Regression Equation Research Articles

Prediction of 1cm dose-equivalent rate on the day after administration of 177Lu-DOTATATE from 111In-somatostatine receptor scintigraphy prior to treatment.

When patients administered 177Lu-DOTATATE are released or discharged from rooms where radiopharmaceuticals are used, the time required for release or discharge varies across patients. This study investigated whether the amount of radioactivity accumulated on 111In-somatostatine receptor scintigraphy (111In-SRS) performed prior to treatment can predict the 1cm dose-equivalent rate at a distance of 1m from the patient on the day after 177Lu-DOTATATE administration. Whole-body planar 111In-SRS images were acquired for 21 patients. Pixel values within whole-body and abdominal (35 × 25cm) regions of interest (ROIs) were converted to radioactivity dose (MBq). The 1cm dose-equivalent rate (µSv/h) at a distance of 1m from the patient 18.3 ± 0.5h after administration of 177Lu-DOTATATE was measured using an ionization survey meter. The following relationships were observed between the radioactivity on 111In-SRS and the 1cm dose-equivalent rate on the day after administration of 177Lu-DOTATATE: whole-body ROI: y = 0.16x + 5.01 (r = 0.56, p = 0.009), abdominal ROI: y = 0.27x + 5.13 (r = 0.63, p = 0.002). The regression equations indicate that patients cannot be released or discharged from the radiopharmaceutical room the day after 177Lu-DOTATATE administration if the whole-body and abdominal ROI doses are greater than 81 and 48MBq, respectively, on 111In-SRS. The amount of radioactivity accumulated on 111In-SRS may be a predictor of release criteria for patients receiving 177Lu-DOTATATE.

Non-financial reporting—A key element in assessing sustainable corporation performance

In the modern economy, non-financial reporting has become an essential tool for evaluating the social performance of companies. This article explores the importance of non-financial reporting as a central element in assessing sustainable performance, focusing on analyzing sustainability reports published by 20 companies listed on the Bucharest Stock Exchange (BVB). The study examines how these companies approach environmental, social, and governance (ESG) aspects in their reports and what is the relationship between these aspects and financial reporting indicators. Through the statistical analysis of the non-financial reports published by companies participating in the study with the help of the Pearson coefficient and the regression equations, the correlation between the financial and non-financial indicators is determined in order to validate the research hypotheses. The results indicate increased attention to transparency and social responsibility, highlighting the correlation between sound reporting practices and cooperative performance by combining social and environmental aspects with financial information. The research also highlights the challenges encountered in the reporting process and the level of compliance with international sustainability standards.

Predictors of self-care behaviors in hypertensive patients based on the protection motivation theory

IntroductionGlobally, hypertension is a significant public health concern and a leading cause of premature death. Since this disease is incurable, it is necessary to promote patients’ self-care behaviors to control it. The goal of this research was to identify the elements that influence self-care actions in individuals with hypertension, utilizing the Protection Motivation Theory (PMT) framework.MethodsA study was carried out in Omidiyeh, located in southern Iran, using a cross-sectional design, involving 397 adults with hypertension (198 females and 199 males) who were selected from comprehensive health centers using a stratified random sampling technique. Data was gathered through a demographic data collection form and a questionnaire created by the researcher, which was based on the PMT. Data were assessed utilizing SPSS 25 and AMOS 24 software, and various statistical tests including one-way ANOVA, Pearson correlation, multiple regression, independent t-test, and structural equation modeling were conducted.FindingsThe variables of intrinsic reward (r = 0.182), extrinsic reward (r = 0.288), and response cost (r = 0.126) showed a significant negative correlation with self-care behaviors. On the other hand, perceived susceptibility (r = 0.212), perceived severity (r = 0.110), self-efficacy (r = 0.555), and response efficacy (r = 0.424) demonstrated a significant positive correlation with self-care behaviors. Specifically, self-efficacy and response efficacy were the most powerful predictors of self-care behaviors, respectively.ConclusionThe results showed that several factors can forecast self-care behaviors in patients with hypertension. Researchers are recommended to incorporate PMT in educational interventions and concentrate on self-efficacy and response efficacy constructs.

A study of the impact of ChatGPT self-efficacy on the information seeking behaviors in ChatGPT: the mediating roles of ChatGPT characteristics and utility

PurposeThe purpose of this study was to examine the factors that influence the information seeking behaviors of ChatGPT users. Specifically, we investigated how ChatGPT self-efficacy, ChatGPT characteristics and ChatGPT utility affect the frequency and duration of information seeking via ChatGPT. We also tested the mediating roles of ChatGPT characteristics and utility in the relationship between ChatGPT self-efficacy and information-seeking behaviors.Design/methodology/approachThis study adopts a quantitative approach and collects data from 403 ChatGPT users using an online questionnaire. The data are analyzed using linear regression and structural equation modeling (SEM).FindingsThe linear regression analyses revealed that ChatGPT self-efficacy is positively and significantly related to the information seeking behaviors in ChatGPT. Second, mediation analyses also showed that ChatGPT characteristics and utility significantly mediate the relationship between ChatGPT self-efficacy and information-seeking behaviors in ChatGPT independently and sequentially.Originality/valueThis study is the first to investigate the factors and mechanisms that influence information-seeking behaviors in ChatGPT, a new phenomenon in the media landscape. The findings in this study suggest that ChatGPT self-efficacy acts as an important motivator for information-seeking behaviors in ChatGPT and that ChatGPT characteristics and utility provide information regarding potential mechanisms in the relationship between ChatGPT self-efficacy and information-seeking behaviors in ChatGPT. The study contributes to the literature on information seeking, self-efficacy and generative AI.

Using Bland-Altman plot-based harmonization algorithm to optimize the harmonization for immunoassays.

Harmonization has been recommended by theInternational Organization for Standard (ISO) to achieve equivalent results across invitro diagnostic measurement devices (IVD-MDs). We aim to evaluate the effectiveness of Bland-Altman plot-based harmonization algorithm (BA-BHA) created in this study and compare it with weighted Deming regression-based harmonization algorithm (WD-BHA) proposed in ISO 21151:2020. Eighty patient sera were used as the harmonization reference material (HRM) to develop IVD-MD-specific harmonization algorithms. Another panel of 40 patient sera was used to validate the effectiveness of harmonization algorithms. We compared regression slopes, intercepts, Bland-Altman plot layouts, percent differences, limits of agreement (LoAs), between-method coefficients of variation (CV) before and after harmonization. After harmonization by WD-BHA, acceptable slopes and intercepts between measured values and HRM targets were observed in weighted Deming regression, but not in Passing-Bablok analysis. Mean differences were-5.5 to 5.0 % and differences at specific levels were-33.9 to 23.9 %. LoAs were-64.6 to 74.6 %. Between-method CV was 22.9 % (±12.9 %). However, after harmonization by BA-BHA, both weighted Deming and Passing-Bablok regressions equations presented harmonized results. Mean differences were-0.3 to 0.2 % and differences at specific levels were-1.1 to 1.6 %. LoAs were-23.3 to 23.2 %. Between-method CV was 8.4 % (±4.0 %). The data points were evenly distributed at both sides of the mean in Bland-Altman plots. The inequivalence of test results between different methods can be improved but unacceptable analytical differences at specific levels may be hidden in terms of an acceptable slope and intercept on WD-BHA. The new protocol BA-BHA may be a viable alternative to optimize the harmonization for immunoassays.

Enhancing Rwanda's Global Competitiveness: Evaluating the Impact of 'Made in Rwanda' Policies on Local Manufacturing Growth and Innovation

The study aimed at Enhancing Rwanda's Global Competitiveness: Evaluating the Impact of 'Made in Rwanda' Policies on Local Manufacturing Growth and Innovation. The specific objectives of the study were: to establish the impact of ‘Made in Rwanda’ policies on the growth of local manufacturers in Kenya sectors between 2017 and 2023; and to examine the extent to which ‘Made in Rwanda’ policies have improved the competitive advantage of local manufacturers in regional and international markets. Descriptive research, a method of gathering data, was used in this study to address inquiries about the present state of the research participants. The sample size of 246 respondents was proportionally distributed across the different sectors. The main instrument that was used for data collected was a semi-structured questionnaire. Descriptive statistics was used to show trends and inferential statistics was used to anlyse the relation between the various variables with multiple regression analysis crowing the hypothesis testing. Crucially insightful results came from the regression study done to investigate the link between the 'Made in Rwanda' policies and local manufacturers' competitive advantage. Here, the regression equation could be shown as Y=2.5+0.7X1+0.5X2+ε. With an intercept (β0) at 2.5, local manufacturers' competitive advantage is expected to be 2.5 units should both independent variables equal zero. With β1=0.7, the coefficient for Growth 'Made in Rwanda' Policies shows a direct link whereby competitive advantage rises by 0.7 units for every unit increase in growth policies. With p < 0.001, this is statistically significant and indicates rather strong evidence on the favorable impact of growth policy on company competitive advantage. With β2=0.5, the coefficient Competitive Advantage "Made in Rwanda" Policies also shows that, alongside every unit increase in competitive advantage policies, each caused a 0.5 unit increase in competitive advantage of manufacturers. This is statistically significant (p = 0.01) and once more shows to be especially crucial for raising competitiveness. For local producers, the correlated independent variables explain 68 percent of the variance in competitive advantage. All things considered, 'Made in Rwanda' policies have greatly helped the local manufacturer to grow over the past few years. According to the study's findings, strategic actions including policy incentivizing, infrastructure access, and capacity-building initiatives have improved production capability and market positioning. Thanks to these policies, local producers will not only develop but also be more suited to compete against foreign players on their path into regional and worldwide markets. This rightly emphasizes the need of a constant and adequate government support as well as an ongoing assessment of these policies to guarantee they remain relevant and efficient in handling the problems encountered in the manufacturing sector Keywords: 'Made in Rwanda' policies, local manufacturers, competitive advantage, production output, employment growth, export volume, product differentiation, policy incentives, infrastructure, government support programs, trade agreements, and capacity building.

Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach

In the field of construction engineering, the cracking of concrete structures is a common engineering problem, which has a great impact on the overall stability and service life of the engineered structure. During structural repair, crack detection is the most critical step. Automatic detection significantly reduces the engineering cost and human factor error compared with manual detection. However, due to the changeable environment of the project site and different image specifications, using a single algorithm makes it difficult to balance high efficiency and high accuracy. In this study, we designed a combined recognition method including the region growth algorithm and machine learning regression that can achieve a tradeoff between accuracy and efficiency. Firstly, the regression method learns the image features of the dataset and the specific region growth threshold, and the regression function is trained by using the open-source dataset to determine the region growth threshold using the characteristics of the images included in the tests. The region growth algorithm is used to expand the threshold from the seed points of the image to obtain the crack recognition results. The results show that this method improves the accuracy of SSIM by 7% compared with the traditional region growth algorithm, and does not significantly increase the computational cost, with an increase of 0.78 s per photo process. Compared with the deep learning method, the recognition accuracy of SSIM is decreased by 5.96%, but it takes less resources and has high efficiency.

Developing a New Method for the Estimation of Valsartan (VST) in Pharmaceutical Dosage Samples by Using Diazotization and Coupling Reactions Spectrophotometrically

Introduction: A new method for valsartan (VST) estimation in pharmaceutical dosage samples by spectrophotometry was developed. Method: The method was based on the formation of coloured dye by the diazotization reaction of 3-amino-2-naphthol with sodium nitrite in an acidic medium to form diazonium compounds, which were then coupled with VST in a basic medium. Results: The drug sample showed linearity in the range 4.6 - 24.2 μgmL-1, and the λmax was found at 432nm. Sandell’s sensitivity (9.950×10-3), Molar absorbtivity (Ɛ= 4.377×104), regression equa-tion (y= 0.0775x + 0.0041), correlation coefficient (r2= 0.968), detection limit (DL= 0.668) and quantitation limit (QL= 2.024) were evaluated. Conclusion: The percentage recovery of the drug samples was found to be 100%. This method successfully determined VST in Pharmaceutical dosage samples.

Correlation Between Symptom Clusters and Self-Management Among Maintenance Haemodialysis Patients: A Cross-Sectional Study.

The purpose of this study was to explore the relationship between symptom clusters and self-management among maintenance haemodialysis (MHD) patients. MHD patients experience disease progression and multiple symptom burdens that severely impact quality of life, and self-management of symptoms may significantly improve patient-reported outcomes. A cross-sectional study. This cross-sectional descriptive study included 194 patients undergoing MHD. The patients were assessed using the Dialysis Symptom Index (DSI) and the Haemodialysis Self-Management Instrument (HD-SMI). We used descriptive analysis, exploratory factor analysis, Pearson's correlation analysis and linear regression analysis to examine (1) the level of individual self-management, (2) the presence of symptom clusters by symptom severity and (3) the correlation between symptom clusters and self-management behaviours. This study was conducted in accordance with the STROBE checklist. The top five most severe symptoms among the patients were itching, feeling tired or lack of energy, difficulty sleeping, dry mouth and dry skin. We identified five groups of symptoms: (1) poor sleep, (2) neuromuscular, (3) gastrointestinal, (4) skin irritation and (5) psychological. In the present study, MHD patients reported low to moderate levels of self-management behaviours (50.84 ± 10.56), and low self-management ability was correlated with greater severity of the five symptom clusters (p < 0.01). Linear regression analysis revealed that all five symptom clusters were included in the regression equation, explaining 30% of the total variance in self-management skills among MHD patients. Enhanced awareness of symptom clusters and comprehensive symptom management are necessary to improve patients' quality of life. Nursing practices should incorporate comprehensive symptom assessments to help patients develop effective self-management strategies to improve quality of life.

A comprehensive validation of GRA with ant colony optimization for robust optimal design: A case study on the forming process

Sheet metal forming design involves numerous factors and controlling all these parameters to prevent cracks is a major challenge to maintain the quality. Therefore, the careful selection of process parameters is critical for ensuring product longevity. Several researchers employed different techniques for optimal selection of process parameters but consistency among the techniques and validation of results in real time scenarios will play a pivotal role in determining the suitable parameters. Therefore, the current work presents a validation method of Grey Relational Analysis (GRA) results with Ant Colony Optimization (ACO) for the robust optimum design with an illustrative example of forming process. Al 6061 – T6 alloy was chosen as a material for deep drawing process and L27 Orthogonal Array was planned to conduct experiments with four input parameters such as blank thickness, Die and Blank Temperature, Die Speed, Lubrication at three levels each. Punch force and Thickness variation were considered as the output parameters. GRA Technique was implemented to find the best optimal combination and regression equation was developed to predict the nature of objective function. These results were given as an input to ACO, a nature inspired algorithm to search for the optimal solution with in the design space. Sensitivity analysis has also been performed to highlight the effectiveness of the proposed solution in terms of solution quality and computational efficiency. The ACO method, GRA technique and the experimental results are almost similar with a margin of acceptable deviation. The results indicated the robustness of the projected approach in achieving the quality of solution.

Length-weight relationship and condition factor of Nile tilapia (Oreochromis niloticus) fed diets supplemented with guava and star gooseberry leaf extract

Background Nile tilapia (Oreochromis niloticus) is predominant cultured species in aquaculture. However, there is a scarcity of literature regarding relationship between guava and star gooseberry leaf extract and the condition factor. Thus, the present study aims to investigate the effect of guava and star gooseberry leaf extract-supplemented diets on the specific growth rate, length-weight relationship, and condition factor of Nile tilapia. Methods Six hundred and thirty Nile tilapia (8.7±0.4 g) were randomly distributed among twenty-one tanks (30 fish per tank) within a recirculation system. Over a 60-day period, the fish were fed diets supplemented with 5g/Kg and 10g/Kg of guava leaf extract (GLE-5, GLE-10), star gooseberry leaf extract (SGLE-5, SGLE-10), and a mixture of both (MxLE-5, MXLE-10). Subsequently, specific growth rate, length-weight relationship, and condition factor were determined. Results After 60 days, the specific growth rate was significantly higher in all the GLE, SGLE, and MxLE groups compared to the control group. The final lengths and weights differed significantly both in the control group and all the GLE, SGLE, and MxLE groups. The analysis of the regression equation indicated a positive correlation (r = 0.970, 0.977, 0.976, 0.974, 0.974, 0.974, and 0.969) between the length and weight of Nile tilapia in the control group and in all the GLE, SGLE, and MxLE groups. The regression exponent “b” values in all the GLE, SGLE, and MxLE groups were &gt;3, indicating a positive allometric growth pattern in Nile tilapia compared to the control (b=2.866), which exhibited a negative allometry. The final condition factor values did not differ significantly in either the control group or any of the plant extract groups. Conclusions Nile tilapia exhibited positive allometric growth patterns and maintained good health when fed with GLE, SGLE, and MxLE groups. Therefore, these plant extracts demonstrate suitability for commercial Nile tilapia production.

Selection and genetic parameters of productivity of sheep (&lt;i&gt;ovis aries&lt;/i&gt;) of the Trans-Baikal breed of the Khangil type

The study was conducted to investigate the selection and genetic parameters of productivity of fine-wool sheep of the Trans-Baikal breed of the Khangil typein order to increase the efficiency of the selection process. The relationships between the selected traits (live weight, wool yield) and the exterior and constitutional features were determined using the method of correlation and regression analysis. Of the assessed parameters, the greatest variability was observed for body weight (11.9…19.4 %), wool yield (9.9…11.1 %) and latitudinal linear measurements (8.2…12.4 %). According to the constitution indices, rams differed from ewes by greater leg length, better chest development, stronger skeleton, while ewes were characterized by a more stretched, compact and massive body with a better developed back part. Live weight and wool yield of rams were more closely associated with linear measurements than those of ewes. Live weight of both males and females correlated more strongly with chest girth (respectively +0.916, p 0.001 and +0.740, p 0.001), wool yield – with chest depth in rams (+0.737, p 0.001) and hip width in ewes (+0.469, p 0.001). In Trans-Baikal breed of the Khangil type rams, with an increase in the hip width measurement by 1 cm, it is possible to predict an increase in live weight by 5.50 kg (r = 0.839; p 0.001), in ewes with an increase in chest girth by 1 cm – by 1.04 kg (r = 0.740; p 0.001). The analysis of paired regression equations shows that the live weight of Trans-Baikal breed of the Khangil type ewes is largely determined by the linear measurement of the chest girth: in rams – 83.9 %, in ewes – 54.7 %, the influence of other factors accounts for 16.1 and 45.3 %, respectively. At the same time, in the multivariate regression models, 94.3 and 74.7 % of the change in body weight is explained by the effect of a complex of linear measurements, and the remaining share is attributed to the influence of other factors.

Ensemble probability distribution of annual runoff for the past 70 years in two main watersheds of China

ABSTRACT Water resources in China, especially in the major basins of the Songhua and Yangtze Rivers, are characterized by uneven distribution both temporally and spatially, leading to notable challenges in per capita water availability. In this study, we investigate the ensemble probability distribution of annual runoff over the past 70 years in two of China's major watersheds: the Songhua River and the Yangtze River. By dividing each basin into several regions from upstream to downstream, based on annual mean discharge as a proxy for annual runoff, we observed a significant correlation between the annual runoff of the control sections and that of the upstream and downstream regions in these large watersheds. Consequently, this study establishes the probability distribution of annual runoff for each region within the basins, anchored on the design annual runoff of the control sections, using the joint bivariate logarithmic normal distribution of two interrelated random variables. Furthermore, we developed a relationship between the conditional probability distribution and correlation diagram data, and a regression equation correlating regional annual runoff with the watershed control section's runoff. This investigation into the historical patterns of runoff over the past 70 years provides a comprehensive understanding of the dynamics in these critical watersheds.

A new Late Cretaceous metatherian from the Williams Fork Formation, Colorado.

Heleocola piceanus, a new, relatively large metatherian from Upper Cretaceous ('Edmontonian') strata of the Williams Fork Formation in northwestern Colorado is described, based on a recently discovered jaw fragment (MWC 9744), in addition to three isolated teeth initially referred by other studies to Aquiladelphis incus and Glasbius piceanus. Although sharing several morphologic characters with the Lancian genus Glasbius, H. piceanus lower molars are considerably larger than those of Glasbius and differ from the latter in lacking a buccal cingulid, possessing carnassiform notches on the cristid obliqua and entocristid, and bearing an entoconulid on m3. To examine the relationship of Heleocola piceanus to other metatherians, H. piceanus was scored into a previously existing taxon-character matrix. Our phylogenetic analysis recovers H. piceanus as the sister taxon to Glasbius, which is consistent with our morphologic comparisons. H. piceanus represents the oldest member of the Glasbiidae. A regression equation for predicting body mass of dentally conservative metatherians that utilizes the length of m1 estimates the mass of H. piceanus at 855-1170 g, which is comparable in mass to today's muskrat (Ondatra zibethicus) and large relative to other Late Cretaceous pediomyoids. Based upon its molar morphology, specifically the low inflated cusps, low height differential between the trigonid and talonid, and near-bunodont morphology, H. piceanus is interpreted as an omnivore with a plant-dominated diet.

Experimental Study on Direct Shear Behavior of New-to-Old Interface for Recycled Aggregate Concrete with Different Replacement Ratios

The large amount of construction waste produced by the construction industry brings severe natural resource consumption and environmental pollution, elevating the awareness of sustainable development. Recycled aggregate concrete, crushed from construction waste, is recognized as an eco-friendly material and the current optimal solution for the environmental problem. The interface shear failure between substrate recycled coarse aggregate concrete (RAC) and overlay natural aggregate concrete becomes vital for structural safety. In order to study the direct shear performance, a total of 19 specimens were designed to carry out the direct shear test with different replacement ratios, interface types and curing ages. The whole process and failure mode were recorded. The relationships between the shear capacity and deformation, ductility, damage evolution, and energy dissipation were evaluated and discussed. The results demonstrate that the RAC component in the interface was the weak line in the shear plane, accelerating the damage evolution. In the early curing stage, the replacement ratio had a slight influence on the shear properties. Increasing the recycled aggregate replacement ratio from 0 to 100% improved the normalized strength ratio by 8.94% and 14.62%, respectively, for curing ages of 3 days and 7 days. A regression equation was proposed to predict the shear strength, accounting for the curing ages. With the increase in the replacement ratio, the ductility and energy dissipation gradually enhanced.

Targeting Unc5b in macrophages drives atherosclerosis regression and pro-resolving immune cell function

Atherosclerosis results from lipid-driven inflammation of the arterial wall that fails to resolve. Imbalances in macrophage accumulation and function, including diminished migratory capacity and defective efferocytosis, fuel maladaptive inflammation and plaque progression. The neuroimmune guidance cue netrin-1 has dichotomous roles in inflammation partly due to its multiple receptors; in atherosclerosis, netrin-1 promotes macrophage survival and retention via its receptor Unc5b. To minimize the pleiotropic effects of targeting netrin-1, we tested the therapeutic potential of deleting Unc5b in mice with advanced atherosclerosis. We generated Unc5bfl/flCx3cr1creERT2/WT mice, which allowed conditional deletion of Un5b (∆Unc5bMØ) in monocytes and macrophages by tamoxifen injection. After inducing advanced atherosclerosis by hepatic PCSK9 overexpression and western diet feeding for 20 wk, Unc5b was deleted and hypercholesterolemia was normalized to simulate clinical lipid management. Deletion of myeloid Unc5b led to a 40% decrease in atherosclerotic plaque burden and reduced plaque complexity compared to Unc5bfl/flCx3cr1WT/WT littermate controls (CtrlMØ). Consistently, plaque macrophage content was reduced by 50% in ∆Unc5bMØ mice due to reduced plaque Ly6Chi monocyte recruitment and macrophage retention. Compared to CtrlMØ mice, plaques in ∆Unc5bMØ mice had reduced necrotic area and fewer apoptotic cells, which correlated with improved efferocytotic capacity by Unc5b-deficient macrophages in vivo and in vitro. Beneficial changes in macrophage dynamics in the plaque upon Unc5b deletion were accompanied by an increase in atheroprotective T cell populations, including T-regulatory and Th2 cells. Our data identify Unc5b in advanced atherosclerosis as a therapeutic target to induce pro-resolving restructuring of the plaque immune cells and to promote atherosclerosis regression.

Mesoscopic shear evolution characteristics of frozen soil-concrete interface

The mechanical properties of frozen-concrete interfaces affect the stability and durability of engineering structures in cold regions. To investigate these properties, laboratory tests and numerical simulations were conducted to study the mesoscopic evolution of the shear stress-displacement relationship and the shearing process at the interface. The direct shear tests were performed at different environmental temperatures (−2 °C, −5 °C, and −10 °C) and normal stresses (100 kPa, 200 kPa, and 300 kPa) on the frozen soil-concrete interface, and Particle Flow Code (PFC) model of direct shear was developed. The mesoscopic parameters (particle displacement, rotation, force chain, stress, coordination number, porosity, fabric, etc.) of the interface during shearing were simulated using the PFC model. Moreover, the relationship among the interface temperature, cohesion, and friction coefficient was determined based on experimental data, and the accuracy of the PFC model was verified using previous experimental data. The results of the PFC shear model aligned well with those of the laboratory test, and the formation of shear bands was simulated well. The displacement of the soil particles on the upper layer outside the shear zone was uniform, and the direction was the same, whereas the particles inside the shear zone showed significant differences in the dislocation and rotation of the soil particles. The force chain, stress field, coordination number, and porosity were similar in the shear process and showed a concentrated distribution in the opposite direction of the shear motion, which reflected the consistency of the microcosmic response of the particles under the action of macroscopic external forces. The regression equations for the temperature, cohesion, and friction coefficient in this study can be used to simulate the shear behavior of frozen soil-concrete interfaces under different temperatures and normal stresses.

Development and validation of a new anthropometric equation to predict fat mass percentage in a white Spanish population.

(1) To develop a new regression equation for estimating fat mass percentage (%FM) from anthropometric measurements in a heterogeneous Caucasian population and (2) to compare it with the Durnin and Womersley equation, which is one of the most used anthropometric equations for fat mass assessment. Body mass, stature, and four skinfolds (biceps, triceps, subscapular, and supracrestal) were assessed by an accredited anthropometrist, according to the International Society for Advancement in Kinanthropometry. Participants completed a dual-energy X-ray absorptiometry (DXA) whole-body scan to determine their %FM. A new anthropometric equation to estimate %FM was developed using multiple forward regression analyses with DXA as the reference method. Tests for the accuracy of the different equations included mean differences, coefficient of determination, standard error of the estimate (SEE), concordance correlation coefficient (CCC), and Bland-Altman plots. Spain. Two hundred and eighteen healthy Caucasian participants aged 18-65 years participated in this cross-sectional study. Our proposed equation explained 89.9% of the variance in the DXA-derived %FM, with a low random error (SEE = 3.00%), a very strong agreement (CCC = 0.93), no fixed or proportional bias, and a relatively low individual variability (5.84%). However, the Durnin and Womersley equations obtained a fixed bias of -3.65% when compared to DXA and a greater individual variability (6.74%). The proposed equation can accurately estimate %FM in a heterogeneous Caucasian population with a wide age range (18-65 years). Additionally, the Durnin and Womersley equation was inadequate when applied to our participants.

Statistical models for classification by handedness of Olympic Trap shooters in digital training services and remote coaching

AbstractIn this paper, we address the problem of classification by handedness of Olympic Trap shooters applying statistical methods to newly available data gathered from the field. We assess the performance of binary classification models based on KNN and Binary Regression, with both symmetric and asymmetric link functions, in a context characterized by unbalanced data. Our results show promising classification performance, suitable for first non-critical applications in data driven training services and remote coaching, encouraging further future research.

Spirometric Values of Healthy School Children in Three Rural Schools of Bangladesh

Background: The prevalence of asthma in Bangladesh is about 7%. The spirometric values in healthy children were obtained in a single urban school more than a decade ago. No rural data is available till date. The objective of this study is to determine the spirometric values of healthy school going children in three rural schools of Bangladesh. Materials and Methods: This cross-sectional study was carried out from July 2019 to June 2020 among 300 healthy children among both boys and girls aged 11 to 15 years in three rural schools. Among 350 approached students 332 students responded to the study, 18 students did not meet inclusion criteria and 14 students could not follow spirometry procedure. Informed written consent was taken from guardians. History regarding socio-demographic profile, passive smoking, concurrent or past respiratory illness and medication were taken and weight, height and BMI were measured of the children. Spirometry was done with spirometer and reports were generated by software installed in a laptop. Results: Boys showed higher FVC, FEV1 and PEFR but lower FEV1/FVC ratio than those of girls. Regression equations for lung function values were determined for boys and girls considering height as independent variable. Conclusions: Spirometric indices were higher in boys than those of girls and they tended to increase with height, except FEV1/FVC ratio that was higher in girls with a negative correlation with height. BANGLADESH J CHILD HEALTH 2023; VOL 47 (1) : 17-23