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İnsanlık tarihindeki birçok salgın, yetersiz kentsel sanitasyon sistemleri ve evsel alanların sıhhi olmayan düzenlemeleri gibi bir dizi nedenden dolayı, insanların diğer canlılarla birlikte yaşama biçimlerini ve kentsel alan kullanımlarını etkilemiştir. Aralık 2019'da ortaya çıkan ve halen devam eden Covid-19 süreci, şehirleri kalıcı olarak etkileyen küresel bir pandemi olarak tarihsel süreci etkilediği gibi bugünümüzü ve geleceğimizi de etkilemektedir. Son iki yılda "yeni normal" olarak belirtilen yaşam düzenine uyum sağlamakta zorlanan kentsel kullanıcıları, salgının ekonomik, sosyal, fiziksel ve psikolojik etkileriyle mekânsal kullanımlarını değiştirmektedir. İnsanların kamusal alan kullanımlarında odak noktası olan kent mobilyaları da bu süreçten etkilenmiştir. Kent mobilyaları kullanımının bir ürünü olan kentsel oturma elemanları da bu süreçte en çok etkilenen ve üzerinde düşünülmesi gereken konulardan biri olmuştur. Çalışmanın kavramsal çerçevesinde kent mobilyası olarak oturma elemanlarına ait bilgiler incelendikten sonra, kentsel oturma elemanlarının tasarım kriterleri ile salgın arasındaki ilişkiden bahsedilecektir. Çalışmada incelenecek olan kentsel oturma elemanları, güncel tasarım süreçleri ve eğilimlerin izlenebildiği proje yarışmalarının bir türü olarak kent mobilyaları tasarım yarışmaları kapsamında seçilmiştir. Bu araştırmanın amacı, yaşanan Covid-19 pandemisinin kamusal alan kullanımındaki kentsel oturma elemanı tasarımları üzerindeki etkisinin literatür kapsamında belirlenmiş olan parametreler üzerinden değerlendirmesinin sunulmasıdır. Bu bağlamda çalışma, pandeminin kent mobilyaları tasarımı üzerindeki etkisinden kamusal alanların kullanımına kadar getirdiği değişikliklere odaklanan birçok araştırmaya da ilham kaynağı olacaktır.

Background: Laboratory professionals aim to provide a reliable laboratory service using public resources efficiently while planning a test's procurement. This intuitive approach is ineffective, as seen in the COVID-19 pandemic, where the dramatic changes in admissions (e.g. decreased patient admissions) and the purpose of testing (e.g. D-dimer) were experienced. A model based on objective data was developed that predicts the future test consumption of coagulation tests whose consumptions were highly variable during the pandemic. Methods: Between December 2018 and July 2021, monthly consumptions of coagulation tests (PTT, aPTT, D-dimer, fibrinogen), total-, inpatient-, outpatient-, emergency-, non-emergency -admission numbers were collected. The relationship between input and output is modeled with an external input nonlinear autoregressive artificial neural network (NARX) using the MATLAB program. Monthly test consumption between January and July 2021 was used to test the power of the forecasting model. Results: According to the co-integration analysis, the total number as well as the number of emergency and nonurgent examinations and the number of working days per month are included in the model. When the consumption of aPTT and fibrinogen was estimated, it was possible to predict the consumption of other tests. Fifty months of data were used to predict consumption over the next six months, and prediction based on NARX was the more robust approach for both tests. Conclusion: The deep learning model gives better results than the intuitive approach in forecasting, even in the pandemic era, and it shows that more effective and efficient planning will be possible if ANN-supported decision mechanisms are used in forecasting.

After the settlement textures were designed and constructed, they continue to exist without any change for years, and they have considerable effects on building energy consumption and the natural environment. With the changes in our lives following the COVID-19 global pandemic, employers have adopted working from home in many sectors, and energy expenditures in residences are increasing even more. The decrease of energy usage is a top objective in the design of the settlements from an economic and environmental standpoint. Also, while known energy modeling methods require extra expertise, labor and time in the integration of energy efficient design strategies into design processes, BIM systems have a significant potential in the evaluation of building energy efficiency. In this study, for the comprehensive evaluation of design parameters, different settlement texture alternatives, have been developed and building design parameters determined. These settlement textures were interpreted based on their annual energy consumption. By comparing the results, optimum values were sought for the settlement texture design parameters which are H/W, orientation, building height, and form factor. In addition, energy modelling and simulations were carried out with BIM software, and the use, advantages and capabilities of BIM systems were tested in the energy efficient design for reducing energy consumption. As a result, energy consumption in buildings get changes greatly in regard to combination of settlement scale design parameters. Alternative with form factor 3.00,10 storey, directed to east-west, and H/W 0.5 showed best performance and provided 7% to %17 energy reduction according to different parameter combinations.

In this study, the overall energy status of Turkey in the early stage of the COVID-19 pandemic was analyzed. The situation in the energy market and electricity demand in the pandemic period as glob...

The main goal of this study is to evaluate the impact of population mobility on electricity generation in Russian cities in the conditions of the spread of COVID-19, and identify hotspots. Furthermore, the evaluation is also conducted using hybrid fuzzy decision-making modelling. In this context, q-ROF DEMATEL and TOPSIS methods are taken into consideration. Additionally, a comparative evaluation is also performed with the help of Intuitionistic and Pythagorean fuzzy sets. The results are quite similar that allows to conclude that the findings are reliable and coherent. The study proves the hypothesis that human behavior changed during the COVID-19 pandemic, and electricity consumption is declining in major cities around the world. The biggest fall in energy generation was in Moscow and Yekaterinburg. In St. Petersburg and Nizhny Novgorod, the fall in energy generation is no so crucial because these cities have low building density. The study uses Long Short-Term Memory models with many different parameters. The Q-Rung Orthopair Fuzzy Sets model forecasts new COVID-19 using ten parameters. This study identifies factors influencing the spread of COVID-19 based on the theory of "broken windows" and outlines directions in limiting population mobility, which can form the basis of state policy. According to the analysis the air temperature is the variable that most affects this process.

In this study, metal analyzes were made on filtered samples belonging to different periods of 2017 and 2018 at the air quality stations in Yenibosna, Aksaray and Kadıköy in Istanbul, and were evaluated together with sulfate, nitrogen oxides, carbon monoxide and ozone parameters published by the Istanbul Metropolitan Municipality. Correlations among the metals and among gases were calculated. Considering all the data, the heavy metals with the highest correlation were Fe-Cu (0.93) and Mn-Zn (0.80). In order to determine whether the metal analysis results are at the level of pollution, the enrichment factor was calculated by taking the aluminum element as a reference. The elements that was seen enrichment in all stations are Cd, Zn, Cu and Pb. In addition, the ratios of the average enrichment factors to each other were calculated in order to determine the changes in the compared periods (summer-winter or months) at the stations. In the Aksaray station, where summer-winter comparison was made, the metals with the highest enrichment in winter were Pb and Ni. In order to see the effect of the quarantines applied periodically throughout the country due to the Covid-19 pandemic on the air pollution in Istanbul, the pollutant gas data shared by the IMM AQMC for 2019, 2020 and 2021 years were evaluated and seen that different situations at each station. In Kadıköy station, both the lowest CO and the highest NO and NOx (although they decreased significantly) emissions were determined in 2021.

Satisfying customer demand is one of the growing concerns of supply chain managers. On the other hand, the development of internet communications has increased online demand. In addition, the COVID-19 pandemic has increased the demand for online shopping. One of the useful concepts that help to address this concern is the omni-channel strategy, which integrates online and traditional channels with the aim of improving customer service level. For this purpose, this paper proposes an algorithm for evaluating Omni-channel Distribution Network Configurations (OCDNCs). The algorithm applies an extended Data Envelopment Analysis (DEA) model to evaluate OCDNCs based on cost, service, transparency, and environmental criteria; and then, forms a consensus on the evaluation results generated according to different criteria by utilizing an uncertain optimization model. To the best of our knowledge, this is the first attempt in which such an algorithm has been employed to take into account the mentioned criteria in a model to evaluate OCDNCs. The application of the proposed models was investigated in a case study in relation to the Indian retail industry. The results show that the configuration with the most connections among its members was the most stable, robust, and efficient.

In the present study, the purpose was to determine the direct and indirect effects of the crisis management skills and distance education practices of universities on student satisfaction and organizational image in the continuing Coronavirus pandemic. To conduct the study, a questionnaire was applied to 467 students who had to receive compulsory distance education at TRNC universities during the pandemic process. The relation levels between the crisis management and distance education practices of universities, corporate image, student satisfaction, and direct and indirect effects between the variables, were designed with a structural equation modeling by forming hypotheses according to the sub-dimensions of the student satisfaction scale. The findings of the study showed that as the crisis management of the university administrations in the pandemic process was perceived positively by the students, their organizational image and satisfaction increased. However, it was detected that there was a lower level of relationship between attitudes towards distance learning and crisis management, and that this had a limited effect on student satisfaction. It was concluded that the structural equation model can be used to explain the causal relationship between the variables. The study also showed that the determinants of organizational image and student satisfaction in education must be understood better and that universities must review their crisis management and distance education practices and develop new service plans.

In 2020, tourism was highly affected by COVID-19 and its restrictions, such as tourist traffic. Decisions related to trips were made in a state of high risk and uncertainty. This article’s main aim is to present the results of research on decision making by people practising sailing tourism during COVID-19. The survey was conducted in the first quarter of 2021 on 580 sailors from Poland, Germany, Croatia, Italy, France, and Turkey. This is interesting because of the specificity of this form of nautical tourism, which is characterised by high flexibility in the planning and implementation of the cruise. Sailing tourism is also environmentally friendly due to the type of propulsion used and the low noise levels generated. Research has shown that country-specific travel restrictions impact sailing tourism and cruise decisions. The obtained results are important for developing sailing tourism and may contribute to rationalising decisions taken during crises.