Center for Environmental Sciences & Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

In this study, land use land cover (LULC) map of 1987, 1997 and 2007 derived from digital satellite images of Landsat-5 TM of 1987, IRS-1C LISS III images of 1997 and IRS-P6 LISS III images of 2007, respectively, to monitor and predict future LULC scenario. Future LULC has been predicted using CA Markov Model for 2017, 2027 and 2050 by using LULC map of 1987 & 1997, 1997 & 2007 and 1987 & 2007. The period (image interval / time steps) between different predictions years (i.e., 2017, 2027 and 2050 using 1987 & 1997, 1997 & 2007 and 1987 & 2007 LULC) are 10, 20, 30, 43 and 53 years. The number of iteration was based on the time steps i.e., iterations 20 to predict LULC for 2017 (prediction from 1997 to 2017); iterations 30 for 2027 (prediction from 1997 to 2027); iterations 53 for 2050 (prediction from 1997 to 2050). The relationships (correlations) of quantity of predicted LULC found strong positive correlation for three time periods (0.981, 0.984, 0.966 for 2017, 0.981, 0.984, 0.975 for 2027, 0.977, 0.987, and 0.980 for 2050) and established that there are almost no effect in quantity of prediction results of different time steps (iterations) images and time intervals are used to predict future LULC. The predicting location of predicted LULC of 2017, 2027 & 2050 for the three cases showing positive correlation, where r are 0.728, 0.758 and 0.708 for 2017-when relatively less time steps used; r are 0.696, 0.761 and 0.674 for 2027-when medium time steps used; r are 0.599, 0.721, 0.574 for 2050-when more time steps used. The analysis established that although there are nearly no effect on quantitative prediction results but have small impact of iterations (time steps) and time intervals on spatial distribution of predicted LULC results. © 2020 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives.

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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Ca markov modeling of land use land cover change predictions and effect of numerical iterations, image interval (time steps) on prediction results

In this study, attempts has been made to find out cellular automata (CA) contiguity filters impacts on Land use land cover change predictions results. Cellular Automata (CA) Markov chain model used to monitor and predict the future land use land cover pattern scenario in a part of Brahmaputra River Basin, India, using land use land cover map derived from multi-temporal satellite images. Land use land cover maps derived from satellite images of Landsat MSS image of 1987 and Landsat TM image of 1997 were used to predict future land use land cover of 2007 using Cellular Automata Markov model. The validity of the Cellular Automata Markov process for projecting future land use and cover changes calculates using various Kappa Indices of Agreement (Kstandard) predicted (results) maps with the reference map (land use land cover map derived from IRS-P6 LISS III image of 2007). The validation shows Kstandard is 0.7928. 3x3, 5x5 and 7x7 CA contiguity filters are evaluated to predict LULC in 2007 using 1987 and 1997 LULC maps. Regression analysis have been carried out for both predicted quantity as well as prediction location to established the cellular automata (CA) contiguity filters impacts on predictions results. Correlation established that predicted LULC of 2007 and LULC derived from LISS III Image of 2007 are strongly correlated and they are slightly different to each-other but the quantitative prediction results are same for when 3x3, 5x5 and 7x7 CA contiguity filters are evaluated to predict land use land cover. When we look at the quantity of predicted land use land cover of 2007 area statistics are derived by using 3x3, 5x5 and 7x7 CA contiguity filters, the predicted area statistics are the same. Other hands, the spatial difference between predicted LULC of 2007 and LULC derived from LISS III images of 2007 is evaluated and they are found to be slightly different. Correlation coefficient (r) between predicted LULC classes and LULC derived from LISS III image of 2007 using 3x3, 5x5, 7x7 are 0.7906, 0.7929, 0.7927, respectively. Therefore, the correlation coefficient (r) for 5x5 contiguity filters is highest among 3x3, 5x5, and 7x7 filters and established/produced most geographically / spatially distributed effective results, although the differences between them are very small. © 2020 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives.

Cellular automata (CA) contiguity filters impacts on CA markov modeling of land use land cover change predictions results

This research paper focuses on providing an algorithm by which (Unmanned Aerial Vehicles) UAVs can be used to provide optimal routes for agricultural applications such as, fertilizers and pesticide spray, in crop fields. To utilize a minimum amount of inputs and complete the task without a revisit, one needs to employ optimized routes and optimal points of delivering the inputs required in precision agriculture (PA). First, stressed regions are identified using VegNet (Vegetative Network) software. Then, methods are applied for obtaining optimal routes and points for the spraying of inputs with an autonomous UAV for PA. This paper reports a unique and innovative technique to calculate the optimum location of spray points required for a particular stressed region. In this technique, the stressed regions are divided into many circular divisions with its center being a spray point of the stressed region. These circular divisions would ensure a more effective dispersion of the spray. Then an optimal path is found out which connects all the stressed regions and their spray points. The paper also describes the use of methods and algorithms including travelling salesman problem (TSP)-based route planning and a Voronoi diagram which allows applying precision agriculture techniques. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Drones

An approach for route optimization in applications of precision agriculture using uavs

Future perspectives and challenges in hyperspectral remote sensing

Revisiting hyperspectral remote sensing: origin, processing, applications and way forward

Preconditioning is a well-documented strategy that induces hepatic protection, renal protection, cardioprotection and neuroprotection but its mechanism still remains to be elucidated. Hence, the present study investigated the protective mechanism underlying pain attenuating effects of vincristine-preconditioning in chemotherapeutic agent-induced neuropathic pain. Neuropathic pain was induced by administration of vincristine (50 µg/kg, i.p.) for 10 days in rats. Vincristine-preconditioning was induced by administration of vincristine (2, 5 and 10 µg/kg, i.p) for 5 days before administration of pain-inducing dose of vincristine (50 µg/kg, i.p.). Vincristine-preconditioning (10 µg/kg, i.p) for 5 days significantly reduced vincristine (50 µg/kg, i.p.) induced pain-related behaviors including paw cold allodynia, mechanical hyperalgesia and heat hyperalgesia. However, vincristine (2 and 5 µg/kg, i.p) did not significantly ameliorate the vincristine (50 µg/kg, i.p.) induced neuropathic pain in rats. Furthermore, to explore the involvement of calcium channels in pain attenuating mechanism of vincristine-preconditioning, T-type calcium channel blocker, ethosuximide (100 and 200 mg/kg, i.p.) and L-type calcium channel blocker, amlodipine (5 and 10 mg/kg, i.p.) were used. Pretreatment with T-type calcium channel blocker, ethosuximide significantly abolished vincristine-preconditioning-induced protective effect. However, pretreatment with L-type calcium channel blocker, amlodipine did not alter vincristine-preconditioning-induced pain-related behaviors. This indicates that vincristine-preconditioning has protective effect on pain-related parameters due to opening of calcium channels, particularly T-type calcium channels that lead to entry of small magnitude of intracellular calcium through these channels and prevent the deleterious effects of high-dose vincristine.

Fundamental and Clinical Pharmacology

Pain attenuating actions of vincristinet-preconditioning in chemotherapeutic agent-induced neuropathic pain: key involvement of T-type calcium channels

Galgotias University

Land Use/Cover Change Detection in the Western Part of Upper IndoGangetic Plains of Uttar Pradesh, India-A Geospatial Approach

Aim of the study: The current study was aimed to investigate the neuropathic pain attenuating mechanism of pregabalin using chronic constriction injury (CCI) model in rats. Material and Methods: The sciatic nerve was ligated by placing four loose ligatures around it to induce neuropathic pain. The pain development in terms of cold allodynia, mechanical hyperalgesia and heat hyperalgesia was assessed on the 7th and 14th day after surgery, using acetone drop, pinprick and hot plate tests. On the 14th day after the injury, pain parameters were assessed 30 minutes after administration of pregabalin (30 mg/kg) and sodium nitroprusside (5 mg/kg) in CCI-subjected rats. Results: CCI led to induction of neuropathic pain, which was more prominent on 14th day in comparison to 7th day. A single administration of pregabalin and sodium nitroprusside on 14th day, markedly reduced pain parameters and increased serum nitrite levels. Pretreatment with L-NAME abolished neuropathic pain attenuating effects of pregabalin suggesting that pregabalin may increase the levels of nitric oxide to mitigate neuropathic pain. Pretreatment with naloxone significantly abrogated pain attenuating effects of pregabalin and sodium nitroprusside in CCI-subjected rats suggesting that pregabalin and nitric oxide-mediated analgesic action are mediated through release of endogenous opioids. Moreover, naloxone failed to modulate pregabalin-induced increase in nitric oxide levels suggesting that the opioid system does not control the nitric oxide levels and opioids may be downstream modulators of nitric oxide. Conclusion: Pregabalin may increase the release of nitric oxide, which may increase the release of endogenous opioids to attenuate neuropathic pain in CCI subjected rats.

International Journal of Neuroscience

Investigating the possible pain attenuating mechanisms of pregabalin in chronic constriction injury-induced neuropathic pain in rats

Neuropathic pain is a chronic pain state caused by injury of the nervous system and there are various conditions associated with it such as diabetic neuropathy, postherpetic neuralgia, cancer pain, trigeminal neuralgia, cervical radiculopathy and anticancer and anti-HIV-induced neuropathic pain. The pathophysiological role of voltage-gated T-type calcium channels in neuropathic pain has been well documented. ABT-639 is a peripherally acting, selective T-type calcium channel blocker and it is shown to efficiently reduce nociceptive and neuropathic pain in rats in multiple models. However, three clinical studies exploring the role of single dose or multiple doses of ABT-639 (100 mg) in diabetic neuropathy have not found significant pain-attenuating actions. The present review discusses the unsuccessful clinical trials of peripherally acting ABT-639 in patients with diabetic neuropathy.

Journal of Pharmaceutical Negative Results

Unsuccessful story of ABT-639 in neuropathic pain in different phases of clinical trials

The objective of this research is to identify species, provide spatial distribution of the species and estimate the biomass in the mangrove Forest, Bhitarkanika India. Mangrove ecosystems play an important role in regulating carbon cycling, thus having a significant impact on global environmental change. Extensive studies have been conducted for the estimation of mangrove species identification and biomass estimation. However, estimation at a regional level with species-wise biomass distribution has been insufficiently investigated in the past because either research focuses on the species distribution or biomass assessment. Study shows that good relationship has been achieved between stem volume (field measured data) and Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from satellite image and further these two indices are employed to estimate the biomass in the study site. Three models- linear, logarithmic and polynomial (second degree) are used to estimate biomass derived from EVI and NDVI. The hyperspectral data (spatial resolution ~ 30 m) is utilised to identify ten mangrove plant species. We have prepared the spatial distribution map of these species using spectral angle mapper. We have also generated mangrove species-wise biomass distribution map of the study site along with areal coverage of each species. The results indicate that the Sonneratia apetala Buch.-Ham. and Cynometra iripa Kostel has the highest biomass among all ten identified species, 643.12 Mg ha−1 and 652.14 Mg ha−1. Our study provided a positive relationship between NDVI, EVI, and the estimated biomass of Bhitarkanika Forest Reserve Odisha India. The study finds a similar results for both NDVI and EVI derived biomass, while linear regression has more significant results than the polynomial (second degree) and logarithmic regression derived biomass. The polynomial is found slightly better than the logarithmic when using the EVI as compared to NDVI derived biomass. The spatial distribution of species-wise biomass map obtained in this study using both, EVI and NDVI could be used to provide useful information for biodiversity assessment along with the sustainable solutions to different problems associated with the mangrove forest biodiversity. Thus, biomass assessment of larger regions can be achieved by utilization of remote sensing based indices as concluded in the present study. © 2019, Springer Nature B.V.