A Simple Method to Determine Critical Coagulation Concentration from Electrophoretic Mobility

Critical coagulation concentration (CCC) is a key parameter of particle dispersions, since it provides the threshold limit of electrolyte concentrations, above which the dispersions are destabilized due to rapid particle aggregation. A computational method is proposed to predict CCC values using solely electrophoretic mobility data without the need to measure aggregation rates of the particles. The model relies on the DLVO theory; contributions from repulsive double-layer forces and attractive van der Waals forces are included. Comparison between the calculated and previously reported experimental CCC data for the same particles shows that the method performs well in the presence of mono and multivalent electrolytes provided DLVO interparticle forces are dominant. The method is validated for particles of various compositions, shapes, and sizes

Spirituality in pain medicine: A randomized experiment of pain perception, heart rate and religious spiritual well-being by using a single session meditation methodology.

The aim of this study is to investigate different effects on pain perception among randomly assigned volunteers practicing meditation compared to a relaxation condition. The study examines whether participants of the experimental conditions (meditation versus relaxation) differ in the change of pain perception and heart rate measurement and in religious and spiritual well-being after an intervention. METHOD:147 volunteers (long-term practitioners and novices) were randomly assigned to the experimental conditions with a headphone guided 20-minute single session intervention. The change in their pre- and post-intervention pain perception was measured using Quantitative Sensory Testing and Cold Pressor Testing (CPTest), their stress-level was compared by monitoring heart rate, and their religious and spiritual well-being by using the Multidimensional Inventory for Religious/Spiritual Well-Being (MI-RSB48). Additionally, dimensions of the Brief Symptom Inventory (BSI) measured the psychological resilience of the participants; pain and stress experience, and the state of relaxation and spirituality experience were assessed. Five persons were excluded due to failure in measuring the heart rate and 29 participants had to be excluded because of high values on the BSI. RESULTS:The meditation group showed an increase in their pain tolerance on the CPTest and a decrease in their pain intensity for heat after the experimental condition, in contrast to the relaxation group. Futhermore, the meditation group showed a higher level of religious spiritual well-being (MI-RSB48 Total score) as well as in the sub-dimensions General Religiosity, Forgiveness, and Connectedness after the experimental condition, compared to the relaxation group. Our data is consistent with the hypothesis that meditation increases pain tolerance and reduces pain intensity, however, further work is required to determine whether meditation contains similar implications for pain patients

Spearman–rank order correlations between HBI components and main symptoms of major depression.

<p>Spearman–rank order correlations between HBI components and main symptoms of major depression.</p

MDI item means across UA, mild BO, moderate BO, severe BO and MD.

<p><b>UA</b> = physicians unaffected by burnout symptoms and major depression. <b>BO</b> = physicians suffering from burnout symptoms without suffering from major depression. Mild <b>BO</b> is characterized by an HBI_sum in the third quartile (a score between 145–178), individuals with moderate <b>BO</b> have an HBI_sum between the third quartile and ninth decile (a score between 179–200), and severe <b>BO</b> is characterized by an HBI_sum in the highest decile (a score of ≥ 201). <b>MD</b> = physicians suffering from major depression without suffering from burnout symptoms. T-tests revealed significant increases in all MDI item means across <b>UA</b>, mild <b>BO</b>, moderate <b>BO</b>, severe <b>BO</b> and <b>MD</b> (see <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0149913#pone.0149913.s002" target="_blank">S1 Table</a></b>).</p

Odds Ratio for burnout (HBI_sum≥ 145), predicted by the components of the HBI.

<p>Odds Ratio for burnout (HBI_sum≥ 145), predicted by the components of the HBI.</p

Confirmatory Factor Analysis of the HBI components.

<p>Confirmatory Factor Analysis of the HBI components.</p

Linear Regression: Explained variance of HBI_sum by different combinations of HBI components.

<p>Linear Regression: Explained variance of HBI_sum by different combinations of HBI components.</p

HBI components means, separated by burnout grade.

<p>HBI components means, separated by burnout grade.</p

Demographic and work-related information for participants compared to all Austrian physicians.

<p>Demographic and work-related information for participants compared to all Austrian physicians.</p