Search Results (118)

We quantified how exhibit design and routine management shape behavior and space use in captive harbor seals (Phoca vitulina). Using a species-specific ethogram, scan sampling and focal follows on adult females housed in a modern zoo exhibit, we estimated time budgets, mapped space use across depth-defined zones, and modeled behavior sequences as first-order transition networks. Locomotion dominated activity (swimming/active travel), with resting and enrichment-related behaviors next most frequent; social and play behaviors occurred at low but non-negligible rates. Seals showed clear depth preferences, concentrating active swimming in deeper zones and using liminal/shallow areas for rest. Transition graphs revealed stable, low-entropy loops (e.g., swim → turn/pace → swim) consistent with repetitive locomotor routines, while enrichment and feeding windows temporarily diversified sequences and increased exploration. Overall, integrating time budgets with Markov-style transition analysis and spatial heatmaps provides a compact welfare-oriented dashboard: it identifies where exhibit depth and refuge availability support positive behavioral diversity, flags repetitive cycles as targets for enrichment, and offers actionable metrics to evaluate husbandry changes over time. Full article

Background: Parents play a central role in shaping children’s eating behaviors. While previous research has documented associations between parental attitudes and feeding practices, fewer studies have examined how mothers’ own eating styles may contribute to their perceptions of their children’s eating attitudes and behaviors and how these may influence subsequent feeding practices. Objectives: To our knowledge, this is the first study to examine whether mothers’ eating styles predicted their self-reported restrictive feeding practices indirectly through their perceptions of their children’s appetite and subsequently through their concern about their children’s weight. Methods: A total of 488 mothers (M_age = 33.87 years, SD = 4.81, range = 20–49) of children aged 2–7 years (M_age = 3.85 years, SD = 1.33) completed self-report measures, including the Dutch Eating Behavior Questionnaire (DEBQ) for maternal eating styles, the Child Feeding Questionnaire (CFQ) for parental concerns and restrictive practices, and the Children’s Eating Behavior Questionnaire (CEBQ) for perceptions of child eating attitudes. Structural equation modeling (SEM) was employed to test the hypothesized mediation model, with model fit evaluated using CFI, TLI, RMSEA, and SRMR indices. Results: Our proposed model demonstrated good fit (CFI = 0.94, RMSEA = 0.07) and showed that maternal eating styles were positively associated with perceived child appetite (β = 0.44, p < 0.001). Perceived appetite predicted both maternal concern about child weight (β = 0.39, p < 0.001) and restrictive feeding practices (β = 0.28, p < 0.001), while maternal concern strongly predicted restriction (β = 0.65, p < 0.001). The total indirect effect from maternal eating styles to restriction was significant (β = 0.23, p < 0.001), and the model explained 56% of the variance in restrictive feeding. Conclusions: Our findings suggest that maternal eating styles may bias mothers’ perceptions of their children’s appetite and indirectly influence restrictive feeding practices primarily through increased concern about child weight. Given the cross-sectional design, reliance on maternal self-report, and online convenience sampling, results should be interpreted cautiously. Nonetheless, the study provides the first evidence for a sequential pathway linking maternal eating styles, child appetite perceptions, and weight concern to restrictive feeding, highlighting cognitive and perceptual processes as intervention targets. Full article

Background: Obesity is a risk factor for several non-communicable diseases and premature death. The Western-type diet, rich in calories and diverse in tastes, smells, and textures, promotes the onset and progression of obesity. We compared the effects of two Western-style palatable obesogenic diets—the cafeteria (CAF) diet, which allows for self-selection of calorie-dense food items consumed by humans, and the fast-food diet (FFD)—composed of a fixed combination of cheeseburgers and fries—on the manifestation of obesity-related complications. Methods: 3-month-old female rats consumed either the control (CTRL), FFD, or CAF diet for 12 months. Body weight was monitored weekly. At the end of the experiment, rats underwent metabolic and behavioral testing. Cardiometabolic markers and those characterizing glycoxidative and carbonyl stress, inflammatory status, and tryptophan metabolism were determined. Results: The CAF rats gain most weight (CTRL: +111 ± 40 g; FFD: +211 ± 77 g; CAF: 316 ± 87 g). CAF feeding produced a classical metabolic syndrome–like profile with severe obesity, insulin resistance, dyslipidemia, and liver steatosis, whereas the FFD model led to moderate obesity with preserved insulin sensitivity but elevated blood pressure and hepatic cholesterol accumulation. Thus, the CAF group developed a severe metabolic syndrome-like pathology assessed as continuous metabolic syndrome z-core (CTRL: −2.3 ± 1.0; FFD: −0.4 ± 1.9; CAF: 3.0 ± 2.4). Despite these differences, both diets promoted neuroinflammation and social deficits, likely mediated through gut microbiota–derived metabolites such as 5-HIAA and indoxyl sulfate. Conclusions: In female rats, self-selected CAF diet drives more severe and distinct pattern of metabolic syndrome-like pathology than a fixed FFD. Full article

Background: Food cue reactivity (FCR) has been associated with a higher obesity risk, but little is known about what factors influence FCR during infancy. This study examined the moderating effects of maternal feeding styles and bottle feeding on the associations between 2-month and 6-month FCR. Methods: Data came from 299 mother–infant dyads who participated in a larger early-obesity-risk study and provided information via online questionnaires (i.e., socio-demographics) and/or during lab visits (i.e., anthropometrics) prenatally and at 2 and 6 months postpartum. Food-related practices (i.e., bottle use, milk type), feeding styles and FCR were measured by previously validated mother-reported measures: Infant Feeding Practices, Infant Feeding Styles, and Baby Eating Behavior Questionnaires. A regression model with moderation effects between 2-month FCR, feeding styles, and bottle feeding on 6-month FCR was tested using Mplus, controlling for selected variables (i.e., milk type, infant birthweight). Maternal pressure interacted with 2-month FCR and bottle feeding to predict 6-month FCR. Results: The moderating role of higher pressure was significant only for infants who received most of their feeds via a bottle (“high” bottle feeding). No other interactions were significant. Maternal feeding pressure in combination with frequent bottle feeding further strengthens the positive association between early and late FCR in infancy. Conclusions: Given the previously established links between FCR and weight outcomes among children, reducing the controlling maternal feeding practice of pressure during feeding in infancy, especially among mothers who frequently bottle feed, might be an important intervention target for optimizing weight outcomes in the first year of life. Full article

Remote sensing video (RSV) provides continuous, high spatiotemporal earth observations that are increasingly important for environmental monitoring, disaster response, infrastructure inspection and urban management. Despite this potential, operational use of video streams is hindered by very large data volumes, heterogeneous acquisition platforms, inconsistent preprocessing practices, and the absence of standardized formats that deliver data ready for immediate analysis. These shortcomings force repeated low-level computation, complicate semantic extraction, and limit reproducibility and cross-sensor integration. This manuscript presents a principled multi-level analysis-ready data (ARD) model for remote sensing video, named VideoARD, along with VideoCube, a spatiotemporal management and query infrastructure that implements and operationalizes the model. VideoARD formalizes semantic abstraction at scene, object, and event levels and defines minimum and optimal readiness configurations for each level. The proposed pipeline applies stabilization, georeferencing, key frame selection, object detection, trajectory tracking, event inference, and entity materialization. VideoCube places the resulting entities into a five-dimensional structure indexed by spatial, temporal, product, quality, and semantic dimension, and supports earth observation OLAP-style operations to enable efficient slicing, aggregation, and drill down. Benchmark experiments and three application studies, covering vessel speed monitoring, wildfire detection, and near-real-time three-dimensional reconstruction, quantify system performance and operational utility. Results show that the proposed approach achieves multi-gigabyte-per-second ingestion under parallel feeds, sub-second scene retrieval for typical queries, and second-scale trajectory reconstruction for short tracks. Case studies demonstrate faster alert generation, improved detection consistency, and substantial reductions in preprocessing and manual selection work compared with on-demand baselines. The principal trade-off is an upfront cost for materialization and storage that becomes economical when queries are repeated or entities are reused. The contribution of this work lies in extending the analysis-ready data concept from static imagery to continuous video streams and in delivering a practical, scalable architecture that links semantic abstraction to high-performance spatiotemporal management, thereby improving responsiveness, reproducibility, and cross-sensor analysis for Earth observation. Full article

Background/Objectives: Zinc deficiency remains a public health concern in South Asia but is rarely studied through gestation to infancy. Methods: We identified maternal and infant factors related to plasma zinc of 3 mo old Bangladeshi infants (n = 317) in the context of a trial of a daily antenatal to 3 mo postpartum multiple micronutrient supplementation (MMS) with 15 vitamins and minerals, including 12 mg zinc, versus iron–folic acid (IFA). Factors explored included maternal age, parity, and plasma zinc in early (pre-supplementation) and late pregnancy, at 3 months postpartum, and in milk; cord blood zinc (n = 83); birth outcomes; and infant feeding and biomarkers. Consequently, infant zinc was explored with 3 mo anthropometry and growth rates. Results: Mean ± SD infant plasma zinc was 15.63 ± 6.65 µmol/L, with 10.1% deficiency (<9.9 µmol/L). In adjusted analyses, infant zinc was positively associated with maternal age [20–30 years +0.11 µmol/L (p = 0.018) and ≥30 years +0.28 µmol/L (p = 0.003) relative to <20 years], maternal early pregnancy zinc (+0.01 µmol/L per 1 µmol/L maternal zinc, p = 0.011), and infant ferritin (+0.001 µmol/L per 1 µg/L, p = 0.007); conversely, infant zinc was −0.13 µmol/L lower (p = 0.013) with maternal parity ≥2 versus 0–1 and with partial versus exclusive breastfeeding (−0.15 µmol/L, p = 0.038). Relationships with MMS, maternal later pregnancy, postpartum, milk, and cord blood zinc were absent. Length-for-age (+0.02 per µmol/L, p = 0.047) but not weight-for-length Z-scores at 3 months were associated with infant zinc. Conclusions: Thus, infant zinc was associated with pre- but not post-MMS maternal zinc, age and parity, feeding style, and infant iron status. Infant length but not weight was associated with plasma zinc. Full article

Background/Aim: Nutrition plays a pivotal role in development, not only in the early stages of life but also during adolescence, a period marked by vulnerability to the onset of overweight, obesity and eating disorders, with repercussions for reproductive and bone health. This narrative review aims to explore how parenting style, parental feeding practices and social media exposure influence eating behaviors in children and adolescents. Methods: A narrative review of the literature was performed through the PubMed and Scopus databases, including studies on participants aged 0–18 years. Both observational and interventional studies focusing on parenting approaches and the impact of social media on dietary behaviors were included. Given the narrative design, studies were selected based on conceptual relevance rather than formal inclusion or exclusion criteria, and on their contribution to understanding the multifactorial determinants of eating behavior. Results: A substantial body of research has demonstrated the critical influence of the family in cultivating positive eating habits and fostering a healthy relationship with food in children, serving as a role model and through responsive and authoritative parenting. Conversely, controlling or restrictive styles may contribute to dysfunctional eating patterns. Social media can positively and negatively influence children’s eating behaviors and parental feeding practices, promoting nutritional awareness or exposure to unhealthy food marketing and unrealistic body ideals. Conclusions: Healthcare professionals should promote an educational, trust-based approach to nutrition, empowering parents and youth for responsible digital engagement. Integrating family, school and media education is essential for preventing obesity and eating disorders in the digital age. Full article

Postpartum lactating people are particularly vulnerable to inequities in social determinants of health (SDH), yet no validated tool currently exists to assess these factors comprehensively. This study aimed to co-develop and establish the content validity of an instrument to integratively evaluate SDH in this population. Guided by the Mixed Methods Appraisal Tool, an interdisciplinary e-Delphi panel assessed item sufficiency, clarity, coherence, and relevance. Statistical analyses included the item-level (I-CVI) and scale-level (S-CVI/Ave) content validity indices, average agreement between experts (AABE), Fleiss’ kappa (κ), and Aiken’s V coefficient (V) (p < 0.05). Cognitive interviews were conducted with postpartum lactating participants representing diverse characteristics to assess interpretability. The initial version of the instrument included 135 items across nine sections addressing general demographics, education, employment, home environment, lifestyle, social support, healthcare access, stress, intimate partner violence, insomnia, and nutrition. Based on expert input, it was refined to 131 items through structural and lexical revisions. Content validity indices indicated strong agreement: I-CVI ranged from 0.66–1.00, S-CVI/Ave > 0.95, AABE > 14.26, and κ and V > 0.90. Final adjustments following cognitive interviews led to a 128-item version optimized for clarity and relevance. This instrument offers strong content validity for SDH assessment in postpartum lactating people and supports sustainable use in health research. Full article

Motor insurance can use telematics data not only to understand individual driving style but also to implement innovative coaching strategies that feed back to the drivers, through an app, the aggregated information extracted from the data. The purpose is to encourage an improvement in their driving style. A precondition for this improvement is that drivers are digitally engaged, that is, they interact with the app. This paper proposes a narrow understanding of the term engagement, referring to users’ interactions with the app. This interaction is also a behavior producing specific data that can be tracked and used by insurance companies. Based on the empirical investigation of the dataset of a company selling a telematics motor insurance policy, our research investigates if there is a correlation between engagement with the app and improvement of driving style. The analysis distinguishes different groups of users with different driving abilities, and takes into account time differences. Our findings contribute to clarifying the methodological challenges that must be addressed when exploring engagement and coaching effectiveness in proactive insurance policies. We conclude by discussing the possibility and difficulties of tracking and using second-order behavioral data related to policyholder engagement with the app. Full article

Background/Objective: Problems associated with eating and weight in childhood are complex and have a multifactorial etiology. In recent years, childhood obesity has become a global public health problem with short- and long-term physical, psychological, and social health consequences. This is a cross-sectional study that evaluates the relationship between parenting styles, eating styles, and parents’ body mass index (BMI) and their children’s body mass index (BMI) and disordered eating behaviors (DEBs). Method: A sample of 372 dyads of mothers or fathers (mean age = 38 (SD = 8.8)) and boys or girls (mean age = 8.9 years (SD = 0.31)) was used. Results: Path analysis found that an authoritarian parenting style had a significant positive relationship with food approach (β = 0.36, p < 0.001) and food avoidance factors (β = 0.23, p < 0.001). Parental depression was positively associated with food approach (β = 0.20, p < 0.001) and food avoidance factors (β = 0.19, p < 0.001). Food approach factors significantly predicted compensatory behaviors (β = 0.14, p < 0.001). Lastly, both binge eating (β = 0.10, p < 0.05) and compensatory behaviors (β = 0.31, p < 0.001) showed significant positive relationships with children’s BMI. Conclusions: A clearer understanding of the relationships among these factors could facilitate earlier and more effective interventions targeting nutrition- and weight-related issues. Full article

Background/Objectives: Food selectivity is a prevalent and challenging issue in childhood, particularly in children with autism spectrum disorder (ASD), which may result in restricted dietary patterns and nutrient deficiencies. This study aimed to identify high-risk subgroups of children by combining food selectivity, diet, BMI, gastrointestinal symptoms, sensory processing, and parental feeding practices in children with ASD and in typically developing children (TDC). Methods: To achieve this aim, we ran a cross-sectional, survey-based study, including 408 children (aged 3 to 12.11 years), with gender-matched groups. Both parents completed a survey on children’s diet, anthropometric curves, gastrointestinal symptoms, and the Brief Autism Mealtime Behavior Inventory (BAMBI), Short Sensory Profile (SSP), and Caregiver’s Feeding Style Questionnaire (CFSQ). Data analysis included comparative tests, correlations, and k-means cluster analysis. Results: Children with ASD exhibited significantly greater sensory processing difficulties, higher food refusal, limited food variety in the diet, and autism-related mealtime characteristics compared with TDC across all age groups. Caregivers of children with ASD reported higher controlling and contingency management feeding practices compared to the parents of the TDC. We found a strong correlation between sensory sensitivities and feeding issues. Notably, Body Mass Index (BMI) was not significantly associated with dietary restriction or gastrointestinal symptoms. Cluster analysis revealed a high-risk sub-phenotype in both groups of children with some differences, characterized by high food selectivity, taste, tactile, and smell sensitivity, gastrointestinal symptoms, and overactive parental practices. Conclusions: The early identification of this subgroup might foster more tailored, multidisciplinary, and effective assessment and clinical intervention. Full article

Cruciferous vegetables are popular in Asian dishes. However, striped flea beetles prefer to feed on leaves, which can damage the appearance of crops and reduce their economic value. Due to the lack of pest monitoring, the occurrence of pests is often irregular and unpredictable. Regular and quantitative spraying of pesticides for pest control is an alternative method. Nevertheless, this requires manual execution and is inefficient. This paper presents a system powered by solar energy, utilizing batteries and supercapacitors for energy storage to support the implementation of edge AI devices in outdoor environments. Raspberry Pi is utilized for artificial intelligence image recognition and the Internet of Things (IoT). YOLOv5 is implemented on the edge device, Raspberry Pi, for detecting striped flea beetles, and StyleGAN3 is also utilized for data augmentation in the proposed system. The recognition accuracy reaches 85.4%, and the results are transmitted to the server through a 4G network. The experimental results indicate that the system can operate effectively for an extended period. This system enhances sustainability and reliability and greatly improves the practicality of deploying smart pest detection technology in remote or resource-limited agricultural areas. In subsequent applications, drones can plan routes for pesticide spraying based on the distribution of pests. Full article

This paper provides a comparative study of unsupervised Deep Learning (DL) methods for anomaly detection in Flight Data Monitoring (FDM). The paper applies Long Short-Term Memory (LSTM), Gated Recurrent Units (GRUs), Convolutional Neural Network (CNN), classic Transformer architecture, and LSTM combined with a self-attention mechanism to real-world flight data and compares the results to the current state-of-the-art flight data analysis techniques applied in the industry. The paper finds that LSTM, when integrated with a self-attention mechanism, offers notable benefits over other deep learning methods as it effectively handles lengthy time series like those present in flight data, establishes a generalized model applicable across various airports and facilitates the detection of trends across the entire fleet. The results were validated by industrial experts. The paper additionally investigates a range of methods for feeding flight data (lengthy time series) to a neural network. The innovation of this paper involves utilizing Transformer architecture and LSTM with self-attention mechanism for the first time in the realm of aviation data, exploring the optimal method for inputting flight data into a model and evaluating all deep learning techniques for anomaly detection against the ground truth determined by human experts. The paper puts forth a compelling case for shifting from the existing method, which relies on examining events through threshold exceedances, to a deep learning-based approach that offers a more proactive style of data analysis. This not only enhances the generalization of the FDM process but also has the potential to improve air transport safety and optimize aviation operations. Full article

Background: This study aimed to investigate the correlation between parental feeding practices and children’s body composition in two Chinese regions with distinct socioeconomic characteristics. Methods: A cross-sectional study was conducted in Shenzhen (economically developed) and Yulin (economically underdeveloped) regions. Data were collected in 2023 from 1298 (age 8–10 years) children and their parents in two regions. Overweight/obesity was defined by Chinese national standards (WS/T 586-2018), and parental feeding practices were assessed using a 26-item child feeding questionnaire (CFQ). Multivariable regression analysis was performed to assess whether the association between parental feeding practices and obesity in children differs by regions. Results: A total of 1298 participants were included, with 678 male students (52.23%) and a mean age of 10.65 ± 0.86 years. In two regions, children with higher pressure to eat (PE) scores had lower rates of overweight, obesity and central obesity. Significant positive associations were observed between children’s body composition and parental feeding practices, including PE, perceived child weight (PCW), and concern about child weight (CN) (all p < 0.001). In regional interaction analysis, PCW had significant positive associations with fat mass index (FMI) (β = 0.32, 95% CI = 0.18, 0.46). Meanwhile, CN also had significant positive associations with both FMI (β = 0.44, 95% CI = 0.34, 0.54) and fat-free mass index (FFMI) (β = 0.07, 95% CI = 0.02, 0.11) (all p < 0.001). Conclusions: Obesity, central obesity, and body composition in children were associated with parental feeding practices in the two regions. CN was associated with higher risk of obesity and central obesity in the two regions. Future efforts to prevent obesity in children may optimize parental feeding practices, especially more scientific awareness of children’s weight status while reducing undue concern. Full article

This study addresses the problem of authorship attribution with a novel method for modeling writing style using dependency tree subtree parsing. This method exploits the syntactic information of sentences using mixed syntactic n-grams (mixed sn-grams). The method comprises an algorithm to generate mixed sn-grams by integrating words, POS tags, and dependency relation tags. The mixed sn-grams are used as style markers to feed Machine Learning methods such as a SVM. A comparative analysis was performed to evaluate the performance of the proposed mixed sn-grams method against homogeneous sn-grams with the PAN-CLEF 2012 and CCAT50 datasets. Experiments with PAN 2012 showed the potential of mixed sn-grams to model a writing style by outperforming homogeneous sn-grams. On the other hand, experiments with CCAT50 showed that training with mixed sn-grams improves accuracy over homogeneous sn-grams, with the POS-Word category showing the best result. The study’s results suggest that mixed sn-grams constitute effective stylistic markers for building a reliable writing style model, which machine learning algorithms can learn. Full article