Decorrelation of Lung and Heart Sound

Abstract— Signal separation is very useful where several signals have been mixed together to form combined signal and our objective is to recover individual original component signals from that combined signal. One of the major problem in neural network and research in other disciplines is finding a suitable representation of multivariate data, i.e. random vectors. For concept and computational simplicity representation is in terms of linear transformation of the original data. This means that each component of the representation is a linear combination of the original variables. There are linear transformation methods such as principal component analysis and Independent Component Analysis (ICA). ICA is a recently developed method in which the goal is to find a linear representation of non-gaussian data so that the components are statistically independent or as independent as possible. DOI: 10.17762/ijritcc2321-8169.150615

Estimation of local and external contributions of biomass burning to PM2.5 in an industrial zone included in a large urban settlement

A total of 85 PM2.5 samples were collected at a site located in a large industrial zone (Porto Marghera, Venice, Italy) during a 1-year-long sampling campaign. Samples were analyzed to determine water-soluble inorganic ions, elemental and organic carbon, and levoglucosan, and results were processed to investigate the seasonal patterns, the relationship between the analyzed species, and the most probable sources by using a set of tools, including (i) conditional probability function (CPF), (ii) conditional bivariate probability function (CBPF), (iii) concentration weighted trajectory (CWT), and (iv) potential source contribution function (PSCF) analyses. Furthermore, the importance of biomass combustions to PM2.5 was also estimated. Average PM2.5 concentrations ranged between 54 and 16 μg m−3 in the cold and warm period, respectively. The mean value of total ions was 11 μg m−3 (range 1–46 μg m−3): The most abundant ion was nitrate with a share of 44 % followed by sulfate (29 %), ammonium (14 %), potassium (4 %), and chloride (4 %). Levoglucosan accounted for 1.2 % of the PM2.5 mass, and its concentration ranged from few ng m−3 in warm periods to 2.66 μg m−3 during winter. Average concentrations of levoglucosan during the cold period were higher than those found in other European urban sites. This result may indicate a great influence of biomass combustions on particulate matter pollution. Elemental and organic carbon (EC, OC) showed similar behavior, with the highest contributions during cold periods and lower during summer. The ratios between biomass burning indicators (K+, Cl−, NO3−, SO42−, levoglucosan, EC, and OC) were used as proxy for the biomass burning estimation, and the contribution to the OC and PM2.5 was also calculated by using the levoglucosan (LG)/OC and LG/PM2.5 ratios and was estimated to be 29 and 18 %, respectively

An investigation into the stress-relieving and pharmacological actions of an ashwagandha (Withania somnifera) extract

Background: Ashwagandha (Withania somnifera (L.) Dunal) is a herb traditionally used to reduce stress and enhance wellbeing. The aim of this study was to investigate its anxiolytic effects on adults with self-reported high stress and to examine potential mechanisms associated with its therapeutic effects. Methods: In this 60-day, randomized, double-blind, placebo-controlled study the stress-relieving and pharmacological activity of an ashwagandha extract was investigated in stressed, healthy adults. Sixty adults were randomly allocated to take either a placebo or 240 mg of a standardized ashwagandha extract (Shoden) once daily. Outcomes were measured using the Hamilton Anxiety Rating Scale (HAM-A), Depression, Anxiety, and Stress Scale -21 (DASS-21), and hormonal changes in cortisol, dehydroepiandrosterone-sulphate (DHEA-S), and testosterone. Results: All participants completed the trial with no adverse events reported. In comparison with the placebo, ashwagandha supplementation was associated with a statistically significant reduction in the HAM-A (P = .040) and a near-significant reduction in the DASS-21 (P = .096). Ashwagandha intake was also associated with greater reductions in morning cortisol (P < .001), and DHEA-S (P = .004) compared with the placebo. Testosterone levels increased in males (P = .038) but not females (P = .989) over time, although this change was not statistically significant compared with the placebo (P = .158). Conclusions: These findings suggest that ashwagandha's stress-relieving effects may occur via its moderating effect on the hypothalamus-pituitary-adrenal axis. However, further investigation utilizing larger sample sizes, diverse clinical and cultural populations, and varying treatment dosages are needed to substantiate these findings