Influence of Inorganic Additives on the Surface Characteristics, Hardness, Friction and Wear Behavior of Polyethylene Matrix Composites.

The aim of this research was to analyze the effect of inorganic additives on the tribological properties of the high-density polyethylene (HDPE) matrix composite surface. Titanium (Ti) and hexagonal boron nitride (hBN) were added in different mass fractions. The samples were produced by pressing a pre-prepared mixture of granules. The composite samples with the following mass fractions of additives were fabricated: 5% hBN, 10% hBN, 28% Ti-2% hBN, 23% Ti-7% hBN, and 20% Ti-10% hBN. An even distribution of individual additives' concentrations was confirmed. Observations of morphology, surface topography, hardness, and tribological measurements were conducted using reciprocating motion tests with the "pin-on-flat" and rotational tests with the "pin-on-disc" configuration. Subsequently, microscopic observations and measurements of the wear track profile were carried out. Additionally, geometry parameters of the contacting elastic body were calculated for various counter-samples. It was found that the Shore D hardness of samples containing Ti and hBN increased with the Ti content, while the coefficient of friction (COF) value decreased. The addition of hBN alone did not significantly affect the hardness, regardless of the ratio, while the COF increased with the increasing hBN content. The COF value doubled with the addition of 10% hBN (COF = 0.22), whereas the addition of 90% Ti-10% hBN resulted in a decrease in the COF value, to COF = 0.83. The highest hardness value was obtained for the sample containing 28% Ti-2% hBN (66.5), while the lowest was for the sample containing 10% hBN (63.2). The wear track analysis, including its height and width caused by deformation, was detected using a focal differentiation microscope and scanning electron microscopy. Additionally, EDS maps were generated to determine the wear characteristics of the composite.

Do patients read emails from their physician containing tips on improving lifestyle habits? A pilot study.

INTRODUCTION: Healthcare providers and organizations occasionally use electronic messages to provide information to patients. There is insufficient data on whether patients actually read the emails they receive. In this study, we aimed to assess the cooperation of patients in reading multiple information pages sent over 6 months from their diabetologist via email. METHODS: Adults with non-optimally controlled type 2 diabetes received via email, once every 2 weeks for 6 months, a message containing information and tips on how to improve diabetes control through lifestyle choices. The information was provided in a format that required the recipient to actively click on a "read more" tab in order to reveal the entire text. Each email contained a short questionnaire requesting a response. Analysis compared the effect of patient variables on co-operation with reading the emails and answering the questionnaires. MAIN FINDINGS: 45 patients completed the study, 53.3% of them read 66-100% of the emails, 17.8% read 34-65% of the emails and only 26.7% read less than 33% of the emails. Women answered more questionnaires than men did. Answering a questionnaire on nutrition or medications correlated with reading the following email sent. CONCLUSIONS: This study is the first to demonstrate that most patients do indeed read a significant portion of emails sent by their physician. Email could be an effective means of sharing information and improving patient engagement with treatment.

Simulation and visualization of multiple KEGG pathways using BioNSi.

Motivation: Many biologists are discouraged from using network simulation tools because these require manual, often tedious network construction. This situation calls for building new tools or extending existing ones with the ability to import biological pathways previously deposited in databases and analyze them, in order to produce novel biological insights at the pathway level. Results: We have extended a network simulation tool (BioNSi), which now allows merging of multiple pathways from the KEGG pathway database into a single, coherent network, and visualizing its properties. Furthermore, the enhanced tool enables loading experimental expression data into the network and simulating its dynamics under various biological conditions or perturbations. As a proof of concept, we tested two sets of published experimental data, one related to inflammatory bowel disease condition and the other to breast cancer treatment. We predict some of the major observations obtained following these laboratory experiments, and provide new insights that may shed additional light on these results. Tool requirements: Cytoscape 3.x, JAVA 8 Availability: The tool is freely available at http://bionsi.wix.com/bionsi, where a complete user guide and a step-by-step manual can also be found.