Abuse of codeine-containing cough syrups: a report from India

AIM: To study the socio-demographic and clinical profile of patients seeking treatment for abuse of codeine-containing cough syrups (CCS). DESIGN: Observational; case series. SETTING: An addiction clinic in North India. PARTICIPANTS: Forty-six consecutive treatment-seeking patients of DSM-III-R-diagnosed dependence on CCS, from January 1994 to June 1995. MEASUREMENTS: Semi-structured interview schedule for patients and their family covering socio-demographic and clinical variables. FINDINGS: All patients were male. Many were young (mean age 27 years), with completed school education (85%) and from urban backgrounds (80%). The mean age of starting CCS use was 23 years. Initiated commonly through friends (89%) and often for curiosity (63%), 89% of the patients progressed to daily use of CCS in less than 6 months (54% in less than a month), and in quantities much higher than prescribed limits. Opioid-like withdrawal was reported by 92%. Concurrent use of other substances, psychiatric co-morbidity and HIV-related risk behaviour were present in 72%, 24% and 45%, respectively. Most of the patients reported a 'stimulant' effect of CCS ('alert', 96%; 'more active', 94%). CONCLUSIONS: The combination of an opioid and a sympathomimetic agent in the CCS may cause a special, distinct euphoretic effect. This effect, along with the low price, easy availability and 'pure' preparation of CCS, may be responsible for the rapidly rising popularity of the CCS as drugs of abuse in India.     

Modeling the performance of molten carbonate based direct carbon fuel cell anode

A mathematical model is developed to study the performance of a molten carbonate based direct carbon fuel cell anode. The direct carbon fuel cell(DCFC) is a fuel cell which uses solid carbon as fuel and molten carbonate as electrolyte. The model assumes that the 4 electron carbon oxidation reaction is the primary reaction driving the DCFC. However, the 2 electron CO oxidation reaction and the reverse Boudouard reaction is also considered in this model. The model studies the effect of performance parameters on the performance of the DCFC. The effect of the bulk conductivity in the solid phase, the bulk conductivity in the liquid phase, carbon loading and the thickness of the anode layer on the potential and current distribution in the cell is modeled. Model results are compared with experimental data and found to compare well.     

High‐Density Periodically Ordered Magnetic Cobalt Ferrite Nanodot Arrays by Template‐Assisted Pulsed Laser Deposition

A novel nanopatterning method using pulsed laser deposition through an ultrathin anodic aluminium oxide (AAO) membrane mask is proposed to synthesize well‐ordered nanodot arrays of magnetic CoFe₂O₄ that feature a wide range of applications like sensors, drug delivery, and data storage. This technique allows the adjustment of the array dimension from ～35 to ～300 nm in diameter and ～65 to ～500 nm in inter‐dot distance. The dot density can be as high as 0.21 Terabit in.^?2. The microstructure of the nanodots is characterized by SEM, TEM, and XRD and their magnetic properties are confirmed by well‐defined magnetic force microscopy contrasts and by hysteresis loops recorded by a superconducting quantum interference device. Moreover, the high stability of the AAO mask enables the epitaxial growth of nanodots at a temperature as high as 550 °C. The epitaxial dots demonstrate unique complex magnetic domains such as bubble and stripe domains, which are switchable by external magnetic fields. This patterning method creates opportunities for studying novel physics in oxide nanomagnets and may find applications in spintronic devices.     

Prediction of cardiovascular risk by measuring carotid intima media thickness from an ultrasound image for type II diabetic mellitus subjects using machine learning and transfer learning techniques

The Journal of Supercomputing - Cardiovascular disease (CVD) is a fatal disease that causes increased death in developing and developed nations. Among the various reasons, the increase in carotid...     

Preparation and Characterization of Biocement Mortar Containing Silane-treated Nano-Si3N4 Prepared from Rice Husk Ash

Silicon - This present study aims to develop an eco-friendly high performance biocement using rice husk biomass derived nano Si3N4. The main aim of this study was to investigate the significant...     

Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

Directive-based programming models, such as OpenMP, OpenACC, and OmpSs, enable users to accelerate applications by using coprocessors with little effort. These devices offer significant computing power, but their use can introduce two problems: an increase in the total cost of ownership and their underutilization because not all codes match their architecture. Remote accelerator virtualization frameworks address those problems. In particular, rCUDA provides transparent access to any graphic processor unit installed in a cluster, reducing the number of accelerators and increasing their utilization ratio. Joining these two technologies, directive-based programming models and rCUDA, is thus highly appealing. In this work, we study the integration of OmpSs and OpenACC with rCUDA, describing and analyzing several applications over three different hardware configurations that include two InfiniBand interconnections and three NVIDIA accelerators. Our evaluation reveals favorable performance results, showing low overhead and similar scaling factors when using remote accelerators instead of local devices.     

Entropy generation minimization in turbulent mixed convection flows

This paper reports the results of a numerical investigation of turbulent mixed convection from a symmetrically heated vertical channel, bathed by a steady upward flow of cold air. The computations have been performed using FLUENT 6.2 by employing the k–ε model for turbulence with enhanced wall treatment. The entropy generation rates due to (i) heat transfer across a finite temperature difference and (ii) irreversibility due to fluid friction have been calculated as post-processed quantities with the computed velocity and temperature profiles. Optimal inlet velocities at which the total entropy generation rate reaches a minimum value are found to exist, for every set of heat flux and aspect ratio. Further, this optimum velocity turns out to be independent of the aspect ratio and increases linearly with the heat flux. Simple and easy to use correlations for the optimum Reynolds number and the dimensionless average wall temperatures corresponding to the optima are developed. Plots of total entropy generation rate against the velocity clearly demonstrate that near the optimum conditions, buoyancy does not have a significant role to play in deciding the optimum. For the range of parameters considered in this study, it is seen that for optimum conditions, the ratio of the entropy generation due to fluid friction to total entropy generation rate, known in literature as the Bejan number, varies within a narrow band (0.14–0.22).     

A Bayesian approach for the simultaneous estimation of surface heat transfer coefficient and thermal conductivity from steady state experiments on fins

This paper explores the potential of the Bayesian approach to estimate multiple parameters from simple, inexpensive experiments on natural convection heat transfer from a vertical rectangular fin. A vertical fin of rectangular cross-section is placed on two heated horizontal aluminium blocks of size 250 × 75 × 10 (all in mm) that act as a horizontal base and hold the extended surface made up of mild steel of size 250 × 160 × 4 (all in mm). A heater is placed below the aluminium block and to restrict the heat flow, the bottom side of the heater is insulated with glass wool. Steady state experiments are carried out to obtain the temperature distribution for different levels of heating and temperatures on the fin are recorded with K-type thermocouples. Using data from these experiments, two critical parameters namely, the average heat transfer coefficient and the thermal conductivity of the extended surface are first individually and later simultaneously obtained using the Bayesian approach thereby obviating the need for sophisticated equipment. The above two parameters are correlated thereby making their simultaneous estimation very challenging. The Markov Chain Monte Carlo (MCMC) is used for the estimation without and with subjective priors on the two parameters. The uncertainties are obtained explicitly in the form of standard deviation. The addition of subjective priors is the hallmark of the Bayesian approach as it reduces the standard deviation of the estimates. This considerably helps regularizing the ill-posedness and becomes a necessity for estimating correlated parameters. A discussion on the optimum number of temperature measurements needed for estimating the parameters with a given accuracy using the Bayesian method is also presented.     

Heat transfer and hydromagnetic electroosmotic Von Kármán swirling flow from a rotating porous disc to a permeable medium with viscous heating and Joule dissipation

Magnetohydrodynamic flow and heat transfer in an ionic viscous fluid in a porous medium induced by a stretching spinning disc and modulated by electroosmosis under an axial magnetic field and radial electrical field is presented in this study. The effects of convective wall boundary conditions, Joule heating and viscous dissipation are incorporated. The governing partial differential conservation equations are transformed into a system of self-similar coupled, nonlinear ordinary differential equations with associated boundary conditions. The Matlab bvp4c solver featuring a shooting technique and the fourth-order Runge–Kutta–Fehlberg method are used to numerically solve the governing dimensionless boundary value problem. Multivariate analysis is also performed to examine the thermal characteristics. An increase in rotation parameter induces a reduction in the radial velocity, whereas it elevates the tangential velocity. Greater electrical field parameter strongly damps the radial velocity whereas it slightly decreases the tangential velocity. Increasing magnetic parameter also damps both the radial and tangential velocities. An increment in electroosmotic parameter substantially decelerates the radial flow but has a weak effect on the tangential velocity field. Increasing permeability parameter (inversely proportional to permeability) markedly damps both radial and tangential velocities. The pressure gradient is initially enhanced near the disk surface but reduced further from the disk surface with increasing magnetic parameter and electrical field parameter, whereas the opposite effect is produced with increasing Joule dissipation. Increasing magnetic and rotational parameters generate a strong heating effect and boost temperature and thermal boundary layer thickness. Nusselt number is boosted with increasing Brinkman number (viscous heating effect) and Reynolds number. The simulations are relevant to electromagnetic coating flows, bioreactors and electrochemical sensing technologies in medicine.