Search Results (3,361)

Accurately predicting how quickly people will adopt electric vehicles (EVs) is vital for planning charging stations, managing supply chains, and shaping climate policy. We present a forecasting model that uses three separate Long Short‑Term Memory (LSTM) branches—one for past EV sales, one for infrastructure and policy signals, and one for economic trends. An attention mechanism first highlights the most important weeks in each branch, then decides which branch matters most at any point in time. Trained end‑to‑end on publicly available data, the model beats traditional statistical methods and newer deep learning baselines while remaining small enough to run efficiently. An ablation study shows that every branch and both attention steps improve accuracy, and that adding policy and economic data helps more than relying on EV history alone. Because the network is modular and its attention weights are easy to interpret, it can be extended to produce confidence intervals, include physical constraints, or forecast adoption of other clean‑energy technologies. Full article

Polysaccharides and phenols are commonly co-localized in various plant-derived foods, including highland barley (Hordeum vulgare L. var. nudum Hook. f.). The interactions between these compounds can influence multiple characteristics of food products, including their physicochemical properties and functional performance, such as bioavailability, stability, and digestibility, which may support promising application of the phenol and polysaccharide complex in health food industry. In this study, two complexes with potential existence in highland barley, such as β-glucan-ferulic acid (GF) and β-glucan-quercetin (GQ), were prepared using the equilibrium dialysis method in vitro. FTIR and SEM results showed that ferulic acid and quercetin formed complexes with β-glucan separately, with covalent and non-covalent bonds and a dense morphological structure. The pH value, reaction temperature, and concentration of phosphate buffer solution (PBS) were confirmed to have an impact on the formation and yield of the complex. Through the test of the response surface, it was found that the optimum conditions for GF and (GQ) preparations were a pH of 6.5 (6), a PBS buffer concentration of 0.08 mol/L (0.3 mol/L), and a temperature of 8 °C (20 °C). Through in vitro assays, GF and GQ were found to possess good antioxidant activity, with a greater scavenging effect of DPPH, ABTS, and hydroxyl radical than the individual phenolic acids and glucans, as well as their physical mixtures. Taking GF as an example, the DPPH radical scavenging capacity ranked as GF (71.74%) > ferulic acid (49.50%) > PGF (44.43%) > β-glucan (43.84%). Similar trends were observed for ABTS radical scavenging (GF: 54.56%; ferulic acid: 44.37%; PGF: 44.95%; β-glucan: 36.42%) and hydroxyl radical elimination (GF: 39.16%; ferulic acid: 33.06%; PGF: 35.51%; β-glucan: 35.47%). In conclusion, the convenient preparation method and excellent antioxidant effect of the phenol–polysaccharide complexes from highland barley provide new opportunities for industrial-scale production, development, and design of healthy food based on these complexes. Full article

Cardiorespiratory fitness is a predictor of long-term health, traditionally assessed through structured exercise protocols that require maximal effort and controlled laboratory conditions. These protocols, while clinically validated, are often inaccessible, physically demanding, and unsuitable for unsupervised monitoring. This study proposes a non-invasive, unsupervised alternative—predicting the heart rate a person would reach after completing the step test, using wearable data collected during natural daily activities. Ground truth post-exercise heart rate was obtained through the Queens College Step Test, which is a submaximal protocol widely used in fitness settings. Separately, wearable sensors recorded heart rate (HR), blood oxygen saturation, and motion data during a protocol of lifestyle tasks spanning a range of intensities. Two machine learning models were developed—a Human Activity Recognition (HAR) model that classified daily activities from inertial data with 96.93% accuracy, and a regression model that estimated post step test HR using motion features, physiological trends, and demographic context. The regression model achieved an average root mean squared error (RMSE) of 5.13 beats per minute (bpm) and a mean absolute error (MAE) of 4.37 bpm. These findings demonstrate the potential of test-free methods to estimate standardized test outcomes from daily activity data, offering an accessible pathway to infer cardiorespiratory fitness. Full article

Over the last few decades, the growing demand for sustainable resources has made biopolymers increasingly popular, as they offer an eco-friendly alternative to conventional synthetic polymers, which are often associated with environmental issues such as the formation of microplastics and toxic substances. Functionalization of biomaterials involves modifying their physical, chemical, or biological properties to improve their performance for specific applications. Cellulose and bacterial cellulose are biopolymers of interest, due to the plethora of hydroxyl groups, their high surface area, and high porosity, which makes them ideal candidates for several applications. However, there are applications, which require precise control of their wetting properties. In this review, we present the most effective fabrication methods for modifying both the morphology and the chemical properties of cellulose and bacterial cellulose, towards the realization of superhydrophobic bacterial cellulose films and surfaces. Such materials can find a wide variety of applications, yet in this review we target and discuss applications deriving from the wettability control, such as antibacterial surfaces, wound healing films, and separation media. Full article

The discharge of oily wastewater threatens the ecosystem and human health, and the efficient treatment of oily wastewater is confronted with problems of high mass transfer resistance at the oil-water-solid multiphase interface, significant light shielding effect, and easy deactivation of photocatalysts. Although traditional physical separation methods avoid secondary pollution by chemicals and can effectively separate floating oil and dispersed oil, they are ineffective in removing emulsified oil with small particle sizes. To address these complex challenges, photocatalytic technology and photocatalysis-based improved technologies have emerged, offering significant application prospects in degrading organic pollutants in oily wastewater as an environmentally friendly oxidation technology. In this paper, the degradation mechanism, kinetic mechanism, and limitations of conventional photocatalysis technology are briefly discussed. Subsequently, the surface interface modulation functions of metal doping and heterojunction energy band engineering, along with their applications in enhancing the light absorption range and carrier separation efficiency, are reviewed. Focus on typical studies on the separation and degradation of aqueous and oily phases using photocatalytic membrane technology, and illustrate the advantages and mechanisms of photocatalysts loaded on the membranes. Finally, other new approaches and converging technologies in the field are outlined, and the challenges and prospects for the future treatment of oily wastewater are presented. Full article

The current paper presents a comprehensive intelligent system designed to optimize the performance of a barrier eddy current separator (BECS), comprising a conveyor belt, a vibration feeder, and a magnetic drum. This system was trained and validated on real-world industrial data gathered directly from the working separator under 81 different operational scenarios. The intelligent models were used to recommend optimal settings for drum speed, belt speed, vibration intensity, and drum angle, thereby maximizing separation quality and minimizing energy consumption. the smart separation module utilizes YOLOv11n-seg and achieves a mean average precision (mAP) of 0.838 across 7163 industrial instances from aluminum, copper, and plastic materials. For shape classification (sharp vs. smooth), the model reached 91.8% accuracy across 1105 annotated samples. Furthermore, the thermal monitoring unit can detect iron contamination by analyzing temperature anomalies. Scenarios with iron showed a maximum temperature increase of over 20 °C compared to clean materials, with a detection response time of under 2.5 s. The architecture integrates a Digital Twin using Azure Digital Twins to virtually mirror the system, enabling real-time tracking, behavior simulation, and remote updates. A full connection with the PLC has been implemented, allowing the AI-driven system to adjust physical parameters autonomously. This combination of AI, IoT, and digital twin technologies delivers a reliable and scalable solution for enhanced separation quality, improved operational safety, and predictive maintenance in industrial recycling environments. Full article

The constitutive model is widely employed to characterize the rheological properties of metallic materials under high-temperature conditions. It is typically derived from a series of high-temperature tests conducted at varying deformation temperatures, strain rates, and strains, including hot stretching, hot compression, separated Hopkinson pressure bar testing, and hot torsion. The original experimental data used for establishing the constitutive model serves as the foundation for developing phenomenological models such as Arrhenius and Johnson–Cook models, as well as physical-based models like Zerilli–Armstrong or machine learning-based constitutive models. The resulting constitutive equations are integrated into finite element analysis software such as Abaqus, Ansys, and Deform to create custom programs that predict the distributions of stress, strain rate, and temperature in materials during processes such as cutting, stamping, forging, and others. By adhering to these methodologies, we can optimize parameters related to metal processing technology; this helps to prevent forming defects while minimizing the waste of consumables and reducing costs. This study provides a comprehensive overview of commonly utilized experimental equipment and methods for developing constitutive models. It discusses various types of constitutive models along with their modifications and applications. Additionally, it reviews recent research advancements in this field while anticipating future trends concerning the development of constitutive models for high-temperature deformation processes involving metallic materials. Full article

Background/Objectives: Iron deficiency without anaemia (IDNA) is common in non-dialysis-dependent chronic kidney disease (CKD) and contributes to fatigue, reduced exercise tolerance, and impaired quality of life (QoL). While intravenous (IV) iron replacement is known to benefit anaemic patients, its role in IDNA remains uncertain. This study aimed to evaluate the impact of ferric derisomaltose (FDI) on patient-reported QoL outcomes in CKD patients with IDNA. Methods: This was a post hoc analysis of the double-blind, multicentre Iron and the Heart randomised controlled trial. Fifty-four participants with IDNA (ferritin < 100 µg/L or transferrin saturation < 20% and haemoglobin 110–150 g/L) and CKD stages G3b–G5 were randomised 1:1 to receive either 1000 mg FDI (n = 26) or placebo (n = 28). An additional 10 iron-replete CKD patients served as controls. SF-36v2 QoL surveys were collected at baseline, 1 month, and 3 months. Results: SF-36v2 scores declined across all domains, but deterioration was consistently milder in the FDI group. Role physical declined by 3% in the FDI group versus 12% with placebo and 4% in controls. Bodily pain improved by 2.8% with FDI but worsened by 1.5% in the placebo group. Mental health improved by 3.4 points with FDI and declined by 2.7 points in the placebo group, creating a 6.1-point separation. While differences did not reach statistical significance, likely due to small sample size, the consistent trends favour FDI. Conclusions: IV iron may attenuate QoL decline in non-dialysis-dependent CKD patients with IDNA. These findings support the need for larger, adequately powered trials to assess patient-centred outcomes in this population. Full article

This paper proposes a novel hierarchical control architecture that combines Model Predictive Control (MPC) with Explicit Model-Following Control (EMFC) to enable accurate and efficient trajectory tracking for quadrotor electric Vertical Takeoff and Landing (eVTOL) aircraft operating in urban environments. The approach addresses the challenges of strong nonlinear dynamics, multi-axis coupling, and stringent safety constraints by separating the planning task from the fast-response control task. The MPC layer generates constrained velocity and yaw rate commands based on a simplified inertial prediction model, effectively reducing computational complexity while accounting for physical and operational limits. The EMFC layer then compensates for dynamic couplings and ensures the rapid execution of commands. A high-fidelity simulation model, incorporating rotor flapping dynamics, differential collective pitch control, and enhanced aerodynamic interference effects, is developed to validate the controller. Four representative ADS-33E-PRF tasks—Hover, Hovering Turn, Pirouette, and Vertical Maneuver—are simulated. Results demonstrate that the proposed controller achieves accurate trajectory tracking, stable flight performance, and full compliance with ADS-33E-PRF criteria, highlighting its potential for autonomous urban air mobility applications. Full article

One of the persistent challenges in multispectral image analysis is the interference caused by dense cloud cover and its resulting shadows, which can significantly obscure surface features. This becomes especially problematic when attempting to monitor surface changes over time using satellite imagery, such as from Landsat-8. In this study, rather than simply masking visual obstructions, we aimed to investigate the role and influence of clouds within the spectral data itself. To achieve this, we employed Independent Component Analysis (ICA), a statistical method capable of decomposing mixed signals into independent source components. By applying ICA to selected Landsat-8 bands and analyzing each component individually, we assessed the extent to which cloud signatures are entangled with surface data. This process revealed that clouds contribute to multiple ICA components simultaneously, indicating their broad spectral influence. With this influence on multiple wavebands, we managed to configure a set of components that could perfectly delineate the extent and location of clouds. Moreover, because Landsat-8 lacks cloud-penetrating wavebands, such as those in the microwave range (e.g., SAR), the surface information beneath dense cloud cover is not captured at all, making it physically impossible for ICA to recover what is not sensed in the first place. Despite these limitations, ICA proved effective in isolating and delineating cloud structures, allowing us to selectively suppress them in reconstructed images. Additionally, the technique successfully highlighted features such as water bodies, vegetation, and color-based land cover differences. These findings suggest that while ICA is a powerful tool for signal separation and cloud-related artifact suppression, its performance is ultimately constrained by the spectral and spatial properties of the input data. Future improvements could be realized by integrating data from complementary sensors—especially those operating in cloud-penetrating wavelengths—or by using higher spectral resolution imagery with narrower bands. Full article

Background/Objectives: Improvements in depression and anxiety, associated with moderate increases in physical activity, might induce reductions in emotional eating, especially in women with obesity, where emotion-driven eating is highly problematic. This pilot, field-based study sought to assess whether physical activity increase, itself, primarily predicts improved mood (biochemical theories) or if psychosocial factors associated with cognitive–behavioral treatment are principal correlates (behavioral theories). An aim was to inform improved treatment processes. Methods: Women with obesity participated in 6-month community-based behavioral obesity treatments emphasizing either: (a) standard education in weight-reduction methods (n = 28), (b) eating-related self-regulation methods (n = 24), or (c) self-regulation + relaxation training (n = 24). They completed a series of behavioral and psychological self-reports at baseline and Months 3 and 6. Results: Findings confirmed no significant difference in 3-month increases in physical activity, by group. There were significantly greater overall improvements in depression, emotional eating, self-regulation, and self-efficacy across the two self-regulation-focused groups (ps < 0.02), with anxiety improvement not reaching significance (p = 0.055). Separate significant paths from 3-month changes in depression and anxiety → self-efficacy change → emotional eating change were found. The same significant path was detected emanating from 6-month anxiety change; however, the hypothesized path of 6-month changes in depression → self-regulation → self-efficacy → emotional eating was, rather, significant. Weight reduction was considerably greater in the two self-regulation-based groups (~6% reduction), with simultaneously entered changes in self-regulation and self-efficacy significant predictors of those weight changes. Conclusions: Findings suggested viability in behavioral theory-driven explanations of the physical activity-mood improvement relationship. Future treatment foci on self-regulatory skills development leading to improvements in eating-related self-efficacy, emotional eating, and weight were suggested to extend the findings of this pilot study. Full article

This study explored gender-specific nuances in the applicability of Social Cognitive Theory (SCT) to predict physical activity behavior. This study aimed to determine whether similar or different prediction patterns emerge for men and women, particularly emphasizing the tenability of the SCT model’s theoretical assumptions across gender. Six hundred fifty-four participants (58.1% women, 41.1% men) completed two validated questionnaires at separate time points (t1 = social cognitive and demographic variables; t2 = physical activity behavior). We employed a multigroup Structural Equation Model (SEM) to examine the validity of the theoretical assumptions and the influence of gender. The results suggest that SCT’s theoretical assumptions hold true for men and women, indicated by a highly satisfactory fit of the SEM despite the variance explained being small (R²_women = 11.9%, R²_men = 7.3%). However, the importance of the specific theoretical paths and the underlying mechanisms of action might differ between genders, and the interplay of the social and cognitive variables to predict physical activity may vary significantly for men and women. The use of SCT can be recommended for explaining and predicting physical activity behavior, although gender-specific differences in the underlying theoretical relationships should be taken into consideration when designing interventions or when being used to explain physical activity behavior. Full article

Background/Objectives: Juvenile idiopathic arthritis (JIA) and inflammatory bowel disease (IBD) are chronic autoimmune conditions that impact the physical and psychological well-being of pediatric patients. While previous studies have shown a high prevalence of mental health challenges among youth with chronic conditions, the prevalence of mental health issues in Canadian pediatric patients with JIA and IBD remains unclear. We aimed to estimate the prevalence of documented mental health disorders and related medication use of youth with JIA or IBD at a tertiary care centre. Methods: We conducted a retrospective chart review of youths aged 12–17 diagnosed with JIA or IBD at McMaster Children’s Hospital (MCH) to understand the prevalence of generalized anxiety disorder (GAD), separation anxiety disorder, social anxiety disorder (SAD), obsessive–compulsive disorders (OCD), eating disorders, major depressive disorder (MDD), adolescent adjustment disorder, suicide attempt/suicide ideation, self-harm behaviour, substance use disorder, and attention deficit disorders (ADD). Results: We reviewed 429 patient charts, including 303 patients with IBD and 126 with JIA. Our findings identified 90 IBD patients and 20 JIA patients who had one or more documented mental health conditions. Proportionately, there was a higher prevalence of mental health conditions among IBD patients (30%) compared to JIA patients (16%). The most frequently observed conditions in both IBD and JIA patients were GAD (63%, 50%), ADD (33%, 35%), and MDD (29%, 15%). Conclusions: These findings highlight the critical need for early mental health screening and integrated care approaches that address both medical and psychosocial needs in adolescents with chronic illnesses. Future research should incorporate prospective study designs, include diverse geographic and demographic populations, and explore targeted interventions to improve mental and physical health outcomes in this vulnerable group. Full article

Background and Clinical Significance: Serratus Anterior Muscle Pain Syndrome (SAMPS) is an underdiagnosed cause of anterior chest wall pain, often attributed to myofascial trigger points of the serratus anterior muscle (SAM) or dysfunction of the Long Thoracic Nerve (LTN), leading to significant disability and affecting ipsilateral upper limb movement and quality of life. Current diagnosis relies on exclusion and physical examination, with limited treatment options beyond conservative approaches. This case report presents a novel approach to chronic SAMPS, successfully diagnosed using Sonoguided Digital Palpation (SDP) and treated with ultrasound-guided hydrodissection of the LTN using 5% dextrose in water (D5W) without local anesthetic (LA), in a patient where conventional treatments had failed. Case Presentation: A 72-year-old male presented with a three-year history of persistent left chest pain radiating to the upper back, exacerbated by activity and mimicking cardiac pain. His medical history included two percutaneous coronary interventions. Physical examination revealed tenderness along the anterior axillary line and a positive hyperirritable spot at the mid axillary line at the 5th rib level. SDP was used to visualize the serratus anterior fascia (SAF) and LTN, and to reproduce the patient’s concordant pain by palpating the LTN. Ultrasound-guided hydrodissection of the LTN was then performed using 20–30cc of D5W without LA to separate the nerve from the surrounding tissues, employing a “fascial unzipping” technique. The patient reported immediate pain relief post-procedure, with the pain reducing from 9/10 to 1/10 on the Numeric Rating Scale (NRS), and sustained relief and functional improvement at the 12-month follow-up. Conclusions: Sonoguided Digital Palpation (SDP) of the LTN can serve as a valuable diagnostic adjunct for visualizing and diagnosing SAMPS. Ultrasound-guided hydrodissection of the LTN with D5W without LA may provide a promising and safe treatment option for patients with chronic SAMPS refractory to conservative management, resulting in rapid and sustained pain relief. Further research, including controlled trials, is warranted to evaluate the long-term efficacy and generalizability of these findings and to compare D5W to other injectates. Full article

Engineering of Cupriavidus necator could enable the production of various polyhydroxyalkanoates (PHAs); particularly, poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (P(3HB-co-3HH)), a biopolymer with enhanced mechanical and thermal properties compared to poly(3-hydroxybutyrate) (PHB), can be efficiently produced from vegetable oils. However, challenges remain in the recovery process, particularly in removing residual oil and minimizing degradation of the polymer structure during extraction steps. This study investigated the effects of ethanol-based defatting on the recovery and polymeric properties of P(3HB-co-3HH). The proposed method involves the addition of ethanol to the cell broth to effectively remove residual oil. Ethanol improved the separation of microbial cells from the broth, thereby streamlining the downstream recovery process. Using ethanol in the washing step increased the recovery yield and purity to 95.7% and 83.4%, respectively (compared to 87.4% and 76.2% for distilled water washing), representing improvements of 8.3% and 7.2%. Ethanol washing also resulted in a 19% higher molecular weight compared to water washing, indicating reduced polymer degradation. In terms of physical properties, the elongation at break showed a significant difference: 241.9 ± 27.0% with ethanol washing compared to water (177.7 ± 10.3%), indicating ethanol washing retains flexibility. Overall, an ethanol washing step for defatting could simplify the recovery steps, increase yield and purity, and retain mechanical properties, especially for P(3HB-co-3HH) from oils. Full article