Evolution Of System Research Articles

Tracking earmarked funding to international organizations: Introducing the earmarked funding dataset

AbstractOver the past two decades, donor funding of international organizations (IOs) such as the United Nations, has shifted from core resources toward earmarked contributions. While core resources provide IOs with discretion how to achieve their mandates, earmarked contributions require IOs to focus their assistance on specific themes, sectors, countries, or projects, as determined by the donors. Our understanding of the drivers and effects of earmarked funding has been limited by the lack of systematic data. To address this gap, we introduce the Earmarked Funding Dataset. The dataset contains 342,812 earmarked aid activities from nearly 50 donors with over 340 IOs with a mandate in international development from 1990 to 2020. We first explore the data descriptively to cast light on the evolution of the multilateral development system. We then use the data to examine whether and how donors financially reward well-performing IOs. To that end, we combine our data with newly available performance data synthesized from Multilateral Organization Performance Assessment Network (MOPAN) evaluations of 32 IOs in 2009–2020. Using difference-in-difference estimations, we find a significantly positive relationship between outcome performance and earmarked contributions. In contrast, performance does not seem to affect core resources. These patterns suggest that donors reward well-performing multilaterals with more funding, albeit based on development outcomes which are not easily contractible. From a policy perspective, these findings suggest that performance-based approaches to aid allocation—as they are currently practiced—upload the financial risks of organizational reform processes to international organizations.

ADVANCING POS SYSTEMS FOR SEAMLESS RETAIL EXPERIENCES

This research paper explores the significance of advancing point of sale (POS) technologies in modern commerce, with a focus on their role in improving business operations and enhancing customer experiences. POS systems serve as critical tools for businesses across various industries, facilitating transactions, managing sales processes, and providing valuable insights into business performance. The paper delves into the evolution of POS systems, from traditional cash registers to sophisticated digital solutions, and examines the current state of POS technology, including hardware and software components. Moreover, it discusses recent trends and advancements in POS innovation, such as the integration of emerging technologies like artificial intelligence (AI) and Internet of Things (IoT), and their implications for businesses. Through empirical research, case studies, and expert analysis, the paper aims to provide insights into the benefits and challenges of adopting advanced POS technologies, as well as recommendations for businesses seeking to leverage these technologies to drive growth and improve operational efficiency in today's dynamic market place. Keywords- Point of Sale (POS) Systems, Advancing Technologies, Retail, Business Operations, Customer Experience, Emerging Technologies, Artificial Intelligence (AI), Internet of Things (IoT), Payment Processing, Inventory Management, Cloud-based POS, Customer Engagement, Digital Commerce, Innovation, Competitive Advantage.

On the aeroelastic bifurcation of a flexible panel subjected to cavity pressure and inviscid oblique shock

The aeroelasticity of a panel in the presence of a shock is a fundamental issue of great significance in the development of hypersonic vehicles. In practical engineering, cavity pressure emerges as a crucial factor that influences the nonlinear dynamical characteristics of the panel. This study focuses on the aeroelastic bifurcation of a flexible panel subjected to both cavity pressure and oblique shock. To this end, a computational method is devised, coupling a high-fidelity reduced-order model for unsteady aerodynamic loads with nonlinear structural equations. The solution is meticulously tracked by continuous calculations. The obtained results indicate that cavity pressure plays a pivotal role in determining the bifurcation and stability characteristics of the system. First, the system exhibits hysteresis behaviour in response to the ascending and descending dynamic pressures. The evolution of hysteresis behaviour originates from the phenomenon of cusp catastrophe. Second, variations in cavity pressure induce three types of bifurcation phenomena, exhibiting characteristics akin to supercritical Hopf bifurcation, subcritical Hopf bifurcation and saddle-node bifurcation of cycles. The system's response at the critical points of these bifurcations manifests as long-period asymptotic flutter or explosive flutter. Lastly, the evolution of the dynamical system among these three types of bifurcations is an important factor contributing to the discrepancies observed in certain research results. This study enhances the understanding of the nonlinear dynamical behaviour of panel aeroelasticity in complex practical environments and provides new explanations for the discrepancies observed in certain research results.

Wireless Patient Health Monitoring System

Wireless Patient Health Monitoring Systems (WPHMS) have emerged as transformative solutions in modern healthcare, facilitating continuous and remote monitoring of patients' vital signs in real-time. This paper presents a comprehensive exploration of a Wireless Patient Health Monitoring System leveraging the Blynk app, a versatile IoT platform. The system is designed to enable seamless data collection, transmission, and visualization of critical health parameters such as pulse rate, temperature, and blood pressure. By integrating cutting-edge hardware components with intuitive software interfaces, the proposed system offers unprecedented flexibility and accessibility in patient monitoring, transcending the limitations of traditional wired monitoring systems. The research begins with a thorough review of existing literature on wireless healthcare technologies, highlighting the evolution of patient monitoring systems and the role of IoT platforms in revolutionizing healthcare delivery. Building upon this foundation, the paper proceeds to outline the hardware architecture of the WPHMS, detailing the selection and integration of microcontroller boards, sensor modules.

Beyond retribution: Individual reparations for IHL violations as peace facilitators

Abstract Three decades after the United Nations Security Council invoked its Chapter VII powers to create the ad hoc criminal tribunals, there can be little doubt that the prosecution of individuals responsible for serious violations of international humanitarian law (IHL) contributes to restoring and maintaining peace. While there is little doubt that the reparatory function of justice is just as crucial as retribution, under international law today, reparations for IHL violations remain harrowingly insufficient or borderline non-existent. In scholarship and strategic litigation, various attempts have been made to distil an individual right to reparations from black-letter IHL. This article argues that such approaches are doomed to fail, as procedural aspects of international obligations rarely, if ever, emerge through the evolution of an existing customary international obligation, let alone via the crystallization of a new customary international norm. They are usually triggered by a political shift that makes States adopt novel regulations setting forth the jurisdictional ramifications of enforcing a pre-existing right or obligation. This article thus advances a two-fold argument. First, it asserts that States’ increased compliance with the obligation to provide compensation for violations of IHL attributable to them would contribute to “the restoration and maintenance of peace” just as much as the prosecution of persons responsible for serious violations thereof. Second, it argues that the individual right to claim reparations for IHL violations can only be established through a political decision of States, and that the establishment of an international mechanism for Ukraine might be an important precedent for the evolution of the current international system.

Exploring the physical characteristics and nonlinear wave dynamics of a (3+1)-dimensional integrable evolution system

This study comprehensively explores the [Formula: see text]-dimensional Mikhailov–Novikov–Wang [Formula: see text] integrable equation, with the primary objective of elucidating its physical manifestations and establishing connections with analogous nonlinear evolution equations. The investigated model holds significant physical meaning across various disciplines within mathematical physics. Primarily, it serves as a fundamental model for understanding nonlinear wave propagation phenomena, offering insights into wave behaviors in complex media. Moreover, its relevance extends to nonlinear optics, where it governs the dynamics of optical pulses and solitons crucial for optical communication and signal processing technologies. Employing analytical methodologies, namely the unified [Formula: see text], Khater II ([Formula: see text]hat.II) method, and He’s variational iteration [Formula: see text] method, both numerical and analytical solutions are meticulously examined. Through this investigation, the intricate behaviors of the equation are systematically unveiled, shedding illuminating insights on various physical phenomena, notably including wave propagation in complex media and nonlinear optics. The outcomes not only underscore the efficacy of the analytical techniques deployed but also accentuate the equation’s pivotal role in modeling a broad spectrum of nonlinear wave dynamics. Consequently, this research significantly advances our comprehension of complex physical systems governed by nonlinear dynamics, thereby contributing notably to interdisciplinary pursuits in mathematical physics.

Nonlinear stability evolution of railway wagon system due to wheel profile wear

Nonlinear stability evolution of railway wagon system due to wheel profile wear

Stochastic evolution equations with Wick-analytic nonlinearities

We study nonlinear stochastic partial differential equations with Wick-analytic type nonlinearities set in the framework of white noise analysis. These equations include the stochastic Fisher–KPP equations, stochastic Allen–Cahn, stochastic Newell–Whitehead–Segel, and stochastic Fujita–Gelfand equations. By implementing the theory of C 0 − semigroups and evolution systems into the chaos expansion theory in infinite dimensional spaces, we prove the existence and uniqueness of solutions for this class of stochastic partial differential equations.

Local Self-Assembly of Dissipative Structures Sustained by Substrate Diffusion.

The coupling between energy-consuming molecular processes and the macroscopic dimension plays an important role in nature and in the development of active matter. Here, we study the temporal evolution of a macroscopic system upon the local activation of a dissipative self-assembly process. Injection of surfactant molecules in a substrate-containing hydrogel results in the local substrate-templated formation of assemblies, which are catalysts for the conversion of substrate into waste. We show that the system develops into a macroscopic (pseudo-)non-equilibrium steady state (NESS) characterized by the local presence of energy-dissipating assemblies and persistent substrate and waste concentration gradients. For elevated substrate concentrations, this state can be maintained for more than 4 days. The studies reveal an interdependence between the dissipative assemblies and the concentration gradients: catalytic activity by the assemblies results in sustained concentration gradients and, vice versa, continuous diffusion of substrate to the assemblies stabilizes their size. The possibility to activate dissipative processes with spatial control and create long lasting non-equilibrium steady states enables dissipative structures to be studied in the space-time domain, which is of relevance for understanding biological systems and for the development of active matter.

Local Self‐Assembly of Dissipative Structures Sustained by Substrate Diffusion

The coupling between energy‐consuming molecular processes and the macroscopic dimension plays an important role in nature and in the development of active matter. Here, we study the temporal evolution of a macroscopic system upon the local activation of a dissipative self‐assembly process. Injection of surfactant molecules in a substrate‐containing hydrogel results in the local substrate‐templated formation of assemblies, which are catalysts for the conversion of substrate into waste. We show that the system develops into a macroscopic (pseudo‐)non‐equilibrium steady state (NESS) characterized by the local presence of energy‐dissipating assemblies and persistent substrate and waste concentration gradients. For elevated substrate concentrations, this state can be maintained for more than 4 days. The studies reveal an interdependence between the dissipative assemblies and the concentration gradients: catalytic activity by the assemblies results in sustained concentration gradients and, vice versa, continuous diffusion of substrate to the assemblies stabilizes their size. The possibility to activate dissipative processes with spatial control and create long lasting non‐equilibrium steady states enables dissipative structures to be studied in the space‐time domain, which is of relevance for understanding biological systems and for the development of active matter.

The Impact of the Industrial Internet on the Innovation and Development Level of China’s Manufacturing Industry: Under the Perspective of Government Incentives

In the era of the digital economy, it has become an inevitable trend for manufacturing enterprises to establish industrial Internet platforms toward achieving transformation and innovative development. However, the current development model of industrial Internet platforms is still imperfect, wherein the application scenario is complex, the investment cost is too high, the return-on-investment cycle is too long, and other factors have hindered the willingness of manufacturing enterprises to employ cloud services and capital investment. For this reason, governments have introduced a series of relevant incentive policies to promote the development of industrial Internet platforms and the transformation and upgrading of manufacturing enterprises. Considering the role of government incentives, this study first constructs an evolutionary game model with local governments, manufacturing enterprises, and industrial Internet platforms as the main players. Then, the dynamic change process of each game player’s strategy choice and the stable state of the system evolution under multiple scenarios are analyzed, and the validity of the conclusions is verified through a numerical simulation analysis. Finally, the statistical data of 28 provinces in China from 2018 to 2020 are used to conduct an empirical test to explore the impact of the industrial Internet on the transformation and innovation development of the manufacturing industry and the role of government incentives. The results show that the development of the industrial Internet has a significant role in promoting the innovation and development of the manufacturing industry; government incentives can promote the innovation and development of the industrial Internet and manufacturing industry, but incentives should not be too generous; and the impact of developing the industrial Internet on the level of innovation input/output of the manufacturing industry shows obvious regional differences. This study takes the local government as an independent game participant into consideration, which enriches the research field of combining evolutionary game theory with the transformation and innovative development of the manufacturing industry. In addition, this study provides theoretical guidance and practical references for the government to formulate incentive policies to promote the development of industrial Internet platforms and for manufacturing enterprises to utilize these platforms to carry out innovation and perform upgrades.

Hydration, strength, and microstructure evolution of Portland cement-calcium sulphoaluminate cement-CSH seeds ultra-early strength cementitious system

Improving the very early age strength of precast concrete components at ambient temperature and ensuring the development of later strength is of significant engineering importance. This objective was successfully achieved by incorporating a specific percentage of 0–3% CSH seeds (CSHs) and 5%-20% calcium sulphoaluminate cement (CSA) into Portland cement (PC). The hydration, strength and microstructure evolution of Portland cement-calcium sulphoaluminate cement-CSH seeds cementitious system were investigated. Hydration heat tests reveal that CSHs effectively accelerated the early hydration of the slurry within the first 12 h without affecting its later hydration. CSHs and CSA acted synergistically to enhance hydration kinetics. However, it is crucial to control the proportion of CSA within the range of 5%-10%; exceeding this ratio can severely inhibit the hydration of silicates. Strength tests indicate that the addition of CSHs and CSA can increase the compressive and flexural strengths of mortar within the first 12 h by 282% and 208%, respectively, without impacting the development of its later-age strength. Together, they synergistically provide favorable support for the strength and toughness of matrix. Based on linear regression analysis and nitrogen adsorption and desorption tests, it was concluded that CSHs enhance the hydration dependence of matrix strength, while CSA diminishes this characteristic. This is because CSHs refine the pore size distribution of the paste, increasing the proportion of micropores, whereas CSA promotes the formation of more mesopores and macropores, leading to coarser pores; however, 5% CSA is beneficial for further refining the pore structure. The microcosmic phase evolution of the early-strength cementitious system was analyzed through X-ray diffraction and scanning electron microscope-energy dispersive spectrometer experiments. Results demonstrate that low proportions of CSA and CSHs promote the co-growth of ettringite and C-S-H gel, ensuring a more rapid formation of a dense hydration network in the early stages, thereby accelerating strength development. These findings provide a reference for the design and preparation of precast concrete.

Evolutionary game and system dynamics for analysis on stakeholder strategies of regional high-speed rail project in investment decision stage

This paper studies the strategic choices under the conflict among stakeholders of regional high-speed rail project at the investment decision stage in the context of the ‘high-speed rail controversy’. This study develops a tripartite evolutionary game model among the central government, the local government and China Railway, analyzes the evolutionary stability strategy, discusses the influence of multiple factors on the choice of tripartite strategy, and further calculates and analyzes the stability of the equilibrium point in the tripartite evolutionary game system. Then the dynamic change trend of strategy choice brought by the change of each factor is investigated through system dynamics simulation. The results show that the lower the intervention cost and reward to the other two parties, and the increase of the opportunity cost of non-intervention and punishment to the other two parties, the faster the convergence of the central government's choice of intervention strategy. The increase of the rewards and punishments, and the increase of negotiation profits, non-negotiation costs, and loss of reputation for non-negotiation, and the decrease in the negotiation costs and non-negotiation profits all contribute to the shortening of the convergence time of the local government's choice of negotiation strategy. The increase of the rewards and punishments, the increase of support profits, the loss of reputation for non-support, and the decrease of the profits for non-support and the extra cost for support will promote the convergence of China Railway's choice of the support strategy. Finally, the simulation results are discussed so as to target feasible coordination strategies, which provides a theory basis for the practice of conflict coordination among stakeholders of regional high-speed rail project at the investment decision stage.

Discussion on optimal feedback control for stochastic fractional differential system by hemivariational inequalities

This study focuses on optimal feedback control for stochastic Caputo fractional evolution systems in separable Hilbert spaces. Initially, we deal with the existence of a mild solution, establishing it through the application of the generalised Clarke's subdifferential and a fixed point theorem for multivalued maps. Then, we utilise the Cesari property and the Filippov theorem to demonstrate the existence of feasible pairs. Additionally, we provide pairs of suitable feedback controls under specific conditions. Finally, we present a simple illustration to support our theoretical findings.

Approximate controllability of non-autonomous evolution system with infinite delay

This article deals with the existence and approximate controllability results for a class of nonautonomous second-order evolution systems with infinite delay. To establish sufficient conditions for the proposed control problem the theory of evolution operator with Schauder’s fixed point theorem is used. Further, we extend the approximate controllability results to the integro-impulsive differential system. Finally, to emphasize our theoretical concepts, an example is provided.

Risk Assessment of Radial Distribution Systems using Modified Jelly Fish Search Algorithm to analyse the Performance Indices

One of the essential techniques for figuring out Power Distribution System performance is reliability evaluation. With time, the range of methods for assessing reliability has grown, and the distribution system's evolution has also become more intricate. The likelihood of a network failing grows with time once it begins to function, especially if it is used for an extended period. Reliability indices have been evaluated using different algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and various modified versions of algorithms. The Jelly Fish Search Algorithm has been used in various power system applications such as to determine the most cost-effective way to dispatch generating units' loads, integrate Distributed Generation (DG) units, track the maximum power of photovoltaic systems, and determine optimal power flow solutions, among other uses. The performance indices for the Radial Distribution System (RDS) have not been evaluated using JFSA.Variation of performance indices with respect to unavailability has not been discussed in the literature. Here an attempt is made to analyse the variation of the indices with the unavailability. The proposed algorithm is evaluated first on 3 load point radial distribution system and the computations are performed on the popular IEEE-RBTS Bus2 test system. Based on the output it is observed that for the both the systems the behaviour of the indices with respect to the unavailability is in similar fashion. The equations are derived for the performance indices using the Minitab. With the equations obtained the Performance indices values can be predicted for the given unavailability value. It is the better appropriate method for the assessing the performance indices of Radia Distribution System.

Advancements in Deep Learning for Minimally Invasive Surgery: A Journey through Surgical System Evolution

The surge in artificial intelligence (AI) applications across diverse fields owes much to advancements in deep learning and computational processing speed. In medicine, AI's reach extends to medical image analysis and genomic data interpretation. More recently, AI's role in analyzing minimally invasive surgery (MIS) videos has gained traction, with a growing body of research focusing on organ and anatomy identification, instrument recognition, procedure recognition, surgical phase delineation, surgery duration prediction, optimal incision line identification, and surgical education. Concurrently, the development of autonomous surgical robots, exemplified by the Smart Tissue Autonomous Robot (STAR) and RAVEN systems, has shown promising strides. Notably, STAR is currently employed in laparoscopic imaging to discern the surgical site from laparoscopic images and is undergoing trials for an automated suturing system, albeit in animal models. This review contemplates the prospect of fully autonomous surgical robots in the future.

Advancements in Deep Learning for Minimally Invasive Surgery: A Journey through Surgical System Evolution

The surge in artificial intelligence (AI) applications across diverse fields owes much to advancements in deep learning and computational processing speed. In medicine, AI's reach extends to medical image analysis and genomic data interpretation. More recently, AI's role in analyzing minimally invasive surgery (MIS) videos has gained traction, with a growing body of research focusing on organ and anatomy identification, instrument recognition, procedure recognition, surgical phase delineation, surgery duration prediction, optimal incision line identification, and surgical education. Concurrently, the development of autonomous surgical robots, exemplified by the Smart Tissue Autonomous Robot (STAR) and RAVEN systems, has shown promising strides. Notably, STAR is currently employed in laparoscopic imaging to discern the surgical site from laparoscopic images and is undergoing trials for an automated suturing system, albeit in animal models. This review contemplates the prospect of fully autonomous surgical robots in the future.

PacBio Hi-Fi genome assembly of Sipha maydis, a model for the study of multipartite mutualism in insects

Dependence on multiple nutritional endosymbionts has evolved repeatedly in insects feeding on unbalanced diets. However, reference genomes for species hosting multi-symbiotic nutritional systems are lacking, even though they are essential for deciphering the processes governing cooperative life between insects and anatomically integrated symbionts. The cereal aphid Sipha maydis is a promising model for addressing these issues, as it has evolved a nutritional dependence on two bacterial endosymbionts that complement each other. In this study, we used PacBio High fidelity (HiFi) long-read sequencing to generate a highly contiguous genome assembly of S. maydis with a length of 410 Mb, 3,570 contigs with a contig N50 length of 187 kb, and BUSCO completeness of 95.5%. We identified 117 Mb of repetitive sequences, accounting for 29% of the genome assembly, and predicted 24,453 protein-coding genes, of which 2,541 were predicted enzymes included in an integrated metabolic network with the two aphid-associated endosymbionts. These resources provide valuable genetic and metabolic information for understanding the evolution and functioning of multi-symbiotic systems in insects.

Impact of memory on beamforming optimization for DDPG-assisted RIS-multi-user system

Recently, reconfigurable intelligent surfaces (RIS) have garnered considerable attention as indispensable components driving the evolution of future 6G wireless communication systems. This heightened interest is primarily attributed to notable advancements in programmable meta-material fabrication, which enable the creation of highly versatile and adaptable surfaces. These surfaces, often referred to as intelligent reflecting arrays, represent a significant departure from the conventional capabilities of massive multiple-input multiple-output (MIMO) systems, thereby catalyzing the emergence of intelligent radio environments characterized by enhanced flexibility and efficiency. Our study is dedicated to the comprehensive exploration of coordinated design strategies that encompass both the transmission beamforming matrix at the base station and the phase shift matrix at the RIS. Leveraging recent breakthroughs in deep reinforcement learning (DRL), our approach harnesses the power of a Long Short-Term Memory (LSTM) based DRL algorithm. This algorithm orchestrates the joint design process through iterative interactions with the environment, strategically guided by predefined rewards operating within a continuous framework of states and actions. While recent research has underscored the efficacy of LSTM-based architectures in bolstering the learning capacity of reinforcement learning (RL) algorithms and simplifying the search process, our investigation reveals a nuanced insight. Contrary to prevailing trends, we find that the integration of memory into the Deep Deterministic Policy Gradient (DDPG) with LSTM (DDPG-LSTM) algorithm yields unexpected consequences, negatively impacting the system's overall performance. Through preliminary simulation results, we empirically demonstrate the adverse effect of memory on DDPG performance when applied to RIS systems. This finding not only sheds light on the complexities of optimizing 6G wireless communication systems but also underscores the importance of careful algorithmic design and parameter tuning in achieving desired outcomes in emerging technologies.