Informatics Publishing Limited

R. B. S. Kushwah , V. Kumar

Abstract

The term Biodiversity means the variety and variability among living organisms from all sources and ecosystems on the earth. It includes diversity within species, between species and of ecosystems. Classification is an essential process in our daily lives and a necessary tool for our survival. For example, we need to know which plant, animal, fungi are useful and which are poisonous or dangerous. It is hard to define Biodiversity in mathematical terms. Hence, the 'Biodiversity indices' are used for the purpose. The Shannon-Wiener Biodiversity Index, based on the proportionate abundance of the species, provides an alternate approach to the assessment of Biodiversity. Attempt has been made for the first time in the eight Pas of Madhya Pradesh, following standard sample techniques and formulae, to compute Biodiversity indices in order to find the present status of flora. The value of Shannon-Wiener Biodiversity Indices and Index of Evenness has been computed. The maximum value (2.505, 2.511) was found for Madhav National Park followed by Satpura National Park. The minimum value (1.717,1.763) was found for Pachmarhi Wildlife Sanctuary. The main recommendations of the study are: (1) Demarcation of the 'Biodiversity zone' in each Pas and its conservation; (2) The areas with lower Biodiversity indices need to be given more attention for protection and conservation; (3) 'Eco-development planning' with the active involvement of local people for each PA needs to be adopted along with the village-micro-planning, and (4) The high tourist pressure in PWS, SNP, BNP, RWS and SDS needs to be regulated by 'Eco-tourism planning' in these PAs.

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R. B. S. Kushwah , V. Kumar

Abstract

Attempts have been made for the first time to workout the biodiversity indices for flora in the four Pas, i.e., the Bandhavgarh (BNP), Indravati (lNP), Madhav (MNP), and Satpuda (SNP) National Parks of Madhya Pradesh following standard sampling techniques and formulae. The values of Shannon-Wiener biodiversity indices as computed are found to be 2.508, 2.226, 1.842 and 1.815 respectively for MNP, SNP, INP and BNP. The values of the index of evenness have also been computed which are 0.753,0.668,0.581 and 0.581 respectively for MNP, SNP, INP and BNP. The highest t.value and degree of freedom (df) found for INP while lowest in MNP which reveals that the two types of the selected forest sites (areas) are significantly different upto certain extent in terms of the diversity of dominant species in INP, while not in case of MNP. Thus the areas of these PAs with lower diversity indices needed to be given more attention for protection and conservation of biodiversity. In fact, these areas being peripheral to territorial divisions are more affected by the biotic pressures from the adjoining villages which need to be minimized. Thus the study is not only of academic interest but relevant for management of the Protected Areas.

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Praveen Kumar Verma ¹, Niren Das ¹, P. K. Kaushik ¹, V. Kumar ², Alok Yadav ²

Affiliations
1 Rain Forest Research Institute Deovan Sotai Ali, Post Box # 136, Jorhat -785001 (Assam), IN
2 Environment Management, ICFRE, Dehradun, Uttarakhand, IN

Abstract

Guadua angustifolia Kunth. tree is a potential resource as structural and ornamental building material due to its high mechanical strength. The air layering of side branches of G. angustifolia using dry Sphagnum khasinum moss as substrate has initiated early ischolar_maining in rainy season compared to winter season as well as control conditions.

Keywords

Air-layering, Guadua angustifolia, Rooting, Vegetative Propagation

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D. J. Das ¹, V. Kumar , H. R. Bora , P. K. Verma , P. Gogoi , G. Gogoi , N. K. Vasu ²

Affiliations
1 Rain Forest Research Institute, Jorhat-785001, Assam, IN
2 Kaziranga National Park, Bokakhat, Assam, IN

Abstract

Precise mapping of Kaziranga National Park (KNP), the natural world heritage site, is the prime objective of this paper. High resolution Indian remote sensing satellites including IRS P6 Panchromatic and LISS 4 image, with 2.5 m and 5.8 m spatial resolution respectively, were used for the same along with GPS and extensive field survey. A theme based hybrid approach was followed for classification of digital remote sensing images. The overall classification accuracy was estimated to be 91.7% where as K value implies that the classification process was avoiding 89.9% errors of a hat completely random classification. The Eastern alluvial grassland is found to be the predominant vegetation type which occupies 50.6% of the total park area. Semi-evergreen and moist mixed deciduous forests together occupy 21.8% of the total area followed by short grass (7.7 %). A substantial area (11.7%) was found to be eroded in to the river Brahmaputra and as a result core area of the park is found to be decreased when compared with previous assessments.

Keywords

Kaziranga, Land cover, Mapping, GIS.

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K. K. Singh ¹, A. Kumar ², A. V. Kulkarni ³, P. Datt ¹, S. K. Dewali ¹, V. Kumar ¹, R. Chauhan ¹

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 National Institute of Technology, Kurukshetra 136 119, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Abstract

Snow depth is an important parameter for avalanche forecast and hydrological studies. In the Himalaya, manual snow depth data collection is difficult due to remote and rugged terrain and the severe weather conditions. However, microwave-based sensors in various satellites have the capability to estimate snow depth in all weather conditions. In the present study, experiments were performed to establish an algorithm for snow depth estimation using ground-based passive microwave radiometer with 6.9, 18.7 and 37 GHz antenna frequencies at Dhundhi and Patseo, Himachal Pradesh, India. Different layers in the snowpack were identified and layer properties, i.e. thickness, density, moisture content, etc. were measured manually and using a snow fork. Brightness temperature (T_B) of the entire snowpack and of the individual snow layers was measured using passive microwave radiometer. It was observed that T_B of the snow is affected by various snow properties such as depth, density, physical temperature and wetness. A decrease in T_B with increase in snow depth was observed for all types of snow. T_B of the snowpack was observed higher at Dhundhi in comparison to Patseo. Based on the measured radiometer data, snow depth algorithms were developed for the Greater Himalaya and Pir-Panjal ranges. These algorithms were validated with ground measurements for snow depth at different observatory locations and a good agreement between the two was observed (absolute error: 7 to 39 cm; correlation: 0.95).

Keywords

Brightness Temperature, Microwave Radiometer, Snow Depth Algorithm, Snowpack.

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V. Kumar ¹, R. Sathish ²

Affiliations
1 Department of Electronics & Communication Engineering, M.P. Nachimuthu M. Jaganathan Engineering College, Chennimalai, Erode, IN
2 Department of Electrical and Electronics Engineering, M.P. Nachimuthu M. Jaganathan Engineering College, Chennimalai, Erode, IN

Abstract

Models of real system are of fundamental importance in virtually all disciplines. The models are useful for system analysis i.e., or gaining a better understanding of the system. Models make it possible to predict or simulate a system’s behavior. In engineering, models are required for the design of new processes and for the analysis of existing processes. Advanced techniques for the design of controllers, optimizations, supervision, and fault detection are also based on process model. In this paper a simulated comparison of fuzzy logic and neural network control of the truck backer-upper system is presented. The aim of the controller is to back a truck to a loading dock which is a difficult task. It is a nonlinear control problem for which no traditional control system design method exists. We assumed that there were no linguistic rules available, and therefore the controllers were designed from the available numerical data only.
We provided the same desired input-output pairs to both the neural and the fuzzy approaches, and compared the final control performance of both models. It is known that artificial neural networks and fuzzy logics are powerful tools for handling problems of large dimension. Many studies have been reported on the ability of neural networks and fuzzy logics for approximating nonlinear functions. The chores of this paper are to model the truck backer upper control problem using neural networks and fuzzy logic. This paper proposes a comparative study of neural networks (FFN, RBFN and RNN) and fuzzy logic for modeling the truck backer upper control problem. The body angle ∅, x position and the steering angle θ of the truck are used as training data for neural network and fuzzy logic. The results showed the superiority of the neural controller over the fuzzy one, when the later was influenced by the amount of overlapping between its sets and the missing rules from its rule base.

Keywords

Fuzzy Logic, Neural Networks, Nonlinear System Modeling.

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V. Kumar ¹, R. Sathish ²

Affiliations
1 Department of Electronics & Communication Engineering, M.P. Nachimuthu M. Jaganathan Engineering College, Chennimalai, Erode, IN
2 Department of Electrical and Electronics Engineering, M.P. Nachimuthu M. Jaganathan Engineering College, Chennimalai, Erode, IN

Abstract

In this paper a simulated comparison of fuzzy logic and neural network control of the truck backer-upper system is presented. The aim of the controller is to back a truck to a loading dock which is a difficult task. It is a nonlinear control problem for which no traditional control system design method exists. We assumed that there were no linguistic rules available, and therefore the controllers were designed from the available numerical data only.
We provided the same desired input-output pairs to both the neural and the fuzzy approaches, and compared the final control performance of both models. It is known that artificial neural networks and fuzzy logics are powerful tools for handling problems of large dimension. Many studies have been reported on the ability of neural networks and fuzzy logics for approximating nonlinear functions. The tasks of our paper are to model the truck backer upper control problem using different neural networks and fuzzy logic. This paper proposes a comparative study of neural networks (FFN, RBFN and RNN) and fuzzy logic for modeling the truck backer upper control problem. The body angle ∅, x position and the steering angle θ of the truck are used as training data for neural network and fuzzy logic. The results showed the performance of RBFN, better than other neural networks and fuzzy logic with lesser number of iterations, training period and minimum mean square error (MSE).

Keywords

Fuzzy Logic, Neural Networks and Nonlinear System.

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V. Kumar ¹, A. C. Kapoor ¹

Affiliations
1 Department of Foods and Nutrition, College of Home Science, Haryana Agricultural University, Hissar-125 004, IN

Abstract

Trace elements play an important vole thvougt enzymes and vitamin systems in maintaining good health of human beings. Deficiencies of trace elements lead to abnormalities of growth, anaemia, depression of immune system and susceptiblility to infections. Therefore, the World Health Organisation Technical Report "Trace Element in Human Nutrition" called upon the nutritional scientists to intensify their research into the nutritional status of populations with regard to the trace elements.

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M. Ranjit Kumar ¹, T. Meenambal ¹, V. Kumar ²

Affiliations
1 Department of Civil Engineering, GCT, Coimbatore 641 013, IN
2 Department of Agricultural Engineering, AC&RI, Madurai 625 104, IN

Abstract

Macropore flow carries water from the soil surface to deeper profile or groundwater, bypassing the intermediate soil profile. The phenomenon is ubiquitous and not rare. A theoretical framework of this flow has not been perfected so far, but ignoring this process may lead to incomplete conceptualization of soil-water flow. The macropore flow has been modelled based on observed data on morphometry, macropore size distribution and fractal dimensions of soil voids and stain patterns, and incorporated in the Watershed Processes Simulation (WAPROS) model. The performance of WAPROS model was evaluated to be good (NSE - hourly; daily = 0.8578; 0.9020), when applied to a real watershed. The sensitivity of macropore flow submodel showed that the adjustment factor was linearly related to macropore flow. Simulations were performed for five types of soil, namely sandy loam, sandy clay loam, sandy clay, clay loam and silty clay loam (A, B, C, D and E respectively). The values of macroporosity factors and fractal dimensions generated for the five types of soil have been presented. The model generated data for A, B, C, D and E soil types were: the number of macropores: 379, 3074, 3412, 153 and 0; the macropore flow (mm): 1.5121, 9.3667, 15.1728, 4.4055 and 0; the average pore flow (mm/pore): 0.0040, 0.0030, 0.0044, 0.0287 and 0; and the macropore flow to base flow ratio: 0.0055, 0.0474, 0.1908, 0.2759 and 0. The modelling methodology gives encouraging results. The model can be updated as and when better equations are made available.

Keywords

Groundwater, Hydrologic Simulation, Macropore Flow Model, Sensitivity, Soil Types.

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T. Kumar ¹, V. Kumar ¹

Affiliations
1 Crop Research Station (N.D. University of Agriculture and Technology), Ghaghraghat, Baharaich (U.P.), IN

Abstract

A field experiment was conducted to study the effect of rates and methods of zinc application in rice under flood prone condition. There was significant increase in the yield and yield attributes of rice crop upto 45 kg ZnSO₄/ha. The content and uptake of zinc was also increased significantly with increasing levels of zinc sulphate. Soil applied Zn was superior as compared to its foliar application. Soil application of 45 kg ZnSO₄/ha was found to be the best which recorded the highest net monetary return Rs. 8111 ha 1 with BCR 1.63.

Keywords

Rice, ZnSO₄.

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Ajay Verma ¹, V. Kumar ¹, A. S. Kharab ¹, G. P. Singh ¹

Affiliations
1 Statistics and Computer Center, ICAR-Indian Institute of Wheat and Barley Research, Karnal (Haryana), IN

Abstract

The present study was carried out to identify malt barley genotypes with high yield and stability across eight different environments, using non-parametric statistical measures. Descriptive statistics MR, SD and CV identified DWRB147, DWRB150 and RD2943 stable genotypes. BH902 and PL890 were identified as unstable genotypes by CMR CSD and CCV. Non-parametric measures selected DWRB147 and DWRB150 as the stable genotypes and BH902 and PL890 unstable genotypes. Significant tests for S_i ¹ and S_i ² were based on sum of Z_i ¹ and Z_i ² measures and sum of Z_i ¹ was greater than critical value confirmed significant differences among the twenty genotypes. Results of the NP_i ², NP_i ³ and NP_i ⁴were similar for unstable performance of BH902, DWRB150 and DWRB147. Biplot analysis of PCA1 and PCA2 accounting for 70.08 per cent showed three distinguish groups among non-parametric measures. Clustering by Ward’s hierarchical method expressed four clusters by using the squared Euclidean distance as dissimilarity measure.

Keywords

Non-Parametric Measurements, Rank Correlation, Biplot Analysis, Hierarchical Clustering.

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S. S. Sonavane ¹, B. P. Patil ¹, V. Kumar ²

Affiliations
1 Department of Electronics Engineering, Maharashtra Academy of Engineering, Alandi (Pune), Maharashtra, IN
2 Department of Electronics & Instrumentation Engineering, Indian School of Mines University, Dhanbad-826004, Jharkhand, IN

Abstract

In this paper, a new design of wireless sensor network (WSN) node is discussed which is based on components with ultra low power. We have developed a Low cost and low power WSN Node using MSP430 and nRF24L01. The architectural circuit details are presented. This architecture fulfils the requirements like low cost, low power, compact size and self-organization. Various tests are carried out to test the performance of the nRF24L01 module. The packet loss, free Space loss (FSL) and battery lifetime calculations are described. These test results will help the researchers to build new applications using above node and to work efficiently with nRF24L01.

Keywords

Wireless Sensor Networks, MSP430, nRF24L01, Free Space Loss, Battery Lifetime, Packet Loss.

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Ajay Verma ¹, V. Kumar ¹, A. S. Kharab ¹, G. P. Singh ¹

Affiliations
1 Statistics and Computer Center, ICAR- Indian Institute of Wheat and Barley Research, Karnal (Haryana), IN

Abstract

Genotypes G5, G8, G3, G21 and G18 had achieved higher yields besides b_i > 1.0. G21 and G3 identified as appropriate one, because had higher yield value than the mean, bi values near 1.0 and low S²_di. Lower values (W²_i) resulted for G12, G5, G2, G21 while higher for G5, G3 and G14. Genotypes G12 followed by G2, G20, and G7 had the smallest environmental variance (S²_xi). Smaller values of (CV_i) considered G12, G2, G20, and G10 of stable performance. α² _i measure pointed out G12, G7 and G2 with smallest values. Desirable lower P_i values reflected by G18, G5, G21, and G4 while GAI values identified G18, G11, G4 G10 as desirable genotypes. S_i ⁽¹⁾ and S_i⁽²⁾ showed lower values of G12, G2 and G7 genotypes. Significant tests of S_i ⁽¹⁾ and S_i⁽²⁾ proved the highly significant difference in ranks among the 21 genotypes grown in 8 environments. Genotypes G12, G2, and G7 had the lower S_i⁽³⁾ and S_i⁽⁶⁾ values. Yield of genotypes had significant negative correlation with bi, S_i⁽²⁾, S_i⁽³⁾, S_i⁽⁶⁾, NP_i ⁽²⁾, NP_i⁽³⁾, NP_i⁽⁴⁾ and significant positive correlation with GAI, P_i and Rank Sum. Hierarchical cluster analysis classified genotypes into three clusters as largest cluster included genotypes with more than average yield along with high yielders G18, G11, G3, G5, G21 and unstable performance indicated by non parametric measures. Biplot analysis while considering first two significant principal components grouped the parametric and non parametric measures into four groups. The smaller group consisted of b_i and S² _di and adjacent to group of non parametric measures S_i⁽²⁾, S_i⁽⁶⁾, NP_i⁽²⁾, NP_i⁽³⁾ and NP_i⁽⁴⁾.

Keywords

Barley, Parametric, Non-Parametric Measures, Biplot Analysis, Hierarchical Clustering.

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V. Kumar ¹, S. K. Dhaka ¹, V. Panwar ¹, Narendra Singh ², A. S. Rao ³, Shristy Malik ³, S. Yoden ⁴

Affiliations
1 Radio and Atmospheric Physics Lab, Rajdhani College, University of Delhi, Delhi 110 015, IN
2 Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital 263 002, IN
3 Department of Applied Physics, Delhi Technical University, Delhi 110 042, IN
4 Department of Geophysics, Kyoto University, Kyoto 606850, IN

Abstract

Influence of the solar cycle on temperature structure is examined using radio occultation measurements by COSMIC/FORMASAT-3 satellite. Observations from January 2007 to December 2015 comprising 3,764,728 occultations, which are uniformly spread over land and sea, have been used to study temperature changes mainly in the troposphere along with the solar cycle over 60°N–60°S geographic latitudes. It was a challenging task to identify the height at which the solar cycle signal could be observed in temperature perturbations as different atmospheric processes contribute towards temperature variability. Using a high spatial resolution dataset from COSMIC we are able to detect solar cycle signal in the zonal mean temperature profiles near surface at 2 km and upward. A consistent rise in the interannual variation of temperature was observed along with the solar cycle. The change in the temperature structure showed a latitudinal variation from southern to northern hemisphere over the period 2007–2015 with a significant positive influence of sunspot numbers in the solar cycle. It can be concluded that the solar cycle induces changes in temperature by as much as 1.5°C. However, solar cycle signal in the stratospheric region could not be identified as the region is dominated by large-scale dynamical motions like quasi-biennial oscillation which suppress the influence of solar signal on temperature perturbations due to its quasi-periodic nature.

Keywords

Radio Occultation, Solar Cycle, Sunspot Number, Tropospheric Temperature.

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N. Kumar ¹, S. Chakravarty ², V. Kumar ³, N. Kumar ⁴, A. Bandyopadhyay ⁵

Affiliations
1 Mechanical Engineering Department, Brainware University, Kolkata-700124, IN
2 School of Laser Science and Engineering, Jadavpur University, Kolkata-700032, IN
3 Mechanical Engineering Department, IIEST, Shibpur-711103, IN
4 WMG, The University of Warwick, Coventry CV4 7 AL, GB
5 Mechanical Engineering Department, Jadavpur University Kolkata -700032, IN

Abstract

Laser beam machining (LBM) process deals with material removal with high precision using localized heating characteristics of lasers. Polymers used in different electrical, electronic and Micro-electromechanical systems need to be machined to get desired shape. Machining of these polymers is difficult using conventional machining process. With its large range of process parameters and precise localized heating, LBM provides solution to machining problems of polymers. In the present research, CAD is used to design gear profiles which can be used in electronic systems. These gears are cut from Acrylic film using LBM. The influence of different input parameters namely laser Power, weld Speed and Frequency of laser on profile geometry are studied. Response Surface Methodology (RSM) is used, with the responses chosen as Addendum Diameter (ADD) and Dedendum Diameter (DD). Results are further analyzed and correlations are made using ANOVA approach.

Keywords

LBM, CAD, Addendum, Dedendum, RSM, ANOVA, Acrylic.

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K. K. Yadav ¹, N. Chouhan ², R. Thubstan ², S. Norlha ², J. Hariharan ², C. Borwankar ², P. Chandra ², V. K. Dhar ¹, N. Mankuzhyil ², S. Godambe ², M. Sharma ², K. Venugopal ², K. K. Singh ¹, N. Bhatt ², S. Bhattacharyya ¹, K. Chanchalani ², M. P. Das ², B. Ghosal ², S. Godiyal ², M. Khurana ², S. V. Kotwal ², M. K. Koul ², N. Kumar ², C. P. Kushwaha ², K. Nand ², A. Pathania ², S. Sahayanathan ¹, D. Sarkar ², A. Tolamati ², R. Koul ³, R. C. Rannot ⁴, A. K. Tickoo ⁵, V. R. Chitnis ⁶, A. Behere ⁷, S. Padmini ⁷, A. Manna ⁷, S. Joy ⁷, P. M. Nair ⁷, K. P. Jha ⁷, S. Moitra ⁷, S. Neema ⁷, S. Srivastava ⁷, M. Punna ⁷, S. Mohanan ⁷, S. S. Sikder ⁷, A. Jain ⁷, S. Banerjee ⁷, Krati ⁷, J. Deshpande ⁷, V. Sanadhya ⁸, G. Andrew ⁸, M. B. Patil ⁸, V. K. Goyal ⁸, N. Gupta ⁸, H. Balakrishna ⁸, A. Agrawal ⁸, S. P. Srivastava ⁹, K. N. Karn ⁹, P. I. Hadgali ⁹, S. Bhatt ⁹, V. K. Mishra ⁹, P. K. Biswas ⁹, R. K Gupta ⁹, A. Kumar ⁹, S. G. Thul ⁹, R. Kalmady ¹⁰, D. D. Sonvane ¹⁰, V. Kumar ¹⁰, U. K. Gaur ¹⁰, J. Chattopadhyay ¹¹, S. K. Gupta ¹¹, A. R. Kiran ¹¹, Y. Parulekar ¹¹, M. K. Agrawal ¹¹, R. M. Parmar ¹¹, G. R. Reddy ¹², Y. S. Mayya ¹³, C. K. Pithawa ¹⁴

Affiliations
1 Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India; Homi Bhabha National Institute, Mumbai 400 085, India, IN
2 Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
3 Formerly at Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
4 Raja Ramanna Fellow at Astrophysical Sciences Division, Mumbai 400 085, India, IN
5 Deceased, IN
6 Department of High Energy Physics, Tata Institute of Fundamental Research, Mumbai 400 005, India, IN
7 Electronics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
8 Control and Instrumentation Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
9 Center for Design and Manufacture, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
10 Computer Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
11 Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
12 Formerly at Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
13 Formerly at Reactor Control Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
14 Formerly at Electronics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN

Abstract

The MACE telescope has recently been commissioned at Hanle, Ladakh, India. It had its first light in April 2021 with a successful detection of very high energy gamma-ray photons from the standard candle Crab Nebula. Equipped with a large light collector of 21 m diameter and situated at an altitude of ~4.3 km amsl, the MACE telescope is expected to explore the mysteries of the non-thermal Universe in the energy range above 20 GeV with very high sensitivity. It can also play an important role in carrying out multi-messenger astronomy in India.

Keywords

Gamma-ray astronomy, high energy radiative processes, non-thermal Universe, telescope.

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V. Kumar ¹, A. P. Joshi ¹, H. V. Warrior ¹

Affiliations
1 Department of Ocean Engineering and Naval Architecture, Indian Institute of Technology, Kharagpur 721 302, India., IN

Abstract

The large influx of freshwater and mixing of different water masses make simulating salinity challenging for the Bay of Bengal (BoB) region. This study analyses the variability of the simulated sea surface salinity (SSS) using models present in the Coupled Modal Intercomparison Project Phase 6 (CMIP6). We collected data for 37 models from CMIP6 and validated them against the Argo (2005–14) and Aquarius (2011–14) data. Based on the skill scores, we narrowed down our search to one CMIP6 model, viz. CIESM. This model was used to study the freshwater spread (FWS) in BoB during different seasons. We found that the correlation between pH and FWS was appreciable. The CIESM model was then used to project the future trends for 10 years for the tier-1 scenario. The trend analysis of future projections revealed a positive trend in SSP1-2.6, with a decrea­sing trend in SSP2-4.5 and SSP5-8.5.

Keywords

Climate Models, Freshwater Spread, River Fluxes, Skill Score, Trend Analysis.

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