A UML-driven ASIC design methodology aided by an automated UML-SystemC translator

Master'sMASTER OF ENGINEERIN

Higher order antibunching in intermediate states

Since the introduction of binomial state as an intermediate state, different intermediate states have been proposed. Different nonclassical effects have also been reported in these intermediate states. But till now higher order antibunching or higher order subpoissonian photon statistics is predicted only in one type of intermediate state, namely shadowed negative binomial state. Recently we have shown the existence of higher order antibunching in some simple nonlinear optical processes to establish that higher order antibunching is not a rare phenomenon (J. Phys. B 39 (2006) 1137). To establish our earlier claim further, here we have shown that the higher order antibunching can be seen in different intermediate states, such as binomial state, reciprocal binomial state, hypergeometric state, generalized binomial state, negative binomial state and photon added coherent state. We have studied the possibility of observing the higher order subpoissonian photon statistics in different limits of intermediate states. The effect of different control parameters have also been studied in this connection and it has been shown that the depth of nonclassicality can be tuned by controlling various physical parameters.Comment: 12 Pages LaTeX 2e, 11 figure

Anticancer efficacy of methanolic extracts of some medicinal plants from Jammu region, Jammu & Kashmir, India

51-56The methanolic extracts from ten medicinal plants (Alstonia scholaris, Azadirachta indica, Calotropis gigantea, Emblica officinalis, Mentha citrate, Mentha piperita, Musa paradisiaca, Olea europaea, Punica granatum and Trachyspermum ammi selected from Jammu region, Jammu & Kashmir, India, were evaluated against five human cancer cell lines from four different origins, viz., A-549 (lung), HCT-116 (colon), MCF-7 (breast), PC-3 (prostate) and T-47D (breast) at the concentration of 100 μg/mL using sulphorhodamine blue (SRB) assay. A. indica, O. europaea, M. piperita and M. paradisiaca showed in vitro cytotoxic effect against one or the other human cancer cell line. The methanolic extract of stem and leaves of C. gigantea showed significant cytotoxic activity against four human cancer cell lines from four different tissues. The methanolic extract showed 82-90% growth inhibition at 50 μg/mL and 73-78% growth inhibition at 10 μg/mL against lung, colon and prostate cancer cells. However, 1 μg/mL the extract displayed only 52% growth inhibition against lung (A-549) and prostate (PC-3) cancer cells. The results have shown that C. giagantea may have potential for development of anticancer agents, especially for lung, colon and prostate cancer cells

Publication bias and the tourism-led growth hypothesis

This study attempts to solve the publication bias suggested by recent review articles in the tourism-growth literature. Publication bias is the tendency to report favourable and significant results. Method and data triangulation, and the Solow-Swan model are applied. A sample from 1995 to 2018 is considered with Tonga as a case study. The approach consists of multiple methods, data frequencies, exchange rates, structural breaks, and an overall tourism index developed using principal component analysis (PCA). Consistent results across these dimensions are obtained with the PCA models. Tourism has small, positive, and statistically significant economic growth effects. Theoretically consistent values of the capital share and exchange rates are obtained. The results indicate the importance of multiple methods and the overall tourism index in assessing the tourism-growth relationship and minimising publication biases. The practical implication is the provision of robust elasticity estimates and better economic policies

Pixel-based long-term (2001–2020) estimations of forest fire emissions over the Himalaya

Forest/wildfires have been one of the most notable severe catastrophes in recent decades across the globe, and their intensity is expected to rise with global warming. Forest fire contributes significantly to particulate and gaseous pollution in the atmosphere. This study has estimated the pixel-based emissions (CO, CO2, CH4, NOx, SO2, NH3, PM2.5, PM10, OC, and BC) from forest fires over the Himalaya (including India, Nepal, and Bhutan). The MODIS-based burned area (MCD64A1), Land Use Land Cover (LULC; MCD12A1), NDVI (MOD13A2), percentage tree cover (MOD44A6), gridded biomass, and species-wise emissions factors were used to estimate the monthly emissions from forest fires over the last two decades (2001–2020). A bottom-up approach was adopted to retrieve the emissions. A substantial inter-annual variation of forest burn area was found over the western, central (Nepal), and eastern Himalaya (including Bhutan). The eastern Himalaya exhibited the highest average annual CO2 emission, i.e., 20.37 Tg, followed by Nepal, 15.52 Tg, and the western Himalaya, 4.92 Tg. Spatially, the higher CO2 (0.01–0.02 Tg year−1/km2) and CO (0.007–0.002 Tg year−1/km2) emissions were detected along the south-eastern parts of the eastern Himalaya, southern regions of Nepal, and south-eastern parts of the western Himalaya. The trend of forest fire emissions in 2001–2010 was significantly positive, while in the next decade (2011–2020) a negative trend was recorded. The estimated pixel-based emission and Global Fire Emission Dataset (GFEDv4.1s) data demonstrated a promising association with a correlation coefficient (r) between 0.80 and 0.93. An inventory of forest fire emissions over long-term periods can be helpful for policymakers. In addition, it helps to set guidelines for air quality and atmospheric transport modelling and to better understand atmospheric pollution over the Himalayan and associated regions

Pixel-Based Long-Term (2001–2020) Estimations of Forest Fire Emissions over the Himalaya

Forest/wildfires have been one of the most notable severe catastrophes in recent decades across the globe, and their intensity is expected to rise with global warming. Forest fire contributes significantly to particulate and gaseous pollution in the atmosphere. This study has estimated the pixel-based emissions (CO, CO2, CH4, NOx, SO2, NH3, PM2.5, PM10, OC, and BC) from forest fires over the Himalaya (including India, Nepal, and Bhutan). The MODIS-based burned area (MCD64A1), Land Use Land Cover (LULC; MCD12A1), NDVI (MOD13A2), percentage tree cover (MOD44A6), gridded biomass, and species-wise emissions factors were used to estimate the monthly emissions from forest fires over the last two decades (2001–2020). A bottom-up approach was adopted to retrieve the emissions. A substantial inter-annual variation of forest burn area was found over the western, central (Nepal), and eastern Himalaya (including Bhutan). The eastern Himalaya exhibited the highest average annual CO2 emission, i.e., 20.37 Tg, followed by Nepal, 15.52 Tg, and the western Himalaya, 4.92 Tg. Spatially, the higher CO2 (0.01–0.02 Tg year−1/km2) and CO (0.007–0.002 Tg year−1/km2) emissions were detected along the south-eastern parts of the eastern Himalaya, southern regions of Nepal, and south-eastern parts of the western Himalaya. The trend of forest fire emissions in 2001–2010 was significantly positive, while in the next decade (2011–2020) a negative trend was recorded. The estimated pixel-based emission and Global Fire Emission Dataset (GFEDv4.1s) data demonstrated a promising association with a correlation coefficient (r) between 0.80 and 0.93. An inventory of forest fire emissions over long-term periods can be helpful for policymakers. In addition, it helps to set guidelines for air quality and atmospheric transport modelling and to better understand atmospheric pollution over the Himalayan and associated regions

Morphological and morphometric analysis of lung: A cadaveric study

Background: The lung is a respiratory organ in which steady development begins during the embryonic period at 0–7 weeks’ gestation and continues into early childhood. Cardiothoracic surgeries and procedures such as lobectomy, segmental resection of bronchoscopy, require a thorough knowledge of the anatomy of the lung. Study of length, fissures and lobes of the lung can guide the surgeons for the above procedures and help them to prevent undue complications during surgery. Many variations are noted by researchers till date in both the lungs in regards to length, breadth, fissures, and lobes. In the current study, we have also observed variations in fissures of lung. Aims and Objectives: To study the normal length, breadth, and thickness of both sides of lungs, variations in the length, breadth, and thickness of both sides of the lungs. To study the normal fissures, lobes and their variations, of both right and left lungs, and also to study the number of bronchi, pulmonary artery, and pulmonary vein. Materials and Methods: 50 Right and 50 left lungs were obtained from embalmed cadavers, used for dissection in the Department of Anatomy, King George’s Medical University, Lucknow, UP, by using measuring tape and measuring scale. Photography was done by a DSLR camera. Results: The left lung shows maximum variations in the hilum. Out of 50 left lungs, 6 showed the absence of oblique fissures, 2 lungs had 2 arteries, 2 lungs had 2 Veins, and 1 had 2 bronchi. Out of 50 right lungs, 2 lungs showed 2 arteries, 2 lungs had 2 veins, and 2 had 3 bronchi. Conclusion: Knowledge of normal measurements of both sides of the lungs and their variations may help cardiothoracic surgeons avoid complications during surgery and it may help radiologists resolve uncertain radiographic findings

Monitoring land use/land cover change and high-altitude vegetation trends along with their climatic controls across the Central and Eastern Himalayas

Monitoring the spatial pattern of vegetation growth trends is important in the Central and Eastern Himalayas as many ecosystems in the Himalayas are sensitive to climatic change. The human-induced land use/land cover (LULC) changes are the potential driving forces for changes in ecosystems. This study employed MODIS (MCD12Q1) product to quantify the spatial pattern of LULC from 2001 to 2019. The long-term vegetation datasets (NDVI3g) (1982-2015) were utilized to estimate vegetation trends and climatic variables (e.g., precipitation, soil moisture, temperature, solar radiation) trends. The Mann-Kendall (τ) test and Theil-Sen’s slope were deployed for computing trends over vegetation (e.g., forests, shrublands, savannas, croplands, and grassland). The results showed a prominent large-scale greening trend of croplands (77% of area) and forests including shrublands, savannas, and grassland (42% of area), mostly across the Central (Nepal) Himalayas. The browning trends of forests were also evident, especially over the Eastern Himalaya (Bhutan). The greening trends of vegetation were mainly associated with climatic factors like precipitation and soil moisture, and the corresponding correlation coefficients (r) were 0.69 and 0.28, respectively at p-value ̼ 0.001. Additionally, temperature control on vegetation was found at higher elevation zones of the Central and Eastern Himalayas (r = 0.93, p-value ̼ 0.001), whereas browning trends of vegetation occurred due to temperature-induced moisture stress along with the decreasing trends of solar radiation, and a profound impact was seen over Bhutan. Human-induced land-use change (e.g., shifting cultivation, deforestation) was also attributed to declining vegetation growth since an increase in built-up area was noticed that mainly replaced the croplands and barren land over the study regions. Therefore, the quantification of vegetation trends is important for understanding and managing agriculture and forests ecosystems located in the high-altitude zone, and attention from ecologists and policymakers is required to monitor and manage vegetation in the Himalayas