5,138 research outputs found
Synthesis and Biological Activity of Some Triazolothiadiazoles
The synthesis of a series of novel 3-pyridyl-6-aryl-s-triazolo[3,4-b]-[1,3,4]-thiadiazoles is described. Fourteen new compounds were synthesized and characterized by spectral and elemental analyses. Some compounds were screened for antibacterial activity against S. aureus, E. coli, B. subtilis and P. aeruginosa. Compounds containing aryl substituents at position 6 and the 1,2,4-triazole moiety at position 1 or 2 showed reasonable antibacterial activity.Keywords: 1,2,4-Triazole, thiadiazole, potassium dithiocarbazinate, hydrazine hydrate, antibacterial activit
Numerical simulation of a super cyclonic storm, Orissa 1999: Impact of initial conditions
Numerical simulations are performed using the Penn State University/ National Center for Atmospheric Research Mesoscale Model (MM5) to study the impact of initial conditions on the super cyclone which hit the coast of Orissa in 1999. Because analysis of the cyclone's circulation was inadequate in the initial fields owing to the coarse resolution of the operational analysis systems and sparse oceanic data coverage, synthetic vortex data were generated using empirical relations and used in the analysis. Four-dimensional data assimilation is performed in order to assimilate the synthetic vortex in the initial stage to the model. Considerable improvement in the track is obtained by using the synthetic vortex. With better specification of the initial vortex structure, the model successfully simulated the typical tropical cyclone characteristics, such as asymmetries in the wind field: the strongest winds occurred in the east and close to the cyclone's centre, strong wind gradients were found between the centre and the maximum wind region, and there was a slow decrease in wind speed up to the middle troposphere. Despite failing to produce the intense pressure drop observed for this cyclone, the model shows much better cyclone development with enhanced initial condition than the analysis
Characterization of water uptake and distribution in chickpea (Cicer arietinum L.) seeds during germination by NMR spectroscopy
Experiments were conducted to characterize the changes in water status during imbibition by nuclear magnetic resonance (NMR) spectroscopy in chickpea seeds exposed to static magnetic fields of 100 mT for 1 h. Water uptake during seed germination showed three phases with rapid initial hydration phase I, followed by lag phase II and steady hydration phase III. Comparative analysis of the hydration pattern showed that water uptake was more in phase II and III in magnetically exposed than unexposed seeds. The longitudinal relaxation time (T1) of seed water showed significantly higher values and hence higher molecular mobility of cellular water in magnetically exposed seeds as compared to unexposed seeds. Analysis of transverse relaxation time (T2) revealed a three component of water in germinating chickpea seeds. Interesting observation found in this study was the early appearance of hydration water with least mobility and higher values of relaxation times of cytoplasmic bulk water and hydration water in magnetically treated over untreated seeds. Early hydration of macromolecules, membranes, greater molecular mobility of bulk and hydration water fractions in magnetically exposed seeds may be responsible for quicker germination and appearance of early seedling vigour in chickpea. Activities of enzymes related to germination process such as α-amylase, dehydrogenase and protease were higher in magnetically exposed seeds as compared to unexposed seeds. Moreover, a significant correlation between the relaxation time of cytoplasmic bulk water and the activities of germination related enzymes supported our conclusion that this fraction of water plays a major role in the metabolism of germination process.Key words: Cicer arietinum L., imbibition, nuclear magnetic resonance, longitudinal relaxation time (T1), transverse relaxation time (T2), germination enzymes
Diversification and its Determinants: A Search for Alternative Income and Agricultural Development in Eastern India
The eastern region of India, comprising the states of Bihar, Jharkhand, Assam, Odisha and West Bengal, is one of the most backward regions of the nation. This region occupies about 21.85% of geographical area and supports 34% of the population of the country. Agriculture is the mainstay of economy in the region. About 67% of the cultivators belong to marginal group and over 75% of their earnings are utilized to ensure their food security. Issues related to diversification have been discussed by researchers for a long period and they have been trying to relate diversification to the developmental prospects and various factors responsible for it. Despite this, the eastern region has rich natural resources i.e. fertile land, abundant ground water (145.12 BCM), however, the pace of agricultural development is very slow. In the present study, an attempt has been made to measure diversification using Herfindahl-Hirschman index, known as the most popular method, it was used to measure extent of diversification. The regression model was applied to access the determinants of crop diversification in the region. The study is based on secondary data collected from various published sources from 2001-02 to 2014-15 i.e. for a period of 14 years. The results revealed that in the region, the diversification for the study period was observed very low in almost all the states under study and for the eastern region as a whole. The study pinpointed the fact that despite the rich natural resources, its potential could not be harnessed from the point of view of improving agricultural productivity, poverty alleviation and livelihood improvement. Strengthening of crop diversification depends on market and taking care of production risks through technological support, quality input supply, more insurance coverage and establishment of modern storage-processing centres in the region. Keeping in view the rich natural resources and hidden agricultural development opportunities in the region, government has already taken initiative for Second Green Revolution from the region, however a strong policy push up towards instilling confidence among the farming community is needed in this direction
Diversification and its Determinants: A Search for Alternative Income and Agricultural Development in Eastern India
The eastern region of India, comprising the states of Bihar, Jharkhand, Assam, Odisha and West Bengal, is one of the most backward regions of the nation. This region occupies about 21.85% of geographical area and supports 34% of the population of the country. Agriculture is the mainstay of economy in the region. About 67% of the cultivators belong to marginal group and over 75% of their earnings are utilized to ensure their food security. Issues related to diversification have been discussed by researchers for a long period and they have been trying to relate diversification to the developmental prospects and various factors responsible for it. Despite this, the eastern region has rich natural resources i.e. fertile land, abundant ground water (145.12 BCM), however, the pace of agricultural development is very slow. In the present study, an attempt has been made to measure diversification using Herfindahl-Hirschman index, known as the most popular method, it was used to measure extent of diversification. The regression model was applied to access the determinants of crop diversification in the region. The study is based on secondary data collected from various published sources from 2001-02 to 2014-15 i.e. for a period of 14 years. The results revealed that in the region, the diversification for the study period was observed very low in almost all the states under study and for the eastern region as a whole. The study pinpointed the fact that despite the rich natural resources, its potential could not be harnessed from the point of view of improving agricultural productivity, poverty alleviation and livelihood improvement. Strengthening of crop diversification depends on market and taking care of production risks through technological support, quality input supply, more insurance coverage and establishment of modern storage-processing centres in the region. Keeping in view the rich natural resources and hidden agricultural development opportunities in the region, government has already taken initiative for Second Green Revolution from the region, however a strong policy push up towards instilling confidence among the farming community is needed in this direction
Low-latency vision-based fiducial detection and localisation for object tracking
Real-time vision systems are widely-used in construction and manufacturing industries. A significant proportion of computational resources of such systems is used in fiducial identification and localisation for motion tracking of moving targets. The requirement is to localise a pattern in an image captured by the vision system precisely, accurately, and with a minimum available computation time. As such, this paper presents a class of patterns and, accordingly, proposes an algorithm to fulfil the requirement. Here, the patterns are designed using circular patches of concentric circles to increase the probability of detection and reduce cases of false detection. In the detection algorithm, the image captured by the vision system is first scaled down for computationally-effective processing. The scaled image is then separated by filtering only the colour components, which are made up of outer circular patches in the proposed pattern. A blob detection algorithm is then implemented for identifying inner circular patches. The inner circles are then localised in the image by using the colour information obtained. Finally, the localised pattern, along with the camera and distortion matrix of the vision system, is applied in a perspective-n-point solving algorithm to estimate the marker orientation and position in the global coordinate system. Our system shows significant enhancement in performance of fiducial detection and identification and achieves the required latency of less than ten milliseconds. Thus, it can be used for infrastructure monitoring in many applications that involve high-speed real-time vision systems
Root Coverage Using GEM 21S® and Collagen Membrane Predicting Favourable Treatment Outcomes: A Case Report
U dosadašnjim istraživanjima istaknuto je da humani rekombinantni čimbenik rasta iz trombocita,
kao snažna bjelančevina za cijeljenje rane, može poboljšati klinički nalaz epitelnog pričvrstka
i regeneraciju parodontnog tkiva kada se pomiješa s osteoindiktivnim nosačem. U ovom prikazu
procijenjen je klinički ishod primjene rhPDGF-BB-a s beta-trikalcijevim fosfatom (GEM 21S®) i kolagenom membranom u terapiji recesijskih defekata pomoću koronarno odignutog režnja. Pacijenti su nakon zahvata bili pod nadzorom te se pratilo cijeljenje nakon jednog, tri i šest mjeseci, a primarni je pokazatelj bila dubina recesije. Ovaj pionirski rad je otkrio povoljan klinički i estetski odgovor tkiva na GEM 21S® i kolagene membrane jer su u dvama kliničkim slučajevima korijeni nakon zahvata bili potpuno prekriveni.On mixing with an osteoconductive scaffold, recombinant human platelet derived growth factor
(rhPDGF-BB), a potent wound-healing protein, has been shown to promote clinical attachment
gain and regeneration of the periodontium. This human case report evaluated the clinical outcome
of rhPDGF-BB with beta tricalcium phosphate (GEM 21S®) and a collagen membrane in the treatment of recession defects using coronally advanced flap. Patients were followed postoperatively,
and healing was evaluated at 1, 3 and 6 months, with recession depth as the primary outcome measure. This pioneer case report revealed a favourable tissue response to GEM 21S® and collagen membrane from both clinical and aesthetic point of view showing full root coverage in two cases
Emerging prospects of vitamin D3 in metabolic syndrome: A proof of concept (POC) approach targeting inflammation.
Roboteye technology for thermal target tracking using predictive control
© ISARC 2018 - 35th International Symposium on Automation and Robotics in Construction and International AEC/FM Hackathon: The Future of Building Things. All rights reserved. Thermal cameras are widely used in the fatigue analysis of mechanical structures using the thermoelastic effect. Nevertheless, such analysis is hampered due to blurry images resulting from the motion of structure-under-test. To address the issue this paper presents a system that utilizes robotic vision and predictive control. The system comprises of a thermal camera, a vision camera, a RobotEye, and a fiducial detection system. A marker is attached to a thermal target in order to estimate its position and orientation using the proposed detection system. To predict the future position of the thermal moving object, a Kalman filter is used. Finally, the Model Predictive Control (MPC) approach is applied to generate commands for the robot to follow the target. Results of the tracking by MPC are included in this paper along with the performance evaluation of the whole system. The evaluation clearly shows the improvement in the tracking performance of the development for thermal structural analysis
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