No abstract
NoSQL is a database used to store high volume of data. NoSQL databases are horizontally scalable, distributed, open source and non-relational. High performance is a major concern for practically every data-driven system. NoSQL databases claim to deliver faster performance than the popular Relational database systems in various use cases, most notably those involving huge data. While this is always the case, it should be understood that not all NoSQL databases are created alike where performance is concerned. This being the case, IT professionals works hard to ensure that the database they select is optimized for the success of their application use cases. Such selection can be made in-house, based on tests with academic database benchmarks. We present the Yahoo! Cloud Serving Benchmark (YCSB) framework, with the goal of facilitating performance comparisons of the new generation of NoSQL databases in an environment where resources are limited. Unlike many previous benchmarks that considered a cluster or distributed system that NoSQL is known for, we limit out experiment to a single PC assuming a cluster with a single node or a distributed system with a single PC. We define a core set of benchmarks and report results for four widely used systems: MongoDB, ElasticSearch, Redis, and OrientDB implementation.
ObjectivesNigeria reported an upsurge in cholera cases in October 2020, which then transitioned into a large, disseminated epidemic for most of 2021. This study aimed to describe the epidemiology, diagnostic performance of rapid diagnostic test (RDT) kits and the factors associated with mortality during the epidemic.DesignA retrospective analysis of national surveillance data.Setting33 of 37 states (including the Federal Capital Territory) in Nigeria.ParticipantsPersons who met cholera case definition (a person of any age with acute watery diarrhoea, with or without vomiting) between October 2020 and October 2021 within the Nigeria Centre for Disease Control surveillance data.Outcome measuresAttack rate (AR; per 100 000 persons), case fatality rate (CFR; %) and accuracy of RDT performance compared with culture using area under the receiver operating characteristic curve (AUROC). Additionally, individual factors associated with cholera deaths and hospitalisation were presented as adjusted OR with 95% CIs.ResultsOverall, 93 598 cholera cases and 3298 deaths (CFR: 3.5%) were reported across 33 of 37 states in Nigeria within the study period. The proportions of cholera cases were higher in men aged 5–14 years and women aged 25–44 years. The overall AR was 46.5 per 100 000 persons. The North-West region recorded the highest AR with 102 per 100 000. Older age, male gender, residency in the North-Central region and severe dehydration significantly increased the odds of cholera deaths. The cholera RDT had excellent diagnostic accuracy (AUROC=0.91; 95% CI 0.87 to 0.96).ConclusionsCholera remains a serious public health threat in Nigeria with a high mortality rate. Thus, we recommend making RDT kits more widely accessible for improved surveillance and prompt case management across the country.
This study examined the validity of the J-Curve Phenomenon and Marshall-Lerner Condition in the Nigerian context using data from 1982-2020. The Autoregressive Distributed Lag Bounds test method of cointegration was employed for the analysis of short-run and long-run effects of exchange rate uncertainty on the trade balance. The long-run result endorsed the validity of the Marshall-Lerner Condition in Nigeria. Thus, a depreciation of the Naira improves the trade balance in the long run. However, the results of the short-run dynamics revealed that there is no J-Curve phenomenon in Nigeria. The study recommends diversification of exports to improve the performance of Nigeria’s non-oil exports. In addition, fiscal, monetary and exchange rate policies should be properly harmonized to tackle trade deficits. Furthermore, there should be more investment in Research and Development in Nigeria to improve the value of goods exported and the competitiveness of its exports in the arena of international trade.
The university system is an organized anarchy. It is a system that brings different components from different dimensions with different focus sometimes conflicting one another in one place, in order to achieve a particular goal. This paper examines the university as a system that comprises different faculties, departments and units managing different disciplines and courses/subjects. Chaos and complexity nature of university was examined and results show that each faculty and department is taking a different direction without caring about others, and in the same faculty there are different departments handling different courses. And lecturers are using different methods in the conduct of their lessons and researches, and all these struggles are made towards achieving university objectives. The challenges faced by university system and possible solutions to overcome those challenges were discussed.
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