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Prisons, which are hazardous places for various contagious diseases, carry additional risks for HBV and HCV because of the communal lifestyle (common use of tools like razor blades, tattoo applications, intravenous drug use and homosexual intercourse). The purpose of this paper is to determine the prevalence of HBV and HCV, and also provide information for prisoners in this respect.

This study included 180 prisoners from the Buca F-Type Closed Prison, and 180 prisoners from the Foça Open Prison in Turkey. After the training seminars, serum levels of HBsAg, anti HBs, anti HBc total and anti HCV in the prisoners were assessed using the MICROELISA method.

All the prisoners were male. The mean age was 40(21–73) years. According to the results of 360 prisoners from both prisons, 17 (4.7 percent) prisoners were HBsAg positive and were diagnosed as HBV. Isolated anti HBs was positive in 33 (9.1 percent) prisoners who had been previously vaccinated. In 25 (6.9 percent) prisoners isolated Anti HBc total was positive, and in 61 (16.9 percent) prisoners both Anti HBs and Anti HBc total was positive in those who were considered to be recovered from the HBV. Anti HCV was positive in 2 (0.5 percent) prisoners; the process was repeated twice, and found to be repeatedly positive. Coinfection of HBV and HCV was not detected.

In this study, the prevalence of HBV and HCV was determined to be similar to those in the normal population. However, it is not expedient to generalize this result and apply it to all prisons. For the sake of public health, prisons should be scanned for infectious diseases, and vaccinations must be applied as necessary, in order to provide protection.

It is a study to determine the prevalence of HBV and HCV in the prisoner population, which constitute one of the risk groups because of the communal lifestyle (common use of some tools such as the razor blade, tattoo applications, intravenous drug use and homosexual intercourse), and to compare the results with other groups in Turkey and globally.

Alzheimer’s disease (AD) is the primary cause of dementia in elderly people and needs extensive professional care. The aim of our study was to assess the level of knowledge among primary health-care providers, primarily Family Physicians (FPs) and community pharmacists (CPs), about AD and its treatment.

A cross-sectional study using Google Forms sent by email or message to FPs and CPs in Istanbul in June–July 2023. Turkish modified the Alzheimer’s Disease Knowledge Scale (ADKS) and Alzheimer’s Medicines Knowledge Level Questionnaire (AMKLQ) were used in this study.

A total of 63 FPs with a mean age of 35.3 ± 7.8 and 138 CPs with a mean age of 38.6 ± 12.6 enrolled in the study. There was no statistically significant difference between FPs and CPs in terms of total ADKS score (19.82 ± 2.30 vs 19.23 ± 3.08, p = 0.136), but there was a significant difference in terms of total AMKLQ score (4.31 ± 1.40 vs 3.81 ± 1.49, p = 0.020). Health-care providers with Alzheimer’s training had a higher total AMKLQ score (OR =1.08 CI 95% [1.03–1.14], p = 0.012).

FPs’ knowledge of AD is on par with that of CPs. Nevertheless, it has been observed that FPs have more proficiency in delivering accurate responses to the AMKLQ and ADKS inquiries, which encompass crucial details regarding the treatment of AD. The sole determinant of the highest mean AMKLQ score was found to be professional education. Collectively, these arguments emphasize the need for primary health-care practitioners to obtain comprehensive and ongoing education regarding AD and its treatment.

The purpose of this paper is to study experimentally enhancement of heat transfer in a tube with axial swirling‐flow promoters. The geometric features of flow geometry to improve heat transfer can be selected in order to yield the maximum opposite reduction in heat exchange flow irreversibility by using exergy‐destruction method. The paper seeks to illustrate the use of neural network approach to analyze heat transfer enhancement data for further study in the scope of the experimental program.

For this purpose, 402 experimental measurements are collected. About 225 of those are used as training data for neural networks, the rest is used for testing. Then, these testing results of artificial neural network (ANN) and experimental data are compared. A formula for presenting exergy loses in a tubular heat exchanger is derived first and then the thermodynamic optimum instead of economic optimum is found by minimizing the exergy losses in the system.

Results from all configurations studied show that the heat transfer rate of the heated increases when the swirling‐flow promoter is inserted. From the heat transfer improvement number defined, it is observed that about 100 percent increase in heat transfer rate and five times increase in the pressure drop can be achieved under the condition of constant flow for the single promoter which has three blades, its blade angle is 30° and its location is in the middle of the tube length.

The back‐propagation (BP) algorithm was selected as the neural network algorithm, which uses the generalized delta learning rule. The training time of BP algorithm is considerably long. However, the testing of our neural network is real‐time.

The experimental setup is established to collect the experimental data. It consists of an entrance region, test region (heat exchanger and steam generator), and, flow measurement and control. Also, a software program of neural networks trained BP is written by using Pascal high‐level languages.

An alternative and new approach is proposed in the paper to find optimum flow geometry for a pipe flow with an axial swirling‐flow promoter inserts. It is too difficult to predict the response of a complex physical system that cannot be easily modeled mathematically. The result thus obtained compare well with experimental results, but the computational effort of the ANN and time required in the analysis is much faster as compared. These results show that the ANN can be used efficiently for prediction.

The purpose of this paper is to design a controller for the unmanned aerial vehicle (UAV).

In this study, the constrained multivariable multiple-input and multiple-output (MIMO) model predictive controller (MPC) has been designed to control all outputs by manipulating inputs. The aim of the autopilot of UAV is to keep the UAV around trim condition and to track airspeed commands.

The purpose of using this control method is to decrease the control effort under the certain constraints and deal with interactions between each output and input while tracking airspeed commands.

By using constraint, multivariable (four inputs and seven outputs) MPC unlike the relevant literature in this field, the UAV tracked airspeed commands with minimum control effort dealing with interactions between each input and output under disturbances such as wind.

The purpose of this paper is to present the autopilot design for the missile under various disturbances.

In this study, model predictive control (MPC) method has been used for autopilot design for each axis. The aim of autopilot is that to keep the roll angle value around the zero degree and to track pitch/yaw acceleration commands. This three-axes control methodology also takes into consideration the interaction between pitch, yaw and roll motions.

The purpose of using MPC method for three-axes of the autopilot is to decrease the control effort and to make the close-loop system insensitive against modeling uncertainties and stochastic effects.

This study shows that the missile is able to reach to the desired target with good robustness, low control effort and little miss-distance under disturbances such as aerodynamic uncertainties, thrust misalignment and gust affect by using this alternative control method.

The purpose of this paper is to provide an in-depth performance evaluation of funds offered by the Turkish pension system.

This paper compares aggregate fund index returns with the corresponding asset class returns, estimates a factor model to decompose excess returns to factor exposures, i.e., β return and excess return originating from residual α and analyzes persistence of fund returns using migration tables and Fama–MacBeth regressions and tests for market timing ability.

Majority of pension funds are unable to generate excess returns. Majority of funds are unable to generate a positive α and fund returns are predominantly driven factor exposures. There is evidence for slight persistence in returns, mainly due to factor exposures and funds do not exhibit market timing ability.

In this paper, the authors perform an in-depth analysis of pension fund performance for the Turkish pension fund system. The authors identify weaknesses and strengths of the pension fund industry and provide policy recommendations for a better design of pension fund system.

This study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.

This study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.

The analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.

This study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.

This study aims to examine marketing trends spanning a period of 26 years to scrutinize North American influence in marketing research, as well as enhance comprehension of interdisciplinary marketing knowledge and identify prominent scholars, universities, countries, and articles that warrant further scholarly exploration.

This paper uses bibliometric methods to analyze the publications of eight top-tier journals (Journal of Marketing, Journal of Consumer Research, Journal of Marketing Research, Journal of the Academy of Marketing Science, Marketing Science, Journal of Retailing, Journal of Consumer Psychology and International Journal of Research in Marketing) between 1996 and 2021, as found in the Scopus database.

The findings indicate that North American hegemony in the marketing discipline continues and that the impact of marketing on other disciplines remains controversial. Some universities have a deeply rooted tradition of marketing departments. Some articles from 26 years ago are still frequently cited.

The study covers the period from 1996 to 2021. It includes only articles, uses a single database and is cross-sectional. Future research should explore longer time periods by using various databases for comprehensive analysis.

To the best of the authors’ knowledge, this study constitutes one of the first attempts to understand the scholarly contributions of the marketing discipline by considering eight top-tier journals.

Esta investigación examina las tendencias de marketing durante un período de 26 años para analizar la influencia norteamericana en la investigación de marketing, así como para mejorar la comprensión del conocimiento interdisciplinario en marketing e identificar destacados académicos, universidades, países y artículos que merecen una mayor exploración académica.

Este documento emplea métodos bibliométricos para analizar las publicaciones de ocho revistas de primer nivel (Journal of Marketing, Journal of Consumer Research, Journal of Marketing Research, Journal of the Academy of Marketing Science, Marketing Science, Journal of Retailing, Journal of Consumer Psychology e International Journal of Research in Marketing) entre 1996 y 2021, según se encuentran en la base de datos de Scopus.

Los resultados indican que la hegemonía norteamericana en la disciplina del marketing continúa y que el impacto del marketing en otras disciplinas sigue siendo controvertido. Algunas universidades tienen una tradición arraigada en los departamentos de marketing. Algunos artículos de hace 26 años todavía son citados con frecuencia.

Este estudio constituye uno de los primeros intentos de comprender las contribuciones académicas de la disciplina del marketing considerando ocho revistas de primer nivel.

El estudio cubre el período de 1996 a 2021. Incluye solo artículos, utiliza una sola base de datos y es transversal. Futuras investigaciones deberían explorar períodos más largos de tiempo empleando diversas bases de datos para un análisis completo.

本研究调查了跨越26年的市场营销趋势, 以探讨北美在市场营销研究中的影响, 并增进对跨学科市场营销知识的理解, 识别值得进一步探索的杰出学者、大学、国家和文章。

本文采用文献计量学方法分析了1996年至2021年间八种顶级期刊 (Journal of Marketing、Journal of Consumer Research、Journal of Marketing Research、Journal of the Academy of Marketing Science、Marketing Science、Journal of Retailing、Journal of Consumer Psychology 和 International Journal of Research in Marketing）的出版物, 这些文章可在Scopus数据库中找到。

研究结果表明, 北美在市场营销学科中的霸权地位仍然存在, 并且市场营销对其他学科的影响仍然存在争议。同时, 研究发现一些大学具有根深蒂固的市场营销系传统, 且一些26年前的文章仍然经常被引用。

本研究首次尝试通过考虑八种顶级期刊来理解营销学科的学术贡献。

本研究涵盖了1996年至2021年的时间段。它仅包括文章, 使用了单一数据库, 并且是横断面研究。未来的研究应该通过使用各种数据库进行全面分析, 探索更长时间段。

The purpose of this research is to determine the competitive advantages of higher education institutions (HEIs) and create a new methodology to rank universities according to the competitive advantages.

The research determines the competitive advantages of HEIs by analysing expert opinions through a semi-structured interview form, matches codes and themes to performance indicators using Saldana's two-cycle coding methods, evaluates content validity through Lawshe and reveals the item weights of the ranking with analytical hierarchy process (AHP). Simple additive weighting (SAW) and Technique for Order of Preference by Similarity (TOPSIS) methods were used for ranking universities.

Seven dimensions stand out in regard to what should be considered while ranking HEIs: research and publication, education, management, infrastructure, financial resources, human resources and social and economic contribution. Under the 7 dimensions, 69 indicators were determined.

The research provides a scientific reference point where HEIs can compare themselves with other HEIs regarding where they are in the sector, especially in terms of competitive advantages.

Although there are many different ranking methods that rank universities in the national and international literature, almost all these methods are largely based on the outputs of the university such as the number of publications, the number of patents, the number of projects, etc. A framework which ranks universities by considering different aspects of the institution, such as management, human resources and financial resources, has not been developed yet. In this respect, this research aims to fill this gap in the literature.

In history, spatial organizations for houses have been changed and improved depending on the natural conditions, well-being of people, utilization of resourses, population density, family structure and urbanization rate. It can be said the spatial organization of housing that they are both in a relationship with culture and they are a total configuration of social, demographical, psycological, human behaviorial and environmental structure.

Any housing settlement in Turkish Islamic tradition is macro and micro scaled organization in which social relation and cultural characteristics of society that are necessary for physical environment and society reflect.

Basic element of urban spatial organization in Turkish Islamic housing pattern is “the quarter”. (Quarter is called as “mahalle” in Turkish culture) The quarter contains functional and semantic characteristics which are common for most Islamic civilization and Turkish Islamic cities.

In this study, what meaning does the quarter have as smallest spatial organization element in Anatolia will be examined. In additon what kind kind of evolutionary process does the quarter face in Turkish settlement.