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To enhance the performance of the diesel engine helical intake port, computational fluid dynamics (CFD) was employed to conduct numerical simulations of the intake port and in-cylinder flow of the D19 diesel engine. The primary focus of the study was to investigate the effect of structural design parameters of the diesel engine helical intake port on the cylinder swirl ratio and intake mass. By modifying the three main structural design parameters of the helical intake port, we explored their effect on the in-cylinder swirl ratio. The study utilized deflection angle (θ), helical chamber height (H), and eccentric distance (Δa) as three influential factors, each set at three levels. Orthogonal experiments and linear regression analysis were conducted using swirl ratio and intake mass as evaluation indicators for the airflow characteristics in the intake port. The results show that the influence weights of the intake port structural parameters on swirl ratio and intake mass are as follows: H > Δa > θ, and H > θ > Δa. When the three key structural parameters of θ, H, and Δa are changed individually so that their values are -15 deg, 6.28 mm, and 3 mm, respectively, the in-cylinder swirl ratio obtains the maximum value and satisfies the linear regression equation, y = 0.754-0.005θ + 0.165H + 0.088Δa. From the analysis of the results of the F test, it can be found that the significant p value is 0.362, which is not statistically significant. There is no linear regression relationship between the intake mass and the θ, H, and Δa. [ABSTRACT FROM AUTHOR]

The increase in traffic caused by new development affects the change in traffic conditions on the surrounding roads, and shopping centres are significant traffic generators. The development of local travel generation rates and their characteristics for individual land uses from the aspect of traffic demand is a reliable way to plan traffic in order to come up with preventive solutions to traffic problems, that is, prevention of possible negative consequences on traffic conditions in the street network occurring due to the construction of shopping centres. One of the main aims of this paper is to develop a model for objective assessment of the generated traffic demand for significant changes in land use, such as the construction of shopping centres in medium-sized towns. All these would be steps in the right direction for the promotion of reliable traffic planning and adoption of TIA for every new development before a decision regarding the change in land purpose has been made. This kind of process still has not been established systematically in either Bosnia and Herzegovina and the Republic of Serbia, or in surrounding countries. This paper focuses on the formulation of a model for determining the volume of traffic generated by shopping centres in medium-sized towns in two countries of the Southeast Europe region. The survey was conducted in eight different locations (cities) where there are shopping centres with common facilities. The analysis showed that the number of visitors and vehicles attracted by the shopping centre zone can be determined by a model based on a linear regression analysis. The analysis included exploring several different factors of trip generation in shopping centres, including the relationship between trip generation and combinations of several independent variables. The verification of the model was conducted in real conditions of the traffic flow generated by a shopping centre which was not the analysis subject when forming the forecasting model. In this way, the validity of the proposed model is credibly assessed. The developed model can be applied in the procedures of planning the construction of shopping centres in medium-sized cities in the Republic of Serbia and Bosnia and Herzegovina, and wider, in the region of Southeast Europe, in order to estimate the volume of generated traffic demand, that is, its impact on the conditions of traffic on the surrounding traffic network. [ABSTRACT FROM AUTHOR]

The coal dust produced by surface coal mining has a serious impact on the atmosphere, vegetation, soil and residential environment in the coal mining area and its surrounding area, but the related research on the coverage of coal dust pollution, the quantification of pollution area and the trend of long-term series lags behind. In this study, the concepts of the maximum influence area and the continuous influence area were put forward. Based on the Google Earth Engine platform and the Landsat TM/ETM+/OLI images during 2006—2021, the ECDI (Enhanced Coal Dust Index) and the pollution coverage of coal dust were inversed. By using the linear regression and superposition analysis methods, the time series variation and spatial difference characteristics of coal dust pollution in the Shengli coal mining area were revealed. The results show that: ① the inter-annual variation of coal dust pollution can be categorized into three phases: a severe period (2006—2009), an improvement period (2010—2013), and a stable period (2014—2021). These phases correspond with the coal mine lifecycle, showing an initial increase followed by a decreasing trend. ② From 2019 to 2021, the coal dust pollution coverage was generally higher in spring and summer. Seasonal spatial variations were more pronounced in the relatively unpolluted area, lightly polluted area and moderately polluted area. ③ The overall accuracy of identifying the influence area of coal dust was 92.67% (kappa coefficient = 0.85). As coal production increased, both the perennial continuous influence area and the maximum influence area decreased, with the reductions of 43% and 80%, respectively. The spatial distribution of the annual continuous influence area remained relatively stable, while the maximum influence area decreased. ④ From 2006 to 2021, the relatively unpolluted area increased by 191.69 km2, accounting for 62.70% of the original area. The seriously polluted area decreased by 4.59 km2, representing 19.74% of the original area. The coal dust pollution area with a downward trend accounted for 52.11% of the coal mining area, while 4.07% showed an upward trend. As of 2021, the relatively unpolluted area and lightly polluted area accounted for 91.91% of total mining area (about 601.13 km2).

Abstract Background Early-onset sepsis (EOS) is a serious illness that affects preterm newborns, and delayed antibiotic initiation may increase the risk of adverse outcomes. Purpose The objective of this study was to examine the present time of antibiotic administration in preterm infants with suspected EOS and the factors that contribute to delayed antibiotic initiation. Methods In this retrospective study in China, a total of 82 early preterm infants with suspected EOS between December 2021 and March 2023 were included. The study utilized a linear regression analytical approach to identify independent factors that contribute to delayed antibiotic administration. Results The mean gestational age and birth weight of the study population were 29.1 ± 1.4 weeks and 1265.7 ± 176.8 g, respectively. The median time of initial antibiotic administration was 3.8 (3.1-5.0) hours. Linear regression revealed that severe respiratory distress syndrome (RDS) (β = 0.07, P = 0.013), penicillin skin test (PST) timing (β = 0.06, P

Agriculture is the foundation of Odisha's economy and it continues to be the backbone of the state. The state was recognized for its commendable agricultural production and abundant natural resources. Extensive water reservoirs, forests, substantial rainfall, and a sufficient surplus of labor were pivotal elements that play a significant role in fostering agricultural growth and development. The present research concentrates on the agricultural sector which plays a crucial role in shaping overall Gross Value Added (GVA) of the state and also highlights the study of agricultural sub sectors namely crop, livestock, forestry & logging, fishing & aqua culture. The principle of Pareto's 80/20 rule is used to identify the 20% Vital few agricultural sub sectors (VFS) which contribute 80% to total GVA. Thus by promoting the GVA of these VFS sectors the remaining 80% of agricultural sub sectors contributing 20% to the total GVA will automatically be benefited. The objective is to scrutinize, compare, and forecast data pertaining to the contributions of the agricultural sub sectors to Odisha's GVA spanning from 2011-12 to 2021-22. The GVA data were extracted from the Odisha Economic Survey 2021-22. Additionally, various statistical tools and tests, including analysis of variance, F-test, trend analysis, linear regression analysis, were adopted to derive meaningful insights and to formulate various policy measures for the development of the vital few agricultural sub sectors. Despite a 27% contribution to the Gross Value Added (GVA), significant disparities among sub-sectors were identified, necessitating targeted interventions. Recommendations include investing in irrigation infrastructure, promoting crop diversification, providing modern training, supporting small-scale farmers, improving market connections, and embracing sustainable practices. Addressing these disparities could unleash the sector's full potential, fostering sustainable development and empowering farming communities. [ABSTRACT FROM AUTHOR]

The complex evaluation of thermo-physiological comfort for a particular garment is still challenging, as it depends on the different structural parameters and individual properties of textiles. Measurement of relevant fabric characteristics requires very specific laboratory equipment, such as an M 290 moisture management tester (SDL ATLAS) or similar. For this reason, it is obvious that there is a great demand to predict the overall moisture management capability (OMMC) based on the individual properties that are responsible for clothing comfort and testing according to different standards rather than OMMC -specific calculation using the M 290 tester. Therefore, in this research, linear regression analysis was performed using MATLAB software to predict the OMMC for cotton–polyester fabrics knitted in two patterns, namely 1 × 1 rib and half-Milano rib, using four percentages of fibers. Water vapor permeability, water vapor resistance, water absorption capacity, water absorption time, and air permeability were used as input variables for linear regression analysis to predict the OMMC of fabrics. The performed analysis has shown that the OMMC is directly dependent on the relative water vapor permeability and air permeability, and the linear regression equation suggested in this research can predict the suitability of a textile for a particular garment concerning its moisture management behavior. [ABSTRACT FROM AUTHOR]

The study evaluated the efficacy of a three-month supplemental feeding intervention in encouraging weight gain among toddlers. Through linear regression analysis, this study aimed to elucidate the relationship between baseline measurements and monthly changes in toddler weight. Secondary data were collected and processed from 180 toddlers who underwent the intervention, covering baseline weight along with monthly measurements. These findings reveal a progressive month to month increase in body weight, as seen from the significant positive coefficients at eachmonth (β1 = 0.003, β2 = 0.204, β3 = 0.674), suggesting that the intervention had a positive and cumulative impact on children’s growth over a three-month period. These results underscore the importance of ongoing support and supplementation to achieve optimal growth outcomes. By measuring the impact of interventions on growth parameters, the study contributes valuable insights to the field, informing future strategies to address malnutrition and promote growth in vulnerable populations. [ABSTRACT FROM AUTHOR]

The soil–water characteristic curve (SWCC) is an important parameter of unsaturated soil, and almost all the engineering characteristics of unsaturated soil are more or less related to the SWCC. The SWCC contains important information for geotechnical engineering, water engineering, hydrogeology modelling and climate modelling. It is noted that the experimental measurement of SWCC is costly and time consuming, which limits the implementation of principles of unsaturated soil mechanics in practical engineering. The indirect method, which estimates the SWCC from the index properties of soil, can provide the SWCC with the errors which are within tolerance in practical engineering. In addition, the indirect method can determine SWCC very fast and almost with no cost. In this paper, the domestic sandy soils are selected and the index properties of those sands are used to correlate the SWCC fitting parameters. Consequently, mathematical equations are proposed to estimate SWCC from index properties of domestic sands. The proposed models are trained from 44 sets of experimental data and verified with another independent 8 sets of experimental data from published literature. It is observed that the results from the proposed model agree well with the experimental data from literature. [ABSTRACT FROM AUTHOR]

Background: Early-onset sepsis (EOS) is a serious illness that affects preterm newborns, and delayed antibiotic initiation may increase the risk of adverse outcomes. Purpose: The objective of this study was to examine the present time of antibiotic administration in preterm infants with suspected EOS and the factors that contribute to delayed antibiotic initiation. Methods: In this retrospective study in China, a total of 82 early preterm infants with suspected EOS between December 2021 and March 2023 were included. The study utilized a linear regression analytical approach to identify independent factors that contribute to delayed antibiotic administration. Results: The mean gestational age and birth weight of the study population were 29.1 ± 1.4 weeks and 1265.7 ± 176.8 g, respectively. The median time of initial antibiotic administration was 3.8 (3.1-5.0) hours. Linear regression revealed that severe respiratory distress syndrome (RDS) (β = 0.07, P = 0.013), penicillin skin test (PST) timing (β = 0.06, P < 0.001) and medical order timing (β = 0.04, P = 0.017) were significantly associated with the initial timing of antibiotic administration. Conclusions: There is an evident delay in antibiotic administration in preterm infants with suspected EOS in our unit. Severe RDS, PST postponement and delayed medical orders were found to be associated with the delayed use of antibiotics, which will be helpful for quality improvement efforts in the neonatal intensive care unit (NICU). [ABSTRACT FROM AUTHOR]

Tension members are key members that maintain stability and improve the strength of structures such as cable-stayed bridges, PSC structures, and slopes. Their application has recently been expanded to new fields such as mooring lines in subsea structures and aerospace fields. However, the tensile strength of the tension members can be abnormal owing to various risk factors that may lead to the collapse of the entire structure. Therefore, continuous tension monitoring is necessary to ensure structural safety. In this study, an improved elasto-magnetic (E/M) sensor was used to monitor tension force using a nondestructive method. General E/M sensors have limitations that make it difficult to apply them to operating tension members owing to their solenoid structure, which requires field winding. To overcome this problem, the magnetization part of the E/M sensor was improved to a yoke-type sensor, which was used in this study. For the development of the sensors, the numerical design and magnetization performance verification of the sensor were performed through eddy current solution-type simulations using ANSYS Maxwell. Using the manufactured yoke-type E/M sensor, the induced voltage signals according to the tension force of the specimen increasing from 0 to 10 tons at 1-ton intervals were repeatedly measured using DAQ with wireless communication. The measured signals were indexed using peak-to-peak value of induced voltages and used to analyze the signal change patterns as the tension increased. Finally, the analyzed results were compared with those of a solenoid-type E/M sensor to confirm the same pattern. Therefore, it was confirmed that the tension force of a tension member can be estimated using the proposed yoke-type E/M sensor. This is expected to become an effective tension monitoring technology through performance optimization and usability verification studies for each target tension member in the future. [ABSTRACT FROM AUTHOR]

Virtual try-on services, which significantly reduce return rates and enhance user shopping experiences, pose a crucial question: how can user willingness to use these services be increased? Additionally, "Generation Z" consumers, known for their unique traits and significant consumption potential, have been relatively understudied in this context. To address this theoretical gap, this study employs the Stimulus–Organism–Response (S-O-R) theory as its research framework, using online virtual shoe try-on services as a case study. Focusing on "Generation Z" consumers, this study utilizes literature review, user research, factor analysis, and linear regression to establish a user experience evaluation scale and behavior model. The user experience evaluation scale identifies positive elements such as convenience, price value, visual information acquisition, emotional value, and social interaction. The negative elements include technical limitations, personalized service deficiencies, and uncertainty. In the behavior model, all elements influence user attitudes. Notably, only the negative elements directly affect users' willingness to use the service, except social interaction among the positive elements, which positively impacts usage intention. This study also reveals that "Generation Z" consumers have novel requirements for social interaction. This research effectively addresses existing theoretical gaps and provides a foundational theory for the development of related services and technologies. [ABSTRACT FROM AUTHOR]

Recently, rapid economic development of the Yangtze River Economic Belt region in China and the growing problem of regional habitat quality have seriously threatened the process of biodiversity conservation in the Yangtze River Basin. Studying the impact of changes in landscape pattern indexes on habitat quality in the Yangtze River Economic Belt can provide policy insights for biodiversity conservation in the Yangtze River Basin. However, existing studies are still lacking in exploring the effects of changing landscape pattern indices on habitat quality under future scenarios. Based on the land use data of the Yangtze River Economic Belt from 2000 to 2020, this study simulates the land use situation in 2030, and analyzes the landscape pattern indexes and habitat quality during the 30 years, to investigate the impact of landscape pattern indexes on habitat quality at global and local scales through various methods. The results show that landscape patterns were significantly affected by human activities and land use types, with the Yangtze River Economic Belt experiencing increased levels of land use and structural stabilization during the three decades (Shannon Diversity Index increased from 0.90 in 2000 to 0.94 in 2030), fragmentation of the landscape (Landscape fragmentation index increase from 0.094 in 2000 to 0.102 in 2030), and weakened connectivity (contagion index decrease from 48.213 in 2000 to 45.437 in 2030). The Habitat Quality has a large variation in spatial distribution at the county scale, with an average change in habitat quality of 1.04 % from 2000 to 2030, and an overall downward trend. There is a strong localized spatial autocorrelation between landscape pattern indices and habitat quality, with significant spatial heterogeneity and some form of variability at time scales. The results of this study help to further understand the eco-environmental problems of the Yangtze River Economic Belt, and provide theoretical references for the formulation of ecological environmental protection policies and ecological functional area planning.

ObjectiveTo understand the visual environment sanitation in primary and secondary school classrooms in Minhang District， Shanghai， and to investigate the factors affecting the decline in students’ visual acuity.MethodsIn 2020， among all the primary and secondary schools in Minhang District， according to different types of classroom structures， levels， orientations， unilateral lighting， and bilateral lighting， a total of 20 231 students from 674 classrooms in primary and secondary schools were selected through stratified cluster sampling. Each monitored classroom was regarded as a research unit， and the naked eye vision of students was tested using a standard logarithmic vision chart during the 2020 and 2021 academic years. The change in average visual acuity between the two measurements was taken as the dependent variable， and the visual environment indices were considered as independent variables. The relationship between classroom visual environment indices and the decline in students’ naked eye vision was analyzed.ResultsThe qualification rates for per capita classroom area， window to floor area ratio， average illuminance of the blackboard， uniformity of blackboard illuminance， average illuminance of the desks， uniformity of desk illuminance， lighting coefficient of classroom， blackboard reflection ratio， back wall reflection ratio， and distance between lamps and desks were 79.53%， 88.58%， 46.74%， 70.33%，64.69%， 80.86%， 71.81%， 20.30%， 1.63%， and 97.53%， respectively. The average naked eye vision of primary and secondary school students in the 2020 academic year was 4.75±0.37 （right eye） and 4.76±0.37 （left eye）， while in the 2021 academic year， it was 4.70±0.39 （right eye） and 4.71±0.38 （left eye）. There was a significant decrease in the naked eye vision of primary and secondary school students in the 2021 academic year compared to that of 2020 （P

Based on the energy consumption data of the Changjiang River Administration of Navigation Affairs public building located in Wuhan, China, this paper analyzes the energy consumption characteristics of public buildings. Using the DesignBuilder energy simulation software (v7.0.0.096), various factors influencing building energy consumption are investigated. Furthermore, SPSS (v26.0.0.0) is employed to conduct correlation analyses between measured and simulated energy consumption data. The results indicate that the most significant factors affecting energy consumption are outdoor temperature, office equipment usage time, anticipated room temperature settings, boiler usage time, and per capita daily water consumption. By exploring the factors influencing energy consumption in public buildings, this study contributes novel insights into setting targets, adjusting schemes, and achieving energy-saving effects. [ABSTRACT FROM AUTHOR]

At present, many algorithms use a single minimum eigenvalue to estimate the real noise level, and the levels estimated by these algorithms have been proven to be less than the real noise levels, this is known as underestimation. To address this problem, this paper uses multiple eigenvalues to obtain the relationship between eigenvalues and the real noise level through sample training, calculates the learning coefficients for different noise levels in the relationship expression by linear fitting, and then inputs the learning coefficients into the noise image for noise level estimation. Experiments demonstrate that the algorithm proposed in this paper can significantly improve the underestimation problem of the traditional algorithm and has better estimation accuracy for various noise levels in gray images, color images, and texture images of various scenes. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of predicting the passenger load factor (PLF) in air transportation to optimize capacity management and revenue maximization. Leveraging historical reservation data from 19 Turkish Airlines market routes and sample flights, we propose a novel approach combining deep assessment methodology (DAM) with fractional calculus theory. By modeling the relationship between PLF and the number of days remaining until a flight, our method yields minimal errors compared to traditional techniques. Through a continuous curve constructed using the least-squares approach, we enable the anticipation of future flight values. Our analysis demonstrates that the DAM model with a first-order derivative outperforms linear techniques and the Fractional Model-3 in both modeling capabilities and prediction accuracy. The proposed approach offers a data-driven solution for efficiently managing air transport capacity, with implications for revenue optimization. Specifically, our modeling findings indicate that the DAM wd model improves prediction accuracy by approximately 0.67 times compared to the DAM model, surpassing the fractional model and regression analysis. For the DAM wd modeling method, the lowest average mean absolute percentage error (AMAPE) value achieved is 0.571, showcasing its effectiveness in forecasting flight outcomes. [ABSTRACT FROM AUTHOR]

Abstract Background Medical education requires the implementation of different teaching methods and strategies for future doctors to achieve broad learning objectives. This wide range of methods and strategies includes the use of Information Technologies. For a long time, there was a call for a change in medical education for blending new teaching approaches to lessen medical students’ class time. The COVID-19 pandemic then sped up the transition to the new way of medical education and classroom lectures were quickly moved to a virtual environment. We expect that these changes will continue, and online learning will be one of the main teaching strategies in medical education. Therefore, educational experiences during the COVID-19 pandemic will improve our understanding of online learning and will help to develop blended medical school curricula in the future. For this reason, we aimed to determine students’ overall satisfaction with their online learning experience and to define the main factors affecting students’ satisfaction with their online learning program at Cerrahpaşa Medical Faculty. Methods A cross-sectional survey study was conducted to determine medical students’ overall satisfaction with online learning methods and to identify factors associated with positive and negative satisfaction levels. A questionnaire, consisting of 24 questions to collect demographic characteristics, factors associated with online education experience and overall satisfaction levels was developed and distributed to 1600 medical students. Multivariable linear regression analysis was used to determine the factors associated with positive and negative satisfaction levels. Results Regression analysis showed that being familiar with online teaching techniques (β = 0.19, 95% CI [0.07, 0.30], faculty members’ higher online teaching skill levels (β = 0.42, 95% CI [0.32, 0.51], interactive online teaching approaches (β = 0.54, 95% CI [0.41, 0.67], having a personal workspace (β = 0.43, 95% CI [0.19, 0.67], and a self-reported longer attention span (β = 0.75, 95% CI [0.57, 0.92] were associated with higher overall satisfaction with online learning. The occurrence of technical problems (β = -0.19, 95% CI [-0.26, -0.12] was associated with lower overall satisfaction. Conclusions Higher online teaching skills of faculty members, use of interactive approaches, students’ familiarity with online teaching techniques, provision of a personal workspace, and self-reported longer attention spans positively contributed to higher levels of student satisfaction with online learning. Considering the increasing significance of online educational methods, our study identified key components that affect students’ level of satisfaction. This information might contribute to the development of online educational programs in the future.

The increase in traffic caused by new development affects the change in traffic conditions on the surrounding roads, and shopping centres are significant traffic generators. The development of local travel generation rates and their characteristics for individual land uses from the aspect of traffic demand is a reliable way to plan traffic in order to come up with preventive solutions to traffic problems, that is, prevention of possible negative consequences on traffic conditions in the street network occurring due to the construction of shopping centres. One of the main aims of this paper is to develop a model for objective assessment of the generated traffic demand for significant changes in land use, such as the construction of shopping centres in medium-sized towns. All these would be steps in the right direction for the promotion of reliable traffic planning and adoption of TIA for every new development before a decision regarding the change in land purpose has been made. This kind of process still has not been established systematically in either Bosnia and Herzegovina and the Republic of Serbia, or in surrounding countries. This paper focuses on the formulation of a model for determining the volume of traffic generated by shopping centres in medium-sized towns in two countries of the Southeast Europe region. The survey was conducted in eight different locations (cities) where there are shopping centres with common facilities. The analysis showed that the number of visitors and vehicles attracted by the shopping centre zone can be determined by a model based on a linear regression analysis. The analysis included exploring several different factors of trip generation in shopping centres, including the relationship between trip generation and combinations of several independent variables. The verification of the model was conducted in real conditions of the traffic flow generated by a shopping centre which was not the analysis subject when forming the forecasting model. In this way, the validity of the proposed model is credibly assessed. The developed model can be applied in the procedures of planning the construction of shopping centres in medium-sized cities in the Republic of Serbia and Bosnia and Herzegovina, and wider, in the region of Southeast Europe, in order to estimate the volume of generated traffic demand, that is, its impact on the conditions of traffic on the surrounding traffic network.

Laser cladding is one of the emerging additive manufacturing technologies and has been adopted in various industrial fields. In this study, the morphological characteristics of a single clad of Inconel 718 manufactured by coaxial laser cladding with high laser power from 4200 W to 5400 W, powder feeding rate from 25 g/min to 50 g/min, and cladding speed from 20 mm/s to 50 mm/s are studied. The cross-section of the melt pool is analyzed and classified by type into three types: shallow dilution, flat dilution, and fluctuating dilution. Nine parameters are designed to describe the morphological characteristics of the clad, and the corresponding linear regression models are developed to establish a quantitative relationship between the combined process parameters and morphological characteristics. The results indicate that the total area of the cross-section A, the clad area above the substrate Ac, the area of the molten substrate Am, the total height of the cross-section H, the height of the clad above the substrate hc, the penetration depth hm, the clad width W, the dilution ratio D, and the wetting angle θ are determined by complex coupling of energy input and mass accumulation, and they are proportional to PF0.4/V, P0.5F/V, P/F0.2/V0.4, P2F0.6/V, PF0.7/V, P2/F/V0.3, P/V0.8, P/FV0.2, and PF7/V0.8, respectively. The large linear regression coefficients and the analysis residuals indicate the high reliability of the statistical linear regression models. This work aims to provide a comprehensive understanding of the influence of the main processing parameters on the morphological characteristics of the clad, which is of great value in providing a reference and laying a basis for the practical application of laser cladding technology at a high deposition rate. [ABSTRACT FROM AUTHOR]

Background: Medical education requires the implementation of different teaching methods and strategies for future doctors to achieve broad learning objectives. This wide range of methods and strategies includes the use of Information Technologies. For a long time, there was a call for a change in medical education for blending new teaching approaches to lessen medical students' class time. The COVID-19 pandemic then sped up the transition to the new way of medical education and classroom lectures were quickly moved to a virtual environment. We expect that these changes will continue, and online learning will be one of the main teaching strategies in medical education. Therefore, educational experiences during the COVID-19 pandemic will improve our understanding of online learning and will help to develop blended medical school curricula in the future. For this reason, we aimed to determine students' overall satisfaction with their online learning experience and to define the main factors affecting students' satisfaction with their online learning program at Cerrahpaşa Medical Faculty. Methods: A cross-sectional survey study was conducted to determine medical students' overall satisfaction with online learning methods and to identify factors associated with positive and negative satisfaction levels. A questionnaire, consisting of 24 questions to collect demographic characteristics, factors associated with online education experience and overall satisfaction levels was developed and distributed to 1600 medical students. Multivariable linear regression analysis was used to determine the factors associated with positive and negative satisfaction levels. Results: Regression analysis showed that being familiar with online teaching techniques (β = 0.19, 95% CI [0.07, 0.30], faculty members' higher online teaching skill levels (β = 0.42, 95% CI [0.32, 0.51], interactive online teaching approaches (β = 0.54, 95% CI [0.41, 0.67], having a personal workspace (β = 0.43, 95% CI [0.19, 0.67], and a self-reported longer attention span (β = 0.75, 95% CI [0.57, 0.92] were associated with higher overall satisfaction with online learning. The occurrence of technical problems (β = -0.19, 95% CI [-0.26, -0.12] was associated with lower overall satisfaction. Conclusions: Higher online teaching skills of faculty members, use of interactive approaches, students' familiarity with online teaching techniques, provision of a personal workspace, and self-reported longer attention spans positively contributed to higher levels of student satisfaction with online learning. Considering the increasing significance of online educational methods, our study identified key components that affect students' level of satisfaction. This information might contribute to the development of online educational programs in the future. [ABSTRACT FROM AUTHOR]

Epidemiological studies have reported that the frequency of nuclear cataracts (NUCs) is high among the elderly and in tropical countries. Ultraviolet (UV) irradiation and lens temperature are considered as key physical contributors, although their precise quantification is difficult. The aim of this study is to investigate the association of NUC prevalence with UV irradiation and heat load. First, we assessed the lens temperature using thermodynamic modeling considering the thermophysiological response. We then conducted a multivariate linear regression analysis for the epidemiological analysis of NUC prevalence across five cities. A strong correlation was observed between NUC prevalence and the combined effects of UV irradiation and cumulative equivalent minutes at 43 °C (CEM43°C) derived from the computed lens temperature (adjusted R2 = 0.933, p < 0.0001). Heat load significantly contributed to the prevalence at 52%, surpassing the contributions of UV irradiation (31%) and the decline in DNA repair capacity in the lens (17%). These results suggested that both UV radiation and heat load are associated with NUC, with heat load contributing more. Our findings provided important implications for future interventions, particularly in the context of global warming. [ABSTRACT FROM AUTHOR]

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Virtual try-on services, which significantly reduce return rates and enhance user shopping experiences, pose a crucial question: how can user willingness to use these services be increased? Additionally, “Generation Z” consumers, known for their unique traits and significant consumption potential, have been relatively understudied in this context. To address this theoretical gap, this study employs the Stimulus–Organism–Response (S-O-R) theory as its research framework, using online virtual shoe try-on services as a case study. Focusing on “Generation Z” consumers, this study utilizes literature review, user research, factor analysis, and linear regression to establish a user experience evaluation scale and behavior model. The user experience evaluation scale identifies positive elements such as convenience, price value, visual information acquisition, emotional value, and social interaction. The negative elements include technical limitations, personalized service deficiencies, and uncertainty. In the behavior model, all elements influence user attitudes. Notably, only the negative elements directly affect users’ willingness to use the service, except social interaction among the positive elements, which positively impacts usage intention. This study also reveals that “Generation Z” consumers have novel requirements for social interaction. This research effectively addresses existing theoretical gaps and provides a foundational theory for the development of related services and technologies.

Assessing pension expenditure determinants is crucial for the sustainability of public finances. This study aims to disentangle the impact of demographic and economic variables, such as ageing, productivity, and unemployment, on pension expenditure in Portugal. With the use of time-series data, from 1975 to 2014, statistical evidence was found of co-integration between unemployed people aged between 15 and 64 years old, apparent productivity of labour, the old age dependency ratio and pension expenditure as a share of gross domestic product. The use of a vector error correction model, with impulse-response functions and variance decomposition, showed that ageing has an almost insignificant impact in the long-run, when compared with unemployment and productivity.

The tortuosity of retinal blood vessels is an important phenomenon, and it can act as a biomarker in the diagnosis of several eye diseases. The study of abnormalities in the tortuosity of retinal arteries and veins provides ophthalmologists with important information for disease diagnosis. Our study aims to compare the tortuosity relation between retinal arteries and veins by quantifying the vessels' tortuosity in the retina using 14 tortuosity measures applied to the AV-classification retinal dataset. Two feature sets are created, one for arteries and the other for veins. The comparison between the tortuosity of arteries and veins is based on a two-sample T-test statistical method, a regression analysis between the quantified tortuosity features, principal component analysis at the dataset level, and the introduction of the arteriovenous length ratios concept to compare the variations in these new ratios to see the tortuosity behavior in each image. The methods' results have shown that the tortuosity of retinal arteries and veins is similar. The result of the two-sample T-test supports the research hypothesis, as the P-value obtained was greater than 0.05. Furthermore, the regression analysis between arteries and veins features showed a high correlation ( r 2 = 89.39% and 89.11%) for arteries and veins, respectively. The study concludes that the retinal vessel type has no statistical significance in the tortuosity calculation results. [ABSTRACT FROM AUTHOR]

Тhe mаin rеаsоn for the еxchаnge rate sеnsitivity is the dоubts in its crеdibility rеlаtеd to the trаde, wеаknesses in the finаnciаl sеctоr, еxternаl shоcks, pоlitical errоrs, cоuntry risk, еtc. Тhis paper discuss about potential currency crisis in the Republic of N. Macedonia for the period before pandemic and give the answer to what kind of lessons should we take into account regarding past period which is measured in the research. The paper presents the results of a possible crisis scenario in N. Macedonia and give statistical analysis of the relationship of the indicators of a currency crisis, examining two questions - are disorders in Macedonia that can cause a currency crisis and which generation currency crises would be the closest for Macedonia. [ABSTRACT FROM AUTHOR]

Aims: We aimed to assess the reliability and validity of OpenPose, a posture estimation algorithm, for measurement of knee range of motion after total knee arthroplasty (TKA), in comparison to radiography and goniometry. Methods: In this prospective observational study, we analyzed 35 primary TKAs (24 patients) for knee osteoarthritis. We measured the knee angles in flexion and extension using OpenPose, radiography, and goniometry. We assessed the test-retest reliability of each method using intraclass correlation coefficient (1,1). We evaluated the ability to estimate other measurement values from the OpenPose value using linear regression analysis. We used intraclass correlation coefficients (2,1) and Bland–Altman analyses to evaluate the agreement and error between radiography and the other measurements. Results: OpenPose had excellent test-retest reliability (intraclass correlation coefficient (1,1) = 1.000). The R2 of all regression models indicated large correlations (0.747 to 0.927). In the flexion position, the intraclass correlation coefficients (2,1) of OpenPose indicated excellent agreement (0.953) with radiography. In the extension position, the intraclass correlation coefficients (2,1) indicated good agreement of OpenPose and radiography (0.815) and moderate agreement of goniometry with radiography (0.593). OpenPose had no systematic error in the flexion position, and a 2.3° fixed error in the extension position, compared to radiography. Conclusion: OpenPose is a reliable and valid tool for measuring flexion and extension positions after TKA. It has better accuracy than goniometry, especially in the extension position. Accurate measurement values can be obtained with low error, high reproducibility, and no contact, independent of the examiner’s skills. Cite this article: Bone Joint Res 2023;12(5):313–320.

Super alloys have great interest with good mechanical strength, surface stability, high operating temperatures, and high resistance to corrosion and oxidation features. In the study, new, reliable, and practical equations which give the radiation shielding parameters depending on the density of super alloys are obtained. For this analysis, MAR-247, MAR 302, Inconel 625, Inconel 718, Nimocast 75, WI-52, Inconel 617, Incoloy 800HT, Inconel 939, 713LC, and 7925A super alloys are chosen. The radiation shielding parameters such as linear attenuation coefficient, effective atomic number, half value layer, mean free path, and fast neutron removal cross-section are calculated by using Phy-X/PSD program. Then, new analytical equations providing the radiation shielding parameters by linear regression analysis are evaluated.

Tension members are key members that maintain stability and improve the strength of structures such as cable-stayed bridges, PSC structures, and slopes. Their application has recently been expanded to new fields such as mooring lines in subsea structures and aerospace fields. However, the tensile strength of the tension members can be abnormal owing to various risk factors that may lead to the collapse of the entire structure. Therefore, continuous tension monitoring is necessary to ensure structural safety. In this study, an improved elasto-magnetic (E/M) sensor was used to monitor tension force using a nondestructive method. General E/M sensors have limitations that make it difficult to apply them to operating tension members owing to their solenoid structure, which requires field winding. To overcome this problem, the magnetization part of the E/M sensor was improved to a yoke-type sensor, which was used in this study. For the development of the sensors, the numerical design and magnetization performance verification of the sensor were performed through eddy current solution-type simulations using ANSYS Maxwell. Using the manufactured yoke-type E/M sensor, the induced voltage signals according to the tension force of the specimen increasing from 0 to 10 tons at 1-ton intervals were repeatedly measured using DAQ with wireless communication. The measured signals were indexed using peak-to-peak value of induced voltages and used to analyze the signal change patterns as the tension increased. Finally, the analyzed results were compared with those of a solenoid-type E/M sensor to confirm the same pattern. Therefore, it was confirmed that the tension force of a tension member can be estimated using the proposed yoke-type E/M sensor. This is expected to become an effective tension monitoring technology through performance optimization and usability verification studies for each target tension member in the future.

This study addresses the challenge of predicting the passenger load factor (PLF) in air transportation to optimize capacity management and revenue maximization. Leveraging historical reservation data from 19 Turkish Airlines market routes and sample flights, we propose a novel approach combining deep assessment methodology (DAM) with fractional calculus theory. By modeling the relationship between PLF and the number of days remaining until a flight, our method yields minimal errors compared to traditional techniques. Through a continuous curve constructed using the least-squares approach, we enable the anticipation of future flight values. Our analysis demonstrates that the DAM model with a first-order derivative outperforms linear techniques and the Fractional Model-3 in both modeling capabilities and prediction accuracy. The proposed approach offers a data-driven solution for efficiently managing air transport capacity, with implications for revenue optimization. Specifically, our modeling findings indicate that the DAM wd model improves prediction accuracy by approximately 0.67 times compared to the DAM model, surpassing the fractional model and regression analysis. For the DAM wd modeling method, the lowest average mean absolute percentage error (AMAPE) value achieved is 0.571, showcasing its effectiveness in forecasting flight outcomes.

With the proposal of the goal of "carbon peak, carbon neutrality", the concept of environmental protection has become increasingly popular. To explore the characteristics and influencing factors of consumers' green consumption behavior against a dual-carbon background, this study proposed research variables and hypotheses about green consumption behavior and influencing factors. With the research purpose, research variables, and hypotheses, a questionnaire was designed. Consumers in Anhui Province were chosen as research samples. SPSS26.0 was employed to conduct reliability and validity analysis, correlation analysis, and stepwise linear regression analysis of the questionnaire data to evaluate the factors affecting consumers' green consumption behavior; through these measures, it was verified that there existed a significant relationship between green consumption behavior and the influencing factors of purchase motivation, channel factor, consumer innovation, and price factor. And it was also verified that the influence of incentive factors and psychological factors was not significant. Based on this, the current study proposes countermeasures and suggestions for setting up environmental awareness, reducing the price of green products, expanding green consumption channels, and stimulating consumer innovation. [ABSTRACT FROM AUTHOR]

In order to improve the prediction accuracy of in-situ stress field inversion, an improved ground stress inversion algorithm is proposed. Based on the prior information of ground stress observation, the improved algorithm modifies the tectonic stress to trapezoidal load varying with buried depth. The slope of trapezoidal tectonic stress is determined according to the slope of horizontal principal stress. A simulation calculation method for analytically solving three principal stresses of five observation points in the borehole under four typical load conditions is established, which improves the calculation efficiency of ground stress field inversion. Based on the principle of elasticity, the vertical principal stress is separated and the two regression coefficients related to are solved. Based on the horizontal principal stress observation data, the other two regression coefficients are inversed. The practical engineering application shows that the predicted principal stress is in good agreement with the observed value, which verifies the robustness and effectiveness of the proposed improved algorithm. [ABSTRACT FROM AUTHOR]

This paper calculated the Duration Magnitude (MD) equation using data from the Iraqi Meteorological Organization and seismology (IMOS). It is an empirically determined equation and expressed as: MD = 0.8582 × log(τcoda) - 0.0000262 × R + 2.1203 ± c The epicentral distance and local geological conditions affect the duration of the coda. The data is obtained from 7 seismic stations in the network. The new proposed duration magnitude equation results from applying linear regression analysis to the data of a seismic signal duration with correlation coefficient R²=0.76; and a standard deviation value of 0.049. Station corrections indicated by Sc are also specified for the seismic stations that range from -0.024 to + 0.02. [ABSTRACT FROM AUTHOR]

Adverse pregnancy outcomes are associated with a poor ambient atmospheric environment. Infections by teratogenic pathogens such as cytomegalovirus (CMV) and herpes simplex virus (HSV) are the main cause of the worse pregnant outcomes. However, environmental factors governing these infections are uncertain and epidemiological studies are limited. An epidemiological study on relationships between air pollutants and antibodies against teratogenic pathogens will be explored. In total, 5475 women of childbearing age were enrolled in the study between January 2018 and December 2019 in a hospital in Shantou, China. Antibodies against pathogens were measured by electrochemical luminescence. Everyday air quality data, concerning particulate matter (PM), sulfur dioxide (SO2), nitrogen dioxide (NO2), and other parameters, were acquired from a government web site, and the relationships between them were evaluated with nonparametric and multivariate linear regression analyses. Not only titers of herpes simplex virus HSV(I+II) IgGs in spring, but also titers of cytomegalovirus IgG (CMV IgG) and HSV I IgG in autumn, both had positive associations with concentrations of SO2. When PM2.5 or PM10 exposure is elevated, HSV(I+II) IgGs, TOX IgM should be paid more attention in spring or summer. Air pollution may be crucial for teratogenic pathogen infections. This study highlights air pollution could increase the risk of teratogenic pathogen infection, implying stronger measures should be taken to protect air environment and screenings of associated antibody should be strengthened in different season. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate tourist characteristics, rental factors, non-rental factors, and use intention of shared motorcycles in tourism activities. Linear regression analysis was used to compare the differences and influences of variables. A convenience sampling survey method was adopted to investigate GoShare motorcycle-sharing service. Questionnaires were distributed to 271 respondents aged 20–29 years old who used motorcycles in tourism. With data descriptive statistics, t-test, one-way analysis of variance, and regression analysis were conducted, and four main results were obtained: (1) The respondents tended to follow a "Freestyle travel" type. (2) As a rental factor, "Environmental Efficiency" was the most important. (3) "Renting is not easy" was the most important reason not to rent a motorcycle. (4) Tourist characteristics and rental factors impacted use intention significantly. Therefore, the following suggestions were made in this study: it is necessary to (1) strengthen the promotion of the GoShare motorcycle-sharing service, (2) enhance the quality of the rental service, (3) improve the mobile application, and (4) focus on in-depth tourism and expand the services at scenic spots. [ABSTRACT FROM AUTHOR]

Reliable quantification in biological systems of endogenous low- and high-molecular substances, drugs and their metabolites, is of particular importance in diagnosis and therapy, and in basic and clinical research. The analytical characteristics of analytical approaches have many differences, including in core features such as accuracy, precision, specificity, and limits of detection (LOD) and quantitation (LOQ). Several different mathematic approaches were developed and used for the comparison of two analytical methods applied to the same chemical compound in the same biological sample. Generally, comparisons of results obtained by two analytical methods yields different quantitative results. Yet, which mathematical approach gives the most reliable results? Which mathematical approach is best suited to demonstrate agreement between the methods, or the superiority of an analytical method A over analytical method B? The simplest and most frequently used method of comparison is the linear regression analysis of data observed by method A (y) and the data observed by method B (x): y = α + βx. In 1986, Bland and Altman indicated that linear regression analysis, notably the use of the correlation coefficient, is inappropriate for method-comparison. Instead, Bland and Altman have suggested an alternative approach, which is generally known as the Bland–Altman approach. Originally, this method of comparison was applied in medicine, for instance, to measure blood pressure by two devices. The Bland–Altman approach was rapidly adapted in analytical chemistry and in clinical chemistry. To date, the approach suggested by Bland–Altman approach is one of the most widely used mathematical approaches for method-comparison. With about 37,000 citations, the original paper published in the journal The Lancet in 1986 is among the most frequently cited scientific papers in this area to date. Nevertheless, the Bland–Altman approach has not been really set on a quantitative basis. No criteria have been proposed thus far, in which the Bland–Altman approach can form the basis on which analytical agreement or the better analytical method can be demonstrated. In this article, the Bland–Altman approach is re-valuated from a quantitative bioanalytical perspective, and an attempt is made to propose acceptance criteria. For this purpose, different analytical methods were compared with Gold Standard analytical methods based on mass spectrometry (MS) and tandem mass spectrometry (MS/MS), i.e., GC-MS, GC-MS/MS, LC-MS and LC-MS/MS. Other chromatographic and non-chromatographic methods were also considered. The results for several different endogenous substances, including nitrate, anandamide, homoarginine, creatinine and malondialdehyde in human plasma, serum and urine are discussed. In addition to the Bland–Altman approach, linear regression analysis and the Oldham–Eksborg method-comparison approaches were used and compared. Special emphasis was given to the relation of difference and mean in the Bland–Altman approach. Currently available guidelines for method validation were also considered. Acceptance criteria for method agreement were proposed, including the slope and correlation coefficient in linear regression, and the coefficient of variation for the percentage difference in the Bland–Altman and Oldham–Eksborg approaches. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the correlation between T1 and T2 relaxation times of synthetic MRI (SyMRI) and gestational age (GA) in each hemisphere of preterm and term newborns at the initial 28 days of birth. Methods: Seventy preterm and full‐term infants were prospectively included in this study. All subjects completed 3.0 T routine MRI and SyMRI (MAGiC) one‐stop scanning within 28 days of birth (aged 34–42 W at examination). The SyMRI postprocessing software (v8.0.4) was used to measure the T1 and T2 relaxation values of each brain region. The linear regression equations of quantitative relaxation values with GA were established to compare the variation speed in each brain region. Results: A significant linear and negative correlation was found between relaxation times and GA in the neonate cerebral cortex and subcortical gray and white matter regions (All p<.05). The relaxation time of the left centrum semiovale decreased with maximum variance with increasing GA among all white matter regions (T1: b = –51.45, β = –0.65, p <.0001; T2: b = –8.77, β = –0.71, p <.0001), whereas the right posterior limb of internal capsule showed minimal variance (T1: b = –27.94, β = –0.60, p <.0001; T2: b = –3.25, β = –0.68, p <.0001). Among all gray matter regions, the right globus pallidus and thalamus indicated the most significant decreasing degree of T1 and T2 relaxation values with GA (right globus pallidus T1: b = –33.14, β = –0.64, p <.0001; right thalamus T2: b = –3.94, β = –0.81, p <.0001), and the right and left occipital lobes indicated the least significant decreasing degree of T1 and T2 relaxation values with GA, respectively (right occipital lobes T1: b = –11.18, β = –0.26, p =.028; left occipital lobes T2: b = –1.22, β = –0.27, p =.024). Conclusions: SyMRI could quantitatively evaluate the linear changes of T1 and T2 relaxation values with GA in brain gray and white matter of preterm and term neonates. [ABSTRACT FROM AUTHOR]

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The main idea of this study is to investigate Türkiye’s meat consumption, projection and supplies by using the structure of the Turkish meat industry and Turkish economic indicators. This present study develops several models for the analysis of meat consumption and makes future estimations based on the Regression Analysis Meat Consumption Model (RAMCM). Four forms of Regression Analysis models are used to estimate meat consumption. These models are named Multiple Linear Regression Analysis (MULIRA), Linear Regression Analysis (LIRA), Polynomial Linear Regression Analysis (POLIRA), and Logarithmic Linear Regression Analysis. The models developed in the linear and non-linear forms are applied to estimate meat consumption in Türkiye based on social and economic indicators; Population, Gross National Product (GNP) per capita, Imports of goods and services (% of GDP), Exports of goods and services (% of GDP), electricity consumption per capita, unemployment, Gross capital formation (% of GDP) figures. It may be concluded that the Multiple Linear Regression Analysis models can be used as alternative solutions and estimation techniques for any country's future meat consumption values. [ABSTRACT FROM AUTHOR]