Assam Don Bosco University is a state private, non-profit, co-educational, Catholic research university located in Assam, India. The university was founded on March 29, 2008, by the Salesians of Don Bosco (SDB) and executed by the Don Bosco Society, Azara, Guwahati. The university was officially established through the Assam Don Bosco University Act, 2009, on 9 January 2009 and created under the Assam Private Universities Act 2007.The university which is located in Guwahati, Assam, India is Assam's first state university in the private sector. The Governor of Assam serves as the Visitor. It is ranked by NIRF as the best private university in North East India. ADBU has been awarded the accreditation rating of “A Grade” by NAAC.
This manuscript presents a dual-band Voltage-Controlled Oscillator (VCO) design with temperature resistance circuit. It employs two Temperature Resistant VCOs (TRVCOs) that can operate from 350 MHz to 2.4 GHz and 2 GHz to 6.29 GHz. A temperature resistant circuit (TRC) is used to convert the temperature variation to frequency which can be used as one of the features for estimation of aging effect of the circuit using machine learning model. Three models -linear regression, polynomial regression (2nd degree) and random forest are considered and trained using synthetic data and random forest outperformed the other two in terms of mean absolute error. The variation of the frequency is controlled up to 260 MHz at 1500 degrees C, making it useful for use even in harsh environment. The design is implemented in cadence 90 nm gpdk CMOS Technology.
Managing water infrastructure systems has become increasingly challenging due to rapid economic growth, climate change effects, and the rising frequency of extreme hydro-meteorological events. Regions located in riverine floodplains, such as deltaic and low-lying areas, are particularly vulnerable to flooding and climate-induced disruptions. In this context, there is a critical need for systematic approaches to assess and enhance the resilience of urban water systems. This study develops an integrated framework for resilience assessment by combining the Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling (DEMA-TEL-ISM) with a Dynamic Bayesian Network (DBN). The proposed methodology captures both the causal interdependencies among resilience parameters and their temporal evolution under varying conditions. A total of 43 parameters were identified through literature review and expert consultation and applied to a case study in the Barak Valley region of Northeast India. Data were collected from field surveys, historical records, and official reports, including those from the District Disaster Management Authority, for the period 2022-2024. The results indicate that key driving factors are primarily associated with institutional capacity, climate adaptation investments, and infrastructure development, whereas resource availability factors such as insurance mechanisms and equipment support exhibit relatively lower influence within the system. The spatial assessment further identifies Kanakpur, Dullacherra, and Lalaghat as relatively more resilient locations, while Fanai Cherra Grant and Hailakandi are found to be more vulnerable under disaster conditions. The robustness of the framework is examined by sensitivity analysis and temporal stability assessment of the survey-derived resilience estimates. The proposed framework provides a structured and data-driven tool for evaluating water system resilience and can support decision-making for climate adaptation planning in vulnerable regions.
Sustainable alternatives that comprise lowering the consumption of resources without sacrificing structural performance. With the production of normal concrete, the environmental burden is increasing day by day. Sustainable M30-grade concrete can be developed by using various waste materials from industry, agriculture, and plastics. In this study, methodical experimental investigations are conducted on partial replacement of cement fine aggregate and coarse aggregate using a multi-criteria decision-making (MCDM) tool. MCDM is integrated for the simultaneous evaluation of compressive strength for the optimisation of the concrete mixes. Eight sustainable concrete models (M1 to M8) were developed in addition to a traditional control mix (M0). For the development of eight sustainable concrete models, a logical framework for material selection based on correlation analysis and the Best-Worst Method (BWM) for weightage determination has been used. Compressive strength testing has been used to evaluate the suggested mixes after 28 days, and unit weight and material cost were compared. The findings show that replacement systems based on minerals performed better than dominant mixes based on polymers and biomaterials. The Model M1 achieved the highest compressive strength, 41.48 N/mm², followed by M2 with 40.92 N/mm² and M3 with 39.43 N/mm²compressive strength. The models M1, M2, and M3 outperformed the control mix in compressive strength, weight reduction, and cost effectiveness. While Models M6-M8 demonstrated relatively lower strength and higher weight due to the extensive use of lightweight aggregates, Models M4 and M5 demonstrated intermediate performance because of the inclusion of polymeric and elastomeric materials. Models M1 to M3 are determined to be the most structurally and financially ideal sustainable mixes through a multi-criteria trade-off analysis that integrated strength, weight, and cost.
Present study experimentally investigates the coupled influence of the wing thickness of a T-shaped spur dike and downward seepage on local scour in an alluvial channel. Two configurations were tested under seepage levels of the main discharge. Bed response was quantified using time evolution of maximum scour depth, post-run bed morphology mapping, and bedform celerity at the upstream and downstream wing edges. The thicker wing consistently produced larger equilibrium scour under different seepage levels. The increased seepage indicates a stronger relative seepage response for the thinner wing despite lower absolute scour. Longitudinal profiles show a more extensive erosion footprint for thicker winged spur, with scour growth occurring mainly for initial time, followed by a slower approach to dynamic equilibrium. These findings provide practical guidance for spur-dike detailing in seepage-affected alluvial rivers by showing how wing thickness and seepage jointly control scour depth, footprint, and time to stabilisation.
This study introduces a predator-prey fishery model possessing a distinctive structural composition, featuring a single-stage predator population alongside a two-stage prey population dynamic. Additionally, the model considers harvesting efforts targeting the mature prey and predator populations. The novelty of this work lies in the incorporation of a biologically realistic two-stage prey structure within a fractional-order framework, along with the use of non-singular Caputo-Fabrizio derivatives, which allows for more accurate modeling of memory-dependent processes in ecological systems. To confirm the biological relevance of the proposed model, we first establish the existence and uniqueness of its solution. All equilibrium points of the system are determined and identified. Furthermore, the stability of the system, both locally and globally, is analyzed by employing the Jacobian matrix for system linearization and utilizing the Lyapunov direct approach for a detailed assessment. Lastly, numerical simulations are provided to support the analytical results, along with a graphical analysis of the system's behavior. The numerical simulations are performed employing the three-step Adam-Bashforth technique for fractional-order systems within the Caputo-Fabrizio framework.
