1,506 research outputs found
Decline in Telomere Length by Age and Effect Modification by Gender, Allostatic Load and Comorbidities in National Health and Nutrition Examination Survey (1999-2002)
Background: This study aims to assess the decline in telomere length (TL) with age and evaluate effect modification by gender, chronic stress, and comorbidity in a representative sample of the US population. Methods: Cross-sectional data on 7826 adults with a TL measurement, were included from the National Health and Nutrition Examination Survey, years 1999–2002. The population rate of decline in TL across 10-year age categories was estimated using crude and adjusted regression. Results: In an adjusted model, the population rate of decline in TL with age was consistent and linear for only three age categories: 20–29 (β = -0.0172, 95% CI: -0.0342, -0.0002), 50–59 (β = -0.0182, 95% CI: -0.0311, -0.0054) and 70–79 (β = -0.0170, 95% CI: -0.0329, -0.0011) years. The population rate of decline in TL with age was significantly greater for males and those with high allostatic load and a history of comorbidities. When the population rate of decline in TL was analyzed by gender in 10-year age bins, a fairly consistent yet statistically non-significant decline for males was observed; however, a trough in the rate was observed for females in the age categories 20–29 years (β = -0.0284, 95% CI: -0.0464, -0.0103) and 50–59 years (β = -0.0211, 95% CI: -0.0391, -0.0032). To further elucidate the gender difference observed in the primary analyses, secondary analyses were conducted with reproductive and hormonal status; a significant inverse association was found between TL and parity, menopause, and age at menopause. Conclusions: TL was shorter with increasing age and this decline was modified by gender, chronic stress and comorbidities; individuals with chronic morbidity and/or chronic stress and females in their twenties and fifties experienced greater decline. Female reproductive factors, i.e., parity and menopause, were associated with TL
An extended cohesive damage model study of geometrical ratio effects on failure mechanisms of functionally graded sandwiches with multi-layered cores
Stein Coverage: a Variational Inference Approach to Distribution-matching Multisensor Deployment
This paper examines the spatial coverage optimization problem for multiple
sensors in a known convex environment, where the coverage service of each
sensor is heterogeneous and anisotropic. We introduce the Stein Coverage
algorithm, a distribution-matching coverage approach that aims to place sensors
at positions and orientations such that their collective coverage distribution
is as close as possible to the event distribution. To select the most important
representative points from the coverage event distribution, Stein Coverage
utilizes the Stein Variational Gradient Descent (SVGD), a deterministic
sampling method from the variational inference literature. An innovation in our
work is the introduction of a repulsive force between the samples in the SVGD
algorithm to spread the samples and avoid footprint overlap for the deployed
sensors. After pinpointing the points of interest for deployment, Stein
Coverage solves the multisensor assignment problem using a bipartite optimal
matching process. Simulations demonstrate the advantages of the Stein Coverage
method compared to conventional Voronoi partitioning multisensor deployment
methods
Assessment of Pesticide Use in Major Vegetables From Farmers\u27 Perception and Knowledge in Dhading District, Nepal
A field study was carried out to assess the pesticide use status in major vegetable crops from farmers\u27 perception and knowledge in Dhading, Nepal in 2019. Field study was carried with 100 commercial farmer\u27s using semi-structure questionnaire by face to face interview. This study was analyzed by categorization of farmers into small holder (51) and large holder (49) groups on the basis of mean area of vegetable cultivation (6.48 ropani). The highest amount of pesticides is needed in tomato in both large holders and small holders according to the farmer\u27s experience. Among the study farmer\u27s, 41% of them spray the pesticides by making a cocktail or mixed method and 56% follow the waiting period of 3-5 days in both of the cases. A significant positive correlation was found at 5% level of significance between the knowledge and practice pattern of waiting period of the pesticides and negative correlation was found between the Personal Protective equipment score and health hazard score. Headache was the major health hazards faced by the farmers which was higher in small holders (66.7%) as compared to the large holders (46.9%). Mask was the most used PPE by the farmer\u27s i.e. by 83% in overall. Fourty three percent of the farmer\u27s throw the pesticide containers in secret place after using of it.The use of PPE was seen lower in small holders as compared to the large holders. This study reveals the necessities of suitable program and policies regarding the knowledge, safe handling and use of pesticide among the farmer\u27s level
Granular Matter: Microstructural Evolution and Mechanical Response
Heterogeneous (nano) composites, manufactured by the densification of variously sized grains, represent an important and ubiquitous class of technologically relevant materials. Typical grain sizes in such materials range from macroscopic to a few nanometers. The morphology exhibited by such disordered materials is complex and intricately connected with its thermal and electrical transport properties. It is important to quantify the geometric features of these materials and simulate the fabrication process. Additionally, granular materials exhibit complex structural and mechanical properties that crucially govern their reliability during industrial use. In this work, we simulate the densification of soft deformable grains from a low-density fluid-state to a mechanically rigid solid-state. The simulation is performed via methods of structural optimization that minimize the system free energy in the athermal limit. The effect of grain shapes and sizes (and dispersity therein) is simulated in detail and their effect on the composite morphology is quantified. Furthermore, in the present simulations the composite materials are perturbed under external stress (strain) stimuli to understand the mechanical response and calculate the material stress-strain response, effective Poisson’s ratio and yield stress. A tool is created to simulate the consolidation and stress-perturbation of the different shaped and sized grains using techniques of computational geometry and gradient-based optimization routines to relax microstructures into minimum-energy stable phases. The tool uses MATLAB and C++, wrapped around xml for generating Graphical User Interface (GUI). The tool can be deployed online in nanoHUB platform of Network for Computational Nanotechnology (NCN). Besides computing the data like enthalpy of the system and internal stress, this tool also utilizes visualization technique like Visualization ToolKit (VTK) to graph and visualize the optimized microstructures. Hence, the creation of this tool allows the wider audiences simulate the consolidation and stress-perturbation of the different shaped and sized grains
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