Specific Requirements Research Articles

Functional outcomes of different surgical treatments for common peroneal nerve injuries: a retrospective comparative study

BackgroundThis study aims to assess the recovery patterns and factors influencing outcomes in patients with common peroneal nerve (CPN) injury.MethodsThis retrospective study included 45 patients with CPN injuries treated between 2009 and 2019 in Jing’an District Central Hospital. The surgical interventions were categorized into three groups: neurolysis (group A; n = 34 patients), nerve repair (group B; n = 5 patients) and tendon transfer (group C; n = 6 patients). Preoperative and postoperative sensorimotor functions were evaluated using the British Medical Research Council grading system. The outcome of measures included the numeric rating scale, walking ability, numbness and satisfaction. Receiver operating characteristic (ROC) curve analysis was utilized to determine the optimal time interval between injury and surgery for predicting postoperative foot dorsiflexion function, toe dorsiflexion function, and sensory function.ResultsSurgical interventions led to improvements in foot dorsiflexion strength in all patient groups, enabling most to regain independent walking ability. Group A (underwent neurolysis) had significant sensory function restoration (P < 0.001), and three patients in Group B (underwent nerve repair) had sensory improvements. ROC analysis revealed that the optimal time interval for achieving M3 foot dorsiflexion recovery was 9.5 months, with an area under the curve (AUC) of 0.871 (95% CI = 0.661–1.000, P = 0.040). For M4 foot dorsiflexion recovery, the optimal cut-off was 5.5 months, with an AUC of 0.785 (95% CI = 0.575–0.995, P = 0.020). When using M3 toe dorsiflexion recovery or S4 sensory function recovery as the gold standard, the optimal cut-off remained at 5.5 months, with AUCs of 0.768 (95% CI = 0.582–0.953, P = 0.025) and 0.853 (95% CI = 0.693–1.000, P = 0.001), respectively.ConclusionsOur study highlights the importance of early surgical intervention in CPN injury recovery, with optimal outcomes achieved when surgery is performed within 5.5 to 9.5 months post-injury. These findings provide guidance for clinicians in tailoring treatment plans to the specific characteristics and requirements of CPN injury patients.

Thermal comfort in school children: Testing the validity of the Fanger method for a Mediterranean climate

Thermal comfort is an essential factor when designing or refurbishing schools because it helps to improve wellbeing and academic performance. However, little attention has been paid to assessing the thermal comfort level of children. Previous studies on thermal comfort have mainly focused on adults' perceptions, extrapolating their results to all ages without cross-checking them for relevance. The aim of this research was to determine whether children perceive temperature in a similar way to adults and if their thermal comfort limits are the same. A school in south-eastern Spain was selected as the case study. Thermal comfort surveys of children were conducted and compared with analytical calculations obtained using the Fanger method. The results showed that the Fanger method was not valid for the estimation of children's thermal comfort, especially in girls and younger children. The novelty of this research demonstrates that children have specific thermal comfort requirements that are not covered by current standards and calculation methods, such as the Fanger method. Analysis also determined the correction coefficients necessary for adapting Fanger's analytical method to children according to age and gender in BShs climate.

Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions.

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology; however, it is currently unclear where these originate in the brain. Here we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Participants undergoing invasive electrophysiological monitoring for epilepsy were asked to judge the direction of random-dot stimuli and respond either with a speeded button press (N = 24), or vocally, after a randomized delay (N = 12). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual buildup that was modulated by the strength of the sensory evidence, and an amplitude that predicted participants' choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision-making.

Analysing environmental opinion using highly customisable visualisation tools to understand citizens’ attitudes and barriers

Knowledge of public opinion is key to understanding citizens' attitudes towards environmental policies. However, large polls and surveys generate complex datasets from which it is not always easy to draw conclusions. In addition, tailor-made solutions for analysing public opinion face the challenge of handling too many layers of information, which can easily lead to an overwhelming user experience and impair decision-making. Service design methodologies can support the design of ad hoc visualisation tools focused on user needs. We present Op-e-nion, a case study of a visualisation tool for the analysis of public opinion regarding environmental issues, aimed at administrations and public institutions. The involvement of experts from different fields allowed for the identification of the main metrics necessary to target the least engaged socio-demographic groups as well as the barriers that limited their environmental actions. Experts also highlighted useful aspects of the design process and the final prototype to help them define more effective campaigns and policies to address social challenges and promote citizen action. An innovative step was introduced in the methodology by involving non-state actors in the evaluation of the tool, ensuring problem detection and enhancing the sustainability of the final product. Important aspects for the visualisation of multi-categorical data included simplifying the interaction with the tool while prioritising relevant information, and using highly customizable visualisations to answer specific user requirements and changing needs (i.e. analytical vs. managerial tasks). Improved visualisations of public opinion data will, in turn, better support the development of policies shaped by citizens’ concerns.

Graphene‐Based Lateral Heterojunctions for 2D Integrated Circuits

AbstractA method for patterning single‐layer graphene (SLG) and single‐layer oxidized graphene (SOG) within a continuous atomic layer to form lateral heterojunctions is presented. Raman spectroscopy is employed to investigate the evolution of defect‐related Raman peaks during excimer‐UV irradiation, facilitating the identification of structural changes and defect formation processes. Electrical transport measurements reveal that SOG‐patterned field‐effect transistors (FETs) exhibit varying characteristics depending on the degree of oxidation, thus offering the potential to tailor the electrical properties of graphene devices for specific requirements. Scanning Kelvin probe microscopy measurements reveal the surface potential and work function of the SOG regions compared with those of SLG. The effective functionality of the SOG pattern to operate as a resistor, allowing control of the electrical conductivity in the SOG‐patterned SLG channels, is demonstrated. This capability restricts the current flow while preserving the pristine electrical properties of the graphene channel. Moreover, the SOG pattern can serve as a potential barrier to constructing SLG‐SOG‐patterned integrated circuits, providing exciting opportunities for engineering advanced electronic components. This breakthrough in graphene devices simplifies the fabrication process of graphene‐based FETs and provides the foundation for developing atomically thin integrated circuits for a wide range of applications.

Computer Aided Engineering in the application of rotational forming of axially asymmetric geometries

The research presents the results of an innovative metal forming technology: ‘axially asymmetric metal spinning’. Special attention was paid to the influence of two forming conditions: Constant Contact (CC) and Tangential Contact (TC). The influence of Constant Contact and Tangential Contact were examined and compared. The term Constant Contact was used to describe a forming zone fixed at a certain height. This attribute was defined as naturally occurring in axially symmetrical metal spinning. The term Tangential Contact was used as the opposite to Constant Contact. Tangential Contact was used to describe the phenomena of movement of the forming zone. This attribute was defined as naturally occurring in axially asymmetric metal spinning. For the purpose of comparison, an asymmetric mandrel was manufactured, for which two trajectories were engineered. The trajectories were designed with the CC and TC conditions. The Finite Element Method was used to conduct metal forming simulation in simufact.forming software. Experimental trials were performed on the spinning machine MWS—200. Aluminium Alloy 1050 A was used in the FEM and experimental tests. The geometry measurement was performed using an ATOS 3D scanner and GOM Inspect software. The measurement of residual stresses was performed on a Proto iXRD® diffractometer. After determining the specific requirements of the innovative axially asymmetric spinning technology, a special computer program, called RoMeFo, was created. RoMeFo’s purpose was to engineer the trajectory with the TC condition for the mandrel’s full height. Depending on the method used, details with the following heights were manufactured in the experimental trials: CC—22 mm, TC—30 mm and RoMeFo—60 mm.

Fasta2Structure: a user-friendly tool for converting multiple aligned FASTA files to STRUCTURE format

BackgroundThe STRUCTURE software has gained popularity as a tool for population structure and genetic analysis. Nevertheless, formatting data to meet STRUCTURE's specific requirements can be daunting and susceptible to errors, especially when handling multilocus data. This article highlights the creation of a graphical user interface (GUI) application tailored to streamline the process of converting multiple sequence alignments into a single, cohesive file that is compatible with the STRUCTURE software.ResultsThe application has been developed utilizing Tkinter for the GUI and Biopython for handling FASTA files. This program processes the files, pinpoints variable sites, and converts the sequences into a binary format. Subsequently, the sequences are concatenated and presented within the graphical interface's text area, enabling users to review and confirm the results. Furthermore, the program stores the concatenated results in a file, delivering a ready-to-use input for the STRUCTURE software.ConclusionThis application offers an efficient and dependable solution for transforming multiple aligned FASTA files into a concatenated binary format file, which is compatible with the STRUCTURE software. With its user-friendly graphical interface and error-reduction approach, this tool proves invaluable for researchers engaged in population structure and genetic analysis.

The Facile Synthesis and Application of Mesoporous Silica Nanoparticles with a Vinyl Functional Group for Plastic Recycling.

Due to growing concerns about environmental pollution from plastic waste, plastic recycling research is gaining momentum. Traditional methods, such as incorporating inorganic particles, increasing cross-linking density with peroxides, and blending with silicone monomers, often improve mechanical properties but reduce flexibility for specific performance requirements. This study focuses on synthesizing silica nanoparticles with vinyl functional groups and evaluating their mechanical performance when used in recycled plastics. Silica precursors, namely sodium silicate and vinyltrimethoxysilane (VTMS), combined with a surfactant, were employed to create pores, increasing silica's surface area. The early-stage introduction of vinyl functional groups prevented the typical post-synthesis reduction in surface area. Porous silica was produced in varying quantities of VTMS, and the synthesized porous silica nanomaterials were incorporated into recycled polyethylene to induce cross-linking. Despite a decrease in surface area with increasing VTMS content, a significant surface area of 883 m2/g was achieved. In conclusion, porous silica with the right amount of vinyl content exhibited improved mechanical performance, including increased tensile strength, compared to conventional porous silica. This study shows that synthesized porous silica with integrated vinyl functional groups effectively enhances the performance of recycled plastics.

Active disturbance rejection control of flexible industrial manipulator: A MIMO benchmark problem

Robotic manipulators are widely used in modern industry. In order for robot manipulators to achieve trajectory tracking control, the end-effectors must move precisely along the given trajectories. The nonlinearity, strong coupling, and uncertainty of the system make trajectory tracking very complicated and difficult. An approach for robust feedback control is presented in this paper as a solution to this problem. The design relies on active disturbance rejection control to estimate unknown disturbances affecting the plant. The controlled system is an uncertain two-link manipulator with elastic gear transmissions, described by nonlinear friction and elasticity. It is based on an industrial benchmark problem. The model has two significant uncertainties: parametric uncertainty as well as external disturbances that affect tools and motors. A simulation-based evaluation of the proposed control method and a comparison of its performance, considering specific robustness requirements and trajectory tracking, are presented. The comparison includes the baseline controller, the QFD (Quality Function Deployment) method, and PD-CNN (PD Control Compensation based on the Cascade Neural Network). Computer simulations of the proposed controller are carried out to validate the ABB (Asea Brown Boveri) industrial benchmark. The simulation results demonstrate superiority in meeting stability and target value requirements. The stability and ultimate boundedness of the tracking error of ADRC (Active Disturbance Rejection Control) are demonstrated.

Dilutional rheology of Radiesse: Implications for regeneration and vascular safety.

Calcium hydroxylapatite-carboxymethylcellulose (CaHA-CMC) injectables have emerged as dual-purpose fillers with bioregenerative and direct filling capabilities. This study investigates the rheological properties of CaHA-CMC and its CMC carrier gel at various dilutions. The storage modulus (G'), loss modulus (G″), complex viscosity (η*), loss factor (tan δ), cohesivity, and extrusion force were evaluated for a range of CaHA-CMC aqueous dilutions with an oscillatory rheometer, drop weight testing, and force analysis, respectively. Results revealed a significant decrease in G', η*, and increase in tan(δ) with increasing dilution, indicating a decline in the product's direct filling capabilities. Cohesivity decreased dramatically with dilution, potentially enhancing tissue biointegration and the product's biostimulatory effects. The CMC gel carrier displayed inelastic and non-resilient properties, with rheological changes differing from CaHA-CMC. Dilutional rheology was also correlated with previously published dilution-dependent biostimulatory data where hyperdiluted CaHA-CMC (>1:2) demonstrated a regenerative profile and diluted or hypodiluted mixtures retained meaningful filling properties and increased regeneration. These findings offer a continuum for tailoring the product's rheological profile to match specific tissue requirements. Customizable rheology allows CaHA-CMC to be tuned for either filling and contouring or optimal regenerative effects. Importantly, safety implications related to vascular occlusion suggest that dilutional rheomodulation decreases the risk of vascular events. In conclusion, this study highlights the significant impact of aqueous dilution on the rheological properties of CaHA-CMC and its carrier gel. The findings support the clinical application of tailored dilutions to achieve desired outcomes, providing versatility and safety for aesthetic applications.

Welding Processing of Medium-Manganese Austenitic Steels for Cryogenic Applications

Abstract For several years, the significance of gaseous energy sources (e. g. liquified natural gas and hydrogen) has been increasing worldwide due to environmental and climate policy requirements. Storage and transportation of the liquids occur under cryogenic conditions. This results in specific requirements for the mechanical properties of the materials used at cryogenic temperatures. Nowadays, cold-tough, high-nickel austenites and martensitic steels of type X8Ni9 are used for such purposes. While austenitic materials offer good processing properties, they are not attractive due to their comparatively low strength and high costs. Welding martensitic steel with commonly used nickel-based additives significantly impacts processing quality and process automation due to high magnetic remanence. Additionally, the increased requirements for the storage of liquid hydrogen regarding low-temperature toughness push the conventional low-temperature materials to their limits. A potential solution to the identified challenges can be achieved by using medium- and high-manganese austenitic steels. Within the scope of this work, the medium-manganese steel X2CrMnNiN1775 (1.4371) is investigated as an economical substitute for the conventionally used materials in cryogenic applications. Considering the relevant qualification requirements for welded joints and welding additives, submerged arc welded joints are investigated and their applicability under cryogenic operating temperatures is demonstrated.

Critical Task Need Analysis of English for Room Division Department of Hospitality Industry: Internship Students’ Reflection

English for hospitality workers is mostly used in the room division where this section is directly related to guests that includes the realm of housekeeping and front office work. In this study, it will be discussed how the needs analysis of the use of English is taken from the learner approach to the task approach. The purpose of the study is for ensuring that language instruction is relevant, efficient, and tailored to the specific requirements of the hospitality industry, ultimately contributing to the success of both employees and the hotel itself. This research is a mixed method research that uses 74 internship students and 5 hotel workers in the field of human resources as research samples. In this study, it was found that the needs of learners that are important to consider at the beginning are subjective and objective needs, related to their attitudes towards English and their own needs. In the task approach, the learning level is divided according to the target task and task type (basic user, intermediate user, and proficient user) and then the pedagogical aspects are analyzed where students in getting learning should be with authentic and communicative materials and student-centered. In addition, from interview of hotel worker, hotel workers recognize English language proficiency as a fundamental skill that enhances their effectiveness, job satisfaction, and career prospects in the dynamic and diverse hospitality industry

123VCF: an intuitive and efficient tool for filtering VCF files

BackgroundThe advent of Next-Generation Sequencing (NGS) has catalyzed a paradigm shift in medical genetics, enabling the identification of disease-associated variants. However, the vast quantum of data produced by NGS necessitates a robust and dependable mechanism for filtering irrelevant variants. Annotation-based variant filtering, a pivotal step in this process, demands a profound understanding of the case-specific conditions and the relevant annotation instruments. To tackle this complex task, we sought to design an accessible, efficient and more importantly easy to understand variant filtering tool.ResultsOur efforts culminated in the creation of 123VCF, a tool capable of processing both compressed and uncompressed Variant Calling Format (VCF) files. Built on a Java framework, the tool employs a disk-streaming real-time filtering algorithm, allowing it to manage sizable variant files on conventional desktop computers. 123VCF filters input variants in accordance with a predefined filter sequence applied to the input variants. Users are provided the flexibility to define various filtering parameters, such as quality, coverage depth, and variant frequency within the populations. Additionally, 123VCF accommodates user-defined filters tailored to specific case requirements, affording users enhanced control over the filtering process. We evaluated the performance of 123VCF by analyzing different types of variant files and comparing its runtimes to the most similar algorithms like BCFtools filter and GATK VariantFiltration. The results indicated that 123VCF performs relatively well. The tool's intuitive interface and potential for reproducibility make it a valuable asset for both researchers and clinicians.ConclusionThe 123VCF filtering tool provides an effective, dependable approach for filtering variants in both research and clinical settings. As an open-source tool available at https://project123vcf.sourceforge.io, it is accessible to the global scientific and clinical community, paving the way for the discovery of disease-causing variants and facilitating the advancement of personalized medicine.

Constraint-based high utility mobile trajectory pattern mining for security systems

In security system, high utility pattern mining of a large number of users mobile trajectories is helpful to analyze user behavior patterns, and enhance the internal prevention of the security system.Currently, the frequent pattern mining for mobile trajectory in security systems do not take into account the differences in the safety levels between staying points and the frequency of their occurrence. Existing high utility mobile trajectory pattern mining methods are unable to discover staying points that meet specific user requirements. To solve these problems, a constraint-based high utility mobile trajectory mining algorithm is proposed (names as HUIM-ILC-ACO). It takes into account the user’s stay time, stay frequency, and the safety level of each stopping point and calculates the utility value of each staying point by incorporating these factors through weighted computation. Based on this, the algorithm combines ant colony optimization with length constraints and item constraints to construct a method for mining high utility mobile trajectory patterns that better align with user interests. Experimental results on real datasets and a target mobile trajectory RFID dataset show that proposed algorithm is efficient in terms of runtime and pattern quantity, and it can effectively mine a pattern set that is closer to user interests.

Process information optimization method based on process constituent elements model and polychromatic set theory

This research presents a novel model for optimizing process information in manufacturing steps through the utilization of Process Constituent Elements (PCE), with the aim of enhancing the effectiveness of product process information design. To achieve this objective, a systematic analysis is conducted on six dimensions: input, output, resources, value-adding activities, environment, and process control and inspection content. In addition, specific attributes of PCE are investigated, and an improved FP-growth algorithm is employed to extract the optimized structural expressions of typical PCE, thus determining specific expression requirements. The PCE and their attribute relationships are organized into modular mapping rules, resulting in an optimized representation structure based on a polychromatic set approach. The effectiveness of this approach is quantitatively assessed by developing a comprehensive quality indicator evaluation system for process information and using a fuzzy comprehensive evaluation model for analysis.

Tuning the antimicrobial activity of microbial glycolipid biosurfactants through chemical modification.

Sophorolipids, glycolipid biosurfactants derived from microorganisms such as Starmerella bombicola, possess distinctive surface-active and bioactive properties, holding potential applications in cosmetics, pharmaceuticals and bioremediation. However, the limited structural variability in wild-type sophorolipids restricts their properties and applications. To address this, metabolic engineering efforts have allowed to create a portfolio of molecules. In this study, we went one step further by chemically modifying microbially produced sophorosides, produced by an engineered S. bombicola. Twenty-four new sophoroside derivatives were synthesized, including sophoroside amines with varying alkyl chain lengths (ethyl to octadecyl) on the nitrogen atom and their corresponding quaternary ammonium salts. Additionally, six different microbially produced glycolipid biosurfactants were hydrogenated to achieve fully saturated lipid tails. These derivatives, along with microbially produced glycolipids and three benchmark biosurfactants (di-rhamnolipids, alkyl polyglucosides, cocamidopropyl betaine), were assessed for antimicrobial activity against bacteria (Bacillus subtilis, Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Pseudomonas aeruginosa) and yeast (Candida albicans). Results indicated that microbially produced glycolipids, such as bola sophorosides, acidic sophorolipids and acidic glucolipids exhibit selective antimicrobial activity against the test organisms. Conversely, lactonic sophorolipids, sophoroside amines and quaternary ammonium salts display a broad antimicrobial activity. N-octyl, N-dodecyl and N-octadecyl derivatives exhibit the lowest minimal inhibitory concentrations, ranging from 0.014 to 20.0mgmL-1. This study demonstrates the potential synergy of thoughtful biotechnology and targeted chemistry to precisely tailor glycolipid biosurfactants to meet specific requirements across applications.

Prevalence and correlates of depressive symptoms among matriculated university students in Singapore during Covid-19 pandemic: findings from a repeated cross-sectional analysis

BackgroundDepression is a common issue among university students and has been particularly exacerbated during the COVID-19 pandemic. However, limited research has specifically focused on depression among university entrants.ObjectivesThis study aimed to determine the prevalence of depression severity and identify associated factors during different phases of the COVID-19 pandemic using health screening questionnaires completed by matriculated university students in Singapore.MethodsA repeated cross-sectional study was conducted at a public university in Singapore. Data from health screening questionnaires administered in 2020 and 2021, involving 15,630 newly enrolled university students, were analyzed. The questionnaires covered students’ sociodemographic information, physical health status, own and family medical history, lifestyle behaviours, and the Patient Health Questionnaire (PHQ-9). The PHQ-9 was used to measure the severity of depressive symptoms, categorizing into moderate to severe depressive symptoms (MSDS), mild depressive symptoms (MDS), or no depressive symptom (NDS). Multinomial logistic regression was used to assess the sociodemographic, physical and behavioural correlates of depression.ResultsThe prevalence of MSDS was 1% in both 2020 and 2021, while the rates for MDS were 1.93% in 2020 and 1.64% in 2021. In the 2020 cohort, male freshmen who reported better health had a lower likelihood of experiencing depression. Conversely, students of Malay ethnicity, those majoring in Engineering, those with multiple chronic diseases, monthly alcohol consumers, current smokers, and those with a family history of mental disorder had a higher likelihood of experiencing depression. Moreover, students who lived on-campus in the 2021 cohort were less likely to experience depression than those living off-campus. However, the associations between academic majors, alcohol consumption, and smoking with depression were not significant in the 2021 cohort.ConclusionsThis study reported a low prevalence of both MSDS and MDS among university entrants in Singapore. The study further identified three categories of factors associated with depression: sociodemographic, physical, and behavioural. This study suggests policy interventions to enhance targeted social support that address each student group’s specific requirements and susceptibilities. A more extensive and comprehensive study is warranted to assess the changes in student mental health status post-COVID-19 pandemic.

Deciphering Structure-Activity Relationship Towards CO2 Electroreduction over SnO2 by A Standard Research Paradigm.

Authentic surface structures under reaction conditions determine the activity and selectivity of electrocatalysts, therefore, the knowledge of the structure-activity relationship can facilitate the design of efficient catalyst structures for specific reactivity requirements. However, understanding the relationship between a more realistic active surface and its performance is challenging due to the complicated interface microenvironment in electrocatalysis. Herein, we proposed a standard research paradigm to effectively decipher the structure-activity relationship in electrocatalysis, which is exemplified in the CO2 electroreduction over SnO2 . The proposed practice has aided in discovering authentic/resting surface states (Sn layer) of SnO2 accountable for the electrochemical CO2 reduction reaction (CO2 RR) performance under electrocatalytic conditions, which then is corroborated in the subsequent CO2 RR experiments over SnO2 with different morphologies (nanorods, nanoparticles, and nanosheets) in combination with in situ characterizations. This proposed methodology is further extended to the SnO electrocatalysts, providing helpful insights into catalytic structures. It is believed that our proposed standard research paradigm is also applicable to other electrocatalytic systems, in the meantime, decreases the discrepancy between theory and experiments, and accelerates the design of catalyst structures that achieve sustainable performance for energy conversion.

Deciphering Structure‐Activity Relationship Towards CO2 Electroreduction over SnO2 by A Standard Research Paradigm

AbstractAuthentic surface structures under reaction conditions determine the activity and selectivity of electrocatalysts, therefore, the knowledge of the structure‐activity relationship can facilitate the design of efficient catalyst structures for specific reactivity requirements. However, understanding the relationship between a more realistic active surface and its performance is challenging due to the complicated interface microenvironment in electrocatalysis. Herein, we proposed a standard research paradigm to effectively decipher the structure‐activity relationship in electrocatalysis, which is exemplified in the CO2 electroreduction over SnO2. The proposed practice has aided in discovering authentic/resting surface states (Sn layer) of SnO2 accountable for the electrochemical CO2 reduction reaction (CO2RR) performance under electrocatalytic conditions, which then is corroborated in the subsequent CO2RR experiments over SnO2 with different morphologies (nanorods, nanoparticles, and nanosheets) in combination with in situ characterizations. This proposed methodology is further extended to the SnO electrocatalysts, providing helpful insights into catalytic structures. It is believed that our proposed standard research paradigm is also applicable to other electrocatalytic systems, in the meantime, decreases the discrepancy between theory and experiments, and accelerates the design of catalyst structures that achieve sustainable performance for energy conversion.

Transformative Virtual Reality Games for Adaptive Sports Training: Exploring the Perceptions of Individuals with Mobility Impairments

The rise of virtual reality (VR) technology has opened up new opportunities for individuals with mobility impairments to participate in adaptive sports training. This paper reports on a survey study of individuals with mobility impairments to explore their expectations and needs when designing and developing VR games for adaptive sports training. Results indicate that participants are highly motivated to engage in VR adaptive sports training due to its promising potential and have specific requirements for game design and development, including ease of use, realistic gameplay, and accessible controls. This study highlights the transformative potential of VR technology in providing equal opportunities for individuals with mobility impairments to participate in adaptive sports training and promotes the development of inclusive VR games for disable users. Our findings have actionable implications for game designers, developers, and researchers, as they underscore the importance of accessibility and inclusiveness in the design and development of VR games for adaptive sports training.