Solubilization of Glibenclamide with β-Cyclodextrin & its Derivatives

Gilbenclamide, a widely used potent hypoglycaemic agent was solubllized using β -Cyclodextrin and β -Cyclodextrin derivatives. Complexes were prepared by kneading method in a molar ratio of 1:1 of the drug and the cyclodextrlns respectively. The Glibenclamide β -Cyelocextrin complex was characterized and evaluated by I.R. studies, Differential Scanning Calorimotry 6 X-ray diffractometry. The in-vitro dissolution rates of drug from inclusion complexes of β Cyclodextrins and its derivatives were compared. A significant Improvement In dissolution lor, rates of Gllbenclamide was observed with Inclusion complexes of all the Cyclodextrins. However, the solubilizing effect was more in case of β-Cyclodextrin derivatives.     

Automatic classification of computed tomography brain images using ANN,k-NN and SVM

Computed tomography images are widely used in the diagnosis of intracranial hematoma and hemorrhage. This paper presents a new approach for automated diagnosis based on classification of the normal and abnormal images of computed tomography. The computed tomography images used in the classification consists of non-enhanced computed tomography images. The proposed method consists of four stages namely pre-processing, feature extraction, feature reduction and classification. The discrete wavelet transform coefficients are the features extracted in this method. The essential coefficients are selected by the principal component analysis. The features derived are used to train the binary classifier, which infer automatically whether the image is that of a normal brain or a pathological brain, suffering from brain lesion. The proposed method has been evaluated on a dataset of 80 images. A classification with a success of 92, 97 and 98 % has been obtained by artificial neural network, k-nearest neighbor and support vector machine, respectively. This result shows that the proposed technique is robust and effective.     

An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to improve the existing methods that choose the underloaded hosts, get rid of Virtual Machines (VMs) from them, and finally place them in some other hosts. The researcher proposes a Host Resource Utilization Aware (HRUAA) Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment. The mechanism presented in this study is contrasted with existing mechanisms empirically. The results attained from the study establish that numerous hosts can be shut down, while at the same time, the user's workload requirement can also be met. The proposed method is energy-efficient in workload consolidation, saves cost and time, and leverages active hosts.     

An improved analytical model of 4H-SiC MESFET incorporating bulk and interface trapping effects

An improved analytical model for the current-voltage (I-V) characteristics of the 4H-SiC metal semiconductor field effect transistor (MESFET) on a high purity semi-insulating (HPSI) substrate with trapping and thermal effects is presented. The 4H-SiC MESFET structure includes a stack of HPSI substrates and a uniformly doped channel layer. The trapping effects include both the effect of multiple deep-level traps in the substrate and surface traps between the gate to source/drain. The self-heating effects are also incorporated to obtain the accurate and realistic nature of the analytical model. The importance of the proposed model is emphasised through the inclusion of the recent and exact nature of the traps in the 4H-SiC HPSI substrate responsible for substrate compensation. The analytical model is used to exhibit DC I-V characteristics of the device with and without trapping and thermal effects. From the results, the current degradation is observed due to the surface and substrate trapping effects and the negative conductance introduced by the self-heating effect at a high drain voltage. The calculated results are compared with reported experimental and two-dimensional simulations (Silvaco^®-TCAD). The proposed model also illustrates the effectiveness of the gate-source distance scaling effect compared to the gate-drain scaling effect in optimizing 4H-SiC MESFET performance. Results demonstrate that the proposed I-V model of 4H-SiC MESFET is suitable for realizing SiC based monolithic circuits (MMICs) on HPSI substrates.     

Development and Validation of HPTLC Method for Estimation of Tacrolimus in Formulations

A new, simple, and rapid high-performance thin-layer chromatographic method with a derivatization procedure was developed and validated for quantitative determination of tacrolimus. Tacrolimus was chromatographed on silica gel 60 F₂₅₄ TLC plate using toluene–acetonitrile–glacial acetic acid (6:4:0.1, by volume) as mobile phase. Tacrolimus was visualized using a derivatization reagent containing anisaldehyde–sulfuric acid in absolute alcohol and quantified by densitometric analysis in the reflectance mode at 675 nm. The method was found to give compact spots for the drug (R_f?=?0.40?±?0.03). The linear regression analysis data for the calibration plots showed good linear relationship with r²?=?.9989 in the concentration range 100–800 ng/spot. The method was validated for precision, recovery, repeatability, and robustness as per the International Conference on Harmonization guidelines. The minimum detectable amount was found to be 28.90 ng, whereas the limit of quantitation was found to be 97.04 ng. Statistical analysis of the data showed that the method is precise, accurate, reproducible, and selective for the analysis of tacrolimus. The method was successfully employed for the estimation of equilibrium solubility and quantification of tacrolimus as a bulk drug and in commercially available capsules and in-house developed self-microemulsifying formulations.     

Robustness of group delay representations for noisy speech signals

This paper demonstrates the robustness of group delay based features to additive noise. First, we analytically show the robustness of group delay based representations. The analysis makes use of the fact that, for minimum-phase signals, the group delay function can be represented in terms of the cepstral coefficients of the log-magnitude spectrum. Such a representation results in the speech spectrum dominating over the noise spectrum, both at low and high SNRs. Further, we experimentally demonstrate the robustness of the representation on a voice activity detection (VAD) task, comparing a group delay based VAD algorithm with standard VAD methods as well as a magnitude-spectrum based method.     

Automatic transcription of continuous speech into syllable-like units for Indian languages

The focus of this paper is to automatically segment and label continuous speech signal into syllable-like units for Indian languages. In this approach, the continuous speech signal is first automatically segmented into syllable-like units using group delay based algorithm. Similar syllable segments are then grouped together using an unsupervised and incremental training (UIT) technique. Isolated style HMM models are generated for each of the clusters during training. During testing, the speech signal is segmented into syllable-like units which are then tested against the HMMs obtained during training. This results in a syllable recognition performance of 42·6% and 39·94% for Tamil and Telugu. A new feature extraction technique that uses features extracted from multiple frame sizes and frame rates during both training and testing is explored for the syllable recognition task. This results in a recognition performance of 48·7% and 45·36%, for Tamil and Telugu respectively. The performance of segmentation followed by labelling is superior to that of a flat start syllable recogniser (27·8%and 28·8%for Tamil and Telugu respectively).     

Green synthesis of silver nanoparticles using Zea mays and exploration of its biological applications

The biosynthesis of silver nanoparticles (AgNPs) has been proved to be a cost effective and environmental friendly approach toward chemical and physical methods. In the present study, biosynthesis of AgNPs was carried out using aqueous extract of Zea mays (Zm) husk. The initial colour change from golden yellow to orange was observed between 410 and 450 nm which confirmed the synthesis of AgNPs. Also, dynamic light scattering‐particle size analysis confirmed the average size to be 113 nm and zeta potential value of −28 kV. The morphology of synthesised Zm AgNPs displayed flower‐shaped structure, X‐ray diffraction pattern revealed the strongest peaks at 2θ = 38.6° and 64° which proved that the nanoparticle has the face centred crystalline structure. The Fourier transform infrared spectroscopy results showed strong absorption bands at 1394.53, 2980.02 and 2980.02 cm⁻¹ due to the presence of alkynes, carboxylic acids, alcoholic and phenolic groups. The maximum zone of inhibition was observed against Salmonella typhi (22 mm) and Candida albicans (18 mm). The synthesised nanoparticles exhibited more free radical scavenging activity than the aqueous plant extract. This is the first report on the synthesis of AgNP from Zm husk, delivers the efficient and stable Zm AgNPs through simple feasible approach toward green biotechnology.Inspec keywords: silver, nanoparticles, nanofabrication, light scattering, particle size, X‐ray diffraction, crystal structure, Fourier transform infrared spectra, absorption coefficients, free radicalsOther keywords: green synthesis, silver nanoparticles, biosynthesis, environmental friendly approach, aqueous extract, Zea mays husk, colour change, golden yellow, dynamic light scattering‐particle size analysis, average size, zeta potential value, flower‐shaped structure, X‐ray diffraction pattern, face centred crystalline structure, Fourier transform infrared spectroscopy, absorption bands, alkynes, carboxylic acids, alcoholic groups, phenolic groups, Salmonella typhi, Candida albicans, free radical scavenging activity, aqueous plant extraction, green biotechnology, size 113 nm, wavelength 410 nm to 450 nm     

Enhanced SO2 concentrations observed over northern India: role of long-range transport

The combustion of fossil fuels (coal and petroleum products) constitutes a source of continuous release of anthropogenic SO₂ into the atmosphere. Furthermore, natural sources such as volcanoes can inject large amounts of SO₂ directly into the troposphere and sometimes even into the stratosphere. These event-based volcanic eruptions provide solitary opportunities to study the transport and transformation of atmospheric constituents. In this study, we present an episode of high SO₂ concentration over northern India as a result of long-range transport from Africa using multiple satellite observations. Monthly averaged column SO₂ values over the Indo-Gangetic Plain (IGP) were observed in the range of 0.6–0.9 Dobson units (DU) during November 2008 using observations from the Ozone Monitoring Instrument (OMI). These concentrations were conspicuously higher than the background concentrations (<0.3 DU) observed during 2005–2010 over this region. The columnar SO₂ loadings were highest on 6 November over most of the IGP region and even exceeded 6 DU, a factor of 10–20 higher than background levels in some places. These enhanced SO₂ levels were not reciprocated in satellite-derived NO₂ or CO columns, indicating transport from a non-anthropogenic SO₂ source. As most of the local aerosols over the IGP region occur below 3 km, a well-separated layer at 4–5 km was observed from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. Wind fields and back-trajectory analysis revealed a strong flow originating from the Dalaffilla volcanic eruption in Ethiopia during 4–6 November 2008. Although volcanic SO₂ plumes have been extensively studied over many parts of Asia, Europe, and the USA, analysis of such events for the IGP region is being reported for the first time in this study.     

Growth of highly (1 1 1) oriented CuIn0.75Al0.25Se2 thin films

CuIn_0.75Al_0.25Se₂ thin films prepared onto glass substrates at T_S=573 K were single phase, nearly stoichiometric and polycrystalline with a strong (1 1 1) preferred orientation showing sphalerite structure. The results of X-ray diffraction and electron diffraction studies are compared, interpreted and correlated with micro-Raman spectra. The optical absorption studies indicated a direct band gap of 1.16 eV with high absorption coefficient (>10⁴ cm^?1) near the fundamental absorption edge.