A neural network-based instrumental method for light fastness assessment with dataset validation

A novel instrumental method for the light fastness assessment has been established. The accuracy of the visual method is affected by undesirable constraints, such as the different severity and the complications due to off-tone color change of the specimens. Thus, it was desired to develop an instrumental method of the light fastness assessment. In this regard, a neural network-based instrumental method of the light fastness assessment was developed. First, a proper light fastness panel was prepared, and then the visual light fastness assessments of experienced and inexperienced observers were collected. The accuracy and repeatability of the visual assessment results from these two groups of the observers were analyzed using different statistical criteria. The statistical analysis has shown that the mean of three trials of the inexperienced observers can be combined with the mean of the results obtained by experienced. Thus, all the results from the inexperienced and experienced observers were used to prepare a valid dataset for training a neural network. Different neural network structures trained with the prepared valid dataset. Among all of the implemented structures, the most accurate neural network structure is the one with one hidden layer and a 3-7-1 structure. The root mean square error and correlation coefficients of proposed 3-7-1 NN are 0.32 and 0.975, respectively, for the test sets. According to these results and the results from the comparison of the instrumental and visual assessment of the light fastness, it was concluded that the proposed neural network can be used for the instrumental light fastness assessment.     

Fabrication and in vitro degradation study of novel optically active polymers derived from amino acid containing diacids and 4,4′-thiobis(2-tert-butyl-5-methylphenol)

Chiral bioactive poly(ester-imide)s (PEI)s were synthesized from N,N′-(pyromellitoyl)-bis-(L-phenylalanine) and N,N′-(pyromellitoyl)-bis-(L-leucine) diacids derived from amino acids with 4,4′-thiobis(2-tert-butyl-5-methylphenol) via direct polycondensation reaction in a system of tosyl chloride, pyridine and N,N-dimethylformamide as a condensing agent. The structures of these polymers were confirmed by FT-IR, ¹H-NMR, specific rotation, elemental and thermogravimetric analysis (TGA) techniques. TGA showed that the 10% weight loss temperature in a nitrogen atmosphere was more than 390 °C, which indicates that the resulting PEIs have a good thermal stability. The biodegradability of the monomers and prepared polymers was investigated in culture media and soil burial test for assessing the susceptibility of these compounds to microbial degradation. The results showed that the synthesized monomers and theirs derived polymers are biologically active and they are nontoxic to microbial growth.     

Cellulose-graft-polyacrylamide/hydroxyapatite composite hydrogel with possible application in removal of Cu (II) ions

Cellulose-graft-polyacrylamide/hydroxyapatite composite hydrogels of different weight ratios were prepared through a suspension polymerization method. Physical and chemical characteristics of the composite were investigated by Fourier transform infrared spectroscopy and scanning electron microscopy. The swelling behaviors of the composite hydrogels were investigated under varying conditions of time, temperature and pH. The optimized swelling capacity in standard conditions was found to be 5197% per gram of the hydrogel. The prepared hydrogel has the potential to be used for ion adsorption in water treatment. Such a possibility was examined through adsorption of copper (II) ions from an aqueous solution. The effects on adsorption of varying the time, pH, and initial concentration of copper (II) solution as well as some thermodynamic parameters were also investigated. The maximum adsorption capacity was found to be 175 mg per gram of composite hydrogel in dried state. The mechanism of adsorption was well presented using a pseudo-second-order kinetic model. Finally, the mercury-loaded hydrogel was regenerated without losing its original activity and stability.     

Synthesis and characterization of novel poly(amide-ether)s bearing imidazole pendants: study of physical and optical properties

Two new para-linked diether-diamines, bis(4-(4-amino-2-(4,5-diphenyl-1H-imidazol-2-yl)phenoxy) phenyl)methanone and bis(4-(4-amino-2-(4,5-diphenyl-1H-imidazol-2-yl)phenoxy) phenyl)hexafluoropropane, bearing two ortho-linked phenyl-substituted imidazole pendants and trifluoromethyl groups were synthesized by the nucleophilic chlorodisplacement reaction of the synthesized 2-(2-chloro-5-nitrophenyl)-4,5-diphenyl-1H-imidazole with 4,4′-dihydroxybenzophenone or 4,4′-(hexafluoroisopropylidene)diphenol in refluxing DMAc in the presence of potassium carbonate. These diamines were utilized to prepare a series of novel poly(amide-ether)s (PAEs) via direct phosphorylation polycondensation with aliphatic and aromatic dicarboxylic acids. The polymeric samples were readily soluble in a variety of organic solvents and formed low-colored and flexible thin films via solution casting. These polymers showed glass-transition temperatures (T _gs) between 204 and 308 °C. Thermal behaviors of the PAEs were characterized by thermogravimetric analysis, and the 10 % weight loss temperatures were found to be in the range of 330–450 °C in N₂. The PAEs exhibited fluorescence emission in solution and in solid state with maxima around 423–494 nm and with the quantum yields in the range of 6–28 %.     

The effects of visualization and interaction techniques on feature model configuration

A Software Product Line is a set of software systems of a domain, which share some common features but also have significant variability. A feature model is a variability modeling artifact which represents differences among software products with respect to variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by selecting features in the feature model (referred to as the configuration process) and by instantiating the reference model. However, feature model configuration can be a cumbersome task because: 1) feature models may consist of a large number of features, which are hard to comprehend and maintain; and 2) many factors including technical limitations, implementation costs, stakeholders’ requirements and expectations must be considered in the configuration process. Recognizing these issues, a significant amount of research efforts has been dedicated to different aspects of feature model configuration such as automating the configuration process. Several approaches have been proposed to alleviate the feature model configuration challenges through applying visualization and interaction techniques. However, there have been limited empirical insights available into the impact of visualization and interaction techniques on the feature model configuration process. In this paper, we present a set of visualization and interaction interventions for representing and configuring feature models, which are then empirically validated to measure the impact of the proposed interventions. An empirical study was conducted by following the principles of control experiments in software engineering and by applying the well-known software quality standard ISO 9126 to operationalize the variables investigated in the experiment. The results of the empirical study revealed that the employed visualization and interaction interventions significantly improved completion time of comprehension and changing of the feature model configuration. Additionally, according to results, the proposed interventions are easy-to-use and easy-to-learn for the participants.     

Optimal pricing model for electronic products

Electronic commerce encompasses all electronically conducted business activities, operations, and transaction processing. With the development of electronic commerce via Internet, during the past decade, many companies have changed the way they connect to and deal with their customers and partners. In this paper we introduce a Geometric Programming (GP) based model to analyze the pricing method and the service quality for E-business companies. The proposed method of this paper considers electronic products which are all kinds of products to be sold via web supermarkets. Therefore, they can cover pure digital and also non-digital products. The model proposed in this research work, deals with non-digital goods, which are supplied through web. The resulted non-linear model is directly solved by using Geometric Programming (GP) and a closed form of solution is presented. We assume that the demand is influenced by price, marketing and service expenditures. We also assume that the cost of production is affected by demand. We analyze the solution in different cases, in order to study the behavior of the model and for each case numerical examples are used to demonstrate the implementation of our analysis. The sensitivity analysis is also presented at the end to analyze the behavior of the model.     

Association of low vitamin D levels with metabolic syndrome in hemodialysis patients

Low vitamin D levels have been linked to metabolic syndrome in the general population. In the present study, the relationship between inadequate serum concentrations of vitamin D and metabolic syndrome in patients with end‐stage renal disease undergoing hemodialysis was explored. In a cross‐sectional setting, 145 patients undergoing maintenance hemodialysis were enrolled. Metabolic syndrome was defined using the International Diabetes Federation criteria. Serum concentration of 25(OH) vitamin D was determined by a commercially available enzyme immunosorbent assay method. The prevalence of metabolic syndrome was 53.1%. The prevalence rate of severe vitamin D deficiency (<5 ng/mL) was 3.4%, mild vitamin D deficiency (5–15 ng/mL) 31.0%, vitamin D insufficiency (16–30 ng/mL) 36.6%, and vitamin D sufficiency (>30 ng/mL) 29.0%. With the increasing number of metabolic abnormalities, vitamin D levels significantly decreased (P for trend = 0.028). Among the components of metabolic syndrome, vitamin D deficiency was significantly associated with central obesity (odds ratio [OR], 95% confident interval [CI] = 2.80, 1.11–7.04, P = 0.028). A positive, but nonsignificant association between vitamin D deficiency and raised fasting plasma glucose was noted (OR, 95% CI = 2.40, 0.94–6.11, P = 0.067). Both vitamin D deficiency and insufficiency were significantly associated with an increased likelihood of having metabolic syndrome (P < 0.05). In a final model controlling for age, sex, and parathyroid hormone levels, vitamin D deficiency increased the odds of having metabolic syndrome by more than threefold (OR, 95% CI = 3.26, 1.30–8.20, P = 0.012). Low levels of vitamin D are frequent among hemodialysis patients and are associated with the metabolic syndrome.     

Improved surface bioactivity of stainless steel substrates using osteocalcin mimetic peptide

Although stainless steel has a good biocompatibility for most clinical cases, the higher tissue response (bone bonding property) is required in orthopedic field. In this study, to improve bone-bonding ability of stainless steel substrates, a specific sequence of osteocalcin mimetic peptide is used as bioactive coating material to biochemically modify the surface of metallic samples. This sequence consists of thirteen amino acids present in the first helix of osteocalcin is synthesized in amidic form and physically adsorbed on the surface of 316LS (316 low carbon surgical grade) stainless steel substrates. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) are used to characterize the surface of peptide coated and uncoated substrates. The bioactivity and bone bonding ability of coated and uncoated substrates are assessed by level of hydroxyapatite formation, using transmission electron microscopy (TEM), energy-dispersive x-ray (EDS), and scanning electron microscopy (SEM). The pre-osteoblast cell attachment and proliferation are also evaluated by MTT assay. The results show that the surface of coated sample is homogenously covered by the peptide and display a rougher surface relative to uncoated sample. TEM images reveal the formation of plate-like hydroxyapatite crystals in the presence of the peptide and an amorphous calcium phosphate phase without the peptide. Pre-osteoblast cells proliferation is significantly higher on the surface of peptide coated substrate, while cell attachment remains unaffected by the peptide coatings. Pre-osteoblast cells also demonstrate a higher degree of spreading on the surface of coated sample. It is believed that osteocalcin mimetic peptide improve surface bioactivity and promote hydroxyapatite crystal formation may lead to increased mineralization and bone formation on the surface of metallic biomedical devices.