Production and evaluation of vildagliptin-loaded poly(dl-lactide) and poly(dl-lactide-glycolide) micro-/nanoparticles: Response surface methodology approach

A laboratory scale spray dryer was used to encapsulate vildagliptin (VLG), an antihyperglycemic drug, into different polymers such as poly(dl-lactide) (PDLA), poly(dl-lactide-glycolide)-50:50 (PLGA 50:50), and poly(dl-lactide-glycolide)-75:25 (PLGA 75:25). Response surface methodology (RSM) was employed to evaluate the effects of process and formulation factors on the encapsulation efficiency (EE). The physicochemical properties of the drug-loaded micro-/nanoparticles, mainly the drug loading (DL), particle size distribution, surface morphology, drug–polymer compatibility, and release rate were investigated. % EE of drug-loaded micro-/nanoparticles were in the range of 57.10% to 76.44%. PLGA50:50 micro-/nanoparticles showed highest EE as compared to PDLA and PLGA75:25 micro-/nanoparticles. The mean particle size of the micro-/nanoparticles containing PLGA 50:50, PLGA 75:25, and PDLA polymers were 428?nm, 640?nm, and 1.22 µm, respectively. Surface morphology study revealed smooth, spherical and nonporous surface structures of the micro-/nanoparticles. Fourier transform infrared spectroscopy studies confirmed the drug–polymer compatibility. Powder X-ray diffraction analysis of micro-/nanoparticles revealed that VLG was present in the amorphous form within the micro-/nanoparticles formulations. In vitro release study demonstrated that VLG is slowly released from micro-/nanoparticles for 12?h and the drug release rate was influenced by type and viscosity of polymers used. This work suggests that PDLA, PLGA 50:50, and PLGA75:25 polymers are able to sustain the VLG release rates from micro-/nanoparticles.     

Recycling of silicone rubber waste: Effect of ground silicone rubber vulcanizate powder on the properties of silicone rubber

The silicone rubber vulcanizate powder (SVP) obtained from silicone rubber by mechanical grinding exists in a highly aggregated state. The particle size distribution of SVP is broad, ranging from 2 µm to 110 µm with an average particle size of 33 µm. X‐ray Photoelectron Spectroscopy (XPS) and Infrared (IR) Spectroscopy studies show that there is no chemical change on the rubber surface following mechanical grinding of the heat‐aged (200°C/10 days) silicone rubber vulcanizate. Addition of SVP in silicone rubber increases the Mooney viscosity, Mooney scorch time, shear viscosity and activation energy for viscous flow. Measurement of curing characteristics reveals that incorporation of SVP into the virgin silicone rubber causes an increase in minimum torque, but marginal decrease in maximum torque and rate constant of curing. However, the activation energy of curing shows an increasing trend with increasing loading of SVP. Expectedly, incorporation of SVP does not alter the glass‐rubber transition and cold crystallization temperatures of silicone rubber, as observed in the dynamic mechanical spectra. It is further observed that on incorporation of even a high loading of SVP (i.e., 60 phr), the tensile and tear strength of the silicone rubber are decreased by only about 20%, and modulus dropped by 15%, while the hardness, tension set and hysteresis loss undergo marginal changes and compression stress‐relaxation is not significantly changed. Atomic Force Microscopy studies reveal that incorporation of SVP into silicone rubber does not cause significant changes in the surface morphology.     

Synthesis and characterization of poly(urethane‐ester)s based on calcium salt of mono(hydroxybutyl)phthalate

Calcium‐containing poly(urethane‐ester)s (PUEs) were prepared by reacting diisocyanate (HMDI or TDI) with a mixture of calcium salt of mono(hydroxybutyl)phthalate [Ca(HBP)₂] and hydroxyl‐terminated poly(1,4‐butylene glutarate) [HTPBG₁₀₀₀], using di‐n‐butyltin‐dilaurate as catalyst. About six calcium‐containing PUEs having different composition were synthesized by taking the mole ratio of Ca(HBP)₂:HTPBG₁₀₀₀:diisocyanate (HMDI or TDI) as 3:1:4, 2:2:4, and 1:3:4. Two blank PUEs were synthesized by the reaction of HTPBG₁₀₀₀ with diisocyanate (HMDI or TDI). The polymers were characterized by IR, ¹H NMR, Solid state ¹³C‐CP‐MAS NMR, TGA, DSC, XRD, solubility, and viscosity studies. The T_g value of PUEs increases with increase in the calcium content and decreases with increase in soft segment content. The viscosity of the calcium‐containing PUEs increases with increase in the soft segment content and decreases with increase in the calcium content. X‐ray diffraction patterns of the polymers show that the HMDI‐based polymers are partially crystalline and TDI‐based polymers are amorphous in nature. The dynamic mechanical analysis of the calcium‐containing PUEs based on HMDI shows that with increase in the calcium content of polymer, modulus (g′ and g″) increases at any given temperature. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 1720–1727, 2006     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

Structure-property relations for a phase-pure,nanograined tetragonal zirconia ceramic stabilized with minimum CaO doping

Dense (~97%) CaO-stabilized ZrO₂ ceramic was stabilized with minimum (3 mol%) doping (reported to date) and processed via conventional sintering at a low temperature (~1200°C); compositional analysis via X-ray florescence confirmed the CaO doping accuracy. Phase-pure tetragonal structure (characterized via both X-ray diffraction and Raman spectroscopy) along with uniform nanograins (90 nm) of the ceramic ensured the evolution of no monoclinic phase even after vigorous low-temperature degradation experiments (both thermal and hydrothermal aging for 80-100 h). The sintered ceramic recorded a high hardness (~15 GPa); the indentation toughness value was also comparable to a 3 mol% yttria-stabilized zirconia system. The remarkable structure–property correlations in the 3 mol% CaO-stabilized ZrO₂ ceramic suggests that the same may be worth examining for suitable future applications (e.g., in dental ceramics).     

Comparative wear performance of titanium based coatings for automotive applications using exhaust gas recirculation

This paper reports tribological characterization of titanium based coatings ion bonded on steel balls for automotive applications using exhaust gas recirculation (EGR). It is well known that lubricating oil drawn from EGR operated engine is contaminated with soot and higher amounts of wear debris compared to non-EGR operated engine. In this study, steel balls coated with TiN, TiAlN and TiCN are investigated in both fresh lubricating oil and EGR stressed oil for a comparative assessment of their wear characteristics in two mediums. Normal load was applied on the samples, tested against a rotating cast iron disk, simulating ring-liner interaction. In each experiment, about one quarter of disk was dipped in the oil (a) to ensure the presence of a thin oil film on the disk-ball interface during the experiment, and (b) to avoid exposure of the worn surface to atmospheric air. The results reveal that the wear rates of the coatings based on the change in the scar diameters of the samples, tested in EGR oil was 2-4 times higher than that of fresh lubricating oil. It was found that despite lowest hardness, TiN coated samples showed smaller scar diameters than TiAlN and TiCN coated samples in both lubricating oil environments. A simple geometric model was used to calculate the thickness of the coating removed as a function of the test duration. Results show that TiN coatings last for 120 min in fresh oil as compared to 30 min in the EGR oil under normal loading, whereas TiAlN and TiCN coating last for 60 and 30 min respectively in fresh oil and wear out in 15 min in EGR oil.     

The effect of yttrium and thorium on the oxidation behavior of Ni-Cr-Al alloys

The effect of quaternary additions of 0.5% Y and 0.5 and 1.0% Th to a base alloy of Ni-10Cr-5Al on the oxidation behavior and mechanism was studied during oxidation in air over the range of 1000–1200°C. The presence of yttrium decreased the oxidation kinetics slightly, whereas the addition of thorium caused a slight increase. Oxide scale adherence was markedly improved by the addition of the quaternary elements. Although a number of oxides formed on yttrium-containing alloys, quantitative x-ray diffraction clearly showed that the rate-controlling step was the diffusion of oxygen through short-circuit paths in a thin layer of alumina that formed parabolically with time. Mixed oxides containing both aluminum and yttrium formed by the reaction of Y₂O₃ to form YAlOP₃ initially, and Y₃Al₅O₁₂ (YAG) after longer times. Although the scale adherence of the yttrium-containing alloy was considerably better than the base alloys, spalling did occur that was attributed to the formation of the voluminous YAG particles that grew in a mushroom-like manner, lifting the protective scale off the substrate locally. The YAG particles formed primarily at grain boundaries in the substrate in which the yttrium originally existed as YNi₉. This intermetallic compound reacted to form Y₂O₃, liberating metallic nickel that subsequently reacted to form NiO or NiAl₂O₄ spinel or both. The Y₂O₃ reacted with aluminum to ultimately form the YAG mushrooms. Thorium did not form any mixed oxides; the only oxide involving thorium was ThO₂, which existed as small particles at the oxide-metal interface. A highly beneficial effect of the thoria particles in reducing film spalling was observed. Scale spalling in the base alloy was attributed to void formation at the oxide-metal interface, the voids forming by condensation of excess vacancies from the Kirkendall effect associated with fast back-diffusion, of nickel into the substrate as aluminum was preferentially oxidized and diffused slowly outward. The mechanism of improved scale adherence in the quaternary alloys was the elimination of voids by annihilation of the Kirkendall vacancies at vacancy sinks introduced by the noncoherent interfaces between yttrium and thorium-containing intermetallics or oxides or both.This work is based on a portion of the dissertation of Arun Kumar in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Engineering, University of California, Los Angeles.Supported by NASA-Ames under grant No. NGR 05-007-352.     

VILO: a rapid learning nearest-neighbor classifier for malware triage

VILO is a lazy learner system designed for malware classification and triage. It implements a nearest neighbor (NN) algorithm with similarities computed over Term Frequency $\times $ Inverse Document Frequency (TFIDF) weighted opcode mnemonic permutation features (N-perms). Being an NN-classifier, VILO makes minimal structural assumptions about class boundaries, and thus is well suited for the constantly changing malware population. This paper presents an extensive study of application of VILO in malware analysis. Our experiments demonstrate that (a) VILO is a rapid learner of malware families, i.e., VILO’s learning curve stabilizes at high accuracies quickly (training on less than 20 variants per family is sufficient); (b) similarity scores derived from TDIDF weighted features should primarily be treated as ordinal measurements; and (c) VILO with N-perm feature vectors outperforms traditional N-gram feature vectors when used to classify real-world malware into their respective families.     

Improving the performance of speaker and language identification tasks using unique characteristics of a class

In classification tasks, the error rate is proportional to the commonality among classes. In conventional GMM-based modeling technique, since the model parameters of a class are estimated without considering other classes in the system, features that are common across various classes may also be captured, along with unique features. This paper proposes to use unique characteristics of a class at the feature-level and at the phoneme-level, separately, to improve the classification accuracy. At the feature-level, the performance of a classifier has been analyzed by capturing the unique features while modeling, and removing common feature vectors during classification. Experiments were conducted on speaker identification task, using speech data of 40 female speakers from NTIMIT corpus, and on a language identification task, using speech data of two languages (English and French) from OGI_MLTS corpus. At the phoneme-level, performance of a classifier has been analyzed by identifying a subset of phonemes, which are unique to a speaker with respect to his/her closely resembling speaker, in the acoustic sense, on a speaker identification task. In both the cases (feature-level and phoneme-level) considerable improvement in classification accuracy is observed over conventional GMM-based classifiers in the above mentioned tasks. Among the three experimental setup, speaker identification task using unique phonemes shows as high as 9.56 % performance improvement over conventional GMM-based classifier.     

Two-stage database intrusion detection by combining multiple evidence and belief update

Insider threats have gained prominence and pose the most challenging threats to a database system. In this paper, we have proposed a new approach for detecting intrusive attacks in databases by fusion of information sources and use of belief update. In database intrusion detection, only intra-transactional features are not sufficient for detecting attackers within the organization as they are potentially familiar with the day-to-day work. Thus, the proposed system uses inter-transactional as well as intra-transactional features for intrusion detection. Moreover, we have also considered three different sensitivity levels of table attributes for keeping track of the malicious modification of the highly sensitive attributes more carefully. We have analyzed the performance of the proposed database intrusion detection system using stochastic models. Our system performs significantly better compared to two intrusion detection systems recently proposed in the literature.