A Space and Atmospheric Visualization Science System

SAVS (a Space and Atmospheric Visualization Science system) is an integrated system with user-friendly functionality that employs a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, analysis, and visualization. All of this is accomplished without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. This report describes SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the earth's thermospheric, ionospheric, and mesospheric domains (TIMED). The final chapters provide a user-oriented description of interface functionalities, hands-on operations, and customized modules, with details of the primary modules presented in the appendices. The overall intent of the report is to reflect the accomplishments of the three-year development effort and to introduce potential users to the power and utility of the integrated data acquisition, analysis, and visualization system

Seasonal Variation and Geographical Distribution of COVID-19 across Nigeria (March 2020–July 2021)

Globally, the novel corona virus infection has continued to witness a growing number of cases since December 2019 when the outbreak was discovered and noted in China. Despite this has not been well studied for the case of COVID-19, human contact, public moveableness and environmental variables could have an impact onairborne’spropagation and virus continuance, such as influenza virus. This study aimed to determine the seasonal variation and geographical distribution of COVID-19 across Nigeria. An internet based archival research design was employed for this study on the seasonal variation and geographical distribution of COVID-19 across Nigeria. This involved the use of goggle mobility data and world map on Corona Virus Infection (COVID-19). The search strategy for getting information for this research was done electronically. The keywords in the case search using the goggle mobility software was “COVID-19 Update”, “COVID-19 Update in Nigeria”, ‘COVID-19 Winter Report’, “COVID-19 Case Fatality March 2020–July 2021”, “COVID-19 Case Fatality in Nigeria”. The data gotten from the goggle motor updates were entered into Statistical Package for the Social Sciences (SPSS) which was used in the analysis of the study. Results from the study, reported that official COVID-19 cases number was significantly higher in the Dry season (October 2020–April 2021) with 59.0% (127,213) compared to 41.0% (85,176) in the wet/rainy season (May–September) it revealed that the dry and rainy seasons had a COVID-19 prevalence of 0.063 and 0.041 respectively. Further results from the study showed that the prevalence of COVID-19 was 0.07% in the North-Central, 0.04% in both the North-East and North-West, 0.03% in the South-West, 0.09% in the South-South, and the highest prevalence of 0.16% in the South-East. Considering the case Fatality rate of COVID-19 during the Dry and Wet Seasons. The study revealed that North-Central had a death toll of 196 (10.4%) out of 9457 confirmed COVID-19 cases hence a fatality of 2.07. Fatality rate of 1.49% in South western Nigeria, South-South Nigeria, 1.49%, South-East accounted to a fatality rate of 1.25%. Nigeria based on the finding of this study records increased fatality in Dry season over wet seasons. The study concluded that prevalence of COVID-19 varies in seasons in Nigeria Hence; further Data and Meteorological analysis on weather variations towards the SARS-CoV-2 Virus spread should be evaluated by future researchers. It is imperative to ensure strict and controlled application of social measures, such as social distancing, mandatory wearing of non-medical masks to prevent droplets from entering the respiratory tract, screening of affected patients along with quarantine is essential to defeat and improve infection control

Seasonal Variation and Geographical Distribution of COVID-19 across Nigeria (March 2020–July 2021)

Globally, the novel corona virus infection has continued to witness a growing number of cases since December 2019 when the outbreak was discovered and noted in China. Despite this has not been well studied for the case of COVID-19, human contact, public moveableness and environmental variables could have an impact onairborne’spropagation and virus continuance, such as influenza virus. This study aimed to determine the seasonal variation and geographical distribution of COVID-19 across Nigeria. An internet based archival research design was employed for this study on the seasonal variation and geographical distribution of COVID-19 across Nigeria. This involved the use of goggle mobility data and world map on Corona Virus Infection (COVID-19). The search strategy for getting information for this research was done electronically. The keywords in the case search using the goggle mobility software was “COVID-19 Update”, “COVID-19 Update in Nigeria”, ‘COVID-19 Winter Report’, “COVID-19 Case Fatality March 2020–July 2021”, “COVID-19 Case Fatality in Nigeria”. The data gotten from the goggle motor updates were entered into Statistical Package for the Social Sciences (SPSS) which was used in the analysis of the study. Results from the study, reported that official COVID-19 cases number was significantly higher in the Dry season (October 2020–April 2021) with 59.0% (127,213) compared to 41.0% (85,176) in the wet/rainy season (May–September) it revealed that the dry and rainy seasons had a COVID-19 prevalence of 0.063 and 0.041 respectively. Further results from the study showed that the prevalence of COVID-19 was 0.07% in the North-Central, 0.04% in both the North-East and North-West, 0.03% in the South-West, 0.09% in the South-South, and the highest prevalence of 0.16% in the South-East. Considering the case Fatality rate of COVID-19 during the Dry and Wet Seasons. The study revealed that North-Central had a death toll of 196 (10.4%) out of 9457 confirmed COVID-19 cases hence a fatality of 2.07. Fatality rate of 1.49% in South western Nigeria, South-South Nigeria, 1.49%, South-East accounted to a fatality rate of 1.25%. Nigeria based on the finding of this study records increased fatality in Dry season over wet seasons. The study concluded that prevalence of COVID-19 varies in seasons in Nigeria Hence; further Data and Meteorological analysis on weather variations towards the SARS-CoV-2 Virus spread should be evaluated by future researchers. It is imperative to ensure strict and controlled application of social measures, such as social distancing, mandatory wearing of non-medical masks to prevent droplets from entering the respiratory tract, screening of affected patients along with quarantine is essential to defeat and improve infection control

Antimicrobial resistance in Africa: a systematic review

Background: Antimicrobial resistance (AMR) is widely acknowledged as a global problem, yet in many parts of the world its magnitude is still not well understood. This review, using a public health focused approach, aimed to understand and describe the current status of AMR in Africa in relation to common causes of infections and drugs recommended in WHO treatment guidelines. Methods: PubMed, EMBASE and other relevant databases were searched for recent articles (2013–2016) in accordance with the PRISMA guidelines. Article retrieval and screening were done using a structured search string and strict inclusion/exclusion criteria. Median and interquartile ranges of percent resistance were calculated for each antibiotic-bacterium combination. Results: AMR data was not available for 42.6% of the countries in the African continent. A total of 144 articles were included in the final analysis. 13 Gram negative and 5 Gram positive bacteria were tested against 37 different antibiotics. Penicillin resistance in Streptococcus pneumoniae was reported in 14/144studies (median resistance (MR): 26.7%). Further 18/53 (34.0%) of Haemophilus influenza isolates were resistant to amoxicillin. MR of Escherichia coli to amoxicillin, trimethoprim and gentamicin was 88.1%, 80.7% and 29.8% respectively. Ciprofloxacin resistance in Salmonella Typhi was rare. No documented ceftriaxone resistance in Neisseria gonorrhoeae was reported, while the MR for quinolone was 37.5%. Carbapenem resistance was common in Acinetobacter spp. and Pseudomonas aeruginosa but uncommon in Enterobacteriaceae. Conclusion: Our review highlights three important findings. First, recent AMR data is not available for more than 40% of the countries. Second, the level of resistance to commonly prescribed antibiotics was significant. Third, the quality of microbiological data is of serious concern. Our findings underline that to conserve our current arsenal of antibiotics it is imperative to address the gaps in AMR diagnostic standardization and reporting and use available information to optimize treatment guidelines.</p

The genome of Theobroma cacao.

We sequenced and assembled the draft genome of Theobroma cacao, an economically important tropical-fruit tree crop that is the source of chocolate. This assembly corresponds to 76% of the estimated genome size and contains almost all previously described genes, with 82% of these genes anchored on the 10 T. cacao chromosomes. Analysis of this sequence information highlighted specific expansion of some gene families during evolution, for example, flavonoid-related genes. It also provides a major source of candidate genes for T. cacao improvement. Based on the inferred paleohistory of the T. cacao genome, we propose an evolutionary scenario whereby the ten T. cacao chromosomes were shaped from an ancestor through eleven chromosome fusions