Search Results (573)

Retrieval practice, or the active recall of information from memory, is a highly effective learning strategy that strengthens memory and comprehension. This effect is robust and strongly backed by research in cognitive psychology. The health professions—including medicine, nursing, and dentistry—have widely embraced retrieval practice as a learning and study tool, particularly for course exams and high-stakes licensing exams. This state-of-the-art review examines the historical development, current applications, and future directions for the use of retrieval practice in health professions education. While retrieval-based learning has long been used informally in these fields, its formal recognition as a scientifically supported study method gained momentum in the early 2000s and then saw a surge in both research interest and curricular adoption between 2010 and 2025. This historical review explores the key factors driving this growth, such as its alignment with assessment-driven education and the increasing availability of third-party study resources that rely on retrieval practice as a guiding principle. Despite its proven benefits for learning, however, barriers persist to its adoption by students, including in the health professions. This article discusses strategies for overcoming these challenges and for enhancing retrieval practice integration into health professions curricula. Full article

Aiming at the issues that the field mill type electric field sensor lacks an accurate and complete mathematical model, and its signal is weak and contains a large amount of harmonic noise, on the basis of establishing the mathematical model of the sensor’s induction electrode, the finite element method was adopted to analyze the influence laws of parameters such as the thickness of the shielding electrode and the distance between the induction electrode and the shielding electrode on the sensor sensitivity. On this basis, the above parameters were optimized. A signal processing circuit incorporating a pre-integral transformation circuit, a differential amplification circuit, and a bias circuit was investigated, and a completed mathematical model of the input and output of the field mill type electric field sensor was established. An improved harmonic detection method combining fast Fourier transform and back propagation neural network (FFT-BP) was proposed, the learning rate, momentum factor, and excitation function jointly participated in the adjustment of the network, and the iterative search range of the algorithm was limited by the threshold interval, further improving the accuracy and rapidity of the sensor measurement. Experimental results indicate that within the simulated electric field intensity range of 0–20 kV/m in the laboratory, the measurement resolution of this system can reach 18.7 V/m, and the measurement linearity is more than 99%. The designed system is capable of measuring the atmospheric electric field intensity in real time, providing necessary data support for lightning monitoring and early warning. Full article

The impact of Environmental, Social, and Governance (ESG) scores on financial performance remains a subject of debate, as the literature reports mixed evidence regarding their effect on stock returns. This research aims to examine the relationship between ESG ratings and the change in ESG scores, or ESG Momentum, concerning both returns and risk of a large sample of stocks traded on U.S. exchanges. The study examined a sample of 3856 stocks traded on U.S. exchanges, considering 20 years of quarterly data from December 2002 to December 2022. We applied multi-factor models and tested them through pooled ordinary, fixed effects, and random effects panel regression methods. Our results show negative relationships between ESG scores and stock returns and between ESG Momentum and volatility. Contrarily, we find positive associations between ESG Momentum and returns and between ESG scores and volatility. Although high ESG scores are generally associated with lower long-term stock returns, an increase in a company’s ESG rating tends to translate into immediate positive returns and reduced risk. Accordingly, investors may benefit from strategies that focus on companies actively improving their ESG performance, while firms themselves stand to gain by signaling continuous advancement in ESG-related areas. Full article

As hydrogen fuel cell vehicles gain momentum as crucial zero-emission transportation solutions, the urgency to address hydrogen permeability through the polymer liner becomes paramount for ensuring the safety, efficiency, and longevity of Type IV hydrogen storage tanks. This paper synthesizes existing research findings, analyzes the influence of different materials and structures on gas permeability, elucidates the dissolution and diffusion mechanisms of hydrogen in plastic liners, and discusses their engineering applications. We focus on measurement methods, influencing factors, and improvement strategies for liner gas permeability. Additionally, we explore the prospects of Type IV hydrogen storage tanks in fields such as automotive, aerospace, and energy storage industries. Through this comprehensive review of liner gas permeability, critical insights are provided to guide the development of efficient and safe hydrogen storage and transportation systems. These insights are vital for advancing the widespread application of hydrogen energy technology and fostering sustainable energy development, significantly contributing to efforts aimed at enhancing the performance and safety of Type IV hydrogen storage tanks. Full article

The global crude oil market, known for its pronounced volatility and nonlinear dynamics, plays a pivotal role in shaping economic stability and informing investment strategies. Contrary to traditional research focused on price forecasting, this study emphasizes the more investor-centric task of predicting returns for West Texas Intermediate (WTI) crude oil. By spotlighting returns, it directly addresses critical investor concerns such as asset allocation and risk management. This study applies advanced machine learning models, including XGBoost, random forest, and neural networks to predict crude oil return, and for the first time, incorporates sustainability and external risk variables, which are shown to enhance predictive performance in capturing the non-stationarity and complexity of financial time-series data. To enhance predictive accuracy, we integrate 55 variables across five dimensions: macroeconomic indicators, financial and futures markets, energy markets, momentum factors, and sustainability and external risk. Among these, the rate of change stands out as the most influential predictor. Notably, XGBoost demonstrates a superior performance, surpassing competing models with an impressive 76% accuracy in direction forecasting. The analysis highlights how the significance of various predictors shifted during the COVID-19 pandemic. This underscores the dynamic and adaptive character of crude oil markets under substantial external disruptions. In addition, by incorporating sustainability factors, the study provides deeper insights into the drivers of market behavior, supporting more informed portfolio adjustments, risk management strategies, and policy development aimed at fostering resilience and advancing sustainable energy transitions. Full article

Rainfall simulators are essential tools in soil research, providing a controlled and repeatable approach to studying rainfall-induced erosion. However, the development of high-fidelity rainfall simulators remains a challenge. This study aimed to design, construct, and calibrate a spraying-type rainfall simulator and validate assessment criteria optimized for soil erosion research. The simulator’s design is based on a modified simulator model previously described in the literature and following the defined criteria. The calibration of the simulator was conducted in two phases, on slopes of 0° and 15°, measuring rainfall intensity, drop size, and its spatial distribution, and calculating drop falling velocity, kinetic energy, and momentum. The simulator consists of structural support, a water tank, a water-moving mechanism, a flow regulation system, and sprayers, contributing to its simplicity, cost-effectiveness, durability, rigidity, and stability, ensuring smooth simulator operation. The calibration of the rainfall simulator demonstrated that rainfall intensity increased from 1.4 mm·min⁻¹ to 4.6 mm·min⁻¹ with higher pressure in the hydraulic system (1.0 to 2.0 bar), while spatial uniformity remained within 79–91% across different nozzle configurations. The selected Rain Bird HE-VAN series nozzles proved highly effective in simulating rainfall, achieving drop diameters ranging from 0.8 mm to 1.9 mm, depending on pressure and nozzle type. The rainfall simulator successfully replicates natural rainfall characteristics, offering a controlled environment for investigating soil erosion processes. Drop velocity values varied between 2.5 and 2.9 m·s⁻¹, influencing kinetic energy, which ranged from 0.6 J·min⁻¹·m⁻² to 2.9 J·min⁻¹·m⁻², and impact momentum, which was measured between 0.005 N·s and 0.032 N·s. The simulator design suggests that it is suitable for future applications in both field and laboratory soil erosion research, ensuring repeatability and adaptability for various experimental conditions. Calibration results emphasized the significance of nozzle selection and water pressure adjustments. These factors significantly affect rainfall intensity, drop size, kinetic energy, and momentum, parameters that are critical for accurate erosion modeling. Full article

Microfluidic devices offer well-defined physical environments that are suitable for effective cell seeding and in vitro three-dimensional (3D) cell culture experiments. These platforms have been employed to model in vivo conditions for studying mechanical forces, cell–extracellular matrix (ECM) interactions, and to elucidate transport mechanisms in 3D tissue-like structures, such as tumor and lymph node organoids. Studies have shown that fluid flow behavior in microfluidic slides (µ-slides) directly influences shear stress, which has emerged as a key factor affecting cell proliferation and differentiation. This study investigates fluid flow in the porous channel of a µ-slide using computational fluid dynamics (CFD) techniques to analyze the impact of perfusion flow rate and porous properties on resulting shear stresses. The model of the µ-slide filled with a permeable biomaterial is considered. Porous media fluid flow in the channel is characterized by adding a momentum loss term to the standard Navier–Stokes equations, with a physiological range of permeability values. Numerical simulations are conducted to obtain data and contour plots of the filtration velocity and flow-induced shear stress distributions within the device channel. The filtration flow is subsequently measured by performing protein perfusions into the slide embedded with native human-derived ECM, while the flow rate is controlled using a syringe pump. The relationships between inlet flow rate and shear stress, as well as filtration flow and ECM permeability, are analyzed. The findings provide insights into the impact of shear stress, informing the optimization of perfusion conditions for studying tissues and cells under fluid flow. Full article

Traditional villages (TVs) and intangible cultural heritage (ICH) serve as dual carriers for the living transmission of agrarian civilization, with their spatial compatibility being crucial for the sustainable development of cultural ecosystems. Existing research shows deficiencies in quantitative analysis, multidimensional driving mechanism interpretation, and spatial heterogeneity identification. This study establishes a three-phase framework (“spatial pattern identification–spatial relationship analysis–impact mechanism assessment”) using nationwide data encompassing 8155 TVs and 3587 ICH elements. Through the comprehensive application of the spatial mismatch index, Optimal-Parameter Geographic Detector (OPGD), and multiscale geographically weighted regression (MGWR) model, we systematically reveal their spatial differentiation patterns and driving mechanisms. Key findings: First, TVs exhibit a “three-primary-core and two-secondary-core” strong agglomeration pattern, while ICH shows multi-center balanced distribution. Significant positive spatial correlation coexists with prevalent mismatch: 65% of China’s territory displays positive mismatch (ICH dominance) and 35% displays negative mismatch (TV dominance). Second, the spatial mismatch mechanism follows a “weakened natural foundation with dual drivers of socio-economic dynamics and cultural policy momentum”, where the GDP, tertiary industry ratio, general public budget expenditure, number of ICH inheritors, museums, and key cultural relic protection units emerge as dominant factors. Third, core drivers demonstrate significant spatial heterogeneity, with economic factors showing differentiated regulation while cultural policy elements exhibit distinct regional dependency. The proposed “economy–culture” dual governance approach, featuring cross-scale analysis methods and three-dimensional indicator system innovation, holds practical value for optimizing cultural heritage spatial governance paradigms. Full article

We present high-precision multi-configuration Dirac–Hartree–Fock (MCDHF) calculations for the metastable states of ${\mathrm{Pr}}^{9+}$ and ${\mathrm{Nd}}^{10+}$ ions, systematically investigating their energy levels, transition properties, Landé $g_J$ factors, and hyperfine interaction constants. Our results show excellent agreement with available experimental data and theoretical benchmarks, while resolving critical configuration assignment discrepancies through detailed angular momentum coupling analysis. The calculations highlight the significant role of Breit interaction and provide the first theoretical predictions of electric quadrupole hyperfine constants ($B_{\mathrm{hfs}}$). These findings deliver essential atomic data for the development of next-generation optical clocks and establish lanthanide highly charged ions as exceptional candidates for precision tests of fundamental physics. Full article

This paper develops and presents a system for museums to evaluate behavioural and experiential gains of older adult visitors when engaging with digital interpretation exhibits. The evaluation system is based on the Analytic Hierarchy Process (AHP), utilising existing evaluation methods for museum visitors and refining them into an approach suitable for investigating older visitors. Innovatively, it incorporates the universal design (UD) in museum digital exhibits, injecting strong momentum into creating inclusive museums. An in-depth evaluation was conducted on seven exhibitions across three newly constructed Chinese cultural tourism museums with different digital characteristics, presenting the results and findings through eighty-eight digital interpretation exhibits. Qualitative and quantitative data provide a nuanced picture of digital interpretation and interaction from the perspective of older visitors. The results demonstrate the factors influencing older adults’ engagement with digital interpretation exhibits in museums and how digital interpretation items attract or deter older visitors’ engagement in complex exhibition environments. This study utilised universal design principles to identify the limitations and barriers in digital interpretation for older visitors, analysed the correlation between UD and digital attraction power, explored the reasons behind these outcomes, and identified design recommendations for inclusive museum digital interpretation. Full article

This study aims to mitigate slope-collapse hazards that threaten life and property at the Lujiawan resettlement site in Wanbi Town, Dayao County, Yunnan Province, within the Guanyinyan hydropower reservoir. It integrates centimeter-level point-cloud data collected by a DJI Matrice 350 RTK equipped with a Zenmuse L2 airborne LiDAR (Light Detection And Ranging) sensor with detailed structural-joint survey data. First, qualitative structural interpretation is conducted with stereographic projection. Next, safety factors are quantified using the limit-equilibrium method, establishing a dual qualitative–quantitative diagnostic framework. This framework delineates six hazardous rock zones (WY1–WY6), dominated by toppling and free-fall failure modes, and evaluates their stability under combined rainfall infiltration, seismic loading, and ambient conditions. Subsequently, six-degree-of-freedom Monte Carlo simulations incorporating realistic three-dimensional terrain and block geometry are performed in RAMMS::ROCKFALL (Rapid Mass Movements Simulation—Rockfall). The resulting spatial patterns of rockfall velocity, kinetic energy, and rebound height elucidate their evolution coupled with slope height, surface morphology, and block shape. Results show peak velocities ranging from 20 to 42 m s⁻¹ and maximum kinetic energies between 0.16 and 1.4 MJ. Most rockfall trajectories terminate within 0–80 m of the cliff base. All six identified hazardous rock masses pose varying levels of threat to residential structures at the slope foot, highlighting substantial spatial variability in hazard distribution. Drawing on the preceding diagnostic results and dynamic simulations, we recommend a three-tier “zonal defense with in situ energy dissipation” scheme: (i) install 500–2000 kJ flexible barriers along the crest and upper slope to rapidly attenuate rockfall energy; (ii) place guiding or deflection structures at mid-slope to steer blocks and dissipate momentum; and (iii) deploy high-capacity flexible nets combined with a catchment basin at the slope foot to intercept residual blocks. This staged arrangement maximizes energy attenuation and overall risk reduction. This study shows that integrating high-resolution 3D point clouds with rigid-body contact dynamics overcomes the spatial discontinuities of conventional surveys. The approach substantially improves the accuracy and efficiency of hazardous rock stability assessments and rockfall trajectory predictions, offering a quantifiable, reproducible mitigation framework for long slopes, large rock volumes, and densely fractured cliff faces. Full article

With growing interest in wearable technologies, the development of flexible sensors and products that can monitor the human body while being comfortable to wear is gaining momentum. While various textile-based strain sensors have been proposed, their implementation in practical, exercise-specific applications remains limited. In this study, we developed a knitted strain sensor that monitors elbow angles, focusing on dumbbell exercise, which is a basic exercise in sports, and verified its performance. The material of the developed knitted strain sensor with a plain stitch structure comprised a silver-coated nylon conductive yarn and an acrylic/wool blended yarn. To evaluate the electrical and physical characteristics of the developed sensor, a textile folding tester was used to conduct 100 repeated bending experiments at three angles of 30°, 60°, 90° and speeds of 10, 30, 60 cpm. The system demonstrated excellent elasticity, high sensitivity (gauge factor = 698), fast responsiveness, and reliable performance under repeated stress, indicating its potential for integration into wearable fitness or rehabilitation platforms. Full article

Plastic and especially microplastic (MP) pollution has posed a serious threat to the marine environment for decades. Studies on MPs have started to gain momentum especially in the Sea of Marmara (SoM), which is an international waterway, under the pressure of intense maritime traffic and exposure to domestic and industrial discharges. The aim of this study was to evaluate the MPs found in surface sediments collected from the coastal area of the SoM according to the locations and to reveal the extent of the existing pollution. This is the first study to examine MPs in both the surface sediments of the entire shorelines of the SoM, which have not been previously reported, and in the surface sediments of Çanakkale Strait. Accordingly, the highest MP abundance was detected at Yenice station (St 15) with 1286 items/kg, and the lowest MP abundance was detected at Turan Village station (St 14) with 199 items/kg. The most dominant shapes across all sampling stations and months were fiber (37%) and fragment (26%), while the most dominant color was blue (35%). According to the polymer characterization results, PE (polyethylene) was found to be the most dominant polymer type. Additionally, most stations were found to have “Moderate” and “High” pollution levels in terms of the contamination factor (CF), and regions were classified as “Moderate” and ‘High’ in terms of the pollution load index (PLI), with the St 15 station specifically exhibiting “Very High” pollution levels. Furthermore, hazard index (HI) and pollution risk index (PRI) values were also calculated regionally, revealing that regions have pollution levels classified as “High”, “Very High”, and even “Dangerous”. This study concluded that there are no areas with low pollution levels in SoM, and that the threat posed by MP pollution in this sea is increasing. Furthermore, this study found that stations with high MP pollution levels are located near river discharges and that rivers significantly contribute to MP pollution in the seas. The findings are of great importance in terms of the need to implement sustainable plans and measures to prevent pollution in the SoM and to take concrete steps to protect and ensure the sustainability of coastal ecosystems, particularly those under serious pollution threats. Full article

The Airyprime beam, due to its adjustable focusing ability and controllable orbital angular momentum, has attracted significant attention in fields such as free-space optical communication and particle trapping. However, systematic studies on the propagation behavior of oscillating solitons in PT-symmetric optical lattices remain scarce, particularly regarding their formation mechanisms and self-accelerating characteristics. In this study, the propagation characteristics of Airyprime beams in PT symmetric optical lattices are numerically studied using the split-step Fourier method, and the generation mechanism and control factors of oscillating solitons are analyzed. The influence of lattice parameters (such as the modulation depth P, modulation frequency w, and gain/loss distribution coefficient W₀) and beam initial characteristics (such as the truncation coefficient a) on the dynamic behavior of the beam is revealed. The results show that the initial parameters determine the propagation characteristics of the beam and the stability of the soliton. This research provides theoretical support for beam shaping, optical path design, and nonlinear optical manipulation and has important application value. Full article

The propagation of high-frequency ultrasound waves will generate both physical and chemical effects as they propagate through a liquid medium, such as acoustic streaming, an acoustic fountain, and atomization. These phenomena are believed to be the main factors that contribute to the enhancement of mass transfer in the gas–liquid carbon dioxide (CO₂) absorption system. Computational Fluid Dynamic (CFD) simulation is one of the powerful tools that can be used to model the complex hydrodynamic behavior induced by the propagation of ultrasound waves in the liquid medium. In this study, the ultrasonic irradiation forces were simulated via the momentum source term method using commercial CFD software (ANSYS Fluent V19.1). In addition, a parametric study was conducted to investigate the influences of absorber height and ultrasonic power on the hydrodynamic mixing performance. The simulation results indicated that enhanced mixing and a higher intensification factor were achieved with increased fountain flow velocity, particularly at the lowest absorber height and highest ultrasonic power. Conversely, the energy efficiency was improved with the increase of absorber height and decrease of ultrasonic power. To determine the optimal combination of absorber height and ultrasonic power, this trade-off between the energy efficiency and intensification in the ultrasonic-assisted absorption system (UAAS) is a crucial consideration during process scale-up. Full article