The present study deals with the relationship of noise pollution to the mental health of university students, through the researcher field study with the use of descriptive Correlative approach to investigate this relationship. Noise is one of the elements of environmental pollution that people often expose to in their environment. The problem of noise has been exacerbated now because of cultural and technological progress in crowded cities. As a result, the researchers studied noise as an environmental stimulus that affects the mental health of the human being.The researchers, through their current research try to study a very serious problem, which is the problem of noise pollution on the health side of university students as a

This study was conducted to evaluate the hydrocarbon biodegradation abilities of Enterobacter cloacae, Staphylococcus aureus, Sphingomonas paucimobilis, and Pentoae species which were isolated from different diesel-contaminated soil samples. The isolates were identified by the Vitek 2 system. Fourier-transform spectroscopy (FT-IR) tested the potential of these isolates to biodegrade the diesel according to the peak areas, a significant decrease in the area of the peaks at 2856-2928 cm−1 corresponds to aliphatic hydrocarbons. The appearance of small peaks at 900-1032 cm−1 refers to substituted benzene derivative compounds. An appearance of some new peaks at 3010- 3030 cm−1 which indicate the presence of alcohol (-OH) and ketones (RC=O)

The paper presents an annotated checklist of the Salticidae of Armenia. This study was carried out in 2019-2020 in order to provide an inventory of the Salticidae fauna. Thirteen species are reported for the Armenian fauna for the first time: Afraflacilla epiblemoides (Chyzer, 1891); Aelurillus v-insignitus (Clerck, 1757); Asianellus festivus (C. L. Koch, 1834); Heliophanus dubius C. L. Koch, 1835; Heliophanus kochii Simon, 1868; Heliophanus tribulosus Simon, 1868; Heliophanus curvidens (O. Pickard-Cambridge, 1872); Macaroeris nidicolens (Walckenaer, 1802); Pellenes diagonalis (Simon, 1868); Pellenes geniculatus (Simon, 1868); Pellenes seriatus (Thorell, 1875); Pellenes tripunctatus (Walckenaer, 1802) and Phlegra fasciata (Hahn, 1826).

Background: Concha bullosa is an anatomical variation which defined by pneumatizaton of middle turbinate that occurred with an incidence of (5 to 25%) in the normal population.It has the potential to cause crowding and obstruction of the middle meatus and nasal cavity. There are many surgical techniques which utilized for its management. Study goal: Is to compare the formation of adhesion between endoscopic partial lateral middle turbinectomy and middle turbinate trimming in cases of concha bullosa. Patients and methods: A prospectivecomparative clinical trial was performed in the ENT department at Al-Shahid Ghazi AL Hariri Hospital in Medical City over the period from September 2016 to August 2017. Fifty nine (59) patients {24 males

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

Autorías: Nuha Mohsin Dhahi, Ahmed Thare Hani, Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.