Ventral and lateral spot patterns differentiation between three smooth newt species (Amphibia: Salamandridae: Lissotriton)

The location, shape and area of dark spots on the belly, throat and sides of the body of three closely related species of smooth newts (Lissotriton kosswigi, L. schmidtleri and L. vulgaris) were analysed. Differences were found between species and sexes in the location and shape of dark spots on the belly, throat and lateral surfaces of the body. Discriminant analysis of these spot characteristics allows to identificate of males of all three species with a high degree of confidence (85–91%). In females, only L. vulgaris was correctly distinguished from the other two species (accuracy 81–94%). Anatolian and Thracian populations of L. schmidtleri have very similar patterns of dark spots, which confirm their conspecificity. The differences in the location and size of dark spots make possible successful identification of the species during field research and study of museum specimens. The developed method could be useful for comparative studies of other animal species which have spotted camouflage or aposematic colouration

Determination of relationship between hardness and groundwater quality parameters by neural networks

All life forms on the earth contain water and water is crucial for any life form on the earth. Apart from being the essential ingredient if living organisms, water has numerous other uses and benefits. Groundwaters form a circle of the natural hydrologic chain like surface waters and the other water in the atmosphere. Hydrologic, hydraulic and geologic processes play important roles during underground water's formation, storage, underground flow and coming up to the surface of the earth. In this study, groundwater hardness quality at Samsun Incesu-Derekoy region was modeled by the use of Artificial Neural Network (ANN) structure. In the data set arrangement effective input variables are the five different water quality parameters (pH, chlorine, calcium, magnesium and total hardness) concentrations in the time "t", and the output variable (total hardness) is the concentrations in the time "t + 1". For the model 10,000 epochs were performed and the learning rate is equal to 0.1, and correlation coefficient (r) that achieved in this Study was found 0.591. As a result, we conclude that ANN is the effective modeling technique on estimation of environmental complex water quality problems

Aerodynamic characteristics of flapping motion in hover

The aim of the present work is to understand the aerodynamic phenomena and the vortex topology of an unsteady flapping motion by means of numerical and experimental methods. Instead of the use of real insect/bird wing geometries and kinematics which are highly complex and difficult to imitate by an exact modeling, a simplified model is used in order to understand the unsteady aerodynamics and vortex formation mechanisms during the different phases of the flapping motion. The flow is assumed to be laminar with a Reynolds number of 1,000. Direct numerical simulations, laser sheet visualizations and particle image velocimetry (PIV) measurements are performed for the phenomenological analysis of the flow. The vortex dynamics and their identification are put in evidence with PIV measurements by considering velocity magnitude, streamlines, second invariant of velocity gradient (Q-criteria), vorticity contours and Eurlerian accelerations

Effect of locus of control on acceptability of euthanasia among medical students and residents in Denizli, Turkey

Abstract Not Availabl

Evaluation of Falls and Fall Risk Factors in Multiple Sclerosis Patients

6th Congress of the European-Academy-of-Neurology (EAN) -- MAY 23-26, 2020 -- ELECTR NETWORK[No Abstract Available]Europ Acad Neuro

AN ARTIFICIAL NEURAL NETWORK-BASED MODEL FOR SHORT-TERM PREDICTIONS OF DAILY MEAN PM10 CONCENTRATIONS

Prediction of particulate matter (PM) in the air is an important issue in control and reduction of pollutants in the air. One of the most useful methods to forecast atmospheric pollution is artificial neural network (ANN) because of its high ability to forecast the atmospheric events. In this study ANN technique has been used to predict the PM10 concentration in Istanbul. Meteorological data and PM10 data, which had been collected from Sariyer-Bahcekoy for the one year data, were used. The data were separated into two groups for training and testing the model. The odd days were used for training and the remaining was used for the testing. The transfer function was sigmoid function. In the model, different hidden neuron numbers were altered for proposed ANN structure. We have altered number of neurons for hidden layer between 2 to 10. The prediction of PM10 of the model during the years 2004-2005 follows the actual values with success, with the best calculated correlation coefficient 0.60

Violence toward health care workers in emergency departments in Denizli, Turkey

This study sought to determine the frequency and types of violence that occurred during the previous year against health care workers in emergency departments in Denizli, Turkey, and to discern the views of workers on the prevention of such aggressive behavior. This study was conducted from March 1 to April 15, 2003, and included a group of 79 health care workers from the emergency departments of 3 hospitals in Denizli, namely, the Hospital of Pamukkale University Medical Faculty, the City Hospital of Denizli, and the Hospital of the Social Insurance Foundation. Data were collected from a self-administered questionnaire. In all, 88.6% of participants had been subjected to or had witnessed verbal violence, and 49.4% of them had been subjected to or had witnessed physical violence during the previous year. The most frequent reason (31.4%) for violence was abuse of alcohol and drugs by perpetrators. The second most frequent reason (24.7%) was the long waiting times typical of emergency departments. The most common type of violence was loud shouting; swearing, threatening, and hitting were the next most frequent violent behaviors. In all, 36.1% of subjects who had experienced violence reported that they developed psychological problems after the incident. Most participants commented on the insufficiency of currently available security systems within emergency departments and on the need for further training about violence. All health care personnel within emergency departments should be aware of the risk of violence and should be prepared for unpredictable conditions and events; in addition, security systems should be updated so that violence within emergency departments can be prevented. ©2006 Health Communications Inc