70 research outputs found
Machine learning practices in accounting and auditing
No full textJournal articleIn the current technological era, Machine Learning applications are becoming popular every day. This research paper provides information about the effectiveness of the ML technique in accounting as well as the auditing process. To get proper results, different ML libraries are utilized, concluding seaborn, matplotlib, NumPy and so on. In the introduction section, the research purpose and this research objectives have been developed, through which the entire research process will be developed. “Logistic Regression Machine Learning Model” is built. Literary sources have been analysed in the literature review section, through which it can be easy to gain different perceptions based on the research context. The effectiveness of different types of machine learning algorithms in accounting and auditing has been evaluated properly. To develop a knowledge level, it is important to increase proper attention, and this research paper will provide proper information based on ML effectiveness.Computing and Information TechnologyHolmesglenVictorian Institute of Technology (VIT)Navsari Agricultural Universit
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Correction to: Predictors of patency for arteriovenous fistulae and grafts in pediatric hemodialysis patients.
No full textThe original version of this article unfortunately contained a mistake. The name of Vimal Chadha was presented incorrectly. The corrected author list is given above
A screening strategy to identify novel immunomodulators
No full textUnderstanding the immunomodulatory activities of compounds is important to identify the unintended adverse immunomodulatory effects of therapeutic compounds in development and to select novel compounds that may provide benefit for those diagnosed with immunemediated disorders. In both these cases, it is desirable to identify compounds with immunomodulatory activity early in the drug discovery process in a medium-throughput format. A screening strategy has been designed to fulfil these needs.
The first step in designing the strategy was to select informative assays and optimise individual assays to suit medium-throughput drug discovery. These individual assays investigated effects on a broad range of functions associated with innate and adaptive immune cells including macrophages (activation, cytokine production, phagocytosis and motility), helper T cells (activation and cytokine production), cytotoxic T cells (degranulation and cytokine production), and B cells (antibody production and cytokine production). Cost effectiveness and ease-of-use were important considerations during assay design and optimisation.
Using a compound set comprised of positive controls (i.e. compounds known to alter specific immune functions), a data set was generated to guide the strategy design. Assays were ordered to efficiently use resources and reduce the generation of less informative data. Additionally, using data collected from this compound set, strategies to assess and identify immunomodulatory activity were built and analysed. A second set of compounds was used to validate the screening strategy, and this screen highlighted new and novel activities for these known compounds that suggests they possess additional immunomodulatory effects.
Once validated, several novel compounds were run through the screen, including a traditional Samoan medicine, a heparan sulfate mimetic, and a novel anti-cancer agent; unique immunomodulatory activities were discovered. Finally, a hierarchical cluster analysis was used to cluster compounds sharing similar activity profiles and suggested the potential to develop further statistical methods to provide insight into compound characterisation. Together, this research has developed and validated a novel, medium throughput drug discovery system that can facilitate the identification of the immunomodulatory activities of compounds in the drug discovery environment
Use of Appropriate Loss Function in Rainfall Prediction using Deep Learning
No full textIndia is an agricultural country, and rainfall is the main source of irrigation for agriculture. Prediction of rainfall is very crucial for farmers to make decisions. In this research paper, the prediction model has been developed through deep learning using historical data of 10 years of rainfall. A deep learning approach used Keras API with an artificial neural network technique to predict the daily rainfall. The prediction model has been assessed by four-loss function, i.e., MSE, MAE, Hinge, and Binary Cross-Entropy
An Android Application for Farmers to Disseminate Horticulture Information
No full textToday’s the mobile phone is used worldwide. As the price of smart phone is decreasing, its popularity is increasing day by day. Moreover, android is the mobile operating system used in smart phone, most of its applications are freely available. The use of smart phone is increase in every sector of business, education, etc. So in this research paper, using the concept of Horticulture and Android introduces a “Farmer Helping Service ” system that will provide the detail information of fruits, vegetables and flowers in audio format to the farmers. This system can provide information using android smart phone from anywhere and anytime without using internet and at free of cost. It is very useful to Gujarat Farmer because they will get information in Gujarati Language just by typing number from the mobile keypad. An illiterate person can also easily operate the system
Incentive policies and agricultural performance in sub-Saharan Africa
No full textExports in general, and agricultural exports in particular, are more responsive to price incentives in Sub-Saharan Africa than in developing countries.. These are the results of an econometric investigation on the effects of real exchange rates on exports. It further appears that in Sub-Saharan Africa the impact of real exchange rates is greater on agricultural exports than on the exports of goods and services. Within Sub-Saharan Africa, market-oriented countries generally gained export market shares while interventionist countries lost shares. This occurred when market-oriented, not interventionist countries, maintained realistic exchange rates and did not bias incentives against exports. For example, Kenya and the Ivory Coast exemplify market-oriented, and Tanzania and Ghana interventionist, countries. Pairwise comparisons between the Ivory Coast and Ghana have indicated the superiority of the market-oriented approach in promoting exports and agricultural production.Economic Theory&Research,TF054105-DONOR FUNDED OPERATION ADMINISTRATION FEE INCOME AND EXPENSE ACCOUNT,Export Competitiveness,Environmental Economics&Policies,Access to Markets
A statistical approach for the production of thermostable and alklophilic alpha-amylase from Bacillus amyloliquefaciens KCP2 under solid-state fermentation
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Telomere Length and Distribution in Three Developmental Stages
No full textTelomeres are specialised nucleoprotein structures present at the ends of each chromatid that function to maintain genome stability. It is well established that a gradual decline in telomere length is associated with the process of cellular ageing, and thereby to the pathobiology of age-related diseases. In addition, the localisation of the telomere at the nuclear periphery plays an important role in the spatio-temporal organisation of the genome and in ensuring faithful segregation of chromosomes during meiosis. The aims of this thesis were to investigate telomere localisation in the nucleus, and telomere length in three hitherto early stages of development, gametogenesis, preimplantation embryogenesis and the neonatal period. Specifically:
1. To test the hypothesis that telomeres localised at the nuclear periphery in sperm cells and that this organisation was altered in sub-fertile men
2. To optimise a means of assessing average telomere length using DNA from small sample sizes and using whole genome amplified DNA from single cells
3. To investigate the role of telomere length in reproductive ageing and aneuploidy generation in women by testing the hypothesis that telomere length is significantly shorter in the first polar bodies and cleavage stage embryos of older women
4. To test the hypothesis that “preterm at term” babies (i.e. premature babies assessed at the time of their due date) displayed genetic signs of premature ageing (as manifested by significantly shorter telomeres than their term born counterparts) alongside the already established clinical signs (characterised by hypertension, diabetes and altered body fat distribution)
Results confirmed the peripheral distribution of telomeres in the sperm heads of normally fertile males (using both 2D and 3D imaging) plus the novel finding that telomere distribution patterns are altered in the sperm heads of infertile males. Secondly, a reliable means of measuring telomere length was optimised in order to assess average telomere length using DNA from small sample volumes (down to single cells). Using this technology, average telomere length analysis in polar bodies and embryos found no evidence to support the hypothesis that telomere length is associated with either advanced maternal age or aneuploidy generation. Similarly, results suggest that telomere length is not significantly shorter in “preterm at term” infants compared to term born controls, thus providing no evidence that telomere attrition is involved in the pathobiology of the ‘aged phenotype’ observed in preterm infants. Taken together, results from this thesis provide some novel insights into the function of these highly important features of the genome, but also highlight that a great deal remains to be uncovered in the complex molecular mechanisms that contribute to the regulation of telomere length and nuclear distribution
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