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    Synthesıs, Characterızatıon And Bıologıcal Applıcatıons Of Green Synthesıs Method Of Cuo Nanopartıcles From Daphne (Laurus Nobilis) Leaf Extract

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    Metal oksit nanopartiküllerinin biyosentezi, dolgu malzemesi, opaklaştırıcılar, dezenfektanlar, antimikrobiyal ajanlar, katalizörler, ilaç dağıtım materyalleri gibi sektörlerde ve tıbbi alanlarda artan talep nedeniyle son yıllarda büyük ilgi görmeye başlamıştır. Bazı bitki ve meyve özlerinde bulunan bileşikler, metal nanoparçacıkların biyojenik sentezi için bir indirgeyici görevi görür. CuO nanoparçacıkları, birçok ticari antimikrobiyal maddeye dirençli olan çeşitli patojenlere karşı biyosidal etki gösterdikleri için çok güçlü antimikrobiyal maddelerdir. Defne yaprağı (Laurus nobilis) Lauraceae familyasına ait bir bitki türüdür, tüm Batı ve Asya ülkelerinde yaygın olarak kullanılan baharat çeşitlerinden biridir. Bu çalışmada, CuO nanoparçacıkları, yeşil sentez yöntemi ile basit, uygun maliyetli ve çevre dostu olarak sentezlenmiştir. Bunun için; bitkisel kaynak olarak defne yaprağı ekstraktı, metal iyon kaynağı olarak da 0.1 M CuSO4 çözeltisi kullanılmıştır. Elde edilen CuO nanopartiküllerin karakterizasyonu; X-ışını difraktometresi (XRD), Fourier dönüşümlü kızılötesi spektroskopisi (FT- IR), Taramalı elektron mikroskobu (SEM), Enerji dağılımlı X-ışınının analizi (EDAX) ve Diferansiyel termal analiz (TGA/DTA) metotları ile yapısal analizleri yapıldı. Ayrıca, elde edilen tüm örneklerin antimikrobiyal ve sitotoksik aktiviteleri çalışıldı ve sonuçlar ayrıntılı olarak tartışıldı. Yapılan çalışmalar sonucunda SEM görüntülerinden parçacıkların düzensiz kenarlara sahip olduğu, morfolojisinin ise küresel yapıya benzer bir yapıda olduğu görülmüşütür. TEM analizleri sonucunda ise nanopartiküllerin boyut aralığı yaklaşık 16-36 nm aralığında olduğu anlaşılmıştır. DTA grafiğinden elde edilen sonuca göre nanopartiküller 25-1000 oC sıcaklık aralığında kararlı yapıda olduğu tespit edilmiştir. CuO nanopartiküllerinin stotoksik aktivite sonuçları DLD-1 insan kolon kanseri hücre hattında çalışılmış ve CuO nanopartiküllerin konsantrasyonu arttıkça hücre aktiviteleri azalmıştır.The biosynthesis of metal oxide nanoparticles has attracted much attention in recent years due to its increasing demand in industries and medical fields as fillers, opacifiers, disinfectants, antimicrobial agents, catalysts, drug delivery materials etc. The compoundsin some plant and fruit extracts acts as a reductant of the metal oxide nanoparticles biogenic synthesis. CuO nanoparticles are highly potent antimicrobial agents because they exhibit biocidal effect against various pathogens that are resistant to many commercial antimicrobial agents. Bay leaf (Laurus nobilis) belongs to the family Lauraceae, is one of the most widely used culinary spices in all Western countries and Asian countries. In this study, CuO nanoparticles were synthesized by green synthesis method as simple, cost effective and environment friendly. For this purpose; laurel leaf extract was used as plant source and 0.1 M CuSO4 solution was used as metal ion source. The obtained nanoparticles were characterized by UV-visible spectroscopy (UV–vis), X-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FT-IR), Scanning electron microscopy (SEM), Energy dispersive analysis of x-ray (EDAX). The antimicrobial and antioxidant activities of all the samples obtained were studied and the results were discussed in detail. As a result of the studies, it was seen from the SEM images that the particles had irregular edges and the morphology was similar to the spherical structure. As a result of TEM analysis, it was found that the size range of nanoparticles was in the range of about 16-36 nm. According to the results obtained from the DTA graph, nanoparticles were found to be stable in the temperature range of 25-1000 oC. The results of the cytotoxic activity of CuO nanoparticles were studied on human colon cancer cells and as the concentration of nanoparticles increased, cell activities decreased

    Guidance for the Management of Patients with Vascular Disease or Cardiovascular Risk Factors and COVID-19: Position Paper from VAS-European Independent Foundation in Angiology/Vascular Medicine

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    COVID-19 is also manifested with hypercoagulability, pulmonary intravascular coagulation, microangiopathy, and venous thromboembolism (VTE) or arterial thrombosis. Predisposing risk factors to severe COVID-19 are male sex, underlying cardiovascular disease, or cardiovascular risk factors including noncontrolled diabetes mellitus or arterial hypertension, obesity, and advanced age. The VAS-European Independent Foundation in Angiology/Vascular Medicine draws attention to patients with vascular disease (VD) and presents an integral strategy for the management of patients with VD or cardiovascular risk factors (VD-CVR) and COVID-19. VAS recommends (1) a COVID-19-oriented primary health care network for patients with VD-CVR for identification of patients with VD-CVR in the community and patients' education for disease symptoms, use of eHealth technology, adherence to the antithrombotic and vascular regulating treatments, and (2) close medical follow-up for efficacious control of VD progression and prompt application of physical and social distancing measures in case of new epidemic waves. For patients with VD-CVR who receive home treatment for COVID-19, VAS recommends assessment for (1) disease worsening risk and prioritized hospitalization of those at high risk and (2) VTE risk assessment and thromboprophylaxis with rivaroxaban, betrixaban, or low-molecular-weight heparin (LMWH) for those at high risk. For hospitalized patients with VD-CVR and COVID-19, VAS recommends (1) routine thromboprophylaxis with weight-adjusted intermediate doses of LMWH (unless contraindication); (2) LMWH as the drug of choice over unfractionated heparin or direct oral anticoagulants for the treatment of VTE or hypercoagulability; (3) careful evaluation of the risk for disease worsening and prompt application of targeted antiviral or convalescence treatments; (4) monitoring of D-dimer for optimization of the antithrombotic treatment; and (5) evaluation of the risk of VTE before hospital discharge using the IMPROVE-D-dimer score and prolonged post-discharge thromboprophylaxis with rivaroxaban, betrixaban, or LMWH

    THE EFFECT OF COOLING LOAD ON OPTIMUM INSULATION THICKNESS IN RESIDENTIAL BUILDINGS

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    The main objective of this study is to determine the optimum insulation thickness of residential buildings in Turkey, under the influence of cooling loads by life cycle cost analysis (LCCA) and to specify the Degree Day (DG) regions that the cooling load should also be included in the calculations in the TS 825 ``Heat Insulation Rules in Buildings{''} standard. A 5-storey apartment building with an Area/Volume ratio (A/V) of 0,40 m(-1) is taken as a reference building. The annual energy requirements of the reference building for cooling loads are calculated according to TS EN ISO 13790 standard. Life-cycle cost analysis based on the total cost approach is performed for a period of 30 years. Optimum insulation thicknesses based on climate zones are calculated between 0 cm and 4 cm for wall, 0 cm and 7,5 cm for ceiling, 0 cm and 2,7 cm for floor. As a result, it has been determined that cooling load should be included in the optimum insulation thickness calculations in the DG1 and DG2 regions specified in the TS 825 standard It is concluded that the cooling loads don't affect the optimum insulation thickness in DG3 and DG4 regions where the cooler climate is more effective than DG1 and DG2 regions

    Weighted Ensemble Object Detection with Optimized Coefficients for Remote Sensing Images

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    The detection of objects in very high-resolution (VHR) remote sensing images has become increasingly popular with the enhancement of remote sensing technologies. High-resolution images from aircrafts or satellites contain highly detailed and mixed backgrounds that decrease the success of object detection in remote sensing images. In this study, a model that performs weighted ensemble object detection using optimized coefficients is proposed. This model uses the outputs of three different object detection models trained on the same dataset. The model's structure takes two or more object detection methods as its input and provides an output with an optimized coefficient-weighted ensemble. The Northwestern Polytechnical University Very High Resolution 10 (NWPU-VHR10) and Remote Sensing Object Detection (RSOD) datasets were used to measure the object detection success of the proposed model. Our experiments reveal that the proposed model improved the Mean Average Precision (mAP) performance by 0.78\%-16.5\% compared to stand-alone models and presents better mean average precision than other state-of-the-art methods (3.55\% higher on the NWPU-VHR-10 dataset and 1.49\% higher when using the RSOD dataset)

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