Integrated model for renewable energy planning in Turkey

All economic sectors are associated with energy use; therefore, government organizations aim to supply sustainable energy for human needs and economic growth. In particular, increased environmental concerns of the public in Turkey have impacted policymaking for renewable energy (RE) management in Turkey. The primary objective for RE sources of the Turkish Ministry of Energy is to ensure that 30% of the share of electricity production is from RE resources in 2023. In this paper, the integrated multi-objective, multi-period linear programming model is presented to determine effective allocation of RE supply for seven different geographical regions in Turkey for the period of 2017 to 2024. The integrated model consists of two different stages. The first stage involves qualitative evaluations of RE sources for seven geographical regions. Analytical Hierarchy Process (AHP) is applied to determine criteria priorities and overall ratings of geographical regions across determined criteria for RE sources are computed. The second stage of the integrated model consists of a multi-objective, multi-period linear programming model. The proposed multi-objective linear programming model is coded in MPL (Mathematical Programming Language) and solved using the GUROBI 5.1.0 solver. The output of the integrated model presents the total supply amount of RE sources for geographical regions in planning period. The ε-constraints method is applied to compute the total supply amount of RE from geographical regions for the period of 2017 to 2024. In this study, a systematic decision-making model is generated to allocate renewable energy sources to the geographical regions. The presented model integrates qualitative evaluations and quantitative parameters of different geographical regions to determine the optimal supply amount of RE. The obtained results are consistent with the potential quantities of RE alternatives in geographical regions, regional specifications, and social requirements.     

Interactions between metals accumulated in the narrow-clawed crayfish Astacus leptodactylus (Eschscholtz, 1823) in Dikilitaş Lake,Turkey

The accumulations of Al, Cd, Cr, Cu, Fe, Ni, Pb and Zn in the exoskeleton, gills, hepatopancreas and abdominal muscles of crayfish Astacus leptodactylus (Eschscholtz, 1823) were determined. The strongest correlation observed was between Cr and Ni in the gills (r?=?0.904); moderate to strong correlations between Al, Cr, Fe, Ni and Cu were also observed in gill tissue. Disregarding the gills, the strongest correlation was found between Cu and Zn in the hepatopancreas (r?=?0.808); the correlation between these two metals might have been a result of metallothionein activity. The accumulation of Pb was found to correlate with that of Cd in the exoskeleton, Cd and Zn in the gills, Zn and Cu in the hepatopancreas and Cu in the abdominal muscle. None of these correlations were present in lakewater and sediment samples, suggesting that the crayfish metabolism may be responsible for the co-accumulation of metal–metal pairs. As all correlations in non-gill tissues are observed between divalent metals, a shared transporter such as divalent metal transporter 1 might be involved in the accumulation of these metals.     

Prenatal diagnosis in three cases of iniencephaly with unusual postmortem findings

Iniencephaly is a rare and lethal congenital malformation of the neural tube characterized by occipital bone defect, cervical dysraphism, fixed retroflexion of the fetal head and severe lordosis of the cervicothoracic spine. The etiology is unknown. Prenatally diagnosed cases of iniencephaly are rare because careful and early ultrasonographic evaluation is necessary. We present three cases of iniencephaly prenatally diagnosed by sonography at 20–22 weeks' gestation in which therapeutic abortion was induced. The sonographic findings were compatible with the postmortem findings. The present cases of iniencephaly were found to carry unusual associated malformations such as two lobes in the right lung and chorangiosis of the placenta. Only hypoplastic lungs have been reported by previous authors. We also studied the 677C→T mutation on the methylenetetrahydrofolate reductase gene in the parents in one of the present cases. The mother was found to be heterozygous for the 677CT polymorphism. Copyright © 2001 John Wiley & Sons, Ltd.     

The effect of vinasse on the growth of Helianthus annuus and Pisum sativum: part I--The effects on some enzymes and chlorophyll and protein content

In this study, the composition of vinasse was first analysed. It was found to contain 8.43% dry matter, 3.3% total ash, 4% crude protein and 0.95% total carbohydrates; BOD load was determined as 63 g litre(-1). Subsequently, the effects of vinasse in various concentrations (1, 2.5, 5, 10, 25, 50, 75 and 100%) on the activity of cellulase and pectin methyl esterase and the chlorophyll and protein contents of Pisum sativum and Helianthus annuus were investigated. The activity of these enzymes and the protein and chlorophyll contents in potted plants showed a gradual increase from the control up to 2.5% concentration of vinasse, but decreased at higher concentrations. These different effects of the effluent may be due to the high BOD load and the presence of cell wall cations in it.     

Improving pedestrian safety using combined HOG and Haar partial detection in mobile systems

Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.

Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.

Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.

Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian.     

Land cover change detection in the Turkish coastal zone based on 28-year (1990–2018) Corine data

Environmental Monitoring and Assessment - The present study aims to estimate the effects of PM2.5 on the health and economy of Karaj city from 2012 to 2019. In this study, mortality attributed to...     

Expert system application for prioritizing preventive actions for shift work: shift expert

Introduction. Shift patterns, work hours, work arrangements and worker motivations have increasingly become key factors for job performance. The main objective of this article is to design an expert system that identifies the negative effects of shift work and prioritizes mitigation efforts according to their importance in preventing these negative effects. The proposed expert system will be referred to as the shift expert. Methods. A thorough literature review is conducted to determine the effects of shift work on workers. Our work indicates that shift work is linked to demographic variables, sleepiness and fatigue, health and well-being, and social and domestic conditions. These parameters constitute the sections of a questionnaire designed to focus on 26 important issues related to shift work. The shift expert is then constructed to provide prevention advice at the individual and organizational levels, and it prioritizes this advice using a fuzzy analytic hierarchy process model, which considers comparison matrices provided by users during the prioritization process. An empirical study of 61 workers working on three rotating shifts is performed. After administering the questionnaires, the collected data are analyzed statistically, and then the shift expert produces individual and organizational recommendations for these workers.     

River water quality management model using genetic algorithm

Conventional mathematical programming methods, such as linear programming, non linear programming, dynamic programming and integer programming have been used to solve the cost optimization problem for regional wastewater treatment systems. In this study, a river water quality management model was developed through the integration of a genetic algorithm (GA). This model was applied to a river system contaminated by three determined discharge sources to achieve the water quality goals and wastewater treatment cost optimization in the river basin. The genetic algorithm solution, described the treatment plant efficiency, such that the cost of wastewater treatment for the entire river basin is minimized while the water quality constraints in each reach are satisfied. This study showed that genetic algorithm can be applied for river water quality modeling studies as an alternative to the present methods.