Vitamin C Enhances Vitamin E Status and Reduces Oxidative Stress Indicators in Sea Bass Larvae Fed High DHA Microdiets

Docosahexaenoic acid (DHA) is an essential fatty acid necessary for many biochemical, cellular and physiological functions in fish. However, high dietary levels of DHA increase free radical injury in sea bass (Dicentrarchus labrax) larvae muscle, even when vitamin E (α-tocopherol, α-TOH) is increased. Therefore, the inclusion of other nutrients with complementary antioxidant functions, such as vitamin C (ascorbic acid, vitC), could further contribute to prevent these lesions. The objective of the present study was to determine the effect of vitC inclusion (3,600?mg/kg) in high DHA (5?% DW) and α-TOH (3,000?mg/kg) microdiets (diets 5/3,000 and 5/3,000?+?vitC) in comparison to a control diet (1?% DHA DW and 1,500?mg/kg of α-TOH; diet 1/1,500) on sea bass larvae growth, survival, whole body biochemical composition and thiobarbituric acid reactive substances (TBARS) content, muscle morphology, skeletal deformities and antioxidant enzymes, insulin-like growth factors (IGFs) and myosin expression (MyHC). Larvae fed diet 1/1,500 showed the best performance in terms of total length, incidence of muscular lesions and ossification degree. IGFs gene expression was elevated in 5/3,000 diet larvae, suggesting an increased muscle mitogenesis that was confirmed by the increase in the mRNA copies of MyHC. vitC effectively controlled oxidative damages in muscle, increased α-TOH larval contents and reduced TBARS content and the occurrence of skull deformities. The results of the present study showed the antioxidant synergism between vitamins E and C when high contents of DHA are included in sea bass larvae diets.     

Drug-Free Nasal Spray as a Barrier against SARS-CoV-2 and Its Delta Variant: In Vitro Study of Safety and Efficacy in Human Nasal Airway Epithelia

The nasal epithelium is a key portal for infection by respiratory viruses such as SARS-CoV-2 and represents an important target for prophylactic and therapeutic interventions. In the present study, we test the safety and efficacy of a newly developed nasal spray (AM-301, marketed as Bentrio) against infection by SARS-CoV-2 and its Delta variant on an in vitro 3D-model of the primary human nasal airway epithelium. Safety was assessed in assays for tight junction integrity, cytotoxicity and cilia beating frequency. Efficacy against SARS-CoV-2 infection was evaluated in pre-viral load and post-viral load application on airway epithelium. No toxic effects of AM-301 on the nasal epithelium were found. Prophylactic treatment with AM-301 significantly reduced viral titer vs. controls over 4 days, reaching a maximum reduction of 99% in case of infection from the wild-type SARS-CoV-2 variant and more than 83% in case of the Delta variant. When AM-301 administration was started 24 h after infection, viral titer was reduced by about 12-folds and 3-folds on Day 4. The results suggest that AM-301 is safe and significantly decelerates SARS-CoV-2 replication in cell culture inhibition assays of prophylaxis (pre-viral load application) and mitigation (post-viral load application). Its physical (non-pharmaceutical) mechanism of action, safety and efficacy warrant additional investigations both in vitro and in vivo for safety and efficacy against a broad spectrum of airborne viruses and allergens.     

Flux measurements for a DD neutron generator using neutron activation analysis

The fast and maximum thermal neutron fluxes from the DD-109 neutron generator at the University of Sharjah were experimentally measured by the activation technique using different neutron reactions. The thermal and fast neutron fluxes were found to be 2.960 × 10~6 and6.186 × 10~7 n/cm~2 s, respectively. This was done to verify the modeling results for the optimum moderator thickness needed to maximize the thermal neutron flux. The optimum moderator thickness was found to be between 3.5 and4 cm. The present data were compared with the detailed MCNP model-based calculation performed in earlier work to simulate the generator.     

Removal of cyanide in aqueous solution by oxidation with hydrogen peroxide in presence of activated carbon prepared from olive stones

This work is dedicated to the removal of the very toxic free cyanide from aqueous solution by oxidation with hydrogen peroxide H₂O₂ in the presence of activated carbon prepared from olive stones. Effects of the initial molar ratio [H₂O₂]₀/[CN^?]₀, the initial cyanide concentration, the activated carbon concentration and the temperature on cyanide removal have been examined. The removal of free cyanide in absence of activated carbon showed very slow kinetics. The presence of activated carbon has increased the reaction rate showing thus a catalytic activity. The kinetics of cyanide removal has been found to be of pseudo-first-order with respect to cyanide and the rate constants have been determined for different values of the aforementioned parameters. The apparent activation energy has been determined from tests carried out at three different temperatures. It was found equal to 46.2 kJ/mol in the presence of activated carbon, which is about half of the 82.7 kJ/mol found for the oxidation in absence of the activated carbon.This process can be interesting for the cyanide removal from processed solutions because it does not use soluble metal catalyst and it consumes only hydrogen peroxide as chemical product.     

The Structure And Properties of a Thermo‐mechanically Processed Low Carbon High Strength Steel

Research efforts were given towards development of low carbon high strength steels since recent past. The present study deals with the development of a low carbon high strength steel alloyed with Mn, Ni, Mo, Cu and microalloyed with Ti and Nb. The steel was subjected to three stage controlled rolling operation followed by accelerated cooling. The structure and properties of the steel at various processing conditions were evaluated. Microstructural observation reveals predominantly lath martensite along with twinned martensite structure at all processing conditions. High strength values at higher finish rolling temperatures have been obtained due to fine martensitic structure along with tiny precipitates of microalloying carbide and carbonitride. The strength value increases marginally at lower finishing temperature due to comparatively finer lath size of martensite and increased precipitation density of carbides, carbonitrides along with Cu particles. The variation in impact toughness properties at different finish rolling temperatures is found to be negligible at ambient and subambient temperatures. The formation of stable and large TiN/TiCN particles during casting have impaired the impact toughness values at ambient and at ‐40°C temperatures.     

Twinning-induced sluggish evolution of texture during recrystallization in AISI 316L stainless steel after cold rolling

This paper deals with the evolution of texture in AISI 316L austenitic stainless steel during annealing after 95 pct cold rolling. After 95 pct cold rolling, the texture is mainly of the brass type {110}〈112〉, along with a scatter toward the S orientation {123}〈634〉 and Goss orientation {011}〈100〉. Weak evidence of Cu component is observed at this high deformation level. During annealing, recovery is observed before any detectable recrystallization. Recrystallization proceeds through nucleation of subgrain by twinning within the deformed matrix and, later, preferential growth of those to consume the deformed matrix. After recrystallization, the overall texture intensity was weak; however, there are some discernible texture components. There was no existence of the brass component at this stage. Major components are centered on Goss orientation and Cu component {112}〈111〉 as well as the BR component {236}〈385〉. Also, a few orientations come up after recrystallization (i.e., {142}〈2−11〉 and {012}〈221〉). With increase in annealing temperature, the textural evolution shows emergence of weak texture with another new component, {197}〈211〉. The evolution of texture was correlated with the deformation texture through twin chain reaction.     

Utilizing Genetic Algorithms to Optimize Membership Functions for Fuzzy Weighted Association Rules Mining

It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining. In general, it is unrealistic that experts can always provide such sets. And finding the most appropriate fuzzy sets becomes a more complex problem when items are not considered to have equal importance and the support and confidence parameters required for the association rules mining process are specified as linguistic terms. Existing clustering based automated methods are not satisfactory because they do not consider the optimization of the discovered membership functions. In order to tackle this problem, we propose Genetic Algorithms (GAs) based clustering method, which dynamically adjusts the fuzzy sets to provide maximum profit based on user specified linguistic minimum support and confidence terms. This is achieved by tuning the base values of the membership functions for each quantitative attribute with respect to two different evaluation functions maximizing the number of large itemsets and the average of the confidence intervals of the generated rules. To the best of our knowledge, this is the first effort in this direction. Experiments conducted on 100 K transactions from the adult database of United States census in year 2000 demonstrate that the proposed clustering method exhibits good performance in terms of the number of produced large itemsets and interesting association rules.     

Neural network optimized with evolutionary computing technique for solving the 2-dimensional Bratu problem

In this paper, a stochastic technique is developed to solve 2-dimensional Bratu equations using feed-forward artificial neural networks, optimized with genetic and interior-point algorithms. The 2-dimensional equations are first transformed into a 1-dimensional boundary value problem, and a mathematical model of the transformed equation is then formulated with neural networks using an unsupervised error. Network weights are optimized to minimize the error. Evolutionary computing based on genetic algorithms is used as a tool for global search, integrated with an interior-point method for rapid local convergence. The methodology is applied to solve three cases of boundary value problems for the Bratu equations. The accuracy, convergence and effectiveness of the scheme is validated for a large number of simulations. Comparison of results is made with the exact solution derived using MATHEMATICA, and is found to be in good agreement.