Tench is a cyprinid fish that has undergone human-induced translocations. The natural populations of the species are on the decline due to habitat loss and spawning grounds degradation. The genetic diversity of seven natural populations was investigated to establish the genetic knowledge base for successful conservation efforts and for selective breeding. Twelve microsatellite markers, the sequencing of a 615 bp section of mtDNA (Cytb) and PCR-RFLP analysis of two nuclear markers (Act) and (RpS7) were used to analyze the genetic variation and structure among 175 individuals. All microsatellite loci were found to have moderate levels of polymorphism. The pairwise Fst values between population pairings were moderate; the populations were aligned to four clusters. The Cytb gene showed 20 haplotypes; 67.1% of individuals were categorized as Eastern, while 32.9% to the Western haplogroup. Analysis of the Act and RpS7 genes showed that the level of hybridization among the two haplogroups is high within the sampled populations. Hungarian Tench populations are genetically less diverse compared to natural populations in Western-Europe, but they still represent valuable genetic resources and Lake Fertő, Lake Kolon and Csörnöc-Herpenyő populations can be optimal candidates for future selective breeding programs.
As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficie
... Show MoreFungi produce a series of toxic compounds on corn, especially Fumonisin B1 (FB1) toxin produced by Fusarium spp. and promoting cancer activity in humans and animals. This study aimed to the isolation and identification of fungi associated with local corn seeds and the detection for the presence of FB1 by using ELISA technique. Thirty samples of corn ears were collected from silos and markets in Baghdad city during the period from November 2018 to March 2019. The present study found that Fusarium was the dominant isolate among fungi in terms of the relative density 57.07%, followed by Aspergillus 31.17%, Rhizopus 3.36%, Alternaria 2.88%, Mucor 2.16%, Penicillium 1.92%, Trichothecium 0.96%, and Helminthosporium 0.48%. FB1 was detected in a
... Show MoreIn this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f
... Show MoreDue to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi
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