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Sprouting in Seeds Aided by Nitrogen Sourced from Ammonia Fumes Leached from Aluminum Dross
Nitrogen and water are nutrients essential for the sprouting of seeds and healthy growth of plants. The seeds derive nitrogen from ammonia (NH3), found in ammonium hydroxide commonly added as manure to the soil. In a materials synthesis process, NH3 gas was released when Aluminum-dross (Al-dross), a hazardous industrial foundry waste was beneficiated to extract useful materials (metallic Al, oxides of Al and Mg, etc.) from the waste. Chemical tests, SEM with EDS and XRD were used to characterize sieved black Al-dross (starting raw material) before and after the beneficiation process. Al-dross also contained significant quantities of aluminum nitride (AlN). When treated with an aqueous media (plain or carbonated water), the AlN reacted to release NH3 gas fumes. This work explored the potential of using this gas to act as a source of nitrogen to accelerate the sprouting of seeds and plant germination. Vegetable and fruit seeds were sown in the soil that was directly infused with the NH3 released from Al-dross for two hours, followed by several (8 to 12) hours of self-diffusion time for homogeneous distribution of the gas in the soil. Five pairs of soils (untreated regular and NH3 fumes treated soils) were prepared under similar conditions. 5 different vegetable and fruit seedlings were planted in these pairs of soils. The germination patterns and growth of the sprouts with time were observed. The seeds that preferred an alkaline environment for germination (e.g., ridge gourd and watermelon seeds) sprouted early and in good health in the NH3 treated soil. Seeds preferring acidic soils did not germinate well in NH3 fume-infused soils. The experiments confirmed the viability of the novel concept, where the waste ammonia fumes released from Al-dross could be favorably generated and used in a controlled manner to promote sprouting of certain agricultural seedlings. 2023 Elsevier Ltd. All rights reserved. -
Sputter deposited tungsten oxide thin films and nanopillars: Electrochromic perspective
Tungsten oxide (WO3) thin films and nano pillars were grown on FTO and corning substrates by using DC magnetron sputtering. Structural properties, surface morphology, optical properties, and electrochromic properties were systematically characterized by using SEM, XRD, UVVis Spectrometer, and Electrochemical Analyser respectively. Increased oxygen partial pressure resulted a rise in the optical transmittance from 72% to 89% at a wavelength of 600 nm. Moreover, coloration efficiency was also found to vary with partial pressures for both planar and glad from 30.48 cm2C-1 to 78.36 cm2C-1. We observe that glad deposited nano pillars showing higher coloration efficiency as compared to the planar thin film. The coloration efficiency found for the planar thin film and nano pillars at optimized partial pressure are 37.04 cm2C-1 and 78.36 cm2C-1 respectively. A strong influence of oxygen partial pressure and surface to volume ratio has been observed on the coloration efficiency, which can play a major role in the electrochromic application. 2022 Elsevier B.V. -
SR-Mine: Adaptive Transaction Compression Method for Frequent Itemsets Mining
Extraction of frequent itemsets is a key step in association rule mining. Frequent Pattern (FP) mining from a very large dataset is still a challenging research problem. The basic frequent itemset algorithms are Apriori and FP-growth. FP-growth uses Frequent Pattern Tree (FP-tree) to store the database information in a compressed form. A large number of research papers have been proposed as an improvement of the basic frequent itemset mining algorithms. Several researchers have proposed modifications to existing data structures as well as new data structures to improve the mining process. A new method, Size Reduced Mining (SR-Mine), is proposed to speed up the FP-tree creation. The proposed work is implemented with the basic FP-growth algorithm and with the other two recent algorithms based on FP-tree. The three modified algorithms have been tested with standard datasets and compared with the original algorithms. The proposed method can be applied with the frequent itemset mining algorithms which consider each transaction one by one to construct a data structure for mining. The experimental results show that the proposed method can improve the performance of the mining. 2021, King Fahd University of Petroleum & Minerals. -
Sridevi's Stardom as A Cultural Vehicle for Women Empowerment and Social Commentary: A Textual Analysis of English Vinglish (2012) and Mom (2017)
In the Indian film sector, stardom is more than mere performance; it operates as a cultural text that produces impacts and negotiates with social values, ideals, and contradictions. Female stardom, in this way, is particularly potent in generating discourses of gender and empowerment, both disrupting patriarchal norms while enacting socially accepted moral orders. Sridevi's stardom carries specific cultural resonance, as the films she stars in offer a blend of popular entertainment while carrying deeper social significance. This study seeks to understand Sridevi's stardom and the potential for her representation of women's empowerment, as well as social commentary by analysing the films English Vinglish (2012) and Mom (2017). The study explores the implications related to Sridevi's star persona as a cultural and ideological site for women's empowerment and social critique in contemporary Indian cinema. It applies a purposive sampling method, and utilises textual analysis to investigate performance style, narrative structures, visual framing and symbolic meaning signifying women's power and resilience. The textual analysis of English Vinglish finds empowerment framed through self-assertion and linguistic competence within familial and social spaces whereas in Mom empowerment emerges in the more ambiguous domain of maternal justice and moral authority. Taken collectively, these films showcase how Sridevi's stardom functioned as a cultural vehicle, entertaining audiences while provoking critical consideration of women's roles, autonomy, justice, and empowerment within contemporary Indian society. 2026, Iquz Galaxy Publisher. All rights reserved. -
SS-CNN BruiseFinder: Hyperspectral imaging and CNN-driven spatial-spectral fusion for non-destructive plum bruise analysis
Plum fruit is susceptible to damage at various stages, from growth to packaging, and such bruising is often difficult to detect visually due to its subtle surface appearance. This research seeks to develop a convolutional neural network (CNN) model that leverages 3D convolutional layers to integrate spatial and spectral features from hyperspectral data, enabling accurate bruise analysis in plum fruit. In this study, plums sourced from a Norwegian fruit store were intentionally bruised and then imaged using hyperspectral technology at various time intervals (30 min to 48 h post-bruising). A novel CNN model, dubbed SS-CNN BruiseFinder, is developed to harness the spatial and spectral characteristics of these hyperspectral images for accurate bruise detection and classification. The SS-CNN BruiseFinder model demonstrates detection accuracy ranging from 68.5% to 91.5% and categorization accuracy between 67.39% and 98.16%. To further establish the effectiveness of this approach, three additional deep learning models a custom spectral CNN, ResNet 101, and a bidirectional LSTM model are developed and evaluated on the same dataset, providing a comprehensive validation of the proposed method's superiority. Timely detection of bruising helps prevent contaminated plums from entering the supply chain during transportation or storage. By categorizing plums based on bruise age, retailers can offer consumers more accurate freshness and quality information, enabling them to make better-informed purchasing choices and ultimately enhancing the overall shopping experience. To encourage community engagement and re-implementation, our code is available at https://github.com/SS-CNN BruiseFinder. 2025 Elsevier Ltd -
Stability Analyses of BrinkmanBard Convection in Hybrid-Nanoliquid Saturated-Porous Medium Using Local Thermal Non-equilibrium Model
This paper carries out linear and weakly non-linear stability analyses of natural convection in a Newtonian hybrid-nanoliquid saturated porous medium. The Boussinesq approximation is assumed to be valid in the study, and a two-phase energy model is used. The weighted residual Galerkin technique is employed to obtain the expression for the Rayleigh number and Lorenz model by using a truncated double Fourier series solution. The quadratic non-linear Lorenz model is solved numerically by using the RungeKuttaFehlberg method. Water is considered as a carrier liquid, and copper and alumina nanoparticles are considered with dilute concentration. Linear stability analysis reveals the onset of convection prepones in a hybrid nanoliquid-saturated porous medium. The amount of heat transport is maximum in a hybrid nanoliquid saturated porous medium and minimum in a liquid-saturated porous medium. Local thermal non-equilibrium situation ceases at higher rates of interphase heat transfer coefficient. The assumption of local thermal non-equilibrium is prominent in hybrid nanoliquid saturated porous medium. The results of the hybrid-nanoliquid channel, a hybrid nanoliquid saturated porous medium with the local thermal assumption, are presented as a limiting case of the study. 2024, The Author(s), under exclusive licence to Springer Nature India Private Limited. -
Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review
Wheeled mobile robots (WMRs) have been a focus of research for several decades, particularly concerning navigation strategies in static and dynamic environments. This review article carefully examines the extensive academic efforts spanning several decades addressing navigational complexities in the context of WMR route analysis. Several approaches have been explored by various researchers, with a notable emphasis on the inclusion of stability and intelligent capabilities in WMR controllers attracting the attention of the academic community. This study traces historical and contemporary WMR research, including the establishment of kinetic stability and the construction of intelligent WMR controllers. WMRs have gained prominence in various applications, with precise navigation and efficient control forming the basic prerequisites for their effective performance. The review presents a comprehensive overview of stability analysis and navigation techniques tailored for WMRs. Initially, the exposition covers the basic principles of WMR dynamics and kinematics, explaining the different wheel types and their associated constraints. Subsequently, various stability analysis approaches, such as Lyapunov stability analysis and passivation-based control, are discussed in depth in the context of WMRs. Starting an exploration of navigation techniques, the review highlights important aspects including path planning and obstacle avoidance, localization and mapping, and trajectory tracking. These techniques are carefully examined in both indoor and outdoor settings, revealing their benefits and limitations. Finally, the review ends with a comprehensive discussion of the current challenges and possible routes in the field of WMR. The discourse includes the fusion of advanced sensors and state-of-the-art control algorithms, the cultivation of more robust and reliable navigation strategies, and the continued exploration of novel WMR applications. This article also looks at the progress of mobile robotics during the previous three decades. Motion planning and path analysis techniques that work with single and multiple mobile robots have been discussed extensively. One common theme in this research is the use of soft computing methods to give mobile robot controllers cognitive behaviors, such as artificial neural networks (ANNs), fuzzy logic control (FLC), and genetic algorithms (GAs). Nevertheless, there is still a dearth of applications for mobile robot navigation that leverage nature-inspired algorithms, such as firefly and ant colony algorithms. Remarkably, most studies have focused on kinematics analysis, with a small number also addressing dynamics analysis. 2023 by the authors. -
Stability Analysis of AFTI-16 Aircraft by Using LQR and LQI Algorithms
The stability analysis of the dynamical system of linearized plant model of Advanced Fighter Technology Integration (AFTI)-16 aircraft was proposed along with the optimal control methods by applying linear quadratic regulator (LQR) and linear quadratic algorithm (LQI) algorithms. The LQR and LQI algorithms results were compared with state-space model analysis results. The state-space methods like pole placement method, without using the LQR algorithm the negative feedback system were found to be unstable. By the application of LQR and LQI algorithms to the linearized plant AFTI-16 aircraft open-loop system having negative feedback found to be stable. The stability parameters were verified by using MATLAB programming software. The eigenvalues play a key role in finding closed-loop system stability analysis. MIMO dynamical system with state feedback gain matrices is calculated by using MATLAB programming software. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Stability Analysis ofSalt Fingers forDifferent Non-uniform Temperature Profiles inaMicropolar Liquid
This paper describes the linear stability analysis of salt finger convection for different non-uniform temperature profiles by keeping the solutal concentration uniform throughout the system. The system consists of two parallel plates separated by a thin layer of micropolar liquid with infinite length, in which the system is heated and soluted from above the plate. Normal mode techniques are used to convert the system of partial differential equations into ordinary differential equations; further, Galerkian method is introduced to get the eigenvalue for isothermal, permeable with no-spin boundary conditions. The study also explains the effect of different micropolar parameters on the onset of convection. The phase of temperature flow for different boundary conditions explains the graphical solution of the energy equation and its gradients. It is shown that non-uniform temperature profiles, diffusivity ratio, coupling parameter, and solutal Rayleigh number influence the stability of the system. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Stability and bifurcation analysis of a fractional-order preypredator model with ratio-dependent functional response
This paper explores the dynamics of a fractional preypredator system with a ratio-dependent functional response with memory and hereditary effects in predatorprey interactions. The model is developed by the Caputo fractional derivative, and the existence, uniqueness, positivity, and boundedness of solutions are proven to satisfy biological reality. Stability conditions for local and global stability of both predator-free and coexistence equilibria are proven through linearization and Lyapunov function techniques. The fractional order is used as a bifurcation parameter, and the appearance of Hopf bifurcations is analytically explained with demonstration of the influence of memory on oscillations. To examine discrete-time dynamics, the piecewise constant argument is used to derive a discrete counterpart of the fractional model. The discrete model indicates a wide range of rich complex oscillatory phenomena, including period-doubling and NeimarkSacker bifurcations, leading to periodic, quasiperiodic, and chaotic oscillations. Numerical computations, including bifurcation diagrams, phase portraits, and Lyapunov exponents, verify the analytical results and describe the routes of transition to chaos. A comparative analysis to compare integer- and fractional-order cases indicates that memory effects enhance dynamical richness and sensitivity to parameters. The study provides a unified framework relating continuous fractional dynamics and their discrete implementations and provides additional insight into how memory and discretization interact to modify stability and bifurcation in ecological models. 2026 the Author(s), -
Stability and durability studies on platinum-decorated CNTs electrocatalyst synthesized via microwave-assisted polyol method for PEM fuel cell
In this study, an efficient and viable microwave-assisted polyol route was adopted to decorate Pt nanoparticles on multi-walled carbon nanotubes (CNT). Carbon corrosion tests were conducted on bare CNT (T), functionalized CNT (f-T), and commercial carbon (Vulcan XC-72R); our results indicate that f-T have the highest resistance toward corrosion, indicating its high stability in corrosive environments. The cyclic voltammetry curves were obtained before and after 5000 cycles by subjecting the electrocatalyst to harsh potential cycling; our test results imply that Pt/CNT are more durable when compared to commercial Pt/C. Then, fuel cell studies comprising Pt/CNT as cathode electrocatalyst was studied, and the results showed enhanced performance (maximum power density: 384 mW cm?2) for Pt/f-T than commercial Pt/C (367 mW cm?2) in Polymer electrolyte membrane (PEM) fuel cell, indicating the potential use of carbon nanotubes as support in PEM fuel cell. The Author(s), under exclusive licence to The Materials Research Society 2025. -
Stability and Effciency Enhancement of Perovskite Solar Cells
The greatest notable efficiency increases in recent years have been observed in perovskite solar cells (PSCs). With an ABX3 crystal structure, perovskite is an organic-inorganic hybrid chemical that generally has an arrangement similar to that of BaTiO3-. In this configuration, X stands for halogens, such as oxygen (O), iodide (I?), bromide (Br?), or chloride (Cl?), while A and B are variously sized cations that coordinate 12-fold and 6-fold, respectively, with X anions. Cations such as formamidine and methylammonium alter the lattice parameters, with the bandgap growing as the lattice parameters increase, but they have no direct effect on the valence band maxima. Comparable to the body-centered cubic lattice with extra anions on a unit cell's faces is the ideal perovskite structure. To achieve high power conversion efficiency (PCE), perovskite absorbers and PSC device topologies must have high charge. Consequently, increasing electron mobility, prolonging carrier life span, and lowering defect density all depend on improving the perovskite absorber's material quality. 2026 selection and editorial matter, T.D. Subash, J. Ajayan, and Leong Wai Yie; individual chapters, the contributors. -
Stability and statistical analysis on melting heat transfer in a hybrid nanofluid with thermal radiation effect
The dual solutions for the stagnation point flow in a cobaltCeO2/kerosene hybrid nanofluid with melting heat transfer and thermal radiation are analyzed. The partial differential equations are solved by the conversion of the partial differential equations into nonlinear ordinary differential equations by utilizing suitable scaling group transformations. Numerical solutions are obtained by employing the built-in function in the MATLAB software (bvp4c). Physically recoverable solutions are found employing stability analysis. The factor variables of interest (melting parameter, the nanoparticle volume fraction of cobalt and CeO2) are then further analyzed by utilizing the sensitivity analysis (based on the response surface methodology model) for heat transfer rate, as well as the skin friction coefficient. It is found that the heat transfer and skin friction tend to be significantly higher in a hybrid nanofluid due to the radiation and melting heat transfer. The lower branch is found to be unstable, whereas the upper branch is found to be stable. Also, the heat transfer rate and skin friction coefficient are found to be negatively sensitive toward the melting parameter. The model in this study can be applied for microscopic propulsion systems and the nano-electromechanical systems integrated with a nano-based system. IMechE 2021. -
STABILITY IN CHAOS: IMPACT OF MONETARY, FISCAL, AND FIRM CHARACTERISTICS ON INVESTOR SENTIMENT IN ASIAN EMERGING MARKETS
This study investigates the impact of firm characteristics, monetary policies, and fiscal policies on investor sentiment, specifically focusing on market volatility and trading volume in six Asian emerging markets during the pre-pandemic and pandemic periods. Using panel data regression on a sample of 5,619 firms between 2015 and 2023, this study analyses the distinct roles of firm-specific factors and macroeconomic policies in shaping market behaviour during periods of economic instability. The findings reveal that firm characteristics such as capital structure and payout policies consistently drive both volatility and trading volume. Monetary policies, particularly interest rates and money supply, showed heightened significance during the pandemic, while fiscal policies, though largely insignificant pre-pandemic, became more relevant during the crisis. The study's results provide critical insights for policymakers and investors on the dynamic interplay between firm-level and macroeconomic factors during crisis periods, emphasising the need for coordinated policy responses. 2024, Universiti Malaysia Sarawak. All rights reserved. -
Stability of porous medium convection in polarized dielectric fluids with non-classical heat conduction
International Journal of Mathematical Archive Vol.4, Issue 4, pp.136-144, ISSN No. 2229-5046 -
Stability Testing and Restoration of a DEIG-Based Wind Power Plant with Indirect Grid Control Strategies
In the current scenario, because of government policies, environmental factors, and technological improvements, there is a rapid growth in renewable energy sector. The emphasis is to obtain better system performance by effective resource utilization and providing security and reliability. This paper discusses the design and implementation of indirect grid control of a wind power plant by controlling the parameters in both grid and rotor side converters. The proposed system consists of Doubly Excited Induction Generator (DEIG) with Wind turbine system (WTS) and Mechanical and Electrical Power Controlling Systems (MPCS-EPCS). Various transmission line faults (symmetrical and asymmetrical faults) incur power imbalances in power grid. The developed MPCS and EPCS are helpful to perform grid monitoring and controlling under different types of faulty conditions. The MPCS monitors the effective source utilization and EPCS helpful for matching the grid energy levels under normal and faulty conditions. Modification in the converter topologies to minimize the impact of adverse effects of faults on the DEIG-WTS and to improve resiliency in the power grid is also discussed. To improve the stability and enhancing resource utilization to improve the efficiency of the overall system with the enhancement of fault voltage ride-through capability in DEIG-WTS under fault conditions are also considered. The stability of the system is tested under steady-state and dynamic-state conditions by applying faulty conditions in MATLAB/Simulink environment. 2023 IETE. -
Stable copper nanoparticles as potential antibacterial agent against aquaculture pathogens and human fibroblast cell viability
The developments of green nanotechnology are generating interest of researchers towards synthesis of copper nanoparticles due to their increasing application towards the biomedical field. The utilization of phytochemicals in plant extracts have become a valuable trend in the synthesis of nanoparticles as they possess dual nature of reducing and stabilizing agents. In this work a simple and rapid biosynthesis route for producing stable fenugreek copper nanoparticles (FCuNPs) using Trigonella foenum-graecum is demonstrated and assessed its antibacterial activity against gram negative Vibrio species. The characterization of synthesized FCuNPs was carried out using UVvis spectrophotometer and the SPR of FCuNPs is observed at 350 nm. TEM, HRTEM SAED analysis was done to evaluate the morphology and size of FCuNPs. FTIR spectra of both the plant extract and FCuNPs were recorded in order to study the interaction of phytochemicals with FCuNPs. The antibacterial activity of biosynthesized FCuNPs was tested against V. vulnificus, V. harveyi and V. parahaemolyticus using agar well diffusion technique. Since this method of synthesizing copper nanoparticles does not involve any harmful chemicals, the FCuNPs produced are more biocompatible and were used to evaluate human skin fibroblast cell line by Alamar Blue reduction assay. The outcomes of this report will surely provide a new path in the field of nanotechnology and nano medicine where there is a significant need of antibacterial and cell viability studies. Hence, FCuNPs can be powerful therapeutic materials in numerous biomedical applications, which are to be discovered in the near prospective. 2021 Elsevier Ltd -
Stablecoins Unveiled echnical Definitions, Economic Taxonomy, and Comparative Analysis of Fiat-Backed, Crypto-Collateralised, lgorithmic, and CBDC
Stablecoins are a foundational innovation in digital finance engineered to maintain price stability by linking their value to reference assets such as fiat currencies. This chapter provides a technical and economic definition of stablecoins, classifying them into fiat-backed, crypto-collateralised, algorithmic, and hybrid categories. Through comparative analysis of USD Coin (USDC), Tether (USDT), DAI, and TerraUSD (UST), alongside recent hybrid and CBDC implementations, it examines stability mechanisms such as 1:1 reserve backing, smart contract-based collateral management, and protocol-defined supply adjustments. Evidence shows fiat-backed stablecoins maintain stronger pegs and market dominance, while crypto-collateralised and algorithmic models face volatility, capital inefficiency, and systemic risk exemplified by UST's collapse. Hybrid models like DJED and JANUS propose innovative stabilisation techniques though largely theoretical. Drawing on market data and case studies, the chapter highlights regulatory, technical, and policy distinctions between private stablecoins and CBDCs. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Stacked Ensemble Method of Multi Class Malware Detection Using PE Header and Section Attributes
Malware has now become sophisticated. The type of attacks has changed, too. To identify and remove them is now a great challenge. This paper presents a machine learning model for malware detection in windows. The Malware is detected based on the static collection of features, which includes the Portable Executable (PE) Header and Section data. Several classifiers were trained on a balanced dataset, including Logistic Regression, K-Nearest Neighbour, Support Vector Machine, Multi-Layer Perceptron, XGBoost, and Stacked Ensemble. The proposed stacking method utilises SVM, MLP, and XGBoost, with XGBoost serving as the meta-learner. The model delivered the best performance when compared with all the baseline models for an accuracy of 96.25% and an AUC of 0.9978. 2025 IEEE. -
Stacked LSTM a Deep Learning model to predict Stock market
The goal of Stock Market Prediction is to forecast the future value of a company's financial stocks. The use of machine learning and deep learning technologies in stock market prediction technologies is a recent trend. Machine learning makes predictions based on the values of current stock market indices by training on their previous values in sequential timely order using the artificial neural network, while deep learning makes predictions based on the values of current stock market indices by training on their previous values in sequential timely order using the artificial neural network. 2022 IEEE.