Dark Energy or Apparent Acceleration Due to a Relativistic Cosmological Model More Complex than FLRW?

We use the Szekeres inhomogeneous relativistic models in order to fit supernova combined data sets. We show that with a choice of the spatial curvature function that is guided by current observations, the models fit the supernova data almost as well as the LCDM model without requiring a dark energy component. The Szekeres models were originally derived as an exact solution to Einstein's equations with a general metric that has no symmetries and are regarded as good candidates to model the true lumpy universe that we observe. The null geodesics in these models are not radial. The best fit model found is also consistent with the requirement of spatial flatness at CMB scales. The first results presented here seem to encourage further investigations of apparent acceleration using various inhomogeneous models and other constraints from CMB and large structure need to be explored next.Comment: 6 pages, 1 figure, matches version published in PR

Strain and composition dependence of the orbital polarization in nickelate superlattices

A combined analysis of x-ray absorption and resonant reflectivity data was used to obtain the orbital polarization profiles of superlattices composed of four-unit-cell-thick layers of metallic LaNiO3 and layers of insulating RXO3 (R=La, Gd, Dy and X=Al, Ga, Sc), grown on substrates that impose either compressive or tensile strain. This superlattice geometry allowed us to partly separate the influence of epitaxial strain from interfacial effects controlled by the chemical composition of the insulating blocking layers. Our quantitative analysis reveal orbital polarizations up to 25%. We further show that strain is the most effective control parameter, whereas the influence of the chemical composition of the blocking layers is comparatively small.Comment: 9 pages, 8 figure

Bacteriology of Post Caesarean Wound Infection in a Specialist Hospital in Kano, North Western Nigeria

Post caesarean wound infection is a common cause of maternal morbidity and mortality especially in developing countries where strict adherence to infection control procedures is low. The aim of the present study is to establish the spectrum of microbes causing post caesarean wound infection and antibiotic sensitivity pattern in our locality. Specimens collected were processed and antibiotic sensitivity pattern determined by disc diffusion method. Out of 1,230 patients in this study, 246(20%) were infected. Of which 206 (83.7%) yielded growth. E. coli 65(28.8%) was the most frequently isolated pathogen followed by Proteus mirabilis (23.0%) and Staphylococcus aureus (19.0%) Bacterial pathogens were resistant to commonly used antibiotics such as cotrimoxazole, tetracycline, cefuroxime and cloxacillin, while cephalosporin and fluoroquinolones were highly effective against the isolates. Emergency caesarean section received the risk of post caesarean wound infection. The cephalosporin especially ceftriaxone will be useful as prophylactic antibiotic when combined with metronidazole and administered just before surgery is commenced.Key words: Post caesarean wound infection, bacterial isolates, antibiotic sensitivity patter

Performances of the Industrial, Oil and Gas and the Insurance Sectors in Nigeria – A Correlational Analysis

This paper comparatively examines the performances of Nigeria’s Oil and Gas, Insurance and the Industrial Sectors using their Market Capitalization for a period of 2009-2015 sourced from the Nigerian Stock Exchange. Augmented Dickey-Fuller Test was used to ensure the stationarity of the distribution by means of differencing, ANOVA for the analysis of variances while Pearson Correlation was employed to empirically establish the direction and strength of relationships between sectors’ performances. Findings showed that the industrial sector’s market capitalization consistently reduces as that of the oil and gas sector increases, given a significant strong negative correlation coefficient of -0.738 for the relationship between them. As trend analysis also showed that the performances of the oil and gas sector has been declining since the latter years under review (2014/2015), the paper recommended economic diversification through development of other sectors, particularly the industrial sector. Keywords: Oil and Gas Sector, Insurance Sector, Industrial Sector, and  Market Capitalization JEL CLASSIFICATION: G10, G15,  G19,.

Methicillin resistant S. aureus (MRSA) and their antibiotic sensitivity pattern in Kano, Nigeria

Background: Nosocomial infection caused by methicillin resistant S. aureus (MRSA) presents with management difficulties in infected patients due to their resistance to a number of other frontline antibiotics and constitutessignificant epidemiological problems. This study was undertaken to determine the prevalence of methicillin resistant S. aureus and antibiotic sensitivity pattern in clinical isolates in Kano. There is dearth of  information onthis subject in Kano.Method: One hundred and eighty five (185) S. aureus isolates from various clinical specimens obtained over a 12-month period in the Microbiology Department of Aminu Kano Teaching Hospital (AKTH) were subjected to methicillin susceptibility testing, while including susceptibility testing to other antibiotics by the disc diffusion methods.Result: Out of 185 S. aureus isolates tested, 53(28.6%) were found to be methicillin resistant. While 38(62%) isolates were obtained from in-patients, 15(28%) were from out-patients. Surgical wound infection had the highest prevalence of 32(60%) isolates. Antibiotics sensitivity results of methicillin susceptible staphylococcus aureus MSSA) and MRSA with the third generation cephalosporins and the quinilones were encouraging. AllMRSA isolates were sensitive to vancomycin.Conclusion: A prevalence of 28.6% MRSA in this environment calls for urgent intervention strategies due to its possible rapid spread and therapeutic problem

Clinical implementation of a knowledge based planning tool for prostate VMAT

Abstract Background A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. Methods A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as “optimal” and “sub-optimal” by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Results Plans identified as “sub-optimal” in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as “optimal” observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. Conclusions The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data

Analysis of accidents caused by human factors in the oil and gas industry using the HFACS-OGI framework

Background: Human factors have been identified as the most common causes of catastrophic accidents in the oil and gas industry. Therefore, this study aims to analyze human causal factors of accidents in the oil and gas industry using the Human Factors Analysis and Classification System for the Oil and Gas Industry (HFACS-OGI) framework. Methods: This study involved a quantitative data collection of 184 accident cases in the oil and gas industry that occurred from 2013 to 2017 from the International Association of Oil and Gas Producers (IOGP) database. The causal factors of these accidents were coded using the HFACS-OGI framework. Accident data were analyzed using descriptive statistics and χ2 test. Results: Study findings reveal that 23% of all accidents was recorded in 2013. 32% of accidents occurred in Asia, while 69% of accidents were recorded in onshore locations. Contractors were involved in 86% of accidents, while 28% of accidents occurred during drilling, workover and well services. Contractor’s work environment was the main human factor in 90% of accident cases. Conclusion: The HFACS-OGI framework proves to be a vital tool for robust accident analysis of human factors in the oil and gas industry