Miracle-dz/UniFAR-FTUs huggingface dataset:
The destructive subterranean termite Reticulitermes flavipes (Blattodea: Rhinotermitidae) can colonize arid territories

Reticulitermes flavipes, one of the most destructive subterranean termite species, has been detected for the first time in an arid territory: Lanzarote (Canary Islands, Spain). This invasive species was introduced into several countries but never such a dry region. Although there are places with presence of this termite at similar or even higher temperatures, none has annual rainfall (10.1 mm) as low as Lanzarote. On this island it is present in semi-desert, near an affected urban area. Distribution, genetic, climate and host-plant data are evaluated to track and understand its invasion process in the archipelago.
Resilience and symptoms of depression and anxiety in adolescents: the mediating role of fear of missing out

This research aimed to determine the relationship of resilience and symptoms of depression and anxiety in Indonesian adolescents, particularly the degree to which the fear of missing out (FoMO) influenced resilience toward symptoms of depression and anxiety.Five hundred nine Indonesian adolescents aged 12-18 participated in this research. Three psychological measures were used in this research: the Fear of Missing Out Scale (FoMO), the Depression and Anxiety Stress Scale-21 (DASS-21), and the Connor-Davidson Resilience Scale (CD-RISC). The structural model showed that resilience did not significantly predict FoMO. It significantly and negatively affected depression, anxiety, and stress. Furthermore, FoMO was the strongest predictor for depression, followed by stress and anxiety. Gender significantly predicted psychological symptoms, with females being more prone to depression, anxiety, and stress than males. The percentage of variation explained for depression, anxiety, and stress was 15.8%, 15.1%, and 9.5%, respectively.The study indicated that with higher adolescents’ resilience status there was a lower tendency of depression and anxiety. Based on the mediation results, FoMO did not significantly mediate the relationship between resilience and depression. These findings contribute to the impacts of online anxiety-related variables that can generate symptoms of stress and depression in adolescents.
Regular ArticleDiaphyseal Cross-sectional Geometry of Near Eastern Middle Palaeolithic Humans: The Tibia

External osteometric assessments of Near Eastern Middle Palaeolithic human tibial diaphyseal robusticity have been used to argue for significant differences in locomotor loading regimes between late archaic and early modern humans from the Middle Palaeolithic of that region. Reassessment of tibial diaphyseal strength using cross-sectional geometry of their shafts scaled against biomechanically appropriate measures of body mass and beam length reveals no significant difference between the Near Eastern late archaic human and Qafzeh-Skhul early modern human samples. This is in agreement with other assessments of their comparative levels of locomotor strength and endurance indicating similar levels of summed loads upon their lower limbs once body mass and beam length are appropriately incorporated into the analysis. At the same time, there are no systematic differences in either relative cortical area within cross-sections or the biomechanically relevant distribution of bone (indicated by perpendicular second moments of area) between these samples. What emerges from a consideration of appropriately scaled measures of strength of these NEMP tibiae (however precise the estimates employed) is that, contrary to previous assessments, there are no grounds for inferring a significant change in locomotor activity levels or patterns between late archaic and early modern humans in the Near Eastern Middle Palaeolithic.
Caregiver self-efficacy providing nutritional support for pediatric patients undergoing hematopoietic stem cell transplant is associated with psychosocial factors

Introduction Caregiver self-efficacy in providing nutritional support to pediatric hematopoietic stem cell transplantation (HSCT) patients has been little studied despite the increased risk of these children potentially being over- or under-nourished after HSCT, and nutritional status could possibly affect treatment outcomes. The current study aimed to describe caregiver dietary self-efficacy and its associated psychosocial factors and barriers to following dietary recommendations. Methods Caregivers completed questionnaires pre-HSCT and 30 days, 100 days, and one year post-HSCT. A subset provided a 24-h recall of food intake. Results Results showed generally high caregiver confidence and low difficulty supporting their child nutritionally. However, lower confidence was associated with higher caregiver depression, anxiety, and stress 30 days post-HSCT. Further, higher difficulty at various time points was correlated with lower income, higher depression and anxiety, stress, and miscarried helping (i.e., negative caregiver-child interactions surrounding eating), as well as child overweight status and failure to meet protein intake guidelines. Nutritional criteria for protein, fiber, added sugar, and saturated fat were met by 65%, 0%, 75%, and 75%, respectively. Caregiver attitudes and child behavior were the most frequently reported barriers to healthy eating. Discussion Results suggest that directing resources to caregivers struggling emotionally, economically, or transactionally could support pediatric patients undergoing HSCT in maintaining optimal nutritional status.
Land-use scene classification based on a CNN using a constrained extreme learning machine

ABSTRACT Classifying land-use scenes from high-resolution remote-sensing imagery with high quality and accuracy is of paramount interest for science and land management applications. In this article, we proposed a new model for land-use scene classification by integrating the recent success of convolutional neural network (CNN) and constrained extreme learning machine (CELM). In the model, the fully connected layers of a pretrained CNN have been removed. Then, CNN works as a deep and robust convolutional feature extractor. After normalization, deep convolutional features are fed to the CELM classifier. To analyse the performance, the proposed method has been evaluated on two challenging high-resolution data sets: (1) the aerial image data set consisting of 30 different aerial scene categories with sub-metre resolution and (2) a Sydney data set that is a large high spatial resolution satellite image. Experimental results show that the CNN-CELM model improves the generalization ability and reduces the training time compared to state-of-the-art methods.
Associations between internet addiction and school engagement among Turkish college students: mediating role of psychological distress

Introduction Internet addiction has become a subject of growing concern with adverse consequences. This study aimed to investigate the mediating effect of psychological distress in the relationship between internet addiction and school engagement. Methods Data were obtained from 732 Turkish college students (M = 20.98, SD = 2.58). The data were collected through Young’s Internet Addiction Test, Depression, Stress and Anxiety Scale (DASS21)-Short Form, and University Student Engagement Inventory. Mediation analysis was performed to investigate the mediating effects of depression, anxiety, and stress in the association between internet addiction and school engagement. Results The results of the study showed that internet addiction was positively associated with psychological distress and negatively associated with school engagement, whereas psychological distress had a negative relationship with school engagement. This study also found that depression, anxiety, and stress acted as mediators in the relationship between internet addiction and behavioral engagement, emotional engagement, and cognitive engagement. Conclusion This study has provided evidence that young adults with tendency of internet addiction may experience school engagement problems as well as psychological problems. Our findings underscore the need for special educational intervention programs aimed at encouraging college youth to limit their internet use for their future due to its negative consequences and raising awareness in this vulnerable group and their families.
Advance Wave Modeling and Diffractions for High-Resolution Subsurface Seismic Imaging

Seismic modeling and Imaging for the small-scale feature in a complex subsurface geology such as salt deposit, fracture reservoir, and Carbonate is not casual because of propagated wave affected by many objects once it hits the geologic structure in the subsurface. The principal goal of newly developed seismic modeling & imaging is to get a subsurface image of structural features with greatest sharpness or resolution. Using model dataset the Sigsbee and Marmousi, we illustrate the accuracy of conventional and advance wave modeling techniques. However, in conventional a Finite difference (FD) algorithm is used to generate the data and in advanced wave modeling, the low-rank (LR) approximation is used to acquire zero-offset configuration data. A field dataset from Malaysian basin is re-processed and imaged using diffraction imaging which shows an enhancement in structural interpretation. Furthermore, the results gained from the proposed modeling and imaging approach significantly enhance the bandwidth of the imaged data. Finally, a frequency spectrum shows a recovery of low-frequency from 0 to 60 Hz which is an optimal resolution of seismic imaging.
Evaluation of the Surface Urban Energy and Water Balance Scheme (SUEWS) at a Dense Urban Site in Shanghai: Sensitivity to Anthropogenic Heat and Irrigation

The Surface Urban Energy and Water Balance Scheme (SUEWS) is used to investigate the impact of anthropogenic heat flux QF and irrigation on surface energy balance partitioning in a central business district of Shanghai. Diurnal profiles of QF are carefully derived based on city-specific hourly electricity consumption data, hourly traffic data, and dynamic population density. The QF is estimated to be largest in summer (mean daily peak 236 W m−2). When QF is omitted, the SUEWS sensible heat flux QH reproduces the observed diurnal pattern generally well, but the magnitude is underestimated compared to observations for all seasons. When QF is included, the QH estimates are improved in spring, summer, and autumn but are poorer in winter, indicating winter QF is overestimated. Inclusion of QF has little influence on the simulated latent heat flux QE but improves the storage heat flux estimates except in winter. Irrigation, both amount and frequency, has a large impact on QE. When irrigation is not considered, the simulated QE is underestimated for all seasons. The mean summer daytime QE is largely overestimated compared to observations under continuous irrigation conditions. Model results are improved when irrigation occurs with a 3-day frequency, especially in summer. Results are consistent with observed monthly outdoor water use. This study highlights the importance of appropriately including QF and irrigation in urban land surface models—terms not generally considered in many previous studies.
Biology and Life Table of Fall Armyworm Spodoptera Frugiperda (J.E. Smith) on Maize at Laboratory Conditions in Nepal

The biology and life table of Spodoptera frugiperda (J.E. Smith) was studied at 27±2 °C temperature and 75±10% relative humidity at a Laboratory in the National Entomology Research Center, Lalitpur, Nepal from June to October, 2021.The main purpose of the study is to determine life cycle and to prepare stage specific life table of the insect on the preferred host maize. The mean incubation, larval and pupal periods were found to be 2.79, 14.04 and 9.49 days, respectively. The adult longevity of male and female moths was recorded at 15.39 days and 16.16 days. Pre-oviposition, oviposition and post-oviposition periods of female moths were 3.27 days, 5.39 days and 6.85 days with the fecundity of 1712 eggs per gravid female. The width of head capsules of the first, second, third, fourth and fifth larval instars was observed to be 0.31 mm, 0.51 mm, 0.81 mm, 1.30 mm and 1.95 mm, respectively. The highest apparent mortality (13.39) and indispensable mortality (10.02) were recorded in the insect’s egg stage. Among larval instars, the maximum apparent mortality (7.1) and indispensable mortality (4.72) were recorded in the first instar.
Physical and Physiological Responses during the Stop-Ball Rule During Small-Sided Games in Soccer Players

Small-sided games (SSGs) are a recommended training method for significant performance enhancement, and training efficiency. The stop-ball (SSG-SB) effects on physical responses (e.g., acceleration, deceleration, sprints, total distance, and indicator of workload) have not been investigated yet. This study aimed to investigate the effects of the SSG-SB compared to the small-goals SSG (SSG-SG) on physical and heart rate (HR) responses at high intensity (total distance (>18 km/h)), sprints (>18 km/h), and acceleration and deceleration (>3 m/s²) during a 4 vs. 4 SSG format in youth professional soccer players. Sixteen male elite young soccer players (mean ± SD body height, 176.5 ± 6.3 cm; age, 18.3 ± 0.7 years; body weight, 73.4 ± 7.2 kg) performed two forms of SSGs, i.e., SSG-SB or SSG-SG, for 4 × 4 min with a recovery of 2 min between sets. Data were compared using the t-test. The SSG-SB induced a significantly higher mean HR (180.0 ± 2.0 vs. 173.0 ± 3.0 beats per minute; p < 0.05) compared to the SSG-SG. Likewise, the SSG-SB was significantly higher compared to the SSG-SG for total distance (2580 ± 220.3 vs. 2230 ± 210 m; p < 0.001), player load (98.07 ± 12.5 vs. 89.4 ± 10.5; p < 0.05), sprint distance (7.9 ± 2.3 vs. 5.2 ± 2.0 m; p < 0.05), acceleration (15.6 ± 2.75 vs. 12.5 ± 1.75; p < 0.05), and deceleration (17.3 ± 3.20 vs. 14.4 ± 2.55; p < 0.05). However, no significant difference was found between the SSG-SG and the SSG-SB for maximal velocity, power, and sprints duration. This study provides new information about the effectiveness of the SSG-SB as a training stimulus for soccer.
Assessment of the shortraker rockfish stock in the Bering Sea and Aleutian Islands

Changes in the assessment methodology: The assessment methodology has changed since the last full assessment in 2012. The previous method used the Gompertz-Fox surplus production model to estimate the shortraker rockfish population, and the Kalman filter to statistically estimate the parameter values. In 2014 biomass is estimated using the random effects model. This is the authors’ preferred model used in setting ABC and OFL.
A Risk Evaluation Framework in System Control Subject to Sensor Degradation and Failure

Sensor degradation and failure often undermine users’ confidence in adopting a new data-driven decision-making model, especially in risk-sensitive scenarios. A risk assessment framework tailored to classification algorithms is introduced to evaluate the decision-making risks arising from sensor degradation and failures in such scenarios. The framework encompasses various steps, including on-site fault-free data collection, sensor failure data collection, fault data generation, simulated data-driven decision-making, risk identification, quantitative risk assessment, and risk prediction. Leveraging this risk assessment framework, users can evaluate the potential risks of decision errors under the current data collection status. Before model adoption, ranking risk sensitivity to sensor data provides a basis for optimizing data collection. During the use of decision algorithms, considering the expected lifespan of sensors enables the prediction of potential risks the system might face, offering comprehensive information for sensor maintenance. This method has been validated through a case study involving an access control.
Predictive model and risk analysis for peripheral vascular disease in type 2 diabetes mellitus patients using machine learning and shapley additive explanation

Background Peripheral vascular disease (PVD) is a common complication in patients with type 2 diabetes mellitus (T2DM). Early detection or prediction the risk of developing PVD is important for clinical decision-making. Purpose This study aims to establish and validate PVD risk prediction models and perform risk factor analysis for PVD in patients with T2DM using machine learning and Shapley Additive Explanation(SHAP) based on electronic health records. Methods We retrospectively analyzed the data from 4,372 inpatients with diabetes in a hospital between January 1, 2021, and March 28, 2023. The data comprised demographic characteristics, discharge diagnoses and biochemical index test results. After data preprocessing and feature selection using Recursive Feature Elimination(RFE), the dataset was split into training and testing sets at a ratio of 8:2, with the Synthetic Minority Over-sampling Technique(SMOTE) employed to balance the training set. Six machine learning(ML) algorithms, including decision tree (DT), logistic regression (LR), random forest (RF), support vector machine(SVM),extreme gradient boosting (XGBoost) and Adaptive Boosting(AdaBoost) were applied to construct PVD prediction models. A grid search with 10-fold cross-validation was conducted to optimize the hyperparameters. Metrics such as accuracy, precision, recall, F1-score, G-mean, and the area under the receiver operating characteristic curve (AUC) assessed the models’ effectiveness. The SHAP method interpreted the best-performing model. Results RFE identified the optimal 12 predictors. The XGBoost model outperformed other five ML models, with an AUC of 0.945, G-mean of 0.843, accuracy of 0.890, precision of 0.930, recall of 0.927, and F1-score of 0.928. The feature importance of ML models and SHAP results indicated that Hemoglobin (Hb), age, total bile acids (TBA) and lipoprotein(a)(LP-a) are the top four important risk factors for PVD in T2DM. Conclusion The machine learning approach successfully developed a PVD risk prediction model with good performance. The model identified the factors associated with PVD and offered physicians an intuitive understanding on the impact of key features in the model.
Estimation of degradation rates in water for outdoor cosms with measured concentrations in water and sediment : guidance for inverse modelling using TOXSWA

of nature to improve the quality of life”. Under the banner Wageningen University & Research, Wageningen University and the specialised research institutes of the Wageningen Research Foundation have joined forces in contributing to inding solutions to important questions in the domain of healthy food and living environment. With its roughly 30 branches, 5,000 employees and 10,000 students, Wageningen University & Research is one of the leading organisations in its domain. The unique Wageningen approach lies in its integrated approach to issues and the collaboration between different disciplines.
Vestibular function in cases of posterior semicircular canal canalolithiasis and cupulolithiasis

Objective To analyze and compare the vestibular function of posterior canal cupulolithiasis and canalolithiasis. Methods The results of posterior cupulolithiasis in 45 cases, posterior canalolithiasis in 122 cases and 19 healthy controls were analyzed retrospectively. Results The abnormal rates of vHIT in the canalolithiasis group and the cupulolithiasis group were 42.6 and 37.8%, respectively, both higher than those in the control group (both p < 0.05); there was no statistically significant difference between two BPPV groups (p = 0.573). The abnormal vHIT in 76.9% of the canalolithiasis cases and 82.4% of the cupulolithiasis cases showed normal gain with saccades, with no difference between the groups (p = 0.859). The lesion location of vHIT in the two groups did not show a correlation with the affected side of BPPV (both p > 0.05). 84.4% of canalolithiasis and 65.0% of cupulolithiasis had abnormal VEMP results, with no significant differences in abnormality rates or sides (both p > 0.05). Abnormal results of VEMPs did not show any correlation with side (p > 0.05). The results of pc-ca and pc-cu were both abnormal in 14 cases and 7 cases, and there was no correlation between the site and side of the injury (all p > 0.05). Conclusion The results of vHIT and VEMP in pc-cu and pc-ca were partially abnormal, but they did not show any correlation with side of BPPV. It can be considered that there are scattered vestibular peripheral organ damage in both groups.
Hemodynamic Response to Exercise Training in Heart Failure With Reduced Ejection Fraction Patients

Background Supervised exercise training decreases total and cardiac mortality and increases quality of life of heart failure with reduced ejection fraction (HFrEF) patients. However, response to training is variable from one patient to another and factors responsible for a positive response to training remain unclear. The aims of the study were to compare cardiac hemodynamic changes after an exercise training program in responders (R) versus non-responders (NR) HFrEF patients, and to compare different discriminators used to assess response to training. Methods Seventy-six HFrEF patients (86% males, 57 ± 12 years) completed an exercise training program for 4 weeks. Patients underwent cardiopulmonary exercise testing (CPET) on a cycle ergometer before and after training. Cardiac hemodynamics were measured by impedance cardiography during CPET. The R and NR groups were classified using the median change in peak oxygen uptake (V̇O2peak). Results There were statistically significant differences in V̇O2peak (+35% vs. -1%, P < 0.0001) and in peaks of ventilation (+30% vs. +2%, P < 0.0001), cardiac output (COpeak) (+25% vs. +4%, P < 0.01), systolic blood pressure (+12% vs. +2%, P < 0.05), diastolic blood pressure (+9% vs. +4%, P < 0.05) and heart rate (+8% vs. +1%, P < 0.01) between R and NR after the training program. V̇O2peak was the best discriminator between R and NR (receiver operating characteristic (ROC) area under the curve (AUC) = 0.83, P < 0.0001), followed by COpeak (ROC AUC = 0.77, P < 0.0001). Conclusion V̇O2peak is the best discriminator between HFrEF R and NR patients after the training program. Responders showed improvements in peak hemodynamic parameters. These results pave the way for other studies to determine how the individualization of exercise training programs and peak hemodynamic parameters potentially linked to a better positive response status.