This study investigated the effect of cysteamine added to an extender at different doses (5 and 10 mM) on the freezing of Saanen buck semen containing samples with seminal plasma or those in which the seminal plasma was removed. After the examinations, the ejaculates were pooled. The semen was divided into two equal volumes. The seminal plasma of one group was not removed (Group A), whereas the seminal plasma of the other volume was removed via centrifugation (Group B). Each group was again divided into three equal volumes. Therefore, a total of six groups were created. Subsequent to the equilibration process, diluted semen samples were packaged in 0.25 mL straws, frozen at -110 degrees C, and stored at -196 degrees C. Frozen semen samples were thawed in a water bath for 30 s at 37 degrees C. This procedure was repeated seven times (n=7). In the equilibration stage, 10 mM cysteamine was found to damage the spermatozoa motility regardless of the presence of seminal plasma (p<0.001). After thawing, no statistically significant difference was observed in all the groups. In this study, it was concluded that 10 mM cysteamine damages spermatozoa motility before freezing and the presence of seminal plasma and cysteamine concentrations after thawing had no effect on spermatological properties.

Animal production via SCNT provides a unique tool for protection of valuable individuals, conservation of vulnerable and endangered species and production of transgenic animals. A total of 167 MI and 219 MII stage oocytes were used as the material of the study. The oocytes were enucleated at 44 h after in vitro maturation by aspiration of the polar body and the MI or MII plates. Cycling granulosa cells were used for nuclear transfer. Cell fusion was induced with DC pulses of 2.0 kV/cm 60 mu s, 0.1s apart (2x) delivered by a BTX Electrocell Manipulator 200 (BTX, San Diego, CA, USA). After fusion, the embryos were activated by 1.0 kV/cm 20 mu s DC pulses 0.1s apart (2x) followed by 2 mM 6-DMAP (6-dimethylaminopurine) incubation in culture medium for 4 h in a humidified atmosphere of 5% CO2, 5% O-2, and 90% N-2 at 38 degrees C. The somatic cell transferred embryos were cultured for 8 days in mSOF medium supplemented with 0.4% BSA in a humidified 5% CO2, 5% O-2, and 90% N2 atmosphere at 38 degrees C. After in vitro culture period, all embryos transferred to HSOF containing Hoechst 33342 (5 mu g/mL) and the cell numbers were counted under ultraviolet light using a fluorescent microscope. The fusion (66.66 vs 21.55%) and cleavage rates (15.75 vs 11.11%) were significantly higher in MII stage oocytes than MI stage oocytes (P<0.02). While SCNT embryos were developed to morula stage in MII group (14; 9.58%), all the cleaved embryos were arrested at the 2-4 cell stage in MI group. None of the embryos was developed to blastocyst stage in both groups.

Sheep is a very important source of wool, meat and milk all over the world. Oxidative stress during in vitro culture leads to defects in development of gametes and embryos. Several antioxidants such as cysteamine, L-ascorbic acid, beta mercaptoethanol, cysteine, glutathione, proteins, vitamins are used to supplement culture media to counter the oxidative stress. This study was aimed to detect the effect of cysteamine supplementation to the maturation medium and oviductal cell supplementation to culture medium on the subsequent development rates of sheep embryos with the control group. Oocytes were obtained from slaughtered sheep ovaries. Selected oocytes were incubated with or without 100 mu M cysteamine in TCM-199 medium under 38.5-38.8 degrees C 5% CO2 for 23 h. During IVF fresh semen was collected from ram by electroejaculation, they were washed in H-SOF medium and were fertilized in B-SOF medium with oocytes incubated for 18 hours under 38.5-38.8 degrees C 5% CO2, 5% O-2 and 90% N-2. The oocytes were obtained from maturation medium with/without cysteamine (C+,-) and were cultured in SOF or CR1aa media with/without oviductal cells (Ov+,-) and were grouped as; Group Ia: SOF+(C+ Ov-), Group Ib: SOF+(C+ Ov+), Group Ic: SOF+(C-Ov-) Group Id: SOF+(C-Ov+); Group IIa: CR1aa+(C+ Ov-), Group IIb: CR1aa+(C+ Ov+), Group IIc: CR1aa+(C-Ov-), Group IId: CR1aa+(C-Ov+). Embryos were incubated under 38.5-38.8 degrees C 5% CO2, 5% O-2, 90% N-2 in culture medium for 7 days. Embryo developments were observed and recorded daily. GLM procedure found in SPSS packet program was used for statistical analysis in this study. In conclusion, the addition of cysteamine or oviductal cells in vitro culture media found to have any effect in terms of the capacity of reaching to blastocyst stage in SOF or CR1aa media and no statistical difference is detected between groups.

In this study, we consider a software fault prediction task that can assist a developer during the lifetime of a project. We aim to improve the performance of software fault prediction task while keeping it as applicable. Initial predictions are constructed by Fuzzy Inference Systems (FISs), whereas subsequent predictions are performed by data-driven methods. In this paper, an Artificial Neural Network and Adaptive Neuro Fuzzy Inference System are employed. We propose an iterative prediction model that begins with a FIS when no data are available for the software project and continues with a data-driven method when adequate data become available. To prove the usability of this iterative prediction approach, software fault prediction experiments are performed using expert knowledge for the initial version and information about previous versions for subsequent versions. The datasets employed in this paper comprise different versions of Ant, jEdit, Camel, Xalan, Log4j and Lucene projects from the PROMISE repository. The metrics of the models are common object-oriented metrics, such as coupling between objects, weighted methods per class and response for a class. The results of the models are evaluated according to the receiver operating characteristics with the area under the curve approach. The results indicate that the iterative software fault prediction is successful and can be transformed into a tool that can automatically locate fault-prone modules due to its well-organized information flow. We also implement the proposed methodology as a plugin for the Eclipse environment. (C) 2016 Elsevier B.v. All rights reserved.

High quality software requires the occurrence of minimum number of failures while software runs. Software fault prediction is the determining whether software modules are prone to fault or not. Identification of the modules or code segments which need detailed testing, editing or, reorganising can be possible with the help of software fault prediction systems. In literature, many studies present models for software fault prediction using some soft computing methods which use training/testing phases. As a result, they require historical data to build models. In this study, to eliminate this drawback, Mamdani type fuzzy inference system FIS is applied for the software fault prediction problem. Several FIS models are produced and assessed with ROC-AUC as performance measure. The results achieved are ranging between 0.7138 and 0.7304; they are encouraging us to try FIS with the different software metrics and data to demonstrate general FIS performance on this problem.

The main expectation from reliable software is the minimization of the number of failures that occur when the program runs. Determining whether software modules are prone to fault is important because doing so assists in identifying modules that require refactoring or detailed testing. Software fault prediction is a discipline that predicts the fault proneness of future modules by using essential prediction metrics and historical fault data. This study presents the first application of the Adaptive Neuro Fuzzy Inference System (ANFIS) for the software fault prediction problem. Moreover, Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods, which were experienced previously, are built to discuss the performance of ANFIS. Data used in this study are collected from the PROMISE Software Engineering Repository, and McCabe metrics are selected because they comprehensively address the programming effort. ROC-AUC is used as a performance measure. The results achieved were 0.7795, 0.8685, and 0.8573 for the SVM, ANN and ANFIS methods, respectively. (C) 2014 Elsevier Ltd. All rights reserved.

Software fault prediction is a process which predicts that the software modules are faulty or not by using the software metrics and some soft computing methods.Software metrics are divided into two main categories such as object-oriented and method-level metrics.While class relationships and dependencies are covered by object-oriented metrics, behaviors of the classes can be also measured by method-level metrics.Actually, the complementary relationship between these metric groups is focused in this study and different predictive models are built by using different parameter sets.Each parameter set includes some object-oriented and some method-level metrics.Furthermore, Mamdani style fuzzy inference system (FIS) is employed here to predict faultiness.In contrast to data-driven methods, FIS does not require historical or previous data for modeling.In fact, it is a rule-based approach and rules are extracted with the help of domain experts.In this study, the dataset which consists of the method-level and the class-level metrics' values that are collected from KC1 project of PROMISE repository is employed and most successful model whose performance is 0.8181 according to the evaluation criteria (the area under receiver operating characteristics (ROC) curve (AUC)) is built with the parameters of "coupling between object", "line of code" and, "cyclomatic complexity".

Software fault prediction means identification of the faultprone parts in the software. This enables to focus testing activities on those software modules that are predicted as fault-prone. As can be seen in literature, many soft computing techniques are employed to make more accurate predictions previously. However, software fault prediction has not become routine activity in the software development process, because most of employed methods require historical data to train the model. In fact, collection of the historical data is not a simple job and also collected data represents the project which was observed. It may not be reusable for different projects. To overcome these problems, use of Mamdani type fuzzy inference system to predict software fault prone modules is suggested in this study. Another reason is to eliminate the disadvantages sourced from the small size of data. In this study, object oriented metrics are preferred because of widespread use of object oriented technologies. Experimental results show that fuzzy inference systems are successful and can be competitive with methods previously employed in the literature.

The aims of this study were to investigate the effect of oviductal cells on in vitro maturation (IVM) of canine oocyte in Tissue Culture Medium 199 (TCM-199) or synthetic oviductal fluid (SOF) supplemented with bovine serum albumin (BSA) or fetal calf serum (FCS) and to compare the maturation rates of oocytes from the diestrus and anestrus stages. Following ovariohysterectomy, 13 pairs of ovaries were collected from bitches in anestrus (n = 10) or diestrus (n = 3) and oocytes were harvested by slicing. The oviducts were flushed with TCM-199 containing 10% FCS and were scraped and squeezed into a tube in order to obtain oviductal cells. Selected oocytes were divided into groups for IVM over 48 h for each of the diestrus and anestrus stages as follows: Group Ia, SOF+BSA; Group Ib, SOF+BSA+oviductal cells; Group IIa, SOF+FCS; Group IIb, SOF+FCS+oviductal cells; Group IIIa, TCM-199+BSA; Group IIIb, TCM-199+BSA+oviductal cells; Group IVa, TCM-199+FCS; and Group IVb, TCM-199+FCS+oviductal cells. Afterwards, oocytes were fixed with acetic acid-ethyl alcohol and stained with aceto-orcein to determine nuclear maturation. When compared between anestrus and diestrus stages for all parameters (undetermined nuclear material, germinal vesicles, germinal vesicle break down, metaphase I, metaphase II, and degenerated) in different media, the differences were found to be significant statistically in Group IIa (22.9%) and Group IIIb (35.7%) for the germinal vesicle stage (P < 0.05) as compared to the other groups. In conclusion, in the oocytes obtained from bitches in diestrus and anestrus supplemented with FCS or BSA in SOF medium without oviductal cells, more positive effects were seen on canine oocyte maturation than with TCM-199 medium supplemented with same protein sources and oviductal cells.

This study was conducted to determine the most successful techniques on inmature and in vitro-matured cat oocytes that were parhtenogenically activated using 6-dimethylaminopurine (6-DMAP) and cycloheximide (CHX), in combination with electrical stimulation and calcium ionophore. After 44 h of in vitro maturation, the oocytes with a polar body were separated as mature (M II) and those without a polar body were considered as immature. Four different activation treatments and two control groups were used for parthenogenetic activation with both mature and immature cat oocytes. After 48 h of activation, the oocytes were examined and the non-cleaved oocytes removed. The cleaved oocytes/embryos were cultured in vitro in mSOF medium for an additional four days. After six days of in vitro culture (IVC), embryo quality was evaluated. The results in the present study suggested that (I) both in vitro matured and immature cat oocytes have a potential to develop to morula and blastocyst stages after parthenogenetic activation, (II) electrical stimulation + 6-DMAP is a more useful technique for both matured and immature cat oocytes and (III) to our knowledge, this is the first report that describes morula and blastocyst formation from parthenogenetically activated immature cat oocytes.

The effects of sex and birth type on biparietal diameter (BPD) were examined from 6th to 14th weeks of gestation in 29 pregnant Saanen does by ultrasonography and after birth by observing the kids directly. Fifteen does delivered singles, 13 had twins and one goat had quadruplet males. Twelve of the twins were male and 13 were female; 7 singles were male and 8 were female. In twin pregnancies, the most accurate period for diagnosis of sex of the fetus by observation of the position of the genital tubercle was the 9th week of gestation. However in singles, two errors (13 percent) were made at the 9th week. Twoway anova analysis revealed that birth type did not affect BPD of Saanen goat fetuses, and sexes did not differ until the 14th week (P 0.05). Thus it is concluded that sex of the fetus can be diagnosed directly at the 9th week, but one cannot establish the sex of the fetuses by using only ultrasonographic measurements of BPD in either twin or single pregnancies in Saanen goats.