Influence Of Multiple Factors Research Articles

The Determinants of Presenteeism in Selected European Countries - Modelling from Geographical and Gender Perspectives

In this paper we analyze motives (person-, work-, and organizational-related) of presenteeism among employees in selected European countries. We applied questions on presenteeism from European Working Conditions Surveys (EWCS) for 2010-2021. Based on the preliminary outcomes we observe that presenteeism is gender and geographical-dependent. Therefore, we use geographically weighted regression (GWR) to model determinants of phenomena. We find that men are more motivated by economic issues (the level of earnings, type of work contract, household financial situation, gander pay gap) but women are guided by so-called emotional factors (having children at home or work requiring direct contact with customers). The type of employment contract and fact of having children at home also has an impact on presenteeism. The results of the GWR show that, regardless of gender, there are countries for which the influence of multiple factors was recorded simultaneously, e.g. Spain, Malta, Portugal. However, there are countries for which no influence of factors on presenteeism was identified, e.g. Germany, Slovakia, Sweden, Hungary, Luxemburg or Finland and therefore, the motives of presenteeism should be analysed separately. Finally, the country policy insurance arrangements contribute to the presenteeism.

In-depth molecular dynamics analysis of crack evolution in polycrystalline chromium under uniaxial tensile deformation

Because of its excellent wear resistance and high hardness, chromium is widely used in coating materials. Under external load, micro-cracks on the surface of electroplated chromium coating will cause crack propagation and reduce the performance of the material. Therefore, in this study, the crack evolution process of polycrystalline chromium under uniaxial tension was studied using molecular dynamics. The effects of average grain size, strain rate, and crack location on crack propagation behavior were analyzed, which provided a scientific basis for optimizing the performance of chromium materials. The results show that cracks in polycrystalline chromium tend to fracture along grain boundaries and that stacking faults and holes are the main factors for crack propagation. As the grain size decreases, the crack passivation becomes more pronounced and the rate of crack expansion slows down. As the strain rate increases, the crystal structure of polycrystalline chromium changes more sharply, and the ultimate stress increases. At high strain rates, the direction of crack propagation changes. The degree of crack tip passivation is affected by the initial crack location, and the crack tip can be effectively passivated when it is located at the grain boundary, thus hindering crack propagation. The results of these studies reveal the influence of multiple factors on the crack propagation mechanism of polycrystalline chromium and provide theoretical guidance for the reduction of chromium coating damage.

Research on the prediction of blasting fragmentation in open-pit coal mines based on KPCA-BAS-BP

The blasting block size of open-pit mines is influenced by many factors, and the influencing factors have a very complex nonlinear relationship. Traditional empirical formulas and a single neural network model cannot meet the requirements of modern blasting safety. To improve the prediction accuracy of blasting block size, the measured data of Beskuduk open-pit coal mine is used as training and testing samples. Seven factors including rock tensile strength, rock compressive strength, and blast hole spacing are selected as input variables of the prediction model. The average size of blasting fragmentation X50 is used as the output variable of the prediction model. The kernel principal component analysis (KPCA) is adopted to reduce the dimensionality of the input variables. The beetle antennae search algorithm (BAS) is selected to optimize the parameters of the initial weights and thresholds of the back propagation (BP) neural network. Finally, prediction model of blasting fragmentation in open-pit coal mine based on KPCA-BAS-BP is established. The results show that the average relative error of the model is 1.77%, and the root mean square error is 1.52%. Compared with the unoptimized BP neural network and the BP neural network optimized by the artificial bee colony algorithm (ABC) model, this model has higher prediction accuracy and is more suitable for predicting the blasting block size of open-pit coal mines, it provides a new method for predicting the fragmentation of blasting under the influence of multiple factors, filling the gap in related theoretical research, and has certain practical application value.

Multisource information fusion for safety risk assessment in complex projects considering dependence and uncertainty.

The success of tunneling projects is crucial for infrastructure development. However, the potential leakage risk is particularly challenging due to the inherent uncertainties and fuzziness involved. To address this demanding challenge, a hybrid approach integrating the copula theory, cloud model, and risk matrix, is proposed. The dependence of multiple risk-related influential factors is explored by the construct of the copula-cloud model, and the diverse information is fused by applying the risk matrix to gain a crisp risk result. A case study is performed to test the applicability of the proposed approach, in which a risk index system consisting of nine critical factors is developed and Sobol-enabled global sensitivity analysis (GSA) is incorporated to investigate the contributions of different factors to the risk magnitude. Key findings are as follows: (1) Risk statuses of the studied three tunnel sections are perceived as under grade I (safe), II (low-risk), and III (medium-risk), respectively, and the waterproof material aspect is found prone to deteriorating the tunnel sections. Furthermore, the proposed approach allows for a better understanding of the trends in the risk statuses of the tunnel sections. (2) Strong interactions between influential factors exist and exert impacts on the final risk results, proving the necessity of studying the factor dependence. (3) The developed neutral risk matrix presents a strong robustness and displays a higher recognition capacity in risk assessment. The novelty of this research lies in the consideration of the dependence and uncertainty in multisource information fusion with a hybrid copula-cloud model, enabling to perform a robust risk assessment under different risk matrices with varying degrees of risk tolerance.

Uncertainty prediction of conventional gas production in Sichuan Basin under multi factor control

The establishment of a natural gas production model under multi factor control provides support for the formulation of planning schemes and exploration deployment decisions, and is of great significance for the rapid development of natural gas. Especially the growth rate and decline rate of production can be regulated in the planning process to increase natural gas production. The exploration and development of conventional gas in the Sichuan Basin has a long history. Firstly, based on the development of conventional gas production, the influencing factors of production are determined and a production model under multi factor control is established. Then, single factor analysis and sensitivity analysis are conducted, and multi factor analysis is conducted based on Bayesian networks. Finally, combining the multivariate Gaussian mixture model and production sensitivity analysis, a production planning model is established to predict production uncertainty under the influence of multiple factors. The results show that: 1) the production is positively correlated with the five influencing factors, and the degree of influence is in descending order: recovery rate, proven rate, growth rate, decline rate, and recovery degree. After being influenced by multiple factors, the fluctuation range of production increases and the probability of realization decreases. 2) The growth rate controls the amplitude of the growth stage, the exploration rate and recovery rate control the amplitude of the stable production stage, the recovery degree controls the amplitude of the transition from the stable production stage to the decreasing stage, and the decreasing rate controls the amplitude of the decreasing stage. 3)The article innovatively combines multiple research methods to further obtain the probability of achieving production under the influence of multiple factors, providing a reference for the formulation of production planning goals.

Do Smart Loading Zones help reduce traffic congestion? A causal analysis in Pittsburgh

Rising demand for ride-hailing services and e-commerce delivery intensifies competition for urban curbside spaces, leading to uncoordinated travel behavior, increased traffic congestion and social costs. One possible solution to address those issues is Smart Loading Zones (SLZs), equipped with advanced technologies to optimize curbside use. Yet, the real-world impact of SLZs on traffic flow is unclear due to a lack of real-world data and rigorous studies investigating SLZ’s causal effect on traffic speed. With granular speed data and real-world implementations of SLZs from Pittsburgh, PA, this study applies the regression discontinuity design method to rigorously examine the causal impact of SLZs on traffic speed in the downtown network. The results showed that the introduction of SLZs could enhance the traffic speed of the nearby road segments by 4.5%, while controlling for the underlying trend of speed and multiple influential factors such as time, weather, and road characteristics. In addition, SLZs with a short length could statistically improve traffic speed but those with a long length exert no significant effect. These heterogenous effects might be attributed to the weak enforcement at the time of SLZ deployment in Pittsburgh. The results confirmed the overall positive impact of SLZs on improving congestion. However, policies such as effective dimension planning and robust enforcement policies are essential to maximize the benefits of SLZs.

Dynamic analysis of TBM multi-gear parallel transmission system considering the influence of multiple factors

Dynamic analysis of TBM multi-gear parallel transmission system considering the influence of multiple factors

A Comprehensive Flow–Mass–Thermal–Electrochemical Coupling Model for a VRFB Stack and Its Application in a Stack Temperature Control Strategy

In this work, a comprehensive multi-physics electrochemical hybrid stack model is developed for a vanadium redox flow battery (VRFB) stack considering electrolyte flow, mass transport, electrochemical reactions, shunt currents, and as heat generation and transfer simultaneously. Compared with other VRFB stack models, this model is more comprehensive in considering the influence of multiple factors. Based on the established model, the electrolyte flow rate distribution across cells in the stack is investigated. The distribution and variation in shunt currents, single-cell current and single-cell voltage are analyzed. The distribution and variation in temperature and heat generation and heat transfer are also researched. It can be found that the VRFB stack temperature will exceed 40 °C when operating at 60 A and 100 mA cm−2 at an ambient temperature of 30 °C, which will lead to electrolyte ion precipitation, affecting the performance and safety of the battery. To control the stack temperature below 40 °C, a new tank cooling control strategy is proposed, and the suitable starting cooling point and the controlled temperature are specified. Compared with the common room cooling strategy, the new tank cooling strategy reduces energy consumption by 27.18% during 20 charge–discharge cycles.

Improving the ERA5-Land Temperature Product through a Deep Spatiotemporal Model That Uses Fused Multi-Source Remote Sensing Data

Temperature is a crucial indicator for studying climate, as well as the social and economic changes in a region. Temperature reanalysis products, such as ERA5-Land, have been widely used in studying temperature change. However, global-scale temperature reanalysis products have errors because they overlook the influence of multiple factors on temperature, and this issue is more obvious in smaller areas. During the cold months (January, February, March, November, and December) in the Yellow River Basin, ERA5-Land products exhibit significant errors compared to temperatures observed by meteorological stations, typically underestimating the temperature. This study proposes improving temperature reanalysis products using deep learning and multi-source remote sensing and geographic data fusion. Specifically, convolutional neural networks (CNN) and bidirectional long short-term memory networks (BiLSTM) capture the spatial and temporal relationships between temperature, DEM, land cover, and population density. A deep spatiotemporal model is established to enhance temperature reanalysis products, resulting in higher resolution and more accurate temperature data. A comparison with the measured temperatures at meteorological stations indicates that the accuracy of the improved ERA5-Land product has been significantly enhanced, with the mean absolute error (MAE) reduced by 28.7% and the root mean square error (RMSE) reduced by 25.8%. This method obtained a high-precision daily temperature dataset with a 0.05° resolution for cold months in the Yellow River Basin from 2015 to 2019. Based on this dataset, the annual trend of average temperature changes during the cold months in the Yellow River Basin was analyzed. This study provides a scientific basis for improving ERA5-Land temperature reanalysis products in the Yellow River Basin and offers theoretical support for climate change research in the region.

Peroxymonosulfate promoted dioxygen activation with Mn(II)-nitrilotriacetic acid complexes for sulfadiazine degradation

In the field of peroxymonosulfate (PMS) activation technology, there is a pressing need to reduce PMS consumption and enhance its utilization rate. The present study demonstrates that the introduction of dissolved oxygen (DO) into the Mn(II)-nitrilotriacetic acid (NTA)-activated PMS system significantly enhances the degradation efficiency of sulfadiazine and increases the PMS utilization rate from approximately 15.0 to 41.3 %. Mechanistic analysis reveals that the Mn(II)-NTA/PMS system generates sulfate radicals as well as intermediate valent manganese species in the absence of DO; while in the presence of DO, Mn(II) is oxidized to Mn(III) by dioxygen to form superoxide anions and Mn(III), which can be further oxidized by PMS to higher valence states such as Mn(V) and Mn(VII). Consequently, the production of free radicals decreases while intermediate valent manganese species become more abundant. Additionally, O2•− can also reduce both Mn(VII) and Mn(IV) back to their lower oxidation state (Mn(II)). The cooperative interactions between these active species enhance the efficiency of catalytic cycles of manganese species. Moreover, the influence of multiple factors, the degradation products, and their associated toxicity assessment were investigated. Overall, this research provides valuable insights into the design of highly efficient PMS and DO activation systems.

Isomer engineering of benzofuran derived AIE luminogens: Synthesis, mechanochromism, pH responsive fluorescent switching, cell-imaging and Fe3+ sensing

The influence of multiple factors often leads to the unexpected performances of the designed AIEgens. It is difficult to precisely conclude the influence of the substituted sites and role of isomers on the photophysical properties of the AIEgens which therefore brings uncertainty in the molecular design strategies. Isomer engineering of AIEgens is a less explored domain. There are only a few reports that substantiate the effects and positions of the substituents on the AIE properties. The present investigation explores two isomeric benzofuran-derived luminogens GBY-1 and GBY-4, both featuring a TPE moiety and showcasing AIE and AIEE properties respectively inherited from TPE. The isomeric effect resulting from TPE incorporation at different positions across benzofuran significantly influenced their photophysical properties, mechanofluorochromic properties, and AIE effect. Their distinctive luminogenic features were evident in mechanochromic property as well as in cancer cell imaging. GBY-1 was found to be uniformly dispersed in the cytoplasm, not co-localized with the nucleus, while GBY-4 accumulated near the cell membrane. Furthermore, post-functionalization of one of the luminogens, GBY-1, derived another AIEgen, GBY-5 with a dramatic improvement in the PLQE along with its ability to selectively sense Fe3+ in aqueous environments, within a detection limit of 0.00035 mM.

Social-Cultural Factors Influence on Management of Shared Sanitation, in Nakuru Town West Slums

Sustainable Development Goal (SDG) target 6.2 calls for 'adequate and equitable sanitation for all.' However, rapid urbanization in developing countries has led to the growth of slums, where access to private toilets is impractical. Evident studies showed that shared toilets are more often poorly managed with adverse harmful health risks such as diarrheal diseases, environmental pollution, and economic deprivations. The study's specific objective was to establish social-cultural factors influencing the management of shared sanitation in Nakuru Town's west slums, Nakuru County, Kenya. The study adopted a convergent parallel mixed-method design involving 288 household heads selected through a cluster and random sampling technique. Data was collected using a structured questionnaire and interview guides. Descriptive statistics and inferential statistics was computed. The study findings indicated that the majority, 74.7%, of shared sanitation was poorly managed. The study established statistically significant associations of secondary education (p=0.024), marital status (p=0.025), user satisfaction (p=0.001), household sharing (p=0.000), social norms (p=0.001), cultural beliefs (p=0.002), Rituals on use and cleaning toilet (p=0.038), Privacy and modesty concerns (p=0.002) and management of shared sanitation. In conclusion, a large proportion of households in slums used poorly managed shared sanitation due to the influence of multiple factors like users' satisfaction, Household sharing, marital status, social norms, and cultural beliefs, thus polluting the public health of the place. The study recommended that the Government and all other agencies implementing sanitation promotion interventions should understand the social-cultural practices of the target communities and articulate this knowledge to tailor sanitation initiatives effectively. Future studies should focus on implementing and assessing the effectiveness of behavioral interventions.

Combined Influence of Multiple Factors on Lung Cancer and Anxiety: A Probit Model Analysis

Lung cancer remains a leading cause of cancer-related mortality worldwide, significantly impacting public health. Concurrently, anxiety is a prevalent psychological disorder known to influence the development and progression of various cancers. This research paper aims to examine the combined influence of various factors, including demographic characteristics, environmental exposures, and physical conditioning data, on the incidence of lung cancer and anxiety. Given the binary nature of both lung cancer and anxiety outcomes, the analyses will first employ separate binary probit regression models to identify significant predictors for each condition independently. Then, joint modeling techniques will be implemented with dual purposes. First, by comparing the results of the individual and joint models, the reliability and robustness of the findings will be enhanced through cross-validation. Second, joint models will enable an investigation into potential endogeneity between lung cancer and anxiety. Addressing this endogeneity is crucial as it can potentially improve model robustness and provide deeper insights into the interrelationship between these two health outcomes. For the study purpose, the demographic factors considered include age and gender. Environmental factors encompass smoking history, alcohol consumption, and peer pressure. Physical conditioning data includes pre-existing health conditions such as yellow fingers, anxiety, chronic disease, fatigue, allergy, wheezing, coughing, shortness of breath, swallowing difficulty, and chest pain. By leveraging advanced statistical modeling techniques, this research seeks to uncover nuanced relationships and potential causal pathways that may exist between lung cancer and anxiety. The findings from this study will contribute to the existing body of knowledge by providing additional case study showing the relationship among a multitude of factors on lung cancer and anxiety, respectively. Also, the endogeneity checking among lung cancer and anxiety may enhance the efficiency of models done by others in the future. The research paper's analysis on lung cancer incidences reveals that age and wheezing are significant predictors. In examining anxiety levels, smoking emerged as a significant predictor, indicating a higher likelihood of anxiety among smokers. In addition, the joint probit models confirmed these findings, with age and wheezing significantly predicting lung cancer incidence, and smoking significantly predicting anxiety levels. No significant endogeneity was observed between lung cancer and anxiety, suggesting that these health outcomes are influenced by different sets of factors. These findings underscore the importance of considering demographic, environmental, and physical conditioning data in understanding and addressing lung cancer and anxiety, and checking their potential endogeneity

A Study on the Thermal Physical Property Changes in Formation Rocks during Rapid Preheating of SAGD

The incorporation and application of SAGD rapid preheating technology effectively solve the problem of the long preheating cycle in the SAGD steam cycle. The thermal properties of reservoir rocks are an important factor affecting the heat transfer law governing their formation during the rapid preheating process of SAGD. During the rapid preheating process of SAGD, the expansion of the reservoir and the steam cycle process will cause changes in the pore permeability, oil-water saturation, and temperature of the reservoir rocks, which will inevitably lead to differences in the changes that occur in the thermal properties of the reservoir rocks, compared to those under the influence of a single factor. In this study, experiments were conducted to determine the thermal properties of reservoir rocks under the combined influence of pore permeability, oil-water saturation, and temperature, quantitatively characterizing the changes in the thermal properties of reservoir rocks. Using the orthogonal method to design and carry out experiments for determining the thermal properties of reservoir rocks, the main factors affecting the thermal properties of reservoir rocks and the significance of each factor’s impact on the thermal properties of reservoir rocks were determined through intuitive analysis and variance analysis of the experimental results. Finally, a regression equation that can characterize changes in the thermal properties of reservoir rocks under the influence of multiple factors was obtained through multiple nonlinear regressions of the experimental results.

Hydrogeochemical features, genesis, and quality appraisal of confined groundwater in a typical large sedimentary plain.

The confined groundwater of arid sedimentary plains has been disturbed by long-term anthropogenic extraction, and its hydrochemical quality is required for sustainable development. The present research investigates the hydrochemical characteristics, formation, potential health threats, and quality suitability of the confined groundwater in the central North China Plain. Results show that the confined groundwater has a slightly alkaline nature in the study area, predominantly dominated by fresh-soft Cl-Na and HCO3-Na types. Water chemistry is governed by water-rock interactions, including dissolution of evaporites and cation exchange. Approximately 97% of the sampled confined groundwaters exceed the prescribed standard for F-. It is mainly due to geological factors such as mineral dissolution, cation exchange, and competitive adsorption of HCO3 - and may also be released from compacted soils because of groundwater extraction. Enriched F- in the confined groundwater can pose an intermediate and higher non-carcinogenic risk to more than 90% of the population. It poses the greatest health threat to the population in the north-eastern part of the study area, especially to infants and children. For sustainable development, the long-term use of confined groundwater for irrigation in the area should be avoided, and attention should also be paid to the potential soil salinization and infiltration risks. In the study area, 97% of the confined groundwaters are found to be excellent or good quality for domestic purposes based on Entropy-weighted Water Quality Index. However, the non-carcinogenic health risk caused by high contents of F- cannot be ignored. Therefore, it is recommended that differential water supplies should be implemented according to the spatial heterogeneity of confined groundwater quality to ensure the scientific and rational use of groundwater resources. PRACTITIONER POINTS: The hydrochemistry quality of confined groundwater in an arid sedimentary plain disturbed by long-term anthropogenic extraction was investigated. The suitability of confined groundwater for multiple purposes such as irrigation and drinking were evaluated. The hydrochemical characteristics and formation mechanism of confined groundwater under the influence of multiple factors were revealed.

Multifactor analysis of the infiltration characteristics of film hole irrigation under muddy water conditions

Film hole irrigation under muddy water conditions is a new and effective water-saving irrigation technology. In order to determine the influence of multiple factors on the infiltration process of film hole irrigation under muddy water conditions, 12 sets of indoor infiltration tests were conducted to investigate the effects of four key influencing factors (muddy water sand content, hole diameter, soil bulk density, and infiltration time) on the infiltration characteristics of irrigation with film holes under muddy water conditions, in this study. Based on the experimental data, accurate and effective soil water infiltration and vertical and horizontal wetting front transport models were constructed. Based on the modeling results, the standard regression coefficients of each influencing factor against the fitted parameters were calculated and the effects of the factors on the fitted parameters were analyzed. Error analysis showed that both models could effectively simulate the soil water infiltration process under experimental conditions. Infiltration time was the dominant factor influencing the cumulative infiltration per unit of film hole area, followed by hole diameter, muddy water sand content and lastly, soil bulk density. Infiltration time was also the main influencing factor of the vertical wetting front transport distance, followed by soil bulk density, muddy water sand content, and lastly, hole diameter. Similarly, infiltration time exerted the greatest effect on the horizontal transport distance, followed by hole diameter, soil bulk density and muddy water sand content. The model validation revealed that both the calculated and measured values were distributed around the 1:1 line, reflecting the accuracy of the models. The results of this study can provide theoretical support for the design of film hole irrigation systems under muddy water conditions.

Interfacial cohesion model of ultra‐high performance concrete wet joints under the influence of multiple factors

AbstractThe interfacial cohesion between precast normal concrete (NC) and cast‐in‐place ultra‐high performance concrete (UHPC) is an important index to evaluate their interfacial bond strength, which is of great importance for the application of UHPC as a connection material for precast structural bridges. Interfacial cohesion is related to several influencing factors. However, there needs to be more research on the interrelationship model between multiple influencing factors and interfacial cohesion. This study took the UHPC wet joint in a precast concrete structure as the object. First, the relationship between the interface cohesion of UHPC wet joint and substrate strength, UHPC age, interfacial roughness, interfacial moisture content, and curing method was studied; The result shows that the key factors affecting interfacial cohesion include UHPC age, interface roughness, and substrate strength, with interfacial moisture content potentially playing a secondary role. Second, the failure types of the interface zone surface by using digital image correlation (DIC) are divided into three categories. Finally, the quantitative mathematical model of interfacial cohesion under the coupling effect of multiple factors was established based on the above four factors. The model is in good agreement with the experimental data.

Risk for Waterborne Transmission and Environmental Persistence of Avian Influenza Virus in a Wildlife/Domestic Interface in Mexico.

Aquatic habitats provide a bridge for influenza transmission among wild and domestic species. However, water sources pose highly variable physicochemical and ecological characteristics that affect avian influenza virus (AIV) stability. Therefore, the risk of survival or transmissibility of AIV in the environment is quite variable and has been understudied. In this study, we determine the risk of waterborne transmission and environmental persistence of AIV in a wild/domestic bird interface in the Central Mexico plateau (North America) during the winter season using a multi-criteria decision analysis (MCDA). A total of 13 eco-epidemiological factors were selected from public-access databases to develop the risk assessment. The MCDA showed that the Atarasquillo wetland presents a higher persistence risk in January. Likewise, most of the backyard poultry farms at this wild-domestic interface present a high persistence risk (50%). Our results suggest that drinking water may represent a more enabling environment for AIV persistence in contrast with wastewater. Moreover, almost all backyard poultry farms evidence a moderate or high risk of waterborne transmission especially farms close to water bodies. The wildlife/domestic bird interface on the Atarasquillo wetland holds eco-epidemiological factors such as the presence of farms in flood-prone areas, the poultry access to outdoor water, and the use of drinking-water troughs among multiple animal species that may enhance waterborne transmission of AIV. These findings highlight the relevance of understanding the influence of multiple factors on AIV ecology for early intervention and long-term control strategies.

Bicharacteristic probability of detection of crack under multi-factor influences using alternating current field measurement technique

Alternating Current Field Measurement (ACFM) technique has been widely used in various fields such as oil & gas, aerospace areas. However, during the detection process, the probability of detection (POD) is influenced by multi-factors such as lift-off height, scanning angle and detection speed. In this paper, a bicharacteristic probability of detection (BPOD) model is developed for quantifying the crack detection reliability using integrated Bx and Bz signals in the ACFM technique. A multidimensional BPOD model is established to study the influence of multiple factors on the detection probability of cracks using ACFM technique. A Bayesian network-based method is proposed to reverse the hierarchical impact weights of influence factors on the BPOD of the ACFM technique. The results show that the BPOD model considering both Bx and Bz response signals can evaluate smaller defects than the conventional POD model. The multiple influencing factors can substantially decrease the BPOD of cracks. The hierarchical impact weights on BPOD for cracks are ranked as follows: lift-off height, detection speed, personnel involved in the detection process and scanning angle. This approach can retrospectively find the potential contributors to the missed detections based on the BPOD.

Sex-Moderated Divergence between Adult Child and Parental Dietary Behavior Patterns in Relation to Body Mass Condition-Evaluating the Mediating Role of Physical Activity: A Cross-Sectional Study.

The main objective of this study was to explore the dietary behaviors of parents and their adult children, focusing on patterns, potential intrinsic and extrinsic predictors of body mass, and determinants of becoming overweight. Non-probability, cross-sectional sampling was used to select participants from a university student population. Young adults (19-21 years of age, n = 144) and their parents were examined. The data of those family pairs with complete sets of results were used. Dietary patterns and physical activity were assessed with questionnaires (QEB and IPAQ), and body height, weight measurements, and body mass indexes were calculated. A cophylogenetic approach with tanglegrams and heatmaps was used to study patterns, while predictors of body mass index were identified using multiple linear regression, stepwise logistic regression, and mediation analysis procedures. Cophenetic statistics confirmed significant incongruence between fathers and sons, confirmed by Baker's Gamma correlation (rBG = 0.23, p = 0.021), and mothers and daughters (rBG = 0.26, p = 0.030). The relationships between the dietary patterns of the fathers and daughters, as well as mothers and sons, were of medium strength (rBG = 0.33, p = 0.032, rBG = 0.43, p = 0.031; respectively). Most of the patterns were mixed. Fast food, fried meals, alcoholic drinks, energy drinks, and sweetened beverages were associated significantly with being overweight. Significant intrinsic predictors of excessive weight in young adults were sex (b = 2.31, p < 0.001), PA (b = -0.02, p < 0.001), and eating fermented milk and curd cheese (b = -0.55, p = 0.024), while extrinsic (parental) predictors included eating fast food and fried meals (b = -0.44, p = 0.049). Both physical activity and dietary behaviors independently determined the sons' overweight status (b = -1.25, p = 0.008; b = -0.04, p < 0.001; respectively); while only PA did in daughters (b = -0.04, p < 0.001). No mediating effects of physical activity were observed. Adult children and parental dietary patterns were divergent, reflecting the influence of multiple factors on a child's dietary habits. However, this divergence is moderated by sex. Reciprocal interactions between dietary intake-particularly positive dyads such as fruits and vegetables, fermented milk, and curd cheese-and physical activity significantly impacted children's body mass index (BMI). The study of dietary patterns in conjunction with physical activity (both as independent determinants), particularly in relation to the link between overweight/obese children and overweight/obese parents, presents a separate challenge.