15 research outputs found
Colonial governmentality and Bangladeshis in the anthropocene: Loss of language, land, knowledge, and identity of the Chakma in the ecology of the Chittagong Hill tracts in Bangladesh
No full textAbstract: “Can they do whatever they please. . . Turn settlements into barren land. Dense forests into deserts. Mornings into evenings. Turn fertile into barren. Why shall I not resist!. …. I become my whole self. . . Why shall I not resist”!. This is a section from a poem - ‘Joli No Udhim Kittei’ a Chakma poem written in Bengali script as ‘Rukhe Darabo Na Keno?’ (‘Why shall I not resist!’) by the author \Kabita Chakma in 1992, translated into English. It epitomizes the ongoing violation of human rights that Chakmas (members of one of the Indigenous communities in Bangladesh) experience in the Chittagong Hill Tracts (CHT) where the highest number of Indigenous people in Bangladesh live. In this paper, the first author, a member of the Chakma community and a Lecturer at an Australian university is in conversation with the second author, a Professor at a university in a Bangladeshi university. With reference to Phillipson’s linguicism, and Foucault's notion of governmentality in the era of the Anthropocene, in their conversation, they reflect on the Anthropocene – the forced migration, displacement of Indigenous communities in Bangladesh from their traditional land, extinction of Indigenous languages, disengagement with Indigenous and local languages, and consequently, and the destruction of biodiversity of Chittagong Hill Tracts. </p
South Asian Regionalism: The Limits of Cooperation
No full textLeading South Asia expert Bhumitra Chakma explains the politics of regionalism in South Asia and traces the origins and evolution of the South Asian Association for Regional Cooperation (SAARC) from its inception to the present day. He takes an International Relations perspective and engages three major IR theoretical approaches - neorealism, institutionalism and constructivism - to explain the complex dynamics of South Asian regionalism. Using comparative perspectives based on the experiences of similar regional organizations, the author provides an in-depth analysis of the challenges of cooperation in the region and explores how progress might be made in the future
Mothers Lived Experiences of Caesarean Section: A Qualitative Study among Mothers in Semi-Urban Areas of Bangladesh
No full textThe commercialisation of health services has led to an increasing rate of unnecessary caesarean deliveries in developing countries like Bangladesh. This rising rate of unnecessary caesarean section (CS) is a serious concern, and it is associated with numerous short and long-term complications in both maternal and child health. This study aimed to explore the CS mother's direct experiences with the immediate and long-term physical effects of CS. Twenty-two participants were selected from the Naya Bazar area, Sylhet City Corporation, which included mothers, fathers, traditional birth attendants and community health care providers. A qualitative research approach was adopted, and in-depth interviews and key informant interviews were conducted to focus on the experiences of caesarean mothers. The interviews were conducted face-to-face and analysed thematically. Various short and long-term physical risks were found following CSs. Four important physical consequence themes emerged from the analysis: Medicinal and breastfeeding difficulties, pain and wound complexity, urinary incontinence, and experiences following a CS. Some of the immediate consequences of the post-caesarean period impacted the mother’s ability to care for their child and the lack of mobility. Short and long-term consequences and physical pain impacted them over a long period. Unnecessary CSs can have short and long-term complications that need to be addressed. It is crucial to raise awareness about the potential consequences of CS for both the mother and the child, which would contribute to Sustainable Development Goals 3 (SDGs 3), ensuring well-being amongst the mother and the child
Estimation of total body water (TBW) by bioelectrical impedance analysis (BIA) in dehydrated and perioperative infants and children
No full textThis thesis was scanned from the print manuscript for digital preservation and is copyright the author.
Researchers can access this thesis by asking their local university, institution or public library to
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South Asia's nuclear security
No full textSouth Asia is often viewed as a potential nuclear flashpoint and a probable source of nuclear terrorism. But, how valid are such perceptions? This book seeks to address this question and assesses the region’s nuclear security from two principal standpoints. First, it evaluates the robustness of the Indo-Pakistani mutual deterrence by analysing the strength and weaknesses of the competing arguments regarding the issue. It also analyses the causes and consequences of nuclear arms race between India and Pakistan, the nature of deterrence structure in the region and the challenges of confidence building and arms control between the two countries in order to assess the robustness of South Asia’s nuclear deterrence. Second, it assesses the safety and security of the nuclear assets and nuclear infrastructure of India and Pakistan. The author holds that the debate on South Asia’s nuclear security is largely misplaced because the optimists tend to overemphasise the stabilising effects of nuclear weapons and the pessimists are too alarmists. It is argued that while the risks of nuclear weapons are significant, it is unlikely that India and Pakistan will give up their nuclear arsenals in the foreseeable future. Therefore, what needs to happen is that while nuclear elimination should be the long-term goal, in the interim years the two countries need to pursue minimum deterrence policies to reduce the likelihood of deterrence failure and the possibility of obtaining fissile materials by non-state actors
Author Profiling Tracks at FIRE
No full text[EN] Benchmarking activities are vital for fostering research and addressing new challenging problems. During the last 10 years of the FIRE initiative we have been involved in the organization of more than ten tracks, with the aim of the creation of new resources in several languages that were made available to the research community. This allowed to compare the new several approaches on the same datasets. In this chapter we will focus on the description of three author profiling tracks, on their data creation as well as the results analysis.The work on the author profiling data in Arabic was made possible by NPRP Grant #9-175-1-033 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authorsRosso, P.; Rangel Pardo, FM. (2020). Author Profiling Tracks at FIRE. SN Computer Science. 1:1-11. https://doi.org/10.1007/s42979-020-0073-1S1111Al Sukhni E, Alequr Q. 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Lexical predictors of personality type. In: Proceedings of the joint annual meeting of the interface and the classification society of North America; 2005.Asghari H, Mohtaj S, Fatemi O, Faili H, Rosso P, Potthast M. Algorithms and corpora for Persian plagiarism detection: overview of pan at fire 2016. In: Notebook Papers of FIRE 2016, FIRE-2016, Kolkata, India, December 7–10, CEUR Workshop Proceedings. CEUR-WS.org, vol 1737; 2016. pp 135–144.Bachrach Y, Kosinski M, Graepel T, Kohli P, Stillwell D. Personality and patterns of Facebook usage. In: Proceedings of the ACM web science conference. ACM New York, NY, USA; 2012. pp 36–44.Banerjee S, Chakma K, Naskar DA Sudip, Rosso P, Bandyopadhyay S, Choudhury M. Overview of the mixed script information retrieval (MSIR) at fire-2016. In: Notebook papers of FIRE 2016, FIRE-2016, Kolkata, India, December 7–10, CEUR workshop proceedings. CEUR-WS.org, vol 1737; 2016. pp 94–99.Barrón-Cedeño A, Rosso P, Lalitha-Devi S, Clough P, Stevenson M. Pan@fire: Overview of the cross-language !ndian text re-use detection competition. In: 2nd and 3th international workshops FIRE 2010 and 2011, multilingual information access in south Asian Languages, Springer, LNCS(7536); 2013. pp 59–70.Bensalem I, Boukhalfa I, Rosso P, Abouenour L, Darwish K, Chikhi S. Overview of the araplagdet pan@ fire2015 shared task on Arabic plagiarism detection. In: Notebook papers of FIRE 2015, FIRE-2015, Gandhinagar, India, December 4–6, CEUR Workshop Proceedings. CEUR-WS.org, vol 1587; 2015. pp 111–122.Bishop-Clark C. Cognitive style, personality, and computer programming. Computers in human behavior, vol. 11–2. New York: Elsevier; 1995. p. 241–60.Castro D, Souza E, de Oliveira AL. Discriminating between brazilian and european portuguese national varieties on twitter texts. In: 5th Brazilian conference on intelligent systems (BRACIS); 2016. pp 265–270.Celli F, Polonio L. Relationships between personality and interactions in Facebook. Social networking: recent trends, emerging issues and future outlook. New York: Nova Science Publishers Inc; 2013. p. 41–54.Celli F, Lepri B, Biel JI, Gatica-Perez D, Riccardi G, Pianesi F. The workshop on computational personality recognition 2014. In: Proceedings of the ACM international conference on multimedia, ACM; 2014. pp 1245–1246.Costa PT, McCrae RR. The revised neo personality inventory (neo-pi-r). The SAGE handbook of personality theory and assessment, vol. 2. Thousand Oaks: Sage Publications Inc.; 2008. p. 179–98.Elfardy H, Diab MT. Sentence level dialect identification in Arabic. In: Association for computational linguistics (ACL); 2013. pp 456–461.Estival D, Gaustad T, Hutchinson B, Bao-Pham S, Radford W. Author profiling for English and Arabic emails; 2008.Flores E, Rosso P, Moreno L, Villatoro-Tello E. Pan@fire: Overview of SOCO track on the detection of source code re-use. In: Notebook papers of FIRE, FIRE-2014. India: Bangalore; 2014.Flores E, Rosso P, Moreno L, Villatoro-Tello E. Pan@ fire 2015: Overview of cl-soco track on the detection of cross-language source code re-use. In: Proceedings of the seventh forum for information retrieval evaluation (FIRE 2015), Gandhinagar, India; 2015. pp 4–6.Franco-Salvador M, Rangel F, Rosso P, Taule M, Marti M. Language variety identification using distributed representations of words and documents. Experimental IR meets multilinguality, multimodality, and interaction. Berlin: Springer; 2015. p. 28–40.Golbeck J, Robles C, Turner K. Predicting personality with social media. In: CHI’11 extended abstracts on human factors in computing systems, ACM; 2011. pp 253–262.Gupta P, Clough P, Rosso P, Stevenson M. Pan@fire: Overview of the cross-language Indian news story search (CLINSS) track. In: Notebook papers of FIRE 2012, FIRE-2012, Kolkata, India, December 17–19; 2012.Gupta P, Clough P, Rosso P, Stevenson M, Banchs R. Pan@fire: Overview of the cross-language Indian news story search (CLINSS) track. In: Notebook Papers of FIRE 2013, FIRE-2013, Delhi, India, December 4–6; 2013.Holmes J, Meyerhoff M. The handbook of language and gender. Blackwell handbooks in linguistics. New York: Wiley; 2003.Huang C, Lee L. Contrastive approach towards text source classification based on top-bag-of-word similarity. In: In PACLIC; 2008. pp 404–410.Karimi Z, Baraani-Dastjerdi A, Ghasem-Aghaee N, Wagner S. Links between the personalities, styles and performance in computer programming. J Syst Softw. 2016;111:228–41.Koppel M, Argamon S, Shimoni AR. Automatically categorizing written texts by author gender. Lit Linguist Comput. 2002;17:4.Kosinski M, Bachrach Y, Kohli P, Stillwell D, Graepel T. Manifestations of user personality in website choice and behaviour on online social networks. New York: Springer; 2013. p. 1–24.Litvinova T, Litvinlova O, Zagorovskaya O, Seredin P, Sboev A, Romanchenko O. “ruspersonality”: a Russian corpus for authorship profiling and deception detection. In: Intelligence, social media and web (ISMW FRUCT), 2016 international FRUCT conference on, IEEE; 2016. pp 1–7.Litvinova T, Seredin P, Litvinova O, Zagorovskaya O, Sboev A, Gudovskih D, Moloshnikov I, Rybka R. Gender prediction for authors of Russian texts using regression and classification techniques. In: CDUD@ CLA; 2016. pp 44–53.Litvinova T, Gudovskikh D, Sboev A, Seredin P, Litvinova O, Pisarevskaya D, Rosso P. Author gender prediction in Russian social media texts. In: Conference on analysis of images, social networks, and texts, AIST-2017, IEEE; 2017. pp 1101–1106.Litvinova T, Rangel F, Rosso P, Seredin P, Litvinova O. Overview of the rusprofiling pan at fire track on cross-genre gender identification in Russian. In: Notebook papers of FIRE 2017, FIRE-2017, Bangalore, India, December 8–11, CEUR Workshop Proceedings. CEUR-WS.org, vol 2036; 2017. pp 1–7.Lui M, Cook P. Classifying English documents by national dialect. In: Proceedings of the Australasian Language Technology Association Workshop; 2013. pp 5–15.Maharjan S, Shrestha P, Solorio T, Hasan R. A straightforward author profiling approach in mapreduce. In: Advances in artificial intelligence. Iberamia; 2014. pp 95–107.Maier W, Gomez-Rodriguez C. Language variety identification in Spanish tweets. In: LT4CloseLang 2014; 2014.Mairesse F, Walker MA, Mehl MR, Moore RK. Using linguistic cues for the automatic recognition of personality in conversation and text. J Artif Intell Res. 2007;30–1:457–500.Malmasi S, Zampieri M, Ljubešić N, Nakov P, Ali A, Tiedemann J. Discriminating between similar languages and Arabic dialect identification: a report on the third DSL shared task. In: Proceedings of the third workshop on NLP for similar languages, varieties and dialects (VarDial3); 2016. pp 1–14.Maulana Siagian AHA, Aritsugi M. Dbms-ku approach for author profiling and deception detection in Arabic. In: Metha P, Rosso P, Majumder P, Mitra M (Eds) Working notes of the forum for information retrieval evaluation (FIRE 2019). CEUR workshop proceedings. CEUR-WS.org, Kolkata, India, December 12–15; 2019.Neuman Y, Cohen Y. A vectorial semantics approach to personality assessment. Sci Rep. 2014;4:4761.Oberlander J, Nowson S. Whose thumb is it anyway?: classifying author personality from weblog text. In: Proceedings of the COLING/ACL on main conference poster sessions, Association for Computational Linguistics; 2006. pp 627–634.Paruma-Pabón OH, González FA, Aponte J, Camargo JE, Restrepo-Calle F. Finding relationships between socio-technical aspects and personality traits by mining developer e-mails. In: Proceedings of the 9th international workshop on cooperative and human aspects of software engineering, ACM; 2016. pp 8–14.Pennebaker JW, Mehl MR, Niederhoffer KG. Psychological aspects of natural language use: our words, our selves. Annu Rev Psychol. 2003;54(1):547–77.Quercia D, Lambiotte R, Stillwell D, Kosinski M, Crowcroft J. The personality of popular Facebook users. In: Proceedings of the ACM 2012 conference on computer supported cooperative Work, ACM; 2012. pp 955–964.Rangel F, Rosso P. On the multilingual and genre robustness of emographs for author profiling in social media. In: 6th international conference of CLEF on experimental IR meets multilinguality, multimodality, and interaction, Springer-Verlag, LNCS(9283); 2015. pp 274–280.Rangel F, Rosso P. On the impact of emotions on author profiling. Inf Process Manag. 2016;52(1):73–92.Rangel F, Rosso P. On the implications of the general data protection regulation on the organisation of evaluation tasks. Lang Law. 2019;5:95–117.Rangel F, Rosso P. Overview of the 7th author profiling task at pan 2019: Bots and gender profiling. In: Cappellato L, Ferro N, MÃller H, Losada D (Eds) CLEF 2019 labs and workshops, notebook papers. CEUR Workshop Proceedings. CEUR-WS.org; 2019.Rangel F, Rosso P, Potthast M, Stein B, Daelemans W. Overview of the 3rd author profiling task at pan 2015. In: Cappellato L, Ferro N, Jones G, San Juan E (Eds) CLEF 2015 labs and workshops, notebook papers. CEUR Workshop Proceedings. CEUR-WS.org, vol. 1391; 2015.Rangel F, González F, Restrepo-Calle F, Montes M, Rosso P. Pan at fire: Overview of the PR-SOCO track on personality recognition in source code. In: Notebook papers of FIRE 2016, FIRE-2016, Kolkata, India, December 7–10, CEUR workshop proceedings. CEUR-WS.org, vol 1737; 2016. pp 1–5.Rangel F, Rosso P, Franco-Salvador M. A low dimensionality representation for language variety identification. In: 17th international conference on intelligent text processing and computational linguistics, CICLing. Springer; 2016. LNCS. arXiv:1705.10754Rangel F, Rosso P, Potthast M, Stein B. Overview of the 5th author profiling task at PAN 2017: gender and language variety identification in Twitter. In: Working notes papers of the CLEF 2017 evaluation labs, CLEF and CEUR-WS.org, CEUR workshop proceedings; 2017.Rangel F, Rosso P, Charfi A, Zaghouani W, Ghanem B, Sánchez-Junquera J. Overview of the track on author profiling and deception detection in Arabic. In: Metha P, Rosso P, Majumder P, Mitra M (Eds) Working notes of the forum for information retrieval evaluation (FIRE 2019). CEUR workshop proceedings. CEUR-WS.org, Kolkata, India, December 12–15; 2019.Rangel F, Paolo R, Zaghouani W, Charfi A. Fine-grained analysis of language varieties and demographics. Nat Lang Eng; 2020. (In Press).Rosso P, Rangel F, Hernández-Farías I, Cagnina L, Zaghouani W, Charfi A. 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In: Notebook papers of FIRE 2015, FIRE-2015, Gandhinagar, India, December 4–6, CEUR workshop proceedings. CEUR-WS.org, vol 1587; 2015. pp 19–25.Sun Y, Ning H, Chen K, Kong L, Yang Y, Wang J, Qi H. Author profiling in arabic tweets:an approach based on multi-classification with word and character features. In: Metha P, Rosso P, Majumder P, Mitra M (eds) Working notes of the forum for information retrieval evaluation (FIRE 2019). CEUR workshop proceedings. CEUR-WS.org, Kolkata, India, December 12–15; 2019.Weren E, Kauer A, Mizusaki L, Moreira V, de Oliveira P, Wives L. Examining multiple features for author profiling. J Inf Data Manag. 2014;20:266–79.Xu F, Wang M, Li M. Sentence-level dialects identification in the greater china region. Int J Nat Lang Comput. 2016;5:6.Zaghouani W, Charfi A. Arapâ tweet: a large multiâ dialect twitter corpus for gender, age and language variety identification. In: Proceedings of the 11th international conference on language resources and evaluation (LREC), Miyazaki, Japan; 2018.Zaghouani W, Charfi A. Guidelines and annotation framework for Arabic author profiling. In: Proceedings of the 3rd workshop on open-source Arabic corpora and processing tools, 11th international conference on language resources and evaluation (LREC), Miyazaki, Japan; 2018.Zaidan OF, Callison-Burch C. Arabic dialect identification. Comput Ling. 2014;40(1):171–202.Zampieri M, Gebre B. Automatic identification of language varieties: the case of Portuguese. In: The 11th conference on natural language processing (KONVENS). Osterreichischen Gesellschaft fur Artificial Intelligende (OGAI); 2012. pp 233–237.Zampieri M, Malmasi S, Ljubešić N, Nakov P, Ali A, Tiedemann J, Scherrer Y, Aepli N. Findings of the vardial evaluation campaign 2017. In: Proceedings of the fourth workshop on NLP for similar languages, varieties and dialects; 2017. pp 1–15
Refugees, Citizenship and Belonging in South Asia [electronic resource] : Contested Terrains /
No full textThis book examines forced migration of two refugees groups in South Asia. The author discusses the claims of “belonging” of refugees, and asserts that in practice “belonging” can extend beyond the state-centric understanding of membership in South Asian states. She addresses two sets of interrelated questions: what factors determine whether refugees are relocated to their home countries in South Asia, and why do some repatriated groups re-integrate more successfully than others in “post-peace” South Asian states? This book answers these questions through a study of refugees from Sri Lanka and Bangladesh who sought asylum in India and were later relocated to their countries of origin. Since postcolonial societies have a typical kind of state-formation, in South Asia’s case this has profoundly shaped questions of belonging and membership. The debate tends to focus on citizenship, making it a benchmark to demarcate inclusion and exclusion in South Asian states. In addition to qualitative analysis, this book includes narratives of Sri Lankan and Chakma refugees in post-conflict and post-peace Sri Lanka and Bangladesh respectively, and critiques the impact of macro policies from the bottom up. .This book examines forced migration of two refugees groups in South Asia. The author discusses the claims of “belonging” of refugees, and asserts that in practice “belonging” can extend beyond the state-centric understanding of membership in South Asian states. She addresses two sets of interrelated questions: what factors determine whether refugees are relocated to their home countries in South Asia, and why do some repatriated groups re-integrate more successfully than others in “post-peace” South Asian states? This book answers these questions through a study of refugees from Sri Lanka and Bangladesh who sought asylum in India and were later relocated to their countries of origin. Since postcolonial societies have a typical kind of state-formation, in South Asia’s case this has profoundly shaped questions of belonging and membership. The debate tends to focus on citizenship, making it a benchmark to demarcate inclusion and exclusion in South Asian states. In addition to qualitative analysis, this book includes narratives of Sri Lankan and Chakma refugees in post-conflict and post-peace Sri Lanka and Bangladesh respectively, and critiques the impact of macro policies from the bottom up.
A dynamic optimization approach for nonrenewable energy resources management under uncertainty
No full textThis paper introduces an integrated dynamic optimization approach for nonrenewable energy (NRE) resources management under uncertainty. A hybrid inexact chance-constrained mixed-integer Linear programming (ICCMILP) method is proposed, with an objective of maximizing economic return under constraints of resources availability and environmental regulations. In its solution process, the ICCMILP is transformed into two deterministic submodels, which correspond to the upper and lower bounds for the desired objective function value. Interval solutions, which are feasible and stable in the given decision space, can then be obtained by solving the two submodels sequentially. Thus, decision alternatives can be generated by adjusting decision variable values within their solution intervals. The obtained solutions are useful for decision makers to optimally allocate limited NRE resources over time for acquiring maximized benefit. Meanwhile, regional air quality could be maintained to keep the communities from health damage. Results of a hypothetical case study indicate that reasonable solutions for dynamic planning of NRE resources allocation in a regional system have been obtained. A number of decision alternatives were generated based on the ICCMILP solutions as well as the projected applicable conditions. (C) 2000 Elsevier Science B.V. All rights reserved.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000089265700031&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Energy & FuelsEngineering, PetroleumSCI(E)EICPCI-S(ISTP)4
Mapping and Modelling Specific Sediment Yield and Future Soil Erosion Trends in the Jhelum Catchment, India
No full textAbstract
Soil erosion management is a crucial component of sustainable soil and water management, especially in regions where agricultural productivity is at risk and areas that are more vulnerable to the impacts of climate change, such as the Himalayan region. This study explores soil erosion dynamics in the Jhelum Catchment, India, using advanced mapping and modelling techniques to analyse and predict trends of potential soil loss from 2020 to 2090. The study integrates the RUSLE model with projected climate to assess the impact of climate change on soil erosion and rainfall erosivity. The InVEST SDR model is used to quantify sediment transport and specific sediment yield, enhancing our understanding of the hydrological processes that drive soil erosion and sediment mobilisation in the Jhelum Catchment. The RUSLE, along with advanced climate modelling, land-use data, and spatial analysis, is used in this study to predict trends in soil erosion. Climate data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) is combined with data from the India Meteorological Department (IMD) to project rainfall erosivity (R). R, along with soil erodibility (K), slope length and steepness (LS), land cover (C), and support practices (P) factors, are mapped and applied in the Revised Universal Soil Loss Equation (RUSLE) model, which evaluates the potential for soil erosion. This study forecasts soil loss trends by combining climate data, land-use information, and spatial analysis from 2020 to 2090 under two scenarios [SSP245 (moderate emissions) and SSP585 (high emissions)]. Results indicate escalating soil loss, particularly in less severe areas in 2020, highlighting the dynamic threat. The mean value of soil loss for SSP245 exhibits a continuous rise from 46.17 t/ha/year in 2030 to 51.54 t/ha/year in 2090. SSP585 shows a more severe trend, peaking at 71.67 t/ha/year in 2090. The study also classifies potential soil loss into severity classes, observing a decrease in the percentage area of less severe classes over time. Soil erosion class-wise projections from 2020 to 2090, based on LULC and soil type, reveal trends across various categories of land use, including Agriculture, Forest, Built-up Areas, and Grass/Grazing Land, as well as soil types like Cambisols, Lithosols, Glaciers, and Inland Water. These results highlight the urgent need for proactive interventions, offering practical insights for sustainable land management and providing actionable guidance for strategic planning and policy development focused on sustainable agricultural practices and climate change adaptation. This novel approach integrates advanced modelling and GIS-based analysis, making it applicable to other catchments with similar climate and land-use challenges. The study's findings directly apply to informing land management strategies, making the research highly relevant and practical.Abstract
Soil erosion management is a crucial component of sustainable soil and water management, especially in regions where agricultural productivity is at risk and areas that are more vulnerable to the impacts of climate change, such as the Himalayan region. This study explores soil erosion dynamics in the Jhelum Catchment, India, using advanced mapping and modelling techniques to analyse and predict trends of potential soil loss from 2020 to 2090. The study integrates the RUSLE model with projected climate to assess the impact of climate change on soil erosion and rainfall erosivity. The InVEST SDR model is used to quantify sediment transport and specific sediment yield, enhancing our understanding of the hydrological processes that drive soil erosion and sediment mobilisation in the Jhelum Catchment. The RUSLE, along with advanced climate modelling, land-use data, and spatial analysis, is used in this study to predict trends in soil erosion. Climate data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) is combined with data from the India Meteorological Department (IMD) to project rainfall erosivity (R). R, along with soil erodibility (K), slope length and steepness (LS), land cover (C), and support practices (P) factors, are mapped and applied in the Revised Universal Soil Loss Equation (RUSLE) model, which evaluates the potential for soil erosion. This study forecasts soil loss trends by combining climate data, land-use information, and spatial analysis from 2020 to 2090 under two scenarios [SSP245 (moderate emissions) and SSP585 (high emissions)]. Results indicate escalating soil loss, particularly in less severe areas in 2020, highlighting the dynamic threat. The mean value of soil loss for SSP245 exhibits a continuous rise from 46.17 t/ha/year in 2030 to 51.54 t/ha/year in 2090. SSP585 shows a more severe trend, peaking at 71.67 t/ha/year in 2090. The study also classifies potential soil loss into severity classes, observing a decrease in the percentage area of less severe classes over time. Soil erosion class-wise projections from 2020 to 2090, based on LULC and soil type, reveal trends across various categories of land use, including Agriculture, Forest, Built-up Areas, and Grass/Grazing Land, as well as soil types like Cambisols, Lithosols, Glaciers, and Inland Water. These results highlight the urgent need for proactive interventions, offering practical insights for sustainable land management and providing actionable guidance for strategic planning and policy development focused on sustainable agricultural practices and climate change adaptation. This novel approach integrates advanced modelling and GIS-based analysis, making it applicable to other catchments with similar climate and land-use challenges. The study's findings directly apply to informing land management strategies, making the research highly relevant and practical
Smoking and pre-existing co-morbidities as risk factors for developing severity of COVID-19 infection: Evidence from a field hospital in a rural area of Bangladesh
No full textData Availability: All relevant data are within the paper and its Supporting information files available online at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0295040#sec019 ..Since August 2020; the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) in collaboration with UNICEF has been operating a COVID-19 field hospital at the Teknaf sub-district of Cox’s Bazar in Bangladesh. This paper is focused on estimating the effects of a history of tobacco smoking and pre-existing co-morbidities on the severity of COVID-19 infection among adult patients admitted into the aforesaid hospital. We conducted a retrospective data analysis of COVID-19 adult patients hospitalized from August 27, 2020 to April 20, 2022. Based on inclusion criteria; a total of 788 admitted patients were included in the analysis. We conducted a Chi-squared test and Fisher’s exact test for the categorical variables to see their associations. Multinomial logistic regression models were performed to explore the risk factors for the severity of COVID-19 infection. Among 788 patients, 18.4%, 18.8%, 13%, 7.1%, 3.4%, and 1.9% have had a history of smoking, hypertension, diabetes, chronic obstructive pulmonary disease (COPD), cardiovascular diseases (CVD), and asthma respectively. Overall, the mean age of the patients was 40.3 ± 16.4 years and 51% were female. In multivariate analysis, history of smoking and co-morbidities were identified as the risk factors for the severity of COVID-19 infection; the history of smoking was found linked with an increase in the risk of developing critical, severe, and moderate level of COVID-19 infection- notably 3.17 times (RRR = 3.17; 95% CI: 1.3–7.68), 2.98 times (RRR = 2.98; 95% CI: 1.87–4.76) and 1.96 times (RRR = 1.96; 95% CI: 1.25–3.08) respectively more than the patients who never smoked. It was evident that patients with at least one of the selected co-morbidities such as hypertension, diabetes, COPD, CVD, and asthma exhibited a significantly higher likelihood of experiencing severe illness of COVID-19 compared to patients without any co-morbidity. History of tobacco smoking and pre-existing co-morbidities were significantly associated with an increased severity of COVID-19 infection.The author(s) received no specific funding for this work
