optimal taxation or by studying profit [...] Read more.
Optimal taxation and profit maximization are two very important problems, naturally related to one another since companies operate under a given tax system. However, in the literature, these two problems are usually considered separately, either by studying optimal taxation or by studying profit maximization. This paper tries to link the two problems together by formulating a bilevel model in which the government acts as a leader and a profit maximizing follower acts as a follower. The exact form of the tax revenue function, as well as optimal tax amount and optimal input levels, are derived in cases when returns to scale take on values 0.5 and 1. Several illustrative numerical examples and accompanying graphical representations are given for decreasing, constant, and increasing returns to scale values. Full article
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13 pages, 485 KiB  
Article
Long-Term Trends in PM10, PM2.5, and Trace Elements in Ambient Air: Environmental and Health Risks from 2020 to 2024
by Heba M. Adly and Saleh A. K. Saleh
Atmosphere 2025, 16(4), 415; https://doi.org/10.3390/atmos16040415 (registering DOI) - 3 Apr 2025
Abstract
This study aimed to assess the long-term trends in PM10, PM2.5, and hazardous trace elements in Makkah from 2020 to 2024, evaluating seasonal variations, health risks, and potential mitigation strategies. The results indicated that the PM10 concentrations ranged [...] Read more.
This study aimed to assess the long-term trends in PM10, PM2.5, and hazardous trace elements in Makkah from 2020 to 2024, evaluating seasonal variations, health risks, and potential mitigation strategies. The results indicated that the PM10 concentrations ranged from a minimum of 127.7 ± 14.2 µg/m3 (2020) to a maximum of 138.3 ± 15.7 µg/m3 (2024), while PM2.5 levels varied between 100.7 ± 18.7 µg/m3 and 109.8 ± 21.3 µg/m3. A seasonal analysis showed the highest PM10 and PM2.5 levels during winter (147.8 ± 16.4 µg/m3 and 119.5 ± 21.7 µg/m3 in 2024, respectively), coinciding with lower wind speeds and reduced dispersion. Among the nine trace elements analyzed, Cr VI exhibited the highest increase from 0.008 ± 0.001 µg/m3 (2020) to 0.012 ± 0.001 µg/m3 (2024), while Cd and Ni also rose significantly. The excess cancer risk (ECR) associated with these pollutants exceeded the recommended threshold, with a strong correlation between PM10 and ECR (r = 0.85–0.93, p < 0.01). These findings highlight the need for enhanced air quality monitoring and sustainable urban planning. Future research should focus on identifying the dominant pollution sources and assessing the long-term health impacts to support evidence-based air quality management in Makkah. Full article
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30 pages, 3565 KiB  
Systematic Review
Internet of Things and Deep Learning for Citizen Security: A Systematic Literature Review on Violence and Crime
by Chrisbel Simisterra-Batallas, Pablo Pico-Valencia, Jaime Sayago-Heredia and Xavier Quiñónez-Ku
Future Internet 2025, 17(4), 159; https://doi.org/10.3390/fi17040159 (registering DOI) - 3 Apr 2025
Abstract
This study conducts a systematic literature review following the PRISMA framework and the guidelines of Kitchenham and Charters to analyze the application of Internet of Things (IoT) technologies and deep learning models in monitoring violent actions and criminal activities in smart cities. A [...] Read more.
This study conducts a systematic literature review following the PRISMA framework and the guidelines of Kitchenham and Charters to analyze the application of Internet of Things (IoT) technologies and deep learning models in monitoring violent actions and criminal activities in smart cities. A total of 45 studies published between 2010 and 2024 were selected, revealing that most research, primarily from India and China, focuses on cybersecurity in IoT networks (76%), while fewer studies address the surveillance of physical violence and crime-related events (17%). Advanced neural network models, such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and hybrid approaches, have demonstrated high accuracy rates, averaging over 97.44%, in detecting suspicious behaviors. These models perform well in identifying anomalies in IoT security; however, they have primarily been tested in simulation environments (91% of analyzed studies), most of which incorporate real-world data. From a legal perspective, existing proposals mainly emphasize security and privacy. This study contributes to the development of smart cities by promoting IoT-based security methodologies that enhance surveillance and crime prevention in cities in developing countries. Full article
(This article belongs to the Special Issue Internet of Things (IoT) in Smart City)
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17 pages, 974 KiB  
Article
A School Mental Health Provider Like Me: Links Between Peer Racial Harassment, Depressive Symptoms, and Race-Matched School Counselors and Psychologists
by Sean Darling-Hammond and Cindy Le
Int. J. Environ. Res. Public Health 2025, 22(4), 553; https://doi.org/10.3390/ijerph22040553 (registering DOI) - 3 Apr 2025
Abstract
Legal scholarship and caselaw suggest that exposure to peer racial harassment in school (PRHS) harms student mental health and can derail students’ academic trajectories. Legal precedents call on schools to intervene to reduce student exposure to PRHS when feasible. However, little quantitative social [...] Read more.
Legal scholarship and caselaw suggest that exposure to peer racial harassment in school (PRHS) harms student mental health and can derail students’ academic trajectories. Legal precedents call on schools to intervene to reduce student exposure to PRHS when feasible. However, little quantitative social science has explored the impacts of PRHS, explored whether exposure to PRHS varies by racial group, or identified structural factors that may protect against PRHS. We review data from over 350,000 California 6th–12th-grade students in nearly 1000 schools and estimate that exposure to PRHS is related to a twenty-percentage-point-higher depressive symptom rate for students of all racial groups, that Black students are significantly more likely to experience PRHS, that being in a school with a race-matched school counselor or psychologist is related to lower rates of both PRHS and depressive symptoms, but that White students are more likely than students of other backgrounds to be in a school where the mental health workforce reflects their racial background. The results suggest a need to reduce exposure to PRHS, particularly for Black students, and that expanding the diversity of school mental health providers could be a pathway to protecting students against PRHS and its attendant harms. Full article
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17 pages, 9599 KiB  
Article
Research on Walnut (Juglans regia L.) Yield Prediction Based on a Walnut Orchard Point Cloud Model
by Heng Chen, Jiale Cao, Jianshuo An, Yangjing Xu, Xiaopeng Bai, Daochun Xu and Wenbin Li
Agriculture 2025, 15(7), 775; https://doi.org/10.3390/agriculture15070775 (registering DOI) - 3 Apr 2025
Abstract
This study aims to develop a method for predicting walnut (Juglans regia L.) yield based on the walnut orchard point cloud model, addressing issues such as low efficiency, insufficient accuracy, and high costs in traditional methods. The walnut orchard point cloud is [...] Read more.
This study aims to develop a method for predicting walnut (Juglans regia L.) yield based on the walnut orchard point cloud model, addressing issues such as low efficiency, insufficient accuracy, and high costs in traditional methods. The walnut orchard point cloud is reconstructed using unmanned aerial vehicle (UAV) images, and the semantic segmentation technique is applied to extract the individual walnut tree point cloud model. Furthermore, the tree height, canopy projection area, and volume of each walnut tree are calculated. By combining these morphological features with statistical models and machine learning methods, a prediction model between tree morphology and yield is established, achieving prediction accuracy with a mean absolute error (MAE) of 2.04 kg, a mean absolute percentage error (MAPE) of 17.24%, a root mean square error (RMSE) of 2.81 kg, and a coefficient of determination (R2) of 0.83. This method provides an efficient, accurate, and economically feasible solution for walnut yield prediction, overcoming the limitations of existing technologies. Full article
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30 pages, 7021 KiB  
Article
Anti-Inflammatory Effect of Dendrobium officinale Extract on High-Fat Diet-Induced Obesity in Rats: Involvement of Gut Microbiota, Liver Transcriptomics, and NF-κB/IκB Pathway
by Runze Zhou, Yixue Wang, Shiyun Chen, Fanjia Cheng, Yuhang Yi, Chenghao Lv and Si Qin
Antioxidants 2025, 14(4), 432; https://doi.org/10.3390/antiox14040432 (registering DOI) - 3 Apr 2025
Abstract
The growing prevalence of obesity is being increasingly acknowledged as a major public health issue. This mainly stems from the excessive intake of dietary fats. Dendrobium officinale (DO), recognized as an herb with dual roles of food and medicine, is renowned for its [...] Read more.
The growing prevalence of obesity is being increasingly acknowledged as a major public health issue. This mainly stems from the excessive intake of dietary fats. Dendrobium officinale (DO), recognized as an herb with dual roles of food and medicine, is renowned for its diverse health-promoting effects. Nevertheless, the specifics of its antiobesity and anti-inflammatory properties and the underlying mechanisms are still obscure. The present study shows that treatment with Dendrobium officinale extract (DOE) alleviates obesity, liver steatosis, inflammation, and oxidative stress in rats that are obese due to a high-fat diet (HFD). Firstly, with respect to HFD obese rats, higher doses of DOE significantly reduced TG, TC, LDL-C, blood glucose, and liver AST and ALT, along with lipid droplets. Meanwhile, DOE supplementation significantly reduced oxidative stress induced by ROS and MDA and increased the levels of GSH-Px and SOD in liver tissues. Furthermore, integrated analysis of transcriptomic and microbiomic data revealed that DOE modulated inflammatory responses through the NF-κB/IκB pathway. This regulatory mechanism was evidenced by corresponding changes in the protein expression levels of both NF-κB and IκB. Additionally, DOE was found to modulate gut microbiota composition in obese rats, specifically reducing the relative abundance of Bilophila while increasing beneficial bacterial populations, particularly the genera Akkermansia and Roseburia. These findings suggest that DOE may help retain the homeostasis of the gut microbiota and improve metabolic health by regulating inflammation in the liver and intestine, thereby providing protection against obesity and related metabolic syndromes. Our study demonstrates that DOE, as a natural botanical extract, can effectively facilitate the prevention or treatment of metabolic syndrome through precision dietary interventions. Full article
(This article belongs to the Special Issue The Interaction Between Gut Microbiota and Host Oxidative Stress)
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22 pages, 4739 KiB  
Article
Visible Light Active Natural Rutile Photocatalyst Obtained via Nano Milling
by Kata Saszet, Enikő Eszter Almási, Ádám Rácz, Katalin Bohács, Milica Todea, Klára Hernádi, Zsolt Pap and Lucian Baia
Molecules 2025, 30(7), 1600; https://doi.org/10.3390/molecules30071600 (registering DOI) - 3 Apr 2025
Abstract
Natural rutile is a widely available titanium mineral which shows great potential as a photocatalyst for environmental remediation when processed correctly. Industries invest large sums in the transformation of the rutile mineral into pure, synthetic nano titania. Still, the present study proves that [...] Read more.
Natural rutile is a widely available titanium mineral which shows great potential as a photocatalyst for environmental remediation when processed correctly. Industries invest large sums in the transformation of the rutile mineral into pure, synthetic nano titania. Still, the present study proves that bare natural rutile with trace element content can also be applied as a photocatalyst, without harsh chemical interventions, simply by processing via nano grinding. Samples with different mean primary particle size values were obtained by wet stirred media milling, their compositional and structural properties were investigated, and their photocatalytic properties were evaluated under both visible- and UV-light illumination for the degradation of phenol and ibuprofen. By changing the grain size and the particle size distribution, and due to the doping effect of impurities present in the mineral, the band gap values of the samples and their photocatalytic activities changed as well. The nano milled rutile exhibited visible light photocatalytic activity, with a 33% degradation efficiency in the case of both phenol and ibuprofen, after 22 h of irradiation. The present study not only highlights the photocatalytic degradation of a pharmaceutical by natural rutile mineral, but its findings also suggest that ground nano rutile can function as an environmentally friendly photocatalyst, as it not only avoids the use of harmful chemicals typically employed in TiO2 synthesis but also offers a simpler, more cost-effective alternative for producing photocatalytic materials. Full article
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30 pages, 3427 KiB  
Article
An Enhanced Team-Oriented Swarm Optimization Algorithm (ETOSO) for Robust and Efficient High-Dimensional Search
by Adel BenAbdennour
Biomimetics 2025, 10(4), 222; https://doi.org/10.3390/biomimetics10040222 (registering DOI) - 3 Apr 2025
Abstract
This paper introduces the Enhanced Team-Oriented Swarm Optimization (ETOSO) algorithm, a novel refinement of the Team-Oriented Swarm Optimization (TOSO) algorithm aimed at addressing the stagnation problem commonly encountered in nature-inspired optimization approaches. ETOSO enhances TOSO by integrating innovative strategies for exploration and exploitation, [...] Read more.
This paper introduces the Enhanced Team-Oriented Swarm Optimization (ETOSO) algorithm, a novel refinement of the Team-Oriented Swarm Optimization (TOSO) algorithm aimed at addressing the stagnation problem commonly encountered in nature-inspired optimization approaches. ETOSO enhances TOSO by integrating innovative strategies for exploration and exploitation, resulting in a simplified algorithm that demonstrates superior performance across a broad spectrum of benchmark functions, particularly in high-dimensional search spaces. A comprehensive comparative evaluation and statistical tests against 26 established nature-inspired optimization algorithms (NIOAs) across 15 benchmark functions and dimensions (D = 2, 5, 10, 30, 50, 100, 200) confirm ETOSO’s superiority relative to solution accuracy, convergence speed, computational complexity, and consistency. Full article
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22 pages, 3416 KiB  
Article
Can Integrating SoC Management in Economic Dispatch Enhance Real-Time Operation of a Microgrid?
by Alessia Cagnano
Energies 2025, 18(7), 1802; https://doi.org/10.3390/en18071802 (registering DOI) - 3 Apr 2025
Abstract
The aim of this paper is to develop a self-adaptive control methodology capable of optimizing in real-time the operation of PV-powered microgrids by dynamically managing both the output powers of battery energy storage systems (BESSs) and power exchanges with the utility grid. Control [...] Read more.
The aim of this paper is to develop a self-adaptive control methodology capable of optimizing in real-time the operation of PV-powered microgrids by dynamically managing both the output powers of battery energy storage systems (BESSs) and power exchanges with the utility grid. Control actions are evaluated by solving a constrained multi-objective optimization problem that integrates the optimal state-of-charge (SoC) management of BESSs within a broader economic dispatch framework. In this way, the SoC is continuously optimized alongside other economic objectives, such as minimizing operating costs and maximizing revenues from energy sales to the grid, while maintaining the microgrid’s energy balance. This ensures that BESSs operate efficiently within their optimal ranges, preventing premature depletion or overload and thereby safeguarding overall microgrid performance. To enable real-time adaptability, the methodology employs a Lyapunov-based optimization algorithm combined with a sensitivity analysis, ensuring rapid convergence to optimal solutions, even under rapidly changing conditions. Computer simulations performed on a low-voltage PV-BESS-based microgrid under different operating conditions confirm the effectiveness of the proposed methodology in enhancing real-time economic performance, operational efficiency, and microgrid reliability. Full article
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