Search

Bangladesh Open University (BOU), the sole distributor of distance education (DE) in Bangladesh, is regarded as one of the mega universities in the world. Nonetheless, the institution faces numerous issues and challenges that revolve around not only its administrative and academic operations, but also the lack of acknowledgement of its sociological value and concomitant recognition within the local community. This study examines the perceived challenges facing DE provision in Bangladesh from the point of view of the local Bangladeshi community as well as senior academics and administrators within the institution. Qualitative case study formed the methodological basis of the study. Using purposeful non-random sampling supplemented with snowballing technique, five senior academics and directors from BOU were selected for individual semi-structured interviews. Four focus groups were also formed using stratified purposeful sampling to determine the perception of the community towards DE. The paper introduces an innovative theoretical model, "Adapting Structuration Theory In Distance Education (ASTIDE)", conceptualised as part of a broader study, to address the underlying issues and challenges relating to the future provision of DE in Bangladesh.

Distance Education (DE) theorists have argued about the requirement for a theory to be comprehensive in a way that can explicate many of the activities associated with DE. Currently, Transactional Distance Theory (TDT) (Moore, 1993) and the Theory of Instructional Dialogue (IDT) (Caspi & Gorsky, 2006) are the most prominent theories, yet they still do not represent a unified and comprehensive theory for DE. This paper provides a review of the existing literature on DE theories and identifies potential gaps in theorising distance education. Building on Giddens' (1984) work, an innovative approach to theorising DE is proposed through the conceptualisation of the "Adapting Structuration Theory In Distance Education" (ASTIDE) model as a means to explicate DE operations and practices at the institutional and national/international level. It also presents evidence, from a larger study, of the necessity of a comprehensive model such as the ASTIDE constructed through an investigation into the DE systems of developing and developed countries.

Background: Rearranged during transfection (RET), an oncogenic protein, is associated with various cancers, including non-small-cell lung cancer (NSCLC), papillary thyroid cancer (PTC), pancreatic cancer, medullary thyroid cancer (MTC), breast cancer, and colorectal cancer. Dysregulation of RET contributes to cancer development, highlighting the importance of identifying lead compounds targeting this protein due to its pivotal role in cancer progression. Therefore, this study aims to discover effective lead compounds targeting RET across different cancer types and evaluate their potential to inhibit cancer progression. Methods: This study used a range of computational techniques, including Phase database creation, high-throughput virtual screening (HTVS), molecular docking, molecular mechanics with generalized Born surface area (MM-GBSA) solvation, assessment of pharmacokinetic (PK) properties, and molecular dynamics (MD) simulations, to identify potential lead compounds targeting RET. Results: Initially, a high-throughput virtual screening of the ZINC database identified 2,550 compounds from a pool of 170,269. Subsequent molecular docking studies revealed 10 compounds with promising negative binding scores ranging from -8.458 to -7.791 kcal/mol. MM-GBSA analysis further confirmed the potential of four compounds to exhibit negative binding scores. MD simulations demonstrated the stability of CID 95842900, CID 137030374, CID 124958150, and CID 110126793 with the target receptors. Conclusion: These findings suggest that these selected four compounds have the potential to inhibit phosphorylated RET (pRET) tyrosine kinase activity and may represent promising candidates for the treatment of various cancers. [ABSTRACT FROM AUTHOR]

This article reports on part of a study conducted to collate the policies and practices of two successful distance education providers of the developed world with those of a provider in Bangladesh in order to inform a culturally appropriate distance education framework for a developing country. This article also describes an innovative theoretical model, Adapting Structuration Theory In Distance Education, conceptualized as part of a broader study, to address the underlying issues and to generate propositions for the framework.

Dollar spot caused by Clarireedia spp. (formerly Sclerotinia homoeocarpa) is an economically destructive fungal disease of turfgrass that can significantly compromise turf quality, playability, and aesthetic value. Fungicides are frequently used to manage the disease but are costly and potentially unfavorable to the environment. Repeated use of some active ingredients has resulted in reduced efficacy on C. jacksonii causing dollar spot in cool-season turfgrasses in the US. Experiments were conducted to study fungicide sensitivity of Clarireedia spp. as well as to develop alternatives to fungicides against dollar spot on warm-season turfgrass in Georgia. First, 79 isolates of Clarireedia spp. collected across the state were tested on fungicide-amended agar plates for their sensitivity to thiophanate-methyl (benzimidazole) and propiconazole (dimethyl inhibitor). Seventy-seven isolates (97.5%) were sensitive (0.001 to 0.654 mg/mL) and two isolates (2.5%) were found resistant (>1000 mg/mL) to thiophanate-methyl. However, in the case of propiconazole, 27 isolates (34.2%) were sensitive (0.005 to 0.098 mg/mL) while 52 isolates (65.8%) were resistant (0.101 to 3.820 mg/mL). Next, the efficacy of three bio- and six synthetic fungicides and ten different combinations were tested in vitro against C. monteithiana. Seven bio- and synthetic fungicide spray programs comprising Bacillus subtilis QST713 and propiconazole were further tested, either alone or in a tank mix in a reduced rate, on dollar spot infected bermudagrass 'TifTuf' in growth chamber and field environments. These fungicides were selected as they were found to significantly reduce pathogen growth up to 100% on in vitro assays. The most effective spray program in growth chamber assays was 100% B. subtilis QST713 in rotation with 75% B. subtilis QST713 + 25% propiconazole tank mix applied every 14 days. However, the stand-alone application of the biofungicide B. subtilis QST713 every seven days was an effective alternative and equally efficacious as propiconazole, suppressing dollar spot severity and AUDPC up to 75%, while resulting in acceptable turf quality (>7.0) in field experiments. Our study suggests that increased resistance of Clarireedia spp. to benzimidazoles and dimethyl inhibitors warrants continuous surveillance and that biofungicides hold promise to complement synthetic fungicides in an efficacious and environmentally friendly disease management program. [ABSTRACT FROM AUTHOR]

An artificial intelligence-based system was developed to efficiently predict settling velocity (SV) using a large dataset comprised of 2726 samples. The ranges of particle size and fluid viscosity were 0.212 − 98.59 mm and 0.02 − 92800 mPa.s, respectively. Properties of particle and fluid were fed to a model as the inputs to obtain SV as the output. Six machine learning algorithms were tested for the prediction. The random forest (RF) performed better than other algorithms with a coefficient of determination of 0.98 and a mean square error of 0.0027. A simple decision support system was developed using the RF model. The current study demonstrates the complete methodology of modeling SV with ML. [ABSTRACT FROM AUTHOR]