scholarly journals Unsupervised explainable AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

2021 ◽  
Author(s):  
Toshimichi Ikemura ◽  
Yuki Iwasaki ◽  
Kennosuke Wada ◽  
Yoshiko Wada ◽  
Takashi Abe
Keyword(s):  
Big Data ◽  
Human Genome ◽  
First Year ◽  
Trna Genes ◽  
Self Organizing Map ◽  
Genome Sequences ◽  
Closely Related Species ◽  
Explainable Ai ◽  
Massive Number ◽  
Almost All

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: unsupervised and explainable AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of the viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4~6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers appeared after the epidemic start could be connected to mutations. Because BLSOM is an explainable AI, BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explained BLSOMs for various topics. The tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explained BLSOMs for various eukaryotes, such as fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found evident enrichments in transcription factor-binding sequences (TFBSs) in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) were separated by the corresponding amino acid.

Transformative Learning in Mastery-Oriented CS0 Course

2021 ◽  
pp. 234763112110072
Author(s):  
Srinivasan Lakshminarayanan ◽  
N. J. Rao ◽  
G. K. Meghana
Keyword(s):  
Transformative Learning ◽  
First Year ◽  
Guided Discovery ◽  
Engineering Programs ◽  
Transformative Experiences ◽  
Significant Difference ◽  
Cognitive Levels ◽  
Almost All ◽  
Core Course

The introductory programming course, commonly known as CS1 and offered as a core course in the first year in all engineering programs in India, is unique because it can address higher cognitive levels, metacognition and some aspects of the affective domain. It can provide much needed transformative experiences to students coming from a system of school education that is dominantly performance-driven. Unfortunately, the CS1 course, as practiced in almost all engineering programs, is also performance-driven because of a variety of compulsions. This paper suggests that the inclusion of a course CS0 can bring about transformative learning that can potentially make a significant difference in the quality of learning in all subsequent engineering courses. The suggested instruction design of this course takes the advantage of the unique features of a course in programming. The proposed CS0 course uses “extreme apprenticeship” and “guided discovery” methods of instruction. The effectiveness of these instruction methods was established through the use of the thematic analysis, a well-known qualitative research method, and the associated coding of transformative learning experiences and instruction components.

scholarly journals Blockchain Disrupting Fintech and the Banking System

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 24
Author(s):  
Eduard Alexandru Stoica ◽  
Daria Maria Sitea
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Financial Institutions ◽  
New World ◽  
Great Part ◽  
Banking System ◽  
Daily Activities ◽  
Blockchain Technology ◽  
Almost All

Nowadays society is profoundly changed by technology, velocity and productivity. While individuals are not yet prepared for holographic connection with banks or financial institutions, other innovative technologies have been adopted. Lately, a new world has been launched, personalized and adapted to reality. It has emerged and started to govern almost all daily activities due to the five key elements that are foundations of the technology: machine to machine (M2M), internet of things (IoT), big data, machine learning and artificial intelligence (AI). Competitive innovations are now on the market, helping with the connection between investors and borrowers—notably crowdfunding and peer-to-peer lending. Blockchain technology is now enjoying great popularity. Thus, a great part of the focus of this research paper is on Elrond. The outcomes highlight the relevance of technology in digital finance.

scholarly journals Caterpillars of the marsh fritillary butterfly Euphydryas aurinia can extend their life-cycle in Scotland

2021 ◽  
Author(s):  
Neil O. M. Ravenscroft
Keyword(s):  
Life Cycle ◽  
Conservation Status ◽  
Northern Europe ◽  
First Year ◽  
Winter Mortality ◽  
Closely Related Species ◽  
Euphydryas Aurinia ◽  
High Conservation ◽  
The Uk ◽  
Marsh Fritillary

AbstractThe marsh fritillary Euphydryas aurinia is declining across Europe and is of high conservation interest. Its ecology has been defined and its conservation status assessed primarily from the affinities and populations of young caterpillars in the autumn, before hibernation and high winter mortality. The possibility that caterpillars of E. aurinia can overwinter more than once was investigated on the Isle of Islay, Scotland after caterpillars were found to occur at some locations in the spring despite a pre-hibernation absence. Closely-related species in North America and Northern Europe can prolong larval development by diapausing for a year as does E. aurinia in Scandinavia. Measurements of development and manipulations of distribution confirmed that some caterpillars do extend the life-cycle in Scotland and may occur in areas devoid of larvae in their first year. Caterpillars attempting this life-cycle develop slowly in spring, attain the normal penultimate spring instar and then enter diapause while other caterpillars are pupating. They moult just before diapause, construct highly cryptic webs and on emergence the following spring are 5–6 times heavier than larvae emerging in their first spring, or the equivalent of a month or so ahead. They attain a final, extra instar as larvae in their first spring reach the penultimate instar. Knowledge of this life-cycle is confined in the UK to Islay but its occurrence in this mild climate implies that it is more widespread.Implications for insect conservation Conditions that permit long diapause are probably precise and may not be reflected in recognised qualities of habitat. The species may also be present despite a perceived absence in autumn, the standard period for monitoring. Assessments of the prevalence of the life-cycle and its contribution to the persistence of E. aurinia are required. Populations of E. aurinia are known to fluctuate greatly and do occur below the observation threshold for long periods.

The Multiple Forms of Neurofibromatosis

1982 ◽  
Vol 3 (9) ◽  
pp. 293-298
Author(s):  
Vincent M. Riccardi
Keyword(s):  
First Year ◽  
Multiple Forms ◽  
Tay Sachs Disease ◽  
Marked Variability ◽  
Heritable Disorder ◽  
Basic Biology ◽  
Self Help Groups ◽  
Almost All ◽  
First Year Of Life ◽  
Huntington Chorea

Von Recklinghausen neurofibromatosis (NF)1 has multiple forms in several senses. First, there is the matter of heterogeneity: There is more than one disease designated by the term NF, for example "classical" NF as originally described by Von Recklinghausen2 and "acoustic" NF characterized by bilateral acoustic neunomas.3,4 Second, there is the matter of marked variability in the overall severity and progression of classical NF, the disorder to be considered in this review. NF can cause serious problems, and even death in the newborn period,5 or be associated with only a relatively mild or modest burden into the seventh decade and beyond. In almost all patients NF becomes obvious in the first year of life and some form of specific problems or compromise develops before age 20 years. NF is a heritable disorder, with a frequency of 1 in 3,000.6 This means it affects at least 80,000 Americans, making it much more common than is ordinarily supposed. Indeed, it is more common than Huntington chorea, Duchenne muscular dystrophy, and Tay-Sachs disease combined.4 However, in spite of its commonness,6-10 a realistic appreciation of NF's importance for pediatrics, and for medical care and research in general, is only a recent development. This long overdue change in emphasis reflects a recognition that NF's pathogenesis has bearing on a number of issues in basic biology, including neural crest embryology and genetic influences on the origin of cancer,1 the establishment of several NF clinical research programs, and the activities of several NF patient self-help groups.

Eat Smart! Ontario's Healthy Restaurant Program: A Survey of Participating Restaurant Operators

2003 ◽  
Vol 64 (4) ◽  
pp. 202-207 ◽  
Author(s):  
Lesley A. Macaskill ◽  
John J.M. Dwyer ◽  
Connie L. Uetrecht ◽  
Carol Dombrow
Keyword(s):  
Public Health ◽  
Program Implementation ◽  
Design Method ◽  
Mail Survey ◽  
Health Promotion Program ◽  
First Year ◽  
Communication Education ◽  
Family Style ◽  
Quick Service ◽  
Almost All

Eat Smart! Ontario's Healthy Restaurant Program is a standard provincial health promotion program. Public health units grant an award of excellence to restaurants that meet designated standards in nutrition, food safety, and non-smoking seating. The purpose of this study was to assess whether program objectives for participating restaurant operators were achieved during the first year of program implementation, and to obtain operators’ recommendations for improving the program. Dillman's tailored design method was used to design a mail survey and implement it among participating operators (n = 434). The design method, which consisted of four mail-outs, yielded a 74% response rate. Fifty percent of respondents operated family-style or quick-service restaurants, and 82% of respondents learned about the program from public health inspectors. Almost all respondents (98%) participated in the program mainly to have their establishments known as clean and healthy restaurants, 65% received and used either point-of-purchase table stands or postcards to promote the program, and 98% planned to continue participating. The respondents’ suggestions for improving the program were related to the award ceremony and program materials, media promotion, communication, education, and program standards. Program staff can use the findings to enhance the program.

scholarly journals Investigating Musicians’ Mindfulness through a Phenomenological Matrix

2019 ◽  
Author(s):  
Frank Diaz ◽  
Jason Silveira ◽  
Katherine Strand
Keyword(s):  
Music Education ◽  
Personal Growth ◽  
Cognitive Outcomes ◽  
First Year ◽  
First Year College ◽  
Introductory Course ◽  
The Matrix ◽  
College Music ◽  
Neurophysiological Mechanisms ◽  
Almost All

We investigated the efficacy of a phenomenological matrix of mindfulness as a framework for examining expectations, formal meditation experiences, and appraisals of first-year college music students (N = 18) who participated in a 5-day mindfulness module offered through an introductory course in music education. Participants expressed hopes that meditation would help them manage stress and anxiety, improve their focus and relationships, and support their personal growth and motivation. With respect to lived experiences of formal meditation, we found that without explicit prompting, approximately 86% percent of coded phrases reflected dimensions of experience that could be mapped within the matrix, suggesting its efficacy for coding. Furthermore, almost all participants attributed mindfulness to improving their general wellness, with dereification, breathing, and non-aversive affect frequently mentioned as key factors leading to these improvements. Additionally, consistent with the neurophenomenological aims of the matrix, we list cognitive outcomes and neurophysiological mechanisms potentially attributable to the nature of selected appraisal statements by participants.

Classification of Pests for Rice Crop Using Big Data Analytics

2019 ◽  
Vol 8 (3) ◽  
pp. 27-31
Author(s):  
R. P. L. Durgabai ◽  
P. Bhargavi ◽  
S. Jyothi
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Andhra Pradesh ◽  
Big Data Analytics ◽  
Rice Crop ◽  
Strategic Decisions ◽  
High Productivity ◽  
Almost All ◽  
Big Data Technology

Data, in today’s world, is essential. The Big Data technology is rising to examine the data to make fast insight and strategic decisions. Big data refers to the facility to assemble and examine the vast amounts of data that is being generated by different departments working directly or indirectly involved in agriculture. Due to lack of resources the pest analysis of rice crop is in poor condition which effects the production. In Andhra Pradesh rice is cultivated in almost all the districts. The goal is to provide better solutions for finding pest attack conditions in all districts using Big Data Analytics and to make better decisions on high productivity of rice crop in Andhra Pradesh.

Forecasting the Trends in Cloud Computing and its Impact on Future IT Business

2015 ◽  
pp. 2354-2372
Author(s):  
Ebin Deni Raj ◽  
L. D. Dhinesh Babu ◽  
Ezendu Ariwa ◽  
M. Nirmala ◽  
P. Venkata Krishna
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Business Processes ◽  
Big Data Analytics ◽  
Literature Survey ◽  
Mobile Cloud ◽  
Business Impact ◽  
Current Trends ◽  
To Come ◽  
Almost All

Cloud computing has become the cutting-edge technology for information technology processing and high-end computational tasks. Cloud has started playing its part in almost all business processes. Big data in cloud has become the buzzword. The business impact of cloud has deepened with the growth of big data analytics. Current trends such as green cloud computing, mobile cloud computing, and big data have created social as well as business impact. In this chapter, the authors analyze the field of cloud computing and perform an intense literature survey augmented with mathematical analysis. The forecast on the future of cloud and analysis of the current trends shows that cloud computing is a promising technology that will evolve further in years to come.

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