Appraisal of Groundwater Quality in Ado-Ekiti Metropolitan Area, Nigeria

This study examined the groundwater quality in Ado-Ekiti, Ekiti State, Nigeria. Water samples were randomly collected from ten hand-dug wells (HDW) covering the entire Ado-Ekiti metropolis. The water samples collected using standard method was promptly taken to water laboratory at the Federal Polytechnic Ado-Ekiti for analysis. Physical, chemical and bacteriological tests were carried out. Most physical, chemical and bacteriological parameters analysed were found to be at disparity with both Nigerian and World Health Organization (WHO) standard for drinking water quality. The ground water pollution may not be unconnected with poor and improper waste disposal. In order to guide against cholera and other water borne diseases, public enlightenment on proper waste management is require to be carried out. It is recommended that samples of well water use for drinking and other domestic chores should be taken to laboratory chemical and bacteriological tests once in six months

Survey of foreign assets and liabilities in Nigeria 2011 report

The 2011 survey of foreign assets and liabilities (SOFAL) of enterprises in Nigeria was conducted in June/July 2012 by the Statistics Department of the Central Bank of Nigeria (CBN) in conjunction with the Nigerian Export Processing Zone Authority, Nigerian Investment Promotion Commission and other collaborating agencies. The survey covered large establishments numbering 320 across the country. A total of 275 completed questionnaires were retrieved and analyzed indicating a response rate of 85.9 per cent. The survey instrument was designed to capture cross border transactions/investments of the respondents during 2010 and 2011. Available data from survey returns showed that total foreign claims on the Nigerian economy (liabilities) as at end 2011 rose to N12,729.69 billion from N11,681.32 billion recorded in 2010. A breakdown of the figures showed that 74.8 per cent came in the form of direct investment, while portfolio investment and other capital flows accounted for 10.3 and 14.9 per cent, respectively. The European Union countries accounted for 54.9 per cent of the total inflow, and are followed by other Africa countries with 15.8 per cent. A breakdown in terms of recipient sectors of inward capital flows to Nigeria revealed that the extractive industries sector ranked highest with 49.4 per cent and is followed by manufacturing, which received 29.1 per cent. Total stock of outward investment as at end 2011 was N2,377.03 billion as against N2,500.14 in 2010. In 2011, Outward direct investment dominated with 84.1 per cent of the total, while Africa countries were the preferred investment destination for Nigerian enterprises receiving 93.3 per cent of the total outflow mostly by the Nigeria's banking industry. The survey also indicated a decline in investment flow to the economic free zones around the country

Determination of the impact of strain rate on dynamic recrystallization of hot-deformed 2205 duplex stainless steel

2205 duplex stainless steel suffers poor hot workability, especially whe1981hot-deformed. This investigation aims to determine the strain rate’s effect on the material’s dynamic recrystallization after heat treatment. Secondly, to ascertain the critical strain at which the recrystallization occurs. The as-rolled material was subjected to heat treatment at 1340 °C for some time. After heat treatment, the yielded equiaxed austenite morphology was used for this investigation. Gleeble 1500™ thermo-mechanical was used as a simulant in uniaxial compression mode. The deformation temperature was set at 850 °C, with maximum strain at 0.8 and carried out at 0.001 s-1, 0.01 s-1, 0.1 s-1, 1 s-1, 5 s-1 strain rates. The microstructure of before and after heat-treatment was evaluated using a light microscope, while the critical factors (stress and strain) were determined through the stress-strain curve. It was observed that the lowest strain rate generated the maximum critical stress and critical strain at 191.99 MPa and 0.08283, respectively. However, at the highest strain rate, the maximum critical stress and critical strain experienced by the material were at 336.32 MPa and 0.17577. Overall, it was established that the applied stain rate influenced the critical strain and stress of the material. It can be concluded that dynamic recrystallization can occur at any strain rate, but the applied stress determines the extent of the phenomenon

Design, metallurgical characteristics, and mechanical performance

Funding Information: FMBF acknowledges the funding of CENIMAT/i3N by national funds through the FCT‐Fundação para a Ciência e a Tecnologia, I.P., within the scope of Multiannual Financing of R&D Units, reference UIDB/50025/2020‐2023. The authors ackowledge Fernanda Carvalho for running the differential scanning calorimetry tests on the endodontic files. Publisher Copyright: © 2023 The Authors. International Endodontic Journal published by John Wiley & Sons Ltd on behalf of British Endodontic Society.Aim: To compare two flat-side single-file rotary instruments with three single-file reciprocating systems through a multimethod assessment. Methodology: A total of 290 new NiTi single-file rotary (AF F One Blue 25/0.06 and Platinum V.EU 25/0.06) and reciprocating (One Files Blue R25, Reciproc Blue R25, Reciproc R25) instruments were selected, carefully examined for any major deformations, and evaluated regarding their macroscopic and microscopic design, nickel and titanium elements ratio, phase transformation temperatures, and mechanical performance (time/rotation to fracture, maximum torque, angle of rotation, microhardness, maximum bending, and buckling strengths). One-way anova post hoc Tukey, T-test, and nonparametric Mood's median tests were used for statistical comparisons (α = 5%). Results: Tested instruments had identical blade counts and near-identical helical angles of approximately 24° (rotary instruments) and 151° (reciprocating instruments). The flat-side analysis revealed a few inconsistencies, such as discontinuity segments, different orientations, and gaps in the homogeneity of the bluish colour. Microscopically, flat-side instruments exhibited blade discontinuity and an incomplete S-shaped cross-section. The surface finish was smoother for One Files Blue and more irregular for both rotary instruments. There were distinct phase transformation temperatures amongst all instruments. All heat-treated instruments were in R-phase arrangement, and Reciproc was in R-phase plus austenite at test temperature (20°C). Compared with the reciprocating instruments, both flat-side instruments exhibited lower results in the cyclic fatigue tests using two different clockwise kinematics, maximum torque, angle of rotation, and maximum buckling strength (p <.05). The rotary systems also exhibited low flexibility (p <.05). AF F One Blue had the lowest microhardness, whilst Reciproc had the highest value. Conclusion: This multimethod investigation revealed that the flat-side rotary instruments underperformed the reciprocating instruments regarding cyclic fatigue (with two different clockwise kinematics), maximum torque, angle of rotation, maximum buckling strength, and flexibility. Manufacturing inconsistencies were also observed in some of the flat-side instruments, including discontinuity segments, different orientations, and in the homogeneity of their bluish colour given by the heat treatment.publishersversionpublishe

Women’s Preferences for Maternal Healthcare Services in Bangladesh: Evidence from a Discrete Choice Experiment

Despite substantial improvements in several maternal health indicators, childbearing and birthing remain a dangerous experience for many women in Bangladesh. This study assessed the relative importance of maternal healthcare service characteristics to Bangladeshi women when choosing a health facility to deliver their babies. The study used a mixed-methods approach. Qualitative methods (expert interviews, focus group discussions) were initially employed to identify and develop the characteristics which most influence a women’s decision making when selecting a maternal health service facility. A discrete choice experiment (DCE) was then constructed to elicit women’s preferences. Women were shown choice scenarios representing hypothetical health facilities with nine attributes outlined. The women were then asked to rank the attributes they considered most important in the delivery of their future babies. A Hierarchical Bayes method was used to measure mean utility parameters. A total of 601 women completed the DCE survey. The model demonstrated significant predictive strength for actual facility choice for maternal health services. The most important attributes were the following: consistent access to a female doctor, the availability of branded drugs, respectful provider attitudes, a continuum of maternal healthcare including the availability of a c-section delivery and lower waiting times. Attended maternal healthcare utilisation rates are low despite the access to primary healthcare facilities. Further implementation of quality improvements in maternal healthcare facilities should be prioritised

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

The BLOOM model is a large publicly available multilingual language model, but its pretraining was limited to 46 languages. To extend the benefits of BLOOM to other languages without incurring prohibitively large costs, it is desirable to adapt BLOOM to new languages not seen during pretraining. In this work, we apply existing language adaptation strategies to BLOOM and benchmark its zero-shot prompting performance on eight new languages in a resource-constrained setting. We find language adaptation to be effective at improving zero-shot performance in new languages. Surprisingly, we find that adapter-based finetuning is more effective than continued pretraining for large models. In addition, we discover that prompting performance is not significantly affected by language specifics, such as the writing system. It is primarily determined by the size of the language adaptation data. We also add new languages to BLOOMZ, which is a multitask finetuned version of BLOOM capable of following task instructions zero-shot. We find including a new language in the multitask fine-tuning mixture to be the most effective method to teach BLOOMZ a new language. We conclude that with sufficient training data language adaptation can generalize well to diverse languages. Our code is available at https://github.com/bigscience-workshop/multilingual-modeling

Build_Eco, Planet Care in Play: Educational Toys

One of the biggest global challenges is the ability to separate the level of materials consumed from the growth of the economy. Consequently economic growth is linked to increased waste generated across the planet. Waste management warrants the attention of passionate and co-creative design by people from different levels of living standards. With rural residents seeking the better lifestyle of their urban counterpart’s, the United Nations estimates that 80% of South Africa’s population will be urbanised by 2050. Poverty in apartheid era townships, inner cities and informal settlements is visibly growing an existing divide between poorer communities and households that generate the bulk of waste in South Africa. The measurement of waste management performance is an important first step as highlighted South Africa’s state of waste report (first draft) 2018. Forty two million tons of waste is produced annually and only 11% is recycled This quote summarises the challenge: “... Narrow the gaps. Bridge the divides. Rebuild trust by bringing people together around common goals. Unity is our path. Our future depends on it,” Antonio Guterres, Secretary-General of the United Nations. Build-Eco, a social-entrepreneurial business dedicated to creating educational toys from waste materials. The driving goal is to implement a global opportunity in response to a global problem. With plastic packaging responsible for 40% of plastic waste, it has a serious impact on environmental health and safety across eco-systems. With minimal capital outlay Clean-Ups is a product that provides a bridge between lifestyles across communities. A home industry well suited to individuals seeking self employment opportunities where they can use their hands and don’t have to incur expensive equipment and machinery costs. Ideal for youth, women, immigrants and other marginalised members of communities. With cleaning materials, glue, nontoxic paints, plastic household waste and plastic medication like containers; a business is possible. A key risk is the “quality” locus of control and people skills of each person joining the industry hub. The overall business is scalable and whilst theoretical viable, should be tested through a small scale pilot. The target market is more affluent members of society including young parents, grandparents and business care givers of children that actively invest in useful, educational toys. These care givers want to give children access to classic proven toys, which contribute to caring for the planet

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License