LEMABE: a novel framework to improve analogy-based software cost estimation using learnable evolution model

One of the most important and critical factors in software projects is the proper cost estimation. This activity, which has to be done prior to the beginning of a project in the initial stage, always encounters several challenges and problems. However, due to the high significance and impact of the proper cost estimation, several approaches and methods have been proposed regarding how to perform cost estimation, in which the analogy-based approach is one of the most popular ones. In recent years, many attempts have been made to employ suitable techniques and methods in this approach in order to improve estimation accuracy. However, achieving improved estimation accuracy in these techniques is still an appropriate research topic. To improve software development cost estimation, the current study has investigated the effect of the LEM algorithm on optimization of features weighting and proposed a new method as well. In this research, the effectiveness of this algorithm has been examined on two datasets, Desharnais and Maxwell. Then, MMRE, PRED (0.25), and MdMRE criteria have been used to evaluate and compare the proposed method against other evolutionary algorithms. Employing the proposed method showed considerable improvement in estimating software cost estimation.

Baricitinib for Refractory Eosinophilic Fasciitis: Myth or Reality?

We read the recent article by Sehgal et al with great interest.1 The authors described a 37-year-old patient with eosinophilic fasciitis (EF) who showed no improvement after an initial aggressive treatment strategy (intravenous [IV] methylprednisolone, prednisone, methotrexate, mycophenolate mofetil, and IVIG). Subsequently, the use of the Janus kinase ( JAK) 1/2 inhibitor baricitinib resulted in considerable improvement in the patient's symptoms and skin appearance. However, there are some details that need further clarification.

Offshore Structure Specific Performance Targets

Offshore structures exist in the harshest environments and each region is unique in the severity and development of extreme weathers. This had led to challenges in the identification of a single criterion that's internationally applicable. ADNOC Offshore and Kent, formerly Atkins Oil and Gas, worked closely in 2010 to develop a high-level generalised regional criterion for the Arabian Gulf and in 2020, a major project was conducted to develop a structure-specific criterion that resulted in considerable improvement in risk levels and financial gains. For each of ADNOC Offshore's 480 structures, a Response Based Metocean Analysis (RBMA) was conducted adopting Tromans and Vanderschuren (1995) approach. Structure specific hindcast data at 3-hour intervals over a period of 37 years was analysed, isolating storms and executing hydrodynamic analyses considering joint environmental conditions. Through adopting a combination of peak-over-threshold method and Markov-Chain-Monte-Carlo (MCMC) simulations, convolution of long-term (storms) and short-term (wave probabilities within a storm) was conducted resulting in the generation of the Hazard Curves that account for the possible uncertainties associated with variations in each of the distributions. The structure specific response based metocean analysis resulted in a considerable improvement in the criteria for ADNOC Offshore’s structures. The resulting Hazard Curve ratios (10,000-year to 100-year response parameter ratio) for approximately 95% of the structures were evaluated lower as compared to the 2010 generalised study. It was observed that the water current profiles had a significant impact on the hazard ratios, and specially for assets in the vicinity of the islands. Based on the resulting hazard ratios a detailed risk assessment was conducted and compliance and life extension of most of ADNOC Offshore structures was justified without the need for physical strengthening of their assets. Through the use of machine-learning algorithms associated with serval statistical sampling techniques, extreme value analysis was conducted in conjunction with the MCMC approach and resulted in what is likely to be the largest offshore fleet application of the method.

Bio-Factor Inspired Contemporary Agriculture-Horticulture with Innovative Researches and Ecosystem Transformation for Healthy Life Plausible Governance

While developing countries focused their endeavors on development of livelihood and sustainable food security, developed countries diverted their attention towards development of feel good and wellness. It is found that lot of satisfactory progresses had been made in agriculture and horticulture and forestry land uses as per land capability classes. This scientific persuasion brought considerable improvement in situations and with development of knowledge many innovative developments and constraints also emerged. This study inspired by bio factors “feel good and wellness” brought contemporary transformations of forestry land use in to Forestry- Horticulture, least liable to damage by climatic aberrations. Control of the Governance of countries remains its fast adaptations. This researchers’ theme, “Food is Medicine”, recommended intake of suitable fruits and nuts as mini snack after around 3h of meal of any kind of food menus, to regulate acidity in human animal and fish bio systems. These fruits and nuts needs’ will get easily accomplished by the innovative transformation, “Forestry Horticulture”, which will support accomplish fulfillment of livelihood need and food securities in countries world over. With this transformation nutrient and water management in forestry sector will naturally get revamped for building still better vegetation cover, raising efficiency of fruits and nuts bearing through integrated fostering of wild as well as honey bee pollinators. The bio-factor feel good and wellness will get accomplished under both developing as well as developing countries enable bringing development of healthy stress free life of all gentry facilitating plausible stable governances.

Discrimination of the SARS–CoV-2 strains using of coloured s-LASCA-imaging of GB-speckles, developed for the gene “S” nucleotide sequences

Background: A recent bioinformatics technique involves changing nucleotide sequences into 2D speckles. This technique produces speckles called GB-speckles (Gene Based speckles). All classical strategies of speckle-optics, namely speckle-interferometry, subtraction of speckle-images as well as speckle-correlometry have been inferred for processing of GB-speckles. This indicates the considerable improvement in the present tools of bioinformatics. Methods: Colour s-LASCA imaging of virtual laser GB-speckles, a new method of high discrimination and typing of pathogenic viruses, has been developed. This method has been adapted to the detecting of natural mutations in nucleotide sequences, related to the spike glycoprotein (coding the gene «S») of SARS–CoV-2 gene as the molecular target. Results: The rate of the colouring images of virtual laser GB-speckles generated by s-LASCA can be described by the specific value of R. If the nucleotide sequences compared utilizing this approach the relevant images are completely identical, then the three components of the resulting colour image will be identical, and therefore the value of R will be equal to zero. However, if there are at least minimal differences in the matched nucleotide sequences, then the value of R will be positive. Conclusion: The high effectiveness of an application of the colour images of GB-speckles that were generated by s-LASCA- has been demonstrated for discrimination between different variants of the SARS–CoV-2 spike glycoprotein gene.

The Current and Evolving Therapeutic Paradigm in the Management of Metastatic Renal Cell Carcinoma

There has been tremendous progress in the treatment landscape of advanced or metastatic RCC with novel and efficacious targeted therapies, immunotherapies and combinatorial regimens, leading to an expansion of therapeutic armamentarium over the last two decades. New advances have offered considerable improvement in prognosis, treatment-related toxicities, quality of life, and survival for patients with mRCC. Despite such advantages, there is unmet need for developing novel biomarkers predictive of treatment response, optimize treatment selection, and also improving strategies to overcome therapeutic resistance in heterogenous RCC tumors. Herein, we outline currently available first- and subsequent-lines treatment strategies, unprecedented changes, and also discuss challenges in treatment landscape of RCC.

Discrimination of the SARS–CoV-2 strains using of coloured s-LASCA-imaging of GB-speckles, developed for the gene “S” nucleotide sequences

Background: A recent bioinformatics technique involves changing nucleotide sequences into 2D speckles. This technique produces speckles called GB-speckles (Gene Based speckles). All classical strategies of speckle-optics, namely speckle-interferometry, subtraction of speckle-images as well as speckle-correlometry have been inferred for processing of GB-speckles. This indicates the considerable improvement in the present tools of bioinformatics. Methods: Colour s-LASCA imaging of virtual laser GB-speckles, a new method of high discrimination and typing of pathogenic viruses, has been developed. This method has been adapted to the detecting of natural mutations in nucleotide sequences, related to the spike glycoprotein (coding the gene «S») of SARS–CoV-2 gene as the molecular target. Results: The rate of the colouring images of virtual laser GB-speckles generated by s-LASCA can be described by the specific value of R. If the nucleotide sequences compared utilizing this approach the relevant images are completely identical, then the three components of the resulting colour image will be identical, and therefore the value of R will be equal to zero. However, if there are at least minimal differences in the matched nucleotide sequences, then the value of R will be positive. Conclusion: The high effectiveness of an application of the colour images of GB-speckles that were generated by s-LASCA- has been demonstrated for discrimination between different variants of the SARS–CoV-2 spike glycoprotein gene.

Soil Improvement Using Waste Marble Dust for Sustainable Development

The soils which show very high shear strength in a dry state but rapidly lose their strength on wetting are known as collapsible soils. Such rapid and massive loss of strength produces severe distress leading to extensive cracking and differential settlements, instability of building foundations, and even collapse of structures built on these soils. Waste marble dust is an industrial byproduct and is being produced in large quantities globally poses an environmental hazard. Therefore, it is of the utmost need to look for some sustainable solution for its disposal. The present study focused on the mitigation of the collapse potential of CL-ML soil through a physio-chemical process. The soil is sensitive to wetting, warranting its stabilization. Waste marble dust (WMD) in varying percentages was used as an admixture. The study's optimization process showed that geotechnical parameters of collapsible soil improved substantially by adding waste marble dust. Plasticity was reduced while Unconfined Compressive Strength (UCS) significantly increased while swelling was reduced to an acceptable limit. The California Bearing Ratio (CBR) also exhibits considerable improvement. This study appraises the safe disposal of hazardous waste safely and turns these into suitable material for engineering purposes. Doi: 10.28991/cej-2021-03091746 Full Text: PDF

Optimum Design of Straight Circular Channels Incorporating Constant and Variable Roughness Scenarios: Assessment of Machine Learning Models

In this study, two machine learning (ML) models named as artificial neural network (ANN) and genetic programming (GP) were applied to design optimum canals with circular shapes. In this application, the earthwork and lining costs were considered as the objective function, while Manning’s equation was utilized as the hydraulic constraint. In this design problem, two different scenarios were considered for Manning’s coefficient: (1) constant Manning’s coefficient and (2) the experimentally proved variation of Manning’s coefficient with water depth. The defined design problem was solved for a wide range of different dimensionless variables involved to produce a large enough database. The first part of these data was used to train the ML models, while the second part was utilized to compare the performances of ANN and GP in optimum design of circular channels with those of explicit design relations available in the literature. The comparison obviously indicated that the ML models improved the accuracy of the circular channel design from 55% to 91% based on two performance evaluation criteria. Finally, application of the ML models to optimum design of circular channels demonstrates a considerable improvement over the explicit design equations available in the literature.

Reproductive Potential of Red Chittagong Cattle in Bangladesh

The study was carried out to investigate the phenotypic and genetic potential of reproductive traits of Red Chittagong Cattle (RCC) of Bangladesh. For that purpose accumulated data on a total of 101 animals from four different herds covering a period from 2005 to 2011 were used for analyses. The overall mean (±SE) values of age at first heat (AFH), age at first conception (AFC), age at first calving (AC), calving rate per productive year (CR), interval to post partum heat (IPPH), days open (DO), calving interval (CI) and generation interval (GI) were 35.9±1.1 month, 42.1±1.3 month, 50.6±1.1 month, 0.87±0.01 month, 149.4±9.5 days, 178.6±11.0 days, 454.9±10.4 days and 4.2±0.1 year, respectively. The factors having significant effects on reproductive traits were herd on DO and CI and calving year on DO. Calving parity and calving season had no significant effect on those traits. The heritability estimates of IPPH, DO and CI were very low (0, 0.06 and 0.09) and that of corresponding repeatability estimates were also low (0.06, 0.08 and 0.09, respectively). The heritability estimates for other traits were moderate (0.39 to 0.50). The results indicated that though reproductive potential of RCC for most of the traits are below than expected, that may be due to their lower inherent capability of indigenous Zebu compared to Taurus, but there is still opportunity of considerable improvement of these traits studied as indicated by their phenotypic variations among population.