Growth, studies of milled and irradiated crystalline samples of DBNT for macro-photonic and electro-mechano functionalities.

Single crystals of organic type of NLO crystalline material of DBNT - 8, 9-Dimethoxybenzo[b]naphtho [2,3-d] thiophene are proceeded to be grown by slow evaporation procedure and milled to micro scale and irradiated of Co-60 source of 100 Gy, 500 Gy and 5000 Gy for better scope of classification of system of the monoclinic type of DBNT-pure, micro and irradiated ones. The hardness study specifies the reverse indentation size effect (RISE) with work hardening coefficient above two of all DBNT specimen leads to the micro-tribological workings for springs with proper elastic parameters; the transmittance of DBNT of 5 specimens are 321 nm, 323 nm, 341 nm, 351 nm, and 352 nm for macro, micro, 100 Gy, 500 Gy, 5000 Gy. The photonic utility of identity for 3.86 eV and is 3.8629 eV by the transmittance data. The Non Linear Optical - NLO component this of 1.9, 1.94, 1.95, 1.96, 1.99 times that of KDP from which phase matching provision is enabled the influx property for the DBNT specimens is in the order of microns the (110) and (111) indexing represent for display device configuration. The dielectric behaviour of DBNT shows that polarization properly enabled for all categories by electrical performance, the abnormal variation is due to the vacancies created in the molecule by irradiation.

Isolation and characterization of agro-waste biomass sapodilla seeds as reinforcement in potential polymer composite applications.

Fillers or particulate fillers find a growing utilization as reinforcement material in polymer composites due to their ability to enhance the properties of the ensuing composites. The discarded seed in sapodilla fruit is available in abundant and the shell of the seed can be used as a reinforcing filler. The primary goal of this study is to extract and characterize the sapodilla seed shell powder (SSS) physically and chemically in order to assess its potential for reinforcement as a particulate filler in polymer composites. The sapodilla seed shell filler was characterized experimentally by Physio-chemical analysis, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and Energy dispersive X-ray analysis (EDAX). The morphology and the filler size were determined by Scanning electron microscopy (SEM) and Particle size analysis. The thermal degradation behaviour was evaluated by Thermogravimetric analysis (TGA).

Quantization Friendly MobileNet (QF-MobileNet) Architecture for Vision Based Applications on Embedded Platforms.

Deep Neural Networks (DNNs) have become popular for various applications in the domain of image and computer vision due to their well-established performance attributes. DNN algorithms involve powerful multilevel feature extractions resulting in an extensive range of parameters and memory footprints. However, memory bandwidth requirements, memory footprint and the associated power consumption of models are issues to be addressed to deploy DNN models on embedded platforms for real time vision-based applications. We present an optimized DNN model for memory and accuracy for vision-based applications on embedded platforms. In this paper we propose Quantization Friendly MobileNet (QF-MobileNet) architecture. The architecture is optimized for inference accuracy and reduced resource utilization. The optimization is obtained by addressing the redundancy and quantization loss of the existing baseline MobileNet architectures. We verify and validate the performance of the QF-MobileNet architecture for image classification task on the ImageNet dataset. The proposed model is tested for inference accuracy and resource utilization and compared to the baseline MobileNet architecture. The inference accuracy of the proposed QF-MobileNetV2 float model attained 73.36% and the quantized model has 69.51%. The MobileNetV3 float model attained an inference accuracy of 68.75% and the quantized model has 67.5% respectively. The proposed model saves 33% of time complexity for QF-MobileNetV2 and QF-MobileNetV3 models against the baseline models. The QF-MobileNet also showed optimized resource utilization with 32% fewer tunable parameters, 30% fewer MAC's operations per image and reduced inference quantization loss by approximately 5% compared to the baseline models. The model is ported onto the android application using TensorFlow API. The android application performs inference on the native devices viz. smartphones, tablets and handheld devices. Future work is focused on introducing channel-wise and layer-wise quantization schemes to the proposed model. We intend to explore quantization aware training of DNN algorithms to achieve optimized resource utilization and inference accuracy.

Efficiency of Single Site Phase Transfer Catalyst in Free Radical Polymerization of Butyl Methacrylate - A Kinetic Study

ABSTRACT The effectiveness of single site phase transfer catalyst- 2- benzoylethyldecyldimethylammonium bromide has been studied with the help of kinetics of free radical polymerization of butyl methacrylate. The radical polymerization was catalysed with single site phase transfer catalyst, initiated by water soluble potassium peroxydisulphate initiator in ethyl acetate / water biphasic media, under inert and unstirred condition at constant temperature, 60±1ºC. The dependence of rate of polymerization on various experimental conditions, different concentrations of monomer, initiator, and phase transfer catalyst was evaluated and effect of temperature as well as solvent polarity was determined. The order of the reaction with respect to monomer, initiator and phase transfer catalyst was found to be 1, 0.5 and 0.5 respectively. It was also observed that a slight increase in rate of polymerization as the polarity of solvents increased. A suitable kinetic mechanism has been suggested as per the investigational conditions. Molecular weight of the polybutyl methacrylate which has been polymerized bysingle site phase transfer catalyst was evaluated using gel permeation chromatographic technique.

Is anti-platelet therapy interruption a real clinical issue? Its implications in dentistry and particularly in periodontics.

The use of anti-platelet therapy has reduced the mortality and morbidity of cardiovascular disease remarkably. A considerable number of patients presenting before a dentist or periodontist give a history of anti-platelet therapy. A clinical dilemma whether to discontinue the anti-platelet therapy or continue the same always confronts the practitioner. Diverse opinions exist regarding the management of such patients. While one group of researchers advise continuation of anti-platelet therapy rather than invite remote, but possible, thromboembolic events, another group encourages discontinuation for variable periods. This study aims at reviewing the current rationale of anti-platelet therapy and the various options available to a clinician, with regard to the management of a patient under anti-platelet therapy. Current recommendations and consensus favour no discontinuation of anti-platelet therapy. This recommendation, however, comes with a rider to use caution and consider other mitigating factors as well. With a large number of patients giving a history of anti-platelet therapy, the topic is of interest and helps a clinician to arrive at a decision.