Nanofluids (i.e. nanoparticles dispersed in a fluid) have tremendous potential in a broad range of applications, including pharmacy, medicine, water treatment, soil decontamination, or oil recovery and CO2 geo-sequestration. In these applications nanofluid stability plays a key role, and typically robust stability is required. However, the fluids in these applications are saline, and no stability data is available for such salt-containing fluids. We thus measured and quantified nanofluid stability for a wide range of nanofluid formulations, as a function of salinity, nanoparticle content and various additives, and we investigated how this stability can be improved. Zeta sizer and dynamic light scattering (DLS) principles were used to investigate zeta potential and particle size distribution of nanoparticle-surfactant formulations. Also scanning electron microscopy was used to examine the physicochemical aspects of the suspension. We found that the salt drastically reduced nanofluid stability (because of the screening effect on the repulsive forces between the nanoparticles), while addition of anionic surfactant improved stability. Cationic surfactants again deteriorated stability. Mechanisms for the different behaviour of the different formulations were identified and are discussed here. We thus conclude that for achieving maximum nanofluid stability, anionic surfactant should be added.
Morphological and phonological studies of fungal pathogen infecting alfalfa weevil Hypera postica (Gyllenhal) indicating that infection has been shown to develop along two distinct physiological lines, each culminating in the production of either conidial or resting spores, in host cadavers which are morphologically distinct. The percent of infection and epizootic development appeared to be dependent on host density. Farther evidence to entail proper correlation between conidia and resting spores suggest that these two forms of spores are stages in the development of one pathogen.
This paper deals to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th
... Show MoreThis study aims to study argumentation in political debates by figuring out the logical fallacies employed in the debates of Clinton and Trump, the presidential nominees of the 2016 elections, and Biden and Trump, the leading contenders in the 2020 United States presidential election. The study attempts to answer the questions: (1) What relevance fallacies are adopted in the debate between Trump and Clinton? (2) What rhetorical devices are used to influence the audience and gain voters besides fallacies in the debates selected? The study analyses two texts from two arguments using Damer's (2009) taxonomy of relevance fallacy and rhetorical devices based on Perrine’s (1969) model of communication and interpersonal rhetoric to answe
... Show MoreDegradation is one of the key processes governing the impact of pharmaceuticals in the aquatic environment. Most studies on the degradation of pharmaceuticals have focused on soil and sludge, with fewer exploring persistence in aquatic sediments. We investigated the dissipation of 6 pharmaceuticals from different therapeutic classes in a range of sediment types. Dissipation of each pharmaceutical was found to follow first‐order exponential decay. Half‐lives in the sediments ranged from 9.5 (atenolol) to 78.8 (amitriptyline) d. Under sterile conditions, the persistence of pharmaceuticals was considerably longer. Stepwise multiple linear regression analysis was performed to
Polycystic ovary syndrome (PCOS) is a significant cause of infertility due to ovulation dysfunction in women of childbearing age. Although the pathogenesis of PCOS is still not clear, many studies have shown that many factors within the ovary promote infection. With this syndrome, the disruption of the natural monthly ovulation process causes an imbalance in the body's hormones, and the high level of insulin in the body and the blood sugar imbalance leads to the occurrence of hyperandrogenism, which is the main factor for the occurrence of pathogens, in addition to genetic factors, if any. This study aims to identify this disease and its most important causes, symptoms, and modern treatments to prevent and get rid of it. Polycystic
... Show MoreThe paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.
Selexipag is an orally selective long-acting prostacyclin receptor agonist, which indicated for the treatment of pulmonary arterial hypertension. It is practically insoluble in water ( class II, according to BCS). This work aims to prepare and optimized Selexipag nanosuspensions to achieve an enhancement in the in vitro dissolution rate. The solvent antisolvent precipitation method was used for the production of nanosuspension, and the effect of formulation parameters (stabilizer type, drug: stabilizer ratio, and use of co-stabilizer) and process parameter (stirring speed) on the particle size and polydispersity index were studied. SLPNS prepared with Soluplus® as amain stabilizer (F15) showed the smallest particle size 47nm wi
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