Browsing by Author "Ritesh Kumar"

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A rare case of Turner’s syndrome with thyroid associated orbitopathy
(IP Innovative Publication Pvt. Ltd., 2024) Avina Bishnoi; Subhash Kumar; Supreeth Chandrashekhar; Ritesh Kumar; Rajendra Prakash Maurya
Turner syndrome (TS) is a chromosomal disorder that occurs in 1 per 2500 live-born females, due to complete or partial absence of a second normal X chromosome resulting in short stature and ovarian failure. The risk of autoimmune diseases in patients with TS is quite prominent, especially autoimmune thyroiditis. Nevertheless, Graves’ disease (GD) has been rarely reported in Turner’s syndrome with 45, XO karyotype. Here we report a case of adult phenotypic female who first time presented with Graves’ orbitopathy and later was diagnosed to have Turner’s syndrome. © 2024 Author(s), Published by Innovative Publication.
Aerosol-PM2.5 Dynamics: In-situ and satellite observations under the influence of regional crop residue burning in post-monsoon over Delhi-NCR, India
(Academic Press Inc., 2024) Ram Pravesh Kumar; Ranjit Singh; Pradeep Kumar; Ritesh Kumar; Shadman Nahid; Sudhir Kumar Singh; Charanjeet Singh Nijjar
The increasing air pollution in the urban atmosphere is adversely impacts the environment, climate and human health. The alarming degradation of air quality, atmospheric conditions, economy and human life due to air pollution needs significant in-depth studies to ascertain causes, contributions and impacts for developing and implementing an effective policy to combat these issues. This work lies in its multifaceted approach towards comprehensive understanding and mitigating severe pollution episodes in Delhi and its surrounding areas. We investigated the aerosol dynamics in the post-monsoon season (PMS) from 2019 to 2022 under the influence of both crop residue burning and meteorological conditions. The study involves a broad spectrum of factors, including PM2.5 concentrations, active fire events, and meteorological parameters, shedding light on previously unexplored studies. The average AOD550 (0.79) and PM2.5 concentration (140.12 μg/m³) were the highest in 2019. PM2.5 was higher from mid-October to mid-November each year, exceeding the WHO guideline of 15 μg/m³ (24 h) by 27–34 times, signifying a public health emergency. A moderate to strong correlation between PM2.5 and AOD was found (r = 0.65) in 2021. The hotspot region accounts for almost 50% (2019), 47.51% (2020), 57.91% (2021) and 36.61% (2022) of the total fire events. A statistically significant negative non-linear correlation (r) was observed between wind speed (WS) and both AOD and PM2.5 concentration, influencing air quality over the region. HYSPLIT model and Windrose result show the movement of air masses predominated from the North and North-West direction during PMS. This study suggest to promotes strategies such as alternative waste management, encouraging modern agricultural practices in hot-spot regions, and enforcing strict emission norms for industries and vehicles to reducing air pollution and its detrimental effects on public health in the region and also highlights the need for future possibilities of research to attract the global attention. © 2024 Elsevier Inc.
Comparative evaluation of geospatial scenario-based land change simulation models using landscape metrics
(Elsevier B.V., 2021) Aman Arora; Manish Pandey; Varun Narayan Mishra; Ritesh Kumar; Praveen Kumar Rai; Romulus Costache; Milap Punia; Liping Di
Assessing the performance of land change simulation models is a critical step when predicting the future landscape scenario. The study was conducted in the district of Varanasi, Uttar Pradesh, India because the city being “the oldest living city in the world” attracts a vast population to reside here for short and long-term, leaving the city's ecosystem more exposed to fragility and less resilient. In this work, an approach based on landscape metrics is introduced for comparing the performance of the ensemble models designed to simulate the landscape changes. A set of landscape metrics were applied in this study that offered comprehensive information on the performance of scenario-based simulation models from the viewpoint of the spatial ordering of simulated results against the related reference maps. A supervised support vector machine classification technique was applied to derive the LULC maps using Landsat satellite images of the year 1988, 2001, and 2015. The LULC maps of 1988 and 2001 were used to simulate the LULC scenario for 2015 using three Markov chain-based simulation models namely, multi-layer perceptron-Markov chain (MLP_Markov), cellular automata-Markov chain (CA_Markov), and stochastic-Markov chain (ST_Markov) respectively. The mean relative error (MRE), as a measure of the success of simulation models, was calculated for metrics. The MRE values at both the class and landscape levels were accounted for 21.63 and 11.45% respectively using MLP_Markov simulation model. The MRE values at both the class and landscape levels were accounted for 39.61 and 28.31% respectively using CA_Markov simulation model. The MRE values at both the class and landscape levels were accounted for 55.36 and 45.75% respectively using ST_Markov simulation model. The MRE values considered at class and landscape levels are further evaluated qualitatively for comparing the performance of simulation models. The results indicate that the MLP_Markov performed excellently, followed by CA_Markov and ST_Markov simulation models. This work showed an ordered and multi-level spatial evaluation of the models’ performance into the decision-making process of selecting the optimum approach among them. Landscape metrics as a vital characteristic of the utilized method, employ the maximum potential of the reference and simulated layers for a performance evaluation process. It extends the insight into the main strengths and drawbacks of a specific model when simulating the spatio-temporal pattern. The quantified information of transition among landscape categories also provides land policy managers a better perception to build a sustainable city master plan. © 2021 The Author(s)
Hypothyroidism in Pregnancy
(Springer Nature, 2023) Ritesh Kumar; Ayan Roy; Vahid S. Bharmal
Hypothyroidism in pregnancy remains an important endocrinological problem. The prevalence is on a rising trend. Hypothyroidism can be overt or subclinical. Overt hypothyroidism may either be detected as a new entity during screening or can complicate pregnancy in an already diagnosed hypothyroid patient. Overt hypothyroidism carries a significant risk of adverse foetal-maternal outcomes if not treated early. On the other hand, subclinical hypothyroidism remains a matter of debate, particularly at a lower range of TSH values. The foetal-maternal outcomes are inconsistent across studies, with miscarriage being the most reported adverse outcome. However, treatment of subclinical hypothyroidism requires an individualised approach and consideration of other factors, including autoimmunity. Thus, we describe the intricate relationship between pregnancy and hypothyroidism (both overt and subclinical) to facilitate a clear and concise, evidence-based outlook. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Spatio-temporal variability analysis of evapotranspiration, water use efficiency and net primary productivity in the semi-arid region of Aravalli and Siwalik range, India
(Springer Science and Business Media B.V., 2023) Shubham Kumar; Ritesh Kumar; Manoj Kumar; Alok Kumar Pandey; Prashant K. Srivastava; Sanchit Kumar; Varun Narayan Mishra; V.S. Arya
Sustainable and effective water use management is a global challenge for optimum productivity for all types of vegetation cover. Evapotranspiration (ET) is one of the key components determining the soil moisture conditions ensuring the water availability for vegetation in an area. The present study provides a strong basis for existing water conditions in the study area using evapotranspiration as an important tool. There is a large variability in evapotranspiration during the different months of the year 2022–23 as well as over a long period of study ranging from the year 2001 to 2022. Water use efficiency in the study area is 0.32 g C/kg H2O which is less than half that of China and USA. The study showed an increasing trend of net primary productivity (NPP) and water use efficiency (WUE) during 2001–22. The comparatively lower WUE and NPP in comparison with global average are of great concern for a semi-arid region, which is also India’s leading agricultural producer state. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.