Green synthesis of silver nanoparticles from purple acid phosphatase apoenzyme isolated from a new source Limonia acidissima

Green synthesis of nanoparticles is regarded as a safe and non-toxic process whereas conventional synthesis using chemical methods produces toxic substance. This study provides a novel insight for enzymatic synthesis method of silver nanoparticles using purple acid phosphatase, isolated from Limonia acidissima (wood apple) as a new source and used in the synthesis of silver nanoparticles. Stable silver nanoparticles were produced by sonochemical method using apoenzyme as a stabilising and capping agent and were characterised by various physicochemical techniques like UV–Visible spectroscopy, Fourier-transform infrared, X-ray diffraction and transmission electron microscopy. X-ray study shows that nanoparticles are composed of silver and silver oxide. The synthesised nanoparticles exhibited excellent antimicrobial activity against Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus.     

Behavior of decomposition of rifampicin in the presence of isoniazid in the pH range 1-3

The extent of decomposition of rifampicin in the presence of isoniazid was determined in the pH range 1-3 at 37°C in 50 min, the mean stomach residence time. With increase in pH, the degradation initially increased from pH 1 to 2 and then decreased, resulting in a bell-shaped pH-decomposition profile. This showed that rifampicin degraded in the presence of isoniazid to a higher extent at pH 2, the maximum pH in the fasting condition, under which antituberculosis fixed-dose combination (FDC) products are administered. At this pH and in 50 min, rifampicin decomposed by ~ 34%, while the fall of isoniazid was 10%. The extent of decomposition for the two drugs was also determined in marketed formulations, and the values ranged between 13-35% and 4-11%, respectively. The extents of decomposition at stomach residence times of 15 min and 3 h were 11.94% and 62.57%, respectively, for rifampicin and 4.78% and 11.12%, respectively, for isoniazid. The results show that quite an extensive loss of rifampicin and isoniazid can occur as a result of interaction between them in fasting pH conditions. This emphasizes that antituberculosis FDC formulations, which contain both drugs, should be designed in a manner that the interaction of the two drugs is prevented when the formulations are administered on an empty stomach.     

Cold Simulation of Metalloids Transport in Blast Furnaces

Metalloids normally get transferred at the interface of metal droplets passing through the slag system in the dropping zone and at the slag‐metal interface in the hearth zone in the lower region of a blast furnace. In these high temperature processes, the mass transport being the rate‐controlling factor, the viscosity of the slag system determines the kinetics of the refining reactions accompanied by mass and heat transfer at the metal droplets and slag interface. Slag systems generally possess random network structures comprising internal regions of weak ordering. The presence of these regions may result in non‐Newtonian behaviour of the slag. The rheological characteristics of a fluid relating to its network structure is expressed in terms of the indices consistency (k') and flow behaviour (n'). The extent of metalloids presence in hot metal is subjected to their residence time at the slag‐metal interface. The metal droplet descent through a surrounding fluid system has been studied and a co‐relation between drag Reynolds number and modified Reynolds number has been obtained. This correlation has been used to determine the drag velocity of a metal droplet falling through a slag system and the residence time distribution (RTD) of the metalloids at the slag‐metal interface in the lower region of the blast furnace.     

Robust manufacturing system design using multi objective genetic algorithms,Petri nets and Bayesian uncertainty representation

Decisions involving robust manufacturing system configuration design are often costly and involve long term allocation of resources. These decisions typically remain fixed for future planning horizons and failure to design a robust manufacturing system configuration can lead to high production and inventory costs, and lost sales costs. The designers need to find optimal design configurations by evaluating multiple decision variables (such as makespan and WIP) and considering different forms of manufacturing uncertainties (such as uncertainties in processing times and product demand). This paper presents a novel approach using multi objective genetic algorithms (GA), Petri nets and Bayesian model averaging (BMA) for robust design of manufacturing systems. The proposed approach is demonstrated on a manufacturing system configuration design problem to find optimal number of machines in different manufacturing cells for a manufacturing system producing multiple products. The objective function aims at minimizing makespan, mean WIP and number of machines, while considering uncertainties in processing times, equipment failure and repairs, and product demand. The integrated multi objective GA and Petri net based modeling framework coupled with Bayesian methods of uncertainty representation provides a single tool to design, analyze and simulate candidate models while considering distribution model and parameter uncertainties.     

Microprocessor Control of Cycloconverter: Techniques for Implementation and Testing

Since the 1930's, cycloconverter control circuits have been designed with vacuum tubes, transistors, and integrated circuits. With the advent of microprocessors, much more logical and computational power became available in much less space and cost. This led to the design of converter control circuits using microprocessors [2]-[9]. Each of these papers describes a specific implementation. Advancements in microprocessor technology are still going at full steam. To take full advantage of this technology and its continued advancements, a systematic and broad-based study of techniques that can be used for cycloconverter control-on microprocessor-based systems-is required. This paper reports the findings of such a study [10]. In this study a few general techniques were developed for cycloconverter control. In developing the various Techniques, accuracy of trigger timing and the system's speed of response were used as performance criteria. The techniques developed were tested on a system based on the 8085 CPU. Each technique was tested qualitatively by recording the cycloconverter waveforms produced by using it. For quantitative testing, first, the theoretical trigger timings were found by a digital computer simulation of the cycloconverter. These timings were then compared with those produced on the microprocessor-based system. From the test results it was concluded that an 8 bit data width suffices for cycloconverter control. The main bottleneck in achieving the desired performance is the execution time of the processor. In one of the techniques, when improvement in trigger timing accuracy was achieved it lead to reduction in the speed of response.     

Growth of polysilicon and silicide films for MOS-VLSI application

Doped and undoped polycrystalline silicon films were grown byapcvd and thermal evaporation techniques. The effect of growth and annealing conditions on the crystalline nature of the films and their properties were studied by electrical, optical, x-ray diffraction andsem techniques. Metal silicides such as TiSi₂ and PtSi₂ were prepared by co-evaporation technique over polysilicon layers to study their suitability in microelectronic applications. Some of the properties of polysilicon and silicides are discussed.     

Activity performance and kinetics for glycerol carbonylation with urea over Zn-Co mixed metal oxide catalyst

Efficient carbonylation of glycerol using urea with Zn-Co mixed metal oxide (MMO) catalyst has been achieved. Various methods of catalyst preparation were explored for glycerol carbonate (GC) synthesis. The optimized method of catalyst preparation was found to be co-precipitation (CP) with a Zn:Co ratio of 70:30, achieving 81% glycerol conversion with 97% GC selectivity. X-ray diffraction (XRD) studies revealed the formation of ZnO, Co₃ O₄, and spinel ZnCo₂O₄ phases. Thermal treatment given to the catalyst allows insertion of Zn cations into Co₃O₄ lattice forming ZnCo₂O₄ phase which was also evidenced in X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. Herein, for the first time, reaction kinetics was studied to propose the rate equation, based on which a plausible reaction pathway is proposed involving two-site adsorption of glycerol (basic site) and urea (acidic site), which undergo carbonylation followed by cyclization into GC. A recycle study and hot filtration test have proven the reusability of the catalyst.     

Time-dependent queueing model having heterogeneous servers

The present paper considers a time-dependent queueing model having a finite number of parallel channels each having a different service rate. The probabilities of the exact number of arrivals and departures by a given time and marginal probabilities of the exact number of arrivals are obtained.     

The proposition of Possibilistic sigmoid features and the Shannon-Hanman transform classifier along with the pervasive learning model for the classification of brain tumor using MRI

As part of developing a computer-aided diagnosis system for the early detection/classification of brain tumors, this paper presents an Information set-based sigmoid features and a classifier using MR images. A set of information values constituting an Information set springs forth on fitting a membership function to a set of information source (attribute) values, the sum of which gives the certainty/uncertainty in the attribute values to a class, say, the pixel intensities in an MRI to a disease class. This certainty/uncertainty representation is not attempted in the existing methods, thus failing to produce efficient features. To this end, Hanman-Anirban (HA), Mamta-Hanman (MH), and Possibilistic Renyi entropy functions are employed including the pervasive membership function in the generation of four types of sigmoid features. The pervasive Information set results from the use of pervasive membership function that is a combination of the membership function and non-membership function. Furthermore, the Shannon-Hanman Transform classifier is formulated using the t-norm of error vectors between the training and test feature vectors, and its parameters are learned through the Pervasive learning model. The proposed system comprising features, classifier, and the learning model is tested on two Brain MRI’s datasets. The t-norm based fusion of two features has also been experimented. The Shannon-Hanman Transform classifier along with the Pervasive learning model is found to outperform the other classifiers in the literature with the highest accuracy of 99.51% for the two-class classification with a fusion of two features and 99.09% for the three-class classification with a sigmoid MH feature.

     

Wide area polycrystalline diamond coating and stress control by sp hot filament CVD reactor

This paper discusses large area uniform diamond coatings deposited in the sp³ Inc. Model 600 hot filament diamond deposition system (made by sp³ Inc., California, USA). This model combines proven hot filament thermal reactor technology with advanced controls to produce high quality polycrystalline diamond films over a maximum square area of 380 mm × 380 mm on a wide variety of substrate materials such as carbide-based cutting tools, wear surfaces, Si wafers, etc. The reactor is characterized using instrumented 300 mm Si wafers and modified, accordingly, to optimize performance on 300 mm diameter wafers or multiple 100 mm diameter wafers. Roles of temperature and other process parameters in stress formation and development in the diamond thin films, grown in a wide area hot filament deposition system, are discussed along with some of the ways of controlling these stresses on a production basis.