An SVM-Based Classification and Stability Analysis of Synthetic Emulsions Co-Stabilized by a Nonionic Surfactant and Laponite Clay

Emulsions are metastable systems typically formed in the presence of surfactant molecules, amphiphilic polymers, or solid particles, as a mixture of two mutually immiscible liquids, one of which is dispersed as very small droplets in the other. These dispersions are unwanted occurrences in some areas, like those formed during crude oil production, but are also put into many other useful applications in the oil and gas industry, food industry, and construction industry, among others. These emulsions form when two immiscible liquids come together in the presence of an emulsifying agent and sufficient agitation strong enough to disperse one of the liquids in the other. Thermodynamically, these emulsions are unstable and thus would separate into their individual phases when left alone. To be stabilized, surface-active agents (surfactants) or solids (that act in so many ways like surfactants) ought to be used. Like many commercially available products, several pharmaceutical products are usually supplied in the form of emulsions that must be stabilized before they are being administered. Pharmaceutical emulsions used for oral administration either as medications themselves or as carriers come in form of stable emulsions. Either water-in-oil (w/o) or oil-in-water (o/w), these emulsions after formulation must be classified, majorly as stable or unstable. Only formulations that give stable emulsions are used, and the unstable ones reformulated or discarded. Classifying such emulsions using results obtained by visual observation in most cases can be very tedious and inaccurate. This necessitates the use of a more scientific and intelligent method of classification. The objective of this study is to employ support vector machine (SVM) as a new technique to classify synthetic emulsions. The study will assess the effects of nonionic surfactant (sodium monooleate) and Laponite clay (LC) on the stability of synthetic emulsions prepared using a response surface methodology (RSM) based on a Box-Behnken design. The stability of the emulsions was measured using batch test and TurbiScan, and the SVM was used to classify the emulsions into stable, moderately stable and unstable emulsions. The study showed that an increase in surfactant concentration in the presence of moderate to high concentrations of LC can provide a stable emulsion. Also, a clear classification of the emulsion samples was provided by the SVM, with high accuracy and reduced misclassifications due to human error. A higher accuracy in classification would reduce the risk of using the wrong formulation for any pharmaceutical product

Predicting the Viscosity of Petroleum Emulsions Using Gene Expression Programming (GEP) and Response Surface Methodology (RSM)

This paper summarizes an investigation of certain operating parameters on the viscosity of petroleum emulsions. The production of crude oil is accompanied by emulsified water production, which comes along with various challenges like corroding the transport systems and catalysts poisoning during petroleum refining in the downstream. Several process variables are believed to affect the ease with which emulsified water can be separated from emulsions. Some of the issues have not been extensively examined in the literature. The simplicity with which water is separated from petroleum changes with age (after formation) of the emulsion; notwithstanding, this subject has not been investigated broadly in literature. This study tries to assess the correlation between aging time, water cut, crude oil viscosity, water viscosity and amount of solids and viscosity of petroleum emulsions. To achieve that, a response surface methodology (RSM) based on Box-Behnken design (BBD) was used to design the experiment. Synthetic emulsions were prepared from an Offshore Malaysian Crude oil based on the DoE design and were aged for 7 days. The emulsions viscosities were measured at 60-degree Celsius using an electromagnetic viscometer (EV100). The broad pressure and temperature range of the HPHT viscometer permit the imitation of acute conditions under which such emulsions may form. The data obtained from the RSM analysis was used to develop a prediction model using gene expression programming (GEP). It was discovered that the viscosity of water has no effect on the viscosities of the studied emulsions, as does the water cut and amount of solids. The most significant factor that affects emulsion viscosity is the aging time, with the emulsion becoming more viscous over time. This is believed to be imminent because of variations in the interfacial film structure. This is followed by the amount of solids, also believed to be as a result of increasing coverage at the interface of the water droplets, limiting the movements of the dispersed droplets (reduced coalescence), thereby increasing the viscosity of the emulsions

Tackling cryptococcal meningitis in Nigeria, one-step at a time; the impact of training.

BACKGROUND:Nigeria is estimated to have 25,000 cases of cryptococcal antigenemia (CrAg) annually. CrAg screening with pre-emptive fluconazole treatment is recommended but not yet implemented in Nigeria. Trainings were conducted to improve health-care provider (HCP) awareness and clinical skills in the management and prevention of cryptococcal meningitis (CM). METHODS:HCPs providing care for people living with HIV were targeted for training at 13 sites from April to November 2018 Course content was adapted from CDC Cryptococcal Screening Program Training Manual and LIFE-website. "Hands-on" training on CrAg testing and lumbar puncture was included. A 14-point pre and post-test assessment instrument was designed to capture the impact of the training and focus group discussions (FGDs) were conducted. RESULTS:A total of 761 HCPs were trained. 519 HCPs completed the pre-test evaluation while 470 (90.6%) took part in the post-test evaluation. Post-training, HCPs were significantly more likely to respond correctly to all 14 assessment items, with the mean percentage score rising to 91.0% from a pre-training value of 60.0%. FGDs revealed that many of the HCPs were not aware of the CrAg screening and pre-emptive treatment recommendations in Nigerian guidelines, and reported not having seen or managed a case of CM. Also, they highlighted challenges with routine CrAg screening due to a lack of access to CD4 testing, CrAg test kits, antifungal drugs, as well as the need for similar trainings across all tiers of care in Nigeria. CONCLUSION:Training significantly improved HCPs' understanding of Nigerian policy on CrAg screening, CM diagnosis and best management practices. This training could be included in routine capacity building efforts for HCPs involved in HIV care in Nigeria