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The research uniquely focuses on advancing the field of fuzzy sets, specifically proposing a novel approach using Hexagonal Type-2 Fuzzy Variable (HT2FV), to handle higher degrees of uncertainty. Flooding, a recurrent and impactful phenomenon, necessitates a robust approach to effective disaster management. The study delves into the humanitarian supply chain dynamics during movement crises and flood catastrophes, introducing a novel methodology to harness the potential of HT2FV. Central to the paper is the innovative defuzzification concept of Critical Value (CV) reduction, strategically employed to eliminate fuzzy components within HT2FV, transforming it into crisp data. The research extends its novelty by proposing a comprehensive approach to distributing relief materials, employing a Multi-objective, Multi-level, Multi-modal (MOMLMM) approach, with a primary focus on boats for inundated areas. Significantly, the study aims to optimize the allocation of resources, minimize time and cost under uncertain environments, and enhance disaster relief operations. The paper is the first to use new hexagonal fuzzy numbers (HFNs) and focuses on how they can be used to sort vulnerable areas using the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of the Multi-Criteria Decision-Making (MCDM) process. A case study of the 2022 Assam flood is looked at and solved using the Weighted Sum (WS), Neutrosophic Compromise (NC), and Goal Programming (GP) systematically on the LINGO solver to see if the suggested method can be used. Further, sensitivity analysis is employed to establish optimal credibility levels to validate the proposed methods. A real-life case study lends practicality, substantiating the approach's efficacy. At the same time, comprehensive comparative analysis compares and contrasts findings from different studies to synthesize existing knowledge and identify future scope, contributing significantly to the field of fuzzy sets. [ABSTRACT FROM AUTHOR]

Human-animal conflict in Assam, India's north-eastern state, is rising continuously. Because it occurs year-round, it damages agricultural productivity and kills people and animals, including elephants. When a herd of wild elephants emerges from a deep forest and enters human-inhabited territory around the Kaziranga National Park (KNP) in Assam, an alert must be sounded for the neighbourhood residents and forest workers to prevent conflicts. Another concern is that many wild animals die near the KNP while crossing the national highway NH-37 which traverses the area. During floods, animals flee to the highlands for food and shelter. An automated animal identification and warning system near the KNP may reduce human-animal confrontations. This paper reports the design of a system that attempts to address the above concerns. Artificial Intelligence (AI)-based strategies are utilized to recognize wild animals from live video sequences, provide warnings to avoid encounters, and protect humans and animals. Deep learning models and YoloV5 with the SENet attention layer are used to recognize wild animals in real-time. This model is trained using a public and customized dataset of animal species. Cameras attached to the cloud-based AI system take photographs from several KNP locations to confirm the model. The model's 96% accuracy in animal photographs and videos taken day and night and in feed from contemporaneous location has shown its utility. The model also improves reliability by 1–13% over previous methods. • Efficient real-time wild animal detection system designed using YOLOv5 and SENet attention layer. • The model enhances detection accuracy using fine-grain features of the object, enabling the detection of a diverse class of animals captured with varied illumination, distance, and background variations with the provision of auto-alarm generation. • Better detection rate is obtained by weighing noisy channels and focusing on specific feature sets using the SENet attention layer. [ABSTRACT FROM AUTHOR]

• Landscape ecological vulnerability was assessed using bagging ANN-MLP and RF models. • B-MLP model was found best fit model for LEV assessment based on ROC curve, recall, precision, F1-score and accuracy. • Largest area under very high LEV was recorded in the southern part of the plains. • Rainfall, soil, vegetation and LULC were found influencing factors for LEV. • Plantation, embankments and geotextile technology are suggested to check erosion. Riverbank erosion is one of the most catastrophic hazards that renders floodplains vulnerable across the world vulnerable. It creates a significant negative impact on the environment and socio-economic life. This paper attempts to assess the landscape ecological vulnerability (LEV) to riverbank erosion in the Middle Brahmaputra floodplains of Assam, India by employing two machine learning models, namely artificial neural network-multilayer perceptron (ANN-MLP) and random forest (RF). Bagging ensembles were created for both ANN-MLP and RF (B-MLP and B-RF) to generate LEV zones. A total of eleven site-specific parameters were considered for the study. The receiver operating characteristic (ROC) based area under curve (AUC), accuracy, precision, recall and F1-score were used to validate the models and judge the models' performance. A sensitivity analysis was performed to deduce the most influential LEV parameters. The results revealed that B-MLP was the better-performing model compared to B-RF based on all five validation metrics. The largest area was found under very high vulnerability zone followed by very low, low, high and moderate vulnerability zones, based on both ensemble models. The western part of the floodplains was found to be more vulnerable than the eastern part. Moreover, the southern bank faced more vulnerability in comparison to the northern bank. The factors namely rainfall, soil type, vegetation and land /use land cover (LULC) influenced bank erosion vulnerability. This research provides evidence that the study area is under severe threat to riverbank erosion and urgently requires the implementation of effective mitigation measures. The study might benefit policymakers and local stakeholders to protect the floodplains from bank erosion and reduce vulnerability. [ABSTRACT FROM AUTHOR]

This paper estimates the health costs of arsenic contamination of drinking water in Assam, India, where nearly one million people are affected. Applying the Three Stage Least Square (3SLS) procedure to data collected through a primary survey of 355 households in 2013, it estimates three structural equations to determine health costs due to arsenic contamination. The estimates show that the average annual health cost of a 1 microgram increase in arsenic concentration per liter of drinking water is about INR4 per household. Furthermore, if the average level of arsenic concentration is reduced to the safe limit of 50 microgram per liter, the average annual welfare gain for a household is estimated to be INR 862 (USD 14). Projecting these figures to the entire arsenic-affected population of Assam, the annual health costs of a 1 microgram increase in arsenic concentration per liter are estimated to be about INR 0.76 million (USD 0.01 million) and the welfare gains from reducing the level of arsenic concentration to the safe limit are estimated to be INR 153 million (USD 2.49 million). The results also indicate that these health costs and welfare gains vary significantly across different levels of arsenic concentration and across districts. Finally, the paper draws policy implications for providing safe drinking water in Assam. [ABSTRACT FROM AUTHOR]

Abstract: Human-wildlife conflicts impact upon the wellbeing of marginalised people, worldwide. Although tangible losses from such conflicts are well documented, hidden health consequences remain under-researched. Based on preliminary clinical ethnographic inquiries and sustained fieldwork in Assam, India, this paper documents mental health antecedents and consequences including severe untreated psychiatric morbidity and substance abuse. The case studies presented make visible the hidden mental health dimensions of human–elephant conflict. The paper illustrates how health impacts of conflicts penetrate far deeper than immediate physical threat from elephants, worsens pre-existing mental illness of marginalised people, and leads to newer psychiatric and social pathologies. These conflicts are enacted and perpetuated in institutional spaces of inequality. The authors argue that both wildlife conservation and community mental health disciplines would be enhanced by coordinated intervention. The paper concludes by generating questions that are fundamental for a new interdisciplinary paradigm that bridges ecology and the clinic. [Copyright &y& Elsevier]

Abstract Aromatic rice has its great demand due to its natural fragrance and used for special cuisines. 'Joha', a non-basmati aromatic rice of Assam, India traditionally cultivated by the local farmers in a very small way. Joha rice possesses few significant features that are superior over the popularly known aromatic rice like Basmati. However, it is lagging behind to attain the global market. In this paper, an attempt has been made to investigate the morphological, physicochemical and cooking characteristics of 22 traditionally cultivated aromatic rice landraces and their cooking qualities. Among all the collections, Keteki Joha exhibited highest germination index (66%) that is important for cultivation. Identify the overall results of the field experiment, Gufur Phisa Jwsa could revealed best agronomic performance for grain yield, whereas, Kharika Joha showed high hulling and milling having medium-slender, translucent, creamy white kernels. Findings of the present investigation would be a boon for developing Joha rice of Assam in future breeding program and to establish in the global scenario. [ABSTRACT FROM AUTHOR]

Kaolin available in Deopani, Assam of northeastern region of India was characterized by FTIR, XRD, DTA and by wet chemical analysis methods. The major impurities in the clay are quartz and siderite. Wet sieving of the clay by −53-μm sieve removes almost all the quartz and a major amount of Fe bearing impurities. The iron content of the clay may be reduced further by treating with wet high intensity magnetic separator (WHIMS) or leaching with organic acids. The effectiveness of various leachants follows the order: Oxalic>Oxalic+EDTA>Malonic>Citric acid. Almost all the nonstructural iron may be removed at room temperature by using 0.4 M oxalic acid solution. The leached clay may find use as a ceramic raw material and filler material for paper and other materials. [Copyright &y& Elsevier]

Electricity generation for rural applications through biomethanation process is very promising in countries like India where availability of biomass feedstock is very high. However, sustainability of biomass power plants requires meticulous planning starting from assessment of feedstock availability to collection, storage, transport and conversion in power plant. All these parameters are spatially inter-linked and therefore use of spatial tools such as GIS is helpful in such planning. This paper investigates electrical power generation potential of a newly constructed biomethanation plant in Sonitpur district of Assam, India. Spatial availability of locally available biomass feedstocks for methane generation is assessed using GIS. The GIS is also used for optimal biomass collection and transportation network design. Altogether, 7 different types of biomass feedstock (kitchen waste, vegetable waste, cow dung, pig droppings, goat droppings, poultry droppings and rice straw) are identified in the surrounding villages of the plant within optimum biomass supply radius. Biomass feedstock of the area can produce 37,000 m 3 methane; sufficient for continuous generation of 5.3 MW electricity. Power supply from the proposed plant would improve rural living standard and key areas such as education and health will be particularly benefited. However, biomass assessment and supply logistics would require managerial attention to minimize cost of power generation. [ABSTRACT FROM AUTHOR]

Technological uplift is imperative for enterprises to achieve and sustain competitiveness in terms of both cost and quality of products. While the literature on technology adoption is voluminous, studies focused on adoption related issues concerning rural, nonfarm, and informal micro-entrepreneurs in developing economies are few and far between. In view of significance of these enterprises in employment and income generation at the lower end of income distribution in developing countries, a study of factors influencing adoption of modern technology in such enterprises assumes importance. Using firm-level data collected through a primary survey, the present paper analyses the determinants of adoption and extent of deployment of weaving technologies in the handloom micro-enterprises in rural areas of Assam. The results of the Cragg's Double Hurdle model reveal the significance of financial inclusion, availability of family labor, and social network on adoption and extent of deployment of weaving technologies. The presence of proper market linkages also appears to be crucial for adoption and use of such technologies in the rural areas. The study urges for a comprehensive policy framework to tackle the existing bottlenecks related to access to credit/capital, market linkages, and extension services to promote the technology adoption among the rural micro-entrepreneurs. [ABSTRACT FROM AUTHOR]

This paper identifies and analyzes the determinants of technology adoption in the handloom industry in Assam. Binary logistic regression model is used to analyze the primary data in which the dependent factor (technology adoption) is dichotomous. Results show that education and annual income of the industry owners play a crucial role in the adoption of modern technology. In the case of small owners, gender has positive and significant influence, whereas age, education, and distance to the nearest market have significant but negative influences on the adoption of modern technology. In the case of contractual workers, age has a negative but significant influence on the adoption, whereas annual income, access to government credit, and access to training have positive and significant influences on the adoption of modern technology. As access to training and credit increases the likelihood of the adoption of modern technology for the contractual workers, adequate facilities for such determinants should be made available to the grass root workers. [ABSTRACT FROM AUTHOR]

Agricultural residues are a promising source of biomass energy. However, agricultural residues are seasonally available and loosely distributed over large geographical areas and hence require spatio-temporal assessment. Satellite image is a handy input for such assessment and high resolution image could increase the preciseness of estimation. In the present study, rice cropland is mapped using high resolution WorldView-2 satellite image in a rural area of Assam, India. The rice cropland map in combination with agricultural statistics is then analyzed in GIS in order to assess rice straw availability for potential bioenergy generation. About 54% land of study area belongs to rice cropland, which can contribute 5360 tonnes surplus rice straw per annum (equivalent to 83,296 GJ). Potential electric power capacity from the surplus rice straw in the study area is 523.50 kW. However, at individual village level the potential varies from 4.45 kW to 28.69 kW. Considering the power crisis in India, the findings of this work are expected to assist policy makers and biomass energy developers in decision making process. Particularly, this paper generated information on village level rice straw residue availability and subsequently potential electric power capacity. Such information is limited in the India expect for few states. [ABSTRACT FROM AUTHOR]

The agriculture sector of Assam, a state in the northeast part of India, supports more than 75% of its population. Agriculture in Assam is highly susceptible to flood risk, not only through reduced time availability for cropping but also through higher production risks due to varying flood timing, frequency and intensity. Farmers however have few institutional safeguards to hedge that risk. This paper explores the role of crop diversification as a means for the farmers in the flood plains of Assam to cope with flood induced production risks and limits. An application of a generalized linear model to original farm level survey data reveals that farmers in the plains of Assam who are confronted with greater flood risk tend to diversify their cropping pattern more. This diversification is also shown to be a strategy that extracts higher returns from farming. [ABSTRACT FROM AUTHOR]

Abstract: This study aims at estimating the rate of bed aggradation of the Jia Dhansiri River in Assam, India. It is carried out using two methods: (1) measurement of channel cross section in the field, and (2) measurement of variously dated maps for the period 1995–2006. Following these two methods, data on parameters pertaining to bed aggradation are generated and authenticated by comparison. Data on total bed aggradation during 1995–2006 are extrapolated from cross section graphs and again verified with a model proposed in this paper based on average water level of base year and current year and total bed aggradation. The rates of bed aggradations are 5.27cm/y at Dhansiri Khuti village, 5.09cm/y at Barigain village, 5.27cm/y at Bagishakash village, and 2.64cm/y at Thalthali village. No degradation zones are found in between during the study period except in minor magnitude and localized cases. If these rates of bed aggradation are continued and no significant changes in the channel morphology occur, then the river bed may merge with the low river bank after 11years at Dhansiri Khuti village, 17years at Barigaon village, 6years at Bagishakash village, and 7years at Thalthali village. The average channel aggradation during 11–years of period in the 16–km reach has estimated to be 3.65cm/y. Again, if this rate is continued then the river bed will overtop low banks of the 16–km reach after 16years. At this situation the river may attain a state of geomorphic threshold which may be channel shift following vulnerable slope(s). [Copyright &y& Elsevier]

Abstract: Spatial assessments of crop residue biomass and its power potential at village level in Sonitpur district of Assam, India is presented in this paper. Recent IRS P6 LISS-III remote sensing data of the study area is analyzed in GIS environment to map crop areas and subsequently residue biomass availability at village level. Altogether 16 different types of crop residues are identified in the district with rice crop as dominant residue. About 0.17 million tonnes of crop residue biomass, having about 17MW potential power, is spatially distributed in the rural areas of the district. Village level biomass power mapping is done assuming combustion route of decentralized power generation. Considering the acute shortage of grid connected power supply in the study area, the decentralized crop residue based power generation could be an attractive option. At individual level, thermal power plant up to 72kW could be possible to cater the essential power need of the villager. [Copyright &y& Elsevier]

Abstract: This paper highlights on the current malaria situations in Bhutan and its challenges for future prevention and control strategies. In Bhutan, malaria affects more than half of the entire population, mostly residing in the southern districts bordering with Indian states of Assam and West Bengal. Over the past ten years, due to concerted efforts, the morbidity and mortality due to malaria has significantly declined. These preventive and control measures focused on the mass distribution of long lasting insecticidal treated nets, focal indoor residual spray and use of artemisinin-based combination therapies. However, considerable challenge lies ahead and research is needed to generate local evidence for sustainable elimination of malaria from Bhutan. The article should be of value and interest to planners, malaria programs and for future researchers on malaria in Bhutan. [Copyright &y& Elsevier]

Abstract: A thermal characterization of two coal samples from Ledo and Tikak collieries of Makum coalfield, Assam, India using XRD, FT-IR, and TGA was reported in this paper. The coal samples were heated for 20, 40 and 60 min in a 1000-watt heater (temperature ∼250 °C) in presence of air and characterized by XRD and FT-IR spectroscopy. Both the coals contain amorphous and crystalline phases. The raw coals also contain very small peaks due to quartz, calcite, gypsum, pyrite, and chlorite. The XRD patterns were found to change upon heating. In the coals heated for 20 and 40 min, it was observed that both amorphous and crystalline parts are common in them; crystalline part being the major one in the 40 min heated samples. The XRD patterns of the samples heated for 60 min indicate the presence of major quantities of α-quartz, hematite, and chlorite in them. They also show some new peaks, which are assigned to be kaolinite, illite, magnetite and very small in comparison to the amorphous portion in raw coals. α-quartz was found to be most stable crystalline phase of silica in the coals. The crystallinity % (X-ray) of the coals heat-treated for different times was determined and found to be increasing with time of heating. The FT-IR spectra of raw and heat-treated coal samples at 250 °C were also recorded and compared. The spectra were observed to be almost similar and it was observed that few functional groups disappear on heating at 250 °C. The same coal samples were also characterized by thermogravimetric analysis (TGA) and differential thermal analysis (DTA) techniques. On heat treatment in air atmosphere up to 800 °C, 20–27% weight loss occurs due to removal of various volatile materials. DTA results indicate the chemical reactivity of the coal sample initially at 80–110 °C due to loss of water, and two other major reactions at around 420 and 530 °C due to primary and secondary volatization. [Copyright &y& Elsevier]