Modeling of the Magnetization and Magnetocaloric Effect in Ni2MnGa Heusler Alloy with the Effective Field Theory

Journal of Low Temperature Physics - This study modeled and investigated the magnetocaloric effect in Ni2MnGa Heusler alloy characterized by its magnetic entropy change (ΔSm) and its...     

CD46 (membrane cofactor protein of complement, measles virus receptor): structural and functional divergence among species (review)

OBJECT: In this retrospective study, the authors analyzed the frequency, anatomical distribution, and appearance of traumatic brain lesions in 42 patients in a posttraumatic persistent vegetative state. METHODS: Cerebral magnetic resonance (MR) imaging was used to detect the number of lesions, which ranged from as few as five to as many as 19, with a mean of 11 lesions. In all 42 cases there was evidence on MR imaging of diffuse axonal injury, and injury to the corpus callosum was detected in all patients. The second most common area of diffuse axonal injury involved the dorsolateral aspect of the rostral brainstem (74% of patients). In addition, 65% of these patients exhibited white matter injury in the corona radiata and the frontal and temporal lobes. Lesions to the basal ganglia or thalamus were seen in 52% and 40% of patients, respectively. Magnetic resonance imaging showed some evidence of cortical contusion in 48% of patients in this study; the frontal and temporal lobes were most frequently involved. Injury to the parahippocampal gyrus was detected in 45% of patients; in this subgroup there was an 80% incidence of contralateral peduncular lesions in the midbrain. The most common pattern of injury (74% in this series) was the combination of focal lesions of the corpus callosum and the dorsolateral brainstem. In patients with no evidence of diffuse axonal injury in the upper brainstem (26% in this series), callosal lesions were most often associated with basal ganglia lesions. Lesions of the corona radiata and lobar white matter were equally distributed in patients with or without dorsolateral brainstem injury. Moreover, cortical contusions and thalamic, parahippocampal, and cerebral peduncular lesions were also similarly distributed in both groups. CONCLUSIONS: The data indicate that diffuse axonal injury may be the major form of primary brain damage in the posttraumatic persistent vegetative state. In addition, the authors demonstrated in this study that MR imaging, in conjunction with a precise clinical correlation, may provide useful supportive information for the accurate diagnosis of a persistent vegetative state after traumatic brain injury.     

Comparison of copper emission rates from wood treated with different preservatives to the environment

This study describes a laboratory method for the estimation of emission from preservative-treated wood in the different situations where emissions could enter the environment for use classes 3 (not in contact with ground) and 4 and 5 (in contact with the ground, fresh water or sea water) according to OECD Guidelines. Samples of scotch pine sapwood (Pinus sylvestris L.) were treated with CCA (1% and 2%), ACQ-1900 (3% and 7%), ACQ-2200 (2%), Tanalith E 3491 (2% and 2.8%), and Wolmanit CX-8 (2%).     

Evaluation of a technique for identification of Shiga-like toxin-producing Escherichia coli by using polymerase chain reaction and digoxigenin-labeled probes

A polymerase chain reaction (PCR) technique for the identification of Shiga-like toxin (SLT)-producing Escherichia coli was assessed by using 95 strains of SLT-producing E. coli and 5 Shigella dysenteriae type 1 strains. PCR was used for the amplification of slt gene sequences from whole bacterial colonies. A digoxigenin-labeled DNA probe was used for identification of the PCR products in a spot blot hybridization assay. Modifications were made to adapt this technique for the proper identification of 10 SLT-producing isolates which were refractory to the heat lysis step that was used to liberate whole-cell DNA for PCR and 6 isolates which gave nonspecific amplification products. The sensitivity and specificity of this assay were each 99% when compared with toxin neutralization results by using SLT-specific monoclonal antibodies. These values indicate that this detection technique could be suitable for use in a clinical laboratory.     

Accurate and simple synthesis formulas for coplanar waveguides

Simple and accurate closed‐form formulas obtained by using a differential evolution algorithm are presented for the synthesis of coplanar waveguides (CPW). The results of the synthesis formulas proposed in this article are compared with those of the quasi‐static analysis, the synthesis formulas reported by the other researchers and also the experimental works available in the literature. The accuracy of the proposed synthesis formulas is found to be better than 0.75% for 9256 CPWs samples. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Concomitant Crystallization of Copper(II) Sachharinato Complexes with 2-methylpyrazine as a Monomer and an One-dimensional Polymer: Syntheses,Crystal Structures,Spectroscopic and Thermal Properties

The reaction of [Cu(sac)₂(H₂O)₄] · 2H₂O with 2-methylpyrazine (mpyz) leads two complexes, concomitant crystallization of a mononuclear complex [Cu(sac)₂(mpyz)(H₂O)₂] (1) and a polymeric complex [Cu(sac)₂(μ-mpyz)]_n (2). Both complexes have been characterized by elemental analyses, magnetic measurements, FT-IR and ESR, TG-DTA and single-crystal X-ray diffraction analyses. Single-crystal X-ray analyses show that complex 1 consists of discrete molecules in which the copper(II) ions exhibits a square-pyramidal coordination geometry. The individual molecules of 1 are connected into a hydrogen-bonded chain structure, which is further assembled to form a three-dimensional network by π–π stacking interactions. Complex 2 is an 1D coordination polymer in which copper(II) centers are bridged by the mpyz ligand. The chains are further assembled to form two-dimensional frameworks by π–π and C–H···π stacking interactions.     

Mechanism of impaired metabolic signaling by a truncated human insulin receptor. Decreased activation of protein phosphatase 1 by insulin

Previous studies have shown that a human insulin receptor lacking the COOH-terminal 43-amino acid domain (HIR delta CT) displays a compromised ability to stimulate glucose transport and glycogen synthase, whereas mitogenic signaling and stimulation of the insulin receptor tyrosine kinase activity remain intact (Maegawa, H., McClain, D. A., Freidenberg, G., Olefsky, J. M., Napier, M., Lipari, T., Dull, T. J., Lee, J., and Ullrich, A. (1988) J. Biol. Chem. 263, 8912-8917). In this study, we examined the effect of insulin on protein phosphatase 1 (PP-1) activity and phosphorylation in cells expressing wild-type human insulin receptor (HIRc) and HIR delta CT cells using phosphorylase alpha as substrate in the presence of 3 nM okadaic acid. Basal PP-1 activity was significantly lower in HIR delta CT than in HIRc cells (p < 0.05). Insulin stimulated PP-1 activity in HIRc cells (25-30% increase over basal activity) in a time- and dose-dependent manner. Insulin failed to stimulate PP-1 activity in HIR delta CT cells. Western blotting with the catalytic subunit antibody and the regulatory subunit antibody revealed similar amounts of the 37-kDa band (catalytic subunit) and the 160-kDa band (presumed regulatory subunit) in HIRc and HIR delta CT cells. We conclude that the COOH-terminal domain of the insulin receptor is an important element in mediating the effect of insulin on PP-1 and suggest that activation of PP-1 may be linked to signaling insulin's metabolic actions.     

A novel chaotic Henry gas solubility optimization algorithm for solving real-world engineering problems

The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm (HGSO). The new algorithm is named chaotic Henry gas solubility optimization (CHGSO). The hybridization is aimed at enhancement of the convergence rate of the original Henry gas solubility optimizer for solving real-life engineering optimization problems. This hybridization provides a problem-independent optimization algorithm. The CHGSO performance is evaluated using various conventional constrained optimization problems, e.g., a welded beam problem and a cantilever beam problem. The performance of the CHGSO is investigated using both the manufacturing and diaphragm spring design problems taken from the automotive industry. The results obtained from using CHGSO for solving the various constrained test problems are compared with a number of established and newly invented metaheuristics, including an artificial bee colony algorithm, an ant colony algorithm, a cuckoo search algorithm, a salp swarm optimization algorithm, a grasshopper optimization algorithm, a mine blast algorithm, an ant lion optimizer, a gravitational search algorithm, a multi-verse optimizer, a Harris hawks optimization algorithm, and the original Henry gas solubility optimization algorithm. The results indicate that with selecting an appropriate chaotic map, the CHGSO is a robust optimization approach for obtaining the optimal variables in mechanical design and manufacturing optimization problems.

     

Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features

The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. So, vulnerability detection applications play a significant part in software development and maintenance. The ability of the forecasting techniques in vulnerability detection is still weak. Thus, one of the efficient defining features methods that have been used to determine the software vulnerabilities is the metaheuristic optimization methods. This paper proposes a novel software vulnerability prediction model based on using a deep learning method and SYMbiotic Genetic algorithm. We are first to apply Diploid Genetic algorithms with deep learning networks on software vulnerability prediction to the best of our knowledge. In this proposed method, a deep SYMbiotic-based genetic algorithm model (DNN-SYMbiotic GAs) is used by learning the phenotyping of dominant-features for software vulnerability prediction problems. The proposed method aimed at increasing the detection abilities of vulnerability patterns with vulnerable components in the software. Comprehensive experiments are conducted on several benchmark datasets; these datasets are taken from Drupal, Moodle, and PHPMyAdmin projects. The obtained results revealed that the proposed method (DNN-SYMbiotic GAs) enhanced vulnerability prediction, which reflects improving software quality prediction.

     

A combo technology of autotrophic and heterotrophic denitrification processes for groundwater treatment

In this study,a sequential process (heterotrophic up-flow column and completely mixed membrane bioreactors) was proposed combining advantages of the both processes.The system was operated for 249 days with simulated and real groundwater for nitrate removal at concentrations varying from 25 to 145 mg·L-1 NO3-N.The contribution of heterotrophic process to total nitrate removal in the system was controlled by dozing the ethanol considering the nitrate concentration.By this way,sulfur based autotrophic denitrification rate was decreased and the effluent sulfate concentrations were controlled.The alkalinity requirement in the autotrophic process was produced in the heterotrophic reactor,and the system was operated without alkalinity supplementation.Throughout the study,the chemical oxygen demand in the heterotrophic reactor effluent was (23.7 ± 22) mg·L-1 and it was further decreased to(7.5 ± 7.2) mg·L-1 in the system effluent,corresponding to a 70％ reduction.In the last period of the study,the real groundwater containing 145 mg·L-1 NO3-N was completely removed.Membrane was operated without chemical washing in the first 114 days.Between days 115-249 weekly chemical washing was required.