The aim of the present study is to formulate floating effervescent microsponge tablet of the narrow absorption window drug, Baclofen (BFN) for controlling drug release and thereby decrease the side effect of the drug. The microsponges of BFN were prepared by non-aqueous emulsion solvent diffusion method (oil in oil emulsion method). The effects of drug: polymer ratio, stirring time and type of Eudragit polymer  on the physical characteristics of microsponges were investigated and characterized for production yield, loading efficiency, particle size, surface morphology, and in vitro drug release from microsponges. The selected microsponge formula was incorporated into the floating effervescent gastro-retentive tablet. The prepared fl

Hybrid architecture of ZnO nanorods/graphene oxide ZnO-NRs@GO synthesized by electrostatic self-assembly methods. The morphological, optical and luminescence characteristics of ZnO-NRs@GO and ZnO-NRs thin films have been described by FESEM, TEM, HRTEM, and AFM, which refers to graphene oxide have been coated ZnO-NRs with five layers. Here we synthesis ZnO-NRs@GO by simple, cheap and environmentally friendly method, which made it favorable for huge -scale preparation in many applications such as photocatalyst. ZnO-NRs@GO was applied as a photocatalyst Rodamin 6 G (R6G) dye from water using 532 nm diode laser-induced photocatalytic process. Overall degradation of R6G/ ZnO-NRs@GO was achieved after 90 minutes of laser irradiation while it ne

      In this work, four electronic states ( ,   , and   ) of some diatomic molecules (InF and InCl) was studied by TD-DFT with energy represented by the exchange-correlation energy. The SAOP/ATZP model was applied here to determine all parameters (r_e, B_e, D_e, , , T_e , and were determined to creation reliable values for electron spectroscopy. Also, another set of this calculation has been used represented by two theoretical models: ATZP and et-QZ3P-xD model. Therefore these theoretical models for (   and   , and   ) of the molecules have been compared with many values, theoretical and experimental values,  and appear converge

The present study tackles the complex issue of the urgent need for Environmental Auditing (EA) in Iraq in the absence of laws that support environmental management and in the light of the high rates of cancerous diseases in Iraq, which coincided significantly with the increase in oil production, according to the numbers indicated in the Iraqi Ministry of Health. The study aimed to investigate the mediating role of Management Systems (MS) related to the role of EA supporting sustainability reports concerning the reduction of the negative effects of gas emissions from oil companies. We adopted the descriptive approach which relies on studying relationships through a questionnaire that was distributed to a group of workers at Doura Refinery in

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.