The effects of nutrients and physical conditions on phytase production were investigated with a recently isolated strain of Aspergillus tubingensis SKA under solid state fermentation on wheat bran. The nutrient factors investigated included carbon source, nitrogen source, phosphate source and concentration, metal ions (salts) and the physical parameters investigated included inoculum size, pH, temperature and fermentation duration. Our investigations revealed that optimal productivity of phytase was achieved using wheat bran supplemented with: 1.5% glucose. 0.5% (NH4)2SO4, 0.1% sodium phytate. Additionally, optimal physical conditions were 1 × 105 spore/g substrate, initial pH of 5.0, temperature of fermentation 30˚C and fermentation dura

This research includes problems that facing the philosophy of education in the variables of knowledge and Informatics society (techno _ social).

 The problematic research included three questions:

 1- What are the concepts and characterization related to the problematic of relationship between the philosophy of education and informatics variables (techno - social).

2-What kind of problems facing speech philosophy of education in the variables information (techno - social)

  3 - What are the perceptions of educational proposed to address problematic philosophy of education in the scope of human (human nature) and (values ​​and morals), in addition the research may explain the co

Breast tumor patients generally have more oxidative stress than normal females. This was clear from significant decrease (P<0.05) in tissue GSSG-Red activity. The study had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the GSH- Red might be used as markers for prognosis of the disease. Results of molecular characterization show optimum enzyme concentration substrate conc., optimum pH, temperature & time & effect of some (chemotherapies in constant conectrations) for GSSG-Red activity.

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

The objective review is to inspect the involvement of Interleukin-6 (IL-6) in rheumatoid arthritis (RA) and to highlight the role of IL-6 and its variants in the pathogenesis of RA and response to anti-IL-6 agents. Several genetic and environmental risk factors and infectious agents contributed to the development of RA. Interleukin-6 is engaged in self-targeted immunity by modifying the equilibrium between T regulatory (T-reg) and T helper-17 (Th-17) cells. The evidences reported that IL-6 parti

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization