Subscale Model Research Articles

Digital phenotyping of social functioning and employment in people with schizophrenia: Pilot data from an international sample.

Individuals living with schizophrenia experience significant impairments in social functioning. As a major clinical outcome, social functioning requires appropriate measurement tools that can capture its dynamic nature. Digital phenotyping, using smartphone technology to collect high volume ecologically valid data, can potentially capture these facets. We investigated the viability of digital data, such as GPS, Accelerometer, and screen activation as a proxy for common social functioning measurements. We used an ordinary least squares linear regression approach to compare the performance of digital signals with the performance of past social functioning scale (SFS) scores for predicting current SFS scores and subdomain values in 62 individuals with schizophrenia using smartphone and clinical assessments over the course of a year. The outcome of interest was the current SFS, for which we compared the capacity of the digital data (active and passive), and prior SFS scores to predict SFS scores. Overall, the sub-scale models in order of performance (measured by RMSE score) were: (i) employment, (ii) social engagement, (iii) interpersonal behavior, (iv) recreation, (v) prosocial activities, (vii) performance, and (vii) competence. Digital data were particularly capable of predicting subdomain scores for employment (R2 = 0.746, Mean Squared Error (MSE) = 1.663) and social engagement (R2 = 0.710, MSE = 2.318). Digital phenotyping may have the capacity to operate as a proxy for certain social functioning measures. Future research should expand on this pilot data by focusing on establishing the reliability and validity of digital phenotyping to measure social functioning, and exploring which subdomains of social functioning are best measured digitally.

Subscale modeling of material flow in orthogonal metal cutting

Enhanced simulation capability for the cutting process is crucial to making quick evaluations of cutting forces and temperatures, which are significant for assessing the machinability of the workpiece material and predicting tool wear. In this paper, the material flow in orthogonal cutting, including primary and secondary shear zones, is represented by a viscous/viscoplastic model that includes the temperature-sensitive Johnson-Cook flow stress model. A stabilized staggered finite element procedure is developed to handle incompressible Navier-Stokes material flow in combination with convection-dominated hardening and thermomechanical interaction. To handle material flow at tool-workpiece contact, a mixed method is used to reduce spurious oscillations in contact stresses along with simplified heat transfer in the tool-workpiece interface. A novel feature is that the velocity field is resolved as a subscale field to the velocity field of the distributed primary zone deformation model. It appears that the finite element solution to the subscale material flow model is significantly more cost-effective in contrast to directly addressing the velocity field and compared to the chip-forming simulations (DEFORM 2D). The cutting forces, temperature, and stress-strain state of the material in the critical deformation regions can be accurately estimated using the subscale model. The results obtained show that the trend of the estimated forces and temperatures is consistent with our experimental measurements, the DEFORM 2D simulations, and the experimental data from the literature.

Ground Tests on BOLT at Mach 7: Cross-Facility Comparison and Stability Analysis

Transition measurements have been obtained through two experimental campaigns conducted independently by the German Aerospace Center and the French Aerospace Lab with the French Alternative Energies and Atomic Energy Commission on subscale models of the BOLT-1 flight experiment geometry. This paper details a cross-facility comparison of measurements obtained at Mach 7, as well as subsequent computational analysis. Infrared thermography measurements obtained by both campaigns have facilitated a global comparison of the transition front across facilities at analogous conditions, which are found to be in good agreement. High-frequency surface pressure fluctuation data demonstrate significant amplification of instabilities with Mack-mode characteristics in the outboard regions of the acreage. These measurements are compared to stability analyses of varying fidelity. The computational methods employed to characterize the boundary-layer transition phenomena include the traditional line-marching implementation of the parabolized stability equations (PSEs), 2D eigenvalue analysis coupled with PSE. Although the 2D eigenvalue analysis is found to predict instabilities, which correlate in terms of frequency and acreage location to the experimental measurements, the predicted amplification for these instabilities is lower than would typically be expected for transition. Line-marching results for traveling crossflow produce the best match to the experimental transition front, with a consistent transition N factor of approximately 3–3.5.

Application of Nonlinear Optimization in Flight Path Reconstruction of a Sub-scale Aircraft

One key challenge in working with free-flight test data is ensuring its compatibility with the dynamic systems of sub-scale unmanned aircraft. This is crucial to avoid errors in measurements, bias, or scaling issues that could compromise the integrity of the estimated results. We refer to this initial processing step as data compatibility checking, a rigorous process that forms the foundation of our research.Typically, this verification process involves flight path data reconstruction (FPR) predicated on estimating the aircraft’s flight kinematics. The predominant methodologies encompass the stochastic approach, the Extended Kalman Filter (EKF), and the deterministic approach, employing the Output Error Method (OEM). In this research, we propose to approach the problem from the perspective of a nonlinear optimizer to estimate the reconstruction of data derived from free-flight tests of a sub-scale aircraft.The nonlinear optimizer we employ in this research was designed to verify the authenticity of the data representing the aircraft's actual flight. It does this by comparing the measurements of attitude angles, accelerations, and velocities with the expected kinematic behavior of the aircraft. This rigorous evaluation process ensures that the reconstructed data is as close to the actual flight as possible, enhancing the reliability of our results.The sub-scale model deployed in these tests was engineered to emulate the dynamic characteristics of a full-scale aircraft, utilizing the Froude number criterion for appropriate scaling. The chosen aircraft for this project was a Cessna 177B, and the sub-scale aircraft was developed by the Aeronautical Systems Laboratory (LSA) at the Aeronautics Institute of Technology (ITA).This study will delineate the outcomes achieved through FPA employing OEM techniques and compare these results with the studies derived from the proposed nonlinear estimation method.

Examining the Performance of the Sexual Minority Adolescent Stress Inventory with Transgender and Gender-Diverse Youth and Sexual Minority Emerging Adults: A Methodological Study.

Purpose: We examined the psychometric properties and criterion validity of the Sexual Minority Adolescent Stress Inventory (SMASI) among 730 sexual minority (SM) and transgender and gender-diverse (TGD) youth aged 14 to 24 years who participated in a human immunodeficiency virus study. Methods: We tested the factor structure of the global scale and subscales and measurement invariance across age, gender identity, sex assigned at birth, sexual identity, ethnoracial identity, and city. For criterion validity, we regressed mental health and substance use measures on the global scale. Results: The global scale had excellent fit (comparative fit index = 0.95) and high reliability (omega = 0.89). Subscale model fit was adequate. We confirmed invariance by gender identity and age and established criterion validity. Conclusion: The SMASI exhibits strong psychometric properties among SM emerging adults and TGD youth. Modifications could enhance the SMASI to better capture both sexual and gender minority stress among ethnoracial minority youth.

Predicting CDR status over 36 months with a recall-based digital cognitive biomarker.

Word-list recall tests are routinely used for cognitive assessment, and process scoring may improve their accuracy. We examined whether Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) derived, process-based digital cognitive biomarkers (DCBs) at baseline predicted Clinical Dementia Rating (CDR) longitudinally and compared them to standard metrics. Analyses were performed with Alzheimer's Disease Neuroimaging Initiative (ADNI) data from 330 participants (mean age=71.4±7.2). We conducted regression analyses predicting CDR at 36 months, controlling for demographics and genetic risk, with ADAS-Cog traditional scores and DCBs as predictors. The best predictor of CDR at 36 months was M, a DCB reflecting recall ability (area under the curve =0.84), outperforming traditional scores. Diagnostic results suggest that M may be particularly useful to identify individuals who are unlikely to decline. These results suggest that M outperforms ADAS-Cog traditional metrics and supports process scoring for word-list recall tests. More research is needed to determine further applicability with other tests and populations. Process scoring and latent modeling were more effective than traditional scoring. Latent recall ability (M) was the best predictor of Clinical Dementia Rating decline at 36 months. The top digital cognitive biomarker model had odds ≈ 90 times greater than the top Alzheimer's Disease Assessment Scale-Cognitive subscale model. Particularly high negative predictive value supports literature on cognitive testing as a useful screen. Consideration of both cognitive and pathological outcomes is needed.

Design and application of a vehicle robot to FAST reflector surface

PurposeThis paper aims to introduce a wheeled vehicle robot for adapting to the surface terrain of the 500-m diameter reflector of the FAST radio telescope in China.Design/methodology/approachBy analyzing vehicles applied for different off-road environments, a six-wheeled architecture with a passive “triple-bogie” suspension is selected. A subscale model of the vehicle robot is designed, along with statics modeling and multibody simulations of the dynamics on simulated reflector panel surfaces. The slope- and step-climbing abilities of the subscale vehicle are discussed in accordance with numerical and experimental tests. An engineering scale vehicle is subsequently manufactured and tested on surface terrains of lateral as well as vertical gaps, and is finally validated on the FAST reflector.FindingsThis model of vehicle robot exhibits strong structure stability under desired payload. It can stably cross lateral gaps for maximum surface slope 28° and can traverse vertical gap for maximum surface slope 23°. The traversing abilities satisfy the mobility requirements subjected to surface terrains of FAST reflector.Originality/valueThe engineering vehicle robot negotiates the lateral as well as vertical gaps between triangle panels and has been successfully applied to the FAST reflector serving for inspection and maintenance work.

New evidence of predictive validity of SRSS-IE scores with middle and high school students

IntroductionWe report predictive validity of the newly defined Student Risk Screening Scale – Internalizing and Externalizing (SRSS-IE 9, with 9 items) when used for the first time by middle and high school teachers from 43 schools.MethodsThe sample included 11,773 middle school-aged students representing four geographic regions, and 7,244 high school-aged students representing three geographic regions.ResultsResults indicated fall SRSS-IE externalizing and internalizing latent factors as well as subscale scores (SRSS-E5, SRSS-I4, respectively) predicted year-end behavioral (office discipline referrals and in school suspensions) and academic (course failures) outcomes for middle and high school students as well as referrals to special education for middle school students. Internalizing scores also predicted referrals to special education for high school students. Externalizing and internalizing scores predicted nurse visits at the middle and high school levels with all models except for subscale models of internalizing in middle school. SRSS-IE 12 subscale scores for externalizing (SRSS-E7) and internalizing (SRSS-I5) using the original 12 items were similarly predictive of these outcomes, with few variations.DiscussionWe discuss educational implications, limitations, and directions for future inquiry.

Characteristics of Twin-Runner Darreus Water-Turbines for Tidal Current Power Generation

In order to make the electrical-power generation feasible under the lower tidal-current condition the twin-runner Darreus water-turbine was developed. The counter rotations of twin runners are expected to increase the power output. In order to find out the best distance between the runners the wind-tunnel tests using the subscale model were carried out. At the dimensionless distance of 0.18 the rotational numbers were increased up to 156 percent of those at the single-runner configuration. With this distance the water-channel test was also conducted. It was confirmed that the revolution numbers of the twin runners were increased by 20 percents of those in the single-runner configuration. The increasing effect of speed by a diffuser was investigated. At the stand-alone test of a diffuser in the wind tunnel the velocity of the current passing through the diffuser was accelerated by 1.1 of the free-stream velocity, however, in the water-channel test the subscale Darreus model with the shorter diffuser showed no increasing effect. This was primarily because of the short length of the diffuser to the mouth distance, which was determined from the standpoint of the structural efficiency. The demonstrative power generation test is planned at the Kanmon strait in March, 2012.

Multi-scale procedure for the mechanical analysis of composite laminate structures considering mixed boundary conditions

This paper presents a multi-scale procedure for the study of flat composite structures with discontinuities. In this procedure, the structure is solved using shell elements while the laminate performance and the structural discontinuities (e.g. connections or change in the laminate thickness) are analysed with a subscale model made with solid 3D elements. The kinematics of both models are coupled following the Kirchhoff–Love theory. This coupling is used during the homogenization procedure where the characteristic behaviour of the different micro-models is obtained. Periodical boundary conditions are used for the laminates whereas a combination between periodical and linear boundary conditions are used for the discontinuities. The proposed procedure allows to reproduce accurately the structure elastic behaviour, as well as the stress and strain states in regions with discontinuities, which until now could only be accurately simulated by means of expensive numerical models using volumetric solid elements.

Similarity assessment of using helium to predict smoke movement through buildings with double skin façades during building integrated photovoltaics fires

In comparison to the building attached photovoltaics (BAPVs), Building Integrated Photovoltaics (BIPVs) drive more changes in building envelope. Therefore, tackling the fire safety of building integrated photovoltaic is more complicated due to these changes and the interaction between photovoltaic panels and the building. The photovoltaic fire hazards, including smoke generation of solar glazing, closely affect the fire safety of the building and occupants. This effect is further exemplified in the case of solar double skin façade systems where the stack effect influences smoke spread from ignited integrated photovoltaic panels via the vertical space of plenum in double skin façade. In scientific research field, the sub-scale model or laboratory-scale experiments is often applied to study the building fire smoke spread, which is much less costly, time and effort consuming, compared with full-scale test. However, the major concern of the sub-scale fire tests is providing the efficient but safe ignition source. There are methods such as cold smoke and hot gas (hot smoke test), each of which has their specific limitations on the cost and safety. This paper proposes an alternative method of helium smoke to substitute the real fire test for simulating a real integrated solar façade fire. First the fire dynamic simulator model with helium source is validated by experimental helium test along with particle image velocimetry in terms of helium concentration and flow velocity. The differences between the experiments and simulations are in the acceptable range (23 and 24%). Helium smoke result similarity is then compared to small scale real fire which showed close agreement according to the small coefficient of variation (between 1.6 and 11%).

Boundary layer control for low Reynolds number fan rig testing

Ultra-high bypass ratio turbofans offer significant reductions in fuel and pollution due to their higher propulsive efficiency. Short intakes might lead to a stronger fan-intake interaction, which creates uncertainty in stability at off-design conditions. Due to the prohibitive cost of full-scale experimental testing, subscale testing in wind tunnels is used to understand this behaviour. The low Reynolds number of subscale models results in unrepresentative laminar shock-boundary layer interactions. The boundary layer state thus needs to be conditioned to better represent full-scale transonic fans. This paper proposes the use of an inexpensive and robust flow control method for the suction side of a fan blade. Design guidelines are given for the location and height of the discrete roughness elements used to control the boundary layer state. This paper also presents a rapid experimental validation methodology to ensure and de-risk the application of the boundary layer trip to 3D rig blades. The experimental methodology is applied to a generic aerofoil representative of a fan tip section. The experimental method proves that it is possible to reproduce boundary layers and pressure distributions of a full-scale fan blade on a 1/10 subscale model. The results obtained confirm that the boundary layer trip method successfully promotes transition at the location representative of full-scale blades, avoiding unrepresentative laminar shock wave boundary layer interactions. This highlights the importance of conditioning boundary layers in low Reynolds number fan rig testing.

Reliability and Validity Evidence of Two Distance Education Learning Environments Scales​

ABSTRACT Students more than ever are completing their university studies online. At the onset of the Covid-19 pandemic, most higher education providers were required to move to exclusively deliver online curriculum. It is therefore imperative that educators have access to psychometrically sound measures of students’ online learning experiences. The reliability and validity properties of the Distance Education Learning Environments Scale (DELES) and Student Engagement in the e-Learning Environment Scale (SELES) were examined. A sample of 151 Australian undergraduate students completed the DELES and SELES after completing their studies online during 2020 due to Covid-19. Cronbach alpha coefficients, subscale item correlations and linear regression analyses were completed with bootstrapping. Cronbach alpha coefficients for the SELES subscales ranged from .68 to .93 and .75 to .96 for the DELES subscales. The within subscale correlations ranged from .29 to .66 for the SELES (p < .001) and .30 to .68 for the DELES (p < .001) and the between subscale correlations ranged from .18 to .75 (p < .001) respectively. Regression findings indicated that the SELES and DELES subscale models each accounted for 56.6% and 22.2% of the unique variance of the DELES Enjoyment, respectively. These findings present important psychometric evidence about the DELES and SELES.

Effect of Directional Added Mass on Highway Bridge Response during Flood Events

This article presents a new analysis to determine the variation in modal dynamic characteristics of bridge superstructures caused by hydrodynamic added mass (HAM) during progressive flooding. The natural frequency variations were numerically and experimentally extracted in various artificial flood stages that included dry conditions, semi-wet conditions, and fully wet conditions. Three-dimensional finite element modeling of both subscale and full-scale models were simulated through a coupled acoustic structural technique using Abaqus®. Experiments were performed exclusively on a subscale model at a flume laboratory to confirm the numerical simulations. Finally, an approach to quantify the directional HAM in the dominant axes of vibration was pursued using the concept of effective modal mass. It is shown that specific vibrating modes with the largest effective mass are strongly affected during artificial flood events and are identified as the dominant modes. Numerical simulation shows that large directional HAM is introduced on those dominant modes during flood events. For the full-scale representative bridge, the magnitude of the HAM along the first structural mode was estimated to be over 5.8 times the bridge’s structural modal effective mass. It is suggested that directional HAM should be included during the design of bridges over streamways that are prone to flooding in order to potentially be appended to the AASHTO code.

Validity and Reliability of the Korean Version of the Climate, Health, and Nursing Tool

Climate change has various negative effects on human health, which has resulted in increased burden on the health care system. Nurses contribute significantly to assessing climate-related health risks and creating a healthy environment. This study aimed to evaluate the reliability and validity of the Korean version of the Climate, Health, and Nursing Tool (K-CHANT) to measure nurses' awareness, motivation, concern, and behaviors at work and at home regarding climate change and health. The 22 items of English CHANT were translated into Korean with forward-backward translation techniques. Internal consistency reliability, test-retest reliability, and construct validity using confirmatory factor analysis were performed using SPSS WIN (25.0) and AMOS (26.0). Survey data were collected from 220 master's, doctoral, and post-doctoral nursing students. The K-CHANT consists of 20 items across 5 domains. Two items of the original CHANT were excluded because of low content validity index and standardized regression weights. The internal consistency reliability of the K-CHANT, assessed by Cronbach's αá was .81, with an intraclass correlation coefficient of .66~.90. The five subscales model was validated by confirmatory factor analysis (SRMR < .08, RMSEA < .08, AGFI > .70, CFI > .70). The K-CHANT has satisfactory construct validity and reliability to measure nurses' awareness, motivation, concern, and behaviors at work and at home regarding climate change and health. Future research should examine nurses' perceptions and behaviors related to the health effects of climate change and develop an action plan to improve it.

Validity and Reliability of a Core Competencies Instrument for Nursing Students

Introduction: One of the basic competencies to become a professional nurse is clinical performance. Therefore, many studies use tools modified and supplemented by Choi to measure the clinical performance of nursing students, but there is no tool to measure the core competencies of nursing students. Aim/Objectives: This methodological study tested the reliability and validity of a self-report instrument measuring the core competencies of nursing students. Internal consistency, reliability, and construct validity were assessed using confirmatory and exploratory factor analysis. Methods: Questionnaire data was collected from 249 nursing students at four universities in J province, South Korea, from August 20 to September 30, 2020. Results: The core competencies showed reliable internal consistency, with a Cronbach’s alpha of 0.90 for the total scale. Factor loadings of the 32 items on seven subscales ranged from 0.53 to 0.88, and three factors explained a total variance of 66.22%. The seven subscales model was validated by confirmatory factor analysis (root mean square residual 0.90). Conclusions: The results demonstrate that the instrument is useful in measuring the core competencies of nursing students.

The characteristics of ventilated pool fires of Daegok-Sosa subway lines using Model-Scale tunnels and stations

The characteristics of ventilated pool fires for Daegok-Sosa subway lines with a length of 15.12 km in Seoul, South Korea were studied. The model-scale tunnels and stations were built in scale 1:50 and temperature distribution, smoke (Carbon Monoxide (CO)) spreading, back-layering phenomenon and longitudinal ventilated flow velocity were systematically investigated. Present subscale model was based on the Froude number similitude and a heptane pool fire was used as the heat source. Heat release rate of pool fire in model-scale tunnel was 1.13 kW corresponding to an equivalent 20 MW in full scale. The occurrence of smoke back-layering phenomenon could be observed by whether the upstream temperature rose at a certain position during the whole process of the fire test. In the single line parallel tunnel, the smoke was restricted to downstream of fire source, however, in the double track tunnel the smoke back layering slightly occurred in upstream region of fire source and then it soon disappeared. The smoke propagated far downstream side and the tunnel safety measures should be taken for passenger’s safe evacuation from the CO toxic gas. The longitudinal air velocities in upstream side near the fire source were accelerated and were about 11% higher than the downstream velocities in single line parallel tunnel and more than 20% higher in double track tunnel caused by the blocking effect of fire source. A generalized quasi one-dimensional flow network solver was employed to calculate the longitudinal air velocity in tunnels using the finite volume Ghost Junction Method (GJM) which were compared with the present experimental data. The required minimum longitudinal air velocities (2.0 m/sec for single line parallel tunnel and 2.5 m/sec for double track tunnel) specified in the Korean railway facility technical standards were well satisfied in this experiment.

Development of a Chinese College Students' Attitudes Toward Sexual Swear Words Scale.

Sexual swear words are frequently used and considered vulgar and controversial in Chinese. The study of attitude is not only an important part of the study of swear words, but is also an important way for predicting their use. To date, few independent studies have been conducted on Chinese sexual swear words; those that have been conducted mostly focus on language ontology rather than language use. The studies have mainly used qualitative research methods, with a lack of empirical analysis and use of measurement tools. It is feasible and necessary to study college students as the object of sexual swear words because of the prevalence of “Zu'an culture” and the abuse of sexual swear words. Based on the current research status of Chinese swear words and the context of using swear words on campus, this paper combines the research of linguistic differences in swearing, psychological theories, and social science measurement theories and uses SPSS and Mplus statistical software to develop Chinese college students' attitudes toward Sexual Swear Words Scale. The participants consist of students from Zhejiang Normal University and other universities. A total of 262 college students participated in the preliminary test. Through item analysis and exploratory factor analysis, the formal scale was formed. A total of 608 college students were formally tested, and confirmatory factor analysis, reliability, and validity tests were carried out to produce the final scale. The scale contains three subscales: Cognition (17 items), Affection (17 items), and Behavior Tendency (15 items). The results show that each subscale model fits well, has good reliability and validity, and can be used as an important tool to measure attitudes of Chinese college students toward sexual swear words.

Free-Flight Aerodynamic Testing of the Skylon Space Plane

The determination of aerodynamic coefficients for complex high-speed vehicles still requires experimental measurement. This paper details the development of the free-flight measurement technique within the University of Oxford High Density Tunnel. In particular, a novel image processing technique is developed for calculating the position of the model from high-speed video. This study focuses on the measurement of high Reynolds number experimental aerodynamic data for a subscale model of the Skylon space plane of Reaction Engines. Testing was undertaken at a Mach 7 test condition replicating flight at an altitude of 63.5 km. Results for lift, drag, and pitching moment coefficients were obtained over a range of angles of attack. Lift coefficient was nearly linear over the range of angles of attack tested, and drag coefficient was parabolic in shape, but sensitive to model yaw. The vehicle was also shown to be statically unstable, a common characteristic of canard configuration vehicles.

A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations

Lending decisions are usually made with proprietary models that provide minimally acceptable explanations to users. In a future world without such secrecy, what decision support tools would one want to use for justified lending decisions? This question is timely, since the economy has dramatically shifted due to a pandemic, and a massive number of new loans will be necessary in the short term. We propose a framework for such decisions, including a globally interpretable machine learning model, an interactive visualization of it, and several types of summaries and explanations for any given decision. The machine learning model is a two-layer additive risk model, which resembles a two-layer neural network, but is decomposable into subscales. In this model, each node in the first (hidden) layer represents a meaningful subscale model, and all of the nonlinearities are transparent. Our online visualization tool allows exploration of this model, showing precisely how it came to its conclusion. We provide three types of explanations that are simpler than, but consistent with, the global model: case-based reasoning explanations that use neighboring past cases, a set of features that were the most important for the model's prediction, and summary-explanations that provide a customized sparse explanation for any particular lending decision made by the model. Our framework earned the FICO recognition award for the Explainable Machine Learning Challenge, which was the first public challenge in the domain of explainable machine learning.11Authors are listed alphabetically.