Genetic Algorithm�CArtificial Neural Network Modeling of Moisture and Oil Content of Pretreated Fried Mushroom

In this research, the effect of different pretreatments (osmotic dehydration and gum coating) on moisture and oil content of fried mushroom was investigated, and artificial neural network and genetic algorithm were applied for modeling of these parameters during frying. Osmotic dehydration was performed in solution of NaCl with concentrations of 5% and 10%, and methyl cellulose was used for gum coating. Either pretreated or control samples were fried at 150, 170, and 190 °C for 0.5, 1, 2, 3, and 4 min. The results showed that osmotic dehydration and gum coating significantly decreased (0–84%, depending upon the processing conditions) oil content of fried mushrooms. However, moisture content of fried samples diminished as result of osmotic pretreatment and increased by gum coating. An artificial neural network was developed to estimate moisture and oil content of fried mushroom, and genetic algorithm was used to optimize network configuration and learning parameters. The developed genetic algorithm–artificial neural network (GA–ANN) which included 17 hidden neurons could predict moisture and oil content with correlation coefficient of 0.93 and 96%, respectively. These results indicating that GA–ANN model provide an accurate prediction method for moisture and oil content of fried mushroom.     

Introduction of two polyvinyl alcohol resins for efficient solid support Cu-catalyzed N-arylation of α-aminoacids with aryl halides in aqueous media

In this article, two polyvinyl alcohol (PVA)-based resins were prepared by crosslinking of epoxidized PVA-chains using of 4-(4-aminobenzyl)benzenamine as a crosslinker and polymerization of acrylated PVA chains in the another approach. The prepared PVA resins showed well hydrophilic and swelling properties in various organic solvents, which are used in solid-phase organic synthesis (SPOS). Swelling properties of these resins were examined in dimethylformamide, tetrahydrofuran, water, ethanol, methanol, dichloromethane, and dioxane. Furthermore, the both resins were characterized by FTIR and ¹H-NMR and their properties such as epoxy equivalent weight (EEW) of epoxidized PVA and density of the resins were determined by analytical methods. Then, α-amino acids such as L-aspartic acid, L-leucine, L-alanine, L-serine, L-valine, L-threonine, and L-tyrosine were immobilized on both resins through esterification reaction between these α-amino acids with the present hydroxyl groups on PVA resines, to carry out their solid-phase N-arylation reaction in the presence of CuI as a catalyst in milder and greener conditions than free resin protocols. Hydrolysis of the correponding N-arylated α-amino acids immobilized on the resins gave the N-arylated α-amino acids in high to excellent yields. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47597.     

Stiffness of bi-modulus hexagonal and diamond honeycombs

Cellular materials are widely used in various applications because of their low density and high strength. The mechanical behavior of cellular materials under various loading conditions has been investigated. Nevertheless, many of these previous studies assume that the Young’s modulus of constituting struts is the same in tension and compression. The present work first derives analytical expressions for the effective Young’s moduli of hexagonal and diamond lattices composed of struts with different tension and compression moduli under the assumption of small strain deformation. It also uses the finite element method to further investigate the mechanical responses of these lattices. The macroscopic Young’s moduli under both compressive and tensile loads are reported as a function of the ratio of compression and tension moduli of constituting struts. The numerical finite element models are implemented by a user defined material subroutine in ABAQUS. Results reveal that the effective Young’s moduli of periodic hexagonal and diamond lattices significantly decrease with decreasing ratio of compression and tension moduli of the struts. Furthermore, the mechanical behavior of hexagonal lattices composed of struts with different tension-compression moduli is dependent on the loading direction and whether they are compressed or stretched. The unique mechanical properties of bi-modulus cellular materials could find important applications in the automotive and construction industries.

     

Schweißen ermüdungsbeanspruchter Altstahlkonstruktionen – Untersuchungen zum Sprödbruchverhalten geschweißter Verbindungen aus Flussstahl

Welding of existing steel structures – brittle fracture behaviour of welded mild steel. Welding processes cause notch effects and residual stresses. Therefore the risk of brittle fracture grows. In comparison with modern steels, old mild steels have a lower ductility. So it is necessary to evaluate brittle fracture behaviour of mild steel after welding. This evaluation is done by means of fracture mechanics parameters. The results show that for plate thicknesses of mild steel up to 11 mm there is no risk of brittle fracture. For higher plate thicknesses a procedure to evaluate brittle fracture behaviour is described taking the actual state of stress and actual material properties into consideration.     

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.     

Short- and Long-Term Effects of Prenatal Exposure to Iron Oxide Nanoparticles: Influence of Surface Charge and Dose on Developmental and Reproductive Toxicity

Iron oxide nanoparticles (NPs) are commonly utilized for biomedical, industrial, and commercial applications due to their unique properties and potential biocompatibility. However, little is known about how exposure to iron oxide NPs may affect susceptible populations such as pregnant women and developing fetuses. To examine the influence of NP surface-charge and dose on the developmental toxicity of iron oxide NPs, Crl:CD1(ICR) (CD-1) mice were exposed to a single, low (10 mg/kg) or high (100 mg/kg) dose of positively-charged polyethyleneimine-Fe₂O₃-NPs (PEI-NPs), or negatively-charged poly(acrylic acid)-Fe₂O₃-NPs (PAA-NPs) during critical windows of organogenesis (gestation day (GD) 8, 9, or 10). A low dose of NPs, regardless of charge, did not induce toxicity. However, a high exposure led to charge-dependent fetal loss as well as morphological alterations of the uteri (both charges) and testes (positive only) of surviving offspring. Positively-charged PEI-NPs given later in organogenesis resulted in a combination of short-term fetal loss (42%) and long-term alterations in reproduction, including increased fetal loss for second generation matings (mice exposed in utero). Alternatively, negatively-charged PAA-NPs induced fetal loss (22%) earlier in organogenesis to a lesser degree than PEI-NPs with only mild alterations in offspring uterine histology observed in the long-term.