Ionic liquid-based deep eutectic solvents as novel solvent-cum-catalyst media for thermal dehydrogenation of chemical hydrides

The current work explores the usage of novel synthesized Deep Eutectic Solvent (DES) as a catalyst cum solvent media for the thermal dehydrogenation of chemical hydrides, namely Ammonia Borane (AB) and Ethylene diamine bisborane (EDAB). In the first instance, the quantum chemistry based COSMO-SAC (COnductor like Screening MOdel Segment Activity Coefficient) model was used for the selection of the pertinent solvent. 1-Butyl-3-methylimidazolium methanesulfonate: Imidazole ([BMIM][MeSO₃]:[Im]) turned out to be an ideal eutectic mixture with the highest predicted solubility with amine boranes. The DES was synthesized by combining the Hydrogen Bond Acceptor (HBA), namely 1-Butyl-3-methylimidazolium methanesulfonate and Imidazole as Hydrogen Bond Donor (HBD) at a molar ratio of 1:2 and T = 70 °C. The formation of DES was confirmed by recording the NMR spectra. Further, the thermal dehydrogenation study was performed at a vacuum of 4 × 10^?2 mbar (gauge pressure) of AB/DES and EDAB/DES systems at 105 °C, where a hydrogen equivalent of 1.40 and 2.55 was produced, respectively. The residual samples were further analyzed through ¹H NMR analysis for the reaction mechanism and to confirm the role of Ionic Liquid-based DES as catalyst cum solvent media.     

Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Correlation of fecundability and serum estradiol after danazol treatment in patients with advanced endometriosis

OBJECTIVE: To examine the relationship between pregnancy incidence and the level of serum E2 during danazol therapy. DESIGN: Danazol was given by 200 mg four times daily for 3 months. Serum E2 level was checked after completing the therapy, but before stopping medication. Patients then were advised to conceive at the appropriate time over a 6-month period. SETTING: Reproductive and Endocrine Laboratory of the Department of Obstetrics and Gynecology, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan. PATIENTS: Infertile women with invasive endometriosis receiving conservative surgery and danazol treatment. INTERVENTIONS: Serum E2 is checked before medication and at the end of danazol therapy, but before stopping medication. MAIN OUTCOME MEASURES: Whether pregnancy is related to the change of serum E2 caused by danazol therapy. RESULTS: There were 24 pregnancies in 38 patients with invasive endometriosis after treatment. Pregnant patients had significantly lower serum E2 levels as compared with the nonpregnant patients. CONCLUSIONS: After conservative surgery for invasive endometriosis associated with infertility, the therapeutic period of danazol treatment could be shortened to 3 months. Because there is significant correlation of fecundability and serum E2 after danazol medication, serum E2 could be a guideline for predicting pregnancy or for prolonging or changing of treatment after danazol therapy.     

Prevalence of hepatitis B and C virus infections among haemodialysis patients in Pune (western India)

Vascular injuries may occur as complications of elbow dislocation and usually involve the brachial artery. A case report is presented in which only the radial artery was compromised as a result of the dislocation.     

Pigeon perception and discrimination of rapidly changing texture stimuli

The perception and discrimination of rapidly changing texture stimuli by pigeons was examined in a target localization task. Five experienced pigeons were rewarded for finding and pecking at a randomly placed odd target block of small repeated elements embedded in a larger rectangular array of contrasting distractor elements. On dynamic color test trials, the color of the target, distractor, or both of these regions changed at rates of 100, 250, 500, or 1000 ms per frame. The number of colors appearing within such trials also varied. Pigeons performed well above chance in all test conditions, with target-associated changes producing the best discrimination. The results suggest: (a) global relational information can exclusively guide target localization behavior, (b) pigeons can perceptually group and segregate colored textured differences quite rapidly (< or = 100 ms), and (c) pigeons may possess automatic search control processes that can be captured by stimulus-driven changes in the display.     

A new method to estimate parameters of linear compartmental models using artificial neural networks

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models.