System Model Research Articles

Myosin-Catalyzed ATP Hydrolysis in the Presence of Disease-Causing Mutations: Mavacamten as a Way to Repair Mechanism.

Hypertrophic cardiomyopathy is one of the most common forms of genetic cardiomyopathy. Mavacamten is a first-in-class myosin modulator that was identified via activity screening on the wild type, and it is FDA-approved for the treatment of obstructive hypertrophic cardiomyopathy (HCM). The drug selectively binds to the cardiac β-myosin, inhibiting myosin function to decrease cardiac contractility. Though the drug is thought to affect multiple steps of the myosin cross-bridge cycle, its detailed mechanism of action is still under investigation. Individual steps in the overall cross-bridge cycle must be queried to elucidate the full mechanism of action. In this study, we utilize the rare-event method of transition path sampling to generate reactive trajectories to gain insights into the action of the drug on the dynamics and rate of the ATP hydrolysis step for human cardiac β-myosin. We study three known HCM causative myosin mutations: R453C, P710R, and R712L to observe the effect of the drug on the alterations caused by these mutations in the chemical step. Since the crystal structure of the drug-bound myosin was not available at the time of this work, we created a model of the drug-bound system utilizing a molecular docking approach. We find a significant effect of the drug in one case, where the actual mechanism of the reaction is altered from the wild type by mutation. The drug restores both the rate of hydrolysis to the wildtype level and the mechanism of the reaction. This is a way to check the effect of the drug on untested mutations.

Institutions and financial development: Comparative analysis of developed and developing economies

PurposeThis article aims to investigate how institutional characteristics affect the level of financial development of economies collectively and compare between developed and undeveloped economies.Design/methodology/approachA dynamic panel with 131 countries, including developed and developing ones, was utilized; the estimators of the generalized method of moments system (GMM system) model were selected because they have econometric characteristics more suitable for analysis, providing superior statistical precision compared to traditional linear estimation methods.FindingsThe results from the full panel suggest that concrete and well-defined institutions are important for financial development, confirming previous research, with a more limited scope than the present work.Research limitations/implicationsLimitations of this research include the availability of data for all countries worldwide, which would make the research broader and more complete.Originality/valueA panel of countries was used, divided into developed and developing countries, to analyze the impact of institutional variables on the financial development of these countries, which is one of the differentiators of this work. Another differentiator of this research is the presentation of estimates in six different configurations, with emphasis on the GMM system model in one and two steps, allowing for comparison between results.

Analysis of Uncertainties and Associated Convective Processes in Simulations of Extreme Precipitation Over Cities With a Regional Earth System Model: A Case Study

Analysis of Uncertainties and Associated Convective Processes in Simulations of Extreme Precipitation Over Cities With a Regional Earth System Model: A Case Study

Rainfall-runoff modelling – a comparison of Artificial Neural Networks (ANNs) and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS)

ABSTRACT This article presents comparison of Artificial Neural Networks (ANNs) and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) model for rainfall-runoff (R-R) process. Aim of the present work is to forecast runoff one day ahead at Shivade station of Upper Krishna Basin, India, using 17 years of daily rainfall and discharge data. The R-R modelling can be exercised using various traditional methods which generally require exogenous data in the form of basin parameters. Unavailability of such data becomes major impediment in applying these models at many basins. In such situations, soft computing techniques like ANNs have been extensively applied to model R-R process. Though ANN is now an established tool in hydrology, compared to HEC-HMS, its results are viewed with suspicion owing to its data-driven nature rather than a model-driven nature. In this study, ANN model performed reasonably well, with a higher correlation coefficient (0.87) and the lowest Root Mean Square Error (136.28 m3/s) when compared with HEC-HMS (0.76, 139.8 m3/s) respectively. Novelty of the present work lies in model development using restricted basin data. Both models showed less accuracy in predicting extreme events. Finally, it is concluded that ANN model can be used as a supplementary technique along with HEC-HMS for this phenomenon.

Identification of the existing Integrated Farming Systems in Udaipur District of Rajasthan

The integrated farming system (IFS) is an integrative whole-farm-oriented technique mainly used to resolve the problems of small and marginal farmers to enhance income and employment, living standards, etc. Due to numerous crises and challenges such as unawareness, poverty, droughts, dry climate, the small and marginal distribution of land, etc., the identification of an appropriate integrated farming system model is highly required. So, this research aims to deliver a solution for the identification and finalization of the IFS model which is a critical task in front of farm families, Agri-scientists, policy-makers, and business organizations. This study is conducted through a field survey in the district of Udaipur, Rajasthan. This work experimented with randomly selecting 4 panchayat samitis out of 20 panchayat samitis, 4 villages selected from each panchayat samiti ee to identify existing integrated farming systems among farm families. This study observed the prominent integrated farming system model among the considered models. This work identifies the IFS models which are the most prominent farming system (M1: crop+ dairy) and are adopted by most farm families. This research work also identified integrated farming models M1 and M2 as the most preferred, profitable, and very suitable for business decision-making. Similarly, M3 and M4 are also good but less preferred than M1 and M2.

Dual Challenge-Response Systems of a Three-Dimensional "Bionic" Fluorescent Physically Unclonable Function Label.

Inspired by the light and dark variations observed in natural cloud clusters under sunlight, we propose a three-dimensional (3D) "bionic" fluorescent physically unclonable function (PUF) label. The minimalist preparation process eliminates the need for expensive traditional instruments, thus offering new insight into the widespread adoption of 3D PUF labels. The Eu(CCA)3(H2O)2 powder, which is the first to propose its secondary building unit, was chosen as the fluorescent material. Its 3D morphology is preserved in the resin to mimic cloud-like structures. Furthermore, the luminescent properties are elucidated through experimental tests and first-principles calculations. To overcome the coding capacity limitation of traditional two-dimensional (2D) fluorescent PUF labels, a dual challenge-response system model is proposed. The shallow and deep models provide anticounterfeiting information from macro and micro perspectives, respectively. This successfully increases the encoding capacity from 210×10 to 2100×10000 for a 10 × 10 pixel binary code. Therefore, 3D "bionic" fluorescent PUF labels strike a balance between the simple usage of PUF labels and enhanced label security.

Assessment of Storm‐Associated Precipitation and Its Extremes Using Observational Data Sets and Climate Model Short‐Range Hindcasts

AbstractHeavy precipitation, often associated with weather phenomena such as tropical cyclones, extratropical cyclones (ETCs), atmospheric rivers (ARs), and mesoscale convective systems (MCSs), can cause significant socio‐economic loss. In this study, we apply atmospheric feature trackers to quantify the contributions of these storm types in observational data sets and climate model short‐range hindcasts. We generate a global hourly storm data set at 0.25° spatial resolution covering 2006–2020, based on the tracking results from TempestExtremes and Python FLEXible object TRacKeR. Our analyses show that these four storm types account for 67% of global annual mean precipitation and 82% of top 1% precipitation extremes, with MCSs mainly over the tropics, and ARs and ETCs over the midlatitudes. The percentage of precipitation contributions from these storms also show strong seasonality over many geographical locations. We further apply the tracking results to the Energy Exascale Earth System Model (E3SM) short‐range hindcasts and evaluate how well these storms are simulated. The evaluation show that E3SM, with ∼1° resolution, significantly underestimates storm‐associated precipitation totals and extremes, especially for MCSs in the tropics. Our analysis also suggests that model fails to capture the correct mean diurnal phases and amplitude of MCS precipitation. This phenomenon‐based approach provides a better understanding of precipitation characteristics and can lead to enhanced model evaluation by revealing underlying problems in model physics related to precipitation processes associated with the heavy‐precipitating storms.

Parameters extraction of photovoltaic models using enhanced generalized normal distribution optimization with neighborhood search

AbstractThe photovoltaic system has been widely integrated into electrical power grids to produce clean and sustainable energy sources. Precisely modeling of systems is crucial to simulate and asset the performance of such power system. Modeling of system is a challenge because the characteristic curve of current and voltage is nonlinear and has unknown parameters due to insufficient data points in manufacture’s data sheet. This work proposes generalized normal distribution optimization based on neighborhood search strategies () to extract the parameter of single diode model (), double diode model (), and module model (). The root means square error () is used as a performance indicator. Two commercial models like RTC France solar cell and PWP201 are used to validate the ability of to precisely estimated the system’s parameters. The results show the superiority of over competitive optimization methods and can reduce the to 2.05296E-03 for PWP201 and to 9.8248E-04 for RTC France solar cell which prove that can be used as competitor method to identify the parameters of solar system. The statistical analysis shows the robustness of through statistical measurements and Wilcoxon rank test.’

Displacement Mechanism and Flow Characteristics of Polymer Particle Dispersion System Based on Capillary Bundle Model

During the development of oil reservoirs, a rapid increase in water cut following reservoir flooding leads to inefficient or ineffective circulation of injected water, rendering a significant portion of the remaining oil in the reservoir inaccessible. The displacement method using polymer particle dispersion systems effectively solves the issue of rapid water breakthrough in oil reservoirs. Owing to the particle phase separation phenomenon, polymer particles can selectively penetrate into the larger pores where water circulation is inefficient, enhance their flow resistance, and thereby achieve equilibrium displacement along with an increased swept volume. This paper investigates the heterogeneous distribution of polymer particles within a porous medium, incorporates the red blood cell dendrite concentration distribution theory from biological fluid mechanics, and develops a mathematical model to delineate the viscosity characteristics of polymer particle dispersion systems, taking into account the phase separation phenomenon. Building on this foundation, it formulates a capillary bundle model for the polymer particle dispersion system specifically designed for oil displacement and proceeds to determine its relative permeability curve. Simulation outcomes reveal that at a water saturation level of 0.063, the concentration of polymer particles in fractured large pore capillaries is markedly elevated, yet capillaries with a pore size under 26 μm remain devoid of polymer particles. With the increase of water saturation, the concentration of polymer particles in large pore capillaries reduces, whereas it progressively augments in medium pore capillaries. Upon reaching a peak water saturation of 0.751, capillaries smaller than 18 μm are entirely free of polymer particles. These findings suggest that the heterogeneous distribution of polymer particles markedly inhibits the percolation capabilities of the dispersed system following a water phase breakthrough, facilitating the entry of more dispersion into oil-laden capillaries and thus enhancing the flow capacity of the oil phase.

Coupling material and energy flow analysis with life cycle assessment to support circular strategies at the urban level

Abstract Purpose This study aims to investigate how the coupling of Material and Energy Flow Analysis (MEFA) with Life Cycle Assessment (LCA) under an urban metabolism (UM) perspective (referred to as the UM-LCA approach) can support the design, evaluation, and monitoring of urban-level circular strategies. For this purpose, we apply the UM-LCA approach to the urban area of Umeå (Sweden) by expanding the goal and scope of a recent MEFA study conducted by the authors of the article. Methods The modeling combines MEFA with LCA and is performed both retrospectively and prospectively. The MEFA was performed in the prior study following a bottom-up approach to map and quantify material and energy flows in the urban system at the sectoral level. The quantified flows are used in the present study to construct the life cycle inventory (LCI) model of the urban system. The LCI model is first used as a basis of the retrospective LCA (rLCA), which is conducted to assess the environmental performance of the urban system with its sectors. The LCI model is then modified according to future scenarios and is used as a basis of the prospective LCA (pLCA), which is performed to assess the environmental implications of implementing circular strategies in the future. Results and discussion The rLCA shows that the construction and household sectors are major drivers of environmental impacts in the urban system, with households being the largest contributors to 11 out of 12 analyzed impact categories. It also reveals the most impacting flows within these sectors, including food in households and steel in the construction sector. These findings indicate that the construction and household sectors and their most impacting flows should be prioritized in a circular strategy. Furthermore, the pLCA highlights that a future circular strategy promoting reductions in the material used in these two sectors could lead to higher reductions in all impact categories, ranging from 4.3 to 8.6%, than a strategy focused only on recycling, which could lead to reductions ranging from 0.2 to 1.2%. Conclusions This study concludes that the UM-LCA approach has great potential to comprehensively analyze, both retrospectively and prospectively, the environmental performance of an urban system providing valuable insights that could support policy makers in designing, assessing, and monitoring urban-level circular strategies. However, further research should address identified limitations of the UM-LCA approach (e.g., limited available data, inability to consider social and economic aspects) to facilitate its applicability and enhance its comprehensiveness.

Distributed HAPS-assisted communications in FSO/RF space-air-ground integrated networks

Space-air-ground integrated (SAGI) communication networks have been envisioned as one of the pillars of the next generation communications (6 G). This type of networks are expected to offer fairness and high quality of services in various scenarios where traditional terrestrial communication systems cannot efficiently support due to inherent limitations, e.g., limited coverage areas. In this paper, a distributed transmission scheme is proposed in a SAGI communication network that utilizes free-space-optical (FSO)/radio frequency (RF) links. More specifically, a set of N high altitude platform systems are cooperatively transmit the received signal to the ground station, using the decode-and-forward relaying protocol. For this system, generic analytical expressions for the outage probability (OP) have been derived that take into consideration the impact of turbulence, pointing errors, and atmospheric attenuation (for the FSO links) as well as the impact of composite fading (for the RF links). Moreover, asymptotic closed-form expressions for the OP are also presented, which are used to extract useful insights for the system under consideration. The numerical evaluated results that are illustrated reveal the impact of various system and channel models parameters on the system’s performance. From these results, it is shown that the proposed scheme outperforms a pure FSO-based relaying scheme, which has been used as a benchmark, under different environmental conditions.

Net primary production annual maxima in the North Atlantic projected to shift in the 21st century

Abstract. Shifts in the day of peak net primary production (NPP) were detected in different biogeochemical provinces of the North Atlantic (25–65° N). Most provinces displayed a shift toward earlier peak NPP, with the largest change points in the 21st century and in the northern parts of the domain. Furthermore, the occurrences of the first day with a mixed-layer depth (MLD) shallower than 40 m and the day of peak NPP are positively correlated over most of the domain. As was the case for the day of peak NPP, the largest change points for the day of MLD shallower than 40 m occur around or after the year 2000. Daily output from two fully coupled CMIP6 Earth system models, EC-Earth3-CC and NorESM2-LM, for the period 1750–2100 and under the SSP5-8.5 scenario, were used for the analysis. The ESM NPP data were compared with estimates derived from Carbon, Absorption and Fluorescence Euphotic-resolving (CAFE) satellite-based data. The ESMs showed significant differences from the CAFE model, though the timing of peak NPP was well captured for most provinces. The largest change points in the day of peak NPP occur earlier in EC-Earth3-CC than in NorESM2-LM. Although SSP5-8.5 is a scenario with very high warming, EC-Earth3-CC generates change points for most provinces in the early part of the 21st century, before the warming has deviated far from lower-emissions scenarios. NorESM2-LM displays the largest change points centered around the mid 21st century, with two out of eight provinces displaying the largest change point before the year 2050. The early timing of the detected shifts in some provinces in both ESMs suggests that similar shifts could already have been initiated or could start in the near future. This highlights the need for long-term monitoring campaigns in the North Atlantic.

Voltage stability assessment of the power system using novel line voltage collapse index

Nowadays, for the maximum utilization of the power available, power systems are operated at their maximum stability limit due to the scarcity of natural resources. In this situation, quick monitoring and control of the power systems are very necessary for the electrical operators. This paper presents a novel line voltage stability index based on V-Q sensitivity. The index is created utilizing the network’s ABCD parameters and is based on an exact transmission system model. The new index is evaluated in terms of ABCD parameters from the reactive power equation of the power system. The proposed line index can predict the voltage collapse under heavy MVA loading, heavy reactive loading, randomly chosen heavy reactive loading, and different N-1 contingencies conditions. This has also the capability to predict voltage stability under different contingencies. The proposed method is compared with four existing methods named line stability index (Lmn), fast voltage stability index (FVSI), line stability factor (Lqp), and line voltage stability index (LVSI). Results show that the critical situation of the power system that has been investigated by the proposed approach is more accurate than these four existing methods under different operating scenarios. The accuracy and applicability of the proposed method are investigated on IEEE 14-bus and IEEE 118-bus systems.

The carbonate pump feedback on alkalinity and the carbon cycle in the 21st century and beyond

Abstract. Ocean acidification is likely to impact all stages of the ocean carbonate pump, i.e. the production, export, dissolution and burial of biogenic CaCO3. However, the associated feedback on anthropogenic carbon uptake and ocean acidification has received little attention. It has previously been shown that Earth system model (ESM) carbonate pump parameterizations can affect and drive biases in the representation of ocean alkalinity, which is critical to the uptake of atmospheric carbon and provides buffering capacity towards associated acidification. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we show divergent responses of CaCO3 export at 100 m this century, with anomalies by 2100 ranging from −74 % to +23 % under a high-emission scenario. The greatest export declines are projected by ESMs that consider pelagic CaCO3 production to depend on the local calcite/aragonite saturation state. Despite the potential effects of other processes on alkalinity, there is a robust negative correlation between anomalies in CaCO3 export and salinity-normalized surface alkalinity across the CMIP6 ensemble. Motivated by this relationship and the uncertainty in CaCO3 export projections across ESMs, we perform idealized simulations with an ocean biogeochemical model and confirm a limited impact of carbonate pump anomalies on 21st century ocean carbon uptake and acidification. However, we highlight a potentially abrupt shift, between 2100 and 2300, in the dissolution of CaCO3 from deep to subsurface waters when the global-scale mean calcite saturation state reaches about 1.23 at 500 m (likely when atmospheric CO2 reaches 900–1100 ppm). During this shift, upper ocean acidification due to anthropogenic carbon uptake induces deep ocean acidification driven by a substantial reduction in CaCO3 deep dissolution following its decreased export at depth. Although the effect of a diminished carbonate pump on global ocean carbon uptake and surface ocean acidification remains limited until 2300, it can have a large impact on regional air–sea carbon fluxes, particularly in the Southern Ocean.

Viable System Model (VSM): A New Approach to Accounting Information System Development Model

This article discusses the potential for using the Viable System Model (VSM) as a new approach in developing accounting information systems. This article takes the form of a systematic literature review. The analysis was carried out using a comparative approach between the System Development Life Cycle (SDLC-Model) and the Viable System Model (VSM) in general and specifically in the field of accounting and accounting information systems. The SDLC is primarily focused on the development and management of software or systems, while the VSM is concerned with the broader understanding and management of complex organizations. Both concepts have their unique applications and are important in their respective domains. The results of the study show that the VSM has a more holistic approach in developing accounting information systems. The research results also show that VSM is more suitable for developing accounting information systems in organizations that are complex, flexible, and adaptive to the speed of change in the company’s ongoing organizational business environment. The VSM provides a framework for understanding how organizations and systems can adapt to changing environments and maintain viability. It is particularly useful for complex organizations that need to respond to dynamic conditions. Keywords: accounting information system development, viable system model, system development life cycle

Efficient spin-up of Earth System Models using sequence acceleration.

Marine and terrestrial biogeochemical models are key components of the Earth System Models (ESMs) used to project future environmental changes. However, their slow adjustment time also hinders effective use of ESMs because of the enormous computational resources required to integrate them to a pre-industrial equilibrium. Here, a solution to this "spin-up" problem based on "sequence acceleration", is shown to accelerate equilibration of state-of-the-art marine biogeochemical models by over an order of magnitude. The technique can be applied in a "black box" fashion to existing models. Even under the challenging spin-up protocols used for Intergovernmental Panel on Climate Change (IPCC) simulations, this algorithm is 5 times faster. Preliminary results suggest that terrestrial models can be similarly accelerated, enabling a quantification of major parametric uncertainties in ESMs, improved estimates of metrics such as climate sensitivity, and higher model resolution than currently feasible.

Exploring the prospects, advancements, and challenges of in vitro modeling of the heart-brain axis

Research on bidirectional communication between the heart and brain has often relied on studies involving nonhuman animals. Dependance on animal models offer limited applicability to humans and a lack of high-throughput screening. Recently, the field of 3D cell biology, specifically organoid technology, has rapidly emerged as a valuable tool for studying interactions across organ systems, i.e., gut-brain axis. The initial success of organoid models indicates the usefulness of 3D cultures for elucidating the intricate interactivity of the autonomic nervous system and overall health. This perspective aims to explore the potential of advancing in vitro modeling of the heart-brain axis by discussing the benefits, applications, and adaptability of organoid technologies. We closely examine the current state of brain organoids in conjunction with the advancements of cardiac organoids. Moreover, we explore the use of combined organoid systems to investigate pathophysiology and provide a platform for treatment discovery. Finally, we address the challenges that accompany the use of 3D models for studying the heart-brain axis with an emphasis on generating tailored engineering strategies for further refinement of dynamic organ system modeling in vitro.

Application of Fuzzy Control and Neural Network Control in the Commercial Development of Sustainable Energy System

Sustainable energy systems (SESs) occupy a prominent position in the modern global energy landscape. The purpose of this study is to explore the application of fuzzy control and neural network control in photovoltaic systems to improve the power generation efficiency and stability of the system. By establishing the mathematical model of a photovoltaic system, the nonlinear and uncertain characteristics of photovoltaic system are considered. Fuzzy control and neural network control are used to control the system, and their performance is verified by experiments. The experimental results show that under the conditions of low light and moderate temperature, the fuzzy neural network control achieves a 3.33% improvement in power generation efficiency compared with the single control strategy. Meanwhile, the system can still maintain relatively stable operation under different environmental conditions under this comprehensive control. This shows that fuzzy neural network control has significant advantages in improving power generation efficiency and provides beneficial technical support and guidance for the commercial development of SESs.

Research on dynamic stability of rolling missiles employing direct/aerodynamic force compound control

The direct/aerodynamic force compound control can enhance the maneuverability and response characteristics of missiles, and the dynamic stabilization is the precondition of normal operation for rolling missiles. Aiming at the stability problem caused by the cross-coupling effect of rolling missiles employing direct/aerodynamic force compound control, proposing a typical topological control system structure described by the complex coefficient theory, and deducing the dynamic stability conditions. Firstly, the mathematic model is established based on the kinematics and dynamics theories of rotating airframes and the direct/aerodynamic force compound control mechanism. Then, a three-loop autopilot and the direct/aerodynamic force ratio distribution method are designed to establish the complex summation model of the compound control system by selecting suitable complex variables. Furthermore, deducing the dynamic stability conditions and verifying them by numerical simulations. Finally, the stable regions of the rolling missile in different cases are obtained and found to be influenced by many factors, such as parameters of the autopilot, hybrid force distribution proportion and rolling rate. The derived dynamic stability criterion is effective for evaluating the stability of rolling missiles employing direct/aerodynamic force compound control and the research method used in this paper can provide reference for the stability study of strongly coupled nonlinear systems.

Experimental validation of the appropriate channel model for an indoor Visible Light Communication system

Visible light communication (VLC) is a technology with significant potential to revolutionize indoor communication performance and satisfy the demands of fifth-generation (5G) and beyond technologies. To achieve an efficient VLC system that delivers optimal performance and coverage, it is imperative to create a reliable channel model. As a result, this research is centered around the evaluation of existing channel models for planning the VLC network coverage within indoor environments. The primary focus of this study is to enforce three types of channel models, Line of Sight (LoS), Nakagawa’s first reflection model, and the Spherical model through MATLAB simulations and obtain simulation results by varying the distance parameter. Furthermore, this research intends to implement a physical prototype representing a real-world scenario, and thereby determine the nearest channel model that aligns with the physical measurements obtained from the physical prototype.