In this study, polymeric ultrafiltration (UF) membranes were prepared by phase inversion method to obtain both antibacterial and organic antifouling properties. The membranes were cast from a solution of polyvinylidene fluoride (PVDF) and formative silver (Ag) nanoparticles were successfully immobilized on a polymer. This was done using a solvent N, N-dimethylformamide (DMF) which is a solvent for the PVDF polymer meanwhile it is a reducing agent for silver ion. The effect of silver nanoparticles additives on the performance of polymeric ultrafiltration membrane was verified. Chemical composition and morphology of the surfaces of the membranes were characterized by Fourier transform infrared spectroscopy

            Felodipine is a calcium-channel blocker with low aqueous solubility and bioavailability. Lipid dosage forms are attractive delivery systems for such hydrophobic drug molecules. Nanoemulsion (NE) is one of the popular methods that has been used to solve the dispersibility problems of many drugs. Felodipine was formulated as a NE utilizing oleic acid as an oil phase, tween 80 and tween 60 as surfactants and ethanol as a co-surfactant. Eight formulas were prepared, and different tests were performed to ensure the stability of the NEs, such as particle size, polydispersity index, zeta potential, dilution test, drug content, viscosity and in-vitro drug release. Result

The aim of this paper is to explore the relationship between sustainability reporting (SR) and corporate reputation (CR) in the context of initial public offering (IPO) companies in the developing market of Malaysia. This study utilises secondary data from 2007 to 2017 derived from the content analysis of the annual reports and Datastream of 139 sampled IPO companies listed on Bursa Malaysia. The study also employs ordinary least squares (OLS) regression. The result shows that CR has a positive association with SR quantity and quality and its dimensions, i.e., society, environmental, employee, and product. This result suggests that IPO companies can use SR practices to improve their CR. Most companies give little attention to SR issues. Mor

Long before the pandemic, labour force all over the world was facing the quest of incertitude, which is normal and inherent of the market, but the extent of this quest was shaped by the pace of acceleration of technological progress, which became exponential in the last ten years, from 2010 to 2020. Robotic process automation, work remote, computer science, electronic and communications, mechanical engineering, information technology digitalisation o public administration and so one are ones of the pillars of the future of work. Some authors even stated that without robotic process automation (RPA) included in technological processes, companies will not be able to sustain a competitive level on the market (Madakan et al, 2018). R

Throughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.

Interval methods for verified integration of initial value problems (IVPs) for ODEs have been used for more than 40 years. For many classes of IVPs, these methods have the ability to compute guaranteed error bounds for the flow of an ODE, where traditional methods provide only approximations to a solution. Overestimation, however, is a potential drawback of verified methods. For some problems, the computed error bounds become overly pessimistic, or integration even breaks down. The dependency problem and the wrapping effect are particular sources of overestimations in interval computations. Berz (see [1]) and his co-workers have developed Taylor model methods, which extend interval arithmetic with symbolic computations. The latter is an ef

Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to