Autor: Cakır, R. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Water holding properties and soil water types in fine textured Vertisol soils of Thrace region in Turkey
Autorzy:: Cakir, R.
Cangir, C.
Powiązania:: https://bibliotekanauki.pl/articles/971457.pdf
Data publikacji:: 2019
Wydawca:: Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:: cracking soils
texture
clay
hydraulic properties
Opis:: The study was carried out on 16 selected model soil profiles, located on lands covered with soils exhibiting vertic properties in Thrace Region of Turkey. Different horizons and/or sub-horizons of 16 characteristic soil profiles were evaluated in field or laboratory conditions in terms of water holding capacity and water types properties. Total of 105 soil samples were analyzed for routine physical characteristics. Soil water holding capacity was determined applying negative potentials (Ψ) of -0.33 bar, -15.5 bar and -31.5 bar (pF 2.54; 4.2 and 4.5), using a pressure-membrane extraction apparatus. In addition to gravitational, available, unavailable and hygroscopic soil water types, the soil samples were investigated also in terms of crystal-lattice water content. The highest amounts of the listed water types were determined in soils of Büyük Mandira, Türkgeldi and Seymen containing the highest rates of smectite clay mineral. The mass percentage (Pw) rates of the mentioned water types of the investigated profies varied in the ranges of 29.1–66.3%, 10–2.15%, 22.0–32.4%, 6.0–9.0% and 5.6–8.6%, respectively. Though the mass percentages of enumerated water types in the soils of Osmanli and Yeni Mahalle, all owning high sand and lower clay content on the other hand, are between 28.9–40.6%, 6.1–15.5%, 7.4–16.8%, 2.4–4.8% and 1.7–4.4%, respectively.
Źródło:: Polish Journal of Soil Science; 2019, 52, 2; 247-258
0079-2985
Pojawia się w:: Polish Journal of Soil Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Superconducting Cavity Utilization for Linear Accelerator Systems
Autorzy:: Yildiz, H.
Cakir, R.
Porsuk, D.
Powiązania:: https://bibliotekanauki.pl/articles/1401998.pdf
Data publikacji:: 2015-08
Wydawca:: Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:: 29.20.Ej
42.60.By
Opis:: Self amplified stimulated emission free electron laser production from electron energy above 1.5 GeV is studied to obtain 1-100 nm laser wavelength. Design simulations of linear accelerating system with gun and enjector system has been done in more detail by considering space charge effect for electron beam. Electromagnetic field for superconducting cavities, solenoid fields, cavity defects such as Higher Order Modes, Multipacting, Lorentz Force Detuning, and beam behaviour along the beamline are very important details for this study. Optimised cavity cell design layout are provided in order to obtain quality factor $10^9$ for designed cavities throughout the main linear acceleration. To determine coupling factor, and zero modes and also other modes with relative errors are searched.
Źródło:: Acta Physica Polonica A; 2015, 128, 2B; B-246-B-247
0587-4246
1898-794X
Pojawia się w:: Acta Physica Polonica A
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Biometrical and biochemical properties of fruits of mini cucumber plants grown under various irrigation regimes in an unheated greenhouse
Autorzy:: Çebi, U.K.
Çakir, R.
Altintas, S.
Ozdemir, A.G.
Powiązania:: https://bibliotekanauki.pl/articles/12193499.pdf
Data publikacji:: 2018
Wydawca:: Uniwersytet Przyrodniczy w Lublinie. Wydawnictwo Uniwersytetu Przyrodniczego w Lublinie
Opis:: The study aimed to determine the most appropriate irrigation scheduling for mini-type cucumber plants grown as a spring-summer cycle crop. The research was conducted in a greenhouse structure in the fields of the Research Institute in Kirklareli. Marathon cucumber plants were used as the plant material in the trials. The split plot design experimental layout in 3 replications was used in the research. Four different plant–pan coefficients (0.75, 1.00, 1.25 and 1.50) and two irrigation intervals (2 and 4 days) were applied as subplots and main plots of the study, respectively. As a result of the 3-year investigation, it was determined that yields, number of cucumber fruits, and fresh cucumber fruit weight, length and diameter increased with the increase in the irrigation water amount. The highest average total soluble solids (Brix) value of 5.0 was recorded under conditions of most severe stress imposed on the plots with lowest water application rates of Kcp 0.75. While the lowest values of 4.0–4.1 were obtained for plants growing under more favorable moisture conditions in plots with application of Kcp 1.25 and 1.50. Statistically significant positive linear relationships were obtained for irrigation water amount on one hand, and fruit number, fruit mean weight, fruit length and diameter on the other, while the relationship between water applied and TSS (Brix) was negative.
Źródło:: Acta Scientiarum Polonorum. Hortorum Cultus; 2018, 17, 5; 199-212
1644-0692
Pojawia się w:: Acta Scientiarum Polonorum. Hortorum Cultus
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Prediction and classification of pressure injuries by deep learning
Wykrywanie i klasyfikacja odleżyn z wykorzystaniem deep learning
Autorzy:: Yilmaz, A.
Kızıl, H.
Kaya, U.
Cakır, R.
Demiral, M.
Powiązania:: https://bibliotekanauki.pl/articles/2047948.pdf
Data publikacji:: 2021
Wydawca:: Akademia Bialska Nauk Stosowanych im. Jana Pawła II w Białej Podlaskiej
Tematy:: deep learning
pressure ulcers
artificial intelligence
nursing care
odleżyny
sztuczna inteligencja
opieka pielęgniarska
Opis:: Pressure injuries are a serious medical problem that both negatively affects the patient's quality of life and results in significant healthcare costs. In cases where a patient doesn’t receive appropriate treatment and care, death may result. Nurses play critical roles in the prevention, care, and treatment of pressure injuries as members of the healthcare team who closely monitor the health status of the patient. Today, the use of artificial intelligence is becoming more prevalent in healthcare, as in many other areas. Artificial intelligence is a method that aims to solve complex problems by using computers to mathematically simulate the way the brain works. In this article, we compile and share information about a deep learning model developed for the detection and classification of pressure injuries. Deep learning can operate on many types of data. Convolutional Neural Networks (CNN) prefer images because they can handle 2D arrays. In this case, the images, annotated according to the National Pressure Injury Advisory Panel pressure injury classification system, have been fed into a deep learning model using CNN. The developed CNN model has a 97% success in detecting and classifying pressure injuries, and as more images are collected and fed into the CNN, the prediction accuracy will increase. This deep learning model allows for the automatic detection and classification of pressure injuries, an indicator of health outcomes, at an early stage and for quick and accurate intervention. In this context, it is expected that the quality of nursing care will increase, the prevalence of pressure injury will decrease, and the economic burden of this health problem will decrease.
Odleżyny są problemem zdrowotnym, który negatywnie wpływa na jakość życia pacjenta i powoduje poważne koszty opieki. W przypadku braku odpowiedniego leczenia i opieki może to doprowadzić do śmierci pacjenta. Pielęgniarki odgrywają kluczową rolę w zapobieganiu, opiece i leczeniu odleżyn jako członkowie zespołu opieki zdrowotnej, którzy ściśle i stale monitorują stan zdrowia danej osoby. Obecnie w dziedzinie zdrowia, podobnie jak w wielu innych dziedzinach, coraz częściej wykorzystuje się sztuczną inteligencję. Sztuczna inteligencja jest metodą, która ma na celu rozwiązywanie złożonych problemów poprzez matematyczne symulowanie sposobu działania mózgu z wykorzystaniem komputerów. Niniejszy artykuł jest przeglądem zaprojektowanym w celu podzielenia się informacjami na temat modelu deep learning opracowanego do wykrywania i klasyfikacji odleżyn. Deep learning może działać na wielu typach danych. Konwolucyjne sieci neuronowe (ang. convolutional neural networks, CNN) preferują obrazy, ponieważ mogą obsługiwać macierze 2D. Obrazy, uporządkowane zgodnie z systemem klasyfikacji odleżyn według National Pressure Injury Advisory Panel (NPIAP), zostały przekształcone w "Deep Learning Model" z wykorzystaniem CNN. Opracowywany model CNN ma 97% skuteczności w wykrywaniu i klasyfikowaniu odleżyn, a im więcej obrazów zostanie zebranych i wykorzystanych w CNN, tym większe będzie prawdopodobieństwo trafnej prognozy. Ten model deep learning daje możliwość automatycznego wykrywania i klasyfikacji odleżyn, które są wskaźnikiem jakości zdrowia, na wczesnym etapie oraz dokładnej i szybkiej interwencji. W tym kontekście oczekuje się, że jakość opieki pielęgniarskiej wzrośnie, zmniejszy się częstość występowania odleżyn oraz obciążenie ekonomiczne związane z tym problemem zdrowotnym.
Źródło:: Health Problems of Civilization; 2021, 15, 4; 328-335
2353-6942
2354-0265
Pojawia się w:: Health Problems of Civilization
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: The effect of luteolin on spermatological parameters, apoptosis, oxidative stress rate in freezing rabbit semen
Autorzy:: Akarsu, S.A.
Acısu, T.C.
Güngör, İ.H.
Çakır Cihangiroğlu, A.
Koca, R.H.
Türk, G.
Sönmez, M.
Gür, S.
Fırat, F.
Esmer Duruel, H.E.
Powiązania:: https://bibliotekanauki.pl/articles/16647483.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: rabbit
semen
cryopreservation
luteolin
oxidative stress
apoptosis
Opis:: The aim of the present study was to determine the effects of Luteolin (LUT) on semen quality, oxidative stress, apoptosis, acrosomal integrity, mitochondrial membrane potential and dead sperm ratio in rabbits. Ejaculates from six New Zealand rabbits were collected, evaluated and pooled. The pooling was divided into five groups as control (no additive) LUT 25 μM, LUT 50 μM, LUT 100 μM and LUT 200 μM and LUT added. It was then filled into a falcon tube with Tris-based extender at a final concentration of approximately 35 x 106 spermatozoa. Diluated rabbit semen samples were drawn into frozen and thawed. Frozen semen straws were thawed at 37°C in 30 seconds. According to our findings, no statistical difference was found between all doses of luteolin and the control group in the CASA (computer assisted sperm analysis) analysis performed at 4°C. However, total motility, progressive motility and rapid sperm percentage were found to be higher in the frozen and thawed rabbit semen at a dose of LUT 50 μM compared to the other groups (p<0.05). While amplitude of lateral head displacement (ALH) and beat cross-frequency (BCF) values were found at the lowest dose of LUT 200 μM, a statistically significant difference was observed between the other groups. When the flow cytometry results were examined, no statistical difference was found between the rate of dead sperm, acrosomal integrity, mitochondrial membrane potential and apoptosis rate. Morever, the H2O2 percentage was found to be lower in all experimental groups compared to the control group (p<0.001). In conclusion, the addition of LUT in long-term storage of rabbit semen provided a protective effect for spermatozoa with its antioxidative properties against damage caused by cryopreservation.
Źródło:: Polish Journal of Veterinary Sciences; 2023, 26, 1; 91-98
1505-1773
Pojawia się w:: Polish Journal of Veterinary Sciences
Dostawca treści:: Biblioteka Nauki

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