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).

Many waste materials can be repurposed effectively within asphalt concrete to enhance the performance and sustainability of pavement. One of these waste materials is sawdust ash (SDA). This study explores the beneficial use of SDA as a substitute for limestone dust (LD) mineral filler in asphalt concrete. The replacement rate was 0%, 15%, 30%, 45%, and 60% by weight of total mineral filler. Scanning electron microscopy (SEM) was employed to assess the surface morphology of Sawdust (SD), SDA, and LD. In addition, a series of tests, including Marshall stability and flow, indirect tensile strength,moisture susceptibility, and repeated uniaxial loading tests, were conducted to examine the performance characteristics of asphalt mixtures of diffe

Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had

A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa

In this paper, certain types of regularity of topological spaces have been highlighted, which fall within the study of generalizations of separation axioms. One of the important axioms of separation is what is called regularity, and the spaces that have this property are not few, and the most important of these spaces are Euclidean spaces. Therefore, limiting this important concept to topology is within a narrow framework, which necessitates the use of generalized open sets to obtain more good characteristics and preserve the properties achieved in general topology. Perhaps the reader will realize through the research that our generalization preserved most of the characteristics, the most important of which is the hereditary property. Two t

BN Rashid, International Journal of Research in Social Sciences and Humanities, 2019 - Cited by 1

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

   History matching is a significant stage in reservoir modeling for evaluating past reservoir performance and predicting future behavior. This paper is primarily focused on the calibration of the dynamic reservoir model for the Meshrif formation, which is the main reservoir in the Garraf oilfield. A full-field reservoir model with 110 producing wells is constructed using a comprehensive dataset that includes geological, pressure-volume-temperature (PVT), and rock property information. The resulting 3D geologic model provides detailed information on water saturation, permeability, porosity, and net thickness to gross thickness for each grid cell, and forms the basis for constructing the dynamic reservoir model. The dynamic reservoir mo

This research examines the scientific impact of Al-Hafiz Sharaf al-Din al-Damiati, who descended from a famous scholarly family known as (Al-Damiati) in reference to the city of Damietta in Egypt. This family was distinguished by producing scholars and writers during the Ayyubid and Mamluk eras, the most prominent of whom was Sharaf al-Din. He was preceded by a scholar of no lesser scientific stature, Shams al-Din al-Damiati (d. 693 AH), who was famous for his knowledge of the science of readings. Sharaf al-Din al-Damiati was famous for his mastery of the science of hadith and genealogy. The political situation that prevailed during his era was represented by the occupation of the city of Baghdad in 656 AH/1258 AD, the end of the Abbasid Ca