Physical Data Research Articles

Abstract 4124709: Accelerometer-Measured Sedentary Behavior and Future Cardiovascular Disease

Background: Current consensus guidelines emphasize the importance of achieving 150 minutes or more of moderate to vigorous physical activity (MVPA) per week to promote cardiovascular health but give little guidance about sedentary behavior. Research Question: Is sedentary behavior associated with cardiovascular (CV) disease in a manner distinct from insufficient physical activity? Aims: Examine associations between accelerometer-measured sedentary behavior with risk of specific CV outcomes, including potential interactions with MVPA. Methods: Using 89,530 individuals providing one week of accelerometer-based physical activity data from the UK Biobank, we fit Cox models adjusted for demographic and lifestyle factors to assess associations between sedentary time (as a spline term) and incident atrial fibrillation (AF), myocardial infarction (MI), heart failure (HF), and CV mortality. We assessed the potential effect of MVPA on these associations by including MVPA as an adjustment variable, as well as performing subgroup analyses stratified at the guideline-recommended MVPA threshold. Results: Among 89,530 individuals (age 62±8 years, 56.4% women) undergoing accelerometry, median sedentary time was 9.4 hours/day (quartile-1: 8.2, quartile-3: 10.6). In multivariable models, using the second quartile (8.2-9.4 hours/day) as a referent, sedentary time in the top quartile (>10.6 hours/day) was associated with greater risk of HF (hazard ratio [HR] 1.45, 95% CI 1.28-1.65), and CV mortality (HR 1.62, 95% CI 1.34-1.96), with evidence of a threshold effect at 10.6 hours/day. Higher sedentary time was also associated with greater risk of incident AF (HR 1.11, 95% CI 1.01-1.21) and MI (HR 1.15, 95% CI 1.00-1.32), with an approximately linear relation. Associations with HF and CV mortality persisted after adjustment for MVPA, as well as among individuals both above and below the guideline-based activity threshold of ≥150 minutes MVPA/week. Conclusions and Relevance: Sedentary behavior is broadly associated with future adverse CV outcomes. For HF and CV mortality, associations appear distinct from insufficient MVPA, and sedentary time in excess of 10.6 hours/day conferred an increased risk.

Machine Learning Model for Predicting Walking Ability in Lower Limb Amputees.

Background/Objectives: The number of individuals with lower limb loss (LLL) is rising. Therefore, identifying the walking potential in individuals with LLL and prescribing adequate prosthetic systems are crucial. Various factors can influence participants' walking ability, to different extents. The aim of the present study was to apply machine learning methods to develop a predictive mode. This model can assist rehabilitation and limb loss care teams in making informed decisions regarding prosthesis prescription and predicting walking ability in individuals with LLL. Methods: The present study was designed as a prospective cross-sectional study encompassing 104 consecutively recruited participants with LLL (average age 62.1 ± 10.9 years, 80 (76.9%) men) at the Medical Rehabilitation Clinic. Demographic, physical, psychological, and social status data of patients were collected at the beginning of the rehabilitation program. At the end of the treatment, K-level estimation of functional ability, a Timed Up and Go Test (TUG), and a Two-Minute Walking Test (TMWT) were performed. Support vector machines (SVM) were used to develop the prediction model. Results: Three decision trees were created, one for each output, as follows: K-level, TUG, and TMWT. For all three outputs, there were eight significant predictors (balance, body mass index, age, Beck depression inventory, amputation level, muscle strength of the residual extremity hip extensors, intact extremity (IE) plantar flexors, and IE hip extensors). For the K-level, the ninth predictor was The Multidimensional Scale of Perceived Social Support (MSPSS). Conclusions: Using the SVM model, we can predict the K-level, TUG, and TMWT with high accuracy. These clinical assessments could be incorporated into routine clinical practice to guide clinicians and inform patients of their potential level of ambulation.

Design, Synthesis of Flurbiprofen Based 1,3,4-Oxadiazoles and Constrained Anticancer, Antioxidant Agents: In silico Docking Analysis.

Flurbiprofen, a primary component of a nonsteroidal anti-inflammatory drug (NSAID) used to relieve symptoms of arthritis, and is a considerable interest in medicinal chemistry due to its demonstrated potential as an effective agent in various therapeutic applications. In consideration of the 1,3,4-oxadiazole therapeutic potential and anticancer activity, a new series of flurbiprofen scaffolds have been prepared through a straightforward reaction between 5-(1-(2-fluoro-[1,1'-biphenyl]-4-yl)ethyl)-1,3,4-oxadiazole-2-thiol (4) and various organic active 2-chloro-N-phenyl acetamides (5). The synthesized series (6a-6k) was characterized using a combination of spectroscopic techniques, including FT-IR, mass, 1H-NMR, and 13C NMR, followed by physical data. The cytotoxicity of the newly synthesized congeners was investigated against MCF-7 (human breast cancer cell line) and A-549 (human lung carcinoma epithelial) cell lines and anti-inflammatory activity as DPPH and H2O2 radical scavenging ability. In the series, analogues 6c, 6e, 6h, and 6k showed excellent inhibitory activity against MCF-7 cells in the range of IC50 values of 9.10-13.67 μg mL-1 compared to DXN (IC50=9.24 μg mL-1). In this series, analogues 6c, 6f, 6h, and 6j show remarkable H2O2 radical scavenging inhibition IC50 of 48.25±0.21, 47.33±0.15, 51.10±0.25, and 44.40±0.07 μM by using ascorbic acid as a standard, whose IC50 is 49.90±0.27 μM. According to the docking results, the most potent cytotoxic compounds have a stronger binding affinity with the Flurbiprofen complex (PDB: 1R9O) because of their interactions with residues such as Arg416(A), Trp103(A), Phe97(A), Gly279(A), Ile188(A), Glu283(A), Thr287(A), Val462(A), Phe459(A), Leu345(A), Ile417(A), and Cys418(A). Furthermore, in silico drug-likeness prediction analysis suggested that the majority of the synthesized compounds exhibit good oral bioavailability based on their Lipinski's Rule of Five and toxicity using ADME/Tox predictions.

Health-care utilisation and associated economic burden in major depressive disorder and treatment-resistant depression in a longitudinal population-based cohort study of 110.000 patients

Major depressive disorder (MDD), and particularly treatment-resistant depression (TRD), lead to high levels of health-care use and disease burden. The aim of this study was to evaluate and compare the health-care resource utilisation and associated costs in these patient groups. It was a population-wide, retrospective analysis of NHS health-care electronic records in northwest London using the Discover-NOW platform, one of the largest interlinked datasets in Europe hosted by Imperial College Health Partners, which contains coded emergency and routine, primary and secondary, physical and mental health data, covering a population of more than 2.5 million. Eligible patients were adults with a diagnosis of MDD who had been prescribed at least one antidepressant between 2015 and 2020. A total of 110,406 patients were included, 101,333 [92%] with MDD and 9073 [8%] with TRD. Mean duration of depression was 52.8 (SD 41.7) months for MDD and 70.8 (SD 37.8) months for TRD (p < 0.0001). Patients with TRD had significantly higher risks of both psychiatric and somatic comorbidities such as anxiety, asthma, and alcohol misuse (all p < 0.0001). They also demonstrated increased primary care and emergency attendance rates, more frequent and longer hospitalizations, and on average 1.5 times greater total healthcare costs compared to MDD patients. Primary care visits represented the largest proportion overall (TRD mean 162 [SD 96] vs. MDD 108 [90] visits per patient, p < 0.0001; cost per patient £17,348 [SD £33,040] vs. £12,011 [£25,588], p < 0.0001) during the study period. In secondary care, accident and emergency visits accounted for the highest use (TRD mean 5.5 [10.6] vs. MDD 3.54 [SD 6.0] visits per patient, p < 0.0001) while non-elective hospitalisations incurred the highest costs (mean £2518 [£8064] vs. £1909 [SD £6807], p < 0.0001). Demand increased with the duration of depression and the number of lines of treatment. The study highlights the substantial clinical and economic burden associated with MDD and especially TRD across different care settings.

Generalized Laplace Transform with Adomian Decomposition Method for Solving Fractional Differential Equations Involving ψ-Caputo Derivative

In this study, we introduced the ψ-Laplace transform Adomian decomposition method, which is a combination of the efficient Adomian decomposition method with the generalization of the classical Laplace transform to treat fractional differential equations with respect to another function, ψ, in the Caputo sense. To validate the effectiveness of this method, we applied the derived recurrent scheme of the ψ-Laplace Adomian decomposition on several test numerical problems, including a real-life scenario in pharmacokinetics that models the movement of drug concentration in human blood. The solutions obtained closely matched the known solutions for the test problems. Additionally, in the pharmacokinetics case, the results were consistent with the available physical data. Consequently, this method simplifies the verification of numerous related aspects and proves advantageous in solving various ψ-fractional differential equations.

Physical activity policy implementation and physical activity levels in the European Union: Are we on track to close the gap between policy and practice?

National policies are a key starting point to achieve changes in population health. This study aimed to provide an overview of the relationship between physical activity policy implementation and the levels of sufficient physical activity across the European Union over the last decade.Data from the 23 indicators of the European Union Health-Enhancing Physical Activity Monitoring Framework established to monitor country implementation of the European Union Physical Activity Guidelines from 2015, 2018 and 2021, and physical activity prevalence data from the Special Eurobarometer on Sport and Physical Activity in 2013, 2017 and 2022 were analysed.European Union Member States significantly increased their physical activity policy implementation from 2015 to 2021 by 13.2 % (63.30 ± 18.89 versus 76.51 ± 14.94 %, p < 0.001, 95 % CI [-19.97, -6.45]). However, no significant change in levels of sufficient physical activity was found between 2013 and 2022 (60.59 ± 15.67 versus 61.70 ± 17.67 %, p = 0.360, 95 % CI [-3.61, 1.39]). Additionally, most European Union countries are not on track to meet the targeted 10 % relative reduction in levels of insufficient physical activity by 2025.Physical activity policies in the European Union do not appear to be related with the intended goal of increasing levels of physical activity. Policies may need to be reviewed and policy monitoring expanded, strengthened, and better integrated.

Additions to Space Physics Data Facility and pysatNASA: Increasing Mars Global Surveyor and Mars Atmosphere and Volatile EvolutioN Dataset Utility

The Space Physics Data Facility (SPDF) is a digital archive of space physics data and is useful for the storage, analysis, and dissemination of data. We discuss the process used to create an amended dataset and store it on the SPDF. The operational software to generate the archival data software uses the open-source Python package pysat, and an end-user module has been added to the pysatNASA module. The result is the addition of data products to the Mars Global Surveyor (MGS) magnetometer (MAG) dataset, its archival location on SPDF, and pysat compatibility. The primary and metadata format increases the convenience and efficiency for users of the MGS MAG data. The storage of planetary and heliophysics data in one location supports the use of data throughout the solar system for comparison, while pysat compatibility enables loading data in an identical format for ease of processing. We encourage the use of the outlined process for past, present, and future space science missions of all sizes and funding levels. This includes balloons to Flagship-class missions.

Dynamic response of rock landslides and avalanche debris flows impacting flexible barriers based on shaking table tests

Flexible barrier structures are commonly installed in mountainous regions to resist the impact effects of rock avalanches. Without reliable physical data, the study of rock landslide initiation and the impact mechanism of avalanche debris flow under seismic excitation remains poorly understood. In this study, a model of rock slope-flexible barrier system was developed to simulate seismic slope failure behavior and debris flow impact on flexible barriers. Seismic waves in shaking table tests were triaxially loaded to effectively simulate actual seismic responses. The results indicate that the response of the Acceleration Amplification Factor (AAF) is closely associated with seismic damage and deformation within the overlying rock layers and differential propagation of seismic energy on either side of the shear band triggers rockslide initiation. Furthermore, the progressive failure mode of modeled slopes under multiple seismic events is slip-compression cracking failure. Crushing spreading at the intersection of the cracking and slip surfaces is the source of the loose fractured rock mass. Finally, this paper examines the impact patterns and dynamic responses of large individual blocks and loose fractured deposits on flexible barriers. Large blocks cause localized strong acceleration in the steel wire nets, increasing the risk of local damage, whereas loose deposits tend to induce overall seismic deformation and instability of the supporting structure. The natural seismic damage mechanisms of the barrier structure are revealed. It is recommended that flexible barrier structures in earthquake-prone mountainous areas incorporate a reasonable footing design to ensure the columns can deflect out-of-plane in response to seismic activity.

A study on Modeling and Simulation of Sports Training Injury Optimization from a Biomechanical Perspective

With the development of artificial intelligence technology today, sports training is one of the important ways to keep people healthy. Reasonable sports training can keep people happy, and can also improve the physical quality of athletes. However, because the intensity of sports training is greater than the physical endurance, it may lead to physical injury. The sports training injury model can collect the physical data of athletes, and simulate whether the actions that athletes want to practice are standard and correct through the collected data. If there are errors in the simulated exercise actions, the wrong exercise actions can be corrected in time, so as to reduce the incidence of sports injury accidents. The construction of the experimental model and the calculation and analysis process of the construction data are very complex, and the existing simulation models are difficult to achieve this, which has a significant impact on the subsequent development of the simulation model. In view of this phenomenon, this paper, on the basis of the sports training injury model, combined with the neural network method, conducted an effective research on the construction of the sports training injury model, and inspected the performance of the model by testing the accuracy of the evaluation of the injury risk level, the degree of sports training injury, and the accuracy of the evaluation of the prediction results of the sports training injury model. The experimental data shows that the maximum accuracy of the sports training injury model in the horizontal and vertical directions was 94.43% and 95.26% respectively, and the maximum accuracy of the single injury degree and the composite injury degree was 48.68% and 55.01% respectively, which had high accuracy and operational efficiency, and can effectively avoid the occurrence of training injury.

NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0

Abstract. Accurate representation of fire emissions is critical for modeling the in-plume, near-source, and remote effects of biomass burning (BB) on atmospheric composition, air quality, and climate. In recent years application of advanced instrumentation has significantly improved knowledge of the compounds emitted from fires, which, coupled with a large number of recent laboratory and field campaigns, has facilitated the emergence of new emission factor (EF) compilations. The Next-generation Emissions InVentory expansion of Akagi (NEIVA) version 1.0 is one such compilation in which the EFs for 14 globally relevant fuel and fire types have been updated to include data from recent studies, with a focus on gaseous non-methane organic compounds (NMOC_g). The data are stored in a series of connected tables that facilitate flexible querying from the individual study level to recommended averages of all laboratory and field data by fire type. The querying features are enabled by assignment of unique identifiers to all compounds and constituents, including thousands of NMOC_g. NEIVA also includes chemical and physical property data and model surrogate assignments for three widely used chemical mechanisms for each NMOC_g. NEIVA EF datasets are compared with recent publications and other EF compilations at the individual compound level and in the context of overall volatility distributions and hydroxyl (OH) reactivity (OHR) estimates. The NMOC_g in NEIVA include ∼4–8 times more compounds with improved representation of intermediate volatility organic compounds, resulting in much lower overall volatility (lowest-volatility bin shifted by as much as 3 orders of magnitude) and significantly higher OHR (up to 90 %) than other compilations. These updates can strongly impact model predictions of the effects of BB on atmospheric composition and chemistry.

Low-dose radiographic inspection of welding by a novel aperiodic reverse stochastic resonance method

Abstract Low-dose radiographic inspection is a growing trend in industry to minimize radiation risks to humans and the environment. However, reduction in radiation dose often introduces significant noise, which affects image quality and hinders accurate identification of subtle defects. This study addresses this issue by introducing a novel phenomenon called aperiodic reverse stochastic resonance (ARSR), observed in nonlinear systems excited by aperiodic binary signals. ARSR enables simultaneous amplitude amplification and reversal of signals under specific noise conditions. Leveraging ARSR, we propose an image denoising framework for low-dose radiographic inspections. First, a set of projection data is obtained by using Radon transform to reduce the dimensionality of x-ray images from different angles. Then, the projection data is modulated based on the ARSR system. Finally, the image is reconstructed based on the inverse Radon transform. Simulations and experimental comparison results in welding applications validate the effectiveness of the framework, demonstrating significant improvements in image quality for low-dose radiographic defect detection. Unlike advanced methods such as Gaussian filtering, BM3D, and DnCNN, which operate at the pixel level, ARSR performs denoising at the projection data stage, reducing noise impact, preserving original information, and focusing on physical data processing during imaging. This approach enhances the detection of subtle defects, highlighting the potential of stochastic resonance in image processing.

Design, Synthesis, QSAR Studies, and Molecular Modeling of Some Novel Bis Methyl 2-[3-(benzo[d]thiazol-2-yl)-2-terephthaloyl-bis-4-oxo-thiazolidin- 5-ylidene]acetates and Screening of their Antioxidant and Enzyme Inhibition Properties.

Benzothiazolamine-based bisthiourea precursors were prepared in good yields. These bisthiourea derivatives were cyclized into symmetrical Bis Methyl 2-[3-(benzothiazol- 2-yl)-2-terephthaloyl-bis-4-oxo-thiazolidin-5-ylidene]acetates, by their condensation with (DMAD) dimethyl but-2-meditate in the presence of dry methanol. All these compounds were evaluated for their biological applications. Antioxidant activities were performed by adopting a DPPH radical assay, and an in vitro enzyme inhibition assay was performed to investigate their enzyme inhibitory potential against butyrylcholinesterase (BChE) and acetylcholinesterase (AChE). Molecular modeling and QSAR studies were performed to monitor the binding propensity of imidathiazolidinone derivatives with enzymes and DNA. Also, electronic and steric descriptors were calculated to determine the effect of structure on the activity of imidathiazolidinone derivatives. The characterization of all the synthesized compounds was done by their physical data, FT-IR, NMR and elemental analysis.

Using heart rate data from wrist worn activity trackers to define thresholds for moderate to vigorous physical activity in children and young people with cystic fibrosis

BackgroundChildren and young people with cystic fibrosis (CYPwCF) are encouraged to do an average of 60 min of moderate-to-vigorous physical activity (MVPA) daily. However, there are no agreed heart rate (HR) thresholds for defining MVPA, so it is difficult to ascertain whether these targets are actually achieved. Wearable activity trackers enable continuous monitoring of fitness-related measures such as HR and could be used to measure duration and intensity of habitual MVPA. We aimed to define personalized and responsive MVPA thresholds from HR in CYPwCF, to determine habitual time spent in MVPA during childhood and adolescence. MethodsContinuous daily HR data were collected from 142 CYPwCF wearing activity trackers over 16 months. Linear mixed-effects models were used to develop personalised estimates of resting heart rate (RHR), peak heart rate (PHR) and MVPA thresholds, which were defined using the American College of Sports Medicine heart rate reserve (HRR) method. Results309,926 days of physical activity data showed that both RHR and PHR declined with age in CYPwCF, with considerable variability within and between individuals. The HRR method produced personalised MVPA thresholds for each CYPwCF based on age, which inherently accounted for individual demographic variability and personal factors such as cardiovascular fitness or disease severity. ConclusionsBy accounting for within and between person variability in RHR and PHR, our novel method provides more accurate age-related personalised MVPA thresholds for CYPwCF than existing estimates. Our findings provide population-based estimates for RHR, PHR and MVPA thresholds at different ages in CYPwCF. This approach may help guide development of international standards for objective MVPA measurement in the era of remote HR and activity monitoring and facilitate accurate measurement of habitual physical activity in children and young people.

The association between physical outputs and match outcome across different playing styles for a professional second-tier football team across two complete seasons.

Elite-level football requires an array of physical, technical, psychological, and tactical skills. The aim of this study was to measure the association between physical outputs (distance, decelerations, accelerations) and the match outcome (win, draw, lose) in professional football. This research also examined whether the same association is influenced if a team adopts a possession or transition-based playing style. Thirty-six elite-outfield football players from an English Championship team participated in the study during the 2020/2021 and 2021/2022 seasons using physical and event data collected from an English Championship club over the 2020-2021 and 2021-2022 seasons, this study conducted a univariate analysis of variance (ANOVA) and Hedge g effect size (ES) to measure the research aims. The results showed no significant differences were found between match outcomes for each physical output metric calculated. There was a trivial ES shown for all conditions except decelerations, with win/lose having a moderate ES (g=0.53). When playing a possession-based playing style there was no significant difference or non-trivial ES found for any physical output and match outcomes. When playing a transition-based playing style there was a moderate ES found for win/draw (P=0.38, g=0.90) and win/loss (P=0.98, g=0.64). This research provides important evidence for utilizing intense deceleration actions as a physical KPI during match play for teams adopting a transitional playing style. Subsequently, training interventions should be adopted to physically prepare players to complete and sustain intense deceleration actions during match play.

A rare prenylated isoflavone-quinone from the roots of Flemingia philippinensis

In order to make more rational use of Flemingia Philippinensis, a systematic separation from the roots of F. philippinensis was performed in the current study. The investigation of chemical constituents resulted in the isolation of a rare prenylated isoflavone-quinone, fleminquinone A (1), together with four known analogues (2–5). Their structures were established by extensive physical and spectroscopic data analysis. Anti-inflammatory activities of the isolated compounds were evaluated in lipopolysaccharide induced mouse mononuclear macrophage leukemia cells RAW 264.7 model. Compound 1 exhibited significant inhibitory effects on LPS-induced NO production and COX-2. Compound 1 also significantly affected the levels of inflammatory cytokines.

Looking beyond sleep duration in understanding obesity risk in adolescents: the role of circadian timing and misalignment on adolescent dietary outcomes, physical activity, and body mass index.

This study evaluated the differences in obesity-related outcomes across multiple adolescent sleep health domains, including circadian misalignment (CM), circadian timing, and sleep duration. 53 adolescents (aged 14-18; body mass index [BMI] percentile < 95%; 53.7% female) completed a cross-sectional study that included baseline assessment of height; weight; demographics; and 10 days assessment of sleep, physical activity, and dietary outcomes. Sleep duration, sleep timing, and physical activity data were collected from all participants using wrist-worn and waist-worn actigraphs. Dietary intake was measured using the Automated Self-Administered 24 Hours dietary recalls on 3 randomized days. Circadian timing was measured using dim-light melatonin onset (DLMO), and CM was calculated as the distance of time between DLMO and the average sleep onset time. Participants were categorized into groups (early vs late circadian timing, aligned vs misaligned circadian timing, and adequate sleep vs short sleep), and differences in dietary outcomes, physical activity, and BMI were analyzed using t-tests. Adolescents with later DLMO (M = 21:30 ± 1:11) had 0.63 higher BMI and 0.47% less averaged daily percent fat consumption than adolescents with early DLMO. Adolescents with CM (M = 1:42 ± 1:06) consumed 451.77 more averaged daily kcal consumption compared with those with circadian alignment. No statistically significant differences were found in any obesity-related outcome between sleep duration groups. Our cross-sectional findings indicate that focusing on sleep timing and circadian alignment, beyond sleep duration, may promote better health outcomes for healthy adolescents. The findings of this study could enhance sleep education and inform clinical models for prevention efforts for pediatric obesity.

Association of relationship satisfaction with blood pressure: a cross-sectional study of older adults in rural Burkina Faso

ObjectivesThe objective of this study is to examine the association between relationship satisfaction and blood pressure (BP) in a low-income setting and to screen for gender moderation in this context....

The Role of Body Mass Index on Physical Activity, Symptoms, and Related Outcomes Following Pediatric Concussion

To determine the step count and self-reported activity levels for obese and nonobese pediatric patients following concussion and predict self-reported symptoms, quality of life, and psychological health over time. Participants completed the Post-Concussion Symptom Scale (PCSS), Pediatric Quality of Life (PedsQL), and Behavioral Symptom Inventory-18 (BSI-18) at an initial visit (<72hours), 3-5days postinjury, 10-18days postinjury, and 1 and 2months postinjury. Physical activity data (eg, step count) were collected via a commercial actigraph. Participants were categorized into obese and nonobese body mass index (BMI) groups based on age- and sex-adjusted growth standards. Mann-Whitney U tests compared groups while nonparametric series regression models examined the effect of obese BMI and average daily step count on PCSS, PedsQL, and BSI-18 outcomes at 1 and 2 months postinjury. One hundred ninety-four participants were included: 153 (78.9%; M=14.6±2.4years; 50% female) in the nonobese group and 41 (21.1%; M=14.2±2.0years; 44% female) in the obese group. The obese group had a 22.8% lower average daily step count in the week postinjury (P=.02). At 2 months, there was a significant association between obese BMI and worse PCSS total score (P=.042), PedsQL (P=.017), and BSI-18 anxiety (P=.046). Average daily step count in the first week postinjury was associated with a higher PCSS total score at 2months (P=.031). Pediatric patients following concussion with an obese BMI had a lower daily average step count in the week after injury and exhibited worse concussion symptoms, quality of life, and anxiety at 2months compared with those with a nonobese BMI. Active Injury Management (AIM) after Pediatric Concussion: NCT03869970.

A Provably Secure and Lightweight Two-Factor Authentication Protocol for Wireless Sensor Network

Wireless Sensor Networks (WSNs) are rapidly being integrated into various fields, significantly impacting and facilitating many aspects of human life. However, the increasingly prominent security issues associated with WSNs have become a significant challenge. This paper provides an in-depth analysis of the security challenges faced by WSNs in resource constrained and open communication environments. As a key component of the Internet of Things (IoT), a WSN can perceive, collect and transmit physical environmental data in real-time, and is widely used in military, medical, agricultural and other fields. However, the insecurity of communication channels and unauthorized user access pose severe threats to network security and data integrity. To address these challenges, this paper proposes a provably secure two-factor authentication protocol. This protocol utilizes a Chebyshev chaotic map and a two-factor authentication mechanism, which not only enhances security in WSNs but also improves authentication efficiency. The protocol is validated through security proof and performance experiments, demonstrating excellent security, functionality and efficiency. This provides strong support for secure and efficient communication in WSNs across various application scenarios.

Perancangan Basis Data Sistem Reservasi Wisma Universitas Terbuka dengan Metode Database Life Cycle

The current of wisma’s Universita Terbuka reservation system still faces various obstacles, especially related to data consistency and integrity anomalies. This problem causes errors in recording and confusion in the transaction process, such as duplication of invoice numbers, which in turn can reduce reporting accuracy. This research aims to design a basis data for the Open University guesthouse reservation system using the Basis data Life Cycle (DBLC) method. This method includes several stages, starting from needs analysis, conceptual, logical, and physical basis data design. The results show a well-structured and optimized basis data design, which supports the management of reservation data, check-in, check-out, and room reservation management. The normalization process to achieve Third Normal (3NF) ensures that the data is free from redundancy and remains consistent. The physical model of the basis data is implemented using SQL queries, which are ready to be applied to a Basis data Management System (DBMS). The designed basis data is expected to improve operational efficiency, record accuracy, and maintain data integrity in the Open University guesthouse reservation system. This research is also expected to contribute to the development of literature on systematic life cycle-based basis data design.