Search Results (3,383)

Decision-making, defined as a cognitive process involving the selection of a course of action among several alternatives, is pivotal in personal and professional life and is founded on responsiveness to the context of decisional strategies—in terms of pieces of contextual features collected, evaluated, and integrated. This study explored the behavioral and electrophysiological (EEG) correlates of individual tendencies to rely on three distinct decisional strategies: Information (I-ds), Situation (S-ds), or Task (T-ds). A total of 51 individuals performed a decision-making task that required participants to face real-life decision-making situations, during which an unexpected event prompted them to appraise the situation and rely on different sources of contextual features to make the best decision and manage the problem. The behavioral data and EEG frequency bands (delta, theta, alpha, beta, and gamma) were collected during the decision-making task. The results evidenced a general predisposition to adopt a T-ds. In addition, EEG findings reported a higher increase in theta band power in the right frontal area (AF8) compared to the left temporoparietal site (TP9). Moreover, for the gamma band, higher activity was found in the T-ds compared to the I-ds in AF8. Overall, responsiveness to the context was closely linked to the assignment’s requirements. Additionally, adopting a T-ds requires high levels of multilevel attention control systems and a significant workload on human performance. Nevertheless, the T-ds remain the most employed type of responsiveness to the context approach, when compared to situational and contextual aspects. Full article

Soil salinisation is a critical problem in northern China’s arid and semi-arid irrigated regions, posing a substantial impediment to the sustainable advancement of agriculture in these areas. This research utilises the Donghaixin Irrigation District, located on the southern bank of the Yellow River in Inner Mongolia, as a case study. This study examines the spatial distribution and determinants of soil salinisation through macro-environmental variables and micro-ion composition, integrating regression models and groundwater ion characteristics to elucidate the patterns and causes of soil salinisation systematically. The findings demonstrate that soil salinisation in the study region displays notable spatial clustering, with surface water-irrigated regions exhibiting greater salinisation levels than groundwater-irrigated areas. More than 80% of the land exhibits moderate salinity, predominantly characterised by the ions Cl⁻, HCO₃⁻, and SO₄²⁻. The hierarchy of ion concentration variation with escalating soil salinity is as follows: Na⁺ > K⁺ > SO₄²⁻ > Cl⁻ > Mg²⁺ > HCO₃⁻ + CO₃²⁻ > Ca²⁺. The susceptibility of ions to soil salinisation is ordered as follows: Ca²⁺ > Na⁺ > HCO₃⁻ + CO₃²⁻ > Mg²⁺ > K⁺ > Cl⁻ > SO₄²⁻. In contrast to the ordinary least squares (OLS) model, the geographic weighted regression (GWR) model more effectively elucidates the geographical variability of salinity, evidenced by an adjusted R² of 0.68, particularly in high-salinity regions, where it more precisely captures the trend of observed values. Ecological driving elements such as organic matter (OM), pH, groundwater depth (GD), total dissolved solids (TDS), digital elevation model (DEM), normalised difference vegetation index (NDVI), soil moisture (SM), and potential evapotranspiration (PET) govern the distribution of salinisation. In contrast, anthropogenic activities affect the extent of salinisation variation. Piper’s trilinear diagram demonstrates that Na cations mainly characterise groundwater and soil water chemistry. In areas irrigated by surface water, the concentration of SO₄²⁻ is substantially elevated and significantly affected by agricultural practises; conversely, in groundwater-irrigated regions, Cl⁻ and HCO₃⁻ are more concentrated, primarily driven by evaporation and ion exchange mechanisms. Full article

L-rhamnose has recently gained attention for its potential to enhance vaccine antigenicity. To optimize its use as a vaccine adjuvant, it is important to understand the dehydration behavior of L-rhamnose monohydrate, which plays a critical role in modifying its physicochemical properties. This study investigated the spectroscopic characteristics of L-rhamnose and its monohydrate using terahertz time-domain spectroscopy (THz-TDS), Raman spectroscopy, and powder X-ray diffraction (PXRD). The results indicate that THz-TDS can more effectively distinguish the spectral features of these two compounds and can be used to reflect the structural changes in L-rhamnose monohydrate before and after dehydration. THz spectral data show that dehydration of L-rhamnose occurs at 100 °C, and continuous heating at 100 °C can complete the dehydration process within 6 min. Density functional theory (DFT) calculations revealed that water molecule vibrations significantly affect the THz absorption peaks. These findings indicate that removing water during dehydration causes substantial changes in molecular structure and dynamics. Overall, this study highlights the value of combining THz-TDS with DFT calculations to investigate the structures of carbohydrates and their hydrates, providing an accurate method for understanding the dehydration process and molecular interactions in hydrated systems. This approach holds significant importance for the development of effective vaccine adjuvants. Full article

Children with severe motor and communication impairments (SMCIs) face significant challenges in expressing emotions, often leading to unmet needs and social isolation. This study investigated the potential of machine learning to identify emotions in children with SMCIs through the analysis of physiological signals. A model was created based on the data from the DEAP online dataset to identify the emotions of typically developing (TD) participants. The DEAP model was then adapted for use by participants with SMCIs using data collected within the Building and Designing Assistive Technology Lab (BDAT). Key adaptations to the DEAP model resulted in the exclusion of respiratory signals, a reduction in wavelet levels, and the analysis of shorter-duration data segments to enhance the model’s applicability. The adapted SMCI model demonstrated an accuracy comparable to the DEAP model, performing better than chance in TD populations and showing promise for adaptation to SMCI contexts. The models were not reliable for the effective identification of emotions; however, these findings highlight the feasibility of using machine learning to bridge communication gaps for children with SMCIs, enabling better emotional understanding. Future efforts should focus on expanding the data collection of physiological signals for diverse populations and developing personalized models to account for individual differences. This study underscores the importance of collecting data from populations with SMCIs for the development of inclusive technologies to promote empathetic care and enhance the quality of life of children with communication difficulties. Full article

Dynamic path planning enables vehicles to autonomously navigate in unknown or continuously changing environments, thereby reducing reliance on fixed maps. Deep reinforcement learning (DRL), with its superior performance in handling high-dimensional state spaces and complex dynamic environments, has been widely applied to dynamic path planning. Traditional DRL methods are prone to capturing unnecessary noise information and irrelevant features during the training process, leading to instability and decreased adaptability of models in complex dynamic environments. To address this challenge, we propose a dynamic path-planning method based on our Causal State-Masking Twin-delayed Deep Deterministic Policy Gradient (CSM-TD3) algorithm. CSM-TD3 integrates a causal inference mechanism by introducing dynamic state masks and intervention mechanisms, allowing the policy network to focus on genuine causal features for decision optimization and thereby enhancing the convergence speed and generalization capabilities of the agent. Furthermore, causal state-masking DRL allows the system to learn the optimal mask configurations through backpropagation, enabling the model to adaptively adjust the causal features of interest. Extensive experimental results demonstrate that this method significantly enhances the convergence of the TD3 algorithm and effectively improves its performance in dynamic path planning. Full article

This study aimed to explore the prevalence of learning disabilities (LDs) and the emotional–behavioral difficulties in 208 children from the Crete region in Greece, and who voluntarily presented themselves for study and were evaluated by a university-based interdisciplinary team of mental health professionals. The Greek version of the Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V GR) was used, with its five Primary Index scores and full-scale IQ (Verbal Comprehension Index, VCI; Visual Spatial Index, VSI; Fluid Reasoning Index, FRI; Working Memory Index, WMI; and Processing Speed, PCI). Five diagnostic categories were established for the purpose of analysis: (a) no LDs (TD group), (b) Attention Deficit Hyperactivity Disorder (ADHD), (c) Specific Learning Disabilities (SLDs), (d) Extremely Low FSIQ (below 79), and (e) Emotional/Behavioral difficulties. The results revealed a 25.5% prevalence of SLDs, 18.75% ADHD, 8.65% Extremely Low FSIQ, and 5.29% emotional/behavioral problems, suggesting that 58% of the study population struggled with some kind of learning difficulty. Statistically significant differences were observed between the “Extremely Low FSIQ” group, the “SLD”, the “ADHD”, and the “TD” diagnostic groups in terms of the “VCI”, “FRI”, and the “FSIQ” scales (p < 0.001). Likewise, the “Extremely Low FSIQ” group differed significantly from the “SLD” and “TD” groups in terms of the “VSI”, the WMI, and the “PSI” (p < 0.001). The “Behavioural/emotional” and “SLD” groups differed in terms of “VCI” and “Full scale IQ” (p < 0.001). The analysis indicated that the children with severe learning difficulties differed from the other groups in terms of their cognitive profiles and that they needed tailor-made educational programs and interventions in a typical classroom. This study offers comparative data from a community sample of children, as well as generated initial evidence from non-clinical settings on the usability and the diagnostic accuracy of the Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V). Further research is suggested. The present study was funded by the Crete Region (MIS 5162111). Full article

This paper presents the application of reinforcement learning algorithms in the tuning of PID controllers for the control of some classes of continuous nonlinear systems. Tuning the parameters of the PID controllers is performed with the help of the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which presents a series of advantages compared to other similar methods from machine learning dedicated to continuous state and action spaces. The TD3 algorithm is an off-policy actor–critic-based method and is used as it does not require a system model. Double Q-learning, delayed policy updates and target policy smoothing make TD3 robust against overestimation, increase its stability, and improve its exploration. These enhancements make TD3 one of the state-of-the-art algorithms for continuous control tasks. The presented technique is applied for the control of a biotechnological system that has strongly nonlinear dynamics. The proposed tuning method is compared to the classical tuning methods of PID controllers. The performance of the tuning method based on the TD3 algorithm is demonstrated through a simulation, illustrating the effectiveness of the proposed methodology. Full article

Magnetorheological fluids (MRFs) are functional fluids that exhibit rapid and reproducible rheological responses to external magnetic fields. MRFs have been used to develop haptic devices with fine haptic information for teleoperated surgical systems. To achieve this, we developed various compact MRF clutches for haptics and integrated them into a twin-driven MRF actuator (TD-MRA). Several types of TD-MRAs were developed in prior studies. This study used three sets of TD-MRAs to construct a haptic device with a delta-type linkage system that displays a three-dimensional (3D) force vector for users in virtual reality or teleoperation systems. We described the kinematic design of the linkage system based on the torque performance of the TD-MRA and evaluated the output force performance using an open-loop force controller. The haptic interface was designed to achieve greater than 2 N of output forces and a motion range of ±50 mm. Experimental results demonstrated an average error of 0.1 N, indicating that the open-loop controller performed effectively in all directions at the tested platform positions. Full article

Groundwater is crucial for domestic, agricultural, and ecological uses, particularly in the lower reaches of arid basins, where its quality often limits availability. A total of 26 phreatic groundwater samples were collected from a typical endorheic watershed on the Tibetan Plateau to assess the hydrochemical characteristics of phreatic groundwater in the lower reaches of arid inland watersheds. The hydrochemical characteristics, quality, and formation mechanisms of groundwater were analyzed using the Entropy-Weight Water Quality Index (EWQI), irrigation water quality indexes (such as sodium adsorption ratio, soluble sodium percentage, and permeability index), hydrochemical diagrams, and correlation analysis. The findings indicate that phreatic groundwater in the lower reaches is slightly alkaline, with a substantial TDS variation from 252.58 to 1810.41 mg/L. Groundwater is predominantly characterized by fresh hydrochemical facies of HCO₃-Ca and HCO₃-Na types, with a few saline Cl-Na types present. The concentrations of NO₃⁻, NO₂⁻ and NH₄⁺, in groundwater range from 0.32 to 100.00 mg/L, 0.00 to 0.48 mg/L, and 0.00 to 0.20 mg/L, respectively, and 3.59%, 26.92%, and 7.69% of the samples exceeding the permissible drinking limits recommended by Chinese guideline and World Health Organization. Groundwater is classified as fresh at 80.8% of sampling sites and brackish at 19.2%. Approximately 96.2% of the sampled groundwaters is rated as excellent to medium quality according to EWQI assessments, suitable for domestic use, while 3.8% is of extremely poor quality and should be avoided for direct consumption. Groundwater from all sampling sites is suitable for agricultural irrigation and does not pose permeability hazards to the soil. Most groundwaters are suitable for long-term irrigation in terms of sodium hazards, with only 3.8% and 7.7% of samples falling into the “Permissible to Doubtful” and “Doubtful to Unsuitable” categories, respectively. Salinity poses the primary threat in long-term irrigation, with 38.5%, 53.8%, and 7.7% of sampled groundwaters exhibiting moderate, high, and very high salinity risks, respectively. Groundwater chemistry is primarily governed by water-rock interaction and evaporation, with additional impacts from agricultural inputs of nitrogen contaminants and chemicals. Agricultural practices contribute to elevated groundwater salinity in the study area, while natural evaporation drives salinity accumulation in the lower parts. In managing and utilizing groundwater resources in the study area and similar arid regions globally, attention should be paid to salinity caused by agricultural activities and natural evaporation, as well as nitrogen pollution from farming. Full article

Effective pretreatment is essential for achieving long-term stable operation and high water recovery during the desalination of alternative waters. This study developed a process modeling approach for technical, economic, energetic, and environmental assessments of pretreatment technologies to identify the impacts of each technology treating brackish water desalination brine with high scaling propensity. The model simulations evaluated individual pretreatment technologies, including chemical softening (CS), chemical coagulation (CC), electrocoagulation (EC), and ion exchange (IX). In addition, combinations of these pretreatment technologies aiming at the effective reduction of key scaling constituents such as hardness and silica were investigated. The three evaluation parameters in this assessment consist of levelized cost of water (LCOW, $/m³), specific energy consumption and cumulative energy demand (SEC|CED, kWh/m³), and carbon dioxide emissions (CO₂, kg CO_2-eq/m³). The case study evaluated in this work was the desalination brine from the Kay Bailey Hutchison Desalination Plant (KBHDP) with a total dissolved solids (TDS) concentration of 11,000 mg/L and rich in hardness and silica. The evaluation of individual pretreatment units from the highest to lowest LCOW, SEC|CED, and CO₂ emissions in the KBHDP brine was IX > CS > EC > CC, CS > IX > EC > CC, and CC > CS > EC > IX, respectively. In the case of pretreatment combinations for the KBHDP, the EC + IX treatment combination was shown to be the best in terms of the LCOW and CO₂ emissions. The modeling and evaluation of these pretreatment units provide valuable guidance on the selection of cost-effective, energy-efficient, and environmentally sustainable pretreatment technologies tailored to desalination brine applications for minimal- or zero-liquid discharge. Full article

A fast and green approach for the non-chromatographic assaying of volatile metalorganic compounds (VMOCs) is presented, involving the use of thermal desorption microwave-induced plasma optical emission spectrometry for the multi-species simultaneous determination of VMOCs in wastewater plant samples after headspace solid-phase microextraction (HSSPME-TD-MIP-OES), and optimized as a tool for the assessment of ambient exposure to hazardous VMOC pollutants. With the aim of VMOC monitoring, all species are separated and quantified within 10 s in comparison with about 10–20 min required by conventional GC-based procedures. Calibration against aqueous standards was carried out for several metalorganic species. The method was successfully applied for the quantitative extraction of As, Bi, Hg, Sb, Si and Sn compounds. Limits of detection ranging from 5 to 30 ng L⁻¹ and relative standard deviations lower than 4% were obtained. The method is appropriate for high-sample-throughput measurements, and it proved to be suitable for the analysis of wastewater and sewage sludge samples. Full article

Background: Understanding the balance between intensity and volume during training and competition is crucial for optimizing players’ performance and recovery in professional soccer. While worst-case scenarios (WCSs) are commonly used to assess peak match demands, little is known about how the time spent within WCS thresholds varies across congested and non-congested periods, especially when considering differences in playing time. This study examines the time spent at different percentages of WCSs during congested and non-congested periods for players with lower and higher playing times throughout training sessions and matches. Methods: Data were collected from a professional soccer team across a congested and non-congested match period. Twenty players were divided into two groups based on playing time: the top 10 playing times (PT 1–10) and the bottom 10 playing times (PT 11–20). WCS thresholds for total distance (TD) and the distance covered above 20 km·h⁻¹ (D20) were quantified in 10% increments, starting from 50% and increasing up to >100%. The time spent at each threshold was compared between periods and groups for the integrated soccer exercises performed during all training sessions. Repeated measures of ANOVA were used to analyze differences between playing time groups and periods. Results: During training, players spent significantly more time within the 50–90% WCS TD and WCS D20 thresholds during non-congested periods compared to congested periods (p < 0.05). However, no significant differences were observed in the time spent for >90% of the WCSs between periods (p > 0.05). Both PT 1–10 and PT 11–20 groups exhibited similar patterns of WCS achievement, with small effect sizes observed for a few indicators. Conclusion: Coaches should design training sessions that replicate or exceed match demands, particularly during non-congested periods. Future strategies should integrate larger-sided games with longer durations and dissociated contents to better individualize and optimize training loads, especially for non-starters. Full article

Nowadays, volatile organic compounds (VOCs) increasingly jeopardize ecosystem sustainability and human well-being. In this study, UiO-66 and its different electron beam (EB) irradiation doses (100, 300, 500 kGy) modified materials supported Pt catalysts, Pt/UiO-66 and Pt/UiO-66-X (X = 100, 300, and 500, representing the irradiation doses), were synthesized, and a series of characterizations were conducted on the samples. On this basis, the effectiveness of these catalysts was evaluated through the degradation of ethyl acetate. The study findings indicated that the sample irradiated at 100 kGy demonstrated superior catalytic performance. Thereafter, extensive tests with regard to water resistance, stability, and cycle performance indicated that the Pt/UiO-66-100 catalyst was characterized by satisfactory reusability and catalytic stability, even when faced with high heat and humidity. Further work with in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and thermal desorption–gas chromatography–mass spectrometry (TD-GC–MS) uncovered the process of degradation of ethyl acetate. This research provides a guideline for the design of high-performance VOC degradation catalysts through EB modification. Full article

This paper represents a comparative study of two rivers, namely, the Andarax River, Spain, and the River Liffey, Ireland, considering different climatic conditions and human activities and their influences on most water quality parameters. Water samples collected from different sampling sites along each river were analysed for field parameters such as the pH, dissolved oxygen (DO), total dissolved solids (TDS), electrical conductivity (EC), and nitrates, phosphates, and potassium (NPK) levels of floodplain soil. Spatial changes were assessed using various geostatistical methods such as the Pearson correlation, multiple linear regression (MLR), and water quality index (WQI). The Andarax River had a higher TDS and was turbidly higher with EC due to agricultural activities and the naturally higher evaporation in the semiarid climate. In contrast, DO levels varied widely in the River Liffey, especially in reaches under the influence of urbanisation and agricultural runoff. The artificial surface and agriculture are the strongest negative determinants of water quality in both rivers, with artificial surfaces contributing about 35.72% to the DO variation. The WQI identified the water quality in the Andarax River as poor to very poor in certain locations, while the River Liffey exhibited a good to medium quality overall, although with localised degradation in areas of high human activity. The results of this study are important for developing targeted remedial measures in diversified climate conditions and a customised water sustainability plan to address the challenges of each area. Full article

Aims: To develop and evaluate a novel AI-based video analysis tool for the quantitative assessment of “Places Pegs in” and “Blue Board” tasks in the Bayley Scales of Infant Development (BSID-II). Methods: A prospective cohort study was conducted from February 2022 to December 2022, including children aged 12–42 months referred for suspected developmental delay. Participants were evaluated using the BSID-II, and their performances on the two tasks were video recorded and analyzed with the novel tool. Sensitivity and specificity were determined by comparing the tool’s results to standard BSID-II assessments by therapists. Data collected included total time, number of trials, successful trials, and time and spatial intervals for each trial. Children were classified into typically developing (TD) (MDI ≥ 85) and developmental delay (DD) (MDI < 85) groups based on their mental developmental index (MDI). Results: A total of 75 children participated in the study, and the mean values of MDI and PDI for the enrolled children were 88.9 ± 18.7 and 80.0 ± 16.7. The “Places Pegs in” had 86.5% sensitivity and 100% specificity; the “Blue Board” had 96.9% sensitivity and 89.5% specificity. Differences in cumulative successes over time were observed between age groups and TD and DD groups. The tool automatically calculated maximum successes at specific time points. Interpretation: The AI-based tool showed high predictive accuracy for BSID-II tasks in children aged 12–42 months, indicating potential utility for developmental assessments. Full article