Multiple decomposition-aided long short-term memory network for enhanced short-term wind power forecasting.

With the increasing penetration of grid-scale wind energy systems, accurate wind power forecasting is critical to optimizing their integration into the power system, ensuring operational reliability, and enabling efficient system asset utilization. Addressing this challenge, this study proposes a novel forecasting model that combines the long-short-term memory (LSTM) neural network with two signal decomposition techniques. The EMD technique effectively extracts stable, stationary, and regular patterns from the original wind power signal, while the VMD technique tackles the most challenging high-frequency component. A deep learning-based forecasting model, i.e. the LSTM neural network, is used to take advantage of its ability to learn from longer sequences of data and its robustness to noise and outliers. The developed model is evaluated against LSTM models employing various decomposition methods using real wind power data from three distinct offshore wind farms. It is shown that the two-stage decomposition significantly enhances forecasting accuracy, with the proposed model achieving R2 values up to 9.5% higher than those obtained using standard LSTM models

The Reasons of Renal Transplant Recipients’ Admission to the Emergency Department; a Case Series Study

Introduction:  Renal transplantation are admitted to emergency department (ED) more than normal population. The present brief report aimed to determine the reasons of renal transplant patients’ ED visits.Methods: This retrospective case series study analyzed the reasons of renal transplant recipients’ admission to one ED between 2011 and 2014. The patient data were collected via a checklist and presented using descriptive statistics tools.Results: 41 patients with the mean age of 40.63 ± 10.95 years were studied (60.9% male). The most common ED presenting complaints were fever (36.6%) and abdominal pain (26.8%). Infections were the most common final diagnosis (68.3%). Among non-infectious causes, the most common was acute renal failure (9.7 %). 73.2% of the patients were hospitalized and no cases of graft loss and mortality were seen.Conclusion: The most common reason for ED admission was fever, and infections were the most common diagnosis. Acute gastroenteritis being the most frequent infection and among non-infectious problems, acute renal failure was the most frequent one.

The Top 100 Cited Articles on Ocular Trauma: A Bibliometric Analysis

Objective: Eye injuries are one of the leading causes of disabling ocular morbidity. The objective of this bibliometric study was to evaluate the top 100 cited articles on ocular trauma published between 1975 and 2018 via multidimensional citation analysis. Methods: We analyzed the top 100 cited articles among 3,768 ocular trauma articles published between 1975 and 2018; these articles were obtained from the databases in Web of Science and PubMed based on their citation rates per article, publication years, countries of origin, institutions or organizations, the most common subjects, funding status, article types, and levels of evidence. The data obtained were analyzed with the SPSS® 20.0 software package program. Results: In the top 100 cited articles on ocular trauma, the total number of authors was 420 and the average authorship was 4.20±2.23 (range: 1–14). In our study, 70 of the top 100 cited articles were published in journals with an impact factor (IF) of ≥2.00 (range: 2.016–8.806), and Q index or quartile score of these journals was mostly Q1. Although the most preferred journal was Ophthalmology according to the total number of citations and articles (n=2,183 and n=23, respectively), Eye was the most preferred journal according to the mean number of citations per article. Besides, the three most common topics among the top 100 cited articles were mechanical eyeball injury (40 articles), epidemiology of ocular trauma (19 articles), and traumatic eye infection (17 articles). The average level of evidence was found to be 3.14±0.66 (range: 1–4), and the mean number of citations per article was the highest level at 2. Moreover, we also found that the most commonly preferred article type by authors was clinical research (92 articles), and most of them were in the B level of evidence group (70 articles). Conclusion: Analysis of the top 100 most cited articles on ocular trauma as an update study can provide us scientific contributions and vital current data in clinical implementations

Finsler Geometry for Two-Parameter Weibull Distribution Function

To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science. Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area. In this paper, two-dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling. The metric definition for two-parameter Weibull probability density function which has shape (k) and scale (c) parameters in two-dimensional Finsler space is realized using a different approach by Finsler geometry. In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications. For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two-parameter Weibull probability density function, especially used for determination of wind energy potential of a region

Short-Term Solar Power Forecasting Based on CEEMDAN and Kernel Extreme Learning Machine

The use of renewable energy sources contributes to environmental awareness and sustainable development policy. The inexhaustible and nonpolluting nature of solar energy has attracted worldwide attention. Accurate forecasting of solar power is vital for the reliability and stability of power systems. However, the effect of the intermittency nature of solar radiation makes the development of accurate prediction models challenging. This paper presents a hybrid model based on Kernel Extreme Learning Machine (Kernel-ELM) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for short-term solar power forecasting. The decomposition technique increases the number of stable, stationary, and regular patterns of the original signals. Each decomposed signal is fed into Kernel-ELM. To validate the performance of the hybrid model, solar power data from the BSEU Renewable Energy Laboratory, measured at 5-minute intervals, are used. To validate the proposed model, its performance is compared to some state-of-the-art forecasting models with seasonal data. The results highlight the good performance of the proposed hybrid model compared to other classical algorithms according to the metrics

The Sister-Chromatid Exchange and Acetylcholine Esterase Enzyme Levels among Patients with Insecticide Intoxication in the Cukurova Region, Turkey.

This study included 45 patients with intentional insecticide intoxication and 21 with accidental intoxication who were treated at the First-Aid and Emergency Department of Balcali Hospital at the Faculty of Medicine in the Cukurova University, Adana, Turkey, while the control group consisted of 25 people selected from university personnel known to be healthy. Patients with a history of X-ray exposure in the last 6 months or of any virus disease as well as continuous drug users and smokers were excluded, leaving a total of 49 patients. Acetylcholine esterase (Pseudocholinesterase) enzyme (AchE), sister-chromatid exchanges (SCE), the mitotic index (MI), and the replication index (RI) were evaluated. Blood samples were cultured for SCE evaluation and sera separated for AchE levels. Insecticide exposure was generally intentional for suicide in adolescents and at older ages, but accidental for children. AchE levels were found to be significantly lower in organophosphorus (OP) and carbamated (CB) insecticide poisoning groups in comparison with the control group (p&#60;0.001), while the pyrethroid (PY) group was not statistically different for the AchE effect (p&#62;0.05). SCE was found to be significantly higher in OP and CB groups (p&#60;0.001), while the PY and control groups were statistically similar for SCE levels (p&#62;0.05). This study showed an increase in SCE in response to orally ingested insecticides. These findings indicate that insecticide exposure results in cell abnormalities, with resulting impediments to the division and replication of cells, as suggested by MI decreases and RI increases, while the speed of the division cycles of stimulated cells increases.</p

Akut miyokard infarktüsünde tanı koydurucu enzimlerin belirlenmesi ve genetik varvasyonların analizi

TEZ3322Tez (Uzmanlık) -- Çukurova Üniversitesi, Adana, 1999.Kaynakça (s. 93-105) var.xiii, 105 s. ; 30 cm.

Production And Characterization Of Carbon Fiber Reinforced Polymeric Matrix Composites

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2009Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2009Karbon fiber takviyeli polimerik matrisli kompozitler düşük yoğunluk, yüksek mukavemet ve sıcaklık altında mükemmel ablatif davranışları gibi özelliklerinden dolayı yüksek sıcaklık uygulamalarında tercih edilen mühendislik malzemeleridir. Bu çalışmada, karbon fiber esaslı polimerik matrisli kompozitlerin yüksek sıcaklık altında ısıl davranışları ve mekanik özellikleri incelenmiştir. Yapılan deneysel çalışmalarda takviye elemanı olarak karbon fiber, polimerik matris olarak da fenolik reçine kullanılmıştır. Kompozit parçanın üretilmesi, spreyleme prosesi ile gerçekleştirilmiştir. Kısa fiberli kompozit malzemelerin elastisite modülü ve termal iletkenlik özelliklerin modellenmesi için Cox ve Halphin-Tsai tasarımlarından yararlanılmıştır. Yük ve vakum altında üretilen numunelere dinamik ve statik ısı akısı testleri, termogravimetrik analiz, kayma dayanımı ve ısıl iletkenlik testleri uygulanmıştır. Elde edilen veriler incelendiğinde vakum altında üretilen numuneler en iyi sonucu vermektedir. Bu sonuçlar ağırlık kaybı % 14, kupon arkası sıcaklık 75 °C, ısıl iletkenliği 0,7 W/ m °C, ilk bozunma sıcaklığı 190 °C, 900 °C’deki ağırlık kaybı % 11 ve kayma dayanımı 8 MPa olarak belirlenmiştir.Carbon fiber reinforced polymeric matrix composites are engineering materials which are preferred for high temperature applications because of their low density, high strength and excellent ablative properties. In this study, the temperature on the back of coupon, weight loss, first decomposition temperature and shear strength of carbon fiber reinforced polymeric matrix composites were investigated. In experimental studies, carbon fiber and phenolic resin were used as reinforcement and matrix. Laminated composite was produced by spray-up process. Cox and Halpin-Tsai modeling studies were used for Young’s modulus and thermal conductivity prediction of short-fiber reinforced composites. Composites produced in load and vacuum were tested dynamic and static heat flux, thermogravimetric analysis, shear strength and thermal conductivity. Based on the experimental data, composites produced in vacuum showed the best results, including weight loss of 14 %, the temperature on the back of coupon of 75 °C, thermal conductivity of 0.7 W/ m °C, first decomposition temperature of 190 °C, weight loss at 900 °C of 11 %, shear strength of 8 MPaYüksek LisansM.Sc

The most cited articles on cancer immunotherapy: An update study

Purpose: The purpose of this bibliometric study was to point out the emergence and development of immunotherapy in cancer treatment and shifting tendencies on this field in the last years. We aimed to create an ease of access for the researchers of this dynamic field