Search Results (49)

Background/Objectives: Adolescents with chronic physical health conditions (CHCs) use specific coping strategies to respond to condition-related stressors. However, most studies of CHC-related stress and coping focus on a single condition. The objective of this study was to measure CHC-related stress and identify associated coping strategies in adolescents with a variety of CHCs. A secondary objective was to examine the relationship between CHC-related stress, coping strategies, health-related quality of life, and perceived severity of chronic illness. Methods: Teens (n = 38, 68.42% female, mean age 17.9 years) with CHCs completed the Responses to Stress Questionnaire (RSQ) for CHC-related stress, the PedsQL to assess health-related quality of life, and the Perceptions of the Severity of Chronic Illness (PSCI) measure. The most frequently reported conditions were asthma, food allergies, and multiple conditions. We used fuzzy cluster analysis to identify two clusters, high stress and low stress, based on ratings of CHC-related stressors. Relationships between coping strategies and the PedsQL and PSCI, and between the PSCI and PedsQL, were assessed using Pearson partial correlations. Relationships between the PSCI, PedsQL, and coping strategies for the two clusters were assessed using adjusted mean differences. We adjusted for multiple comparisons by controlling the false discovery rate. Significance was set at p < 0.05. Results: Teens were most likely to use secondary control engagement coping and involuntary engagement to respond to CHC-related stressors. Teens in the two clusters differed on health-related quality of life but not coping strategies or perceived condition severity. CHC diagnosis category was associated with cluster membership. Conclusions: This exploratory study highlighted relationships among quality of life, coping strategies, and CHC diagnosis category that should be explored in future studies. Improved understanding of CHC-related stress and coping strategies in teens with CHCs could have an impact on their quality of life and well-being. Full article

This study aimed to examine the role of childhood sexual abuse in attachment styles and involvement in BDSM (bondage, discipline, dominance, submission, and sadomasochism) practices in adult intimate relationships. A model was built to test the predictive value of factors for involvement in BDSM practices. This study included 318 participants. Demographic data were collected and three questionnaires were used: the Childhood Trauma Questionnaire (CTQ) identified past sexual abuse, the Adult Attachment Scale (RSQ) assessed attachment style in adulthood, and the Sadomasochism Checklist (SMCL) assessed interest in masochistic practices. The results show that childhood sexual abuse is associated with practicing and enjoying BDSM, positively with submissiveness, negatively with dominance, and positively with a composite score measuring both submissiveness and dominance. It is also linked to fearful and preoccupied attachment styles in adulthood, but not dismissive attachment. Men exhibit higher levels of submissiveness and dominance in BDSM compared to women. Older individuals are more inclined to engage in BDSM. Urban residents show higher involvement in BDSM compared to those in other environments. Homosexual or bisexual individuals in open relationships are more frequently involved in BDSM. These findings highlight the complexity of connections between past experiences, sexual preferences in BDSM, and secure attachment in intimate relationships. Full article

Objective: Low birth weight is a serious public health problem even in developed countries. The objective of this study was to assess the ability of machine learning to predict low birth weight rates in big cities in the USA on an ecological/population level. Study design: The study was based on publicly available data from the Big Cities Health Inventory Data Platform. The collected data related to the 35 largest, most urban cities in the United States from 2010 to 2022. The model-agnostic approach was used to assess and visualize the magnitude and direction of the most influential predictors. Results: The models showed excellent performance with R-squared values of 0.82, 0.81, 0.81, and 0.79, and residual root mean squared error values of 1.06, 0.87, 1.03, 0.99 for KNN, Best subset, Lasso, and XGBoost, respectively. It is noteworthy that the Best subset selection approach had a high RSq and the lowest residual root mean squared error, with only a four-predictor subset. Influential predictors that appeared in three/four models were rate of chlamydia infection, racial segregation, prenatal care, percentage of single-parent families, and poverty. Other important predictors were the rate of violent crimes, life expectancy, mental distress, income inequality, hazardous air quality, prevalence of hypertension, percent of foreign-born citizens, and smoking. This study was limited by the unavailability of data on gestational age. Conclusions: The machine learning algorithms showed excellent performance for the prediction of low birth weight rate in big cities. The identification of influential predictors can help local and state authorities and health policy decision makers to more effectively tackle this important health problem. Full article

Previous studies on tractor performance and efficiency were conducted prior to the implementation of emission reduction technologies and the increased density and complexity of tractor portfolios. This study presents a robust methodology for forecasting specific fuel consumption based on public information, which incorporates physical attribute-based cohorts and technological generation groupings, alongside variables such as wheelbase, mass, and power take-off power. The proposed model significantly improves forecasting accuracy, enhancing the current R-squared (RSq) from 0.6091 to 0.8519 and reducing the root mean square error (RMSE) from 0.0098 to 0.0065. Additionally, the model provides accurate predictions of drawbar performance and efficiency. Its simplicity results in low cognitive and computational demands, making it accessible via widely available spreadsheet software on any computer or handheld device. This accessibility supports data-driven decision-making for tractor replacement strategies, ultimately promoting sustainable profitability in agricultural business operations. Full article

Animal production requires efficiency, safety and environmental sustainability. Bioactive compounds from tropical plants could modulate ruminal fermentation, providing an alternative method to antibiotic treatment and addressing concerns about antibiotic resistance. In this study, the aim was to determine the effects of Tithonia diversifolia extract (TDE) on performance, intake, digestibility and blood parameters [i.e., glucose, blood urea nitrogen (BUN), aspartate aminotransferase (AST), alanine aminotransferase (ALT)] in crossbreed sheep. The main biocompounds of the TDE include caffeic acid (CA), quercetin (QCT), luteolin (LT) and apigenin (AP). Experiment 1: An in vitro dry matter digestibility (IVDMD) study was conducted to determine the optimal inclusion levels. The IVDM values were 73.09a, 82.03b, 81.01b, 73.20a and 74.51a for the control, 5, 10, 15 and 20 g/kg for the DM treatments, respectively (R-Sq adj = 0.857). The levels of 5 and 10 g were selected for the in vivo experiment. Experiment 2: Twenty-eight male crossbred hair lambs were assigned to four treatments (n = 7): control, 20 mg monensin/day, 5 g TDE/day and 10 g TDE/day groups. No differences in animal performance were observed, including body weight and feed conversion (p > 0.05). The TDE at 10 g/day improved NDF digestibility) (61.32%) and reduced the ruminal acetate to propionate ratio. The total digestible nutrients (TDN) were higher in 10 g TDE treatment with 66.41% and the lowest acetate production (67.82%) (p = 0.042), and propionate production (21.07%) were observed. The TDE were safe at 5 g and 10 g/day for liver function and exhibited lower BUN levels suggesting an improvement in protein metabolism. TDE extract at 10 g/day (TDE10), showed improvements in total tract digestibility of NDF and reduced the ruminal acetate to propionate ratio. However, due to TDE10 reducing the DM intake, the improvements in digestibility and ruminal fermentation were not reflected in growth performance improvements. Full article

Dust containing lead and zinc is a harmful contaminant, which causes serious harm to the natural environment and human health. At present, it is believed that the microscopic morphology of lead-zinc dust is intimately related to its biological toxicity. Chemical composition serves as a pivotal factor influencing the structural characteristics of dust. However, research on the impact of chemical composition variations on the microscopic morphology of dust containing lead and zinc remains inadequate. The particle size analysis reveals that as PbO content increases and ZnO content decreases, the particle size of the dust diminishes, but some samples exhibit a larger agglomeration structure. Combined with the results of the box number method, it is evident that at lower magnifications, an increase in PbO content leads to a decrease in image complexity and a loosening of aggregated structures. The similarity in pile shapes amplifies this trend, resulting in a decline in the box-counting dimension (D value) within the PbO/ZnO ratio range of 26.45 to 138, accompanied by an inverse change in the corresponding goodness of fit R-sq value. At the observation multiple of 30,000 times (30 K), smaller particles within the sample become visible, and the presence of relatively larger particles and complex sizes enhances the fractal characteristics of the sample, leading to a higher D value. Within the PbO/ZnO ratio range of 90/10 to 99/1, a coupling relationship exists between the chemical composition of the sample and the morphology of the dust. Specifically, the PbO/ZnO ratio exhibits a positive correlation with the D value. Conversely, the diversity of corresponding fractal features is negatively correlated with the D value. When the PbO content surpasses 99%, this correlation weakens, and the diversity of graphical representations displays an alternating pattern of growth and decrease. Notably, the D value and the goodness of fit (R-sq) of the D value are negatively correlated, indicating that as the complexity of the graph increases, the goodness of fit decreases. Full article

Cyber security is supportive of robotic service provision, the objective of which is to help marketers achieve their aim of providing a high level of service. Marketers need to be aware of cyber security issues and adhere to established cyber security policies. We investigate trust and commitment in relation to customer retention while assessing the mediating role of robotic service quality (RSQ). We employ a survey-based study that utilises 231 valid responses from customers in São Paulo, Brazil. To analyse the data, we used partial least squares structural equation modelling (PLS-SEM). The results show that trust and commitment have a positive impact on customer retention. RSQ has a partial mediation effect on the relationship between the latent constructs of trust, commitment, and customer retention. Thus, it can be suggested that RSQ, which embeds trust and commitment, assists in building a loyal customer base. Marketers outside the Latin American region can benefit from the results of this study since it incorporates cyber security awareness and policy within marketing strategy implementation, ensuring that RSQ is aligned in terms of the digitalisation goals of the company. Full article

Iberian ham is a highly valued product, and considerable efforts have been made to characterize it quickly and accurately. In this scenario, portable NIR devices could provide an effective solution for the assessment of its attributes. However, the calibration quality of NIR equipment is directly influenced by the relevance of the used spectral region. Therefore, this study aims to evaluate the suitability of different NIR spectrometers, including four portable and one benchtop instrument, with varying spectral working ranges for quantifying the fatty acid composition of Iberian ham. Spectral measurements were carried out on both the muscle and the fat of the ham slices. The results showed that 24 equations with an RSQ > 0.5 were obtained for both the muscle and fat for the NIRFlex N-500 benchtop instrument, while 19 and 14 equations were obtained in the muscle and 16 and 10 equations in the fat for the Enterprise Sensor and MicroNIR, respectively. In general, more fatty acids could be calibrated when the spectra were taken from lean meat, except with the SCiO Sensor. Measurements performed in the lean and fat zones delivered complementary information. These initial findings indicate the suitability of using miniaturized NIR sensors, which are faster, are less expensive, and enable on-site measurements, for analyzing fatty acids in Iberian ham. Full article

In this study, the effect of certain 3D printing conditions on the tensile strength of 3D-printed specimens was investigated. The printing material was CARBON: PLUS (NEEMA3D™, Athens, Greece), which consists of Polyethylene Terephthalate Glycol (PET-G) reinforced with 20% carbon fiber. All samples were printed with a closed-type, large-format Fused Filament Fabrication (FFF) 3D printer. Before printing the samples, three parameters related to the 3D printing settings were selected in order to vary their values (flow = the flow of the material, wall = the total thickness of the wall, and layer = the thickness of the print layer). Each parameter was given three different values for experimentation. In this study, all 27 possible combinations of variable parameters were fabricated. Each experiment was repeated twice, and from the test results, the maximum tensile strength was obtained for each specimen separately. From the results of the measurements, the most critical parameter appeared to be the height of the layer. The other two variable parameters, the flow and wall, locally affected the strength of the specimens. Later, an empirical model was developed according to the full factorial design for each combination of values. Finally, the R-sq (pred) value achieved was equal to 97.02%, and together with the residual analysis performed, the accuracy of the proposed maximum tensile strength mathematical model was proven. Full article

Currently, the NRC amino acid (AA) requirements for pigs published in 2012 are used as a reference in variable swine industries. However, recent results in several articles suggest that the standardized ileal digestible (SID) AA–lysine (Lys) ratio significantly evolved over the last two decades, while some publications report inconsistent outcomes. Therefore, the present study used a meta-regression analysis to assess the relative ratio to lysine to maximize the feed efficiency of four essential amino acids (tryptophan, valine, isoleucine, and methionine) in pig diets. According to the PRISMA guidelines, articles examining the target AA requirement using a basal diet supplemented with varying levels of crystalline AA (tryptophan, valine, isoleucine, or methionine) were identified across Scopus, PubMed, and Science Direct. As a result, 23, 22, 16, and 9 articles using tryptophan, valine, isoleucine, and methionine were selected and categorized into experiments for inclusion in our meta-analysis. The results suggested that the requirements of tryptophan, valine, isoleucine, and methionine in our meta-regression analysis were superior to NRC recommendations, regardless of the regression models and the growth phases with significant RSQ values (RSQ ≈ 1). Also, the QUAD and CLP regression models emphasized higher requirements than the LP model for the great majority of amino acids and growth phases. The results of the QUAD and CLP models were selected as estimations of the amino acid requirements for pigs under challenged conditions, whereas the LP model was chosen to estimate the amino acid requirements of genetically improved pigs under a modern housing system. The results of this meta-regression analysis could be used to refresh the information on the NRC amino acids (AA) requirements for swine. Full article

Objectives: From a cross-cultural perspective, aging well may encompass pertinent challenges in terms of adjustment, sexual well-being, and satisfaction with life in the late years. Considering the paucity of empirical data concerning cultural diversity of experiencing aging, this study aims to help fill this gap by assessing the specific patterns of sexual satisfaction, adjustment to aging (AtA), and life satisfaction with life (SwL) of older adults in Portugal and Spain. Methods: This cross-national study included 326 older adults, age 65 and older, from Portugal and Spain. Five instruments were applied: (a) Adjustment to Aging Scale (ATAS); (b) Satisfaction with Life Scale (SwLS); (c) New Sexual Satisfaction Scale-Short (NSSS-S); (d) Mini-Mental State Exam; and (e) Sociodemographic, Health and Lifestyle questionnaire. K-means cluster analysis was employed to identify and characterize the clusters considering adjustments to aging, sexual satisfaction, and life satisfaction. One-way ANOVAs were conducted to analyze differences in sexual well-being among clusters. Results: Findings indicated three clusters, which explained 77.7% (R-sq = 0.777) of the total variance: Cluster 1: “Most skilled” (n = 26, 8.0%), Cluster 2: “Least adjusted” (n = 115, 35.3%), and Cluster 3: “Aging strivers” (n = 185, 56.7%). Participants in Cluster 1 were mostly Portuguese, with high levels of AtA, sexual satisfaction, and SWL. Conversely, Cluster 2 included mostly Portuguese participants with moderate sexual satisfaction and lower levels of AtA and SwL. Participants from Cluster 3 were mostly Spanish, with moderate levels of AtA and reduced sexual satisfaction and SwL. Conclusions: This study innovates by exploring the elaborate interplay among sexual satisfaction, AtA, and SwL in a cross-cultural perspective, with implications for tailoring interventions, service planning, development, and evaluation of culturally diverse older populations. Full article

Carbohydrates are the main components of lentils, accounting for more than 60% of their composition. Their content is influenced by genetic factors, with different contents depending on the variety. These compounds have not only been linked to interesting health benefits, but they also have a significant influence on the techno-functional properties of lentil-derived products. In this study, the use of near-infrared spectroscopy (NIRS) to predict the concentration of total carbohydrate, fibre, starch, total sugars, fructose, sucrose and raffinose was investigated. For this purpose, six different cultivars of macrosperm (n = 37) and microsperm (n = 43) lentils have been analysed, the samples were recorded whole and ground and the suitability of both recording methods were compared. Different spectral and mathematical pre-treatments were evaluated before developing the calibration models using the Modified Partial Least Squares regression method, with a cross-validation and an external validation. The predictive models developed show excellent coefficients of determination (RSQ > 0.9) for the total sugars and fructose, sucrose, and raffinose. The recording of ground samples allowed for obtaining better models for the calibration of starch content (R > 0.8), total sugars and sucrose (R > 0.93), and raffinose (R > 0.91). The results obtained confirm that there is sufficient information in the NIRS spectral region for the development of predictive models for the quantification of the carbohydrate content in lentils. Full article

Potato is a globally significant crop, crucial for food security and nutrition. Assessing vital nutritional traits is pivotal for enhancing nutritional value. However, traditional wet lab methods for the screening of large germplasms are time- and resource-intensive. To address this challenge, we used near-infrared reflectance spectroscopy (NIRS) for rapid trait estimation in diverse potato germplasms. It employs molecular absorption principles that use near-infrared sections of the electromagnetic spectrum for the precise and rapid determination of biochemical parameters and is non-destructive, enabling trait monitoring without sample compromise. We focused on modified partial least squares (MPLS)-based NIRS prediction models to assess eight key nutritional traits. Various mathematical treatments were executed by permutation and combinations for model calibration. The external validation prediction accuracy was based on the coefficient of determination (RSQ_external), the ratio of performance to deviation (RPD), and the low standard error of performance (SEP). Higher RSQ_external values of 0.937, 0.892, and 0.759 were obtained for protein, dry matter, and total phenols, respectively. Higher RPD values were found for protein (3.982), followed by dry matter (3.041) and total phenolics (2.000), which indicates the excellent predictability of the models. A paired t-test confirmed that the differences between laboratory and predicted values are non-significant. This study presents the first multi-trait NIRS prediction model for Indian potato germplasm. The developed NIRS model effectively predicted the remaining genotypes in this study, demonstrating its broad applicability. This work highlights the rapid screening potential of NIRS for potato germplasm, a valuable tool for identifying trait variations and refining breeding strategies, to ensure sustainable potato production in the face of climate change. Full article

Passive psychoeducation is an easily accessible and cost-effective self-guided intervention that does not use elements of active psychotherapies or require homework. The present study aimed to investigate the acceptability and efficacy of a 7-week app-based passive psychoeducation stress management program to promote adaptive emotion regulation and coping skills in university students (i.e., 80% psychology students). Participants were tested via Lime-Survey^® at pre- and post-test with the Depression Anxiety Stress Scale-21 (DASS-21), the Response Styles Questionnaire (RSQ), and the Emotion Regulation Questionnaire (ERQ). A stratified permutation block randomization by age, gender, and the DASS-21 stress subscale was performed. Each week, the psychoeducation group (n = 123) received different psychoeducation modules. At the end of each module, participants answered questions about their satisfaction with each module and adherence to psychoeducation. The control group (n = 130) received no intervention. The psychoeducation program led to a significant improvement in the adaptive emotion regulation strategy: “reappraisal” (p = 0.004) and a significant reduction in the dysfunctional coping style: “symptom-related rumination” (p = 0.01) but not to a significant reduction in depression, anxiety, and stress scores compared to the control group. Thus, the present study might demonstrate a preventive effect of an app-based passive psychoeducation program in students with low clinically relevant psychopathological symptoms. Full article

Traditional methods for determining the chemical composition of cattle feces are uneconomical. In contrast, near-infrared reflectance spectroscopy (NIRS) has emerged as a successful technique for assessing chemical compositions. Therefore, in this study, the feasibility of NIRS in terms of predicting fecal chemical composition was explored. Cattle fecal samples were subjected to chemical analysis using conventional wet chemistry techniques and a NIRS spectrometer. The resulting fecal spectra were used to construct predictive equations to estimate the chemical composition of the feces in both cows and calves. The coefficients of determination for calibration (RSQ) were employed to evaluate the calibration of the predictive equations. Calibration results for cows (dry matter [DM], RSQ = 0.98; crude protein [CP], RSQ = 0.93; ether extract [EE], RSQ = 0.91; neutral detergent fiber [NDF], RSQ = 0.82; acid detergent fiber [ADF], RSQ = 0.89; ash, RSQ = 0.84) and calves (DM, RSQ = 0.92; CP, RSQ = 0.89; EE, RSQ = 0.77; NDF, RSQ = 0.76; ADF, RSQ = 0.92; ash, RSQ = 0.97) demonstrated that NIRS is a cost-effective and efficient alternative for assessing the chemical composition of dairy cattle feces. This provides a new method for rapidly predicting fecal chemical content in cows and calves. Full article