A PSO-based model to increase the accuracy of software development effort estimation

Development effort is one of the most important metrics that must be estimated in order to design the plan of a project. The uncertainty and complexity of software projects make the process of effort estimation difficult and ambiguous. Analogy-based estimation (ABE) is the most common method in this area because it is quite straightforward and practical, relying on comparison between new projects and completed projects to estimate the development effort. Despite many advantages, ABE is unable to produce accurate estimates when the importance level of project features is not the same or the relationship among features is difficult to determine. In such situations, efficient feature weighting can be a solution to improve the performance of ABE. This paper proposes a hybrid estimation model based on a combination of a particle swarm optimization (PSO) algorithm and ABE to increase the accuracy of software development effort estimation. This combination leads to accurate identification of projects that are similar, based on optimizing the performance of the similarity function in ABE. A framework is presented in which the appropriate weights are allocated to project features so that the most accurate estimates are achieved. The suggested model is flexible enough to be used in different datasets including categorical and non-categorical project features. Three real data sets are employed to evaluate the proposed model, and the results are compared with other estimation models. The promising results show that a combination of PSO and ABE could significantly improve the performance of existing estimation models.     

Evaluation of Factors Influencing Microwave Osmotic Dehydration of Apples Under Continuous Flow Medium Spray (MWODS) Conditions

Microwave osmotic dehydration under continuous flow medium spray (MWODS) conditions is an innovative concept with high potential for enhancing moisture loss as well as improving product quality. Quantification of mass transfer kinetics under different processing conditions is important for managing and optimizing the osmotic dehydration process. A response surface methodology was used for evaluating and quantifying the moisture loss and solids gain kinetics of apples during the MWODS process. Experiments were designed according to a central composite rotatable design with all independent variables included at five levels (sucrose concentration, 33.3–66.8°Brix; medium temperature, 33.3–66.8 °C; medium flow rate, 2,120–3,480 ml/min; and medium contact time, 5–55 min). The process responses were moisture loss (ML), solids gain (SG), and weight reduction (WR) and were related to process variables using second-order polynomial regression models. The lack of fit was not significant (p?>?0.05) for any of the developed models. For ML, SG, and WR, the medium contact time was the most significant factor during the MWODS process followed by medium temperature and sucrose concentration. The effect of medium flow rate was only significant with moisture loss and weight reduction. The quantity of ML, SG, or WR achieved over a 30 min treatment time was chosen as the drying rate. These rates were shown to be responsive to the osmotic treatments increasing with sucrose concentration, medium flow rate, and medium temperature.     

Optimisation study of gum extraction from Basil seeds (Ocimum basilicum L.)

Basil seed ( Ocimum basilicum L.) is cultivated in large quantities in different regions of Iran. This seed has reasonable amounts of gum with good functional properties which is comparable with commercial food hydrocolloids. A central composite rotatable design was applied to evaluate the effects of temperature, pH and water/seed ratio on the yield, apparent viscosity and protein content of water-extracted Basil seed gum. All of the variables significantly ( P  < 0.05) affected the extraction yield, whereas the effect of water/seed ratio on apparent viscosity and the effects of pH and water/seed ratio on protein content were not significant ( P  > 0.05). Numerical optimisation determined the optimum extraction conditions based on the highest yield and viscosity and the lowest protein content as being temperature 68.71 °C, pH 8.09 and water/seed ratio 65.98:1. Power law model well described non-Newtonian pseudoplastic behaviour of BSG. Flow behaviour index ( n ) and consistency index ( K ) of 1% crude and pure BSG samples were 0.306, 0.283 and 17.46, 20.22 Pa s ⁿ , respectively.     

Functional Heterodimerization between the G Protein-Coupled Receptor GPR17 and the Chemokine Receptors 2 and 4: New Evidence

GPR17, a G protein-coupled receptor, is a pivotal regulator of myelination. Its endogenous ligands trigger receptor desensitization and downregulation allowing oligodendrocyte terminal maturation. In addition to its endogenous agonists, GPR17 could be promiscuously activated by pro-inflammatory oxysterols and chemokines released at demyelinating lesions. Herein, the chemokine receptors CXCR2 and CXCR4 were selected to perform both in silico modelling and in vitro experiments to establish their structural and functional interactions with GPR17. The relative propensity of GPR17 and CXCR2 or CXCR4 to form homo- and hetero-dimers was assessed by homology modelling and molecular dynamics (MD) simulations, and co-immunoprecipitation and immunoenzymatic assay. The interaction between chemokine receptors and GPR17 was investigated by determining receptor-mediated modulation of intracellular cyclic adenosine monophosphate (cAMP). Our data show the GPR17 association with CXCR2 or CXCR4 and the negative regulation of these interactions by CXCR agonists or antagonists. Moreover, GPR17 and CXCR2 heterodimers can functionally influence each other. In contrast, CXCR4 can influence GPR17 functionality, but not vice versa. According to MD simulations, all the dimers reached conformational stability and negative formation energy, confirming the experimental observations. The cross-talk between these receptors could play a role in the development of the neuroinflammatory milieu associated with demyelinating events.     

Multi-scale modelling of elastic moduli of trabecular bone

We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results.     

Rice Bran Oil Improves Insulin Resistance by Affecting the Expression of Antioxidants and Lipid‐Regulatory Genes

The present study investigated the molecular effects of rice bran oil (RBO) on lipid‐regulatory genes (sterol regulatory element binding protein‐1 [Srebf1] and peroxisome proliferator‐activated receptors‐α [Ppara]) and the expression of catalase (CAT) and superoxide dismutase (SOD1) genes in insulin‐resistant rats. Rats were divided into five groups: animals that received standard diet (control); rats fed standard diet containing RBO as the sole source of fat (RBO); a high‐fructose diet (HFD) group, which was further divided into two subgroups: rats fed HFD either for only 1 month (HFD1) or for 2 months (HFD2) and rats fed HFD containing RBO for 1 month; while rats in the last group fed HFD for 30 days then treated with RBO for another 30 days. The HFD induced a state of insulin resistance (IR) as indicated by the hyperinsulinemia and elevated homeostasis model assessment insulin resistance index. Hepatic lipid levels and radical scavenging enzymes were altered by the HFD. Lipid‐regulatory genes, Srebf1 and Ppara, were upregulated while Sod1 and Cat were downregulated in insulin‐resistant rats. Addition of RBO to the two diet regimens alleviated the disorders of IR to some extent. RBO reduced the hepatic levels of triacylglycerol, malondialdehyde, SREBP, and PPAR‐α mRNA. Hepatic SOD and CAT were elevated at gene and protein levels. The HFD induces de novo lipogenesis by upregulating the lipid‐regulatory genes resulting in increased serum and hepatic triacylglycerol. Moreover, IR induced by the HFD caused a state of oxidative stress. Supplementation of RBO to fructose‐fed rats not only improves insulin resistance but also downregulates lipogenic genes and improves the unbalanced oxidative status.     

Isolation and Identification of Current Biosurfactant-Producing Microbacterium maritypicum ABR5 as a Candidate for Oily Sludge Recovery

Biosurfactants have a wide range of applications in different areas, including petroleum microbiology and environmental biotechnology. In this study, removing and recovering oil from oily sludge using microbactan-producing bacteria have been investigated. The best biosurfactant-producing isolate was obtained from a petroleum reservoir and was identified by 16S rDNA analysis as Microbacterium maritypicum ABR5. Its 16S rDNA sequence was deposited in GenBank, NCBI under the accession number MK100468. Chemical analysis using thin-layer chromatography and Fourier Transform Infrared confirmed that the produced biosurfactant was glycolipoprotein. The strain reduced surface tension from 72 to 34.6 mN m⁻¹. The addition of 5 mg L ZnO nanoparticles to the biosurfactant-producing medium showed no bacterial toxicity effect and raised the emulsification index to 25.7%. Higher concentrations of ZnO nanoparticles, such as 10 and 100 mg L, decreased the bacterial growth rate and biosurfactant production. The mixing of M. maritypicum ABR5 culture medium and oily sludge increased the oil recovery from oily sludge by up to 70% after 5 days of incubation. This is the first report of biosurfactant production by a newly identified strain, M. maritypicum ABR5, isolated from a petroleum reservoir. We proposed that the isolated biosurfactant-producing strain could be considered an economical asset for oil recovery from oily sludge in the petroleum industry and environmental biotechnology.     

A unified lumped approach in kinetic modeling of biomass pyrolysis

Thermogravimetry analysis and gas chromatography techniques are used at different heating rates (from 5 to 50 K/min) to map all the products and to develop suitable kinetic models of biomass pyrolysis. A three-independent-parallel-reactions model is used to model kinetic of total devolatilization. This part accounts for the total char yield and devolatilization time. The evolutions of condensable vapors (tar and H₂O) and non-condensable gases (H₂, CH₄, CO and CO₂) are also studied using gas chromatography technique. It is shown that the final total yield of gases increases by increasing the heating rate, whereas those of tar decrease by increasing heating rate. A kinetic model was then proposed and the parameters for that were calculated, which can predict the change of the gases yields at different heating rates. The performance of the kinetic models was evaluated for other experimental works available in the literature or by exposing the biomass to different heating program.     

A study of carboxylic acids and nano-TiO2 effects on stress relaxation of cotton fabrics

This study presents an evaluation on stress relaxation of cotton fabrics before and after performing the finishing process. The process includes a series of treatments on fabric samples through the Pad-dry curing method. A group of organic acids along with a proportion of catalyst and co-catalyst mixture constituted the treatment agents. Stress relaxation behavior of untreated and treated samples was assessed along two different directions of weft and warp using stress relaxation tester. In addition, an Italian Mesdan tensile tester was applied to measure physical and mechanical properties such as elongation, strength, Poisson’s ratio, and shear modulus. In the mean time scanning electron microscopy was applied to consider surface of samples before and after treatments. The results prove that the stress relaxation of treated samples has shown reasonably acceptable values when compared with those obtained for untreated one. Furthermore, the curve fitting of Maxwell’s model over the experimental data also justified that an interlaced model is more appropriate for explaining the stress relaxation in cotton fabrics. Beside the result of stress relaxation, Poisson’s ratio, and shear modulus illustrated remarkable increments. On the other hand, a reverse trend was observed for tensile properties in both directions. Orthotropic feature evaluation of fabrics toward both the direction of warp and weft also infers different response of stress relaxation in each direction.