It is a challenging task for Bangladesh to meet its increasing demand of energy while its economy is rapidly growing. Though prices of oil, coal, and fossil fuels around the world have been volatile, the price trend in Bangladesh demonstrates a persistent rise in the immediate past. This is further exacerbated by depleting reserves of natural gas. Cumulatively, these two effects heighten Bangladesh's energy needs. Bangladesh presently mitigates her energy requirements predominantly through natural gas, supplemented by a handful of coal and furnace oil plants. Consequently, due to scarcity of natural gas, oil and coal resources, nuclear power surfaces as a palatable strategic option for Bangladesh's future development agenda. However, a successful nuclear power program entails an extensive infrastructure. Just like the other nuclear energy-producing countries, Bangladesh also face challenges to safeguard the health and security of nuclear reactors, the proper management for nuclear waste treatment and the security concerns over the safe usage of nuclear materials. Additionally, the development of nuclear energy is also bewildered because of the complex nature of fission technology, lack of efficient human resources, and non-existence of proper legal instruments to guide safe nuclear power production. Moreover, the further challenges include the questions, for example: whether the nuclear power plant project is supported by the mass people or not? What are the strategies for nuclear waste disposal? Whether the recent initiatives for nuclear energy production is necessary or the country should more concern with renewable sources? This paper evaluates the nuclear energy development in Bangladesh. It operates under qualitative methodological framework and utilises secondary sources for analysis. We advance several recommendations in this paper to remedy the highlighted issues: (1) creating a comprehensive legal and regulatory system; (2) fortifying home-based technology of nuclear development and simultaneously localising of foreign-based technology; (3) reducing the cost of nuclear energy production; (4) fast-tracking the procedure of efficient development of nuclear technology; (5) accelerating the procedure of switching to more

This study investigates the variables affecting the adoption of blockchain technology (BT) among small and medium-sized enterprises (SMEs) with the application of artificial intelligence (AI) via the mediating lens of risk-taking behavior. As an initial sample, 150 owners/top managers from 150 SMEs (one informant from each) in Dhaka, Bangladesh, were chosen. A stratified random sample was employed for this cross-sectional study. Applying structural equation modeling, the combined influence of internal and external variables influencing the intention to adopt BT is explored. Results show that: (1) knowledge of artificial intelligence has a positive and significant effect on the adoption of blockchain technology; (2) the relevant advantage of artificial intelligence has a positive and significant effect on the adoption of blockchain technology; (3) perceived ease of use of artificial intelligence has a positive and significant effect on the adoption of blockchain technology; (4) risk-taking behavior mediates the relationship between knowledge of artificial intelligence and adoption of blockchain technology; (5) risk-taking behavior does not mediate the relationship between relevant advantage and perceived ease of use of artificial intelligence with the adoption of blockchain technology. The current study is one of the few empirical investigations relating to SMEs using artificial intelligence and blockchain technologies for business operations. The study’s limitations are the small sample size and use of a single informant. However, the findings on the adoption of blockchain technology have applications for boosting the competitiveness of SMEs. This study’s originality stems from two factors: the novelty of blockchain technology and its potential to upend SMEs’ conventional mode of operation. It highlights the need to consider the key variables affecting SMEs’ adoption of blockchain technology with artificial intelligence.

Apparently, word clouds have grown as a clear and appealing illustration or visualization strategy in terms of text. Word clouds are used as a part of various settings as a way to give a diagram by cleansing text throughout those words that come up with most frequently. Generally, this is performed constantly as an unadulterated text outline. In any case, that there is a bigger capability to this basic yet intense visualization worldview in text analytics. In this work, we investigate the adequacy of word clouds for general text analysis errands and also analyze the tweets to find out the sentiment and also discuss the legal aspects of text mining. We used R software to pull twitter data which depends altogether on word cloud as a visualization technique and also with the help of positive and negative words to determine the user sentiment. We indicate how this approach can be viably used to explain text analysis tasks and assess it in a qualitative user research.

The present study was carried out to investigate the microbiological quality and antibiotic resistance patterns of pathogenic bacteria isolated from vegetable samples. A total of 14 vegetable samples, 7 from local and 7 from super shops, were randomly collected from different locations of Dhaka city. Concentrations of total heterotrophic bacteria, total coliform, faecal coliform, Pseudomonas spp., Listeria spp. and Staphylococcus aureus were enumerated from each sample by serial dilution and spread plate technique. Presence of Salmonella spp., Shigella spp. and Vibrio spp. were determined by enrichment and selective plating methods. Antibiotic sensitivity patterns of the isolated bacteria were determined using Imipenem (10 ?g), Ceftriaxone (30 ?g), Sulphamethoxazole (25 ?g), Ampicillin (10 ?g), Gentamicin (10 ?g), Aztreonam (30 ?g), Cefuroxime (30 ?g) and Oxacillin (5 ?g) antibiotic discs. The local market vegetables showed higher proportions of E. coli (4/7, 57.14%) but the super shop vegetables showed higher proportions of Pseudomonas spp. (5/7, 71.42%) and Listeria spp. (5/7, 71.42%). Pathogenic bacteria isolated form the super shops showed increased resistance against (5/8, 62.5%) antibiotics tested against the pathogenic bacteria. Contamination of vegetables by a range of pathogenic bacteria in local and super market vegetables is a serious threat to public health if they are consumed raw or unprocessed. Higher antibiotic resistance in pathogens isolated form supermarket vegetables needs to be investigated in order to monitor and control spread of infections with drug resistant bacteria. DOI: http://dx.doi.org/10.3329/sjm.v4i1.22755 Stamford Journal of Microbiology, Vol.4(1) 2014: 13-18

No abstract