Counterfactual shock in energy commodities affects stock market dynamics : Evidence from the United States

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Textile industry in Nupeland

Man became conscious of whom he was when he took  sedimentary life. The consciousness led to the need to cover his body either from nakedness, to look beautiful or in response to the harsh weather; and to keep the body warm. This began with the use of leaves to animal skins then to the weaving and production of fabric for clothing. Though no one can said when clothing or textiles began in the world and in Nupeland in particular, no doubt it has a fair long history and has undergone changes overtime. It is in the light of this that using historical methodology of both  primary and secondary sources, the paper investigate textile industry in Nupeland. Using content analysis, the paper concluded that the industry in Nupeland had benefitted from the technology and skills of neighbouring communities before it became  synonymous with the Nupe. The industry has also declined due to modern production

How COVID‐19 pandemic may hamper sustainable economic development

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Compare the out-of-sample performance of mean-variance optimization relative to equally weighted or naîve 1/N portfolio

Masteroppgave i finansiering og investering - Nord universitet 202

COVID-19 pandemic and economic policy uncertainty regimes affect commodity market volatility

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Methanolic extract of Nauclea diderrichii (stem-bark) show anti-microbial, anti-oxidant and anti-inflammatory bioactivities

The aqueous stem-bark extract of the tropical plant Nauclea diderrichii is used in ethnomedicine to manage symptoms of rheumatism through minimally examined mechanisms. The objective of the study is to examine the scientific bases for the ethnomedicinal use of the plant for the management of rheumatism. As part of this effort to explain its ethnomedicinal efficacy, this study compared and contrasted the anti-microbial, anti-oxidant and anti-inflammatory activities of the methanolic extract with that of the diethylether extract. Broth dilution assay, DPPH radical scavenging assay and carrageenan-induced foot swelling of 7-day old chicks were utilized for the experimental assessment of the bioactivities of Nauclea diderrichii. Polar methanolic extract exhibited a higher antioxidant status in vitro as estimated quantitative differences in total phenolic content, in total antioxidant capacity and in DPPH and H2O2 radical scavenging converged to show the methanolic extract as a more potent anti-oxidant. The methanolic extract also possess better in vivo anti-inflammatory activity as demonstrated by the 1.5-fold lower ED50 relative to that of the diethylether. The methanolic extract demonstrated better broad-spectrum anti-microbial activity against a panel of six clinical isolates of bacterial and fungi pathogens in vitro. The relative strength of the bioactivities of the methanolic extract derives from a higher slew of phytochemical content that is a 3-fold difference larger. The results of this study support the beneficial effect of Nauclea diderrichii in its continuing ethnomedicinal use to target rheumatism chemotherapeutically

Trade volume affects bitcoin energy consumption and carbon footprint

The environmental sustainability of bitcoin is making waves in the empirical literature, yet, no study has thus far examined the financial determinants of bitcoin energy consumption and carbon footprint. Here, we use novel estimation methods comprising dynamic ARDL simulations and general-to-specific VAR to examine steady-state effects, cumulative impulse-response, and counterfactual shocks of bitcoin trade volume on bitcoin energy bitcoin carbon footprint to ensure genuine causal inferences. We observed an increase in bitcoin trade volume spur both carbon and energy footprint by 24% in the long-run, whereas a dynamic shock in trade volume escalates bitcoin energy and carbon footprint by 46.54%

Teachers' Perception on Influence of Social Adjustment on Academic Performance of Students with Mild Mental Retardation in Gombe State Special School

This study focused on determining the perception of teachers on influence of social adjustment on academic performance in West African Examinations Council/National Examinations Council (WAEC/NECO) of students with mild mental retardation in Gombe state, with emphasis on special secondary school. Descriptive survey design was adopted for the study. A total population of 37 teachers were used as respondents. Using drop and pick method, data was collected using adapted social adjustment (questionnaire) from Mei- Yin, Huei – Shyong & Cheng-Jung (2000) in Taiwan with 22 items. The instrument was reduced to 18 items. The instrument was validated by 2 experts and reliability was of 0.82 was obtained through Chronbach’s Alfa coefficient determination formula and the original reported reliability is 0.85. Data was analysed using descriptive (frequency, percentage, mean and SD) statistics. The study found that level of academic performance WAEC/NECO of mentally retarded students is moderate in Gombe state special school, while the level of social adjustment on academic performance WAEC/NECO of mentally retarded students was found to be high as perceived by the teachers. The study concludes that the teachers in Gombe state special school are heterogeneous and social adjustment has great influence on academic performance of mentally retarded students. The study recommends that government should make it a policy that, all mentally retarded persons between the ages of 5-7 are subjected to social adjustment programmes which will transit them into formal school system and parents of mentally retarded children should improve their closeness with their children and also build in hope of their rehabilitation

Binary logistic regression methods for modeling broncho-pneumonia status in infants from tertiary health institutions in north central Nigeria

Acute respiratory tract infections, predominantly bronchopneumonia, are one of the leading causes of infant deaths in developing countries and around the world. This work models the effects of the significant risk factors on infants’ bronchopneumonia status and also fits some reduced models and determines the best model with minimum number of parameters. The data for this study consist of a random sample of 433 births to women seen in the obstetrics clinic of two sampled tertiary health institutions in north-central Nigeria. These include University Teaching Hospital (UTH) Abuja, and Federal Medical Center (FMC) Keffi, Nasarawa State. Binary logistic regression was used to identify and model the effects of the various risk factors while stepwise regression technique was used to fit some reduced logistic regression models. Then the best fitting model with minimum number of parameters was identified using likelihood ratio statistic. It was observed that baby’s weight at birth, baby’s weight four weeks since birth, and mother’s occupation have significant effects on infant’s bronchopneumonia status. Additionally, among the four fitted reduced models, model4 is the best predictor of infants’ bronchopneumonia status, followed by model3 and then model2. Therefore, community service like home visiting for health education, supplementation of vitamin A, etc., would be an advantage if provided for teenaged pregnant women as it would, in turn, reduce incidence of low birth weight and thereby reduce bronchopneumonia infection among these children.Keywords: Bronchopneumonia, Multiple Logistic Regression Model, Fitness, likelihood ratio tes

Advancing COP26 climate goals : Leveraging energy innovation, governance readiness, and socio-economic factors for enhanced climate resilience and sustainability

Climate change adaptation and mitigation remain critical to achieving sustainable development while reducing climate vulnerability, particularly among climate-exposed and sensitive regions. Yet, achieving a balance between climate-resilience pathways, high economic productivity, high human development, and energy efficiency appears complex, leading to potential trade-offs. Here, we examine the overarching effect of the diversified energy portfolio, socio-economic drivers, and governance adaptation readiness on Climate change vulnerability across 212 economies. Contrary to the poor conventional panel techniques reported in the existing literature, we employ novel machine learning and dynamic panel estimation techniques that control for chaos, nonlinearity, mutual coupling, and heterogeneity in dynamic systems. The convergent cross-mapping causality technique reveals mutual coupling effects between energy portfolio, governance readiness, socio-economic drivers, and climate change vulnerability. The rapidly increasing population and increasing demand for resources under the business-as-usual society and economic structure that normalizes unsustainable development pathways due to weak governance structures create ineffective climate-resilient policies that lead to unabated emissions with consequences on climate change. The effect of social and governance readiness leads the transformation process to attain sustainable development. Thus, high social and governance readiness spurs climate resilience through climate change adaptation and mitigation to achieve sustainable development. Alternative (renewables) and nuclear energy have displacement effects on fossil fuels, yet, the magnitude of displacement is not large enough to replace future fossil fuel consumption. Conversely, a low-carbon future is still attainable by replacing the fossil energy portfolio with more natural gas and carbon-abatement technologies. Our study demonstrates that energy innovations are useful climate-resilience pathways that lessen climate change vulnerability.© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed