bluuebunny/crossref_metadata_2025 huggingface dataset:
Association Between Psychological Distress and Coping Styles in Family Caregivers of People with Intellectual Disability or Chronic Mental Disorder in Mongolia
Authors: Sendmaa Delgermaa , Ganbaatar Namuun , Regzedmaa Orgilmaa , Nuden Erdenetuul , Chuluun Enkhtuul , Luvsangenden Sundui-Yanjmaa , Gochoosuren Gankhuyag , Myagmarjav Dolgorjav , Badamdorj Oyungoo , Zuunnast Khishigsuren , Dashtseren Myagmartseren , Nyam Naranbaatar , Nolan Fiona
Published: November 2024

Around the world, family caregivers are an important source of support for people with intellectual disability (ID) and for those with severe mental disorder (SMD), although the level of support can be influenced by the culture and government healthcare systems in each country. However, there is little evidence about the mental health and coping mechanisms of these caregivers in low-income countries. To address this need, we aimed to elicit whether there are potential links between coping style, mental health, and perceived burden experienced by this group, using a sample from a central Asian upper middle-income country. Methods: We recruited 120 participants, of which 60 were caregivers of people with ID and 60 of people with SMD. All participants were recruited from Ulaanbaatar, the capital city of Mongolia, Central Asia, and were asked to complete of the Depression, Anxiety and Stress Scale (DASS) and the Coping Orientation to Problems Experienced inventory scale (COPE). Multiple regression analyses were used to investigate associations between these measures. Results: We found that DASS scores were significantly higher among the sample of caregivers of individuals with ID than in those of SMD. Mental and behavioral disorders were associated with higher DASS scores in the sample of caregivers of those with SMD. Good coping styles, indicated by higher scores in the COPE, were associated with increased age in caregivers of individuals with ID. Conclusion: Although overall the carers of people with SMD appeared to have better active coping skills and better acceptance of the caring role, they demonstrated comparatively high levels of stress. This study was not registered.
Measuring Parental Response Styles to Child Stress in Severe Pediatric Illness: A Validation Study
Authors: Pitillas Carlos , Zerolo Blanca Egea , Jódar Rafael , Ribeiro Ana
Published: November 2024

Background: Pediatric illnesses not only impose physical challenges on affected children, but also profoundly impact their emotional well-being. Understanding how parents respond to their children’s psychological distress during medical experiences is crucial for enhancing the overall support provided to these families. Aim: This study evaluated the internal structure of the Parental Response Styles Questionnaire (PRSQ), designed to differentiate parental responses to psychological distress in children with pediatric illnesses. Methods: A sample of 701 parents of children with medical issues responded to the PRSQ, reporting their different emotional expressions and responses to their children’s expressions of distress during the medical experience. Results: Factor analysis confirmed, in three of the five subsamples, an internal scale structure consisting of four factors: apathy and dysphoria, irritability and rejection, overprotectiveness, and perceived maladjustment. The invariance analyses revealed that congenital heart disease and neurological disorders are more similar in function to each other than pediatric cancer. Parents of children with neurological disorders exhibited a notably insecure pattern of parental responsiveness. Conclusions: In pediatric contexts, parental responses to their children’s emotional distress are significant factors in the process of adaptation. These responses can be measured, differentiated, and, ideally, managed by nurses and other healthcare professionals. The Parental Response Styles Questionnaire (PRSQ) is a promising tool for assessing parental reactions during their children’s treatment, and its structure appears to be particularly robust across diagnoses such as pediatric cancer, congenital heart disease, and neurological disorders.
Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
Authors: Mashala Dimakatso Given , Ntimana Cairo Bruce , Seakamela Kagiso Peace , Mashaba Reneilwe Given , Maimela Eric
Published: November 2024

Sociodemographic factors affect how metabolic syndrome (MetS) manifests and progresses. This study aimed to investigate the prevalence between MetS and sociodemographic factors among adult participants in the Dikgale HDSS. This was a comprehensive retrospective study where the records of 575 participants were meticulously evaluated. MetS was defined using a joint interim statement (JIS). The data were analyzed using the Statistical Package for SPSS, version 25. A chi-square test was used to compare proportions between groups, with Cramer’s V used to assess the strength of association. Logistic regression was used to determine the association between MetS and sociodemographic profiles. A p-value of less than 0.05 was considered statistically significant. The prevalence of MetS was 28.2% (females 33.3% vs. males 15.6%, p ≤ 0.001). In addition, logistic regression showed males to have lower odds of MetS as compared to females (OR = 0.36, 95% CI: 0.2–0.6, and AOR = 0.4, 95% CI: 0.2–0.6). The 55–60 age group had the highest proportion of affected individuals, and MetS was also more common among individuals with low educational attainment. In addition, on regression, the same association was observed. This study found sociodemographic disparities in MetS among rural adults, especially females, who had an increased risk of MetS, and participants with low educational attainment.
Advances on Bioactive Metabolites with Potential for the Biocontrol of Plant Pathogenic Bacteria
Authors: Reveglia Pierluigi , Corso Gaetano , Evidente Antonio
Published: November 2024

The increase in the world population, which will be almost 10 billion by 2050, will require considerable efforts to significantly increase food production. Despite the considerable progress made in agriculture, this need is becoming an emergency due to desertification, environmental pollution and climate changes. Biotic stresses, such as pathogenic bacteria and fungi, primarily contribute to significant losses in agricultural productivity and compromise food safety. These harmful agents are predominantly managed using large quantities of synthetic pesticides. However, this widespread use has led to substantial environmental pollution, increased pest resistance and toxic residues in agricultural produce, which subsequently enter the food supply, posing severe health risks to humans and animals. These challenges have significantly driven the advancement of integrated pest management strategies to reduce or eliminate synthetic pesticides. A practical and viable alternative lies in biopesticides—methods developed from natural products that are safe for human and animal health. This approach aligns with the strong demand from consumers and public authorities for safer pest control solutions. This review was focused on the isolation, chemical and biological characterization of natural products for the biocontrol of phytopathogenic bacteria and, in some cases, fungi with potential eco-friendly applications.
The Evolution of Wisteria Vein Mosaic Virus: A Case Study Approach to Track the Emergence of New Potyvirus Threats
Authors: Morelli Massimiliano , D’Attoma Giusy , Saldarelli Pasquale , Minafra Angelantonio
Published: November 2024

Wisteria vein mosaic virus (WVMV, Potyvirus wisteriae), a virus belonging to the genus Potyvirus, is responsible for Wisteria vein mosaic disease (WMD), a severe disease that affects Wisteria, a genus of garden plants acclaimed worldwide. Although probably originating in the Far East, WVMV infection was first reported in the US, and subsequently in numerous countries. Following the first molecular detection of an Italian isolate, WVMV Bari, its full-length genome was achieved using NGS barcoding technology. A PhyML phylogenetic analysis, supported by clustering algorithm validation, identified a clear separation between two phylogroups. One major clade comprised WVMV strains isolated from Wisteria spp. A second clade grouped three highly divergent strains, at the borderline species threshold, all found in non-wisteria hosts. Relying on a Relative Time Dated Tips (RTDT) molecular clock, the first emergence of WVMV clades has been traced back to around the 17th century. A network inference analysis confirmed the sharp separation between the two host-related phylogroups, also highlighting the presence of potential intermediate variants. Inter-population genetic parameters revealed a very high genetic differentiation in both populations, which was made reliable by statistically significant permutation tests. The migrant number (Nm) and fixation index (FST) evidenced a restricted gene flow and strong population structures. According to the dN/dS ratio and negative neutrality tests, it was derived that purifying selection at the expense of non-silent variants is underway within WVMV populations. Targeting WVMV evolutionary traits, the present effort raised interesting questions about the underestimated potential of this culpably neglected species to spread in economically relevant crops. The main intention of our study is, therefore, to propose an evolution-based analysis approach that serves as a case study to investigate how other potyviruses or newly emerging viruses may spread.
Through the Lens of Age: Using Dog Photographs to Uncover Welfare and Stress
Authors: Dutra Luisa Mascarenhas Ladeia , Vasconcellos Angelica da Silva , Young Robert John
Published: November 2024

This study evaluated the potential of using dogs’ apparent age, judged from photographs, as a non-invasive tool for assessing their welfare. Traditional welfare assessment methods often rely on behavioral and physiological indicators, which can be resource-intensive and invasive. This research explored whether apparent age, a measure used in humans to predict health and longevity, can also serve as an indicator of welfare in dogs by investigating its association with relative telomere length (RTL), a biomarker of biological aging. Photographs of 60 domestic dogs were evaluated by canine specialists and general volunteers via the citizen science platform Zooniverse. Participants estimated the age of 20 dogs from three different age categories: young (0–2 years), adult (2–5 years), and senior (6+ years). The accuracy of these predictions was compared to the dogs’ chronological ages and RTLs. Generalized linear models were used to assess factors influencing prediction accuracy, including the dogs’ age, sex, and origin. Results indicated that both specialists and volunteers reliably estimated the age of senior dogs, with no significant differences in accuracy between groups. Dogs with accurate apparent age estimates had RTLs matching their chronological age, while those with premature aging signs had shorter RTLs. This suggests apparent age could be a practical, non-invasive welfare assessment tool, offering a potentially accessible method for new welfare assessment protocols.
Optical System Design of a Self-Calibrating Real Entrance Pupil Imaging Spectrometer
Authors: Wang Xinrui , Li Xin , Zhang Quan , Shi Yuanjian , Wei Wei , Liu Enchao
Published: November 2024

Presently, on-orbit calibration methods have several problems, such as low calibration accuracy and broken traceability links, so an urgent need exists to unify traceable and high-precision on-orbit radiometric calibration loads as benchmarks for cross-transfer radiometric calibration. Considering the deficiencies of current on-orbit calibration, this paper proposes adjusting the size of the variable diaphragm at the entrance pupil and the integration time to attain large dynamic attenuation, converting the radiometric calibration into absolute geometric calibration of the attenuation device, and realizing a self-calibrating real entrance pupil imaging spectrometer (SCREPIS) that can be directly used to view the Earth and the Sun and quickly obtain apparent reflectance data. An initial structural design method based on the distance between individual mirrors is proposed according to the instrument design requirements. The design of a real entry pupil image-side telecentricity off-axis three-reflector front optical system with a 7° field of view along the slit direction, a 3.7 systematic F-number, and a 93 mm focal length is finally realized, and the system image plane energy is verified to change proportionally to the variable diaphragm area. Finally, the front system and rear Offner optical system are jointly simulated and optically designed. The system provides instrumental support for cross-calibration and theoretical support and a technical basis for planning space-based radiation references.
A Historical Review of the Artificial Pollination of Vanilla planifolia: The Importance of Collaborative Research in a Changing World
Authors: Karremans Adam P.
Published: November 2024

The natural fertilization of Vanilla planifolia has long been a matter of speculation. Stingless (tribe Meliponini) and orchid bees (tribe Euglossini) are often cited as effective pollinators, but direct evidence is notoriously lacking. As with other food-deceptive orchids, the natural fruit-set in V. planifolia is low and does not occur spontaneously outside its native range in Middle America. Fruiting has, therefore, necessitated human intervention through artificial pollination. How Vanilla first came to be artificially pollinated is a controversial issue spurring egotism and nationalism. There are numerous texts offering differing versions of the historical events that led to the discovery of the artificial fertilization of V. planifolia and its propagation as a crop. Historical records show Vanilla was simultaneously being pollinated in several parts of the world. I argue that the suspected independent simultaneous discoveries made in Liège, Paris, Padua, the Dutch colony of Java (Indonesia), and the French insular colonies Réunion (Bourbon), Guadeloupe, and Martinique are not unconnected. I conclude that they can be traced back to a single discoverer whose feat was spread around the globe by a tight network of corresponding naturalists. This view contrasts with previous authors. Finally, current concerns regarding Vanilla pollination and production are addressed, highlighting the need for immediate actions to conserve the genetic diversity of the crop’s wild relatives to attenuate the effect of extreme climates in a changing world. A plea is made to shift the focus to Middle America, stimulating and supporting local research and conservation efforts and the allocation of funds from this billion-dollar industry.
Progress in Understanding and Enhancing Rice Tolerance to Biotic and Abiotic Stresses
Authors: Wu Weixun , Zhang Yingxin , Jiao Guiai , Wei Xiangjin
Published: November 2024

Rice growth and development occur in several distinct stages: a seedling stage, a vegetative stage, a reproductive stage, and maturity [...]
Soil Microbial and Metabolomic Shifts Induced by Phosphate-Solubilizing Bacterial Inoculation in Torreya grandis Seedlings
Authors: Li Yi , Guan Yuanyuan , Jiang Zhengchu , Xie Qiandan , Wang Qi , Yu Chenliang , Yu Weiwu
Published: November 2024

Phosphorus is crucial for plant growth and development, but excess fertilizer not absorbed by plants often binds with metal ions like iron and manganese, forming insoluble compounds that contribute to soil environmental pollution. This study investigates the impact of Burkholderia sp., a phosphate-solubilizing bacterium utilized as a biofertilizer, on the fertility of T. grandis soil, alongside the associated shifts in soil metabolites and their relationship with microbial communities after inoculation. The soil microbial community structures and metabolite profiles were analyzed via amplicon sequencing and high-resolution untargeted metabolomics. The inoculation of phosphate-solubilizing bacteria led to a significant (p < 0.05) enhancement in total phosphorus, potassium, and nitrogen concentrations in the soil, with a marked increase in available phosphorus in bulk soil (p < 0.05). Moreover, the microbial community structure exhibited significant shifts, particularly in the abundance of bacterial phyla such as Acidobacteria, Chloroflexi, Proteobacteria, and the fungal phylum Ascomycota. Metabolomic analysis revealed distinct metabolites, including fatty acids, hormones, amino acids, and drug-related compounds. Key microbial taxa such as Chloroflexi, Proteobacteria, Acidobacteria, Verrucomicrobia, Mucoromycota, and Ascomycota indirectly contributed to soil phosphorus metabolism by influencing these differential metabolites. In conclusion, the application of phosphate-solubilizing bacteria offers an innovative approach to improving soil quality in T. grandis, promoting phosphorus utilization efficiency, and enhancing soil ecosystem health by optimizing microbial communities and metabolite compositions.
Insulator-YOLO: Transmission Line Insulator Risk Identification Based on Improved YOLOv5
Authors: Zhang Nan , Su Jingyi , Zhao Yang , Chen Hua
Published: November 2024

This study introduces an innovative method for detecting risks in transmission line insulators by developing an optimized variant of YOLOv5, named Insulator-YOLO. The model addresses key challenges in small-defect detection, complex backgrounds, and computational efficiency. By incorporating GhostNetV2 in the backbone to streamline feature extraction and introducing SE and CBAM attention mechanisms, the model enhances its focus on critical features. The Bibi-directional Feature feature Pyramid pyramid Network network (BiFPN) is applied to enhance multi-scale feature fusion, and the integration of CIoU and NWD loss functions optimizes bounding box regression, achieving higher accuracy. Additionally, focal loss mitigates the imbalance between positive and negative samples, leading to more accurate and robust defect detection. Extensive evaluations demonstrate that Insulator-YOLO significantly improves detection accuracy and efficiency in real-world power line insulator defects, providing a reliable solution for maintaining the integrity of transmission systems.
Synergistic Impact of Magnets and Fins in Solar Desalination: Energetic, Exergetic, Economic, and Environmental Analysis
Authors: Kaviti Ajay Kumar , Siva Prasad M. , Naga Teja V. Bhanu Venkata , Sikarwar Vineet Singh
Published: November 2024

This study investigates the effectiveness of combining magnets with parabolic and truncated fins in enhancing the distillation process of solar stills. The integration of magnets accelerated evaporation rates, while the fins increased the heat absorption area, resulting in improved output, vis-à-vis traditional solar stills. A comparative assessment revealed that the parabolic fin solar still (PFS) with magnets outperformed the truncated fin solar still (TCFS), producing 20%, 15%, and 16% more distillate at three different depths (1, 2, and 3 cm). The superior performance of the PFS is attributed to the magnetism of the water and the fins’ more extensive surface area for heat absorption. Efficiency measurements at a water depth of 1 cm showed that the PFS achieved the maximum energy and exergy efficiencies at 30.49% and 8.85%, respectively, compared with TCFS’s 25.23% and 6.22%. Economically, the PFS setup proved more feasible, with a 20.9% lower cost per liter of distilled water than TCFS. Additionally, the environmental impact assessment indicated a significant reduction in CO2 emissions, potentially generating revenues of approximately USD 1242.32 through carbon credits. These results reflect a considerable margin to enhance the efficiency of solar desalination through well-planned adjustments, which bodes well for the future of optimized solar distillation systems from an economic and environmental perspective.
Diels–Alder Cycloaddition of N-Azobenzene Maleimides with Furan and Electrochemical Study of Redox Reactions
Authors: Venegas-Villalvazo David Fernando , Figueroa-Hernández David Abraham , Pineda-Contreras Armando , Flores-Alvarez José Manuel , García-Ortega Héctor , González-González Juan Saulo
Published: November 2024

This work reports the synthesis of aminoazobenzene compounds derived from 3,5-dimethylaniline (1a–1f) via a diazo-coupling reaction with aromatic amines. These aminoazobenzenes were acylated with maleic anhydride to obtain the corresponding maleimides (2a–2f). The maleimides were then used as dienophiles in a Dies–Alder cycloaddition reaction with furan as the diene, yielding the adducts (3a–3f). All synthesized compounds were characterized using FTIR, 1H, and 13C NMR spectroscopy. Additionally, electrochemical studies using cyclic voltammetry were conducted to determine the oxidation–reduction reactions present in the compounds.
Giovanni Botero on Religion and Politics
Authors: Zhu Xin
Published: November 2024

Giovanni Botero’s political thought is significantly influenced by Machiavelli, yet it possesses its own distinctive features, particularly in its religious perspective. In contrast to Machiavelli’s condemnation of Catholicism, Botero argues that Catholicism, far from weakening individuals, could instill in them the courage to defy death and foster military virtues through the promise of eternal life. While Botero agrees with Machiavelli that religion plays a central role in politics, he asserts that Catholicism is more effective than other sects as it is better suited to maintaining social order and disciplining the human conscience. However, he refutes the idea that religion should serve merely as an instrument of domination. Instead, he suggests that it should be the foundation of the state and the purpose of governance. Furthermore, he maintains that religion and the state are interdependent, functioning together to ensure the maintenance and strengthening of both.
Concurrent Coxsackievirus A6 Infection and Kawasaki Disease: A Case Report
Authors: Puenpa Jiratchaya , Saelim Noree , Wanlapakorn Nasamon , Korkong Sumeth , Yorsaeng Ritthideach , Poovorawan Yong
Published: November 2024

Background and Clinical Significance: Kawasaki disease (KD) is an acute febrile vasculitis that primarily affects children and is associated with systemic inflammation, particularly in the coronary arteries. Coxsackievirus A6 (CVA6) has emerged as a significant agent in atypical presentations of hand, foot, and mouth disease (HFMD), raising the possibility of its involvement in KD. Case Presentation: This report presents the case of an 18-month-old Thai boy admitted with symptoms of high fever, sore throat, and ulcerative lesions, initially diagnosed with herpangina. As his condition progressed, additional KD symptoms developed, including conjunctival injection, rash, and elevated inflammatory markers, fulfilling the diagnostic criteria for KD. Notably, throat swab analysis confirmed CVA6 as the causative agent. Phylogenetic analysis revealed that the CVA6 strain closely aligned with Chinese strains from 2023, showing a high nucleotide sequence homology of 98.4%. Conclusions: In conclusion, this case highlights a possible association between CVA6-associated herpangina and KD, suggesting that CVA6 infection may act as a trigger for KD in genetically susceptible children. These findings highlight the need for increased awareness among healthcare providers to promptly identify and manage Kawasaki Disease during peak enterovirus seasons, reducing its impact on children.
Dynamics of Amaranthus in Urban and Rural Value Chains in Communities of KwaZulu-Natal Province, South Africa
Authors: Olusanya Ruth , Kolanisi Unathi , Ngobese Nomali , Mayashree Chinsamy
Published: November 2024

Sub-Saharan Africa falls among the developing countries with poor standards of living contributing to the high prevalence of malnutrition. Interventions have been conducted, but malnutrition continues to linger, with devastating impacts on vulnerable groups. In Africa, 90% of its children cannot access the minimum balanced diet. Also, 60% of the people in this region do not access daily meals for dietary needs. Traditional vegetables like Amaranthus are identified to have great potential to combat malnutrition; however, Amaranthus is underutilized due to limited awareness of its potential and poor post-harvest practices along the value chain. This study evaluates the dynamics of Amaranthus along its value chain in the urban and rural communities of KwaZulu-Natal. South Africa. Mixed-design research and a purposive convenient random sampling approach were explored. Semi-structured questionnaires were used to collect data for the survey, and this was strengthened by a series of five n = (30) face-to-face interviews with six key informants from urban and rural formal and informal markets. The findings revealed that eleven species of Amaranthus have been identified in South Africa such as Amaranthus spinosus varieties, including A. dubius, and A. cruentus, which are the most sold and consumed, mostly being sold by street vendors. Thus, poor perception and attitudes along with limited access to Amaranthus in some upper-class markets contribute to underutilization. Promoting Amaranthus at all levels of markets might create better awareness of its utilization.
Anti-Maneuvering Repeater Jamming Using Up- and Down-Chirp Modulation in Spaceborne Synthetic Aperture Radar
Authors: Sha Yu , Feng Xiaoxiao , Wei Tingcun , Du Jiang , Yu Weidong
Published: November 2024

With the continuous development of synthetic aperture radar (SAR) jamming technology, low-power maneuvering repeater jammers are now flexible and can be located on multiple unmanned aerial vehicles (UAVs) and unmanned vehicles (UVs) at the same time, which greatly increases the difficulty of the anti-maneuvering repeater jamming method for spaceborne SAR. Due to the low-power transmission, the locations of the low-power repeater jammers and the protected areas in the imaged swath are relatively close in distance, while the transmission delay of the jamming is approximately equal to the pulse repetition interval (PRI). According to this phenomenon, an anti-maneuvering repeater jamming method using up- and down-chirp modulation is proposed in this paper. After alternately transmitting up- and down-chirp modulation signals, echoes of the jamming and the protected area are recorded in the same location within the echo-receiving window and are related to different chirp modulations. To remove the jamming echoes, de-chirping and frequency filtering are adopted after echo data segmentation. With jamming interference removal using frequency notch filtering, parts of the spectra corresponding to the desired echoes of the imaged swath are simultaneously removed. To recover the unwanted removed range spectra, linear prediction is introduced to improve the focusing quality. Finally, simulation results on both point and distributed targets validate the proposed anti-maneuvering repeater jamming method by using up- and down-chirp modulation.
Development of a Real-Time Wearable Humming Detector Device
Authors: Mazouzi Amine , Campeau-Lecours Alexandre
Published: November 2024

This study focuses on the development of a wearable real-time Humming Detector Device (HDD) aimed at enhancing the control of assistive devices through humming. As the need for portable user-friendly tools in assistive technology grows, the HDD offers a non-invasive solution to detect vocal cord vibrations. Vibrations, detected thanks to an accelerometer worn on the neck, are processed in real time using a Fast Fourier Transform (FFT) to identify specific humming frequencies, which are then translated into commands for controlling assistive devices via Bluetooth Low Energy (BLE) transmission. The device was tested with 13 healthy subjects to validate its potential and determine the optimal number of distinct commands that users can achieve. The HDD’s portability and precision make it a promising alternative to traditional voice recognition systems, particularly for individuals with speech impairments.
Causality-Driven Feature Selection for Calibrating Low-Cost Airborne Particulate Sensors Using Machine Learning
Authors: Sooriyaarachchi Vinu , Lary David J. , Wijeratne Lakitha O. H. , Waczak John
Published: November 2024

With escalating global environmental challenges and worsening air quality, there is an urgent need for enhanced environmental monitoring capabilities. Low-cost sensor networks are emerging as a vital solution, enabling widespread and affordable deployment at fine spatial resolutions. In this context, machine learning for the calibration of low-cost sensors is particularly valuable. However, traditional machine learning models often lack interpretability and generalizability when applied to complex, dynamic environmental data. To address this, we propose a causal feature selection approach based on convergent cross mapping within the machine learning pipeline to build more robustly calibrated sensor networks. This approach is applied in the calibration of a low-cost optical particle counter OPC-N3, effectively reproducing the measurements of PM1 and PM2.5 as recorded by research-grade spectrometers. We evaluated the predictive performance and generalizability of these causally optimized models, observing improvements in both while reducing the number of input features, thus adhering to the Occam’s razor principle. For the PM1 calibration model, the proposed feature selection reduced the mean squared error on the test set by 43.2% compared to the model with all input features, while the SHAP value-based selection only achieved a reduction of 29.6%. Similarly, for the PM2.5 model, the proposed feature selection led to a 33.2% reduction in the mean squared error, outperforming the 30.2% reduction achieved by the SHAP value-based selection. By integrating sensors with advanced machine learning techniques, this approach advances urban air quality monitoring, fostering a deeper scientific understanding of microenvironments. Beyond the current test cases, this feature selection method holds potential for broader applications in other environmental monitoring applications, contributing to the development of interpretable and robust environmental models.
Path Planning and Motion Control of Robot Dog Through Rough Terrain Based on Vision Navigation
Authors: Chen Tianxiang , Huangfu Yipeng , Srigrarom Sutthiphong , Khoo Boo Cheong
Published: November 2024

This article delineates the enhancement of an autonomous navigation and obstacle avoidance system for a quadruped robot dog. Part one of this paper presents the integration of a sophisticated multi-level dynamic control framework, utilizing Model Predictive Control (MPC) and Whole-Body Control (WBC) from MIT Cheetah. The system employs an Intel RealSense D435i depth camera for depth vision-based navigation, which enables high-fidelity 3D environmental mapping and real-time path planning. A significant innovation is the customization of the EGO-Planner to optimize trajectory planning in dynamically changing terrains, coupled with the implementation of a multi-body dynamics model that significantly improves the robot’s stability and maneuverability across various surfaces. The experimental results show that the RGB-D system exhibits superior velocity stability and trajectory accuracy to the SLAM system, with a 20% reduction in the cumulative velocity error and a 10% improvement in path tracking precision. The experimental results also show that the RGB-D system achieves smoother navigation, requiring 15% fewer iterations for path planning, and a 30% faster success rate recovery in challenging environments. The successful application of these technologies in simulated urban disaster scenarios suggests promising future applications in emergency response and complex urban environments. Part two of this paper presents the development of a robust path planning algorithm for a robot dog on a rough terrain based on attached binocular vision navigation. We use a commercial-of-the-shelf (COTS) robot dog. An optical CCD binocular vision dynamic tracking system is used to provide environment information. Likewise, the pose and posture of the robot dog are obtained from the robot’s own sensors, and a kinematics model is established. Then, a binocular vision tracking method is developed to determine the optimal path, provide a proposal (commands to actuators) of the position and posture of the bionic robot, and achieve stable motion on tough terrains. The terrain is assumed to be a gentle uneven terrain to begin with and subsequently proceeds to a more rough surface. This work consists of four steps: (1) pose and position data are acquired from the robot dog’s own inertial sensors, (2) terrain and environment information is input from onboard cameras, (3) information is fused (integrated), and (4) path planning and motion control proposals are made. Ultimately, this work provides a robust framework for future developments in the vision-based navigation and control of quadruped robots, offering potential solutions for navigating complex and dynamic terrains.
Effects of Income on Family Care Organization in Mexico: An Analysis Based on Data from the Encuesta Nacional de Ingreso y Gasto de los Hogares (ENIGH) from 2010 to 2020
Authors: Saucedo-Delgado Odra A. , Nieto María Rosa , De-La-Sota-Riva-Echánove Marcela
Published: November 2024

This article examines the impact of income level on family care organizations in Mexico to elucidate how families apportion care responsibilities according to their economic standing. The study design employed a quantitative approach, utilizing two distinct methodologies to construct two indices: one representing the time devoted to care and the other representing care transferred to the market. Factor analysis converts minutes and hours into a time index and transforms the number of domestic workers and health and hospital expenses into a market index. A regression model estimates the effect of income on these indices, aiming to analyze the relationship between income and spending on health and services and between income and time spent on home care. The results are based on data from the National Household Income and Expenditure Survey (ENIGH) 2010–2020, using a nationally representative sample of 81 thousand dwellings. The data analysis concluded that households with higher incomes spend a more significant proportion of their expenditure on domestic care-paid services and have greater access to professional care. In contrast, lower-income households face significant challenges due to their limited financial resources and the higher demands for unpaid care.
Enabling Industry 5.0-Driven Circular Economy Transformation: A Strategic Roadmap
Authors: Hsu Chih-Hung , Li Ze-Hao , Zhuo Hong-Ji , Zhang Ting-Yi
Published: November 2024

Because Industry 4.0 is not a better solution to the problems of the circular economy development process, the European Union proposed Industry 5.0 as a supplement to Industry 4.0. However, presently, no relevant research exists on the promotion of a circular economy under Industry 5.0, and the limited understanding of this process is the fundamental obstacle for enterprises to pursue digitalization and sustainable operations. This study addresses this knowledge gap by developing a roadmap explaining the use of the drivers of Industry 5.0 to support and promote the transformation to a circular economy. This study first screens the literature and determines 11 drivers of Industry 5.0. Secondly, on this basis, a fuzzy explanatory structure model of these drivers promoting a circular economy is constructed. Finally, a strategic roadmap is constructed for Industry 5.0 to promote a circular economy. The results reveal that the 11 key factors driving the circular economy are complementary, among which the quantitative criteria and indicators are the most critical and are present at the bottom of the strategic map. Value chain integration and the transformation into a sustainable business model are the most complex drivers. The strategic roadmap can explain the effects of the various drivers on the transformation to a circular economy and the order required to promote this transformation. The resulting management mindset is expected to assist manufacturers, industrialists, academia, and governments in providing services, thus forming a strategic guideline driven by Industry 5.0 factors to promote the circular economy.
Orchestrating Resources in Green Startups: Learning from Case Studies
Authors: Phani B. V. , Bhaskar Ramswarup , Bigliardi Barbara , Venturini Karen
Published: November 2024

This study examines the characteristics of green startups and the progression of their resource utilization patterns during the pandemic emergency, focusing on case studies from the Startup Incubation and Innovation Centre (SIIC) of the Kanpur Indian Institute of Technology (IITK). This study explores how these startups overcame lockdown challenges and identified the resources they utilized throughout various development stages. The findings reveal that the green startups in the sample share characteristics of visionary and inventive startups, often lacking formal business education but possessing strong technical skills and social engagement. They rely heavily on human and social resources in the early stages, leveraging their networks and stakeholder support to define and develop their green innovations. The research also highlights the importance of open innovation strategies, particularly in the product development stage, where startups leverage research labs and expertise within the IITK ecosystem. This study increases the literature on green startups and offers practical recommendations for young green entrepreneurs, emphasizing the importance of operating in familiar industries, building stakeholder networks, and utilizing open innovation strategies for successful green innovation development.
Analysis of the Factors Influencing the Purchase of Electric Vehicles in Brazil
Authors: Schvartz Marceli Adriane , Avila Lucas Veiga , Leal Filho Walter , Neves Canha Luciane , Siluk Julio Cezar Mairesse , Barros Thiago Antônio Beuron Corrêa de , Felipe Dias Lopes Luis , Steinhorst Kraetzig Elda Rodrigues
Published: November 2024

The transport sector, and especially the increase in individual vehicle ownership, contribute significantly to air pollution. The transition to electric vehicles (EVs) is seen as a sustainable alternative to reduce emissions of polluting gases. However, in Brazil, the EV market has not yet reached a significant size. Given this scenario, this study aims to analyze the factors that influence the decision to buy EVs in Brazil, highlighting personal, psychological, economic, performance, and environmental variables and barriers. The aim is also to develop a model with guidelines that can help stakeholders. The quantitative stage of the study involved a survey of 514 respondents. The data were analyzed using statistical methods, including structural equation modeling (SEM), which allowed for a deeper investigation of the proposed hypotheses. The survey findings reveal that, in the Brazilian context, performance factors—such as autonomy, availability of recharging infrastructure, and maintenance—are the main drivers influencing EV purchase decisions. Environmental factors, including energy reuse, pollution reduction, and minimizing environmental impacts, have also gained significant importance. Economic factors are crucial, particularly concerning cost–benefit perceptions. The differences between Brazil and other regions highlight the importance of accounting for cultural and economic variations when analyzing consumer behavior towards EVs.
Assessment of the Ecological Safety of Honey with the Help of “Factor Area” Models
Authors: Palamarchuk Igor , Adamchuk Leonora , Palamarchuk Vladyslav , Andrushchenko Mykola , Priss Olesia , Glowacki Szymon , Hutsol Taras , Bezaltychna Olena
Published: November 2024

The man-made load on the environment and the decrease in biodiversity cause a direct negative environmental impact on the existence of honey bees and beekeeping products. The priority directions of the food industry are the use of high-quality environmentally friendly raw materials and the prevention of the ingress and formation of harmful substances in food products, including honey. This implies the need to develop methods for assessing the environmental safety of the studied raw materials and products. The purpose of this study was to implement a mathematical modeling method for studying the environmental safety of honey. Five types of honey were studied: Robinia, rapeseed, linden, buckwheat, and sunflower. Mathematical models were built according to the following parameters: total activity of β-emitting radionuclides; residues of levomycetin (chloramphenicol), nitrofuran (according to AOZ and AMOZ), metronidazole, and pesticides (according to hexachloran); and the content of water-insoluble substances (mechanical impurities) and heavy metals. On the basis of the obtained data and established quality criteria, calculation graphic models were built. Using algebraic methods, they derived new formulas for calculating quality coefficients. Multivariate analysis and programming methods were used to evaluate honey using mathematical modeling. The most and least ecologically dangerous contaminants and their share of influence for different types of honey were determined based on the complex of research on negative factors. The proposed mathematical models can be implemented for practical use in specialized laboratories as a tool for determining the environmental safety of honey of various botanical origins.
Generative AI for Consumer Behavior Prediction: Techniques and Applications
Authors: Madanchian Mitra
Published: November 2024

Generative AI techniques, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers, have revolutionized consumer behavior prediction by enabling the synthesis of realistic data and extracting meaningful insights from large, unstructured datasets. However, despite their potential, the effectiveness of these models in practical applications remains inadequately addressed in the existing literature. This study aims to investigate how generative AI models can effectively enhance consumer behavior prediction and their implications for real-world applications in marketing and customer engagement. By systematically reviewing 31 studies focused on these models in e-commerce, energy data modeling, and public health, we identify their contributions to improving personalized marketing, inventory management, and customer retention. Specifically, transformer models excel at processing complicated sequential data for real-time consumer insights, while GANs and VAEs are effective in generating realistic data and predicting customer behaviors such as churn and purchasing intent. Additionally, this review highlights significant challenges, including data privacy concerns, the integration of computing resources, and the limited applicability of these models in real-world scenarios.
Citizens’ Attitudes and Practices Towards Waste Reduction, Separation, and Recycling: A Systematic Review
Authors: Konstantinidou Anna , Ioannou Konstantinos , Tsantopoulos Georgios , Arabatzis Garyfallos
Published: November 2024

The aim of this systematic review is to analyze the attitudes and practices adopted by citizens in waste reduction, separation, and recycling, taking into consideration specific socio-demographic factors such as gender, age, income level, and level of education that might have an influence on these practices. The study was based on an extensive review of published articles found in Scopus. In total 27 articles were selected for analysis after filtering and evaluation based on a series of predefined criteria set for the present review, such as time period, geographical coverage, and thematic relevance. Many studies have shown that women, compared to men, in addition to being more aware, adopted more frequently recycling practices. Furthermore, age emerged as a very important factor, as younger citizens were more actively involved and at the same time more willing to recycle waste compared to older citizens. Additionally, education level proved to be a decisive factor, as citizens with higher educational levels possessed greater knowledge regarding recycling and, at the same time, had more environmentally conscious awareness about environmental problems. This resulted in citizens being more involved in various recycling practices. Finally, income proved to be an equally important factor in both shaping recycling attitudes and practices. It turned out that people who received higher incomes had more opportunities and resources for participating in pro-environmental activities. However, some studies have shown opposite results where the effect of income on waste separation practices was either not statistically significant or negative. Finally, from the research, it was clear that there is a need to incorporate environmental issues into educational programs and information campaigns. All these should be tailored to the needs of the socio-demographic groups targeted and at the same time be concerned with promoting best recycling practices as well as waste reduction.
The Impact of Enterprise Digital Transformation on Audit Fees—An Intermediary Role Based on Information Asymmetry
Authors: Xin Jinguo , Du Kun , Xia Yuqi
Published: November 2024

This study investigates the impact of enterprise digital transformation through information and communication technology (ICT) on auditing fees. Based on data from publicly listed companies in China and employing information asymmetry theory, the research finds that the adoption of three factors associated with digital transformation—artificial intelligence (AI), cloud computing (CC), and big data technologies (BD)—exhibits a significant inverted U-shaped effect on auditing fees. Further analysis reveals that this effect is moderated by the quality of internal controls, the level of corporate governance, and discretionary accruals. These findings underscore the necessity for a nuanced understanding of the relationship between technology and auditing, as well as the importance for audit organizations to integrate new technologies into their practices to effectively respond to the rapid adoption of digital technologies by enterprises.
Critical Factors for Implementing Smart Manufacturing: A Supply Chain Perspective
Authors: Chiang Ai-Hsuan , Trimi Silvana , Kou Tun-Chih
Published: November 2024

In a rapidly evolving technological landscape, manufacturers are increasingly pressured to undertake digital transformation, with smart manufacturing serving as a crucial milestone in this process. This study investigates the key factors influencing the implementation of smart manufacturing from a supply chain perspective, employing the analytical hierarchy process (AHP) to analyze collected data from senior managers of manufacturing firms. The findings highlight several critical factors, including the commitment of senior executives, the recruitment of skilled professionals, interdepartmental collaboration, and financial support. Moreover, this study reveals differing priorities between large and small manufacturers: large firms emphasize the importance of the Industrial Internet of Things (IIoT), while smaller firms prioritize understanding end-consumer needs and product trends. This study emphasizes that smart manufacturing is not only for optimizing the operational efficiency of manufacturing firms but also for supporting sustainability efforts through more effective use of resources and reduced environmental impact of work processes.