Oilfield Scale-Induced Permeability Damage Management During Waterflooding

The precipitation, accumulation and disposition process of oilfield sulphate scales is a major ongoing flow assurance problem in hydrocarbon production. This pose serious injectivity and productivity problems in a water flooded reservoirs. Several works and software packages such as multi-scale 6.0 and scalechem have been developed for predicting scaling tendency and average scalesprecipitation inside the reservoir but neglecting the fact that not all the occurring scale precipitation would cause formation damage near the well bore region. Some of the precipitated scales escape through the pore spaces to render havoc to flow in the production string since it is not all the scale precipitation inside the reservoir would plug the formation. For an adequate planning and monitoring of water injection, scale treatment schedule and disposition programme, there is the need to estimate the fraction of sulphate scales precipitation that occupies pore spaces and the corresponding degree of permeability damage at well bore vicinity. It is also imperative to evaluate the effects of oilfield scale induced permeability damage on the success of water flooding project. In this paper, an interactive software package has been developed for predicting the fraction of oilfield scales that occupies pore space and the corresponding permeability damage at different location away from the well bore. The software complement the existing oilfield scaling prediction software such as multi-scale 6.0, scalechem and scalbute recently reported by Fadairo et al. This is useful for adequate planning and controlling of water injection project, oilfield scale treatment schedule and disposition programme

Occurrence of antibiotic-resistant Staphylococcus aureus in some street-vended foods in Ogun State, Nigeria

Staff PublicationFood borne illnesses of microbial origin are a major international health problem associated with food safety and an important cause of death in developing countries. This study was carried out to investigate the occurrence of antibiotic-resistant Staphylococcus aureus in some street-vended foods in Ogun State, Southwerstern Nigeria. A total of 140 street-vended food samples which included 20 samples each of fish sausages, meat sausages, fried fish, fried meat, fried yam, moin-moin and jollof rice were purchased from vendors in three different communities (Sabo, Isale-Oko and Makun) in Sagamu, Ogun State, Nigeria. Demographic survey was carried out on the hygienic and safety attitudes cultivated by the vendors recruited for this study. Microbiological analyses were carried out on the food products to isolate typical S. aureus strains. The samples were serially diluted and dilution factors of up 10-6 were cultured on Mannitol salt agar medium employing the spread plate technique. The disc-diffusion method was employed to determine the antibiotic resistance patterns of the isolated S. aureus strains. Most vendors were aware of the heath risk associated with unhygienic practices. Percentage products contaminated ranged from 0%, as obtained from fried yam, to 40% obtained from fish sausages. Prevalence of S. aureus strains obtained from samples ranged from 0 (as in fried yam) to 5.20 + 1.2 cfu ml-1 (as obtained from jollof rice). The isolates were subjected to antibiotic susceptibility assay employing the disc diffusion technique. Results on the resistance patterns of the isolated S. aureus strains revealed that resistance was highest to gentamycin (45.8%) and lowest to cotrimoxazole (4.2%) and erythromycin (4.2%). In conclusion, street vended food samples are frequently contaminated with S. aureus and that these could serve as potential vehicle for the transmission of resistant strains of the pathogen. Increased resistance of S. aureus to certain broad spectrum antibiotics such as gentamicin and amoxicillin should stimulate the interest of researchers

Computational study of the inhibitory potential of Gongronema latifolium (benth) leave on farnesyl pyrophosphate synthase, a target enzyme in the treatment of osteoporosis. A molecular modelling approach

Background & Aim: Osteoporosis is an increasing medical threat which is referred to as a systemic skeletal disorder that is characterized mainly by low bone mass and microarchitectural wear of bone tissue and strength, which eventually results in an increase in the fragility of bone and makes bone to be susceptible to fracture. Osteoporosis is known globally as a severe health problem affecting approximately 200 million people worldwide. Therefore, a pharmacological solution is urgently needed. Studies have shown that farnesyl pyrophosphate synthase is a crucial enzyme in the mevalonate pathway that causes bone resorption, thus serving as a key pharmacological target. Experimental: Gongronema latifolium’s (Benth) phytoconstituents were screened against the mevalonate pathway enzyme farnesyl pyrophosphate synthase computationally using molecular docking, pharmacokinetics screening and Molecular Mechanics/Generalized Born Surface Area approach to identify compounds with the better inhibitorypotentials against this target in this study. Results: The study resulted that five compounds; hyperoside, rutin, epigallocatechin-3-gallate, kaempferol-3-arabinoside, and isoquercetin show a better inhibitory potential by binding to the active site of farnesyl pyrophosphate synthase compared with a co-crystalized ligand. These hit compounds were further subjected to pharmacokinetics studies to predict their drug-likeness and toxicity characteristics which show that all hit compounds except Rutin are drug-like leaving Kaempferol-3-Arabinoside as the most drug-like hit compound compared to the co-crystallized ligand. Recommended applications/industries: This study suggests that G. latifolium leaf could be a good plant source for a drug-like compound that may treat osteoporosis by inhibiting the farnesyl pyrophosphate synthase, in the mevalonate pathway, thereby stopping bone resorption

A rare case of left additional renal artery in a Nigerian goat

The report of the occurrence of additional renal arteries in domestic animals is rare in the literature. We report a case of an additional renal artery in the left kidney found in a Red Sokoto goat cadaver. The additional renal artery originated from the abdominal aorta 3.80 cm cranial to the origin of the main renal artery. The additional renal artery was relatively long, being 6.30 cm from its origin to the cranial pole region of the kidney where it supplied the kidney. This to the best of our knowledge is the first report in the literature indexed in the Medline of an additional renal artery in a goat

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Cloud client prediction models for cloud resource provisioning in a multitier web application environment

In order to meet Service Level Agreement (SLA) requirements, efficient scaling of Virtual Machine (VM) resources must be provisioned few minutes ahead due to the VM boot-up time. One way to proactively provision resources is by predicting future resource demands. In this research, we have developed and evaluated cloud client prediction models for TPCW benchmark web application using three machine learning techniques: Support Vector Machine (SVM), Neural Networks (NN) and Linear Regression (LR). We included the SLA metrics for Response Time and Throughput to the prediction model with the aim of providing the client with a more robust scaling decision choice. Our results show that Support Vector Machine provides the best prediction model

Predicting cloud resource provisioning using machine learning techniques

In order to meet Service Level Agreement (SLA) requirements, Virtual Machine (VM) resources must be provisioned few minutes ahead due to the VM boot-up time. One way to do this is by predicting future resource demands. In this research, we have developed and evaluated cloud client prediction models for TPC-W benchmark web application using three machine learning techniques: Support Vector Machine (SVM), Neural Networks (NN) and Linear Regression (LR). We included the SLA metrics for Response Time and Throughput to the prediction model with the aim of providing the client with a more robust scaling decision choice. Our results show that Support Vector Machine provides the best prediction model