Kinetics of the enzymatic degradation of poly(vinyl acetate) in solution

The enzymatic degradability of poly(vinyl acetate) was investigated in toluene solutions at various temperatures with hog pancreas lipase. The polymer degraded by specific scission to yield oligomeric products with a molecular weight of 700. Continuous distribution kinetics were used to determine the rate coefficients. The variation of the rate coefficients with the temperature indicated an optimum at 55°C. The p‐toluene sulfonic acid catalyzed degradation of poly(vinyl acetate) was also investigated. The degradation mechanism was random chain scission, and the energy of activation for degradation was determined from the variation of the rate coefficients with the temperature. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2579–2582, 2003     

Role of MoS2 morphology on wear and friction under spectrum loading conditions

One of the ways by which grease is evaluated is by using a four‐ball wear test using ASTM D2266. However, actual applications may require bearings to be subjected to spectrum loading conditions. This study focuses on using ball milling to mitigate the wear from sharp edges in the MoS₂ particles. Two different blends of greases were formulated using MoS₂ in the as‐received state (unmilled) and milled MoS₂; they were tested under spectrum loading conditions where the load and frequency of the tests were treated as variables. It was found that ball milling of the MoS₂ significantly reduces the wear under spectrum loading condition both for ramp‐up and ramp‐down conditions. It was also shown that shortening the time step for both the ramp‐up and ramp‐down cycles resulted in larger wear for unmilled MoS₂ particles in comparison with milled MoS₂ particles in grease. The milling process did not play a significant role when frequency of the test was either ramped up or down. Copyright © 2015 John Wiley & Sons, Ltd.     

Toxoplasma lymphadenitis. Analysis of cytologic and histopathologic criteria and correlation with serologic tests

Fear reactions of rats given bilateral lesions to the septum, hippocampus, or amygdala were compared with those of rats given sham lesions, in 2 animal models of anxiety: the shock-probe burying test and the elevated plus-maze test. Septal lesions produced anxiolytic effects in both tests (i.e., an increase in open-arm activity and a decrease in burying), whereas hippocampal and amygdaloid lesions produced neither of these effects. On the other hand, hippocampal and amygdaloid lesions impaired rats' passive avoidance of the electrified shock-probe, whereas septal lesions did not. These dissociations suggest that limbic structures such as the septum, amygdala, and hippocampus exert parallel but distinct control over different fear reactions.     

Bonsai: diverse and shallow trees for extreme multi-label classification

Machine Learning - Extreme multi-label classification (XMC) refers to supervised multi-label learning involving hundreds of thousands or even millions of labels. In this paper, we develop a suite...     

An Integrated Hydrologic Modeling and Data Assimilation Framework

The Land Information System (LIS) is a multiscale hydrologic modeling and data assimilation framework that integrates the use of satellite and ground-based observational data products with advanced land-surface modeling tools to aid several application areas, including water resources management, numerical weather prediction, agricultural management, air quality, and military mobility assessment.     

Hourly River Flow Forecasting: Application of Emotional Neural Network Versus Multiple Machine Learning Paradigms

Water Resources Management - Monitoring hourly river flows is indispensable for flood forecasting and disaster risk management. The objective of the present study is to develop a suite of hourly...     

Identifying the degree of genetic interactions using Restricted Boltzmann Machine—A study on colorectal cancer

The phenomenon of two or more genes affecting the expression of each other in various ways in the development of a single character of an organism is known as gene interaction. Gene interaction not only applies to normal human traits but to the diseased samples as well. Thus, an analysis of gene interaction could help us to differentiate between the normal and the diseased samples or between the two/more phases any diseased samples. At the first stage of this work we have used restricted Boltzmann machine model to find such significant interactions present in normal and/or cancer samples of every gene pairs of 20 genes of colorectal cancer data set (GDS4382) along with the weight/degree of those interactions. Later on, we are looking for those interactions present in adenoma and/or carcinoma samples of the same 20 genes of colorectal cancer data set (GDS1777). The weight/degree of those interactions represents how strong/weak an interaction is. At the end we will create a gene regulatory network with the help of those interactions, where the regulatory genes are identified by using Naïve Bayes Classifier. Experimental results are validated biologically by comparing the interactions with NCBI databases.