Abstract Background: The emptied sheep’s ovarian follicles recently used as a container for spermatozoa during cryopreservation, it was found a proper carrier to cryopreserving spermatozoa in vapor-dependent cryopreservation. The aim of this study was to evaluate the effect of two periods of exposure to liquid nitrogen (LN2)vapor on the parameter of spermatozoa during cryopreservation in this technique. Method: The study was conducted on 30 semen samples from patients with oligozoospermia diagnosed by semen analysis according to the standard criteria of World Health Orgnization (WHO) 2010. Sheep’s ovarian follicles obtained from local slaughterhouse and prepared by slicing the ovaries and evacuating the follicular fluid and oocyte. Each semen sample diluted 1:1 with cryosolution (glycerol 10%) and injected within eight emptied sheep’s ovarian follicles. The first four follicles represent P1; exposed to LN2 vapor for 7.5 minutes and the other four follicles represent P2; exposed to LN2 vapor for 15 minutes before emerged in liquid nitrogen. Sperm progressive motility, total motility, normal morphology and DNA fragmentation index (DFI) were analyzed for all samples pre-freezing and post-thawing. Results: After two months of cryopreservation, sperm progressive motility and total motility significantly (P<0.01) increased post-thawing in P2 as compared with P1, while both of P1 and P2 significantly (P<0.01) decreased as compared with pre-freezing. Normal morphology significantly (P<0.01) decreased post thawing in both P1 and P2 as compared with pre-freezing, while no significantly difference foundbetween P1and P2. DFI significantly (P<0.01) increased post-thawing in P1 and P2 as compared with pre-freezing, while in P2 DFI was significantly lower than in P1. Conclusions: The exposure to liquid nitrogen vapor for 15 minutes in emptied ovarian follicles technique gives a better results than exposure to the vapor for 7.5 minutes regarding sperm progressive motility, total motility and DFI.
In this paper , concrete micro-piles were used to improve the bearing capacity of the soil which is supporting the shallow foundation by using groups of (4; 6 and 9)bored short micro-piles which have, (D=0.125m and D=0.1m), and length to diameter ratio (L/D) equal to (6; 10 and 12) respectively. To calculate the bearing capacity of the micro-piles,(Tomlinson) and (Lamda) methods were used; also the soil properties were taken from Al-Muthana airport,(Al-Qyssi,2001) [1]. The results show that; increasing the number of piles and/ or the diameters and lengths; and the interaction between the bearing capacity of the shallow foundation with the bearing capacity of the pile group which leads to increasing the strength against the external loads
... Show MoreIndustrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
... Show MoreIn this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF4] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF6]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreThis experiment presented essential oils by GC/MS, pigment content, and their antioxidant activities as well as sensory evaluation of delight samples. Limonene (66.88%) was the most prevalent yield. The peels of clementine had DPPH and ABT Scavenging activity. All levels of pigment extract had better scores for all sensory values and recorded acceptable scores in terms of appearance, color, aroma, and overall acceptability compared to control delight. Besides, delight samples containing 15 mg astaxanthin pigment extract showed maximum sensory scores compared to other samples and control delight. On the other hand, the product was less acceptable to the panelists compared to control in the case of the addition of 3.75 mg astaxanthin pigme
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