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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]

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]

• 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]

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]

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]

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]

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]

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]