Interaction Of Multiple Variables Research Articles

Transitioning towards more plant-based diets: sharing expert knowledge through a system lens

Transitioning towards more plant-based protein diets is essential for public and planetary health. Current research about consumption practices of protein sources provides limited insight in the multidisciplinary nature and interconnectivity of the food environment. This study aimed to collect mental models of review authors by synthesizing both their implicit and explicit system views into an overarching system view. Published reviews were used to select participants and identify variables that explain the protein transition in relation to the food environment. To overcome differences in disciplines and scale levels (e.g. individual, interpersonal, environmental), variables were organized according to the Determinants of Nutrition and Eating Framework. Eight review authors shared their mental models in an interview. Participants were asked to construct a causal loop diagram (CLD), a tool proven valuable in making one's ontology explicit to others. Implicit system views in narrative were converted into CLDs using a coding framework. The overarching system view suggests that a multitude of feedback loops sustain current consumption patterns of protein sources, for example by reinforcement through habit, availability and peer support. Several aspects require further research, such as variable relationships that were subject to disagreement and the lack of reciprocity between the physical and social elements of the food environment. In addition, knowledge gaps were exposed, including long-term behaviour and interaction of multiple variables. As a boundary object, the overarching system view can facilitate the direction of future research. The findings underscore the interconnected nature of many disparate elements within the food environment, stressing the need for holistic methods like systems thinking. These are essential in developing a systemic understanding and facilitating the transition towards more plant-based diets.

A robust carbonation depth model in recycled aggregate concrete (RAC) using neural network

Carbonation depth involves complex physical process and interactions of multiple variables and is thus extremely complicated to predict in concrete structures. It is imperative to quantify this depth due to its vital role in the corrosion of rebars in recycled aggregate concrete (RAC). This paper developed a novel carbonation depth prediction model from a large database of 445 experimental results using artificial neural network (ANN). The relative importance and effect of the independent parameters in the carbonation depth are identified using Garson index and parametric analysis, respectively. Among all the architectures considered, the N 8-10-1 having 10 nodes in the hidden layer provided the best prediction in good agreement with experimental results. The model demonstrated superior performance relative to existing carbonation depth equations in the literature. Despite the presence of fuzziness in the data, the effect of each variable in the development of carbonation is explored in great detail. The model proposed here can provide a robust prediction of carbonation depth that can be used as a basis for assessing the structural health of recycled aggregate concrete structures.

Influence of clinical factors on the protective or deleterious impact of genetic variants in orthodontically induced external root resorption: an observational study

BackgroundPrediction of susceptibility to Orthodontically Induced External Apical Root Resorption (OIEARR) has been hampered by the complex architecture of this multifactorial phenotype. The aim of this study was to analyze the impact of the interaction of multiple variables in the susceptibility to OIEARR.MethodsThe study evaluated 195 patients requiring orthodontic treatment. Nine clinical and treatment variables, single nucleotide polymorphisms (SNPs) from five genes and variables interactions were analyzed as risk factors for OIEARR using a multiple linear regression model.ResultsThe model explained 29% of OIEARR variability (ANOVA: p < 0.01). Duration of treatment was the most important predictor and gender was the second, closely followed by premolar extraction. For genes encoding osteoprotegerin (OPG), the receptor activator of nuclear factor κ B (RANK) and the IL1 receptor antagonist (IL1RN), the effect of analyzed variants changed from protective to deleterious depending on the duration of treatment and the age of the patient.ConclusionsThis work shows that in OIEARR the impact of genetic susceptibility factors is dynamic changing according to clinical variables.

Coupling effect of key parameters of heat recovery components on the HAT cycle performance

Humid Air Turbine (HAT) cycle that uses a water-air mixture as a working fluid has a significant advantage in the distributed generation technologies and combined heat and power. The feature of the HAT cycle is that air humidification is carried out at a variable temperature. This cycle is considered as one of the optimal humidified gas turbine cycles to achieve the energy cascade utilization. However, most studies typically use the method of a single variable to investigate the coupled process of humidification and heat recovery, which limits the further performance improvement of the HAT cycle. Herein, we study the interactions among air humidification, heat recovery and system performance to elaborate the effects of interactive variables on the HAT cycle performance. Considering the complexity of the interaction of water-air ratio, aftercooler effectiveness and recuperator effectiveness, a thorough numerical analysis was carried out from the following perspectives: the thermodynamic correlation between components and systems was investigated by controlling a single parameter; the interaction of multiple variables was performed with identical turbine inlet temperature (TIT) and pressure ratio (PR) conditions; and the coupling relationship between interactive variables with a variation of TIT and PR conditions. A thorough analysis revealed that the variables that significantly impact the HAT cycle efficiency are successively RE, W/A, and AE. The analysis of the coupling effects of interactive variables under different TITs is consistent with the above results. As the PR increases, the W/A and AE have a more significant effect on HAT cycle efficiency and the effect of RE on the HAT cycle efficiency greatly diminishes. The HAT cycle efficiency, specific work output, and heat recovery achieved 43.9%, 556 kJ/kg, 5505.33 kW, where its corresponding TIT, PR, W/A, AE, RE values are 1280 °C, 8, 1.5,0.75, 0.9, respectively. Overall, a thorough analysis of interactive variables is of great significance to fully understand the effect of heat recovery on the efficiency enhancement and specific work output improvement from the thermodynamic perspective.

Examining intercollegiate athletic department employees’ workplace behaviors using latent profile analysis

ABSTRACT Research examining workplace behaviors has increased over the last 20 years; however, much of this research within the sport context has looked at these issues using a variable-centered approach (e.g., examining work–life interface of mothers). This type of research is useful in describing how work behaviors manifest within specific populations. It does not, however, tell us about how the interaction of multiple variables impacts outcomes. Using social role theory as the guiding framework, the purpose of the study was to examine the presence of naturally occurring groups across a range of workplace behaviors within intercollegiate athletic department employees (N = 4,672) using latent profile analysis. Results indicate naturally occurring groups are present, and contrary to prior research, women were overrepresented in groups with lower levels of conflict (i.e., work–family and family–work) and underrepresented in groups with the higher levels of conflict, whereas men tended to be overrepresented in groups with higher levels of conflict and underrepresented in groups with lower levels of conflict. Further, both men and women with children were overrepresented in the profiles with higher levels of conflict. This work has important theoretical and practical implications for workplace behavior and organizational leadership.

The macroecology of fish migration

AbstractAimWe still lack a consensus on the main variables driving changes in migratory strategies. Different hypotheses have been proposed: productivity, energy, environmental heterogeneity, and genetic predisposition. This work takes an integrative view and analyses migrations from a macroecological perspective estimating the extent to which different environmental variables and historic factors influence migratory life histories.LocationGlobal.Time periodCurrent.Major taxa studiedActinopterygian fishes.MethodsUsing public domain museum records, global repositories, and global measures of temperature, productivity, precipitation and heterogeneity, we spatially analysed the distribution of anadromous, catadromous, amphidromous, potamodromous and oceanodromous migratory fish using 1,676 species and compared it to 1,616 non‐migratory fishes. After analysing the individual roles of productivity and temperature in shaping biodiversity, we conducted path analyses including several environmental variables and principal coordinates of phylogenetic structure (PCPS).ResultsThe different migratory strategies are not evenly distributed around the globe and phylogeny is a relevant variable in shaping current patterns. Productivity is positively related to species richness, except for anadromy and potamodromy, for which we observed a unimodal curve. Temperature significantly drives migratory species richness (except for anadromy). The role of environmental heterogeneity, measured as temperature seasonality and annual range, is strongest for anadromous species, which helps explain their skewed distribution towards higher latitudes and why the kinetic energy hypothesis fails in explaining their richness patterns.Main conclusionsOverall, migratory fish richness can be explained by the interaction of multiple variables, such as productivity, temperature, environmental heterogeneity, and the role of phylogeny, but these variables interact differentially in each strategy, diverging most for the anomalous anadromous fishes. Integrating these results into a global framework to better understand the evolutionary and ecological dynamics of migration will help with predicting responses to anthropogenic climate change.

Predictors of throwing performance in amateur male cricketers: A musculoskeletal approach

Optimal throwing speed and accuracy is built on a complex interaction of multiple variables. Although strength and power has been associated with throwing speed in cricketers, the individual muscles that contribute to optimal function of the shoulder-complex has not been adequately explored in connection with throwing performance. Consequently, this study aimed to investigate the correlation between musculoskeletal variables and overhead throwing performance in cricketers. Thirty-two amateur male cricketers were tested using a battery of 16 tests (strength, flexibility, scapula positioning) as well as a throwing speed (TS) and a novel accuracy test (TA). Only two of the sixteen tests were correlated with throwing performance in the multiple regression analysis. Non-dominant hip abduction strength correlated positively with TS (p < 0.05): on average, a strength increase of 10 newtons (N) was associated with an increase in TS of 0.60 km/h (95% CI: 0.12–1.08). Non-dominant pectoralis minor length correlated positively with TA (p < 0.01): on average, a one-centimetre increase in the length correlated to an increase, of 0.633 points (95% CI: 0.225–1.041). This cross-sectional study demonstrated that from an array of musculoskeletal variables, only non-dominant hip abduction strength correlated with TS, while only non-dominant pectoralis minor length correlated with TA in amateur cricketers.

Correlation of NOD2 genotypes with Helicobacter pylori infection in a South‐European country

AbstractOutcome of Helicobacter pylori (H. pylori) infection in a specific individual is unpredictable and results from interaction of multiple variables, including host genetic factors. This study aimed to investigate if NOD2 mutations increased the risk of H. pylori infection and if it has any relationship with bacterial genotype or gastric histopathological modifications. This prospective study involved 86 patients (54 females; mean age, 48.7 ± 13.6 years) with positive 13C‐urea breath test (UBT) and a sex and age‐matched control group of 266 individuals, 64 of them with negative UBT. The three main NOD2 mutations (L1007fsinsC, R702W, and G908R) were obtained for all patients and controls. Fifty‐one infected patients were submitted to endoscopy with gastric biopsies. H. pylori was isolated, and genotypes were determined by PCR. Histopathological features were graded according to the updated Sydney system. Overall, NOD2 mutations were found in 14 patients (16.3%) and in 31 controls (11.7%) (OR = 1.40, 95% CI = 0.78‐2.50; P = .264). Genotype frequencies for L1007fsinsC (1.2% vs 0.8%), R702W (11.6% vs 7.6%) and G908R (5.8% vs 3.4%) were not statistically different between the two groups. A significant positive association was observed between NOD2 polymorphisms and peptic ulcer but only in univariate analysis. There were no other correlations with clinical variables, gastric histological patterns and H. pylori genotypes. NOD2 mutations are not associated with increased prevalence of H. pylori infection or more severe gastric histopathological modifications induced by this bacterium. However, such host polymorphisms could influence clinical manifestations.

Optimising drone flight planning for measuring horticultural tree crop structure

In recent times, multi-spectral drone imagery has proved to be a useful tool for measuring tree crop canopy structure. In this context, establishing the most appropriate flight planning variable settings is an essential consideration due to their controls on the quality of the imagery and derived maps of tree and crop biophysical properties. During flight planning, variables including flight altitude, image overlap, flying direction, flying speed and solar elevation, require careful consideration in order to produce the most suitable drone imagery. Previous studies have assessed the influence of individual variables on image quality, but the interaction of multiple variables has yet to be examined. This study assesses the influence of several flight variables on measures of data quality in each processing step, i.e. photo alignment, point cloud densification, 3D model building, and ortho-mosaicking. The analysis produced a drone flight planning and image processing workflow that delivers accurate measurements of tree crops, including the tie point quality, densified point cloud density, and the measurement accuracy of height and plant projective cover derived from individual trees within a commercial avocado orchard. Results showed that flying along the hedgerow, at high solar elevation and with low image pitch angles improved the data quality. Optimal flying speed needs to be set to achieve the required forward overlap. The impacts of each image acquisition variable are discussed in detail and protocols for flight planning optimisation for three scenarios with different drone settings are suggested. Establishing protocols that deliver optimal image acquisitions for the collection of drone data over horticultural tree crops, will create greater confidence in the accuracy of subsequent algorithms and resultant maps of biophysical properties.

Research on the evolution of participants collaboration mechanism in PPP model based on computer simulation: based on the old community renovation project

The system dynamic model (SD model) can simulate the dynamic change of the system from the overall perspective and carry out dynamic analysis of the structure, behavior and causality of the system by computer simulation under different assumptions. Therefore, to solve the problem of tripartite game between the government, private sector and owners which caused by the application of PPP model in the old community renovation, this paper establishes a three-party game model based on the evolutionary game theory and simulates the evolvement path of each participant by establishing SD Model with relevant computer Software. The research finds that: (1) the government, the community owners and the private sectors will eventually reach a stable and balanced state (supervision, participation, effort); (2) the government is dominant in the renovation, and the strategic choice of the private sectors and the community owners depends on the government’s strategy, the variables determined by the government and the relationship between these exogenous variables; (3) although a single variable could influence the strategic choice of each party, the formation of the final stable state depends on the interaction of multiple variables, and the government should handle the relationship between each stakeholders.

Abstract 4351: A neighborhood-wide association study (NWAS) in prostate cancer: A new methodologic approach

Abstract Background: Cancer results from complex interactions of multiple variables at biological, individual and social levels. However, comprehensive, empirical methods to assess social and neighborhood-level effects are limited. We propose a Neighborhood-Wide Association Study(NWAS), analogous to a genome-wide association study(GWAS), to comprehensively identify neighborhood signatures associated with disease. Methods: Pennsylvania State Cancer Registry data from 1995-2005 were linked to the 2000 U.S. Census data. In a successively more stringent multiphase approach, we evaluated the association between neighborhood exposures(n = 14,663, standard deviation adjusted census variables) and prostate cancer aggressiveness (n = 6,416 aggressive Stage&amp;gt;3/Gleason grade &amp;gt;7 cases vs. n = 70,670 non-aggressive Stage&amp;lt;3/Gleason grade&amp;lt;7 controls) in White men. Each phase accounted for age, year of diagnosis, spatial correlation, and multiple testing. We used generalized estimating equations in Phase 1 and Bayesian mixed effects models in Phase 2 to calculate odds ratios(OR) and credible intervals(CI). Variables meeting statistically significant thresholds after Bonferroni adjustment were identified and used in subsequent phases. In Phase 3, principal components analysis grouped correlated variables. Results: From 14,663 census variables, 17 variables that were most significantly associated with prostate cancer aggressiveness were identified. The top two hits related to transportation (OR = 1.05;CI = 1.001-1.09) and poverty (OR = 1.07;CI = 1.01-1.12). Significant associations between prostate cancer and income, housing, employment, and immigration were also found. Conclusions: This NWAS methodology addresses gaps in neighborhood and cancer research by proposing a standardized, agnostic evaluation of neighborhood using readily accessible data from the U.S. Census. This approach has implications for health disparities research and can be applied broadly to large-scale, public health data. Citation Format: Shannon Lynch, Nandita Mitra, Michelle Ross, Craig Newcomb, Karl Daily, Tara Jackson, Charnita Zeigler-Johnson, Harold Riethman, Charles Branas, Timothy Rebbeck. A neighborhood-wide association study (NWAS) in prostate cancer: A new methodologic approach. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4351.

Contrasting precipitation seasonality influences evapotranspiration dynamics in water‐limited shrublands

AbstractWater‐limited ecosystems occupy nearly 30% of the Earth, but arguably, the controls on their ecosystem processes remain largely uncertain. We analyzed six site years of eddy covariance measurements of evapotranspiration (ET) from 2008 to 2010 at two water‐limited shrublands: one dominated by winter precipitation (WP site) and another dominated by summer precipitation (SP site), but with similar solar radiation patterns in the Northern Hemisphere. We determined how physical forcing factors (i.e., net radiation (Rn), soil water content (SWC), air temperature (Ta), and vapor pressure deficit (VPD)) influence annual and seasonal variability of ET. Mean annual ET at SP site was 455 ± 91 mm yr−1, was mainly influenced by SWC during the dry season, by Rn during the wet season, and was highly sensitive to changes in annual precipitation (P). Mean annual ET at WP site was 363 ± 52 mm yr−1, had less interannual variability, but multiple variables (i.e., SWC, Ta, VPD, and Rn) were needed to explain ET among years and seasons. Wavelet coherence analysis showed that ET at SP site has a consistent temporal coherency with Ta and P, but this was not the case for ET at WP site. Our results support the paradigm that SWC is the main control of ET in water‐limited ecosystems when radiation and temperature are not the limiting factors. In contrast, when P and SWC are decoupled from available energy (i.e., radiation and temperature), then ET is controlled by an interaction of multiple variables. Our results bring attention to the need for better understanding how climate and soil dynamics influence ET across these globally distributed ecosystems.

Building a Model of Employee Training through Holistic Analysis of Biological, Psychological, and Sociocultural Factors

While theories of adult learning and motivation are often framed as being either biological, psychological, or sociocultural, they represent a more complex, integral process. To gain a more holistic perspective of this process, a study was designed to concurrently investigate relationships between a biological factor (age), psychological factors (motivation for training, perceived work limitations), and sociocultural factors (occupation, purpose of training, and work habits). The Assessment of Adult Literacy (NAAL) was used to elicit information about these factors in regards to work training. Data obtained was statistically correlated to age using the Spearman rank correlation coefficient. Results suggest that the interaction of multiple variables governs several shifts in motivation and need for training as adults age. Contrary to traditional theories of adult education, data suggest that a mixture of pedagogical and andragogical teaching styles is necessary for adult learners.

Exploring the Utility of Background and Cognitive Variables in Explaining Latent Differential Item Functioning: An Example of the PISA 2009 Reading Assessment

Differential item functioning (DIF) may be caused by an interaction of multiple manifest grouping variables or unexplored manifest variables, which cannot be detected by conventional DIF detection methods that are based on a single manifest grouping variable. Such DIF may be detected by a latent approach using the mixture item response theory model and subsequently explained by multiple manifest variables. This study facilitates the interpretation of latent DIF with the use of background and cognitive variables. The PISA 2009 reading assessment and student survey are analyzed. Results show that members in manifest groups were not homogenously advantaged or disadvantaged and that a single manifest grouping variable did not suffice to be a proxy of latent DIF. This study also demonstrates that DIF items arising from the interaction of multiple variables can be effectively screened by the latent DIF analysis approach. Background and cognitive variables jointly well predicted latent class membership.

A New Look at Barrier-Inlet Morphodynamics

Davis, R.A., 2013. A New Look at Barrier-Inlet Morphodynamics.Coastal morphodynamics is dependent on the interaction of multiple variables. An earlier publication demonstrated that the comparative influence of waves and tides was the fundamental relationship in coastal morphology. The discussion in this paper adds the important variables of tidal prism, sediment abundance, and sea-level change to the equation. Tidal prism is critical in that it can be the primary factor in morphodynamics if both wave and tidal climate are held constant. Abundant or scarce sediment availability can produce coastal morphology that would not develop otherwise. Because of the extremely slow rate of sea-level change, its impact is less prominent than the other variables and we see less evidence of its influence than the others, except in certain coastal reaches.

The Cost-Benefit Transfer Model: An Adaptation from Medicine

How does transfer work? When is transfer likely to come about, and when is it likely to fail? Several theorists view transfer as a complex process involving the interaction of multiple variables. The cost-benefit transfer model which we introduce in this article is in keeping with the trend to consider transfer a complex process accounting for a performer's perceptions. The model considers a performer's perception of need, sensibility, and effort to determine the likelihood of putting to use an idea learned in training. In contrast to existing models, the cost-benefit transfer model focuses on the perception of the performer and broadens the definition of the notion of use. The model predicts use through an elegant mathematical formula—specifically, the product of need and sensibility divided by effort. In support of this model, we cite case evidence of academic physicians who used what they learned from a yearlong training program.

Effective Risk Management Tools

Risk management proactively assesses the potential risks and benefits of health care interventions, including both drugs and medical devices. Risk management systematically identifies safety indications and establishes a risk management strategy for potential adverse events. Professionals trained in risk management have unique expertise in assessing the balance between risk and benefit. They play an important role in clinical study oversight (pre- and postmarketing) and in measuring outcomes of health care interventions. Assessing the risks and benefits of any therapy requires consideration of the complex interactions of multiple variables of the population to treat, including disease state, proposed treatment, and potential risks. Several key factors contribute to the effectiveness and acceptability of any treatment. For example, physician compliance with prescribing guidelines and a patient’s ability to tolerate a drug and to understand how to administer medications accurately will affect risk management assessments. Concurrent treatments (drug interactions) and diseases are also important considerations. Other variables include drug treatment ratios (placebo/active) and, increasingly, the use of screening tools to identify pharmacogenetic markers in particular patient populations that correlate with drug metabolism, efficacy, and other outcomes.

Intragroup Subgroup Attitude Clustering, External Intervention, and Intergroup Interaction Patterns: Toward a Dynamical Model of Protracted Intergroup Conflict

Scholars and practitioners working with protracted conflicts in polarized communities have long recognized the complex dynamics between intragroup disputes and intergroup relations in these settings. In fact, the multitude of factors interacting within and between groups in these conflicts, and their tendency to change over time, largely contributes to their intractable natures. Unfortunately, the ability of scholars to conduct research on such dynamic phenomena has been largely constrained by the atomistic, linear approach of traditional research models and methods. However, recent advances in dynamical systems theory have provided a new set of tools for developing computer simulations that allow us to model the dynamic patterns emerging from complex interactions of multiple variables over time. This paper presents one such model: a dynamical model of protracted intergroup conflict. Using data collected from Israeli and Palestinian communities during the current Intifada, we modeled the dynamic relations between conflict escalation and international intervention on intragroup subgroup attitude clustering and patterns of intergroup interactions. Next steps and refinements for the model are discussed.

Completed suicide: an update for the general psychiatrist

AbstractObjectives: To review the most recent information on completed suicide for the general adult psychiatrist.Methods: Literature review.Results: Suicide is the result of a complex interaction of multiple variables. Prediction is highly dependent on clinical evaluation. Predictive factors identify groups better than individuals. Prevention has both clinical and political implications.Conclusions: Reduced access to lethal methods (historically, from barbiturates to modified vehicle exhaust systems and paracetamol), attention to social factors (such as alcohol availability and employment levels) and clinical vigilance, coupled with adequate treatment of psychiatric disorders and close follow-up, should help to reduce suicide rates. Wider cultural issues (eg. religion) are poorly understood and require further research.