A simplified predictive framework for cost evaluation to fault assessment using machine learning

Software engineering is an integral part of any software development scheme which frequently encounters bugs, errors, and faults. Predictive evaluation of software fault contributes towards mitigating this challenge to a large extent; however, there is no benchmarked framework being reported in this case yet. Therefore, this paper introduces a computational framework of the cost evaluation method to facilitate a better form of predictive assessment of software faults. Based on lines of code, the proposed scheme deploys adopts a machine-learning approach to address the perform predictive analysis of faults. The proposed scheme presents an analytical framework of the correlation-based cost model integrated with multiple standards machine learning (ML) models, e.g., linear regression, support vector regression, and artificial neural networks (ANN). These learning models are executed and trained to predict software faults with higher accuracy. The study considers assessing the outcomes based on error-based performance metrics in detail to determine how well each learning model performs and how accurate it is at learning. It also looked at the factors contributing to the training loss of neural networks. The validation result demonstrates that, compared to logistic regression and support vector regression, neural network achieves a significantly lower error score for software fault prediction

SOIL HEALTH STATUS OF SELECT VILLAGE OF DISTRICT SONIPAT, HARYANA AND WAY FORWARD

Soil health and fertility are the basis for gaining sustainable profit through higher productivity by the farmers. Using optimal doses of fertilizers and cropping pattern as per the scientific recommendations is the first step towards sustainable farming. Soil organic carbon (SOC) is the most important component in maintaining soil quality because of its role in improving physical, chemical, and biological properties of the soil. Organic matter is an important source of nitrogen, phosphorus and sulfur. Soil Health card is a Government of India's scheme promoted by the Department of Agriculture & Co-operation under the Ministry of Agriculture and Farmers' Welfare, apart from giving the health index of soil, will also indicate fertilizer recommendations and soil amendment required for the farm. Under Govt. of Haryana sanctioned Soil Health Card project, ARF carried out the fertility status study of 3000 acres of land of village Baroda Mor, block Mundlana, Tehsil Gohana, Sonipat, Haryana and distribute the cards well before the harvesting of Rabi crop with proper recommendation on dosage of appropriate fertilizer as per deficiency of essential nutrient parameter. View Article DOI: 10.47856/ijaast.2021.v08i6.00

Genome wide expression profiling of two accession of G. herbaceum L. in response to drought

<p>Abstract</p> <p>Background</p> <p>Genome-wide gene expression profiling and detailed physiological investigation were used for understanding the molecular mechanism and physiological response of <it>Gossypium herbaceum</it>, which governs the adaptability of plants in drought conditions. Recently, microarray-based gene expression analysis is commonly used to decipher genes and genetic networks controlling the traits of interest. However, the results of such an analysis are often plagued due to a limited number of genes (probe sets) on microarrays. On the other hand, pyrosequencing of a transcriptome has the potential to detect rare as well as a large number of transcripts in the samples quantitatively. We used Affymetrix microarray as well as Roche's GS-FLX transcriptome sequencing for a comparative analysis of cotton transcriptome in leaf tissues under drought conditions.</p> <p>Results</p> <p>Fourteen accessions of <it>Gossypium herbaceum </it>were subjected to mannitol stress for preliminary screening; two accessions, namely Vagad and RAHS-14, were selected as being the most tolerant and most sensitive to osmotic stress, respectively. Affymetrix cotton arrays containing 24,045 probe sets and Roche's GS-FLX transcriptome sequencing of leaf tissue were used to analyze the gene expression profiling of Vagad and RAHS-14 under drought conditions. The analysis of physiological measurements and gene expression profiling showed that Vagad has the inherent ability to sense drought at a much earlier stage and to respond to it in a much more efficient manner than does RAHS-14. Gene Ontology (GO) studies showed that the phenyl propanoid pathway, pigment biosynthesis, polyketide biosynthesis, and other secondary metabolite pathways were enriched in Vagad under control and drought conditions as compared with RAHS-14. Similarly, GO analysis of transcriptome sequencing showed that the GO terms <it>responses to various abiotic stresses </it>were significantly higher in Vagad. Among the classes of transcription factors (TFs) uniquely expressed in both accessions, RAHS-14 showed the expression of ERF and WRKY families. The unique expression of ERFs in response to drought conditions reveals that RAHS-14 responds to drought by inducing senescence. This was further supported by transcriptome analysis which revealed that RAHS-14 responds to drought by inducing many transcripts related to senescence and cell death.</p> <p>Conclusion</p> <p>The comparative genome-wide gene expression profiling study of two accessions of <it>G.herbaceum </it>under drought stress deciphers the differential patterns of gene expression, including TFs and physiologically relevant processes. Our results indicate that drought tolerance observed in Vagad is not because of a single molecular reason but is rather due to several unique mechanisms which Vagad has developed as an adaptation strategy.</p

Tc-99m-tamoxifen: A novel diagnostic imaging agent for estrogen receptor-expressing breast cancer patients

PURPOSEThe aim of the study was to radiolabel, characterize, and perform in vitro and in vivo assessment of Technetium-99m (Tc-99m) tamoxifen for screening ER expressing lesions in breast cancer patients.METHODSIn this study, tamoxifen has been radiolabeled with Tc-99m via Tc-99m-tricarbonyl core. The characterization and quality control tests of Tc-99m-tamoxifen were performed. In vitro recep- tor binding and blocking studies were performed in both positive control (MCF-7) and negative control cell lines (MDA-MB-231). Normal biodistribution studies were performed in female Wistar albino rats. The pilot clinical studies were performed in 4 ER-expressing breast cancer patients. Of the 4 patients, 1 was on tamoxifen therapy. All 4 patients had also undergone Fluorine-18 fluorodeoxyglucose (F-18-FDG) positron emission tomography/computed tomography.RESULTSTamoxifen was radiolabeled with Tc-99m via Tc-99m-tricarbonyl core with more than 95% radio- chemical yield. Mass spectra showed a peak corresponding to the molecular weight of Tc-99m- tricarbonyl and Tc-99m-tamoxifen. The site of binding of Tc-99m-tricarbonyl with tamoxifen was determined by proton nuclear magnetic resonance. The Tc-99m-tamoxifen showed 30% binding with MCF-7 and only 1%-2% receptor binding with MDA-MB-231 cell lines. Also, the percentage of receptor binding was drastically reduced (up to 72%) when ER was saturated with 50 times the excess molar ratio of unlabeled tamoxifen. In a pilot patient study, Tc-99m-tamoxifen uptake was observed in primary and metastatic lesions. However, no uptake was observed in a patient who was on tamoxifen therapy. The uptake of F-18-FDG was noted in all the patients.CONCLUSIONTamoxifen was radiolabeled with an in-house-synthesized Tc-99m-tricarbonyl core. The radio- labeled complex has been characterized and evaluated for receptor specificity in in vitro and in vivo studies. Also, this is the first clinical study using Tc-99m-tamoxifen for imaging ER. More patients need to be evaluated to further explore the role of Tc-99m-tamoxifen in ER-expressing lesions

Earthworm Grazed-Trichoderma harzianum Biofortified Spent Mushroom Substrates Modulate Accumulation of Natural Antioxidants and Bio-Fortification of Mineral Nutrients in Tomato

The present investigation was aimed at evaluating the impact of earthworm grazed and Trichoderma harzianum biofortified spent mushroom substrate (SMS) on natural antioxidant and nutritional properties of tomato. Results of the investigation reveal that earthworm grazing and T. harzianum bio-fortification led to significant improvement in the physico-chemical properties of fresh SMS and its application increased the accumulation of natural antioxidants and mineral content in tomato as compared to either T. harzianum biofortified SMS or fresh SMS. In particular, the earthworm grazed, T. harzianum biofortified SMS (EGTHB-SMS) was found to inhibit lipid peroxidation and protein oxidation with significant increase in total polyphenol and flavonoid content in tomato. Further, it increased Fe2+/Fe3+ chelating activity, superoxide anion radical scavenging activity compared to other treatments. The results thus suggest an augmented elicitation of natural antioxidant properties in tomato treated with EGTHB-SMS, resulting in a higher radical scavenging activity, that is highly desirable for human health. In addition, the use of SMS to enhance the nutritional value of tomato fruits becomes an environment friendly approach in sustainable crop production

Effect of remote ischaemic conditioning on clinical outcomes in patients with acute myocardial infarction (CONDI-2/ERIC-PPCI): a single-blind randomised controlled trial.

BACKGROUND: Remote ischaemic conditioning with transient ischaemia and reperfusion applied to the arm has been shown to reduce myocardial infarct size in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). We investigated whether remote ischaemic conditioning could reduce the incidence of cardiac death and hospitalisation for heart failure at 12 months. METHODS: We did an international investigator-initiated, prospective, single-blind, randomised controlled trial (CONDI-2/ERIC-PPCI) at 33 centres across the UK, Denmark, Spain, and Serbia. Patients (age >18 years) with suspected STEMI and who were eligible for PPCI were randomly allocated (1:1, stratified by centre with a permuted block method) to receive standard treatment (including a sham simulated remote ischaemic conditioning intervention at UK sites only) or remote ischaemic conditioning treatment (intermittent ischaemia and reperfusion applied to the arm through four cycles of 5-min inflation and 5-min deflation of an automated cuff device) before PPCI. Investigators responsible for data collection and outcome assessment were masked to treatment allocation. The primary combined endpoint was cardiac death or hospitalisation for heart failure at 12 months in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02342522) and is completed. FINDINGS: Between Nov 6, 2013, and March 31, 2018, 5401 patients were randomly allocated to either the control group (n=2701) or the remote ischaemic conditioning group (n=2700). After exclusion of patients upon hospital arrival or loss to follow-up, 2569 patients in the control group and 2546 in the intervention group were included in the intention-to-treat analysis. At 12 months post-PPCI, the Kaplan-Meier-estimated frequencies of cardiac death or hospitalisation for heart failure (the primary endpoint) were 220 (8·6%) patients in the control group and 239 (9·4%) in the remote ischaemic conditioning group (hazard ratio 1·10 [95% CI 0·91-1·32], p=0·32 for intervention versus control). No important unexpected adverse events or side effects of remote ischaemic conditioning were observed. INTERPRETATION: Remote ischaemic conditioning does not improve clinical outcomes (cardiac death or hospitalisation for heart failure) at 12 months in patients with STEMI undergoing PPCI. FUNDING: British Heart Foundation, University College London Hospitals/University College London Biomedical Research Centre, Danish Innovation Foundation, Novo Nordisk Foundation, TrygFonden

Insights of effectivity analysis of learning-based approaches towards software defect prediction

Software defect prediction is one of the essential sets of operation towards mitigating issues of risk management in software development known to contribute towards enhancing the quality of software. There is evolution of various methodologies towards resolving this issue while learning-based methodology is witnessed to be the most dominant contributor. The problem identified is that there are yet many unsolved queries associated with practical viability of such learning-based approach adoption in software quality management. Proposed approaches discussed in this paper contributes towards mitigating this challenge by introducing a simplified, compact, and crisp analysis of effectiveness associated with learning-based schemes. The paper presents its major findings of effectivity analysis of machine learning, deep learning, hybrid, and other miscellaneous approaches deployed for fault prediction followed by highlighting research trend. The major findings infer that feature selection, data imbalance, interpretability, and in adequate involvement of context are prime gaps in existing methods. The paper also contributes towards research gap as well as essential learning outcomes of present review work

Measurement of atmospheric aerosols during monsoon and winter seasons at Roorkee, India

208-217 Measurement of aerosol concentration has been carried out in view of some meteorological parameters like wind speed, temperature, relative humidity and rainfall during south-east (SE) monsoon (June-September 2006) and winter (November 2006-February 2007) at Roorkee, India. The measurements were done with the help of laser beam scatterometer for wide range of aerosols (0.05-3.0 μm). The present study reveals the fact that the number density of aerosols is very much affected by meteorological parameters. The aerosol concentration was minimum in August, September and November 2006 and remained around maximum during June-July 2006 and January-February 2007. During monsoon period, the rain plays important role in characterizing aerosol density. The aerosol concentration and size were found to be decreased during September 2006 although relative humidity was found to be very high due to scavenging of aerosol particles.</smarttagtype

Computational analysis of miRNA-target community network reveals cross talk among different metabolisms

To date, only a few conserved miRNAs have been predicted in hexaploid (AABBDD) bread wheat and till now community behavior among miRNA is still in dark. Analysis of publically available 1287279 ESTs from NCBI resulted 262 putative pre-miRNAs and 39 novel mature miRNAs. A total 22,468 targets were identified on 21 chromosomes. MiRNA target community was identified for genomes with different levels of cross talks. Gene ontology of these community targets suggests their differential involvement in different metabolisms along with common and stringent involvement in nitrogen metabolism

Not Available

Not AvailableTo date, only a few conserved miRNAs have been predicted in hexaploid (AABBDD) bread wheat and till now community behavior among miRNA is still in dark. Analysis of publically available 1287279 ESTs from NCBI resulted 262 putative pre-miRNAs and 39 novel mature miRNAs. A total 22,468 targets were identified on 21 chromosomes. MiRNA target community was identified for genomes with different levels of cross talks. Gene ontology of these community targets suggests their differential involvement in different metabolisms along with common and stringent involvement in nitrogen metabolismNot Availabl