BackgroundImaging of the human microcirculation in real-time has the potential to detect injuries and illnesses that disturb the microcirculation at earlier stages and may improve the efficacy of resuscitation. Despite advanced imaging techniques to monitor the microcirculation, there are currently no tools for the near real-time analysis of the videos produced by these imaging systems. An automated system tool that can extract microvasculature information and monitor changes in tissue perfusion quantitatively might be invaluable as a diagnostic and therapeutic endpoint for resuscitation.MethodsThe experimental algorithm automatically extracts microvascular network and quantitatively measures changes in the microcirculation. There are two main parts in the algorithm: video processing and vessel segmentation. Microcirculatory videos are first stabilized in a video processing step to remove motion artifacts. In the vessel segmentation process, the microvascular network is extracted using multiple level thresholding and pixel verification techniques. Threshold levels are selected using histogram information of a set of training video recordings. Pixel-by-pixel differences are calculated throughout the frames to identify active blood vessels and capillaries with flow.ResultsSublingual microcirculatory videos are recorded from anesthetized swine at baseline and during hemorrhage using a hand-held Side-stream Dark Field (SDF) imaging device to track changes in the microvasculature during hemorrhage. Automatically segmented vessels in the recordings are analyzed visually and the functional capillary density (FCD) values calculated by the algorithm are compared for both health baseline and hemorrhagic conditions. These results were compared to independently made FCD measurements using a well-known semi-automated method. Results of the fully automated algorithm demonstrated a significant decrease of FCD values. Similar, but more variable FCD values were calculated using a commercially available software program requiring manual editing.ConclusionsAn entirely automated system for analyzing microcirculation videos to reduce human interaction and computation time is developed. The algorithm successfully stabilizes video recordings, segments blood vessels, identifies vessels without flow and calculates FCD in a fully automated process. The automated process provides an equal or better separation between healthy and hemorrhagic FCD values compared to currently available semi-automatic techniques. The proposed method shows promise for the quantitative measurement of changes occurring in microcirculation during injury.
Day-ahead electricity market (DAM) volatility and price forecast errors have grown in recent years. Changing market conditions, epitomised by increasing renewable energy production and rising intraday market trading, have spurred this growth. If forecast accuracies of DAM prices are to improve, new features capable of capturing the effects of technical or fundamental price drivers must be identified. In this paper, we focus on identifying/engineering technical features capable of capturing the behavioural biases of DAM traders. Technical indicators (TIs), such as Bollinger Bands, Momentum indicators, or exponential moving averages, are widely used across financial markets to identify behavioural biases. To date, TIs have never been applied to the forecasting of DAM prices. We demonstrate how the simple inclusion of TI features in DAM forecasting can significantly boost the regression accuracies of machine learning models; reducing the root mean squared errors of linear, ensemble, and deep model forecasts by up to 4.50%, 5.42%, and 4.09%, respectively. Moreover, tailored TIs are identified for each of these models, highlighting the added explanatory power offered by technical features.
Amaç: Bu çalışmada intihar olgularının demografik yönden irdelenmesi ve ilerleyen yıllar içinde seçilen intihar yöntemleri başta olmak üzere muhtelif yönlerden farklılık oluşup oluşmadığının ve bilhassa da ateşli silahla intihar oranında artış bulunup bulunmadığının araştırılması amaçlanmıştır. Gereç ve Yöntem: Pamukkale Üniversitesi Tıp Fakültesi Adli Tıp Anabilim Dalı otopsi salonunda 2007- 2016 tarihleri arasında otopsisi yapılan 444 intihar olgusu ele alınarak; yaş, cinsiyet, seçilen intihar yeri ve intihar yöntemi, intiharların yıllara ve mevsimlere göre dağılımı gibi parametrelerdeki değişimler yönünden değerlendirilmiştir. Bulgular: Olguların %79,1’i erkek, %20,9’u kadındır. İntiharların en sık 19-30 yaş grubunda gerçekleştirildiği gözlenmiştir. Asının %52,3 oranı ile en sık seçilen intihar yöntemi olduğu, bunu %28,4 oranı ile ateşli silah kullanımının izlediği görülmüştür. Ateşli silahla intihar yönteminin ilerleyen yıllar içerisinde artış gösterdiği, bu artış oranının genç erkeklerde daha yüksek olduğu dikkati çekmiştir. Sonuç: Ateşli silahlarla gerçekleştirilen intiharlarda yıllar içinde artış olduğu görülmüştür. Ergenlerin ve genç yetişkin erkeklerin riskli grubu oluşturması, bu yaş grubuna dikkat edilmesi gerektiğini göstermektedir. İntiharla mücadele için oluşturulacak programlara av tüfeği ve ateşli silahların temini, bulundurulması ve taşınması ile ilgili yeni yasal düzenlemeler ve her türlü ruhsatsız silahla etkili mücadele de eklenmelidir.
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