The Effectiveness of Group Logotherapy in Increasing Resilience and Decreasing Depression among Individuals Affected by Substance Abuse in Tehran

Introduction: Substance use disorder is one of the chronic and often recurrent disorders that predispose a person to serious problems, such as AIDS, hepatitis and other chronic disorders. This study aimed to determine the effectiveness of group logotherapy in increasing resilience and decreasing depression among individuals with addiction in Tehran. Method: Semi-experimental research method with pre-test, post-test design and control group was utilized in this study. The statistical population of this study included all individuals affected by substance abuse referred to drug rehabilitation clinic in Tehran. The sample consisted of 36 individuals with substance abuse; whose depression and resilience scores were as much as two standard deviations lower than the mean. Subjects were randomly assigned to experimental and control groups. Beck Depression Inventory and Caner-Davidson’s Resilience Questionnaire were adopted. Ten 90-minute group logotherapy sessions were held for the experimental group. Data were analyzed using multivariate covariance method. Results: The findings of this study indicated that group logotherapy, increased resilience and decreased depression in the experimental group. Conclusion: Logotherapy can be considered as a new way of introducing purposefulness and meaningfulness in life. It increases the level of resilience and increase happiness for patients with substance abuse through assisting them in discovering their real self, selecting individual values, and finding the meaning of life. Declaration of Interest: None

Orthogonal Signal Correction to Improve Stability Regression Model in Gas Sensor Systems

Metal oxide sensors are the most often used in electronic nose devices because of their high sensitivity, long lifetime, and low cost. However, these sensors suffer from a lack of response stability making the electronic nose systems useless in industrial applications. The sensor instabilities are particularly caused by incomplete recovery process producing gradual drifts in the sensor responses. This paper focuses on a signal processing method combining baseline manipulation and orthogonal signal correction technique in order to reduce effectively the drift impact from the sensor outputs. The proposed signal processing is explored using experimental data obtained from a gas sensor array responding to various concentrations of pine essential oil vapors. Partial Least Square method is then applied on the corrected dataset to establish a regression model for the estimation of gas concentration. In this work, we show essentially how our drift correction approach can help to improve significantly the stability of the regression model, while ensuring good accuracy

Exploring Knowledge Strategy Dimensions Using Fuzzy AHP

Living in knowledge-based world and increasing competition between companies- especially in IT-based companies- in determining the best knowledge strategy lead to more attention to this concept. The purpose of this paper is to review previous studies on knowledge strategy and its dimensions. Then, after categorizing these dimensions, a popular multi-criteria decision-making (MCDM) method- AHP- in Fuzzy environment is used to evaluate dimensions of knowledge strategy (KS). The results show that knowledge sourcing, learning sourcing, learning speed are more effective dimensions of knowledge strategy. As every organization has a leading dimension in KS, IT-based companies should focus on these dimensions for better developing knowledge strategy

Vitamin D deficiency and coronary artery disease

BACKGROUND: Several factors such as hyperlipidemia, diabetes and hypertension have a determining role in cardiovascular disease. In recent years, the effect of vitamin D deficiency on cardiovascular disease has been emphasized. This study compares vitamin D deficiency in coronary heart disease patients with the control group. METHODS: In a cross-sectional study, 25-hydroxycholecalciferol level was compared in 119 individuals including 57 people with confirmed coronary heart disease and 62 healthy people. 25-hydroxyvitamin D [25(OH)D] was assessed using standard protocol. The level of 25(OH)D under 20 ng/dl was determined as cutoff point. RESULTS: The calculated odds ratio was 3.9 (95% confidence interval 2.6-5.5). Vitamin D deficiency significantly different between patients and the control group (p = 0.01). Of 37 (31%) individuals having vitamin D deficiency, 36 (97.3%) had coronary artery disease and from 57 patients with coronary artery disease 36 (63.2%) had vitamin D deficiency. CONCLUSIONS: Vitamin D deficiency is a relatively common disorder. Risk of cardiovascular disease in people with vitamin D deficiency is almost four times of those with normal levels of vitamin D. To confirm the casual relationship between vitamin D and cardiovascular disease, clinical trial studies are suggested

Meat Quality Assessment by Electronic Nose (Machine Olfaction Technology)

Over the last twenty years, newly developed chemical sensor systems (so called “electronic noses”) have made odor analyses possible. These systems involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odors. As commercial instruments have become available, a substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic and other items of everyday life is observed. At present, the commercial gas sensor technologies comprise metal oxide semiconductors, metal oxide semiconductor field effect transistors, organic conducting polymers, and piezoelectric crystal sensors. Further sensors based on fibreoptic, electrochemical and bi-metal principles are still in the developmental stage. Statistical analysis techniques range from simple graphical evaluation to multivariate analysis such as artificial neural network and radial basis function. The introduction of electronic noses into the area of food is envisaged for quality control, process monitoring, freshness evaluation, shelf-life investigation and authenticity assessment. Considerable work has already been carried out on meat, grains, coffee, mushrooms, cheese, sugar, fish, beer and other beverages, as well as on the odor quality evaluation of food packaging material. This paper describes the applications of these systems for meat quality assessment, where fast detection methods are essential for appropriate product management. The results suggest the possibility of using this new technology in meat handling

Electronic Noses and Applications

Abstract: Electronic noses are customized devices employed to detect and to identify gaseous mixtures, even to give the concentration of the atmosphere components. Nowadays, the research in this domain is more and more growing, in Europe and other countries in the world, for many applications, such as environmental protection, food industries, perfumery, public safety, medicine, and pharmacy. Electronic noses allow to detect many organic volatile compounds, for which there is no specific detector. They constitute an alternative to complex, long, and too expensive existing methods, unable to ensure continuous monitoring. Their conception deals with many related areas (metrology, chemistry, physics, electronics, informatics, statistics, modelisation) as well as areas related to the molecules to be detected. The system training is a primary step: during a measurement under a gaseous atmosphere, we must record the sensor time-responses in a treatment system, while specifying the name of the concerned odor. This process must be repeated many times for each studied atmosphere, and for all the chosen atmospheres. So a learning data base can be created, made from representative parameters of all the realized measures. After this training stage, clustering software will classify the data analysis in "concentration" or "nature" groups. Using the group separation rules given by this supervised classification, the system will be able to find itself the name of an odor or a concentration

Nez électronique et applications

International audienc

Electronic Noses and Applications

Electronic noses are customized devices employed to detect and to identify gaseous mixtures, even to give the concentration of the atmosphere components. Nowadays, the research in this domain is more and more growing, in Europe and other countries in the world, for many applications, such as environmental protection, food industries, perfumery, public safety, medicine, and pharmacy. Electronic noses allow to detect many organic volatile compounds, for which there is no specific detector. They constitute an alternative to complex, long, and too expensive existing methods, unable to ensure continuous monitoring. Their conception deals with many related areas (metrology, chemistry, physics, electronics, informatics, statistics, modelisation) as well as areas related to the molecules to be detected. The system training is a primary step: during a measurement under a gaseous atmosphere, we must record the sensor time-responses in a treatment system, while specifying the name of the concerned odor. This process must be repeated many times for each studied atmosphere, and for all the chosen atmospheres. So a learning data base can be created, made from representative parameters of all the realized measures. After this training stage, clustering software will classify the data analysis in “concentration” or “nature” groups. Using the group separation rules given by this supervised classification, the system will be able to find itself the name of an odor or a concentration