Relative Strength Research Articles

Anomaly Detection in Meteorological Data Using a Hierarchical Temporal Memory Model: A Study on the Case of Kazakhstan

In meteorology, which studies atmospheric events, data representing various properties such as temperature, rainfall, and wind speed are collected regularly over a certain period. Unexpected trends in the data may indicate that an abnormal situation is approaching. Therefore, time series (TS) data play an essential role in the early detection of potential meteorological risks. However, applying effective models by considering many complex parameters in performing accurate analysis and anomaly detection (AD) is an important criterion. In this study, machine learning-based AD is performed using a dataset containing meteorological data on different features collected between January 1, 2019, and June 30, 2023, for Kazakhstan, which has the ninth-largest surface area in the world. The Hierarchical Temporal Memory (HTM) model was used for AD, which can provide more accurate forecasts by modeling long-term dependencies and producing effective results in solving TS problems. Detected anomalies are reported at various levels depending on threshold values. In addition, to analyze the ADs more precisely, correlations are calculated using the Spearman model, which allows us to determine the strength and direction of the monotonic relationship between variables. The study's findings show that the HTM is an effective model for AD using TS data on meteorological features.

Country-based modelling of COVID-19 case fatality rate: A multiple regression analysis.

The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection. The determinants of mortality on a global scale cannot be fully understood due to lack of information. To identify key factors that may explain the variability in case lethality across countries. We identified 21 Potential risk factors for coronavirus disease 2019 (COVID-19) case fatality rate for all the countries with available data. We examined univariate relationships of each variable with case fatality rate (CFR), and all independent variables to identify candidate variables for our final multiple model. Multiple regression analysis technique was used to assess the strength of relationship. The mean of COVID-19 mortality was 1.52 ± 1.72%. There was a statistically significant inverse correlation between health expenditure, and number of computed tomography scanners per 1 million with CFR, and significant direct correlation was found between literacy, and air pollution with CFR. This final model can predict approximately 97% of the changes in CFR. The current study recommends some new predictors explaining affect mortality rate. Thus, it could help decision-makers develop health policies to fight COVID-19.

The effect of silica nanoparticles on the shock adiabatic relation and tensile strength in polyurethane

This work exploded the effect of silica nanoparticles on shock adiabatic relation and tensile fracture in polyurethane based on atomistic simulations. It is found that the non-uniform interface structures introduced by nanoparticles can increase the shock impedance, which also leading to increased twisting of polyurethane chains and the generation of local hotspots near the nanoparticles. The interface structures near the nanoparticle consists of polyurethane chains with a high gyration radius, and the average gyration radius increases approximately linearly with the increase in nanoparticle content. At lower shock velocity, the potential energy increment initially increases and then decreases with the increase in nanoparticle content. Bond analysis reveal that flexible segments dominate the bending and twisting deformations of polyurethane, while nanoparticles enhance the corresponding deformation degrees. Furthermore, nanoparticles can serve as void nucleation sites for early-stage tensile damage, resulting in a decrease in fracture strength. Differing from metals, the relationship between tensile strength and fracture temperature follows a more linear law. Nanoparticles inhibit the later growth and coalescence of voids by increasing the temperature and steric hindrance. The density and size distribution characteristics of voids are consistent with the changes in potential energy during the shock compression process. Unlike classical spallation, the curled polyurethane chains in the tensile region gradually orient along the shock direction, evolving into a void-fiber structure.

Trust and easy access to home care staff are associated with older adults' sense of security: a Swedish longitudinal study.

Older adults are increasingly encouraged to continue living in their own homes with support from home care services. However, few studies have focused on older adults' safety in home care. This study explored associations between the sense of security and factors related to demographic characteristics and home care services. The mixed longitudinal design was based on a retrospective national survey. The study population consisted of individuals in Sweden (aged 65+ years) granted home care services at any time between 2016 and 2020 (n=82,834-94,714). Multiple ordinal logistic regression models were fitted using the generalised estimation equation method to assess the strength of relationship between the dependent (sense of security) and independent (demographics, health and care-related factors) variables. The sense of security tended to increase between 2016 and 2020, and was significantly associated with being a woman, living outside big cities, being granted more home care services hours or being diagnosed/treated for depression (cumulative odds ratio 2-9% higher). Anxiety, poor health and living alone were most strongly associated with insecurity (cumulative odds ratio 17-64% lower). Aside from overall satisfaction with home care services, accessibility and confidence in staff influenced the sense of security most. We stress the need to promote older adults' sense of security for safe ageing in place, as mandated by Swedish law. Home care services profoundly influence older adults' sense of security. Therefore, it is vital to prioritise continuity in care, establish trust and build relationships with older adults. Given the increasing shortage of staff, integrating complementary measures, such as welfare technologies, is crucial to promoting this sense of security.

Abstract 4824: Multi-level intervention to increase minority cancer patient enrollment to clinical treatment trials- Study design considerations and baseline characteristics from the ACTWONDER2S Study

Abstract Introduction: Black/African American (AA) and Hispanic cancer patients are underrepresented in cancer clinical trials (CCTs). Disparities stem from multiple factors, thus, comprehensive, multi-level interventions (MLI) are needed. Presented here is a conceptual framework for selecting the appropriate study design for MLIs using ACTWONDER2S, a multi-level intervention (MLI) aimed to increase Black/AA and Hispanic patient participation into CCTs, as an illustrative example. Baseline characteristics of the ACTWONDER2S target populations are also provided. Methods: ACTWONDER2S integrates community health educator and digital tools into an MLI targeting community residents and physicians in the Moffitt Cancer Center (MCC) catchment area, as well as MCC patients, physicians and CCT coordinators. A literature review of the relative strengths and weakness of 5 candidate designs for MLIs was conducted, and a cluster stratified randomized design was selected. Geospatial analytics were used to identify clusters of census tracts (“priority zones”) with high Black/AA and Hispanic populations for intervention deployment. Baseline characteristics of the priority zones were described using US Census data and other sources. Results: 14 priority zones were identified, which were matched on population characteristics and randomized into intervention (n=7) and control (n=7) zones. There were no statistically significant differences between the intervention and control priority zones in total population size (paired t-test p-value=0.63), proportions of Black/AA (p=0.133) and Hispanic populations p=0.17), and distance (in miles) from MCC (p=0.64). Approximately 35.8% and 16.5% of the intervention priority zones were Hispanic or Black/AA, respectively. Average distance to MCC, cancer cases, referral and CCT enrollment rates were also similar between groups. Conclusion: Decision frameworks for MLI study design selection are lacking. The framework provided here for ACTWONDER2S can be applied to other studies seeking to evaluate MLIs. Furthermore, the randomization of the priority zones produced optimal target populations for testing the efficacy of the MIL within ACTWONDER2S. Citation Format: Dana E. Rollison, Rossybelle P. Amorrortu, Lindsay N. Fuzzell, Melany A. Garcia, Elliott S. Tapia-Kwan, Yayi Zhao, Steven A. Eschrich, Bob R. Gore, Brian S. Mittman, Nathanael B. Stanley, Susan T. Vadaparampil. Multi-level intervention to increase minority cancer patient enrollment to clinical treatment trials- Study design considerations and baseline characteristics from the ACTWONDER2S Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4824.

Community Awareness Model Based on Integrity, Attitude, Knowledge and Perception Towards Solid Waste Management and Environmental Care

Globally, the solid waste management (SWM) and environmental care (EC) are critical issues that require significant attention. Increasing community Awareness is one solution to address these challenges. Community awareness on SWM and EC refers to a community's knowledge and understanding of the importance of proper waste management and environmental care. The objectives in this study are: i) to identify the strength of relationships between variables and ii) to develop a multiple linear regression model for community Awareness, Integrity, Attitude, Knowledge, and Perception. A total of 254 respondents from UiTM Perak Branch, Tapah Campus participated by completing an online questionnaire, with 70.87% female and 29.13% male respondents. The study used a simple random sampling technique and applied correlation analysis and multiple linear regression. The results showed moderate associations (0.4 < r < 0.7) between community Awareness and Integrity, Attitude, Knowledge, and Perception regarding SWM and EC. The multiple linear regression model was found to be significant with a p-value of less than 0.05 where all variables were significantly contributed on community Awareness.

The relationship between exercise intention, behavioural plans, and exercise behaviour among Korean college students using the Health Action Process Approach (HAPA)

ABSTRACT This study was tests whether action plan mediates the relationship between exercise intention and exercise behaviour, and whether this mediation depends on the level of action self-efficacy, maintenance self-efficacy, and action control, using the HAPA model. The participants were 467 university students (269 males, 198 females, mean age 20.99 ± 2.06 years) who completed measures assessing their exercise intentions, action plan, action self-efficacy, maintenance self-efficacy, action control, and exercise behaviour. Data were analysed using hierarchical regression procedures in terms of moderated mediation. The results showed that action plan partially mediated the relationship between exercise intention and exercise behaviour. Action control × maintenance self-efficacy interaction showed that the strength of exercise intention-exercise behaviour relationship progressed linearly through levels of action plan and maintenance self-efficacy. These findings imply that exercise interventions for university students should focus on simultaneously bolstering action plan, action control, and maintenance self-efficacy.

To what extent can we predict variation of bryophyte and tracheophyte community composition at fine spatial scale along an elevation gradient?

Mounting evidence points to the need for high-resolution climatic data in biodiversity analyses under global change. As we move to finer resolution, other factors than climate, including other abiotic variables and biotic interactions play, however, an increasing role, raising the question of our ability to predict community composition at fine scales. Focusing on two lineages of land plants, bryophytes and tracheophytes, we determine the relative contribution of climatic, non-climatic environmental drivers, spatial effects, community architecture and composition of one lineage to predict community composition of the other lineage, and how our ability to predict community composition varies along an elevation gradient. The relationship between community composition of one lineage and 68 environmental variables at 2-25 m spatial resolution, architecture and composition of the other lineage, and spatial factors, was investigated by hierarchical and variance partitioning across 413 2x2m plots in the Swiss Alps. Climatic data, although significant, contributed less to the model than any other variable considered. Community composition of one lineage, reflecting both direct interactions and unmeasured (hidden) abiotic factors, was the best predictor of community composition of the other lineage. Total explained variance substantially varied with elevation, underlining the fact that the strength of the species composition-environment relationship varies depending on environmental conditions. Total variance explained increased towards high elevation up to 50 %, with an increasing importance of spatial effects and vegetation architecture, pointing to increasing positive interactions and aggregated species distribution patterns in alpine environments. In tracheophytes, an increase of the contribution of non-climatic environmental factors was also observed at high elevation, in line with the hypothesis of a stronger environmental control under harsher conditions. Further improvements of our ability to predict changes in plant community composition may involve the implementation of historical variables and higher-resolution climatic data to better describe the microhabitat conditions actually experienced by organisms.

Impacts of land use changes on discharge and water quality in rivers and streams: Case study of the continental United States

AbstractWater quality trends in streams and rivers are impacted by several factors including land use of the watershed; however, it is unclear what influence changes in the land use of a watershed subsequently have on changes in discharge and water quality in streams and rivers. This study seeks to fill this gap by evaluating the relationship between changes in land use and changes in discharge and water quality at United States Geological Survey (USGS) stream gages over the period of 2008–2016. Using land cover data and discharge and water quality data from 60 USGS gages, regression methods were applied to determine the strength of relationship between land use changes and changes in water quality and quantity. Trends in discharge and water quality were mixed, with a majority of watersheds demonstrating a decrease in dissolved oxygen and turbidity, no overall trend for discharge, and increases in specific conductance. A regression analysis revealed that discharge, turbidity, and specific conductance were correlated with changes in individual land use types with an R2 between 0.12 and 0.25. Combining the influences of multiple land uses in multivariate regression improved the predictions for discharge (R2 0.58) and specific conductance (R2 0.47), highlighting the magnitude for which land cover changes influence trends in water quality. Overall, this study demonstrates the impact that large‐scale land use changes have on surface water quality.

Vegetation cover change in Ugam Chatkal National Park, Uzbekistan, in relation to climate variables during the post-Soviet period (1991-2022)

This paper presents a comprehensive study relating to the vegetation cover change in Ugam Chatkal National Park (Uzbekistan) and its relation to climate change during the post-Soviet period (1991-2022). The study utilises remote sensing technology, specifically the Normalised Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI), to monitor spatio-temporal changes in vegetation. Landsat satellite imagery and meteorological data, including temperature and precipitation records form the basis of the analysis. The research aims to understand the impact of climatic factors, such as air temperature, soil temperature and precipitation on vegetation cover. Statistical methods, for example Pearson’s correlation analysis are employed to determine the strength and direction of relationships between these variables. The study reveals that both NDVI and SAVI are strongly correlated with air and soil temperatures, indicating the significant influence of these climatic factors on vegetation health and growth. The findings suggest that changes in vegetation cover in the Ugam Chatkal National Park are closely tied to climate change, with air temperature revealing a substantial correlation with time, indicating a trend towards increasing temperatures. The study also forecasts future climatic and vegetation trends, predicting an increase in air temperature, precipitation and vegetation cover over the next four decades. In particular, the research highlights the magnitude of monitoring and understanding the complex interactions between climate change and vegetation dynamics, which are crucial for environmental management and policy-making in the region.

Thermal impact on superplasticizer-free metakaolin-nano-silica binary and ternary mortars

ABSTRACT Binary and ternary blended mortars were prepared by replacing ordinary Portland cement with varying percentages of MK (10%, 15%, 20%) and NS (1.5%, 3%, 4.5%) to study their performance under elevated temperatures. Superplasticisers were not used to ensure an unadulterated assessment of thermal performance. Heat resistance was evaluated based on the area under the relative residual compressive strength curve concerning temperature. After heat treatment, surface cracking, spalling frequency, and weight loss were assessed. Morphological changes due to elevated temperature exposure were observed through SEM analysis. The findings indicate that the ternary mortar mix with 10% MK and 1.5% NS exhibited the highest thermal resistance. Increased MK and NS proportions resulted in decreased thermal resistance. The mortars remained crack-free until 350°C, with spalling observed at 650°C. Mortar MK10NS3 displayed higher spalling frequency due to its denser pore structure, showcasing the potential of MK and NS in enhancing thermal resistance.

Research on the green innovation effect of digital economy network – Empirical evidence from the manufacturing industry in the Yangtze River Delta

The digital economy is open and borderless, and the development of an urban digital economy forms an associated network. Based on the social network theory, the digital economic association network formed between cities can enable manufacturing enterprises to obtain heterogeneous resources, stabilize the network relationship between nodes, and improve innovation performance. The digital economy's spatial correlation network drives the manufacturing industry's green innovation to improve quality and efficiency. Through the integration of external relations, green innovation, proximity, regional innovation system, and other dimensions of the theory, this study takes 41 prefecture level cities in the Yangtze River Delta from 2006 to 2021 as samples to construct the digital economy correlation network of urban agglomerations and uses the social network analysis method (SNA) to reveal the evolution law of the digital economy correlation networks. We establish the panel fixed effect model to explore the green innovation effect of digital economy networks. The results show that the Yangtze River Delta urban agglomeration constitutes a spatial correlation network of the digital economy, promotes the sharing and exchange of manufacturing resources through factor linkage, and produces a green innovation effect. The network centrality and relationship strength have a significant inverted U-shaped relationship with the green innovation of the manufacturing industry. There is a significant U-shaped relationship between structural holes and the green innovation of the manufacturing industry. Accordingly, we should further improve the design of digital economy development and promote the development of the manufacturing industry.

Relative handgrip strength as a vitality measure in US stroke survivors

Purpose Stroke is a leading cause of long-term disability in the US, yet a feasible assessment measure with predictive value for components of the International Classification of Functioning, Disability, and Health (ICF) Core Set for Stroke is lacking. The purpose of the present study was to explore the predictive value of potential assessment measures on factors within each ICF component in stroke survivors. Materials and Methods Demographic, anthropometric, blood-based biomarker, physical functioning, and Global Physical Activity Questionnaire data were collected on stroke survivors in the 2011–2018 NHANES cycles. Potential predictors (handgrip strength relative to weight, age, sex, race, education level, marital status, poverty ratio, stroke chronicity) of physical function, activities of daily living (ADLs), participation in social activities, metabolic syndrome, and meeting physical activity recommendations were evaluated using weighted linear and ordinal logistic regression. Results Relative handgrip strength was a significant predictor of physical function, difficulty participating in ADLs and social activities, and odds of meeting physical activity recommendations. As relative handgrip strength increased, these factors improved among stroke survivors. Conclusions To decrease disability rates and optimize function among stroke survivors, the use of assessment measures like relative handgrip strength that may predict multiple ICF components is warranted.

Short-term residual characteristics of ambient-cured green geopolymer mortar exposed to elevated temperatures.

Every structure might be exposed to fire at some point in its lifecycle. The ability of geopolymer composites to withstand the effects of fire damage early before it is put out is of great importance. This study examined the effects of fire on geopolymer composite samples made with high-calcium fly ash and alkaline solution synthesised from waste banana peduncle and silica fume. A ratio of 0.30, 0.35, and 0.4 was used in the study for the alkaline solution to fly ash. Also used were ratios of 0.5, 0.75, and 1 for silica oxide (silica fume) to potassium hydroxide ratio. The strength loss, residual compressive strength, percentage strength loss, relative residual compressive strength, ultrasonic pulse velocity, and microstructural properties of the thirteen mortar mixes were measured after exposure to temperatures of 200, 400, 600, and 800 °C for 1 h, respectively. The results reveal that geopolymer samples exposed to elevated temperatures showed great dimensional stability with no visible surface cracks. There was a colour transition from dark grey to whitish brown for the green geopolymer mortar and brown to whitish brown for the control sample. As the temperature rose, weight loss became more pronounced, with 800 °C producing the most significant weight reduction. The optimum mixes had a residual compressive strength of 25.02 MPa after being exposed to 200 °C, 18.72 MPa after being exposed to 400 °C, 14.04 MPa after being exposed to 600 °C, and 7.41 MPa after being exposed to 800 °C. The control had a residual compressive strength of 8.45 MPa after being exposed to 200 °C, 6.67 MPa after being exposed to 400 °C, 3.16 MPa after being exposed to 600 °C, and 2.23 MPa after being exposed to 800 °C. The relative residual compressive strength decreases for green geopolymer mortar are most significant at 600 and 800 °C, with an average decrease of 0.47 and 0.30, respectively. The microstructure of the samples revealed various phase changes and new product formations as the temperature increased.

Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin.

Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.

Association between handgrip strength and metabolic syndrome in relation to gender and adiposity among middle aged and older Saudi populations

Aim This cross-sectional study investigated the association between metabolic syndrome (MetS) and handgrip strength (HGS) with respect to sex and adiposity in Saudi men (n = 287) and women (n = 268). Material and methods Anthropometry, body composition, HGS, and blood biochemistry were measured. The average age of the study population was 57.65 ± 9.3 years (men = 55.1 ± 9.3 years, women = 60.4 ± 9.3 years). We report that HGS/body mass index (BMI), HGS/weight, and HGS/fat (%) were significantly higher in controls than in patients with MetS in men but not in women. According to the ROC analysis, relative HGS (RHGS) was higher than HGS alone in the association with MetS, which was significant for men (p < 0.01). At lower quartiles of HGS, the probability of MetS was higher in women, and the same was found in men in the lower quartiles of HGS/%Fat. Multinomial regression revealed significant associations between age and adiposity and MetS in men and HGS in women. Additionally, the linear regression of age, HGS, and weight exhibited significant associations between HGS with WC in both sexes. Conclusion A higher risk of MetS in the lower quartiles of HGS was found in women, and adiposity moderated the relationship between HGS and MetS in men.

Managing Postoperative Complications in a Patient with Excessive Ankle Stiffness: A Case Study Addressing Balance, Muscle Strength, and Quality of Life

Introduction: Postoperative complications decrease muscle strength and balance. Thus, managing the complications is crucial for optimizing patient outcomes and promoting speedy recovery. This case study explores the use of Instrument-Assisted Soft Tissue Mobilization (IASTM) and electrotherapy in managing postoperative complications in a patient with excessive ankle stiffness, addressing balance and muscle strength, as they are essential components of functional mobility in patients with ankle stiffness. Case Presentation: A 41-year-old female athlete with Achilles tendon contracture participated in this study. A 12-week IASTM and electrotherapy was implemented. Isokinetic muscle strength, balance, and quality of life were investigated. Results: The results showed significant improvement in the stability index, path length and area, dorsiflexion/plantarflexion peak torque, range of motion (ROM), total work, and reduced passive stiffness. The results of all domains of quality of life (SF-36), Foot and Ankle Ability Measure (FAAM), , Achilles Tendon Rupture Score (ATRS), Visual Analog Scale (VAS), and Foot and Ankle Outcome Score (FAOS) improved. The intervention was successful in improving balance, muscle strength, sagittal plane ROM, and quality of life and reduced pain during balance in the patient. Conclusions These findings suggest that the intervention may be an effective treatment option for individuals with excessive ankle stiffness and related balance and strength deficits.

The high-energy tail of energetic electron precipitation: solar wind drivers and geomagnetic responses

Compositional NOx changes caused by energetic electron precipitation (EEP) at a specific altitude and those co-dependent on vertical transport are referred to as the EEP direct and indirect effect, respectively. The direct effect of EEP at lower mesospheric and upper stratospheric altitudes is linked to the high-energy tail of EEP (≳ 300 keV). The relative importance of this direct effect on NOx, ozone, and atmospheric dynamics remains unresolved due to inadequate particle measurements and scarcity of polar mesospheric NOx observations. An accurate parameterization of the high-energy tail of EEP is, therefore, crucial. This study utilizes EEP flux data from MEPED aboard the POES/Metop satellites from 2004–2014. Data from both hemispheres (55–70° N/S) are combined in daily flux estimates. 164 peaks above the 90th percentile of the ≳ 30 keV flux are identified. These peaks are categorized into absolute E1 and E3 events representing weak and strong ≳ 300 keV responses, respectively. A subset of absolute E1 and E3 events with similar ≳ 30 keV responses is termed overlapping events. Additionally, relative E1 and E3 events are determined by the relative strength of the ≳ 300 keV response, scaled by the initial ≳ 30 keV flux. A comparison between E1 and E3 events aims to identify solar wind and geomagnetic conditions leading to high-energy EEP responses and to gain insight into the conditions that generate a high-energy tail, independent of the initial ≳ 30 keV flux level. Superposed epoch analysis of mesospheric NO density from SOFIE confirms an observable direct impact on lower mesospheric chemistry associated with the absolute E3 events. A probability assessment based on absolute events identifies specific thresholds in the solar wind-magnetosphere coupling function (epsilon) and the geomagnetic indices Kp*10 and Dst, capable of determining the occurrence or exclusion of absolute E1 and E3 events. Elevated solar wind speeds persisting in the recovery phase of a deep Dst trough appear characteristic of overlapping and relative E3 events. This study provides insight into which parameters are important for accurately modeling the high-energy tail of EEP.

Timing of Deep and REM Sleep Based on Fitbit Sleep Staging in Young Healthy Adults under Real-Life Conditions.

Sleep timing is controlled by intrinsic homeostatic and circadian components. The circadian component controls the chronotype, which is defined by the propensity to sleep at a particular clock time. However, sleep timing can be significantly affected by external factors such as the morning alarm clock. In this study, we analysed the timing of deep and REM sleep as well as the composition of REM sleep using Fitbit sleep staging in young healthy adults (n = 59) under real-life conditions. Sleep stage percentiles were correlated with the timing of total sleep in time after sleep onset for the homeostatic component and in clock time for the circadian component. Regarding the circadian component, the phase of total sleep is most strongly associated with the phases of early deep sleep and REM sleep. Furthermore, a stronger phase relationship between deep and REM sleep with total sleep is associated with greater consolidation of REM sleep. Chronotype-dependent sleep loss correlates negatively with the strength of the phase relationship between deep sleep and total sleep. In conclusion, the interaction of the circadian component of sleep timing with the timing of sleep stages is associated with REM sleep quality. In particular, the interaction of the circadian component of sleep timing with deep sleep seems to be more vulnerable to external factors.

Research on nonlinear ultrasonic method for evaluating the mechanical properties of 3D printing aluminum alloy

Micro defects, such as pore and inclusions, inevitably appear in the forming process of three-dimensional (3D) printed materials, which would affect the mechanical properties of materials. Therefore, a nondestructive testing method is urgently needed to evaluate the effect of these micro defects on the mechanical properties of materials. In the present work, by using a nonlinear ultrasonic testing technology, mechanical test and characterization of material microstructure, the relationship between the relative acoustic nonlinearity parameter (RANP), tensile strength and material defect ratio of 3D printed aluminum alloy specimens under different scanning powers is investigated. The analysis results show that the greater the material defect ratio is, the smaller the tensile strength is and the greater the RANP is, and the RANP could be used to evaluate the strength of materials. Moreover, fatigue damage induced by high cycle fatigue loading test in the first stage of early performance degradation, the results of nonlinear ultrasonic testing show that the RANP presents an increasing trend as the fatigue load increases. By observing changes in material microstructure, it is found that the increasing acoustic nonlinearity parameter is due to the directional coarsening degree of the precipitated phase increasing, which shows that RANP is very sensitive to the change of material microstructure. The above results show that, the nonlinear ultrasonic testing technology can quantitatively evaluate and predict the mechanical performance and early performance degradation of 3D printing aluminum alloy.