Search Results (3,553)

Background/Objectives: Understanding the interactions between nanoparticles and mucosal tissues is crucial for the development of advanced drug delivery systems, as the diffusion behavior of nanoparticles through mucus is strongly influenced by their size and surface properties, and the viscoelastic nature of the hydrogel matrix. In this study, we investigated the impact of nanoparticle size, surface charge, and hydrogel crosslinking density on nanoparticle diffusion in a mucus model in vitro. Method: Citrate-stabilized and PEGylated 30 and 100 nm gold nanoparticles were used as a model of nanoparticle and their diffusion through mucus-mimicking mucin-based hydrogels of two different crosslinking densities was assessed. Results: Citrate-stabilized 30 nm nanoparticles demonstrated greater diffusion in hydrogels mimicking native mucus compared to more densely crosslinked ones, reaching approximately 50.3 ± 0.2% diffusion within the first 5 min of the assay. This size-dependent effect was not observed for the 100 nm citrate-stabilized nanoparticles, which showed limited diffusion in both hydrogel types. To confer different surface charge, gold nanoparticles were functionalized by the conjugation of poly(ethylene glycol) (PEG) derivatives of identical molecular weight with different terminal moieties (neutral, and positively and negatively charged) to modulate the surface charge and assess their interaction with the negatively charged mucin matrix. PEGylated particles exhibited significantly greater mobility than their citrate-stabilized counterparts, regardless of size or hydrogel density owing to the muco-penetration effect of PEG. Among PEGylated particles, the neutral and negatively charged 30 nm variants demonstrated higher diffusion than the positively charged ones due to weaker interactions with the negatively charged mucin hydrogel. For the 100 nm particles, the neutral PEGylated nanoparticles exhibited greater diffusion than their positively charged counterparts. Conclusions: Overall findings could provide valuable insights into the more rational design of nanoparticle-based drug delivery systems targeting mucosal tissues. Full article

The ubiquitous presence of smartphones has led to new phenomenon such as “phubbing” (the act of ignoring one’s immediate surroundings in favor of using a mobile phone). This behavior has become increasingly common among university students, making it an important subject of study due to its potential negative impact on learning environments. The aim of the present study is to analyze the prevalence of phubbing among university students, the existence of significant differences as a function of specific sociodemographic variables (such as gender, age, academic performance, and connection frequency), and, lastly, the predictive capacity of these elements with the different levels of phubbing experienced. The sample was composed of 1121 Spanish university students, and the instrument selected for the collection of data was the Phubbing Scale, which was divided into three factors, “attachment to the mobile phone”, “communication disturbance”, and “smartphone obsession”, through different validity and reliability tests. The results indicated a moderately high prevalence of phubbing among the population studied. Likewise, statistically significant differences were identified at a multivariate level in the three dimensions. Lastly, it is notable that the frequency of smartphone usage significantly and positively predicted the three dimensions of phubbing. Full article

Understanding household vehicle ownership dynamics in the post-COVID-19 era is critical for designing equitable, resilient, and sustainable transportation policies. This study employs an interpretable machine learning framework to model household vehicle ownership using data from the 2022 National Household Travel Survey (NHTS)—the first nationally representative U.S. dataset collected after the onset of the pandemic. A binary classification task distinguishes between single- and multi-vehicle households, applying an ensemble of algorithms, including Random Forest, XGBoost, Support Vector Machines (SVM), and Naïve Bayes. The Random Forest model achieved the highest predictive accuracy (86.9%). To address the interpretability limitations of conventional machine learning approaches, SHapley Additive exPlanations (SHAP) were applied to extract global feature importance and directionality. Results indicate that the number of drivers, household income, and vehicle age are the most influential predictors of multi-vehicle ownership, while contextual factors such as housing tenure, urbanicity, and household lifecycle stage also exert substantial influence highlighting the spatial and demographic heterogeneity in ownership behavior. Policy implications include the design of equity-sensitive strategies such as targeted mobility subsidies, vehicle scrappage incentives, and rural transit innovations. By integrating explainable artificial intelligence into national-scale transportation modeling, this research bridges the gap between predictive accuracy and interpretability, contributing to adaptive mobility strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities), SDG 10 (Reduced Inequalities), and SDG 13 (Climate Action). Full article

Household food waste remains a persistent challenge despite widespread pro-environmental intentions. Drawing on Brehm’s Motivational Intensity Theory, this study examined how perceived difficulty and perceived ability interact with motivation to predict self-reported food waste. We surveyed 939 participants in Flanders and Spain, measuring motivation to avoid waste, self-rated perceived ability to manage food, meal planning perceived difficulty, and food waste. Moderated moderation analyses revealed that motivation and perceived ability each independently predicted lower waste. Crucially, a significant three-way interaction showed that motivation most effectively reduced waste when perceived difficulty was low and perceived ability was high; when perceived difficulty exceeded perceived ability, motivation had no mitigating effect. These findings underscore that effort mobilization influenced by both individual capacity and situational demands is key to closing the intention–behavior gap in food waste. Practically, interventions should go beyond raising awareness to simplify tasks and bolster consumers’ skills, aligning action demands with realistic effort levels. Full article

The increasing concern for road safety has driven the development of advanced driver behavior analysis systems. This study presents a comprehensive review of various techniques to detect unsafe driving behaviors, with a particular emphasis on using smartphone sensors. By leveraging data from accelerometers, gyroscopes, and GPS, these methods allow for the detection of aggressive driving patterns, which may result from factors such as driver distraction or drowsiness. Modern sensor technology plays a crucial role in real-time monitoring and has significant potential to enhance vehicle safety systems. A Long Short-Term Memory (LSTM) network combined with a Conv1D layer was trained to analyze driving patterns using a sliding window technique. As technology continues evolving, its application in driver behavior analysis holds great promise for reducing traffic accidents and improving driving habits. Furthermore, the ability to gather and analyze large amounts of data from drivers in various conditions opens new opportunities for more personalized and adaptive safety solutions. This research offers insights into the future direction of driver monitoring systems and the growing impact of mobile and sensor-based solutions in transportation safety. Full article

Multisensory behavioral research is increasingly aiming to move beyond traditional laboratories and into real-world settings. Smartphones offer a promising platform for this purpose, but their use in psychophysical experiments requires rigorous validation of their ability to precisely present multisensory stimuli and record reaction times (RTs). To date, no study has systematically assessed the feasibility of conducting RT-based multisensory paradigms on smartphones. In this study, we developed a reproducible validation method to quantify smartphones’ temporal precision in synchronized auditory–tactile stimulus delivery and RT logging. Applying this method to five Android devices, we identified two with sufficient precision. We also introduced a technique to enhance RT measurement by combining touchscreen and accelerometer data, effectively doubling the measure resolution—from 8.33 ms (limited by a 120 Hz refresh rate) to 4 ms. Using a top-performing device identified through our validation, we conducted an audio–tactile RT experiment with 20 healthy participants. Looming sounds were presented through headphones during a tactile detection task. Results showed that looming sounds reduced tactile RTs by 20–25 ms compared to static sounds, replicating a well-established multisensory effect linked to peripersonal space. These findings present a robust method for validating smartphones for cognitive research and demonstrate that high-precision audio–tactile paradigms can be reliably implemented on mobile devices. This work lays the groundwork for rigorous, scalable, and ecologically valid multisensory behavioral studies in naturalistic environments, expanding participant reach and enhancing the relevance of multisensory research. Full article

The paper presents an innovative theoretical concept of a bio-inspired soft gripper system with two parallel jaws, a fixed and a mobile one. It is conceived for gripping fragile or soft objects with complex, irregular shapes that are easily deformable. This novel gripper is designed for handling small objects of masses up to 0.5 kg. The maximum gripping stroke of the mobile jaw is 13.5 mm. The driving motor is a pneumatic muscle, an actuator with inherently compliant, spring-like behavior. Compliance is the feature responsible for the soft character of the gripper system, ensuring its passive adaptability to the nature of the object to be gripped. The paper presents the structural, kinematic, static, and dynamic models of the novel gripper system and describes the compliant behavior of the entire assembly. The results of the dynamic simulation of the gripper have confirmed the attaining of the imposed motion-related performance. Full article

Mobile commerce has transformed the retail landscape, yet the determinants of impulse buying behavior in this environment remain understudied, particularly in emerging markets. This research investigates the factors influencing impulse buying in mobile commerce in Chile using the Stimulus–Organism–Response framework. A quantitative cross-sectional study collected data from 451 mobile shoppers via an online survey. Structural equation modeling with PLS-SEM revealed that eight of the thirteen hypothesized relationships were significant. Mobile application factors (visual appeal and portability) positively influenced hedonic and utilitarian values. Among personal factors, economic well-being, family influence, and credit card use directly impacted impulse buying, while time availability did not. Hedonic value strongly influenced impulse buying behavior, but utilitarian value showed no significant effect. Contrary to expectations, the COVID-19 pandemic negatively impacted impulse buying. These findings extend theoretical understanding of mobile impulse buying determinants and provide practical insights for mobile commerce developers and marketers to enhance their platforms and strategies. Full article

Background/Objectives: Coupling mobile health (mHealth) technology with community-based nutrition programs may enhance diet quality in adolescents. This pilot study evaluated the feasibility, acceptability, and preliminary efficacy of integrating PortionSize Ed (PSEd), an image-assisted dietary assessment and education app, into the six-week Hawaiʻi Food and Lifeskills for Youth (HI-FLY) curriculum delivered via Supplemental Nutrition Assistance Program Education (SNAP-Ed). Methods: Adolescents (grades 6–8) from two classrooms were cluster-randomized into HI-FLY or HI-FLY + PSEd. Both groups received HI-FLY and completed Youth Questionnaires (YQ) and food records (written or app-based) at Weeks 0 and 7. Feasibility and acceptability were assessed via enrollment, attrition, and User Satisfaction Surveys (USS). Diet quality was measured using Healthy Eating Index-2020 (HEI-2020) scores and analyzed via mixed-effects models. Results: Of 50 students, 42 (84%) enrolled and attrition was minimal (2.4%). The sample was 49% female and 85% at least part Native Hawaiian or Pacific Islander (NHPI). PSEd was acceptable, with average USS scores above the scale midpoint. No significant HEI-2020 changes were observed, though YQ responses indicated improvements in sugary drink intake (p = 0.03) and use of nutrition labels in HI-FLY + PSEd (p = 0.0007). Conclusions: Integrating PSEd into SNAP-Ed was feasible, acceptable, and demonstrated potential healthy behavior change among predominantly NHPI youth in Hawaiʻi. Full article

This study investigated the physiological effects of seat vibration during prolonged sitting in a simulated autonomous driving environment. Eleven healthy participants (3 young adults and 8 older adults) viewed a 120-min highway driving video under two conditions: rhythmic seat vibration (2 Hz, mimicking natural respiration) and no vibration. Physiological and behavioral metrics—including Psychomotor Vigilance Task (PVT), seat pressure distribution, heart rate variability (HRV), body acceleration, and skin temperature—were assessed across three phases. Results demonstrated that seat vibration significantly enhanced parasympathetic activity, as evidenced by increased HF power and decreased LF/HF ratio (p < 0.05), suggesting reduced autonomic stress. Additionally, seated posture remained more stable under vibration, with reduced asymmetry and sway, while the no-vibration condition showed time-dependent postural degradation. Interestingly, skin surface temperature was lower in the vibration condition (p < 0.001), indicating a possible thermoregulatory mechanism. In contrast, PVT performance revealed more false starts in the vibration condition, particularly among older adults, suggesting that vibration may not enhance—and could slightly impair—cognitive alertness. These findings suggest that low-frequency seat vibration can support physiological stability and postural control during prolonged sedentary conditions, such as in autonomous vehicles. However, its effects on vigilance appear limited and age-dependent. Overall, rhythmic vibration may contribute to enhancing passenger comfort and reducing fatigue-related risks, particularly in older individuals. Future work should explore adaptive vibration strategies to balance physiological relaxation and cognitive alertness in mobility environments. Full article

Wireless power transfer (WPT) has emerged as a compelling solution for delivering electrical energy without physical connectors, particularly in applications requiring reliability, mobility, or encapsulation. This work presents the modeling, simulation, construction, and experimental validation of an optimized dual-frequency WPT system using magnetically coupled resonant coils. Unlike conventional single-frequency systems, the proposed architecture introduces two independently controlled excitation frequencies applied to distinct transistors, enabling improved resonance behavior and enhanced power delivery across a range of coupling conditions. The design process integrates numerical circuit simulations in PSpice and three-dimensional electromagnetic analysis in ANSYS Maxwell 3D, allowing accurate evaluation of coupling coefficient variation, mutual inductance, and magnetic flux distribution as functions of coil geometry and alignment. A sixth-degree polynomial model was derived to characterize the coupling coefficient as a function of coil separation, supporting predictive tuning. Experimental measurements were carried out using a physical prototype driven by both sinusoidal and rectangular control signals under varying load conditions. Results confirm the simulation findings, showing that specific signal periods (e.g., 8 µs, 18 µs, 20 µs, 22 µs) yield optimal induced voltage values, with strong sensitivity to the coupling coefficient. Moreover, the presence of a real load influenced system performance, underscoring the need for adaptive control strategies. The proposed approach demonstrates that dual-frequency excitation can significantly enhance system robustness and efficiency, paving the way for future implementations of self-adaptive WPT systems in embedded, mobile, or biomedical environments. Full article

In this study, high-conductivity W-doped Ga₂O₃ thin films were successfully fabricated by directly depositing a composition of Ga₂O₃ with 10.7 at% WO₃ (W:Ga = 12:100) using electron beam evaporation. The resulting thin films were found to be amorphous. Due to the ohmic contact behavior observed between the W-doped Ga₂O₃ film and platinum (Pt), Pt was used as the contact electrode. Current-voltage (J-V) measurements of the W-doped Ga₂O₃ thin films demonstrated that the samples exhibited significant current density even without any post-deposition annealing treatment. To further validate the excellent charge transport characteristics, Hall effect measurements were conducted. Compared to undoped Ga₂O₃ thin films, which showed non-conductive characteristics, the W-doped thin films showed an increased carrier concentration and enhanced electron mobility, along with a substantial decrease in resistivity. The measured Hall coefficient of the W-doped Ga₂O₃ thin films was negative, indicating that these thin films were n-type semiconductors. Energy-Dispersive X-ray Spectroscopy was employed to verify the elemental ratios of Ga, O, and W in the W-doped Ga₂O₃ thin films, while X-ray photoelectron spectroscopy analysis further confirmed these ratios and demonstrated their variation with the depth of the deposited thin films. Furthermore, the W-doped Ga₂O₃ thin films were deposited onto both p-type and heavily doped p⁺-type silicon (Si) substrates to fabricate heterojunction diodes. All resulting devices exhibited good rectifying behavior, highlighting the promising potential of W-doped Ga₂O₃ thin films for use in rectifying electronic components. Full article

Based on the steel sheet pile cofferdam project for the main bridge piers of a cross-sea bridge, finite element numerical simulations were conducted to analyze the influence of construction sequences in marine environments, as well as the effects of initial water levels and support positions under various construction conditions on the stress and deformation behavior of steel sheet piles. Using a staged construction simulation with a Mohr–Coulomb soil model and stepwise activation of loads/excavation, this study delivers practically relevant trends: staged dewatering halves the sheet pile head displacement (top lateral movement <0.08 m vs. ~0.16 m in the original scheme) and mobilizes the support system earlier, while slightly increasing peak bending demand (~1800 kN·m) at the bracing elevation; the interaction between water head and brace elevation is explored through fitted response curves and summarized in figures/tables, and soil/structural properties are tabulated for reproducibility. The results indicate that a well-designed dewatering process, along with the coordination between water levels and internal support positions, plays a critical role in controlling deformation. The findings offer valuable references for the design and construction of sheet pile cofferdams in marine engineering under varying construction methods and water level conditions. Full article

Gallium nitride high electron mobility transistors (GaN HEMTs), characterized by their extremely high switching speeds and superior high-frequency performance, have demonstrated significant advantages, and gained extensive applications in fields such as aerospace and high-power-density power supplies. However, their unique internal architecture renders these devices highly sensitive to circuit parasitic parameters. Conventional circuit design methodologies often induce severe issues such as overshoot and high-frequency oscillations, which significantly constrain the realization of their high-frequency performance. To solve this problem, this paper investigates the nonlinear dynamic behavior of GaN HEMTs during switching transients by establishing an equivalent impedance model. Based on this model, a detailed analysis is implemented to elucidate the mechanism by which RC Snubber circuits influence the system’s resonance frequency and the amplitude at the resonant frequency. Through this analysis, an optimal RC Snubber circuit parameter is derived, enabling effective suppression of high-frequency oscillations during the switching transient of GaN HEMT. Experimental results demonstrate that the proposed design achieves a maximum reduction of 40% in voltage overshoot, shortens the ringing time to one-twentieth of the original value, and suppresses noise by 20 dB in the high-frequency range of 20 MHz to 30 MHz, thereby significantly enhancing the stability and reliability of circuit operation. Additionally, considering the heat dissipation requirements in high power density scenarios, this work optimizes the layout of devices, and heat sinks to maintain operational temperatures within safe limits, further mitigating the impact of parasitic parameters on overall system performance. Full article

Increased precipitation and extreme weather due to climate change can remobilize recent and legacy environmental contaminants from soil, sediment, and sewage overflows. Heavy metals are naturally distributed in Earth’s crust, but anthropogenic activity has resulted in concentrated emissions of toxic heavy metals and deposition in surrounding communities. Cities around the world are burdened with heavy metal pollution from past and present industrial activity. The city of Camden, NJ, represents a valuable case study of climate impacts on heavy metal mobilization in stormwater runoff due to similar legacy and present-day industrial pollution that has taken place in Camden and in many other cities. Various studies have shown that lead (Pb) and other toxic heavy metals have been emitted in Camden due to historic and recent industrial activity, and deposited in nearby soils and on impervious surfaces. However, it is not known if these heavy metals can be mobilized in urban stormwater, particularly after periods of high precipitation. In this study, Camden, NJ stormwater was collected from streets and parks after heavy rain events in the winter and spring for analysis with inductively coupled plasma-mass spectrometry (ICP-MS) to identify lead (Pb), mercury (Hg), cadmium (Cd), and arsenic (As). Lead was by far the most abundant of the four target elements in stormwater samples followed by Hg, Cd, and As. The locations with the highest Pb concentrations, up to 686.5 ppb, were flooded allies and streets between commercial and residential areas. The highest concentrations of Hg (up to 11.53 ppb, orders of magnitude lower than Pb) were found in partially flooded streets and ditches. Lead stormwater concentrations exceed EPA safe drinking levels at the majority of analyzed locations, and Hg stormwater concentrations exceed EPA safe drinking levels at all analyzed locations. While stormwater is not generally ingested, dermal contact and hand-to-mouth behavior by children are potential routes of exposure. Heavy metal concentrations were lower in stormwater collected from parks and restored areas of Camden, indicating that these areas have a lower heavy metal exposure risk. This study shows that heavy metal pollution can be mobilized in stormwater runoff, resulting in elevated exposure risk in industrial cities. Full article