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How Can Urban Planners in Türkiye Foster Stronger Connections with the Agricultural/Food Sector While Transitioning from Closed Plans to Open Plans?
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Impact of Connection Types on Metaheuristic-Based Optimum Design of 3D Steel Buildings with RC Shear Core
No full textThis study examines the impact of connection types between a beam and a column, as well as between a beam and a shear core, on the optimal design of 3D steel buildings with reinforced concrete (RC) shear cores. Three metaheuristic algorithms, Adaptive Harmony Search (AHS), Biogeography-Based Optimization with Levy Flight (LFBBO), and Dandelion Optimizer (DO), were implemented to minimize the total weight of the steel frame while incorporating geometric constraints. RC shear core dimensions were treated as fixed due to elevator design considerations. The effectiveness of these algorithms was evaluated using two mid-rise steel building models with 20 and 30 stories, with a focus on the impact of varying connection configurations. Results indicate that LFBBO consistently produced the lightest designs. It is noticed that connection types significantly affect the optimum designs. In the 20-story models, the increase in the proportion of hinged beam connections led to a decrease in the optimum steel weight. Conversely, in the 30-story models, more hinged connections resulted in increased weight. Column-to-column (CtoC) and inter-story drift (ISD) constraints dominated the optimum designs in all models. It is necessary to account for connection types and structural drift when designing steel buildings with shear cores
OBREC DALGA ENERJİSİ DÖNÜŞTÜRÜCÜLERİNİN PERFORMANSLARININ SAYISAL MODELLER İLE İNCELENMESİ
No full textText, imagination and the construction of narrative universes in Ali Smith's short stories
No full textEarly childhood teachers’ understanding and perceptions regarding early childhood education for sustainability
No full textEco-school teachers who primarily incorporate the principles of Education for Sustainable Development (ESD) into their teaching practices serve as active agents of sustainable development, with the potential to foster sustainable behaviors from an early age. This study examined the understanding and perceptions of early childhood eco-school teachers regarding sustainability, sustainable development, Education for Sustainable Development (ESD), and Early Childhood Education for Sustainability (ECEfS). Focus groups and pre-/postconcept maps were used to gather data. The findings showed that while teachers viewed ECEfS as crucial for sustainable development, their understanding of sustainability, sustainable development, and the goals of ESD and ECEfS was limited. Teachers predominantly associated ESD and ECEfS with the environmental pillar, though some acknowledged sociocultural and economic aspects. Moreover, key concepts for ECEfS practice involved respect for differences, saving, consumption habits, and self-confidence. In addition, teachers’ postconcept maps revealed a broader, more comprehensive understanding of ESD compared to their preconcept maps. These findings suggested that teachers needed professional development to enhance their knowledge and implementation skills for ECEfS and address the sociocultural and economic dimensions of sustainability to implement a holistic approach to ECEfS effectively
Impacts of eutrophication and deoxygenation on the sediment biogeochemistry in the Sea of Marmara
No full textThe biogeochemistry of seafloor sediments can be significantly altered in response to deoxygenation and eutrophication-driven organic carbon production, resulting in increased benthic fluxes of dissolved nutrients (such as ammonia and phosphate) and metals. The Sea of Marmara, which has also faced large-scale mucilage outbreaks in recent years, is undergoing severe eutrophication and deoxygenation, but the consequences on sediment biogeochemistry and benthic feedback have not been studied so far. This study aims to understand the impacts of deoxygenation and coastal eutrophication on sedimentary biogeochemical processes in the Sea of Marmara, which experiences varying degrees of anthropogenic pressure along with natural inputs from the adjacent Black Sea via Bosphorus surface inflows. Multicore-obtained undisturbed sediment core samples indicate that oxic respiration no longer plays a significant role in Marmara sediments, but denitrification, metal reduction, and sulfate respiration are prevalent as respiratory pathways. The deep-water sediments become more reducing in the Eastern Marmara compared to the Western part of the sea. Cores from & Idot;zmit Bay, the Easternmost region in Marmara, exhibit permanently sulfidic conditions with anaerobic oxidation of methane (AOM) controlling downcore sulfide profiles. Calculated diffusive benthic nutrient fluxes show markedly high phosphate and ammonium fluxes into the near-bottom waters of highly eutrophic areas of the Eastern Marmara, which are expected to enhance primary production in the upper layer during the dry season. On the other hand, these sediments are a net sink for nitrate due to the denitrification. Benthic nutrient dynamics contribute to the accumulation of organic matter as well as shifting N/P ratios and the development of a steep hypoxic zone at halocline boundary depths. Additionally, we show that sediments are already influenced by widespread hypoxia in the Sea of Marmara and benthic-pelagic coupling has enhanced the existing eutrophication problem, analogous to the benthic "vicious cycle" observed in the shallower Baltic Sea. We conclude that the Sea of Marmara is now on a clear path towards being included within the list of famous "dead zones" of the Earth's oceans, such as the Baltic Sea, the Gulf of Mexico, or Chesapeake Bay. For the marine management efforts and ecosystem modeling studies, hypoxia-induced benthic biogeochemical processes and benthic-pelagic coupled cycling of nutrients in the Sea of Marmara should be considered
Thermoelectric Cooler Design without Using Cold And Hot Face Temperatures
No full textPeltier modules arenow easily accessible materials for accomplishing thermoelectric cooling forelectronics, condensers and essentially any small surface or volume withoutusing moving parts or a refrigerant. Common bismuth telluride-based modules arewell characterized through experiments in which face temperatures weremeasured. In the case of applications, measurement of face temperatures lead toadditional costs and custom manufacturing to place thin temperature sensorswith small form factors, especially for the hot side on which heat dissipationmust be managed at the same time. Moreover, in some specific applications, suchas liquid cooling, temperatures are usually measured away from the cold surfaceand rather in the liquid bulk. Interestingly, a design strategy for predictingthe cooling performance of Peltier modules without continuous measurement ofhot and cold face temperature is lacking.[NÜ1] [NÜ2] Ideal calculationsshould be essentially based on the cooling performance of the hot side andPeltier circuit characteristics. This report presents a modeling framework accompaniedby supporting experiments to predict cooling performance based on performancemetrics of the module, structural parameters and the efficiency of cooling ofthe hot face. First, a heatsink and fan combination was characterized throughsteady-state temperature measurements at constant voltage, where hot sidetemperature is deduced from cold side measurements. These measurements areshown to enable the determination of UAf, the overall heattransfer coefficient multiplied by the effective cooling area of the heatsinkwith the selected fan. We show that by changing fan speeds, data can beextended to different heatsinks and fans through a generalization that involvesfin geometry and efficiency. This framework is then put to use for designing asub-zero condenser for vapors. A cubical structure was manufactured with fourPeltier modules, leading to an ultimate bath temperature of −10°C at room temperature. By the use of anunsteady-state model, heat leakage from the ambient was characterized. Thisinformation was utilized for estimating the actual heat duty of the coolingbath as a function of temperature and condensation performance was measured byremoving water vapor in humid stream. We will present the design methodology,along with details related to temperature control, which allow simplified calculationof realistic cooling capacities in various thermoelectric cooling applications.</p
Gelir Sınıflandırma Kıyaslaması: R (Akademik Çalışma) ile Python (ML Hattı) Dönüşümü
No full textThe primary aim of this research is to construct a robust machine learning pipeline for income classification, predicting whether an individual earns above $50K based on demographic attributes such as work class, education, race, and gender. Initially developed as a statistical study in R-Studio to explore variable relationships and perform exploratory data analysis (EDA), the project has been significantly refactored into a production-ready Python environment to demonstrate modern MLOps standards.The methodology involves an end-to-end pipeline utilizing Scikit-Learn, incorporating advanced data cleaning, K-Nearest Neighbors (KNN) imputation for missing values, and automated feature scaling. While the initial research explored a broad range of algorithms, the current benchmark focuses on comparing the performance of Logistic Regression, Decision Trees, and Random Forest algorithms to establish a strong baseline. Model performance was rigorously assessed using Accuracy, Sensitivity, and F1-Score to account for categorical complexity. This dual-language approach highlights the transition from academic statistical inference to applied machine learning engineering.</p