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Background: Evidence on the prevalence, determinants, and health outcomes of physical activity in disabled people is limited. It is possible that the limited availability of high-quality scientific evidence is due to the extent and nature of disability assessment in physical activity research. This scoping review explores how disability has been measured in epidemiological studies that included accelerometer-based measurement of physical activity. Methods: Data sources: MEDLINE (Ovid), Embase, PsychINFO, Health Management Information Consortium, Web of Science, SPORTDiscus, and CINAHL. Eligibility criteria: Prospective and cross-sectional studies that included an accelerometer measurement of physical activity. Survey instruments used in these studies were obtained, and questions relating to the International Classification of Functioning, Disability and Health domains of (1) health conditions, (2) body functions and structures, and (3) activities and participation, were extracted for analysis. Results: Eighty-four studies met the inclusion criteria, from which complete information on the 3 domains was obtained for 68. Seventy-five percent of studies (n = 51) captured whether a person had at least one health condition, 63% (n = 43) had questions related to body functions and structures, and 75% (n = 51) included questions related to activities and participation. Conclusion: While most studies asked something about one of the 3 domains, there was substantial diversity in the focus and style of questions. This diversity indicates a lack of consensus on how these concepts should be assessed, with implications for the comparability of evidence across studies and subsequent understanding of the relationships between disability, physical activity, and health. [ABSTRACT FROM AUTHOR]

We present results from the JWST First Reionization Epoch Spectroscopically Complete Observations survey on the star-forming sequence (SFS) of galaxies at 1.0 < z < 1.7, around the peak of the cosmic star formation history. Star formation rates (SFRs) are measured from the redshifted, relatively dust-insensitive Paschen- α emission line, and stellar mass measurements include the F444W (4.4 μ m; rest-frame H) band. We find SFRs of galaxies with log(M */ M ⊙) > 9.5 that are lower than found in many earlier studies by up to 0.6 dex, but in good agreement with recent results obtained with the Prospector fitting framework. The difference (log(SFR(Pa α)-SFR(Prospector)) is −0.09 ± 0.04 dex at 1010−11 M ⊙. We also measure the empirical relation between Paschen- α luminosity and rest-frame H- band magnitude and find that the scatter is only 0.04 dex lower than that of the SFR– M * relation and is much lower than the systematic differences among relations in the literature due to various methods of converting observed measurements to physical properties. We additionally identify examples of sources—that, with standard cutoffs via the UVJ diagram, would be deemed quiescent—with significant (log(sSFR)> −11 yr−1), typically extended, Paschen- α emission. Our results may be indicative of the potential unification of methods used to derive the SFS with careful selection of star-forming galaxies and independent SFR and stellar mass indicators. [ABSTRACT FROM AUTHOR]

Metabolic dysfunction associated fatty liver disease (MAFLD) is a common cause of liver disease in children and adolescents. The relationship between insulin resistance (IR) and MAFLD in children with short stature remains largely unknown. The present study was to investigate the relationship between the triglyceride–glucose (TyG) index and alanine aminotransferase (ALT) levels in children with short stature. A total of 1754 children with short stature were enrolled. Anthropometric, biochemical and hormonal indexes were collected through physical measurement examinations and laboratory tests. A nonlinear association was found between the TyG index and ALT. The inflection point of the curve was at a TyG index of 8.24. In multivariate piecewise linear regression, only when the TyG index was greater than 8.24 was there a significant positive association between the TyG index and ALT (β 5.75, 95% CI 3.30, 8.19; P < 0.001). However, when the TyG index was less than 8.24, there was no significant association between the TyG index and ALT (β −0.57, 95% CI −1.84, 0.71; P = 0.382). This study demonstrated a nonlinear relationship between TyG index and ALT in children with short stature. This finding suggests that a high TyG index is associated with elevated ALT in children with short stature. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Materials and Methods Results Conclusions This study aimed to compare the accuracy of digital complete‐arch implant impressions with prefabricated aids using three intraoral scanners (IOSs) and explore the correlation between virtual deviation measurement and physical framework misfit.Four edentulous maxillary master models with four and six parallel and angular implants were fabricated and scanned by a laboratory scanner as reference scans. Ten scans of each master model were acquired using three IOSs (IOS‐T, IOS‐M, and IOS‐A) with and without prefabricated aids. Trueness and precision of root mean square (RMS) errors were measured. Ten aluminum alloy frameworks were fabricated, and the misfit was measured with a micro‐computed tomography scan with one screw tightened.Trueness and precision showed significant improvement when prefabricated aids were used for all three IOSs (p < 0.010). Median (interquartile range) RMS errors of trueness reduced from 67.5 (30.4) to 61.8 (30.3) μm, from 100.6 (35.4) to 45.9 (15.1) μm, and from 52.7 (33.2) to 41.1 (22.5) μm for scanner IOS‐T, IOS‐M, and IOS‐A, respectively (p < 0.010). The precision of IOS‐A and IOS‐M was significantly better than IOS‐T when using prefabricated aid (p < 0.001). RMS errors and the maximum marginal misfit of the framework were significantly correlated (p < 0.001, R2 = 0.845).With the prefabricated aids, the accuracy of IOSs enhanced significantly in digital complete‐arch implant impressions. Three IOSs showed different levels of improvement in accuracy. Virtual RMS errors <62.2 μm could be the clinically acceptable threshold (150 μm) for framework passive fit. [ABSTRACT FROM AUTHOR]

Interviewer ratings of respondents' physical appearance have been collected in several major social surveys. While researchers have made good use of such ratings data in substantive studies, empirical evidence on their measurement properties is rather limited. This study evaluates two potential threats to the quality of interviewer ratings of physical appearance: interviewer effects and halo effects. Using data from the China Family Panel Studies, we show large interviewer effects on interviewer ratings of respondents' physical appearance based on cross-classified models. We also provide possible evidence for halo effects based on high correlations between physical appearance ratings and other theoretically distinct constructs, after controlling for interviewer effects. However, we find support for convergent and discriminant validity of physical appearance ratings when both interviewer effects and halo effects are controlled for. Empirical studies using interviewer observation data should take into account interviewer effects and halo effects when possible or at least discuss their potential impact on the substantive findings. [ABSTRACT FROM AUTHOR]

Purpose: To introduce a novel deep model‐based architecture (DMBA), SPICER, that uses pairs of noisy and undersampled k‐space measurements of the same object to jointly train a model for MRI reconstruction and automatic coil sensitivity estimation. Methods: SPICER consists of two modules to simultaneously reconstructs accurate MR images and estimates high‐quality coil sensitivity maps (CSMs). The first module, CSM estimation module, uses a convolutional neural network (CNN) to estimate CSMs from the raw measurements. The second module, DMBA‐based MRI reconstruction module, forms reconstructed images from the input measurements and the estimated CSMs using both the physical measurement model and learned CNN prior. With the benefit of our self‐supervised learning strategy, SPICER can be efficiently trained without any fully sampled reference data. Results: We validate SPICER on both open‐access datasets and experimentally collected data, showing that it can achieve state‐of‐the‐art performance in highly accelerated data acquisition settings (up to 10×$$ 10\times $$). Our results also highlight the importance of different modules of SPICER—including the DMBA, the CSM estimation, and the SPICER training loss—on the final performance of the method. Moreover, SPICER can estimate better CSMs than pre‐estimation methods especially when the ACS data is limited. Conclusion: Despite being trained on noisy undersampled data, SPICER can reconstruct high‐quality images and CSMs in highly undersampled settings, which outperforms other self‐supervised learning methods and matches the performance of the well‐known E2E‐VarNet trained on fully sampled ground‐truth data. [ABSTRACT FROM AUTHOR]

In this study, three nanofluids, CuO, SiC, and TiO2, are prepared by a two‐step method, and the factors affecting the stability, thermal conductivity, viscosity and density of the three are analyzed, so as to provide theoretical reference for strengthening heat transfer of the nanofluids. First, the effects of different dispersant addition amounts, magnetic stirring time, and ultrasonic oscillation time on the stability of nanofluids are analyzed in this paper, and finally chose the best solution for preparing three nanofluids. Second, the paper determines the thermal conductivity, viscosity, and density of three kinds of nanofluids and explores the factors affecting their physical properties. The thermal conductivity of the three nanofluids at the highest temperature is 2.9, 3.2, and 1.4 times that of the lowest temperature, respectively. When the temperature increased from 25 to 65 °C, the viscosity of CuO nanofluids decreases the most at different volume concentrations, and the viscosity decreases by 41.3% at 0.6% volume concentration. The density of nanofluids decreases with the increase of temperature and increases with the increase of volume concentration. At 25 °C, the density of SiC nanofluid increases the most with the volume concentration, and its density increases by 0.72%. [ABSTRACT FROM AUTHOR]

One of the most promising approaches to food quality assessments is the use of impedance spectroscopy combined with machine learning. Thereby, feature selection is decisive for a high classification accuracy. Physically based features have particularly significant advantages because they are able to consider prior knowledge and to concentrate the data into pertinent understandable information, building a solid basis for classification. In this study, we aim to identify physically based measurable features for muscle type and freshness classifications of bovine meat based on impedance spectroscopy measurements. We carry out a combined study where features are ranked based on their F1-score, cumulative feature selection, and t-distributed Stochastic Neighbor Embedding (t-SNE). In terms of features, we analyze the characteristic points (CPs) of the impedance spectrum and the model parameters (MPs) obtained by fitting a physical model to the measurements. The results show that either MPs or CPs alone are sufficient for detecting muscle type. Combining capacitance (C) and extracellular resistance (Rex) or the modulus of the characteristic point Z1 and the phase at the characteristic frequency of the beta dispersion (Phi2) leads to accurate separation. In contrast, the detection of freshness is more challenging. It requires more distinct features. We achieved a 90% freshness separation using the MPs describing intracellular resistance (Rin) and capacitance (C). A 95.5% freshness separation was achieved by considering the phase at the end of the beta dispersion (Phi3) and Rin. Including additional features related to muscle type improves the separability of samples; ultimately, a 99.6% separation can be achieved by selecting the appropriate features. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusion To introduce a method to calculate retinal irradiance caused by ophthalmoscopy. This may be used to verify the compliance of an instrument with the radiation limits set by light hazard standards. The proposed method is simpler to use and less prone to error than the methods currently found in the light hazard standards.The optical properties of the standardised human eye, specified by current light hazard standards, are used to calculate the magnification of an aerial image of the retinal surface by the combination of the optics of eye and the auxiliary lens used for ophthalmoscopy. The magnification of the aerial image is used to transform the spectral irradiance of the instrument illumination source to retinal irradiation values. The spectral irradiance of the instrument illumination source can be measured directly as the aerial image is located in the focal plane of the viewing optics of the ophthalmoscope. These spectral irradiation values are then processed using weightings specified by current light hazard standards to give a weighted irradiance which is converted directly to a retinal irradiance value.A single formula is provided to calculate the retinal irradiance using the processed, measured spectral irradiance values of the illumination source.The new method introduced here is simpler to use, requires fewer physical measurements and is less likely to introduce measurement error than that currently found in light hazard standards. The only physical measurement that needs to be taken is the illumination source spectral irradiance measured in the viewing focal plane of the instrument. These values are weighted using given in the light hazard standards. The combined irradiance value is then converted to retinal irradiance using the formula given in this paper. [ABSTRACT FROM AUTHOR]

In order to supplement manufacturers' information, this department will welcome the submission by our readers of brief communications reporting measurements on the physical properties of materials that supersede the earlier data or suggest new research applications. [ABSTRACT FROM AUTHOR]

Virtual metrology (VM) in semiconductor manufacturing is to predict product physical quality measurements using the processing information at a wafer fabrication process. The process state parameters from various sensors on production equipment are used for the accurate and reliable prediction of process outcomes, and several deep learning methods have been considered, including convolutional neural network (CNN). Recent studies in the literature have demonstrated the successful VM modeling with CNN for univariate-response prediction. Multivariate process outputs, however, are overlooked in deep learning-based VM modeling although the joint information among the process outputs can be used to improve the prediction performance. In this work, we propose a CNN-based multivariate VM model using multi-sensors process sensor data. We evaluate the proposed model on a real-life case for VM modeling at an etching process in wafer fabrication. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with the process of experimental information gain. Building on previous work, we show that this is a discontinuous process in which the initiating quantum-mechanical matter–instrument interactions are being turned into macroscopically observable events (EOs). In the course of time, such EOs evolve into spatio-temporal patterns of EOs, which allow conceivable alternatives of physical explanation to be distinguished. Focusing on the specific case of photon detection, we show that during their lifetimes, EOs proceed through the four phases of initiation, detection, erasure and reset. Once generated, the observational value of EOs can be measured in units of the Planck quantum of physical action h = 4.136 × 10 − 15 e V s . Once terminated, each unit of entropy of size k B = 8.617 × 10 − 5 e V / K , which had been created in the instrument during the observational phase, needs to be removed from the instrument to ready it for a new round of photon detection. This withdrawal of entropy takes place at an energetic cost of at least two units of the Landauer minimum energy bound of E L a = ln ⁡ 2 k B T D for each unit of entropy of size k B . [ABSTRACT FROM AUTHOR]

The primary objective of this study was to investigate the correlations between instrument measurements and sensory attributes of thickened liquids. For this purpose, a series of thickened liquids was prepared using different thickening agent contents from different sources, which were evaluated by sensory analysis for sensory attributes and by instrument measurements for specific physical properties. The texture attributes (hardness, ease swallowing, and coating (oral cavity, residual feeling in the throat)) of 12 thickened liquid samples were investigated by sensory evaluation. The investigators were 10 panelists trained in evaluating sensory attributes. The line spread test (LST) and the short back extrusion (SBE) method were used for the instrumental analysis. The correlation coefficient between physical properties and each sensory evaluation value was also determined. The results showed that the apparent viscosity from viscosity measurements was highly correlated with each sensory attribute. As thickened liquid is a non-Newtonian fluid, the apparent viscosity was dependent on the shear rate. Hence, the instrumental texture perception of sol (thickened liquid) based on the oral cavity condition could be used to predict human texture perception based on the shear rate, which was obtained from the apparent viscosity similar to gel (strawberry jam). These results indicate that the SBE method is better than the LST for measuring the texture attributes of thickened liquids. [ABSTRACT FROM AUTHOR]

This paper examines a new Conditional Source-term Estimation (CSE) implementation in which an integral inversion is performed for species mass fractions without any chemistry tabulation. To tackle the numerical stiffness due to chemistry, a constant-pressure chemical reactor is considered in conditional space. The objective of this work is to investigate this new method in CSE by comparing its numerical performance (accuracy of predictions and computational efficiency) with previous CSE implementations using tabulated chemistry. For the first time, the constraints for mass and mixture fraction conservation in conditional space are included in the inversion process. The investigation is performed in a Reynolds Averaged Navier-Stokes (RANS) framework using a well-documented turbulent flame with detailed measurements in conditional and physical spaces for many reacting scalars. A chemical mechanism including 16 species and 35 reactions is incorporated. CSE predictions of conditional and Favre averaged temperature and different species mass fractions are analysed. CSE with full chemistry performs as well as CSE with tabulated chemistry, if not slightly better. Numerical errors are discussed. The new CSE implementation is made possible by the proposed numerical treatment of stiffness due to chemistry and first-order Tikhonov regularisation technique with additional physical constraints. The new approach is found to be more CPU intensive than CSE with a pre-tabulation technique, but as a preliminary analysis, the computational cost of CSE with direct integration of a chemical mechanism appears to be much smaller than the run time associated with CMC for a similar set-up. Further investigation is required to refine this initial conclusion. These results open new opportunities towards CSE simulations that involve fuel blends and more complex operating conditions for example with spray and multi-stream inlets with non-uniform compositions for which accurate chemistry tabulations are difficult to generate. [ABSTRACT FROM AUTHOR]

In the analysis of electroencephalography (EEG), entropy can be used to quantify the rate of generation of new information. Entropy has long been known to suffer from variance that arises from its calculation. From a sensor's perspective, calculation of entropy from a period of EEG recording can be treated as physical measurement, which suffers from measurement noise. We showed the feasibility of using Kalman filtering to reduce the variance of entropy for simulated signals as well as real-world EEG recordings. In addition, we also manifested that Kalman filtering was less time-consuming than moving average, and had better performance than moving average and exponentially weighted moving average. In conclusion, we have treated entropy as a physical measure and successfully applied the conventional Kalman filtering with fixed hyperparameters. Kalman filtering is expected to be used to reduce measurement noise when continuous entropy estimation (for example anaesthesia monitoring) is essential with high accuracy and low time-consumption. [ABSTRACT FROM AUTHOR]

To explore the association between fluoride exposure and depression / anxiety in adults, the 1,169 participants were recruited. The demographic information of participants was obtained through questionnaire survey and physical measurements. Morning urine samples were collected, and urinary fluoride (UF) level was determined. Changes in depression and anxiety levels were evaluated using the Patient Health Questionnaire-2 and General Anxiety Disorder-2 scales. The association between psychiatric disorders and UF levels was analyzed. In the total population, the prevalence of depression and anxiety were 3.17% and 4.19%, respectively. These results showed no significant association between depression / anxiety scale scores and UF levels. Logistic regression suggested no significant association between depression / anxiety levels, and UF levels, but there was an interaction between UF and income on depression. Our findings highlighted the interaction between fluoride exposure and monthly income, which may affect depression in adults. [ABSTRACT FROM AUTHOR]

This narrative review examines the interplay among body image perceptions, social media influence, physical measurements, and their impact on psychological well-being, focusing on the roles of cultural and gender differences and the need to understand the research methodologies employed in this field. In the age of digital proliferation, platforms like Instagram and Facebook have reshaped body image concerns, often leading to increased dissatisfaction and psychological distress due to constant exposure to idealized images and a culture of social comparison. Physical attributes such as weight, height, and BMI are scrutinized under societal standards of health and attractiveness, contributing to a spectrum of mental health issues including low self-esteem, depression, and eating disorders. This examination reveals how cultural norms and gender expectations further complicate body image perceptions, affecting individuals differently based on societal and personal ideals. It synthesizes current research and types of methods to illuminate how these factors together influence mental health and self-esteem, advocating for comprehensive interventions and policy measures aimed at mitigating body dissatisfaction and promoting a healthier, more inclusive understanding of body image. By delving into the complexities of body image satisfaction and its psychological implications, this review highlights the necessity of addressing these concerns within public health and social policy frameworks, underscoring the importance of a multifaceted approach to enhance individual and societal well-being. [ABSTRACT FROM AUTHOR]

Objectives: Growth and developmental studies have been a prominent theme in bioarchaeology. These works traditionally focus on metric measurements of long bone length and age‐at‐death or cross‐sectional geometric studies with the use of computed tomography scans for questions on growth and mobility. However, teasing apart aspects of size and shape have been difficult due to the cylindrical nature of immature long bones. This research investigates the methodological use of surface geometries from linear measurements and geometric morphometric methods (GMM) to answer questions on mobility and allometry during childhood. Materials and Methods: Left femora were selected from 42 individuals ranging from fetal to 12 years of age from medieval St Gregory's Priory, Canterbury, UK. Femora were digitized with structured‐light‐scanning for auto3dgm analysis and measurements were obtained from physical caliper measurements. Individuals were put into age groups based on biomechanical milestones during this age range. Results: Ratio and GMM confirm hypotheses of allometry and biomechanical milestones. Geometric morphometrics, however, detects more subtle differences in mobility at each age group. Discussion: The findings of this preliminary study support the potential use of GMM of immature femora, while indicating that the extent in range of mobility that can occur varies at different biological milestones. [ABSTRACT FROM AUTHOR]

Physical properties of mantle minerals are essential for comprehensive geodynamic modeling. High-pressure experiments allow measurements of physical properties but fundamental insights into their evolution with pressure are often experimentally inaccessible. Here we report the first in situ experimental determination of the optical refractive index, its wavelength-dispersion, and optical absorption coefficient of ferropericlase up to ~140 GPa at room temperature. All these properties change gradually in dominantly high-spin (below ~50 GPa) and low-spin (above ~80 GPa) ferropericlase. However, in the mixed-spin state (i.e., significant presence of both high- and low-spin iron), the index dispersion and the absorption coefficient decrease by a factor of three and ~30%, respectively. These anomalies suggest that charge transport by small polaron is reduced in mixed-spin ferropericlase, providing fundamental insights into the factor-of-three lower electrical conductivity of ferropericlase at ~50–70 GPa. [ABSTRACT FROM AUTHOR]

IEEE 802.15.4-based industrial wireless sensor-actuator networks (WSANs) have been widely deployed to connect sensors, actuators, and controllers in industrial facilities. Configuring an industrial WSAN to meet the application-specified quality of service (QoS) requirements is a complex process, which involves theoretical computation, simulation, and field testing, among other tasks. Since industrial wireless networks become increasingly hierarchical, heterogeneous, and complex, many research efforts have been made to apply wireless simulations and advanced machine learning techniques for network configuration. Unfortunately, our study shows that the network configuration model generated by the state-of-the-art method decays quickly over time. To address this issue, we develop a MEta-learning based Runtime Adaptation (MERA) method that efficiently adapts network configuration models for industrial WSANs at runtime. Under MERA, the parameters of the network configuration model are explicitly trained such that a small number of optimization steps with only a few new measurements will produce good generalization performance after the network condition changes. We also develop a data sampling method to reduce the measurements required by MERA at runtime without sacrificing its performance. Experimental results show that MERA achieves higher prediction accuracy with less physical measurements, less computation time, and longer adaptation intervals compared to a state-of-the-art baseline. [ABSTRACT FROM AUTHOR]

Daphnia cucullata is one of the most abundant zooplankton species, found in 85 percent of freshwater and as a model aquatic organism it was chosen from this study. That is why this zooplankton species was chosen. The plankton samples were collected from Keban Reservoir from 2020-2023 with a standard plankton net (55-µm mesh size) at the designated station, Plankton samples were stored in 4% formaldehyde solution. Some water quality parameters were determined by making instant physical measurements with a YSI (EXO 2) model device. Water temperature, pH, electrical conductivity, dissolved oxygen, turbidity (Secchi Disk Depth) and Chlorophyll a were measured. In this study, the fouryear body changes of D. cucullata in August from 2020 to 2023 were monitored. During four years of progressive eutrophication in Keban Reservoir, we found that among the five morphological parameters analyzed in D. cucullata length of head, carapace length, length of tail spine, body length, width of carapace had a tendency to decrease. [ABSTRACT FROM AUTHOR]

Including soil health and physical measurements with traditional soil fertility measurements has the potential to improve corn (Zea mays L.) P fertilizer recommendations. The objectives for this study were to (1) evaluate the accuracy of current South Dakota corn P recommendations in predicting yield increases and (2) determine if the predictability of yield response to P fertilization improves by including selected soil biological, physical, and chemical measurements. This project was conducted in central and eastern South Dakota from 2019 to 2022 at 117 experimental sites that varied in management, landform, and soil type. A treatment of 48.9 kg P2O5‐P ha−1 was compared to a control with no P fertilizer. Soil samples (0–15 cm) collected before fertilization were analyzed for selected soil physical, chemical, and biological parameters. Analysis suggested that the current critical P value of 16 mg Olsen‐P kg−1 was still accurate as it was still within the 68% confidence interval for the linear (12–19 mg kg−1) and quadratic plateau (16–26 mg kg−1) models. Using the critical value of 16 mg Olsen‐P kg−1, we correctly predicted P responsiveness 70% of the time. The accuracy of predicting P responsiveness was not further improved by considering selected enzymes, permanganate oxidizable C, soil respiration, total C, or total N, but was improved by considering pH, soil organic matter, and apparent cation exchange capacity. Therefore, the use of typical soil fertility measurements without soil physical and biological measurements is currently the best option for predicting the responsiveness of corn to P fertilization in South Dakota. Core Ideas: South Dakota's corn Olsen soil test phosphorus (STP) critical value should remain at 16 mg kg−1.Below 16 mg kg−1 STP, corn yields increased 10% at 78% of the sites with P application.P response predictions were not improved by considering biological and physical indicators.Using STP in making P response predictions in South Dakota remains the best method. [ABSTRACT FROM AUTHOR]

This research utilised an open-sourced smoothed particle hydrodynamics (SPH) tool to model and predict the change in wave-induced forces and motions of a free-floating bergy bits approaching a fixed structure in regular waves. Simulation parameters, including particle resolution, fluid viscosity, initial wave condition and boundary treatments, are varied, and their effect on the load imparted to the bergy bit and the structure are investigated. The predicted motions are compared with previously published physical measurements for corresponding scenarios. Both predictions and measurements showed that, in regular waves, the surge motion slowed as the bergy bit approached the structure, and the heave motion increased. For wave loading on bergy bits, the agreement with the experimental data for the root mean square (RMS) force was within 2%. The pressure and velocity fields of the wave–structure–bergy bit interactions are discussed in light of the SPH predictions. This work confirms that the SPH model can accurately capture viscosity–dominated interactions, hydrodynamic damping, and eccentric impact like phenomena and predict both the impact and hydrodynamic loads due to a bergy bit drifting in waves towards a fixed offshore structure. [ABSTRACT FROM AUTHOR]

The primary objective of this study was to investigate the correlations between instrument measurements and sensory attributes of thickened liquids. For this purpose, a series of thickened liquids was prepared using different thickening agent contents from different sources, which were evaluated by sensory analysis for sensory attributes and by instrument measurements for specific physical properties. The texture attributes (hardness, ease of swallowing, and coating (oral cavity, residual feeling in the throat)) of 12 thickened liquid samples were investigated by sensory evaluation. The investigators were 10 panelists trained in evaluating sensory attributes. The line spread test (LST) and the short back extrusion (SBE) method were used for the instrumental analysis. The correlation coefficient between physical properties and each sensory evaluation value was also determined. The results showed that the apparent viscosity from viscosity measurements was highly correlated with each sensory attribute. As thickened liquid is a non-Newtonian fluid, the apparent viscosity was dependent on the shear rate. Hence, the instrumental texture perception of sol (thickened liquid) based on the oral cavity condition could be used to predict human texture perception based on the shear rate, which was obtained from the apparent viscosity similar to gel (strawberry jam). These results indicate that the SBE method is better than the LST for measuring the texture attributes of thickened liquids. [ABSTRACT FROM AUTHOR]

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The accessibility of public open spaces (POS) is assessed by comparing the characteristics of these spaces with the population characteristics across various urban units. Known as "equity mapping" of POS, this method identifies and addresses spatial inequities and environmental justice issues related to POS accessibility. However, research in this area has advanced further in countries with data availability at small spatial scales (e.g. census tracts), enabling the measurement of accessibility within walking distances. To address the challenges of conducting research in data-limited contexts, this case study in Izmir (Türkiye) investigates which spatial analyses can facilitate the development of a comprehensive equity mapping of POS accessibility. Türkiye has demographic data available at the neighbourhood level, including age, gender, and education, but lacks data on income, race/ethnicity, and other characteristics commonly used in mainstream research. This paper assumes that children, the elderly, and low-education groups (a proxy for income level) have a greater need for POS. It explores three forms of overlay analyses: feature-based, raster-based, and fishnet-based. Additionally, it examines the metropolitan area and its sub-regions as terrains with different POS accessibility. The results highlight the Centre as having the weakest POS accessibility in neighbourhoods with high child ratios and low education levels. The fishnet-based density analysis offers a finer lens for identifying the locations of priority areas for POS provisioning, even within neighbourhoods. HIGHLIGHTS: For improving public open space (POS) accessibility, GIS-based measurements of physical and social data can determine priority areas in the city POS accessibility measurements in mainstream research use certain data and spatial units unavailable in data-limited countries In data-limited countries, the grid-based density analysis can provide more accuracy about priority areas for POS planning Taking the city with sub-regions of different POS accessibility helps with determining priority areas Izmir's central city and neighbourhoods with high child ratios and low education levels have the weakest POS accessibility [ABSTRACT FROM AUTHOR]

In this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model have been used. The task is to independently predict characteristic parameters of a buried object of diverse radii allocated at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable data structures (raw B-scans, extracted features, consecutive A-scans) with respect to computational cost and accuracy of surrogates. The usage of raw B-scan data and the applications for processing steps on B-scan profiles in the context of object characterization incur high computational cost so it can be a challenging issue. The proposed surrogate model referred to as the deep regression network (DRN) is utilized for time frequency spectrogram (TFS) of consecutive A-scans. DRN is developed with the main aim being computationally efficient (about 13 times acceleration) compared to conventional network models using B-scan images (2D data). DRN with TFS is favorably benchmarked to the state-of-the-art regression techniques. The experimental results obtained for the proposed model and second-best model, CNN-1D show mean absolute and relative error rates of 3.6 mm, 11.8 mm and 4.7%, 11.6% respectively. For the sake of supplementary verification under realistic scenarios, it is also applied for scenarios involving noisy data. Furthermore, the proposed surrogate modeling approach is validated using measurement data, which is indicative of suitability of the approach to handle physical measurements as data sources. [ABSTRACT FROM AUTHOR]

Background: The morphometric study of the Algerian dromedary population, specifically the Reguibi breed (Camelus dromedarius), involves analyzing various physical measurements and characteristics of these camels. Morphometric studies aim to understand the phenotypic diversity within a population, which can provide insights into their adaptation, genetic variability and potential for selective breeding or conservation efforts. Methods: This study used 60 live dromedaries from the Tindouf slaughterhouse in Algeria's extreme southwest. The animals, 30 males and 30 females, were adults over the age of five years old who grazed in Tindouf's southwestern regions. After four measurements, the substernal void index and live weight were calculated. Result: The mean live weights for males were 507.9 kg±97.3 kg and 445.6 kg±63 kg for females. The average withers height was 1.94±0.10 m for males and 1.84±0.10 m for females. The findings were compared to previous studies on Sahraoui, Targui and Steppe Camels. To the best of our knowledge, this is the first study of the Reguibi population in this region. [ABSTRACT FROM AUTHOR]

Bio-optical and physical measurements were collected in the Mississippi Sound (Northern Gulf of Mexico) during the spring of 2018 as part of the Integrated Coastal Bio-Optical Dynamics project. The goal was to examine the impact of atmospheric and tidal fronts on fine-scale physical and bio-optical property distributions in a shallow, dynamic, coastal environment. During a 25-day experiment, eight moorings were deployed in the vicinity of a frontal zone. For a one-week period in the middle of the mooring deployment, focused ship sampling was conducted with aircraft and unmanned aerial vehicle overflights, acquiring hyperspectral optical and thermal data. The personnel in the aircraft located visible color fronts indicating the convergence of two water masses and directed the ship to the front. Dye releases were performed on opposite sides of a front, and coincident aircraft and unmanned aerial vehicle overflights were collected to facilitate visualization of advection/mixing/dispersion processes. Radiometric calibration of the optical hyperspectral sensor was performed. Empirical Line Calibration was also performed to atmospherically correct the aircraft imagery using in situ remote sensing reflectance measurements as calibration sources. Bio-optical properties were subsequently derived from the atmospherically corrected aircraft and unmanned aerial vehicle imagery using the Naval Research Laboratory Automated Processing System. [ABSTRACT FROM AUTHOR]

Pavement roughness has long been linked to both vehicle fuel efficiency and pavement structural degradation. Perceptions of pavement roughness, however, may vary among users of different sociodemographic features and therefore potentially impact the allocation of resources for highway maintenance and rehabilitation when equity is considered. It is necessary to investigate the major factors that influence the user perception of pavement roughness. Considering the complexity in structure and relationship of field data, this study applied three state-of-the-art machine learning and statistical methods, including a classification tree, a random-parameter ordered-probit model with a random effect (Model 1), and a correlated random-parameter ordered-probit model (Model 2), to the analysis of user perceived roughness. Data were collected from a prior study that conducted in-vehicle tests involving individual user, pavement, and vehicle. The analysis identified more key factors influencing roughness ranking than previous research and accounted for the heterogeneity in individuals and interactions among random parameters. The results indicate that, whereas physical measurements of pavement roughness (e.g., International Roughness Index), visible distresses such as patches and faulting, and joints provided a strong indication of user roughness ranking, other factors (i.e., particular regularly used route, participants' age, income, and gender, number of household infants, and interior vehicle noise levels) were also statistically significant. Two-way group random effects were statistically significant in the data, which should be accounted for in future studies. Results from this study fill an important gap between making accurate prediction and uncovering underlying causality in research of physical infrastructure measurement with user perceptions of infrastructure conditions. [ABSTRACT FROM AUTHOR]

The heat capacity of yttrium(III) bromide (YBr3) in the temperature range from 2 K to 300 K has been determined using a Physical Property Measurement System (PPMS). From these data the absolute entropy of the compound at 298.15 K has been derived. [ABSTRACT FROM AUTHOR]

Conventional sensors can detect the various physical and chemical changes that occur during deformation and the states of materials with a high accuracy. However, almost all existing sensors are bulky and stiff, making them highly susceptible to failure when used in large deformation-compliant structures. By contrast, despite their relatively-low resolution and accuracy, the demand for flexible and stretchable sensors used in detecting human motion and vital signs has drastically increased. There are several types of stretchable sensors that contain functional materials such as carbon nanotubes (CNTs). These stretchable sensors have different working principles and applications based on the attributes of their core components. Several electrical signals are used in the measurement of the different physical parameters such as the electrical resistance and capacitance. Triboelectric nanogeneration or voltage signals that can be identified under contact or impact loading conditions are employed in some measurement methods. Additionally, an array of microstructures with a special shape that is directly related to movement and deformation detection, as well as conductive nano-particles that are elaborately aligned along a certain direction for specific sensor applications, are used in the other methods. In this study, a review of the recently-developed high-performance stretchable sensors made from functional materials using new sensing mechanisms for wearable robot applications is provided. [ABSTRACT FROM AUTHOR]

In this paper, we show that the Dirac delta is a useful technical tool in modelling signals but hard to think about it as a physical signal itself. This thesis is supported here by an example coming from the field of measuring physical quantities and measurement theory. [ABSTRACT FROM AUTHOR]

The heat capacity of yttrium(III) bromide (YBr3) in the temperature range from 2 K to 300 K has been determined using a Physical Property Measurement System (PPMS). From these data the absolute entropy of the compound at 298.15 K has been derived. [ABSTRACT FROM AUTHOR]

Purpose: University students' lecture theatre concentration levels are significantly related to indoor environmental quality (IEQ). The purpose of this study is to investigate the relationship between indoor environmental quality (IEQ) and the self-reported concentration levels of university students during the winter at University College London (UCL), UK. Design/methodology/approach: A questionnaire survey and physical measurements were used to assess the IEQ factors affecting students' concentration levels. Findings: The lecture theatre design factor was the most significant factor influencing students' concentration levels, and the facility environment was more important than the thermal environment, indoor air quality, and acoustic environment in influencing students' concentration levels in this winter investigation at UCL, UK. Additionally, students prefer a colder thermal environment. The concentration level of students was positively correlated with the indoor air quality and negatively correlated with the acoustic environment. Practical implications: Based on model application, this research could provide lecture theatre IEQ design. This research additionally provides an acceptable indoor thermal environment temperature range based on a large sample, which can be used to calibrate a student performance benchmark. Originality/value: As this study evaluates the IEQ factors that influence the concentration levels of university students, interior designers and engineers should consider the rational layout of these factors. Therefore, this study may provide a reference for the interior environmental design of lecture theatres in educational buildings. [ABSTRACT FROM AUTHOR]

This study explored six Oyaki dumpling variants, different heating methods and expansion agents, through bubble observation, sensory evaluations (addressing hardness, crispness, fluffiness, and chewiness), and previously reported physical measurements. Oyaki with bulking agents showed large bubbles, particularly in steamed and fried versions, whereas those without bulking agent had finer bubbles and a lower bubble ratio. The characteristics of these bubbles were closely linked to sensory perceptions and physical properties, with a notable correlation between bubble proportion and both fluffiness (positive) and hardness (negative). Baked (ash-baked) Oyaki ranked as the hardest and crunchiest, while steaming Oyaki, with added dilatants, was identified as the fluffiest. Furthermore, both baked and steamed forms had a high level of chewiness. A questionnaire on texture perception highlighted distinct expressions for each Oyaki type. Each Oyaki type was further analyzed through principal component analysis to classify Oyaki into categories based on hardness and moisture. The findings underscore the significant impact of heating methods (steaming, grilling, deep frying) and bulking agents on Oyaki texture. This insight into Oyaki's textural characteristics could guide manufacturers in selecting appropriate heating techniques and bulking agents to achieve specific textures, and influence decisions on production methods. [ABSTRACT FROM AUTHOR]

Nanotechnology is a swiftly expanding domain with significant applications across various disciplines. Platinum nanoparticles (PtNPs) represent a focal point in scientific investigations, drawing considerable research attention due to their potential applicability in diverse fields. Their inherent non-toxicity and remarkable stability confer distinctive plasmonic properties, rendering them particularly valuable in the realm of bioengineering. This review aims to comprehensively assess the ongoing global research landscape pertaining to the synthesis, mimicry, and utilization of PtNPs. The review covers the biosynthesis, as well as chemical and physical synthesis of PtNPs, incorporating both in-vivo and in-vitro experimental analyses. After their synthesis, a range of nanometrological characterization techniques is explored as analytical tools to facilitate the measurement of physical and chemical properties of nanoparticles. Additionally, the review delves into recent advancements in the functionalization of PtNPs for biomedical applications, encompassing areas such as nanomedicine, combination therapy, cancer treatment, and antibacterial properties. [ABSTRACT FROM AUTHOR]

Living organisms have the ability to self-shape into complex structures appropriate for their function. The genetic and molecular mechanisms that enable cells to do this have been extensively studied in several model and non-model organisms. In contrast, the physical mechanisms that shape cells and tissues have only recently started to emerge, in part thanks to new quantitative in vivo measurements of the physical quantities guiding morphogenesis. These data, combined with indirect inferences of physical characteristics, are starting to reveal similarities in the physical mechanisms underlying morphogenesis across different organisms. Here, we review how physics contributes to shape cells and tissues in a simple, yet ubiquitous, morphogenetic transformation: elongation. Drawing from observed similarities across species, we propose the existence of conserved physical mechanisms of morphogenesis. [ABSTRACT FROM AUTHOR]

Objective: The search for other indicators to assess the weight status of individuals is important as it may provide more accurate information and assist in personalized medicine.This work is aimed to develop a machine learning predictions of weigh status derived from bioimpedance measurements and other physical parameters of healthy infant juvenile cohort from the Southern Cuba Region, Santiago de Cuba. Methods: The volunteers were selected between 2002 and 2008, ranging in age between 2 and 18 years old. In total, 393 female and male infant and juvenile individuals are studied. The bioimpedance parameters are obtained by measuring standard tetrapolar whole-body configuration. A classification model are performed, followed by a prediction of other bioparameters influencing the weight status. Results: The results obtained from the classification model indicate that fat-free mass, reactance, and corrected resistance primarily influence the weight status of the studied population. Specifically, the regression model demonstrates that other bioparameters derived from impedance measurements can be highly accurate in estimating weight status. Conclusion: The classification and regression predictive models developed in this work are of the great importance for accessing to the weigh status with high accuracy of younger individuals at the Oncological Hospital in Santiago de Cuba, Cuba. [ABSTRACT FROM AUTHOR]

Background: In an individual, the development and severity of Non-Communicable Diseases (NCDs) are determined by the presence or absence of clustering of NCD risk factors in them. We aimed to determine the prevalence and the factors associated with clustering of risk factors of NCDs in the district of Puducherry in India. Methodology: We conducted a community-based cross-sectional survey among the adult population (18–69 years) of Puducherry district (N = 1114) between February 2019 and February 2020. Ten risk factors of NCDs (behavioral, physical measurements and biochemical) were assessed. Individuals having ≥ 3 risk factors were regarded as having clustering of risk factors. Categorical variables are summarized using proportions (95% CI). Adjusted prevalence ratio was estimated using weighted forward stepwise generalized linear modelling. Results: Clustering of NCD risk factors was present in majority (95.2%, 95% CI: 93.8–96.3) of the population. The presence of clustering was significantly higher among women (97.1%, 95% CI: 95.9–98.3) and the urban population (97.2%, 95% CI: 96.1–98.3). The risk factors that primarily drove the high prevalence of clustering were raised salt intake and inadequate intake for fruits and vegetables in nine out of 10 people in the district. Nearly 1 in 10 (13.3%, 95% CI: 11.3–15.3), 1 in 5 (21.5%, 95% CI: 19.1–23.8) and 1 in 4 (26.8%, 95% CI: 24.1–29.4) participants had three, four and five risk factors, respectively. Conclusion: We highlight the urgent need for population-based health promotion interventions in the district of Puducherry targeting the highly prevalent NCD risk factors, especially among the women and urban populations. [ABSTRACT FROM AUTHOR]

We prepared 15 novel series of 1,3,4-thiadiazole containing benzo[d]imidazole compounds for the development of potential antimicrobial agents (6a–o). IR, 1H NMR, 13C NMR, and mass spectrometry were used to identify the bioactive structures of these compounds. Using the Broth Dilution method, the synthesized compounds were examined for antimicrobial activity against a variety of bacterial and fungal strains. Compounds 6j showed potency against bacterial strain P. aeruginosa, E. coli, and antifungal activity against A. clavatus at MIC values of 12.5 µg/mL, 50 µg/mL, and 100 µg/mL respectively. 6c, and 6e indicated antibacterial activity against P. aeruginosa at MIC values 62.5, and 50 µg/mL and antifungal activity against C. albicans MIC 250, 100, µg/mL respectively. Density (ρ), ultrasonic velocity (U), and viscosity (η) have been measured in a binary liquid mixture containing 1,3,4-thiadiazole and benzo[d]imidazole over the entire molality range at temperatures T = (303.15,308.15,313.15 and 318.15) K and different solvent DMSO and DMF. The experimentally obtained data have been used to determine the thermo-acoustical parameters adiabatic compressibility (κs), intermolecular free length (Lf), acoustical impedance (Z), and internal pressure (π). It is observed that in DMSO solutions, solute–solute interactions exist whereas solvent–solute interactions are predominant in DMF systems. [ABSTRACT FROM AUTHOR]

In distribution systems, the state estimation task is very complicated due to the problems arising from the unbalanced operation and network configuration changes. Additionally, the convergence process of state estimation gets affected by the loss of physical measurements due to meter failure, communication failure, and large communication time delays. To address the issue of loss of measurement data, a new deep learning approach, namely a convolutional generative adversarial imputed network (CGAIN) with modified loss functions, is proposed. A branch current-distribution system state estimation (BC-DSSE) with different percentages of missing measurement data has been implemented and studied. Furthermore, the analysis has been carried out for different types of uncertainties involving several kinds of measurement devices and pseudo-measurements for different classes of consumer loads. Also, the effect of imputed data on state estimation accuracy is tested at different operating conditions of load. The imputation performance of the CGAIN model is tested by comparing it with statistical methods, and ML/DL approaches. The benefits of the proposed model are validated by Monte Carlo simulations on the modified IEEE 13-node and IEEE 37-node unbalanced distribution test systems. Simulation results show that the proposed model can effectively impute the missed data under any operating condition. Further, the robustness of the algorithm is checked with the largest normalized residual (LNR) test for minimizing the effect of bad data. [ABSTRACT FROM AUTHOR]

The study presents an innovative approach to designing a Circular Microstrip Patch Antenna capable of covering a broad range of frequency bands. The physical measurements of the antenna are 34x22 x 1.57 mm³. Rogers RT5880 (Lossy) substrate has been chosen to build the antenna, which has a dielectric constant (εr) of 2.2. The antenna's radiating patch layer and the ground plane layer has been structured from copper, each with a thikness of 0.035 mm. The resonance at five distinct frequencies: 5.2 GHz, 6.628 GHz, 9.098 GHz, 12.036 GHz, and 13.076 GHz is the key element of this antenna. These frequencies cover a broad range of applications including WLAN, C-band, X-band, and Ku-band. Simulations has been applied using the CST Software version 2021 to validate the antenna performance. The adaptability of the antenna design, coupled with its successful validation, makes it suitable for a broad range of wireless applications across different frequency bands. This highlights their effect and applicability across a variety of technological fields. [ABSTRACT FROM AUTHOR]

This research focuses on the evaluation of a heritage office building in the town of Kenadsa in the Southwest of Algeria (a famous oasis in the arid regions of the country). Emphasizing user's perception as a metric key for performance assessment, this study aims to investigate the users' perception and behaviors of a heritage office building on an oasis settlement. The research was conducted in 2023, and employing a multidimensional approach, both quantitative and qualitative methodologies, along with agent-based modeling, were integrated. One qualitative methodology is based on a series of field surveys and the other quantitative methodology relies on in situ measurements of the physical dimensions of the environment. The quantitative aspect involves an agent-based modeling framework, simulating user interactions by incorporating physical dimensions, spatial layout, historical context, and user behavior. The main findings of this study, examining perceptions and behaviors under varying luminous and thermal environments, show that this integrated approach provides insights into user satisfaction, spatial utilization, and the identification of user behaviors and productivity in each office. [ABSTRACT FROM AUTHOR]

State‐of‐the‐art conformal array pattern synthesis techniques typically suffer from a significant computational burden. This article builds upon the auxiliary array pattern synthesis technique, allowing the technique to work on elliptical contours. This deterministic method is both computationally efficient and capable of handling complex design cases with additional design constraints. In order to highlight the versatility and applicability, the method has been applied to an elliptical arc array comprised of Rampart antennas and an elliptical ring array using dipole elements. The results have been validated through full‐wave electromagnetic simulations, as well as physical measurements. Both arrays presented show good agreement with the proposed synthesis technique. Highlighting the ability to satisfy additional design constraints, such as enforcing a minimal element spacing or having a controlled beamformer‐network complexity. Plain Language Summary: This work presents a fast method to calculate the placement and excitation of antennas along an elliptical contour in order to achieve the desired radiation characteristics. The technique has been validated for an array featuring complex antenna elements and for an elliptical ring array. Key Points: The Auxiliary Array Pattern (AAP) formulation offers a deterministic and, thus, an inherently faster conformal array synthesis methodThe AAP formulation can be extended to support Elliptical contoursElliptical arrays with, for instance, Rampart or dipole elements can be quickly designed using the proposed synthesis method [ABSTRACT FROM AUTHOR]

Urban green spaces are among the resources that provide many social and physical effects to decrease the adverse effects of urbanization. Their inappropriate locations can make them less accessible and, therefore, less sustainable or underutilized. This study presents the citywide and local characteristics of the size and morphological distribution of urban green spaces in Penang Island, Malaysia, using the space syntax method. Space syntax analyses were used to identify if there is a rational pattern for urban green spaces' size and accessibility and to determine the spatial distribution of needs and accessibility. To this aim, physical measurements of 24 parks and green recreational centers were calculated, followed by an axial mapping of the study area which was conducted to perform space syntax analysis. The results first showed that the locations of the green spaces were not equitably distributed, and larger green spaces were established in areas with less accessibility. Second, based on space syntax data, we evaluated the flood risk, land surface temperature, and population density maps. Finally, we proposed potential sites for future green spaces. This paper demonstrates new insights into the consideration for spatial priorities to reshape future urban green space planning in delivering more sustainable greenery. [ABSTRACT FROM AUTHOR]