Search results for: Filiz Bayrakci Karel

Authors: Pınar Karakaya, Meral Mert, Yildiz Okuturlar, Didem Acarer, Asuman Gedikbasi, Filiz Islim, Teslime Ayaz, Ozlem Soyluk, Ozlem Harmankaya, Abdulbaki Kumbasar

Abstract:

Objective: To evaluate the relation of mean platelet volume (MPV) levels with serum paraoxonase-1 activity and brachial artery diameter and intima media thickness in diabetic patients with respect to obesity and diabetic complications. Methods: A total of 201 diabetic patients grouped with respect to obesity [obese (n=89) and non-obese (n=112) and diabetic complications [with (n=50) or without (n=150) microvascular complications and with (n=91) or without (n=108) macrovascular complications] groups were included. Data on demographic and lifestyle characteristics of patients, anthropometric measurements, diabetes related microvascular and macrovascular complications, serum levels for MPV, bBrachial artery diameter and intima media thickness (IMT) and serum paraoxonase and arylesterase activities were recorded. Correlation of MPV values to paraoxonase and arylesterase activities as well as to brachial artery diameter and IMT was evaluated in study groups. Results: Mean(SD) paraoxonase and arylesterase values were 119.8(37.5) U/L and 149.0(39.9) U/L, respectively in the overall population with no significant difference with respect to obesity and macrovascular diabetic complications, whereas significantly lower values for paraoxonase (107.5(30.7) vs. 123.9(38.8) U/L, p=0.007) and arylesterase (132.1(30.2) vs. 154.7(41.2) U/L, p=0.001) were noted in patients with than without diabetic microvascular complications. Mean(SD) MPV values were 9.10 (0.87) fL in the overall population with no significant difference with respect to obesity and diabetic complications. No significant correlation of MPV values to paraoxonase, arylesterase activities, to brachial artery diameter and IMT was noted in the overall study population as well as in study groups. Conclusion: In conclusion, our findings revealed a significant decrease I PON-1 activity in diabetic patients with microvascular rather than macrovascular complications, whereas regardless of obesity and diabetic complications, no increase in thrombogenic activity and no relation of thrombogenic activity with PON-1 activity and brachial artery diameter and IMK.

Keywords: atherosclerosis, diabetes mellitus, microvascular complications, macrovascular complications, obesity, paraoxonase

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Authors: Filiz Celik, Rachel Harrad, Rob Keasley, Paul Bennett

Abstract:

The COVID-19 pandemic has posed a significant challenge to many, with some groups with particular vulnerability to adverse psychological impacts. These include those disadvantaged by mental ill health, either pre-existing or occurring during pregnancy or post-partum. Using a qualitative approach, the research aimed to identify the challenges posed by COVID-19 to women, their infants and families during the perinatal period and to suggest what further support can help alleviate the adverse mental health impact of COVID-19. 21 expectant and new mothers who were currently receiving support via a peri-natal mental health service participated in semi-structured interviews. In these interviews, participants explored the impact of changes in social circumstances and healthcare providers as a result of COVID-19 restrictions, with the resultant audio recordings transcribed and analyzed using Reflexive Thematic Analysis (RTA). Based on these accounts, it was concluded that women, their partners and potentially their infants experienced heightened peri-natal distress, and their experience at this time increased their risk for future mental health problems. Women described emerging as more vulnerable, owing to their role as primary caregivers during the perinatal period and also explained how social isolation and limited access to services meant protective buffers against mental health deterioration were reduced and the resources they needed in order to develop resilience were weakened. Although partners were invited to take part in the research, a sizeable volume of data could not be generated to fully assess the impact of the pandemic on a partner’s mental well-being. However, women expressed concerns about the paternal mental health of partners and husbands which invites us to be further vigilant to paternal mental health and associated experiences. Overall, these interviews serve to highlight and provide a voice to these women and their families who describe experiencing disadvantage at an already vulnerable time in their lives, as well as illustrating the need for services to prioritize the needs of this population when acute events strike, be those future pandemics or other disasters.

Keywords: patient experience, perinatal mental health, covid-19 pandemic, heightened anxiety, birth trauma, post-natal well-being

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Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Oya Isik, Filiz Yurtal, Kubilay Vursavus, Muge K. Davran, Metehan Celik, Munire Akgul, Olcay Karacan

Abstract:

In this study, to discuss the causes and problems of women by bringing together different disciplines engaged in women's studies were aimed. Also, to solve these problems, to share information and experiences in different disciplines about women, and to reach the task areas and decision mechanisms in practice were other objectives. For this purpose, proceedings presented at the Second Congress of Women's Studies held in Adana, Turkey, on 28-30 November 2018 was evaluated. The document analysis model, which is one of the qualitative research methods, was used in the evaluation of the congress proceedings. A total of 86 papers were presented in the congress and the topic distributions of the papers were determined. At the evaluation stage, the papers were classified according to their subjects and descriptive analyses were made on the papers. According to the analysis results of the papers presented in the congress, 64 % of the total 86 papers presented in the Congress were review-based and 36 % were research-based studies. When the distribution of these reports was examined based on subject, the biggest share with the rate of 34.9% (13 reviews and 17 research-based papers) has been studied on women's issues through sociology, psychology and philosophy. This was followed by the economy, employment, organization, and non-governmental organizations with 20.9% (9 reviews and nine research-based papers), arts and literature with 17.4% (15 reviews based papers) and law with 12.8% (11 reviews based papers). The lowest share of the congress was presented in politics with one review based paper (1.2%), health with two research-based paper (2.3%), history with two reviews based papers (2.3%), religion with two reviews and one research-based papers (3.5%) and media-communication with two compilations and two researches based papers (4.7%). In the papers categorized under main headings, women were examined in terms of gender and gender roles. According to the results, it was determined that discrimination against women continued, changes in-laws were not put into practice sufficiently, education and economic independence levels of women were insufficient, and violence against women continued increasingly. To eliminate all these problems and to make the society conscious, it was decided that scientific studies should be supported. Furthermore, support policies should be realized jointly for women and men to make women visible in public life, tolerance or mitigation should not be put forward for any reason or in any group in cases of harassment and assault against women. However, it has been determined that women in Turkey should be in a better position in the social, cultural, psychological, economic and educational areas, and future studies should be carried out to improve women's rights and to create a positive perspective.

Keywords: gender, gender roles, sociology, psychology and philosophy, women studies

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Authors: Vandenbroucke Karel, Georges Annabel, Schuurman Dimitri

Abstract:

In the past years, bundling of transport flows, whether or not implemented in an intermodal process, has popped up as a promising concept in the logistics sector. Bundling of transport flows is a process where two or more shippers decide to synergize their shipped goods over a common transport lane. Promoted by the European Commission, several programs have been set up and have shown their benefits. Bundling promises both shippers and logistics service providers economic, societal and ecological benefits. By bundling transport flows and thus reducing truck (or other carrier) capacity, the problems of driver shortage, increased fuel prices, mileage charges and restricted hours of service on the road are solved. In theory, the advantages of bundled transport exceed the drawbacks, however, in practice adoption among shippers remains low. In fact, bundling is mentioned as a disruptive process in the rather traditional logistics sector. In this context, a Belgian company asked iMinds Living Labs to set up a Living Lab research project with the goal to investigate how the uptake of bundling transport flows can be accelerated and to check whether an online data sharing platform can overcome the adoption barriers. The Living Lab research was conducted in 2016 and combined quantitative and qualitative end-user and market research. Concretely, extensive desk research was conducted and combined with insights from expert interviews with four consultants active in the Belgian logistics sector and in-depth interviews with logistics professionals working for shippers (N=10) and LSP’s (N=3). In the article, we present findings which show that there are several factors slowing down the uptake of bundling transport flows. Shippers are hesitant to change how they currently work and they are hesitant to work together with other shippers. Moreover, several practical challenges impede shippers to work together. We also present some opportunities that can accelerate the adoption of bundling of transport flows. First, it seems that there is not enough support coming from governmental and commercial organizations. Secondly, there is the chicken and the egg problem: too few interested parties will lead to no or very few matching lanes. Shippers are therefore reluctant to partake in these projects because the benefits have not yet been proven. Thirdly, the incentive is not big enough for shippers. Road transport organized by the shipper individually is still seen as the easiest and cheapest solution. A solution for the abovementioned challenges might be found in the online data sharing platform of the Belgian company. The added value of this platform is showing shippers possible matching lanes, without the shippers having to invest time in negotiating and networking with other shippers and running the risk of not finding a match. The interviewed shippers and experts indicated that the online data sharing platform is a very promising concept which could accelerate the uptake of bundling of transport flows.

Keywords: adoption barriers, bundling of transport, shippers, transport optimization

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