Comprehensive Analysis Of Dynamics Research Articles

Single file motion of robot swarms

We present experimental results on the single file motion of a group of robots interacting with each other through position sensors. We successfully replicate the fundamental diagram typical of these systems, with a transition from free flow to congested traffic as the density of the system increases. In the latter scenario we also observe the characteristic stop-and-go waves. The unique advantages of this novel system, such as experimental stability and repeatability, allow for extended experimental runs, facilitating a comprehensive statistical analysis of the global dynamics. Above a certain density, we observe a divergence of the average jam duration and the average number of robots involved in it. This discovery enables us to precisely identify another transition: from congested intermittent flow (for intermediate densities) to a totally congested scenario for high densities. Beyond this finding, the present work demonstrates the suitability of robot swarms to model complex behaviors in many particle systems. Published by the American Physical Society 2024

Blueprints for Progress: Unveiling the Pillars of Urban Evolution in Contemporary American Metropolises

This paper presents a comprehensive analysis of urban development dynamics within the United States, using a dataset provided by the International City/County Management Association (ICMA). The study aims to identify and understand the factors that significantly affect urban growth and sustainability. Through rigorous preprocessing and validation processes, including factor analysis and comparative studies, the study examined variables such as infrastructure development, forms of local government, regional influences, and service provisions. The results highlighted the critical role of infrastructure development in urban growth, with a strong correlation between well-developed infrastructure and sustainable urban development. The form of government and regional characteristics also emerged as influential factors, affecting policy formulation and resource allocation. Notably, services provided by local governments were found to be crucial in supporting urban development. This study sheds light on the complexities of urban development dynamics and offers insights into how policy, governance, and infrastructure impact urban growth and sustainability. It underscores the necessity for tailored approaches that consider local contexts and the specific needs of urban populations. The paper concludes with recommendations for future research, emphasizing the need for longitudinal studies, qualitative insights, and policy impact assessments to build upon the findings and support the development of effective urban development strategies.

THE INVESTMENT PATTERN AND BANKING NEEDS OF THE HOUSING SOCIETIES.

THE INVESTMENT PATTERN AND BANKING NEEDS OF THE HOUSING SOCIETIES THE INVESTMENT PATTERN AND BANKING NEEDS OF THE HOUSING SOCIETIES. UNDER THE GUIDANCE OF Prof. Reji john SOB, GALGOTIAS UNIVERSITY SUBMITTED BY Bineet yadav 22GSOB2010640 MBA 2022-2024 SCHOOL OF BUSINESS GALGOTIAS UNIVERSITY ABSTRACT This study delves into the investment patterns and banking requirements of housing societies, examining their financial management practices for sustainability and growth. Through a comprehensive analysis of market dynamics, company performance, risk assessment, valuation methods, investment strategies, and portfolio management, this research aims to provide insights into effective financial decision-making within the housing society sector. • Market Analysis: The market analysis section explores the macroeconomic factors influencing the housing society sector, including demographic trends, urbanization rates, regulatory environment, and economic indicators. It assesses the demand for residential properties, rental yields, and competition among housing societies. Additionally, it examines the impact of market volatility and economic cycles on investment decisions within the sector. • Company Analysis: Company analysis focuses on the financial performance and operational efficiency of housing societies. It evaluates key metrics such as revenue growth, profit margins, asset utilization, and liquidity ratios to assess the financial health of individual housing societies. Furthermore, it examines governance structures, management capabilities, and strategic initiatives undertaken by housing societies to enhance shareholder value and mitigate risks. • Risk Assessment: Risk assessment involves identifying and evaluating various risks inherent in investing in housing societies. These risks may include market

Characterization of Aerosol and CO2 Co-Emissions around Power Plants through Satellite-Based Synergistic Observations

The tracking of carbon and aerosol co-emissions is essential for environmental management. Satellite-based atmospheric synoptic observation networks provide large-scale and multifaceted data to help resolve emission behaviors. This study employs a comprehensive analysis of atmospheric dynamics, combustion byproducts, and aerosol characteristics around power plants. Strong correlations between Aerosol Optical Depth (AOD) at 500 nm and the column-averaged dry-air mole fraction of carbon dioxide (XCO2) were observed, revealing synchronous peaks in their emission patterns. The investigation into combustion completeness utilized metrics such as the ratio of carbon monoxide (CO)/XCO2 and Black Carbon Extinction (BCEXT)/Total Aerosol Extinction (TOTEXT). Discrepancies in these ratios across cases suggest variations in combustion efficiency and aerosol characteristics. Nitrogen dioxide (NO2) distributions closely mirrored XCO2, indicating consistent emission patterns, while variations in sulfur dioxide (SO2) distributions implied differences in sulfide content in the coal used. The influence of coal composition on AOD/XCO2 ratios was evident, with sulfide content contributing to variations besides combustion efficiency. This multifactorial analysis underscores the complex interplay of combustion completeness, aerosol composition, and coal components in shaping the air quality around power stations. The findings highlight the need for a nuanced understanding of these factors for effective air quality management.

Facilities and Equipment Service Management Model: Team Motivation Practices

This study aims to deepen knowledge of hospital service management, with a focus on functions, procedures and processes related to non-medical Facilities and Equipment. Using four interviews with key professionals and a questionnaire completed by 52 employees, the research explores common themes and their practical implications. The study offers a comprehensive analysis of hospital dynamics, highlighting the complexity of functions and procedures for operational efficiency. It identifies effective process monitoring as crucial to the timely completion of hospital activities and proposes areas for improvement, such as process management and digitalisation, providing valuable guidance for managers and healthcare professionals.

Ratio Analysis of Axis Bank

This report presents a thorough examination of AXIS Bank's financial performance utilizing ratio analysis as the primary tool. Ratio analysis offers a quantitative method to assess the bank's financial health and operational efficiency by comparing key financial metrics over time and against industry benchmarks. The analysis begins by evaluating AXIS Bank's current ratio, which measures the proportion of current assets to current liabilities. A higher current ratio indicates a greater ability to cover short-term obligations, suggesting a healthy liquidity position. Conversely, a lower ratio may raise concerns about liquidity risk. In the case of AXIS Bank, the current ratio analysis reveals a robust position, indicating a prudent allocation of resources towards current assets. Furthermore, the report explores the quick ratio, also known as the acid-test ratio, which provides a more stringent assessment of liquidity by excluding inventory from current assets. This ratio helps determine the bank's ability to meet short-term obligations without relying on inventory liquidation. Comparing the quick ratio with the current ratio provides additional insights into the composition of AXIS Bank's current assets and its liquidity management practices. Additionally, the analysis considers the fixed/worth ratio, which assesses the proportion of fixed assets financed by owner's equity. A higher fixed/worth ratio suggests greater reliance on equity financing for fixed asset investments, indicating a lower financial risk. Conversely, a lower ratio may signal higher leverage and potential financial vulnerability. Evaluating this ratio provides valuable insights into AXIS Bank's capital structure and risk management strategies. Furthermore, the report examines the cash flow statement to assess the bank's cash generation and utilization across operating, investing, and financing activities. Analyzing cash flow patterns helps identify trends in cash generation, liquidity management, and investment decisions. In the case of AXIS Bank, the analysis reveals a positive trend in cash generated from operating and financing activities, indicating healthy cash inflows. However, negative cash flow from investing activities warrants further investigation into the bank's investment strategies and capital expenditure decisions. Overall, this comprehensive analysis of AXIS Bank's financial ratios and cash flow dynamics provides valuable insights into the bank's financial position, liquidity management, and operational efficiency. The findings offer a basis for strategic decision-making and recommendations to optimize performance and ensure sustained growth and stability..

Unlocking Sri Lanka's Tax Landscape: A Comprehensive Analysis of Tax Burden and Policy Dynamics in a Sri Lanka

Unlocking Sri Lanka's Tax Landscape: A Comprehensive Analysis of Tax Burden and Policy Dynamics in a Sri Lanka

Exploring the potential of tin-based perovskite-silicon tandem solar cells through numerical analysis: A pathway to sustainable energy innovation

“Necessity is the mother of invention.” The global imperative to transition from fossil fuels to renewable energy sources, driven by the pressing issue of climate change, highlights the significance of advancing solar energy technologies. While single junction solar cells have reached a peak efficiency of approximately 31 %, the pursuit of higher efficiency has led to the exploration of tandem solar cell architectures, including perovskite-silicon and all-perovskite configurations. However, the widespread use of lead in perovskite structures raises environmental and health concerns. In response to these challenges, this study proposes a novel approach by integrating a tin-based wide bandgap absorber layer with a silicon HIT solar cell (Heterojunction with Intrinsic Layer). The investigation consists of an extensive exploration of six different carrier transport layers (CTL) for the top perovskite layer, considering variations in thickness and defect density. A comprehensive analysis of charge carrier dynamics within the device is conducted to understand the role of defect density in influencing solar cell performance parameters. Simulation results show that the overall tandem device gives an encouraging PCE of 32.12 % in 2 T configuration due to its excellent high value of current density matching 17.63 mA/cm2 and open-circuit voltage of 2.19V. We sincerely hope that our work will open new avenues in the field of Solar Photovoltaics paving the way for future innovations.

A comprehensive analysis and future projection of land use and land cover dynamics in a fast-growing city: A case study of Sekondi-Takoradi metropolis, Ghana

Sekondi-Takoradi is the most urbanized metropolis in the Western region of Ghana. Over the past two decades, it has experienced rapid shifts in both population density and land cover. Unfortunately, these transformations have significantly altered the natural landscape and expanded urban coverage. Previous studies have not established enough evidence on land use and land cover changes in the metropolis. For this reason, this study examined the existence, rate, and spatial distribution of land use and land cover as well as the future changes in land cover in the metropolis. Landsat imagery spanning from 1991, 2009, 2016, to 2023 provided the basis for evaluating the spatiotemporal dynamics of land use and cover within the metropolis. The Random Forest Classification algorithm was employed to categorize the images into three distinct classes: water, vegetation, and built-up areas. Analysis revealed a rapid growth in built-up areas by 63.08 km² (32.91 %), accompanied by a decrease in vegetation and water coverage by 60.99 km² (31.82 %) and 2.08 km² (1.09 %) respectively. This highlights the accelerating urbanization trend, emphasizing the critical need for vigilant monitoring and controlled urban expansion to mitigate potential adverse effects. Projections for 2030 indicate further changes with water areas decreasing to 1.21 km² (0.63 %), vegetation diminishing to 95.31 km² (49.73 %), and built-up areas expanding to 95.14 km² (49.64 %). This signifies a significant shift towards built-up areas, altering the metropolis' land cover composition and potentially impeding the achievement of Sustainable Development Goal 11. Understanding these changes in land use and land cover holds significant value for policymakers, enabling them to effectively monitor and safeguard natural resources.

Influence of a Pair of Unequal Rotational Fluxes On Entrained Gaseous Filament

Abstract Efforts are made to elucidate a comprehensive analysis of entrainment dynamics triggered by a couple of unequal rotational fluxes within a viscous pool. Cylindrical rollers are employed to establish the rotational field. The top drum is equally submerged in both phases and also it provides a constant rotational inertia. Concomitantly, the bottom roller is completely submerged in the viscous bath, and it provides an unequal rotational strength in reference to top roller. The average rotational strength of both rollers is measured using average Capillary number (Ca)avg. The entrainment phenomenon is strongly influenced by both Caavg and gap between the rollers (W/D). Characterization of entrained filament is elucidated by predicting the horizontal distance (L*), radial distance (r*), temporal vertical displacement (Y*), maximum vertical displacement (Ymax*), width (H*), and location of V-shaped diversion (∅s*). Characterization of liquid tip is performed by measuring the travel rate (Y*) along periphery of drum from receding to advancing junction. Air mass ejection from filament tip is analysed by estimating the 1st bubble ejection time (t1st*), volume of accumulated of ejected gaseous masses (v*), and ejection frequency (f). Furthermore, the effect of gravitational pull (specified by Archimedes number, Ar) and viscous drag (measured by Morton number, Mo) on the pattern of entrained air filament is described. Lastly, an analytical framework is established to determine the width of the V-junction by balancing the important influencing forces, which are strongly affecting the filament. Analytical observations show a satisfactory agreement with numerical findings.

Comprehensive Analysis of Land Use and Cover Dynamics in Djibouti Using Machine Learning Technique: A Multi-Temporal Assessment from 1990 to 2023

Understanding land use and land cover (LULC) dynamics in semi-arid regions is vital for unraveling complex environmental processes and resource management. This study delves into the intricate interplay of land patterns and resource dynamics, offering indispensable insights into the environmental repercussions of these changes. The study aims to quantify land use categories in Djibouti's semi-desert region using remote sensing. It analyzes temporal changes and evaluates Random Forest (RF) algorithms for land use classification. Through meticulous quantification and comprehensive temporal analysis, the research contributes significantly to remote sensing and environmental science by enhancing understanding of land use dynamics and informing sustainable land management practices. Leveraging machine learning supervised classification on the Google Earth Engine (GEE) platform using Landsat data spanning four time periods (1990, 2002, 2012, and 2023), alongside spectral indices and Digital Elevation Model (DEM) data, our study achieves unprecedented insights. Our findings reveal a significant landscape transformation, delineating seven major land cover classes: mangroves, bushes, farmland, built-up areas, water bodies, barren land, and salt plains. With overall accuracy ranging from 89% to 95%, our assessments demonstrate significant changes in land use types over the studied period. Notably, mangroves, bushes, farmland, and salt areas witnessed declines, while built-up areas, water bodies, and barren lands expanded. This research underscores the pivotal role of remote sensing in monitoring long-term land use changes and their ecological impacts. By harnessing technological advancements, our study empowers stakeholders to make informed decisions for sustainable resource management and environmental conservation in semi-arid landscapes.

Empowering urban energy transition through data-driven decision-making: A statistical examination of technological innovations in transportation and mobility

Urban energy consumption is a critical aspect of sustainable urban development, with technological innovations playing a pivotal role in shaping energy usage patterns. This paper presents a comprehensive analysis of urban energy consumption dynamics in relation to the adoption of technology across various sectors, including transportation, residential, industrial, and commercial domains. Through extensive data collection and advanced statistical analyses, we investigate the correlation between technology adoption rates and energy consumption behaviors in urban areas. Our findings reveal a strong positive correlation between technology adoption rates and reduced energy consumption across sectors. We employ spatial analyses to identify localized successes, shedding light on regions where technology-driven initiatives have significantly lowered energy demands. These insights offer valuable guidance for urban planners and policymakers aiming to implement targeted interventions and replicate effective strategies. Furthermore, the paper emphasizes the transformative potential of innovative solutions, ranging from smart infrastructure to industrial automation, in promoting energy efficiency and environmental sustainability. By fostering the integration of such technologies, cities can mitigate their carbon footprint, enhance energy resilience, and create more livable environments for residents. This research contributes to the discourse on urban energy transitions and provides actionable insights for urban policymakers and stakeholders striving for a greener, more sustainable urban future.

Employment Dynamics and Unemployment Challenges in India

This study conducts a comprehensive analysis of employment dynamics and unemployment challenges in India, drawing from extensive data spanning sectors and demographics. It elucidates significant shifts in employment patterns, notably the transition from agriculture to manufacturing sectors, and highlights demographic disparities in employment rates, particularly among different age cohorts. Furthermore, it delves into the intricate factors contributing to unemployment, including educational deficiencies, economic slowdowns, and labour market mismatches. Assessing the effectiveness of government interventions such as MGNREGA and Skill India reveals their notable impact on mitigating unemployment rates. The study also uncovers regional disparities in employment opportunities, emphasizing variations across geographical regions and socio-economic groups. Additionally, it sheds light on skill mismatches between labour market demand and available skills, pinpointing areas for improvement. Synthesizing these findings, the study offers evidence-based policy recommendations aimed at fostering inclusive growth and addressing the multifaceted challenges of unemployment in India.

Marburg Virus and Risk Factor Among Infected Population: A Modeling Study

This study aims to investigate the role of individuals with natural immunity in contributing to the overall spread of Marburg virus infection, a highly lethal human pathogen. Marburg virus was initially identified in 1967 during a significant outbreak in Marburg, Germany, and Belgrade, Serbia. Notably, there are currently no approved vaccines or treatments for Marburg virus infection due to its alarmingly high fatality rate. The study developed a mathematical model to better understand the transmission dynamics of Marburg virus disease (MVD), specifically focusing on the spread of infected individuals. Initial analysis employed established methods, evaluating factors such as the positive assessments, the basic reproduction number, and equilibrium point stability. This analytical approach provided valuable insights into MVD dynamics. Following this, numerical simulations were conducted to visually depict the outcomes derived from the analytical analysis. These simulations provided a more comprehensive understanding of the complex dynamics of MVD. Finally, this study presents a comprehensive analysis of Marburg virus transmission dynamics, shedding light on the impact of natural immunity on disease spread and emphasizing the significance of isolation strategies in mitigating the outbreak of this highly lethal pathogen.

Conformational analysis of lipid membrane mimetics modified with Aβ42 peptide by Raman spectroscopy and computer simulations

Peptide-lipid interactions play an important role in maintaining the integrity and function of the cell membrane. Even slight changes in these interactions can induce the development of various diseases. Specifically, peptide misfolding and aggregation in the membrane is considered to be one of the triggers of Alzheimer’s disease (AD), however its exact mechanism is still unclear. To this end, an increase of amyloid-beta (Aβ) peptide concentration in the human brain is widely accepted to gradually produce cytotoxic Aβ aggregates (plaques). These plaques initiate a sequence of pathogenic events ending up in observable symptoms of dementia. Understanding the mechanism of the Aβ interaction with cells is crucial for early detection and prevention of Alzheimer’s disease. Hence, in this work, a comprehensive Raman analysis of the Aβ42 conformational dynamics in water and in liposomes and lipodiscs that mimic the membrane system is presented. The obtained results show that the secondary structure of Aβ42 in liposomes is dominated by the α–helix conformation, which remains stable over time. However, it comes as a surprise to reveal that the lipodisc environment induces the transformation of the Aβ42 secondary structure to a β-turn/random coil. Our Raman spectroscopy findings are supported with molecular dynamics (MD) and density functional theory (DFT) simulations, showing their good agreement. Communicated by Ramaswamy H. Sarma

Does lean inventory management alleviate financing constraints?

PurposeThis study explores the intricate relationship between inventory leanness, financial constraints and digital transformation in listed Chinese manufacturing firms.Design/methodology/approachUsing a large panel data collected from 2,563 Chinese listed manufacturing enterprises over the period from 2012 to 2021, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the U- shaped relationship between inventory leanness and financial constraints. Furthermore, the moderating role of digital transformation is demonstrated.FindingsContrary to traditional assumptions, our research uncovers a U-shaped relationship between inventory leanness and financial constraints, indicating that excessive inventory reduction can exacerbate financial constraints. Digital transformation plays a significant moderating role, particularly in highly digitalized environments.Practical implicationsOur findings have practical significance for top managers and policymakers. We advocate for a balanced approach to lean inventory management to mitigating financial constraints. The study emphasizes the pivotal role of digital transformation in alleviating the impact of inventory leanness on financial constraints, highlighting the need for digital transformation strategies.Originality/valueThis research provides a comprehensive analysis of inventory leanness, financial constraints and digital transformation dynamics. It challenges conventional thinking by revealing the nonlinear nature of the inventory leanness–financial constraints relationship. The concept of moderation highlights the moderating effect of digital transformation. This study offers practical guidance for practitioners and policymakers.

Electroosmotic microchannel flow of blood conveying copper and cupric nanoparticles: Ciliary motion experiencing entropy generation using backpropagated networks

AbstractA novel mathematical model for a hybrid (Cu–CuO/blood) Jeffrey nanofluid passing a vertical symmetric microchannel along with an electroosmosis pump is presented. The focuses on the advancement of mathematical modeling techniques, its comprehensive analysis of microfluidic system dynamics, and its potential to inform the optimal design of devices using nanofluids with broad applications in various fields. Arrhenius's law is used to analyze endothermic–exothermic reactions and activation energy. The governing partial differential equations of the fixed frame are transformed into ordinary differential equations of the wave frame using self‐similarity transformations. Low Reynolds number and long‐wavelength approximations helped to find solutions of the equations by applying a suitable BVP solver in MATLAB. The fluid's velocity, temperature, concentration, and electroosmosis properties are studied graphically. Two‐dimensional contour plots of fluid velocity and three‐dimensional surface plots of fluid properties are discussed. Physically significant quantities of mass transfer rate, skin friction coefficient, entropy generation, and heat transfer rate are studied using contour plots. Artificial neural network simulation using Bayesian regularization backpropagation algorithms is analyzed for training state, error histogram, fit, performance, and regression plots. Conclusively, the comprehensive analysis of the fluid dynamics, entropy generation, mass and heat transfer, and in the microchannel, coupled with the successful implementation of artificial neural network simulation, contributes to an improved understanding of the system's behavior. Entropy generation was raised for enhanced Brownian motion number and reduced values of thermophoresis, activation energy, and endothermic–exothermic reaction parameters. This study's results can be used to improve the efficiency and effectiveness of microfluidic devices used in fields as diverse as electrical cooling and medicine delivery.

A review of large wood dynamics relevant to hazard characteristics for built structures

Large wood exerts an influence on the topography and geomorphology of channels in areas of good vegetation development, and it is also an important component of riverine ecosystems. However, large wood may impact and damage buildings. The formation and failure of logjams can cause backwater rise, local scour, and the amplification of flow discharge, leading to more serious disasters. Therefore, quantifying the processes of large wood recruitment, entrainment, transport, deposition, accumulation and logjams failure is highly significant for the prevention of large wood hazards in channels. Based on existing research on large wood, this review provides a comprehensive analysis of large wood dynamics and hazards. First, the processes involved in large wood recruitment, entrainment, transport, and deposition are reviewed. Second, the results of large wood accumulation probability and the backwater rise, local scour, critical conditions of logjams failure and magnitude amplification of the flow discharge caused by large wood are analyzed comprehensively. Finally, large wood-related hazard mitigation measures are also introduced. Future research directions to improve the mitigation of hazards from large wood should concentrate on exploring quantification models for understanding how large wood impacts and accumulates on various built structures.

Cellular Dynamics of Fas-Associated Death Domain in the Regulation of Cancer and Inflammation.

Fas-associated death domain (FADD) is an adaptor protein that predominantly transduces the apoptosis signal from the death receptor (DR) to activate caspases, leading to the initiation of apoptotic signaling and the coordinated removal of damaged, infected, or unwanted cells. In addition to its apoptotic functions, FADD is involved in signaling pathways related to autophagy, cell proliferation, necroptosis, and cellular senescence, indicating its versatile role in cell survival and proliferation. The subcellular localization and intracellular expression of FADD play a crucial role in determining its functional outcomes, thereby highlighting the importance of spatiotemporal mechanisms and regulation. Furthermore, FADD has emerged as a key regulator of inflammatory signaling, contributing to immune responses and cellular homeostasis. This review provides a comprehensive summary and analysis of the cellular dynamics of FADD in regulating programmed cell death and inflammation through distinct molecular mechanisms associated with various signaling pathways.

Quantifying Impact, Uncovering Trends: A Comprehensive Bibliometric Analysis of Shadow Banking and Financial Contagion Dynamics

This study describes a comprehensive bibliometric analysis of shadow banking and financial contagion dynamics from 1996 to 2022. Through a holistic approach, our study focuses on quantifying the impact and uncovering significant trends in scientific research related to these interconnected fields. Using advanced bibliometric methods, we explored the global network of publications, identifying key works, influential authors, and the evolution of research over time. The results of the bibliometric analysis have highlighted an annual growth rate of 22.05% in publications related to the topics of shadow banking and financial contagion, illustrating researchers’ interest and the dynamic nature of publications over time. Additionally, significant increases in scientific production have been recorded in recent years, reaching a total of 178 articles published in 2022. The most predominant keywords used in research include “systemic risks”, “risk assessment”, and “measuring systemic risk”. The thematic evolution has revealed that over time, the focus on fundamental concepts used in analyzing these two topics has shifted, considering technological advancements and disruptive events that have impacted the economic and financial system. Our findings provide a detailed insight into the progress, gaps, and future directions in understanding the complex interplay of shadow banking and financial contagion. Our study represents a valuable asset for researchers, practitioners, and policymakers with a keen interest in understanding the dynamics of these critical components within the global financial system.