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The patient underwent intensive care after an acute abdominal surgery due to intestinal perforation. The patient was examined for postoperative muscle weakness, and the differential diagnosis was studied. Guillain-Barré syndrome is an acute inflammatory demyelinating polyneuropathy. Infection, surgery, and transplantation have been cited in its etiology. History, clinical examination and follow-up, laboratory tests, and electrophysiological studies are important in its diagnosis, as well as differential diagnosis. Intravenous immunoglobulin and plasmapheresis are the mainstays of care, and supportive care is important for long-term treatment. In this case report, an intensive care unit approach was discussed, in which the surgical paradigm and gastrointestinal stromal tumor were thought of as a rare paraneoplastic complication.

This paper is concerned with the following parabolic-parabolic-elliptic chemotaxis system with singular sensitivity and Lotka-Volterra competitive kinetics,$$ \begin{cases} u_t=\Delta u-\chi_1\nabla\cdot (\frac{u}{w}\nabla w)+u(a_1-b_1u-c_1v),\quad &x\in\Omega\cr v_t=\Delta v-\chi_2\nabla\cdot (\frac{v}{w}\nabla w)+v(a_2-b_2v-c_2u),\quad &x\in\Omega\cr 0=\Delta w-\mu w +\nu u+ \lambda v,\quad &x\in\Omega\cr \frac{\partial u}{\partial n}=\frac{\partial v}{\partial n}=\frac{\partial w}{\partial n}=0,\quad &x\in\partial\Omega, \end{cases} $$ where $\Omega \subset \mathbb{R}^N$ is a bounded smooth domain, and $\chi_i,a_i,b_i,c_i$ ($i=1,2$) and $\mu,\nu,\lambda$ are positive constants. Among others, we prove that for any given nonnegative initial data $u_0,v_0\in C^0(\bar\Omega)$ with $u_0+v_0\not \equiv 0$, (0.1) has a unique globally defined classical solution $(u(t,x;u_0,v_0),v(t,x;u_0,v_0),w(t,x;u_0,v_0))$ with $u(0,x;u_0,v_0)=u_0(x)$ and $v(0,x;u_0,v_0)=v_0(x)$ in any space dimensional setting. Moreover, we prove that there is $\chi^*(\mu,\chi_1,\chi_2)>0$ satisfying \begin{align*} &\chi^*(\mu,\chi_1,\chi_2)= \begin{cases} \frac{\mu \chi^2}{4} &{\rm if}\,\, 0\chi^*(\mu,\chi_1,\chi_2) $$ implies $$\limsup_{t\rightarrow\infty} \|u(t,\cdot;u_0,v_0)+v(t,\cdot;u_0,v_0)\|_\infty\leq M^*\,{\rm and}\,\liminf_{t\rightarrow\infty}\inf_{x\in\Omega}(u(t,x,u_0,v_0)+v(t,x;u_0,v_0))\ge m^*$$ for some positive constants $M^*,m^*$ independent of $u_0,v_0$, the latter is referred to as combined pointwise persistence.

This research, which was conducted to determine the adaptation ability of Italian ryegrass (Lolium multiflorum L.) under the conditions of Sanliurfa, was carried out in Harran University Faculty of Agriculture Osmanbey Campus, Agricultural Research and Application Field in 2017-2018 winter crop growing period with 3 replications. Trial in Cantabile obtained from private companies Helen, Caramba, Rambo, Alberto, Tornado, Trinova, Baqueano Seven different tetraploid Italian grass varieties from private companies were used in the experiment. Plant height, relationship between characters, age yield, hay yield, leaf rate, dry matter yield (kg da-1), crude protein content, crude protein yield, seed yield and plant height observations in seed yield were investigated. According to the results; plant height 48.67- 65.66 (cm), fresh herb yield 1798.06–2764.75 kg da-1, dry herb yield 484.00-746.00 kg da-1, dry matter yield 435.00-671.00 kg da-1, leaf ratio 29.50-35.17%, crude protein ratio 10.03-12.13% and seed yield 48.40-84.18 (kg da-1) it was found that between and Paying attention to dry matter yield and leaf ratio characters will be an option for an efficient and quality product in relationships between characters.

In recent years, it has been drawn a lot of attention to the question of whether logistic kinetics is sufficient to enforce the global existence of classical solutions or to prevent finite-time blow-up in various chemotaxis models. However, for several important chemotaxis models, only in the space two dimensional setting, it has been shown that logistic kinetics is sufficient to enforce the global existence of classical solutions (see [15] and [34]). The current paper is to give a confirmed answer to the above question for the following parabolic-elliptic chemotaxis system with singular sensitivity and logistic source in any space dimensional setting, \begin{equation} \begin{cases} u_t=\Delta u-\chi\nabla\cdot (\frac{u}{v} \nabla v)+u(a(x,t)-b(x,t) u),\quad x\in \Omega\cr 0=\Delta v-\mu v+\nu u,\quad x\in \Omega \quad \cr \frac{\partial u}{\partial n}=\frac{\partial v}{\partial n}=0,\quad x\in\partial\Omega, \end{cases} \end{equation} where $\Omega \subset \mathbb{R}^n$ is a bounded domain with smooth boundary $\partial\Omega$, $\chi$ is the singular chemotaxis sensitivity coefficient, $a(x,t)$ and $b(x,t)$ are positive smooth functions, and $\mu,\nu$ are positive constants. We prove that, for any given nonnegative initial data $0\not\equiv u_0\in C^0(\bar \Omega)$, (0.1) has a unique globally defined classical solution $(u(t,x;u_0),v(t,x;u_0))$ with $u(0,x;u_0)=u_0(x)$, which shows that, in any space dimensional setting, logistic kinetics is sufficient to enforce the global existence of classical solutions and hence prevents the occurrence of finite-time blow-up even for arbitrarily large $\chi$. In addition, the solutions are shown to be uniformly bounded under the conditions $a_{\inf}>\frac{\mu \chi^2}{4}$ when $\chi \leq 2$ and $a_{\inf}>\mu (\chi-1)$ when $\chi>2$.

In this research, the aluminum (Al2024) matrix composites are reinforced with nano magnesium oxide (MgO) and multi-walled carbon nanotubes (MWCNTs). The aim of Al2024 alloy reinforced with MgO and MWCNTs is to reveal the effects of the reinforcement particle ratio on the microstructure and mechanical properties of the hybrid composites, to find the optimum hybrid ratio, and to form a stronger hybrid composite. The composites with the different hybrid ratios are produced via stir casting method. The theoretical and measured densities and porosity content of the composites are studied. The microstructure and fracture surface of the composites are examined by optical microscopy, scanning electron microscopy (SEM), and electron dispersive spectrum (EDS). The hardness, compression, and tensile properties of the composites are studied in this work. Results indicated that the hardness of the aluminum (Al) matrix composites (AMCs) is significantly improved after the reinforcement with MgO and carbon nanotube (CNT), and also heat treatment of T6. The stress–strain curve of the composites is tested by a material testing machine. The maximum tensile and compression strengths are obtained at Al2024-0.2 wt.% (MgO 50% + CNT 50%) the composite as 226 MPa and 684 MPa, respectively .The hardness, compression, and tensile strengths of the hybrid composites are higher than 1.51, 1.39, and 1.31 than that of the base metal. After heat treatment of T6, the maximum harness, compression, and tensile strengths are obtained by 102 HB, 730 MPa, and 277 MPa, respectively, which are 1.82, 1.49, and 1.61 times higher hardness than that that of the base Al2024 alloy. The main strengthening mechanism of nano-MgO particles and MWCNTs-reinforced Al2024/MgO/CNTs composites is observed by the precipitation strengthening mechanism.

Metal matrix composites are widely used in various fields such as aerospace, defense industry, automobiles and other important structural applications. Aluminum and its alloys have been increasingly used in the industry thanks to their lightness, strength and easy formability. Al2O3, SiC, TiC, MgO, CNT and B4C are widely used as reinforcing elements in aluminum matrix composites. In this study, mathematical and finite element modeling was used to examine the mechanical properties of Al-based metal matrix composites. Based on the pressure, sintering temperature and sintering time, the relative densities were successfully analyzed using the adaptive neuro-fuzzy extraction system (ANFIS) method and the artificial neural networks (ANN) method. The porosity content of aluminum-magnesium matrix composites produced by powder metallurgy method and reinforced with SiC were investigated using the ANFIS method. In the ANFIS approach, four input parameters, weight% SiC ratio, used pressure (MPa), sintering temperature (C), sintering time (min) and one output parameter porosity (%) ratio were used. Correlation coefficients and statistical error rates of the analyzed dataset were found to be good. The relative density values of Al-Mg-Al2O3 composites produced by powder metallurgy method were examined by ANN method. It can be said that the estimation rate of the system is 81% and that it is within acceptable limits. Besides, the relative density of composites with Al2O3 and SiC was examined using Taguchi method and the results were compared., Metal matris kompozitler havacılık, savunma sanayii, otomobiller ve diğer önemli yapısal uygulamalar gibi çeşitli alanlarda yaygın olarak kullanılmaktadır. Alüminyum ve alaşımları hafifliği yanı sıra sağlamlığı ve kolay şekillendirilebilme özellikleri sayesinde endüstride giderek artan kullanım alanına sahip olmuştur. Alüminyum matrisli kompozitlerde takviye elamanı olarak Al2O3, SiC, TiC, MgO, CNT ve B4C yaygın olarak kullanılır. Bu alışmada, Al-bazlı metal matris kompozitlerin mekanik özelliklerini incelemek için matematiksel ve sonlu eleman modellemesi kullanılmıştır. Basınç, sinterleme sıcaklığı ve sinterleme süresine bağlı kalarak porozite içeriği uyarlanabilir nöro-bulanık çıkarım sistemi (ANFIS) yöntemi kullanılarak relatif yoğunluklar ise yapay sinir ağları (ANN) yöntemi ile başarılı bir şekilde analiz edilmiştir. Toz metalürjisi yöntemiyle üretilen ve SiC ile güçlendirilmiş alüminyum-magnezyum matrisli kompozitlerin porozite içeriği ANFIS yöntemi kullanılarak incelenmiştir. ANFIS yaklaşımında, dört giriş parametresi, ağırlıkça %SiC oranını, kullanılan basıncı (MPa), sinterleme sıcaklığını (⁰C), sinterleme zamanını (dk) ve bir çıkış parametresi porozite (%) oranını kullanılmıştır. Analizlerin korelasyon katsayılarının ve istatiksel hata oranlarının iyi olduğu görülmüştür. Toz metalürjisi yöntemiyle üretilen Al-Mg-Al2O3 kompozitlerin relatif yoğunluk değerleri ANN yöntemiyle incelenmiştir. Sistemin tahmin oranın %81olduğu ve kabul edilebilir sınırlar içerisinde olduğu söylenebilir. Ayrıca, Taguchi yaklaşımı ile her iki güçlendirici içeren kompozitlerin relatif yoğunluklar analiz edilmiştir ve sonuçlar karşılaştırılmıştır.

Introduction: Influenza A (H1N1) virus have been a serious problem in 2009, which was considered as a pandemic and caused the death of more than 12000 people. Pneumonia is the most common complication of influenza infection and can be seen as viral pneumonia and/or bacterial coinfection. However, since November 2019, the world has been exposed to a new pneumonia agent named SARS - CoV - 2 from the Coronavirus family. In this case series, we aimed to re-evaluate the cases we followed up in the intensive care unit due to severe pandemic Influenza A infection between November 2019 and March 2020 from the Covid-19 perspective. Cases: There were five cases diagnosed with pandemic influenza A (H1N1) pneumonia in intensive care between November 2019 and March 2020, and the average age was 50. Given the risk factors two patients had immunosuppression and two patients had diabetes. Fever, respiratory distress and cough were the most prominent symptoms, and involvement in both lungs was detected in all patients on radiological imaging. Unfortunately, all patients had died despite antiviral therapy, antibiotic treatment against secondary bacterial infection, hemodynamic and respiratory support treatments. Discussion: Considering the literature, covid-19 and influenza co-infections have been detected in 34 cases since November 2019. In general terms, covid-19 and influenza tables are similar, with slight differences. In this case we look back to our findings, similar cases are considered as covid-19 under current conditions.

The study aims to reveal teachers’ perceptions of “Covid-19” and “School in the Covid-19 Process” through metaphors. The differences between the covid-19 perceptions of those who had Covid-19 disease in the participants’ families and those who did not were examined. Phenomenology design, one of the qualitative research methods, was used in the study. Participants consist of a total of 100 teachers, 80 in Hatay and 20 in Gaziantep. The content analysis method was used. It was seen that teachers had 45 different metaphors in the perception of ‘Covid-19’ and were collected in eight categories. The most produced metaphors’ codes related with covid-19 were “Flu”, “Cancer”, “Illness”, “War”, “Flu-pneumonia”. Categories created according to metaphors were “Similar to other diseases”, “Infectiousness”, “Damaging”, “Fatal”, “Uncertainty”, “Social order”, “Immunity”, “Isolating”. Participants created 56 different metaphors in the perception of “School in the Covid-19 Process,” and these metaphors could be gathered in seven categories. The most produced metaphors were “Dangerous zone”, “Abandoned building”, “Pandemic point / Virus slot”, “House”.

The multi-walled carbon nanotubes (MWCNTs) have drawn great attention due to their exceptional mechanical, physical, thermal and electrical properties. The MWCNTs as the reinforcements significantly improved the properties of materials. However, the major challenges in composites containing CNTs are the poor wettability and poor interfacial bonding between matrix and CNTs. In this study, the used MWCNTs have a diameter of 8–10 nm and 1.5 μm in length. MWCNTs are purified in HNO3: H2SO4, sensitized in Sn solution and activated in Pd solution at 90 °C, and coated with the Nickel and Cobalt elements using an electroless coating method. The holding time in the bath is 15, 30 and 60 min, and the bath concentration is also changed. The coatings are characterized by Scanning Electron Microscopy (SEM) equipped with electron dispersive spectrum (EDS), elemental mapping, x-ray diffraction (XRD), Raman spectroscopy, Transmission Electron Microscopy (TEM) and Fourier Transform Infrared (FTIR) spectrometer. The results showed that the Ni and Co coating layers are successfully formed on the surface of MWCNTs. The deposition rate is affected by the holding time and the bath concentration. The optimal results are obtained at the holding time of 60 min in the C concentration sample.

The growing attention regarding aluminum alloy matrix composites within the aerospace, automotive, defense, and transportation industries make the development of new engineering materials with the improved mechanical properties. Currently, materials are selected because of their abilities to satisfy engineering demands high for strength-to-weight ratio, tensile strength, corrosion resistance, and workability. These properties make aluminum alloys and aluminum matrix composites (AMCs) an excellent option for various industrial applications. Soft computing methods such as the artificial neural network (ANN), adaptive-neuro fuzzy inference systems (ANFIS), and Taguchi with ANOVA are the most important approaches to solve the details of the mechanism and structure of materials. The optimal selection of variables has important effects on the final properties of the alloys and composites. The chapter presents original research papers from our works and taken from literature studies dealing with the theory of ANN, ANFIS, and Taguchi, and their applications in engineering design and manufacturing of aluminum alloys and AMCs. Also, the chapter identifies the strengths and limitations of the techniques. The ANFIS and ANN approaches stand out with wide properties, optimization, and prediction, and to solving the complex problems while the Taguchi experimental design technique provides the optimum results with fewer experiments.

The aim of the study is to research and compare the influences of the confirmed cases, test number and time range on the death and recovery rates in the United State of America, China, and Turkey, and to find out the effect of the epidemic in the near future of Turkey. The modelling and prediction of effects of the day, case and test numbers of COVID-19 infection in the USA, China and Turkey are carried out using the artificial neural network approach (ANN). The system are trained and tested with the different numbers of neurons, hidden layers and activation functions to increase the reliability and accuracy of model. The proposed models have a high R2 value for China and Turkey. We can say according to the results that the measures taken by the USA are inadequate. The formulation is applied to predict the effect of Covid-19 infection in Turkey. The test number that is an important factor in detecting the cases should be increased. The results show a good fit between the observed data and those obtained by the ANN model. If the precautions are strictly followed, the case number will be decreased significantly after 160 days for Turkey according to result of the proposed model but due to the uncontrolled variables, this time may result in between 200 and 250 days.

The study aims to determine the effect of a 8 week sprint and pliometric training out regularly on speed, jump and anaerobic power parameters among hearing impaired male athletes at the age of 18-21. The measurement and tests of the study was carried out in 2018 and the article was written in 2019 in Samsun. 45 male volunteers with hearing impairment participated in this study. 15 of whom are sprint training (experimental) group aged 19.6±1,18; 15 of whom are pliometrik training (experimental) group aged 19.33±1,12 and 15 of whom are control group aged 19.87±1,19. The experiment groups was made to take sprint and pliometric training practices for 8 weeks, the content of which had been determined before hand while the participants attended their trainings in their local teams. Two assessments were carried out in specified parameters for three groups at the beginning and end of the study. In statistical analysis, the significance level was taken as α=0,05. One way analysis of variance was used to determine the differences between the groups. When the differences were found, Tukey test was used. Paired sample t-test for within group analysis. There are not any statistically difference in parameters of age, weight and training age of the participants (p>0.05). There is statistically significant difference in height parameter (p

Toz metalurjisi yöntemi, alüminyum alaşımı esaslı metal matris kompozitlerinin üretimi için diğer geleneksel yöntemlere göre umut vadeden alternatif bir yöntemdir. Bu çalışmada, toz metalurjisi yöntemi ile hazırlanan SiC içeren alüminyum alaşım esaslı metal matris kompozitlerin işlem parametrelerinin Taguchi ve Varyans Analizi (ANOVA) yaklaşımı ile görünür yoğunluk üzerine etkisi araştırılmıştır. Taguchi’nin L16 dikey dizisi, minimum görünür yoğunluk elde etmek için işlem parametrelerini optimize etmek için kullanılmıştır. Dikkate alınan parametreler; ağırlıkça SiC oranı (%15 ve 30), sıkıştırma basıncı (260 ve 520 MPa), sinterleme sıcaklığı (300 ve 500°C) ve sinterleme zamanıdır (30 ve 90 dk.) ve bununla birlikte çıkış parametresi de görünür yoğunluktur. ANOVA, her bir değişken parametrenin çıkış parametresi üzerindeki etkisini belirlemek için deneysel veriler kullanılarak gerçekleştirilmiştir. Sinyal-gürültü oranlarının ve ANOVA analizine dayanarak, toz metalürjisi işlem parametrelerinin optimum değerleri (yani ağırlıkça SiC oranı, sıkıştırma basıncı, sinterleme sıcaklığı ve sinterleme zamanı) belirlenmiştir. Mevcut çalışmanın sonuçları, ağırlıkça SiC oranının görünür yoğunluk üzerinde en fazla etkiye sahip faktör olduğunu göstermektedir. İşlem parametrelerinin görünür yoğunluk üzerindeki etkisini incelemek için etkileşim grafikleri oluşturulmuştur. Buna ek olarak; görünür yoğunluğu tahmin etmek için deneysel bir model, regresyon analizi kullanılarak geliştirilmiştir., Powder metallurgy processing is a promising alternative to other conventional methods for the production of aluminum alloy based metal matrix composites. In this study, the influence of process parameters on the apparent density values of the aluminum alloy based metal matrix composites containing SiC prepared via powder metallurgy method was investigated using the Taguchi and Analysis of Variance (ANOVA) approach. A Taguchi’s L16 orthogonal array was used to optimize process parameters to obtain minimum apparent density. The parameters considered were wt.% of SiC (15 and 30%), compaction pressure (260 and 520 MPa), sintering temperature (300 and 500°C) and sintering time (30 and 90 min) with apparent density as the response factor. ANOVA was performed using the experimental data to determine the effect of each parameter on the response parameter. Based on an analysis of the signal-to-noise ratios and ANOVA, the optimal values of powder metallurgy processing parameters (i.e., wt.% of SiC, compaction pressure, sintering temperature and time) were determined. The results indicate that wt.% of SiC is the factor having the most effect on apparent density. Interaction plots were generated to study the interaction effect of process parameters on apparent density. In addition to this, an empirical model for predicting apparent density was developed by using regression analysis.

Objective: To determine the effects of nitrous oxide (N2O) on the speed and quality of the uptake process of sevoflurane during inhalation induction in adult patients. Materials­ and­ Methods: For randomized controlled study, eighty-four American Society of Anesthesiologists I-II patients undergoing gynecological interventions were randomly assigned to receive an 8% sevoflurane mixture with either 67% N2O plus 33% oxygen [Group sevoflurane and nitrous oxide (SA)] or 100% oxygen only [Group sevoflurane (S)]. Both groups were induced by a single-breath induction. End-tidal and inspiratory concentrations of respiratory and anesthetic gasses were continuously assessed during induction as well as time to loss of eyelash reflex, time to cessation of eye movements, and time to initiation of spontaneous breaths. Patients were intubated by the 5th minute of induction and their vital signs, bispectral indexes, reflex responses to intubation and additional drug requirements for intubation were also recorded. Results: End-tidal sevoflurane concentrations and the ratio of alveolar to inspiratory sevoflurane concentrations (FA/Fi) of patients in group SA recorded at the 2nd, the third and the 5th minute of induction showed statistically significant increases when compared with patients in group S. Time to loss of eyelash reflex and time to cessation of eye movements were found to be decreased in group SA by 25 and 13%, respectively. Patients who presented with a reflex response to intubation in group S exceeded patients in group SA by 38.8% and patients who required additional medication for intubation in group S exceeded patients in group SA by 28.6%. Conclusion: The findings of this study support the view that administration of N2O improves the rate and quality of mask induction with sevoflurane. The benefits provided by N2O attributable to the concentrating and second gas effects appear during the first few minutes of induction (2nd, 3rd, and 4th minutes) as well as during intubation when sevoflurane is used for mask induction.

In this work, effects of arcstud welding parameters on ultimate tensile strength of AISI 304 austeniticstainless steels welded arc stud welding method were investigated using neural networkapproach. It was observed that optimum model architecture is 5-6-1 ratio forthis study. A mathematical formulation was derived to estimate the ultimatetensile strength of these joints and experimental results were compared withtest results. Mathematical formula is presented in explicit form. The proposedmodel shows good agreement with experimental results and can be used to predictthe ultimate tensile strength of these joints. R and R2 values oftraining and test sets are higher 0.95 and 0.93, and 0.90 and 0.87,respectively. Percentage error value for test set is not exceeded 13%., Buçalışmada, ark saplama kaynak yöntemiyle birleştirilen 304 östenitik paslanmazçeliklerin çekme dayanımına ark saplama kaynak parametrelerinin etkisi yapaysinir ağları modeli kullanılarak araştırılmıştır. Bu çalışma için optimum modelyapısının 5-6-1 olduğu gözlenmiştir. Birleştirmelerin çekme dayanımınıhesaplamak için bir matematik Formülasyon önerilmiş ve deneysel ve testsonuçları karşılaştırılmıştır. Formülasyon açıkça verilmiş ve önerilen modelile uyum içerisinde olduğu belirlenmiş ayrıca birleştirmelerin çekme dayanımınıtahmin etmede kullanabileceği kanaatine varılmıştır. Eğitim ve test setlerininR ve R2 değerleri 0,95, 0,93 0,90 ve 0,87 olarak bulunmuştur. Test setinin hatadeğeri %13’ün altında olduğu görülmüştür.

Paslanmaz celiklerin kaynaginda en sik gorulen kaynak hatalarindan birisi tane sinirlarina cokelen krom karbur cokelmeleridir. Bu calismada, farkli ozelliklere ve farkli fiziksel boyutlara sahip altlik malzemeler kullanilarak 304 kalite ostenitik paslanmaz celik malzemeler elektrik ark kaynak yontemiyle alin alina birlestirilmistir. Kaynakli numunelerin belirlenen soguma zaman araligi tespit edilmis, makroskobik arastirmalari, optik mikroskop incelemeleri, taramali elektron mikroskobu incelemeleri, krom karbur olusumuyla ilgili krom ve karbon elemetlerine ait elementel incelemeler ve sertlik analizleri yapilmistir. Kaynak metallerinin sertlik degerleri ana metal ve isinin tesiri altindaki bolgenin sertlik degerlerinden yuksek oldugu ve en yuksek sertlik degerinin 5754-H22 altlik kullanilarak yapilan birlestirmede meydana geldigi bu altligin kullanildigi birlestirmede krom karbur olusumunun meydana gelmedigi tespit edilmistir.

In this study mid- and long-term outcomes of the cases with trigger finger we treated using Admix NoKorTM have been presented. Percutaneous release procedures were applied for 24 fingers of 22 (19 female, 3 male patients; mean age, 57; range, 39-72) patients between May 2009 and May 2011. Preoperatively US was performed so as to confirm the presence of trigger finger. Diameters of the tendons of the affected and intact hands measured using US, were compared so as to be able to demonstrate thickening of the tendon of the trigger finger. The patients were monitored for an average period of 25.2 (range, 14-36) months. During surgery, clinically loss of the catching sensation was observed. In two patients percutaneous trigger finger release failed, so we have to proceed with open surgery. During open surgery, we observed longitudinal wounds on the tendon. One patient developed unilateral radial digital nerve damage. Percutaneous release of the trigger finger using Admix NoKorTM 16-G gauge needle can be preferred in the treatment of trigger finger. Trigger finger of the first digit requires more attentive approach and one should be aware of the complications. If required open surgery can be preferred. [Med-Science 2017; 6(3.000): 551-6]

Over past decades, there have been a wonder growth in interest in information systems technology and the application of soft computing (SC) techniques to engineering systems. SC is not a single methodology, but it is a partnership and an innovative approach to constructing computationally intelligent systems. Artificial Intelligence and SC techniques are widely used to solve real world problems. In the current investigation, the optical and scanning electron microscopes (SEM) were used for microstructural studies. The welding process parameters (WPPs) were considered key aspects in the determination of the ultimate tensile strength (UTS) of the joints. The results were obtained experimentally. In order to investigate the effect of the WPPs on the UTS, the artificial neural network (ANN), Taguchi and the adaptive-neuro interference fuzzy system (ANFIS) approaches were developed and compared utilizing experimental results. It was found that the ANFIS provides better results than the ANN and Taguchi but the explicit formulation cannot be obtained analytically for the system. It can be concluded by comparing the three approaches that the ANN has a mathematical formulation with 95.53% accuracy and mean absolute percentage error of 4.47% and can be used to estimate the UTS of the joints for next studies. It was also noted that all WPPs had an important effect on the UTS of the joints.

Effects of friction stir processing (FSP) parameters and reinforcements on the wear behavior of 6061-T6 based hybrid composites were investigated. A mathematical formulation was derived to calculate the wear volume loss of the composites. The experimental results were contrasted with the results of the proposed model. The influences of sliding distance, tool traverse and rotational speeds, as well as graphite (Gr) and titanium carbide (TiC) volume fractions on the wear volume loss of the composites were also investigated using the prepared formulation. The results demonstrated that the wear volume loss of the composites significantly increased with increasing sliding distance, tool traverse speed, and rotational speed; while the wear volume loss decreased with increasing volume fraction of the reinforcements. A minimum wear volume loss for the hybrid composites with complex reinforcements was specified at the inclusion ratio of 50% TiC + 50% Al2O3 because of improved lubricant ability, as well as resistance to brittleness and wear. New possibilities to develop wear-resistant aluminum-based composites for different industrial applications were proposed.

In this study, effects of friction stir processing (FSP) parameters and hybrid ratio on the ultimate tensile strength (UTS) of aluminum (Al) matrix (5083) hybrid composites (AMHCs) were investigated in detail. In order to estimate the ultimate tensile strength of the prepared composites, a mathematical formulation was derived, and test results were compared with those of the model. The effects of factors influencing strength, such as tool rotational and traverse speeds, and volume fractions of, carbon nanotube (CNT), aluminum oxide (Al 2 O 3 ), graphite (Gr), silicon carbide (SiC) and zirconium oxide (ZrO 2 ) were also studied using the proposed formulation. Test results showed that the ultimate tensile strength of these composites significantly increased with increasing CNT, tool rotational and traverse speeds. In addition, the effects of complex reinforcements with different volume fractions on the 5083 AMHCs were examined. A maximum tensile strength for the hybrid composite was found at the inclusion ratio of 10% Gr + 5% ZrO 2 . This study may open up new possibilities to developing highly strength Al alloys for various industrial applications.

In the current study, aluminum-magnesium-titanium alloys were manufactured with sand casting method and the effects of titanium and magnesium on the ductility, porosity, hardness and density of these alloys were investigated. The influences of these elements were also studied using multi-layer perceptron neural network approach. Regression models were advanced to check both the performance and the reliability of the proposed neural network model. It was seen that linear correlation of all output values is highest than 90%. It was also observed that Mg has a greater effect than Al and Ti on the hardness and porosity values, whereas Al has more sensitivity on the ductility of alloys, Bu çalışmada, kum döküm yöntemiyle üretilen alüminyum-magnezyum-titanyum alaşımlarının süneklik, porozite, sertlik ve yoğunluk değerlerine magnezyum ve titanium elementlerinin etkileri çok katmanlı yapay sinir ağları yaklaşımı kullanılarak araştırılmıştır. Önerilen modelin güvenirliği ve performansı ilişkilendirme modeli kullanılarak kontrol edilmiş ve bütün çıkış değerlerinin liner korelasyonunun %90’dan daha büyük olduğu görülmüştür. Sertlik ve porozite oluşumunda magnezyumun, süneklik değerinde ise alüminyumun daha büyük etkiye sahip olduğu tespit edilmiştir

In order to investigate the structure of welds, austenitic stainless steel (SS) studs with a diameter of 6 mm were welded to austenitic SS plates with a thickness of 5 mm using an arc stud welding (ASW) method. The effects of the welding current, welding time, and tip volume of the stud on the microstructure and ultimate tensile strength (UTS) of the welded samples were investigated in detail. The formation of δ-ferrites was detected in the weld zone because of the higher heat generated during the welding process. Higher welding current and time adversely affected the stud and significantly reduced the UTS of the samples. The UTS of the joints was also estimated using artificial neural network (ANN) and Taguchi approaches. The mathematical formulations for these two approaches were given in explicit form. Experimental results showed that the neural network results are more consistent with experimental results than those of the Taguchi method. Overall, it can be concluded that in order to achieve good welding joints and high strength values, ASW parameters should be investigated properly to determine the optimum conditions for each metal.

Bu calismanin amaciAfyonkarahisar Orman Fidanlik Mudurlugunde tohumdan uretilen ciplak koklu 1+0 yasli yaprakli ve 2+0 yasli ibreli agac fidanlarinin uretim maliyet analizlerinin yapilmasidir. Calismalarda; 2014 yili Afyonkarahisar Fidanlik Mudurlugu fidan uretim programi ve 2014 yili Afyonkarahisar Fidanlik Mudurlugu giderleri kullanilarak bugunku net degerleri bulunmustur. Ayrica Orman Genel Mudurlugu’nun 74231 sayili ve 12.01.2015 tarihli oluru ile yayinlanan orman fidanliklarinda yetistirilen fidanlarin 2015 yili satis fiyatlarindan yararlanilarak Afyonkarahisar Orman Fidanlik Mudurlugunun fidan uretim maliyetleri hesaplanarak bu alanda mali kaybi cikarilmistir.Afyonkarahisar Orman Fidanlik Mudurlugunde uretilen ciplak koklu 2,250.000 fidanda toplam 29.900 lira kayip oldugu belirlenmistir.

In this study, the feed-forward (FF) neural networks (NNs) with back-propagation (BP) learning algorithm is used to estimate the ultimate tensile strength of unrefined Al-Zn-Mg-Cu alloys and refined the alloys by Al-5Ti-1B and Al-5Zr master alloys. The obtained mathematical formula is presented in great detail. The designed NN model shows good agreement with test results and can be used to predict the ultimate tensile strength of the alloys. Additionally, the effects of scandium (Sc) and carbon (C) rates are investigated by using the proposed equation. It was observed that the tensile properties of Al-Zn-Mg-Cu alloys improved with the addition of 0.5 Sc and 0.01 C wt.%.

In this paper, the effect of different alloying elements on the ultimate tensile strength of Al-Mg2Si composites is theoretically studied. The feed forward back propagation neural network with sigmoid function is used. The extensive experimental results taken from literature are modeled and mathematical formula is presented in explicit form. In addition, it is observed that magnesium and copper have a stronger effect on the ultimate tensile strength of Al-Mg2Si composites comparison to other alloying elements. The proposed model shows good agreement with test results and can be used to find the ultimate tensile strength of Al-Mg2Si composites.

In the current study, the effect of applied load, sliding speed, and type and weight percentages of reinforcements on the wear properties of ultrahigh molecular weight polyethylene (UHMWPE) was theoretically studied. The extensive experimental results were taken from literature and modeled with artificial neural network (ANN). The feed forward (FF) back-propagation (BP) neural network (NN) was used to predict the dry sliding wear behavior of UHMWPE composites. Eleven input vectors were used in the construction of the proposed NN. The carbon nanotube (CNT), carbon fiber (CF), graphene oxide (GO), and wollastonite additives are the main input parameters and the volume loss is the output parameter for the developed NN. It was observed that the sliding speed and applied load have a stronger effect on the volume loss of UHMWPE composites in comparison to other input parameters. The proper condition for achieving the desired wear behaviors of UHMWPE by tailoring the weight percentage and reinforcement particle size and composition was presented. The proposed NN model and the derived explicit form of mathematical formulation show good agreement with test results and can be used to predict the volume loss of UHMWPE composites.