Scale Components Research Articles

Studies of genetic diversity and genome-wide association for vitamin C content in lettuce (Lactuca sativa L.) using high-throughput SNP arrays.

Lettuce (Lactuca sativa L.) is a source of beneficial compounds though they are generally present in low quantities. We used 40K Axiom and 9K Infinium SNP (single nucleotide polymorphism) arrays to (i) explore the genetic variability in 21 varieties and (ii) carry out genome-wide association studies (GWAS) of vitamin C content in21 varieties and a population of 205 plants from the richest variety in vitamin C ('Lechuga del Pirineo'). Structure and phylogenetic analyses showed that the group formed mainly by traditional varieties was the most diverse, whereas the red commercial varieties clustered together and very distinguishably apart from the rest. GWAS consistently detected, in a region of chromosome 2, several SNPs related to dehydroascorbic acid (a form of vitamin C) content using three different methods to assess population structure, subpopulation membership coefficients, multidimensional scaling, and principal component analysis. The latter detected the highest number of SNPs (17) and the most significantly associated, 12 of them showing a high linkage disequilibrium with the lead SNP. Among the 84 genes in the region, some have been reported to be related to vitamin C content or antioxidant status in other crops either directly, like those encoding long non-coding RNA, several F-box proteins, and a pectinesterase/pectinesterase inhibitor, or indirectly, like extensin-1-like protein and endoglucanase 2 genes. The involvement of other genes identified within the region in vitamin C levels needs to be further studied. Understanding the genetic control of such an important quality trait in lettuce becomes very relevant from a breeding perspective.

Development and validation of the mathematics self-efficacy scale for university students

Background: Academic underperformance in mathematics is widespread across all educational levels. To comprehend its causes, it is crucial to analyze various factors that impact academic advancement in mathematics through their interplay. The present study aimed to develop and validate a mathematics self-efficacy scale for university students. Methods: The research method was correlational and of instrument development type. The statistical population included all undergraduate students of Islamic Azad Universities in Tehran in 2021, of which 300 were selected as a sample using a multi-stage cluster random sampling method. In the process of scale construction, a set of items was initially selected based on a review of the research literature in the field of mathematics self-efficacy and the identification of valid tests in this area. Then, a preliminary version of the questionnaire was administered to a sample of 300 students. Factor analysis, Cronbach’s alpha coefficient, and Pearson correlation coefficient were used to analyze the data. Results: Based on the results of the exploratory factor analysis, the mathematics self-efficacy scale consisted of four components: mathematical achievement and success, general mathematical self-efficacy, mathematical anxiety, and mathematical stress. Cronbach’s alpha for the four components were 0.97, 0.95, 0.95, and 0.93, respectively. The results of the convergent validity evaluation showed that all four components of the mathematics self-efficacy scale were positively correlated with the intrinsic and extrinsic motivation components of the Academic Motivation Scale and negatively correlated with academic motivation. Conclusion: The components of the mathematics self-efficacy scale had acceptable internal consistency and convergent validity. Therefore, it can be concluded that the designed scale can be used as a valid tool to measure the level of mathematics self-efficacy in university students.

Design Method of a Novel Interface Connection Device for Multiscale Test Model Considering Multiparametric Similarity of Internal Forces

ABSTRACTThe multiscale model of building structures, as a balanced solution between accuracy and cost, has been widely used in the analysis of structural seismic performance. A reasonable interface connection method can accurately ensure load transfer and motion coordination between models of different scales. In this paper, a novel interface connection device and the corresponding design method for a multiscale test model of building structures were proposed, in which the upper structure with smaller sized components was replaced by a simplified story‐scale model, and the lower structure was adopted as a component‐scale model. The overall and local equations of motion for this multiscale model were established. For the interface connection between different scale models, a design method considering multiparametric similarity of shear force, axial force, and bending moment was proposed. In this method, the internal nodes at the interface of the component scale model were decomposed, and the coupling relationship of internal force between two adjacent nodes was established. The axial force of each node was decoupled into the interstory shear force and bending moment provided together. Additionally, the overturning moment is provided by adding the overlapping domain. According to the equilibrium relationships of the nodes at the interface, the corresponding transfer matrix was provided, and the design method of the interface connection device was proposed. The accuracy and feasibility of the method were validated by static and shaking table tests on a frame structure.

Pangolin scales as adaptations for innate immunity against pathogens

BackgroundPangolins are the only mammals that have overlapping scales covering most of their bodies, and they play a crucial role in the ecosystem, biological research, and human health and disease. Previous studies indicated pangolin scale might provide an important mechanical defense to themselves. The origin and exact functions of this unique trait remain a mystery. Using a multi-omics analysis approach, we report a novel functional explanation for how mammalian scales can provide host–pathogen defense.ResultsOur data suggest that pangolin scales have a sophisticated structure that could potentially trap pathogens. We identified numerous proteins and metabolites exhibiting antimicrobial activity, which could suggest a role for scales in pathogen defense. Notably, we found evidence suggesting the presence of exosomes derived from diverse cellular origins, including mesenchymal stem cells, immune cells, and keratinocytes. This observation suggests a complex interplay where various cell types may contribute to the release of exosomes and antimicrobial compounds at the interface between scales and viable tissue. These findings indicate that pangolin scales may serve as a multifaceted defense system, potentially contributing to innate immunity. Comparisons with human nail and hair revealed pangolin-specific proteins that were enriched in functions relating to sensing, immune responses, neutrophil degranulation, and stress responses. We demonstrated the antimicrobial activity of key pangolin scale components on pathogenic bacteria by antimicrobial assays.ConclusionsThis study identifies a potential role of pangolin scales and implicates scales, as possible determinants of pathogen defense due to their structure and contents. We indicate for the first time the presence of exosomes in pangolin scales and propose the new functions of scales and their mechanisms. This new mechanism could have implications for multiple fields, including providing interesting new research directions and important insights that can be useful for synthesizing and implementing new biomimetic antimicrobial approaches.

Quality of life under treatment with the immune checkpoint inhibitors ipilimumab and nivolumab in melanoma patients. Real-world data from a prospective observational study at the Skin Cancer Center Kiel

PurposeCombined immunotherapy (ipilimumab + nivolumab) has improved survival in stage IV melanoma patients, making Health-related Quality of Life (HrQoL) crucial due to potential immune-related adverse events (irAEs). Previous studies treated HrQoL as secondary/explorative endpoint, and no specific HrQoL questionnaire for melanoma patients on immune checkpoint inhibitor (ICI) therapy exists. This study aimed to gather specific HrQoL data during combined ICI therapy, tracking changes during and after treatment, and examining associations with gender, irAEs, and treatment response.Methods35 melanoma patients (22 males, 13 females) undergoing combined ICI were surveyed using the Short-form 36 questionnaire (SF-36), the Inflammatory Bowel Disease Questionnaire – Deutsch (IBDQ-D), and the distress thermometer (DT). HrQoL was evaluated during treatment, after six months, and at the onset of autoimmune colitis.ResultsirAEs occurred in 51.4% of patients, with colitis being the most common (26.1%). 45.7% had progressive disease. SF-36 showed stable HrQoL during treatment and follow-up. Women had worse HrQoL on the physical component scale than men (p = 0.019). Patients with progression showed worse HrQoL over time in physical (p = 0.015) and mental health scales (p = 0.04). IBDQ-D showed constant HrQoL throughout treatment and follow-up. Distress on DT remained constant, with women reporting higher levels of distress.ConclusionHrQoL remained stable during and after therapy. Female gender and disease progression negatively impacted HrQoL. The development of irAEs was not associated with HrQoL, though this may not apply to severe irAEs like colitis, which were not assessed.

Impact of Six Months of Three Different Modalities of Exercise on Stress in Post-Treatment Breast Cancer Survivors

Abstract: Background/Objectives: Extensive evidence suggests that exercise is physically and mentally beneficial for cancer survivors. This study reports on changes in self-reported stress, physiological biomarkers for stress (salivary cortisol), and HR-QOL constructs for fifty breast cancer survivors participating in one of three different exercise programs over 6 months. Methods: Fifty post-treatment breast cancer survivors were randomized to either therapeutic yoga-based exercise (YE), comprehensive exercise (CE) (aerobic, resistance, flexibility), or choosing (C) their own exercise activities. Participants completed the Perceived Stress Scale (PSS), Medical Outcomes Short-Form 36® (SF-36), and the Pittsburgh Sleep Quality Index (PSQI). Five samples of salivary cortisol were collected on two consecutive days. The 10 samples were used to calculate the diurnal rhythm slope. Outcome measures were repeated after six months. Results: All groups improved in HR-QOL measures of PSS; PSQI sleep quality components of latency and daytime functioning; and five of the ten SF-36 scales (Mental Component Scale, Social Functioning subscale, Mental Health subscale, Physical Component Scale, Physical Functioning subscale). Although the CE group observed the most favorable change in cortisol (−0.183), where cortisol slope changes approached significance (p = 0.057), but no significant decrease in cortisol between groups were noted. Conclusion: Our results suggest that it is the engagement of, rather than the specific type of exercise, which is associated with improved HR-QOL. However, longer-term studies with better adherence monitoring and larger sample sizes are needed to better determine clinical impact.

Ability of Heart Rate Recovery and Gait Kinetics in a Single Wearable to Predict Frailty: Quasiexperimental Pilot Study.

Aging is a risk factor for falls, frailty, and disability. The utility of wearables to screen for physical performance and frailty at the population level is an emerging research area. To date, there is a limited number of devices that can measure frailty and physical performance simultaneously. The aim of this study is to evaluate the accuracy and validity of a continuous digital monitoring wearable device incorporating gait mechanics and heart rate recovery measurements for detecting frailty, poor physical performance, and falls risk in older adults at risk of falls. This is a substudy of 156 community-dwelling older adults ≥60 years old with falls or near falls in the past 12 months who were recruited for a fall prevention intervention study. Of the original participants, 22 participants agreed to wear wearables on their ankles. An interview questionnaire involving demographics, cognition, frailty (FRAIL), and physical function questions as well as the Falls Risk for Older People in the Community (FROP-Com) was administered. Physical performance comprised gait speed, timed up and go (TUG), and the Short Physical Performance Battery (SPPB) test. A gait analyzer was used to measure gait mechanics and steps (FRAIL-functional: fatigue, resistance, and aerobic), and a heart rate analyzer was used to measure heart rate recovery (FRAIL-nonfunctional: weight loss and chronic illness). The participants' mean age was 74.6 years. Of the 22 participants, 9 (41%) were robust, 10 (46%) were prefrail, and 3 (14%) were frail. In addition, 8 of 22 (36%) had at least one fall in the past year. Participants had a mean gait speed of 0.8 m/s, a mean SPPB score of 8.9, and mean TUG time of 13.8 seconds. The sensitivity, specificity, and area under the curve (AUC) for the gait analyzer against the functional domains were 1.00, 0.84, and 0.92, respectively, for SPPB (balance and gait); 0.38, 0.89, and 0.64, respectively, for FRAIL-functional; 0.45, 0.91, and 0.68, respectively, for FROP-Com; 0.60, 1.00, and 0.80, respectively, for gait speed; and 1.00, 0.94, and 0.97, respectively, for TUG. The heart rate analyzer demonstrated superior validity for the nonfunctional components of frailty, with a sensitivity of 1.00, specificity of 0.73, and AUC of 0.83. Agreement between the gait and heart rate analyzers and the functional components of the FRAIL scale, gait speed, and FROP-Com was significant. In addition, there was significant agreement between the heart rate analyzer and the nonfunctional components of the FRAIL scale. The gait and heart rate analyzers could be used in a screening test for frailty and falls in community-dwelling older adults but require further improvement and validation at the population level.

Efficient Modeling of Spatial Extremes over Large Geographical Domains

Various natural phenomena exhibit spatial extremal dependence at short spatial distances. However, existing models proposed in the spatial extremes literature often assume that extremal dependence persists across the entire domain. This is a strong limitation when modeling extremes over large geographical domains, and yet it has been mostly overlooked in the literature. We here develop a more realistic Bayesian framework based on a novel Gaussian scale mixture model, with the Gaussian process component defined by a stochastic partial differential equation yielding a sparse precision matrix, and the random scale component modeled as a low-rank Pareto-tailed or Weibull-tailed spatial process determined by compactly-supported basis functions. We show that our proposed model is approximately tail-stationary and that it can capture a wide range of extremal dependence structures. Its inherently sparse structure allows fast Bayesian computations in high spatial dimensions based on a customized Markov chain Monte Carlo algorithm prioritizing calibration in the tail. We fit our model to analyze heavy monsoon rainfall data in Bangladesh. Our study shows that our model outperforms natural competitors and that it fits precipitation extremes well. We finally use the fitted model to draw inference on long-term return levels for marginal precipitation and spatial aggregates.

A Priori Test of Scale-Similarity Parameterizations for Subgrid-Scale Fluxes in Convective Storms

Abstract This study evaluates a parameterization scheme for subgrid-scale (SGS) fluxes based on the scale-similarity assumption and employing a large-eddy simulation of an idealized back-building convective system. In this parameterization, the SGS fluxes are decomposed into the “Leonard term,” which depends only on the resolved scale components, the “Reynolds term,” which depends only on the SGS components, and the “cross term,” which corresponds to the interaction between the resolved scale and SGS components. Assuming a linear relationship between the Leonard term and the Reynolds and cross terms, SGS fluxes are expressed as the product of an empirical coefficient and the Leonard term. The Leonard term reasonably represents the SGS flux derived by a smooth filter operation, including the countergradient vertical SGS transport of potential temperature, which cannot be represented by a traditional eddy-diffusivity model. The dependence of the empirical coefficient on filter width is also evaluated. This dependence is related mainly to the Reynolds term, the magnitude of which varies widely with the filter width. The estimation based on the spectral decomposition of the Reynolds term explains the obtained dependence of the empirical coefficient for the vertical flux on filter width. In contrast, the variation of the empirical coefficient with filter width is not required to obtain the horizontal flux. For the parameterization of SGS fluxes in kilometer-scale models that use finite difference or volume methods, the Leonard term is expressed by the horizontal gradient of variables on a discrete grid. The Leonard term on a discrete grid also accurately represents the amplitude and spatial pattern of the SGS flux. Significance Statement Kilometer-scale numerical weather prediction models can reproduce deep convection explicitly. However, they cannot reproduce smaller inner structures within this deep convection. Therefore, a parameterization scheme that can express the nature of the transport associated with such structures is required. Using a large-eddy simulation with a horizontal resolution sufficient to express such inner structures, we evaluated a parameterization based on the scale similarity assumption, including an empirical coefficient. Based on spectral decomposition, we quantitatively estimated the relationship between the empirical coefficient and grid spacing. Our results provide guidance in selecting the value of the empirical coefficient in this parameterization.

The MOST (Mortality Score for TBI): A Novel Prediction Model Beyond CRASH-Basic and IMPACT-Core for Isolated Traumatic Brain Injury

BackgroundDue to significant injury heterogeneity, outcome prediction following traumatic brain injury (TBI) is challenging. This study aimed to develop a simple model for high-accuracy mortality risk prediction after TBI. Study DesignData from the American College of Surgeons (ACS) Trauma Quality Program (TQP) from 2019 to 2021 was used to develop a summary score based on age, the Glasgow Coma Scale (GCS) component subscores, and pupillary reactivity data. We then compared the predictive accuracy to that of the Corticosteroid Randomisation After Significant Head Injury Trial (CRASH)-Basic and International Mission for Prognosis and Analysis of Clinical Trial in TBI (IMPACT)-Core models. Two separate series of sensitivity analyses were conducted to further assess our model's generalizability. We evaluated predictive performance of the models with discrimination [the area under the receiver-operating characteristic curves (AUC), sensitivity, specificity] and calibration (Brier score). Discriminative ability was compared with DeLong tests. Results259,404 patients were included in the present study (mean age, 60 years; 93,495 (36%) female). The mortality score after TBI (MOST) model (AUC = 0.875) had better discrimination (DeLong test p values < 0.00001) than CRASH-Basic (AUC = 0.837) and IMPACT-Core (AUC = 0.821) models, and superior calibration (MOST = 0.02729, CRASH-Basic = 0.02962, IMPACT-Core = 0.02962) in predicting in-hospital mortality. The MOST model similarly outperformed in predicting 3-, 7-, 14-, and 30-day mortality. ConclusionThe MOST model can be rapidly calculated and outperforms two widely used models for predicting mortality in TBI patients. It utilizes a larger, contemporaneous dataset that reflects modern trauma care.

Void drift in narrow rectangular channels for highly advective bubbly flows: A macroscopic drift-flux model derived from two-fluid local simulations

This article addresses the issue of reduced models to describe turbulent two-phase flows in industrial applications. This work is an application based on Bois (2021) theoretical derivations to connect the spatially-averaged drift-flux model (DFM) to the local Reynolds-averaged two-fluid model (TFM). It presents new opportunities to calibrate closure laws or propose new models based on finer-scale descriptions. Highly convective steady bubbly flows with wall-peaking void fraction profiles are considered. Dispersed bubbles are weakly deformable. A new model dedicated to void fraction dispersion in flat rectangular channels is developed for application into the DFM. The model is calibrated based on reference local Euler-Euler two-fluid simulations of pressurised water and steam mono-dispersed bubbles, in adiabatic conditions. 64 conditions are considered to cover regularly the 3D parameter space in void fraction, Reynolds and Eötvös numbers. The new formulation proposed shows a very good fit with the post-processed predictions of local CFD simulations along with a substantial reduction in grid requirement. The model contains sub-filter correlations between vapour concentration and mixture or relative velocities. This model derived from local simulations is validated a posteriori in an industrial component scale code where the full space-filtered DFM is implemented and resolved. This work proves the benefits and feasibility of one-by-one model development and calibration based on two-fluid simulations.

Upscaling bio-based products: poplar and hemp for soil and building circular synergies

Abstract The paper illustrates the rationale of an ongoing research aimed at identifying innovative applications for poplar- and hemp-based products in constructive systems, focusing on load-bearing poplar plywood elements and hemp blocks and panels for the building envelope. The underlying approach extends the circular-based perspective from the building component scale to the territorial and economic one, adopting a context-wise approach. The potential of these renewable materials is examined beyond the application to reversible building systems, to depict their comprehensive contribution to a carbon-neutral region by examining the links with the local territorial management and a potential short supply chain. The contribution describes poplar and hemp agricultural productions, connecting their outputs to several economic sector. After addressing the environmental benefits, the two cultivations produce in terms of climate change mitigation and adaptation, among which carbon uptake, it contextualises poplar- and hemp-based products within current bio-based solutions in the building sector, exploring possible applications in new and existing constructions through circular constructive systems. The results discussion outlines the sustainable multiscale synergies supported by poplar- and hemp-based building products within the research perimeter.

Psychometric Evaluation of the Emotion Beliefs Questionnaire – Norwegian Version (EBQ-N)

Abstract: The Emotion Beliefs Questionnaire (EBQ) assesses beliefs about the controllability and usefulness of positive and negative emotions. The aim of the present study was to establish the construct validity and reliability of the EBQ within the cultural and linguistic context of Norway. The Norwegian version of the EBQ (EBQ-N) was administered to a sample of university students ( N = 380, 64.2% females, 93.7% aged 25 or younger). Confirmatory factor analyses indicated that the EBQ-N is best represented by three first-order factors and a higher-order general factor, consistent with the findings of the initial validation study. The items displayed both adequate convergence in assessing their intended constructs and effective discrimination among the three first-order factors. The scale components demonstrated acceptable to good internal consistency. In the context of its intrinsic properties, the EBQ-N appears to be a valid and reliable instrument for assessing emotion beliefs in Norwegian research and clinical settings.

Growing simplicial complex with face dimension selection and preferential attachment.

When simplicial complexes are used to represent higher-order systems, information regarding when and how interactions happen may be lost. In this paper, we propose the concept of temporal simplicial complexes, in which simplices with timestamps (or temporal simplices) are used to represent interactions, and faces with weights are used to represent relations. Then, we propose a growing model with two rules, face dimension selection (FDS), and preferential attachment. By properly setting the probability parameter vector q in the FDS rule, one can balance network diameter expansion and network centrality, thus attaining more flexibility in the growing process. Our theoretical analysis and simulations that followed show the generalized degree of faces of any dimension follows a power-law distribution, with a scaling component controlled by q. Our work provides a flexible growing model and can be used to study higher-order systems with temporal properties.

Application of vibrothermography to visualise hidden cracking process in concrete at the component scale

A thorough understanding of the cracking process in concrete structures, especially the initiation and expansion processes in the hidden stage, plays a decisive role in the maturity and completion of fracture mechanics theory. However, there exist few simple methods to detect the multi-crack development under the condition of unknown initiation area at the component scale and associated behaviours of the cracks during crack development. In this study, ultrasonic thermal excitation to visualise the multi-point hidden cracking process in concrete components was studied and hidden cracking detecting experiments were conducted. Multi-point initiation and expansion within the range of the components were achieved by destroying a suitably reinforced concrete beam using four-point bending tests with step-by-step cyclic loading. The cracking processes were monitored in real time via the auxiliary use of strain gauge groups and digital image correlation (DIC). The loading process was controlled based on the strain rules, and typical cracking stages were observed. The ultrasonic thermal excitation visualisation effect at typical cracking stages was studied via local monitoring using DIC. The results show that the ultrasonic thermal excitation visualisation method and the corresponding device proposed herein can be used to monitor hidden cracking processes in concrete at the component scale, while multi-point initiation and expansion of 0.01-mm-level crack groups can be detected in a simple and efficient manner.

Effects of postural and kinesthetic awareness on static standing balance and plantar pressure in chronic stroke: a randomized controlled trial.

To determine effects of postural and kinesthetic awareness on plantar pressure and static standing stability in chronic stroke patients. The cross-sectional single-blind study was conducted at the University of Lahore Teaching Hospital, Lahore, Pakistan, from January 19 to March 2, 2023, and comprised stroke patients of both genders. aged 45-60 years having visual spatial neglect. They were randomised into control group A and experimental group B. Group A received routine physical therapy, while group B additionally received postural and kinesthetic awareness sessions. Static component of the Berg balance scale was used to measure balance, and PoData Stabiliometeric plate ("Chinesport, Italy") to measure plantar pressure. Data was analysed using SPSS version 25. Of the 52 patients, 26(50%) were in group A with mean age 51.97±4.37 years and mean weight 79.48±5.7kg. The remaining 26(50%) patients were in group B with mean age 50.69±4.41 years and mean weight 78.27±4.55kg. The outcome measures were significantly better in group B compared to group A (p<0.05). Postural and kinesthetic awareness could possibly be a well-grounded rehabilitative strategy that may support and enhance the balance of individuals with chronic stroke. The study was registered at the United States National Institutes of Health (ClinicalTrials.gov) with registration number NCT05915195.

Strategic Learning Strategies of Doctor of Physical Therapy Students

Introduction. The use of strategic learning strategies has been positively associated with academic performance in several graduate health profession programs. This finding suggests that it may be an important construct to explore in Doctor of Physical Therapy (DPT) education. The Learning and Study Strategies Inventory (LASSI) summarizes a student's perception and use of 10 learning and study strategies. Review of Literature. Although the LASSI has limited reporting in DPT education, other health care education programs have shown correlation with academic performance. The purpose of this study was to examine DPT students' early perceptions of strategic learning with descriptive summaries of LASSI data and examine correlations between demographic and admissions-related data. Subjects. Matriculated DPT students (n = 294) at a 2-year hybrid program who completed the LASSI at orientation in 2020 and 2021. Methods. This was a descriptive study that retrospectively analyzed LASSI scores in entry-level DPT students. LASSI score differences among demographic groups and Spearman's rho correlations between the LASSI, Graduate Record Examination (GRE) scores, grade point averages, grit, and emotional intelligence (EI) were explored. Results. LASSI score means were in the 50th–75th percentile (moderate category) suggesting a need for further development in strategic learning. Group differences in LASSI scores were noted for gender identity (male higher Anxiety management, P &lt; .001; female higher Attitude, P &lt; .001, Time Management, P = .003, and Use of Academic Resources, P = .003), racial–ethnic minoritized group (higher Self-regulation, P = .013), first-generation college students (higher Attitude, P = .047), physical therapy assistants (higher Information Processing, P = .047), students with a primary language other than English (higher Time Management, P = .046), and older students (higher Anxiety management, P = .026). Weak but significant correlations were identified between LASSI scale and component scores and several admissions variables. Highest correlations were with grit (Will, ρ = 0.319, P &lt; .001; Concentration, ρ = 0.312, P &lt; .001), EI (Will, ρ = 0.328, P &lt; .001; Attitude, ρ = 0.302, P &lt; .001; Self-regulation, ρ = 0.382, P &lt; .001; Use of Academic Resources ρ = 0.331, P &lt; .001), and quantitative GRE scores (Anxiety management, ρ = 0.341, P &lt; .001). Discussion/Conclusion. All LASSI scale scores and components were in the moderate category, potentially indicating a need to coach and develop strategic learning strategies. Group differences in LASSI scores may represent varied student needs. The weak relationship between LASSI scores and admissions variables could suggest that the constructs measured by LASSI are not currently captured through typical DPT admissions practices.

Patient Health Engagement Model (PHE) in Affecting Patient Activation and Self-efficacy Among Cardiac Patients

Background: Heart patients must be able to actively manage and take care of their disease, medication, and symptoms. On the other hand, following self-management recommendations also requires patient activation. Objectives: This study assessed the relationships of patient health engagement model (PHE) with self-efficacy and activation in cardiac patients. Methods: This descriptive-analytical study is cross-sectional. The sample size was determined to be 207 cardiovascular patients. Subjects were randomly selected from a list of patients referred to a government hospital in the south of Iran. The data collection tools included the Patient activation measurement (PAM-19), health promotion strategies (SUPPH), and Patient Health Engagement Scale (PHE-S). Data were analyzed using descriptive tests, linear regression, optimal scaling, correlation test, and categorical principal components analysis (CATPCA). Results: All subjects were in the third stage of the PHE model (median = 3). A total of (49.5%) of subjects had good self-efficacy, and 39.7% of patients had a good activation score. The PHE model predicted self-efficacy (P &lt; 0.001, R = 0.264) and patient activation (P &lt; 0.001, R = 0.252). Patient Health Engagement had stronger predictive power for the active participation dimension (P &lt; 0.001, R = 0.222). Conclusions: It seems that PHE is shaped according to the patients' level of activation and self-efficacy. However, more studies need to be conducted. By focusing on the emotional states, mental processes, and behavior of the patients, the PHE model can enhance their engagement in the chronic disease care process. Nonetheless, further research is necessary.

Wind speed retrieval from X-Band marine radar based on the attenuation horizontal component and azimuth scale expansion method

ABSTRACT A method based on attenuation horizontal component and azimuth scale expansion is proposed to extract wind speed from X-band marine radar images. The attenuation horizontal component of each azimuth is first retrieved by ideal attenuation model, and the wind direction is extracted by the azimuthal dependence of the attenuation horizontal component. To overcome the influence of the occlusion area, the azimuth scale expansion method is used to extract the wind direction. Then the attenuation model in the upwind direction is determined according to the attenuation horizontal component. Finally, an empirical function model relationship between the full-range integral area of the attenuation function in the upwind direction and the reference wind speed is established. The radar data used to test the algorithm were collected from a ship in the Yellow China Sea. The real-time reference wind parameters were obtained by an anemometer installed on the main mast of the ship. The experimental results show that the algorithm improves the accuracy of wind speed retrieval, effectively reduces the error caused by outlier interference in radar images, and overcomes the interference of occlusion area by combining the azimuth scale expansion method.

A Multi-scale Framework for Advancing Battery Safety Through Early Calorimetric Analysis of Materials and Components

Batteries are the cornerstone of the global shift toward electrification, powering applications from passenger transportation, like electric vehicles (EVs), to load shifting of renewable energy generation at the grid level. The demand for batteries is accelerating, and is projected to nearly quadruple by 2030. In response to increasing battery demands, in particular demand for longer range EVs, higher energy density and specific energy alternatives to conventional Li-ion battery technologies are being researched. However, higher energy density directly correlates with an increased potential for higher peak temperatures on failure. In addition, safety evaluation of conventional and new battery technologies generally occurs late in development, often at the commercialization stage when mandated by stakeholders or industry standards. This approach can be costly and challenging as it may require a change to manufacturing processes, a re-design of the battery, and even a change in chemistry to meet safety requirements. This is critical; scale-up efforts alone can take tens to hundreds of millions of dollars and &gt;5 years to achieve. Safety risks discovered after commercialization can significantly exacerbate those figures. Furthermore, safety is still a major risk with already commercialized Li-ion batteries. These risks hinder adoption, slow commercialization, and when they become issues, the outcome may result in recalls, fires, injuries, and even fatalities. Providing additional levers to proactively mitigate safety risk at the materials and components scale (e.g., composite cathode) will lead to considerable time and money savings in the long run.