141 research outputs found
A Study on Cultural Capital and High-Risk Behaviors of College Students in Iran
No full textNaseri S. A Study on Cultural Capital and High-Risk Behaviors of College Students in Iran. Mediterranean Journal of Social Sciences. 2018;9(2):185-193.The term cultural capital has gained a widespread popularity as an analogy with economic capital, and capitalism rules and debates since the early 1970s. Essentially, cultural capital is not inherited, yet it is achieved through personal endeavors. Acquisition of cultural capital demands an incessant and hard work in addition to lifelong learning and acculturation. Hence, the present study examines the relationship between forms of cultural capital and high-risk behaviors of Iranian college students. The impact of each form on the incidence of high-risk behaviors is measured. A survey consisting demographical items, and items assessing cultural capital and tendency towards high-risk behaviors are applied. The results suggest a meaningfully negative relationship between sub-types of cultural capital and high-risk behaviors among undergraduate students in Iran. So, the author concluded that with an increase in cultural capital and the sub-types, the incidence of high-risk behaviors decreases consequently
Online social network sites and social capital. A case of facebook
No full textNaseri S. Online social network sites and social capital. A case of facebook. International journal of applied sociology. 2017;7(1):13-19.The present study is a theoretical and literary review of online social network sites and their impact on social capital. In this review, the Facebook is selected as one popular and important online social networking site in the world today. To This end, first two main concepts of social capital, bridging and bonding social capital has been provided. Next, the concept of online social networks and the impact of FB on social networks are discussed
"Röntgensjuksköterskans upplevelser av informationsförmedling till patienter inom nuklearmedicin” : En kvalitativ metodintervjustudie
No full textRegular Exercise Training as a Principal Non-Pharmacological Method Affects Serum Leptin and Cardiovascular Risk Factors in Men with Metabolic Syndrome
No full textBackground and Aim: Regular exercise training is the principal non-pharmacological method for the prevention and treatment of metabolic syndrome or other obesity-related diseases. We investigated the effects of aerobic training on leptin and cardiovascular risk factors in middle-aged men with metabolic syndrome.
Methods: Twenty-six sedentary middle-aged males with metabolic syndrome aged 40 ± 5 years were randomly assigned to two groups as exercise (aerobic training, n =13) and control (no training, n =13). The exercise programs were performed 3 days a week for 10 weeks at 55-75% of HRmax. Fasting blood samples were taken before and after the training period for measuring serum leptin and triglyceride (TG), total cholesterol (TC), LDL, and HDL as cardiovascular risk factors.
Results: No significant differences were observed between groups concerning anthropometric and clinical markers at baseline (p>0.05). Aerobic intervention resulted in significant decrease in anthropometric markers (abdominal circumference, body mass index, body fat percentage; p < 0.05), serum leptin (p = 0.026), TG (p = 0.001) and HDL (p = 0.032) in exercise group, but significant changes were not found in TC (p = 0.522) and LDL (p = 0.546). There were no changes in all measured variables in the control group.
Conclusion: Based on our finding, it seems that regular aerobic exercise is associated with improved serum leptin and cardiovascular function in patients with metabolic syndrome.
*Corresponding Author: Mojtaba Eizadi; Email: [email protected]
Please cite this article as: Naseri Rad R, Eizadi M. Regular Exercise Training as a Principal Non-Pharmacological Method Affects Serum Leptin and Cardiovascular Risk Factors in Men with Metabolic Syndrome. Arch Med Lab Sci. 2020;6:1-8 (e1). https://doi.org/10.22037/amls.v6.3164
Structural and functional heterogeneity of cells in the rat hippocampus
No full textMemory is encoded in the structure and function of the hippocampus. The laminar structure and organization of information flow are well established. The dentate gyrus (DG) is the initial layer that receives and parses incoming signals. The signal is then transmitted to the CA3 and subsequently the CA1 layer. CA1 pyramidal neurons are the primary hippocampal projection neurons that provide a significant output pathway from the hippocampus. DG granule neurons are the primary signal receivers from the major input pathway through the Perforant Path (PP) from the entorhinal cortex (EC). These neurons send their dendrites into the molecular layer of the dentate gyrus (ML/DG), where populations of astrocytes reside. This clear topographic segregation positions astrocytes of the molecular layer to strongly influence signals coming into the DG. Additionally, time-of-day significantly influences hippocampal neuronal excitability and functions in both CA1 and DG, including long-term potentiation, memory acquisition, and recall of learned tasks (Chaudhury et al., 2005). However, mechanisms underlying these diurnal changes are still an open question. Preliminary evidence from Gillette lab revealed for the first time that hippocampal astrocytes in the ML/DG region in brain slices undergo significant changes in structural and morphological complexity over the day-night cycle (Irving et al., 2015). However, this observation brings up the questions of what effects could these morphological changes exert on astrocyte connectivity and, in turn, on their physiological functions, specifically with regards to the time of the day. We proposed a set of experiments to understand the diurnal dynamics in the structure and function of hippocampal neurons and glial cells. We found that 1) the excitability of CA1 pyramidal neurons exhibits a rhythm in resting membrane potential which is coupled to its near-24-h intrinsic redox oscillation, 2) the membrane potential of DG granule neurons displays oscillation over the day-night cycle that is anti-phase to that of the CA1 pyramidal neurons, 3) the peak time of neuronal excitability in the DG coincides with the peak time of seizure incidence in this layer, 4) ML/DG astrocytes are structurally dynamic and their connectivity through gap-junction coupling increases significantly from day to nighttime, 5) ML/DG astrocytes display larger cell body volumes during the day than the nighttime, with no significant diurnal difference in the dry mass, 6) the oligodendrocyte precursor cells, also known as NG-glia, undergo diurnal cell division where they divide in the early day and reside as isolated cells during the nighttime, 7) astrocyte coverage of active synapses is higher at night, the active phase of the nocturnal animal. Thus, we have characterized electrophysiological properties of both neurons and glial cells of hippocampal CA1 and DG layers and the degree of network connectivity over the day-night cycle at both cell and circuit levels. Understanding the dynamics of neurons and astrocytes will enable a greater comprehension of hippocampal network function.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01The student, Ghazal Naseri Kouzehgarani, accepted the attached license on 2020-01-16 at 23:06.The student, Ghazal Naseri Kouzehgarani, submitted this Dissertation for approval on 2020-01-16 at 23:19.This Dissertation was approved for publication on 2020-01-21 at 16:12.DSpace SAF Submission Ingestion Package generated from Vireo submission #14850 on 2020-08-25 at 17:38:23Made available in DSpace on 2020-08-27T00:46:47Z (GMT). No. of bitstreams: 2
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Welfare Effects of Economic Sanctions :The Case of Iran
No full textEconomic sanctions are a low-cost tool that replaces military action with a high economic, political and human cost. The severity of the effects of sanctions depends on the degree of dependence of the target economy on the outside world, the cooperation of the international community with the ones imposing sanctions, and the potential ability to substitute domestic production with imports. If domestic supply is sufficiently resilient, sanctions act, such as an import substitution policy, can lead to higher growth and more employment. Otherwise, sanctions will act as a lack of domestic supply. This study evaluates the welfare effects of sanctions on basic items - whose rising prices affect living standards. We use a multiple choice model and logit function, the income and cost effects of sanctions as well as the impact of exchange rate changes on the price of basic goods on the welfare standard and the probability of households joining the poor group are considered. The results show that, due to the inelastic domestic supply, the possibility of substituting imports is limited, so the cost effects are dominant for the year 2019, in the effective exchange rate scenario, poverty growth is estimated at %2.2 (about 1828 thousand people, and in the official exchange rate scenario, poverty growth is 3.1 percent (and about 2575 thousand People have joined the poor group)
Domain Adaptation in Acoustic Rainfall Sensors
No full textRainfall is increasing in frequency and intensity due to climate change. Hydrological models exist that can report bottlenecks in urban infrastructures. However, these require accurate rainfall estimations with high temporal and spatial resolution. The fulfillment of these requirements is challenged due to high costs. This can be solved with cost-effective acoustic rainfall sensors, that can be densely distributed over a city. A (machine learning) prediction model is then needed to infer rainfall from acoustic data. It is infeasible to create or calibrate a seperate model to the specific characteristics of every acoustic sensor. This research focuses on domain adaptation techniques that transfer a model designed for one sensor, called the source, to a characteristically different one, called the target. A two-stage regressor model is devised that estimates rainfall intensity from acoustic data. In a supervised learning setting, this gave an average score of 0.67. Transfer Component Analysis (TCA) has been used as a semi-supervised domain adaptation technique, where no annotations from the target sensor are needed. This resulted in an average of 0.59. Finally, a supervised domain adaptation technique, where some annotations are used, is proposed using TCA and a mean matching method. Two flavours are researched. In the batched approach a small selection of target annotations are gathered, where after the rainfall is predicted with a delay. The online approach predicts in real-time, but adjusts the prediction model when a new target annotation is available. These resulted in an average of 0.52 and 0.32, respectively
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