Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Monitoring and Prediction of Urban Expansion Using Multilayer Perceptron Neural Network By Remote Sensing and Gis Technologies: A Case Study from Istanbul Metropolitan City

WOS: 000455562500076The most significant occurrence in this era is rapid urbanization. Especially in developing countries, the cities have an obvious expansion due to rapid population growth, economic development and infrastructure development initiatives. It is crucial to monitoring and to predict the urban expansion for sustainable cities in terms of settlement planning, transportation, landscaping, etc. At this point, remote sensing data (especially satellite data) and geographic information system (GIS) techniques allow us to get necessary data with high spatial, spectral and temporal resolution. This study aims to detect the Land Use and Land Cover (LULC) of the Istanbul Metropolitan City from 2003 to 2016 in purpose of urban expansion by using Landsat 5 and Landsat 8 satellite images in a GIS environment and to predict the status of the city in 2030. The study was carried out in two main steps. In the First step, the LULC changes are detected in Land Change Modeler (LCM) between initial and final dates. This step is very similar to a basic change detection process. The second step is to predict the city statues for a future date. In this step, the results from first step such as classification images are evaluated in a Multilayer Perceptron (MLP) approach and then the expansion of the city is predicted. In our case, the change rate of built-up area from 2003 to 2030 is predicted as (+) 48%. The MLP approach allows us to detect the transitions between LULC classes which are very important for city planning. According to results the main transition to built-up area will come from agricultural land. In the end, this study exhibits the advantages of remote sensing and GIS and the importance of urban expansion monitoring in terms of prediction

Development of A Model for Determınıng the Traffıc Accıdent Black Spots Based on Geographıcal Informatıon Systems (Gıs) Aıded Spatıal Statıstıcal Methods

Traffic accidents are one of the important problems in our country as it in the world. The World Health Organization case reports published in 2015 is stated that about 1.25 million people died each year and more than 50 million people injured as a result of traffic accidents in the World. Considering this situation, it is seen that the traffic accidents are human origin and one of the major problems that is negatively affecting life. In this context, many investments and many studies performed to reduce traffic accidents. The thesis takes into account a variety of reasons in order to determine traffic accident black spot. It is aimed to get a descriptive model for determining the traffic accident black spots by using model-based spatial statistical methods. These methods are accident rate, accident frequency, accident severity, Getis Ord Gi *, Moran's I, Poisson regression, Negative Binomial regression and empirical Bayesian method. The ultimate aim of this study is to build a model that allows evaluating all the methods together in Geographic Information Systems (GIS) which is now quite widely in use. In this study, 300 thousand traffic accident data of 2408 different state road covering the years 2005-2013 obtained from General Directorate of Highways. State roads are divided into 32107 sub-segments that all is 1km. depending on the methods are used in the study, 126 sub-segment are decided as traffic accident black spots. According to comparison of the methods used in the study, the Empirical Bayesian method is giving better results than other methods.Trafik kazaları dünyada olduğu gibi ülkemizde de önemli problemlerden birisidir. Dünya Sağlık Örgütü’ nün yayımladığı 2015 yılı durum raporunda trafik kazaları sonucu her yıl yaklaşık 1.25 milyon insanın yaşamını yitirdiği ve 50 milyondan fazla insanın da yaralandığı belirtilmektedir. Bu durum dikkate alındığında, trafik kazalarının hayatı olumsuz etkileyen insan kaynaklı önemli bir problem olduğu görülmektedir. Bu kapsamda trafik kazalarının azaltılmasına yönelik birçok yatırım ve buna bağlı olarak da birçok çalışma gerçekleştirilmektedir. Bu çalışmaların bir kısmı da çeşitli sebepleri dikkate alan trafik kaza kara nokta belirleme çalışmalarıdır. Bu çalışmada trafik kaza kara noktalarının belirlenmesine yönelik bir model geliştirilmesi amacıyla tanımlayıcı, mekânsal ve model bazlı istatistiksel yöntemler çalışılmıştır. Bu yöntemler kaza oranı, kaza frekansı, kaza şiddeti, Getis Ord Gi*, Moran’s I, Poisson regresyon, Negatif Binomiyal regresyon ve Ampirik Bayes yöntemleridir. Bu çalışmanın nihai amacı, günümüzde oldukça yaygın bir şekilde kullanılmakta olan Coğrafi Bilgi Sistemleri (CBS)’de tüm yöntemlerin birlikte değerlendirildiği bir model oluşturmaktır. Bu çalışmada, Karayolları Genel Müdürlüğü’nden temin edilen 2005-2013 yıllarını kapsayan yaklaşık 300 bin trafik kaza verisi ile 2408 adet devlet yolu kullanılmıştır. Devlet yollarının birer km’lik alt segmentlere ayrılması sonucunda elde edilen 32107 segment içinden 126 adet segmentin, kullanılan yöntemler doğrultusunda kara nokta olduğu yargısına varılmıştır. Çalışma bünyesinde uygulanan yöntemlerin analizi yapıldığında ise Ampirik Bayes yönteminin, diğer yöntemlere nazaran daha iyi sonuçlar verdiği görülmüştür

Determination of short-term land cover change by sentinel-2A satellite imagery for Giresun city center

Sentinel-2A uydusu, orta konumsal çözünürlüğe (10-60) sahip olan ve ESA tarafından geliştirilenmultispektral bir araçtır. Genel olarak bu uydu sensörlerinin işlevlerinden bir tanesi de arazi örtüsü vekullanımına ilişkin haritalama işlemleridir. Son yıllarda Sentinel-2A MSI (Multispectral Instrument) uydusensörlerinin yeterliliğini ve potansiyelini göstermek amacıyla farklı çalışmaların yapıldığı görülmüştür.Ülkemizde ise Sentinel-2A uydu görüntüleri ile yapılan çalışmaların sınırlı kalması, bu çalışmanın öneminiortaya koymaktadır. Bu çalışmadaki temel amaç Sentinel-2A uyduları kullanılarak Giresun iline ilişkinarazi örtüsü ve kullanımının zamansal değişimin belirlenmesidir Bu kapsamda, 2017 ve 2018 yıllarınailişkin Sentinel-2A uydusundan Giresun il merkezini kapsayan uydu görüntüleri, ESA’nın veri sağlayıcıweb adresinden temin edilmiştir. Yapılan çalışmada bu iki yıla ilişkin arazi örtüsü değişimleri belirlenmişolup, arazi sınıflarının kayıp ve kazançları hesaplanmıştır. Yaklaşık 29 km2’lik alanda gerçekleştirilenuygulamada, genellikle yeşil ve yapım alanların kendi içerisinde yer değiştiği belirlenmiştir. Bununlabirlikte yeşil alanlardan yapım alanlarına da yaklaşık olarak 63 hektarlık alanın geçtiği hesaplanmıştır.Sonuç olarak ücretsiz erişim imkânı sağlayan Sentinel-2A uydu görüntülerinin, arazi örtüsü vekullanımının belirlenmesinde kullanılabilirliği ortaya konmuştur.The Sentinel-2A satellite is a multispectral instrument with medium spatial resolution (10-60 m)developed by ESA. In general, one of the tasks of the satellite is also mapping process of land cover anduse. In recent years, different studies have been conducted to demonstrate the adequacy and potentialof Sentinel-2A MSI (MultiSpectral Instrument) satellite sensors. In our country, the limited studies doneby the Sentinel-2A satellite images reveal the importance of this study. The main purpose of this studyis to determine the temporal change of land use and land cover of Giresun province using Sentinel-2Asatellites. In this context, the satellite images covering Giresun province center from Sentinel-2Asatellite for 2017 and 2018 were obtained from ESA's data provider web address. The land coverchanges for the years were determined and the losses and gains of the land classes were calculated. Inpractice area which is about 29 km2, it is generally determined that green and construction sites arereplaced within the area. In addition to this, it is calculated that approximately 63 hectares have beenpassed from the green areas to the construction sites As a result, the usage of Sentinel-2A satelliteimages, which provide free access, has been demonstrated in the determination of land use and land

Development of A Model for Determınıng the Traffıc Accıdent Black Spots Based on Geographıcal Informatıon Systems (Gıs) Aıded Spatıal Statıstıcal Methods

Traffic accidents are one of the important problems in our country as it in the world. The World Health Organization case reports published in 2015 is stated that about 1.25 million people died each year and more than 50 million people injured as a result of traffic accidents in the World. Considering this situation, it is seen that the traffic accidents are human origin and one of the major problems that is negatively affecting life. In this context, many investments and many studies performed to reduce traffic accidents. The thesis takes into account a variety of reasons in order to determine traffic accident black spot. It is aimed to get a descriptive model for determining the traffic accident black spots by using model-based spatial statistical methods. These methods are accident rate, accident frequency, accident severity, Getis Ord Gi *, Moran's I, Poisson regression, Negative Binomial regression and empirical Bayesian method. The ultimate aim of this study is to build a model that allows evaluating all the methods together in Geographic Information Systems (GIS) which is now quite widely in use. In this study, 300 thousand traffic accident data of 2408 different state road covering the years 2005-2013 obtained from General Directorate of Highways. State roads are divided into 32107 sub-segments that all is 1km. depending on the methods are used in the study, 126 sub-segment are decided as traffic accident black spots. According to comparison of the methods used in the study, the Empirical Bayesian method is giving better results than other methods.Trafik kazaları dünyada olduğu gibi ülkemizde de önemli problemlerden birisidir. Dünya Sağlık Örgütü’ nün yayımladığı 2015 yılı durum raporunda trafik kazaları sonucu her yıl yaklaşık 1.25 milyon insanın yaşamını yitirdiği ve 50 milyondan fazla insanın da yaralandığı belirtilmektedir. Bu durum dikkate alındığında, trafik kazalarının hayatı olumsuz etkileyen insan kaynaklı önemli bir problem olduğu görülmektedir. Bu kapsamda trafik kazalarının azaltılmasına yönelik birçok yatırım ve buna bağlı olarak da birçok çalışma gerçekleştirilmektedir. Bu çalışmaların bir kısmı da çeşitli sebepleri dikkate alan trafik kaza kara nokta belirleme çalışmalarıdır. Bu çalışmada trafik kaza kara noktalarının belirlenmesine yönelik bir model geliştirilmesi amacıyla tanımlayıcı, mekânsal ve model bazlı istatistiksel yöntemler çalışılmıştır. Bu yöntemler kaza oranı, kaza frekansı, kaza şiddeti, Getis Ord Gi*, Moran’s I, Poisson regresyon, Negatif Binomiyal regresyon ve Ampirik Bayes yöntemleridir. Bu çalışmanın nihai amacı, günümüzde oldukça yaygın bir şekilde kullanılmakta olan Coğrafi Bilgi Sistemleri (CBS)’de tüm yöntemlerin birlikte değerlendirildiği bir model oluşturmaktır. Bu çalışmada, Karayolları Genel Müdürlüğü’nden temin edilen 2005-2013 yıllarını kapsayan yaklaşık 300 bin trafik kaza verisi ile 2408 adet devlet yolu kullanılmıştır. Devlet yollarının birer km’lik alt segmentlere ayrılması sonucunda elde edilen 32107 segment içinden 126 adet segmentin, kullanılan yöntemler doğrultusunda kara nokta olduğu yargısına varılmıştır. Çalışma bünyesinde uygulanan yöntemlerin analizi yapıldığında ise Ampirik Bayes yönteminin, diğer yöntemlere nazaran daha iyi sonuçlar verdiği görülmüştür

Comparison of GIS-based surrogate weighting methods for multi-directional landfill site selection in West Mediterranean Planning Region in Turkey

WOS: 000527908600004On account of sustainable municipal solid waste (MSW) management, the determination of appropriate positions for MSW multi-directional landfill sites includes thought of geomorphological, topographical, hydrological, monetary and environmental parameters. Deciding these regions in a manner that limits ecological contamination and well-being dangers is a significant multi-criteria decision-making issue in the controls of land executives. A landfill site choice procedure has been completed utilizing three pure weighting techniques (rank sum, rank reciprocal and rank-order centroid) coordinated with geographical information system instruments. The outcomes demonstrate that 32,045 km(2) (87.4%) of the total area is inadmissible for landfill sites. This study compares the results of three subjective weighting methods at a large-scale regional planning scenario. The exhibited methodology helps chiefs in deciding safe areas for MSW landfill sites. The results show that in the early period of the spatial planning, simplified pure methods can be adequate. In this case, using more complicated methods will not definitely deduce different findings. However, when regional planning requires identifying the spatial scope of the favored specific sites, considering the intersection area proposed by three methods will be ideal

A GIS‑based multi‑criteria evaluation for MSW landfill site selection in Antalya, Burdur, Isparta planning zone in Turkey

Defining the suitable positions for landfill sites on a regional scale is a decision-making procedure based on a number of criteria. In this study, geographic information system analysis and multi criteria decision making method have been utilised to search for spatial suitability of landfill sites by considering legislative, technical, social and environmental criteria. Fourteen exclusion criteria have been determined and the sites which are not eligible for being landfills have been deducted. Analytical hierarchy process has been used to determine the weights of three main and sixteen provisional evaluation criteria affecting the choice of landfill sites. Weighted linear combination method has been utilised to evaluate all the criteria with combination process. Also landfill suitability map has been created in the study area’s high and low potential. The results indicate that 4.03% of study area is moderately suitable, 3.75% is highly suitable for landfill sites. Only 58% of existing landfill sites embedded in the Antalya–Burdur–Isparta Environmental Plan, coincide with the appropriate areas identified in this study. These findings indicate that planning decisions have been taken regardless of hydrological, geological and land use conditions. This study will propose a systematic protocol for decision makers to identify and assess the hotspots which are suitable for landfill sites in the anticipated planning region.No sponso

A GIS-based multi-criteria model for offshore wind energy power plants site selection in both sides of the Aegean Sea

Location selection for offshore wind farms is a major challenge for renewable energy policy, marine spatial planning, and environmental conservation. This selection constitutes a multi-criteria decision-making problem, through which parameters like wind velocity, water depth, shorelines, fishing areas, shipping routes, environmental protection areas, transportation, and military zones should be jointly investigated. The aim of the present study was thus to develop an integrated methodology for assessing the siting of bottom-fixed offshore wind farms in two different countries (with different legal, political, and socio/economic characteristics). Our methodology combined multi-criteria decision making methods and geographical information systems and was implemented in Cyclades (Greece) and in the sea area of İzmir region (Turkey). Experts used fuzzy sets and linguistic terms to achieve more consistent and independent rankings and results. In the Turkish region, the results showed that 519 km2 (10.23%) of the study area is suitable for offshore wind farms, while in the Greek region, only 289 km2 (3.22%) of the study area was found to be suitable. This spatial suitability analysis may contribute to provide some useful recommendations for the spatial marine planning at the regional scale, as well as for the preliminary assessment of new offshore wind farms in both countries.No sponso