Indian Institute of Engineering Science and Technology, Shibpur

It has been thought of as a class of models where a generalist predator feeds on two distinct prey species. We wish to examine how prey refuge factors affect prey–predator models when fear effects are present. In order to achieve this, a two-prey–one predator model with prey refuge has been taken into consideration in the presence of the predator’s fear effect on two prey species. Both prey species engage in intra-specific competition. We enhance our model by including a switching mechanism in predation. In order to account for the inherent imperfection of environmental conditions, some parameters have been taken as fuzzy numbers. Analytical and numerical results on the system have been examined in fuzzy sense. The system’s positivity, boundedness, and permanence are examined. The system’s local and global stability analyses have been investigated. Hopf bifurcation analysis around the positive interior equilibrium point has been explored. The stability of the limit cycle of our suggested fuzzy system has been discussed. The system’s numerical simulations have been investigated with pertinent tables and graphical illustrations. When the prey refuge parameter and fear parameter exceed the critical value, the system experiences Hopf bifurcation at the positive interior equilibrium point.

Aluminium alloys suffer from a serious backlash of low formability, hindering their implementation in the automobile sector, where demand has been skyrocketing for decades. However, warm forming techniques have been reported to bear the ability to curb this problem using a forming temperature below the recrystallization point, owing to the direct contribution of the activated non-octahedral slip systems. This calls for an investigation on the onset of secondary slip systems along with an estimation of microstructural characterization and analysis of crystallographic texture since both are expected to have a staggering influence on the mechanical properties at elevated temperatures. Hence, the present investigation deals with thorough microstructural analysis derived from the Electron Back Scattered Diffraction (EBSD) maps and analysis of crystallographic texture through Orientation Distribution Function maps of EN AW 6061 samples deformed through tension both at room and elevated temperature (250 °C). Furthermore, Visco Plastic Self Consistent (VPSC) modelling along with the Finite element (FE) method has also been incorporated with an aim to verify the crystallographic texture and deformation behaviour, respectively. These extensive characterization methodologies provided compelling evidences of the formation of deformation substructures at elevated tempaerature along with distinct represtation of work hardening behaviour of the material. The texture analysis further elaborated on the influence of high temperature on the reduction of unidirectional defects at high temperature, allowing it to regain its symmetry.

In this study, we present a predator-prey model that incorporates a delay in the prey’s reproduction resulting from fear induced by predators. Next, we modify our model to a fractional-order system, incorporating the effects of memory. Establishing positivity and boundedness of the solutions demonstrates the well-posedness of the system. The local and global asymptotic stability of the positive equilibria are established under certain suitable parametric conditions. Additionally, we prove the existence and uniqueness of solutions for the fractional-order system while ensuring that they remain bounded. It is observed that, depending on constraints defined by the values of the model parameters, the breeding delay in the model system has both a stabilizing and destabilizing role in the system dynamics. The maximum length of delay that preserves the stability of the limit cycle is calculated. In the presence of delay, it is noticed that the fear factor in model system dynamics plays exactly the opposite role to that of the system without delay; more preciously, when the prey species delayed their breeding, fear acts as a destabilizing factor. We also consider the modified fractional order system to reveal the impact of the forgetting process on the system dynamics. Numerical simulations capture system dynamics and reveal that the delayed model system exhibits abundant dynamics, including several stability changes and chaotic behavior. Order of fractional derivative found to be involved in changing the stability property of the system near the coexistence equilibrium state.

This article investigates a diffusive predator–prey system with harvest delay and reproduction delay. A mathematical analysis of the existence of the positive equilibrium points is provided. In the absence of delay, explicit conditions for Turing instability are derived. It is observed that the diffusion coefficient plays a crucial role in the formation of Turing patterns. Furthermore, to study the influence of delays on the system, we follow the method of stability switching curve. The crossing sets are determined for each wave number, which helps deduce the various Hopf bifurcation curves. It is observed that as the delay parameters pass through these curves, the stability of the coexisting equilibrium changes accordingly. From the stability curves, we can infer that the harvest delay has no significant impact on the dynamics of the system when the reproduction delay is low. While for moderate values of reproduction delay, harvest delay can induce a stability switching phenomenon. Moreover, such switching behavior is also observed when the reproduction delay is varied. To further understand these dynamic changes, the properties of Hopf bifurcation are discussed using normal form theory. Numerical simulations are conducted to sustain the theoretical findings.

A Zn(II)‐stabilized radical‐ligand enabled tandem cyclization via radical‐type C(sp3)‐H functionalization of N‐benzylpyridin‐2‐amines with terminal alkynes producing straightforward access to a wide variety of imidazo[1,2‐a]pyridines in moderate to good yields is reported. In the presence of KOtBu the Zn(II)‐catalyst [ZnIILaCl2] (1a) (La = 2‐((4‐chlorophenyl)diazenyl)‐1,10‐phenanthroline) undergoes one‐electron reduction to the active catalyst [ZnII(La)•−Cl2] [1a]− bearing a ligand‐centered radical. Upon coordination of N‐benzylpyridin‐2‐amine to [1a]−, the radical‐ligand abstracts a hydrogen atom from the benzylic position, forming a benzylic radical intermediate which, through radical addition with the alkyne generates a vinyl radical intermediate. Subsequent cyclization via intramolecular nucleophilic attack by the pyridine nitrogen produces imidazo[1,2‐a]pyridines. Control experiments and spectroscopic investigation confirm the radical‐ligand assisted tandem radical‐type C(sp3)‐H activation, addition, and cyclization steps.

The model reduction technique (MRT) is an integral part of the finite element model updating (FEMU) approach to address the issue of incompleteness in measurement. It basically condenses the size of a finite element (FE) model to fit with the available responses at limited degrees of freedom. The developments in MRTs and substructure coupling for structural health monitoring (SHM) applications have been enormous. The MRTs are partly discussed in the review articles on FEMU. However, no article is dedicated explicitly to MRTs in SHM applications. Thus, a review article on MRTs will likely augment the state-of-the-art developments of MRTs in FEMU for SHM applications. This review article synthesises the growing literature on different variants of MRTs in time and frequency domains. In doing so, the fundamentals of MRT, salient modifications on the basic MRTs to ease the computational efforts and understanding of its implementation and related developments are presented first. Further, the developments of various substructure coupling techniques used to reduce the order of large FE models are presented. The authors’ recently proposed improved MRTs are also briefly presented. Finally, the prospects and challenges in MRT and substructuring techniques are critically discussed. The review, in general, reveals that the developments in MRTs are gaining importance due to their excellent capability of handling incomplete measurements, indicating the relevance of reviewing the subject from time to time to update the latest developments.

Starting from Zakharov integral equation, an equation that governs the evolution of a random field of nonlinear gravity waves (known as the sprctral transport equation) with depth-uniform current in deep water has been deduced. In the narrow-band approximation limit of this evolution equation, we have examined the modulational instability in the perturbed wavenumber space. The main objective of this work is to draw the stability diagrams and to study the effect of depth-uniform current on the growth rate of weakly nonlinear gravity waves. It is found that the effect of randomness reduces the growth rate of instability (GRI) and the extent of instability. The coflowing current decreases the growth rate of the instability, whereas the counterflowing current has the opposite effect. Also, we have regained the deterministic instability growth rate for vanishing spectral bandwidth.

This study uses machine learning (ML) to simplify the complex and time-consuming process of predicting the hardness of high-entropy alloys (HEAs). A stacking regression model combined with a Transformed Target Regressor (TTR) is proposed, utilizing three top-performing base models such as support vector regression (SVR), LightGBM (LGBM), and random forest (RF). The model incorporates 20 key thermodynamic, mismatch, and combination parameters (physical features) along with 18 different elements to enhance generalization and account for various input feature effects, specifically to predict the hardness of HEAs. Feature selection was done in two stages using the Pearson correlation coefficient (Pc) and conditional mutual information-based feature selection (CMIFS) methods. The impact of alloy composition and physical features on hardness was analyzed with SHapley Additive exPlanations (SHAP) values and partial dependence plots (PDPs), helping to better understand the model’s predictions. The stacked model outperformed the individual models, achieving an overall R² score of 0.88 and 0.99 for composition and physical features-based data, respectively. Additionally, the non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize the hardness of the HEAs, resulting in a more than 24% increase in hardness compared to the initial data. The optimized composition of Al17.24Fe24.79Cr1.95Mo6.84 Ti13.03 Nb7.89 Hf8.26 was identified as having the highest hardness. This ML workflow serves as a general framework to optimize alloy chemical spaces and input features to achieve desired properties. Overall, this model provides interpretability and generalization through ensemble learning, offering insights for designing high hardness HEAs. Graphical abstract

This study focuses on the preparation of an Mg-Al-Zn-Ca alloy for biomedical applications and examines the impact of post-casting heat treatments on its electrochemical, thermal and mechanical properties. The alloy's detailed degradation behaviour was examined through immersion tests, potentiodynamic polarisation, and electrochemical impedance spectroscopy in a simulated body fluid. Micro-structural characterisation and phase analysis were performed by optical microscopy, scanning electron microscopy and X-ray diffraction. It has been observed that the cooling rate during post-solutionisation heat treatment significantly influences the evolution of α and β phases and subsequently alters the alloys’ mechanical properties and degradation behaviour. The slowest cooling rate in the furnace-cooled sample favoured re-precipitation of the β phase along grain boundaries and demonstrated the highest hardness and corrosion rate. The representative micrographs of the alloy were numerically simulated using level set scheme in COMSOL ® Multiphysics software to investigate galvanic corrosion behaviour.

As compact relativistic objects, white dwarfs are in different classes than neutron stars. Because white dwarfs are comparatively less compact than neutron stars are, the equation of state of a white dwarf is comparatively more certain. In this work, we investigated the basic properties of nonrotating white dwarfs composed of charged perfect fluid in the context of 4D Einstein-Gauss-Bonnet gravity. For example, we derived the mass, radius, energy density, pressure, charge distribution, and electric field of white dwarfs and demonstrated their dependency on the Gauss-Bonnet coupling constant $\alpha$ in terms of the effect of charge. The structural solutions of white dwarfs are obtained by adopting Chandrasekhar’s equation of state and a significant relationship between charged density and energy density. In this context, we solve the TOV equation with the addition of the charge profile numerically by considering appropriate boundary conditions at the center of the star. By adjusting different parameters, we present a detailed graphical discussion of several characteristics of white dwarfs. We emphasize the mass-radius relationship of our proposed white dwarfs and compare the results with the Chandrasekhar mass limit for viable white dwarf structures. Moreover, the nature of the sound speed profile and adiabatic index in the internal structure of white dwarfs are discussed. As a result, we obtain a physically viable charged white dwarf structure with a mass near the Chandrasekhar mass limit in the context of the Einstein-Gauss-Bonnet gravity.

We report an efficient ligand-free cobalt-copper catalyzed cross-coupling reaction of aryl halides with primary amides, and also investigate a new Co0/CoII-based catalytic cycle for this transformation. This reaction successfully couples...

Molecular memristors have emerged as pivotal components in next‐generation electronics, combining redox‐active functionality at the nanoscale with cognitive behaviors. Synthesis, characterization, and redox‐induced interconversion of a new binuclear open‐shell singlet (S = 0) tetra‐radical nickel(II)‐complex, [NiII2(L•–•–)2] (1) featuring two two‐electron reduced dianionic diradical scaffolds 2,9‐bis(phenyldiazenyl)‐1,10‐phenanthroline (L) as a robust resistive switching element is reported. The complex 1 upon one‐electron ligand‐centered oxidation forms a mono‐cationic tri‐radical species [NiII2(L•–•–)(L•–)]⁺ ([1]⁺), which upon further oxidation transforms to a di‐cationic monometallic species [NiII(L⁰)2] [2]²⁺. Controlled ligand‐centered reduction in the presence of excess Ni(II)‐sources such as NiCl2 or Ni(ClO4)2 transforms the mono‐metallic species [2]²⁺ to the binuclear tetra‐radical complex 1. Complex 1 demonstrates exceptional performance as a molecular memristor, including high endurance over 750 cycles, 2‐h data retention, and ultrafast switching speeds of 55 ns. The consistent On/Off conductivity difference under varying environmental conditions makes it promising for robust data storage and data‐processing applications. Moreover, it supports advanced functionalities such as logic gate operations, 4‐bit edge computing, and adaptive learning behavior, positioning it as a versatile building block for next‐generation all‐in‐one electronic technologies.

Improper plastic disposal results in biological magnification since the plastics accumulated in the landfills and in the ocean find their way into the food web – getting increasingly accumulated at the top of the Ecological Pyramid. The degradation of plastic waste can be achieved by chemical, thermal, photo, and biological processes. Anaerobic co-digestion (AcoD) can be applied to biodegrade plastic waste and the organic fraction of municipal solid waste (OFMSW) while ensuring increased process stability and biogas production. While the anaerobic digestion (AD) or anaerobic mono-digestion of only plastics with high carbon content (higher carbon-to-nitrogen ratio) is challenging, the co-digestion with lower carbon-to-nitrogen ratio organic wastes results in increased biodegradation and biogas production. Pretreatment of plastic waste can surely enhance biodegradability and biogas yield, but further investigation is required to determine the economic viability of various pretreatment techniques available. This review highlights the classification of plastics based on their biodegradability, microbial species responsible for biodegradation, and the changes in the properties of plastics during biodegradation under AD and AcoD. Further, the review delves into the crucial process governing factors that affect AcoD and provides current insights for plastic biodegradation using AcoD. Graphical Abstract

Multi-epitope vaccine (MEV) construction is a technique which combines multiple epitopes, both B cell epitopes and T cell epitopes which have the potential to elicit a much stronger immune response compared to a subunit vaccine. Therefore, recently, a lot of research has been focused on development and improvement of multiepitope vaccines. The strategy of designing a MEV in silico lies in a few basic steps, including procuring the amino acid sequence of the B cell and T cell epitopes from literature search, bioinformatics approach, to construct a potent immunogen capable of eliciting both humoral and cell-mediated response and finally joining these epitopes by linkers. However, a vaccine constructed by merely joining the epitopes may not always result in a stable globular structured protein. In this study, we have focused on developing a strategy where a potential vaccine candidate of Mycobacterium tuberculosis has been used as a scaffold and the low complexity regions of this scaffold have been replaced by the predicated epitopes. Essentially, instead of joining the epitopes by linkers, they have been carefully positioned on a scaffold of a protein that is itself a vaccine candidate to derive a MEV against Mycobacterium tuberculosis. In this study, a methodology has been detailed to tackle this great challenge using a simple approach of protein engineering. A scaffold-based MEV has been designed against Mtb by converting a vaccine candidate protein, Ag85A, into a scaffold by truncating its low complexity non-immunogenic regions, and the gaps were supplemented by the highly immunogenic epitopes. Replicated 500 ns molecular dynamics simulation at different temperatures (300 K and 310 K) and principal component analysis proved that MEV built on the scaffold is more stable than the conventional one.

Sustainability issues in mining regions of India are resolved by implementing a decision-making framework on design and implementation of sustainability programs. The guidelines framed by the international agencies are mostly focussing on formulation and implementation of sustainable development frameworks (SDFs) for the entire mining sector of a nation. As site specific mining, environmental and social sensitivities vary from mine to mine, sustainable development programs for mines should be executed at the micro level, that is, at the level of an individual mine unit. Sustainability programs should be planned on the basis of perceptions of the local people. Spatial decision-making framework is integrated with the site selection process where sustainability programs can be carried out. In this paper, a spatial framework is developed by incorporating Analytic Hierarchy Process (AHP), Fuzzy AHP, GIS and Multi-Criteria Decision Making (MCDM) and need priorities of the local villagers. This spatial framework reveals that in a mining region the areas allocated, around a mine site, for agriculture, afforestation, waste dumping sites, and rehabilitation for are roughly 10%, 30%, 11%, and 29% of the buffer zone area (within a 10-km radius of the mining zone) respectively. There is a significant research need towards the design of spatial frameworks by integration of stakeholder perception, site suitability analysis, and removing ambiguity in stakeholder responses. This paper demonstrates an innovative strategy to fill this research gap.

The objective of this work is to create a magnetostrictive energy harvester (MEH) using Galfenol to assess the structural health of bridges under automotive loads. The MEH is subjected to controlled vibrations—square, triangular, and sinusoidal waves—using a modified cantilever configuration. It generates a voltage difference across the pickup coil terminals using a Galfenol transducer as the magnetostrictive material, which is then converted into steady DC voltage via a rectification cum warning circuit. The effectiveness of the energy harvester has been confirmed through an experimental setup and expanded to monitor the state of a prototype bridge. The MEH produces varying voltages in response to vibrations in its surroundings, allowing for the differentiation between the healthy condition and the declining condition of bridges. Additionally, an adaptive neuro‐fuzzy inference system enables the creation of predictive models based on the existing experimental data. This provides vital insights into the viability of real‐time monitoring and early detection of structural anomalies in bridge structures. This study demonstrates the effectiveness of utilizing Galfenol‐based magnetostrictive energy harvesting to enhance the safety and efficiency of infrastructure maintenance. This technology additionally enhances the durability and long‐term viability of transportation networks.

Two high spin Fe(III) complexes, [Fe(L¹)2]Cl ⋅ H2O (1) and [Fe(L²)2]Cl ⋅ 4H2O ⋅ 0.5MeOH (2), of Schiff base ligands of aminoguanidine with salicylaldehyde and pyridoxal (isolated as the hydrochloride salts L¹H2⁺Cl⁻ and L²H3²⁺Cl⁻2 respectively) are reported. X‐ray crystal structure of both the complexes along with their spectroscopic and variable temperature magnetic properties are also investigated. It is found that complex 2 shows stronger zero field splitting (D=9.5 cm⁻¹) than complex 1 (D=5.5 cm⁻¹), probably due to greater distortion of the Fe(III) coordination polyhedron in complex 2. TD‐DFT calculations are used to assign the electronic spectra of the complexes. Both the ligands show fluorescence at 450–460 nm with lifetime of nanosecond order and quantum yield of 0.04–0.07 at room temperature. Both the Fe(III) complexes are found to efficiently catalyze the aerial oxidation of DTBC to DTBQ with the turn over numbers 100–155 h⁻¹, which is among the highest for mononuclear Fe(III) complexes. The complexes also act as very good fluorometric sensor for S²⁻, and the limit of detection (LOD) is in the octa‐molar region. The pH and temperature dependences of the sensing are also investigated.