General Computational Model Research Articles

Rewiring cattle movements to limit infection spread

Cattle tracing databases have become major resources for representing demographic processes of livestock and assessing potential risk of infections spreading by trade. The herds registered in these databases are nodes of a network of commercial movements, which can be altered to lower the risk of disease transmission. In this study, we develop an algorithm aimed at reducing the number of infected animals and herds, by rewiring specific movements responsible for trade flows from high- to low-prevalence herds. The algorithm is coupled with a generic computational model based on the French cattle movement tracing database (BDNI), and used to describe different scenarios for the spread of infection within and between herds from a recent outbreak (epidemic) or a five-year-old outbreak (endemic). Results show that rewiring successfully contains infections to a limited number of herds, especially if the outbreak is recent and the estimation of disease prevalence frequent, while the respective impact of the parameters of the algorithm depend on the infection parameters. Allowing any animal movement from high to low-prevalence herds reduces the effectiveness of the algorithm in epidemic settings, while frequent and fine-grained prevalence assessments improve the impact of the algorithm in endemic settings. Our approach focusing on a few commercial movements is expected to lead to substantial improvements in the control of a targeted disease, although changes in the network structure should be monitored for potential vulnerabilities to other diseases. This general algorithm could be applied to any network of controlled individual movements liable to spread disease.

Effect of leakage of volatile synthesis products on silicon carbide yield in an electrothermal fluidized bed reactor

Effect of leakage of volatile synthesis products on silicon carbide yield in an electrothermal fluidized bed reactor

A statistical approach for identifying single nucleotide variants that affect transcription factor binding

Non-coding variants located within regulatory elements may alter gene expression by modifying transcription factor (TF) binding sites, thereby leading to functional consequences. Different TF models are being used to assess the effect of DNA sequence variants, such as single nucleotide variants (SNVs). Often existing methods are slow and do not assess statistical significance of results. We investigated the distribution of absolute maximal differential TF binding scores for general computational models that affect TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on invitro and invivo datasets showed that our approach improves upon an existing method in terms of performance and speed. Applications on eQTLs and on a genome-wide association study illustrate the usefulness of our statistics by highlighting cell type-specific regulators and target genes. An implementation of our approach is freely available on GitHub and as bioconda package.

Digital twinning of temperature fields for modular multilayer multiphase pipeline structures

The temperature field of oil and gas wells in the field of petroleum engineering presents a core problem and challenge in the digital twin framework due to its ultra-long-distance and highly variable structural characteristics. The varying wellbore cross-sectional structures with depth make it difficult to establish an effective and generalized analytical model for heat transfer. In this study, we propose, for the first time, a method to automate the construction of multi-layered and multi-component heat transfer models by using a general computational model based on non-steady-state single-phase structural modules. This method enables the automated generation of complex multi-layered and multi-component heat transfer models, thereby achieving the construction of a generalized model for temperature field characterization with varying wellbore cross-sectional structures over ultra-long distances. Utilizing this modeling approach, we validate the proposed method through case studies using actual wellbore temperature field data. The results demonstrate the lightweight and efficient computational analysis of temperature field information under non-steady-state conditions.

On the origins of developmental robustness: modeling buffering mechanisms against cell-level noise.

During development, cells are subject to stochastic fluctuations in their positions (i.e. cell-level noise) that can potentially lead to morphological noise (i.e. stochastic differences between morphologies that are expected to be equal, e.g. the right and left sides of bilateral organisms). In this study, we explore new and existing hypotheses on buffering mechanisms against cell-level noise. Many of these hypotheses focus on how the boundaries between territories of gene expression remain regular and well defined, despite cell-level noise and division. We study these hypotheses and how irregular territory boundaries lead to morphological noise. To determine the consistency of the different hypotheses, we use a general computational model of development: EmbryoMaker. EmbryoMaker can implement arbitrary gene networks regulating basic cell behaviors (contraction, adhesion, etc.), signaling and tissue biomechanics. We found that buffering mechanisms based on the orientation of cell divisions cannot lead to regular boundaries but that other buffering mechanisms can (homotypic adhesion, planar contraction, non-dividing boundaries, constant signaling and majority rule hypotheses). We also explore the effects of the shape and size of the territories on morphological noise.

ModEx: a general purpose computer model exploration system.

We present a general purpose visual analysis system that can be used for exploring parameters of a variety of computer models. Our proposed system offers key components of a visual parameter analysis framework including parameter sampling, deriving output summaries, and an exploration interface. It also provides an API for rapid development of parameter space exploration solutions as well as the flexibility to support custom workflows for different application domains. We evaluate the effectiveness of our system by demonstrating it in three domains: data mining, machine learning and specific application in bioinformatics.

Phenotypic pliancy and the breakdown of epigenetic polycomb mechanisms.

Epigenetic regulatory mechanisms allow multicellular organisms to develop distinct specialized cell identities despite having the same total genome. Cell-fate choices are based on gene expression programs and environmental cues that cells experience during embryonic development, and are usually maintained throughout the life of the organism despite new environmental cues. The evolutionarily conserved Polycomb group (PcG) proteins form Polycomb Repressive Complexes that help orchestrate these developmental choices. Post-development, these complexes actively maintain the resulting cell fate, even in the face of environmental perturbations. Given the crucial role of these polycomb mechanisms in providing phenotypic fidelity (i.e. maintenance of cell fate), we hypothesize that their dysregulation after development will lead to decreased phenotypic fidelity allowing dysregulated cells to sustainably switch their phenotype in response to environmental changes. We call this abnormal phenotypic switching phenotypic pliancy. We introduce a general computational evolutionary model that allows us to test our systems-level phenotypic pliancy hypothesis in-silico and in a context-independent manner. We find that 1) phenotypic fidelity is an emergent systems-level property of PcG-like mechanism evolution, and 2) phenotypic pliancy is an emergent systems-level property resulting from this mechanism's dysregulation. Since there is evidence that metastatic cells behave in a phenotypically pliant manner, we hypothesize that progression to metastasis is driven by the emergence of phenotypic pliancy in cancer cells as a result of PcG mechanism dysregulation. We corroborate our hypothesis using single-cell RNA-sequencing data from metastatic cancers. We find that metastatic cancer cells are phenotypically pliant in the same manner as predicted by our model.

Computational and Communication Aspects of Digital Twin: An Information Theoretical Perspective

Digital twins are replicas of real-world objects that connect physical and digital spaces in real-time. In this letter, we derive bounds on the probability of error for the virtual twin being a true representative under a generic computational and communication model. We show that the representative performance of a digital twin depends on the quality of the model employed by the digital twin and the amount of directed information flowing between the virtual and physical entities. We illustrate the bounds developed and the interdependence of parameters with a numerical example.

Surface damage evolution of artillery barrel under high-temperature erosion and high-speed impact

Thermochemical erosion and mechanical wear are the primary sources of surface damage in artillery barrel chambers, severely restricting the interior ballistic characteristics and service life of the barrel weapon. This paper proposes a general surface damage computational model, which contains three sub-models: collision wear, melting exfoliation, and high-speed jet wear. The combination of the three sub-models can predict the surface damage of mechanical structures caused by the coupling of thermochemical erosion and mechanical wear. The contact force model to describe collision behavior is first proposed, and the collision wear model can be obtained based on the contact force model. Moreover, the temperature distribution of the barrel chamber is calculated, by this the melting exfoliation model can be obtained. Considering that melting exfoliation and collision wear have the non-negligible effect on the attack angle of high-speed jet, this paper equates melting exfoliation and collision wear to the variation of attack angle size and investigates the high-speed jet wear of the barrel chamber. The experimental research of the surface damage on the barrel chamber is organized, and the detailed assessments show that the general surface damage computational model has a good agreement with experimental data.

Multihyperuniform long-range order in medium-entropy alloys

Medium-entropy alloys (MEAs) and high-entropy alloys (HEAs) are alloys composed of mixtures of equal or relatively large proportions of three or more elements, and are distinctly different from traditional metallic alloys which contain one or two major components with smaller amounts of other elements. Recently MEAs and HEAs have received extensive research attention because they are found to possess superior mechanical performance, unusual thermal and electronic transport properties, and are resistant to corrosion; however, a fundamental understanding of the atomic structures of these alloys is still largely lacking. In this work, we develop a multihyperuniform (MH) model for disordered medium-entropy alloys (MEAs), in which the normalized infinite-wavelength composition fluctuations for all atomic species are completely suppressed, i.e., a model with hidden long-range order. Using SiGeSn alloy as a representative example, we show that this new type of highly efficient generic computational model results in stable lower-energy states compared to prevailing alloy models with (quasi)random structures, and captures experimentally observed atomic short-range orders in MEAs that are missing in (quasi)random alloy models. The MH model approximately realizes the Vegard’s law, which offers a rule-of-mixture type predictions of the lattice constants and electronic band gap, and thus can be considered as an ideal mixing state. The multihyperuniformity also directly gives rise to enhanced electronic band gaps and superior thermal transport properties at low temperatures compared to (quasi)random structures, which open up novel potential applications in optoelectronics and thermoelectrics. Our MH model can be readily applied and generalized to other medium- and high-entropy alloys (HEAs) with atomic short-range orders, and may account for some of the previously observed major discrepancies between theory and experiment.

Product-Service System design – an example of the logistics industry

Product-Service System (PSS) has been perceived since the 90s as a concept supporting enterprises of various indus-tries in creating a competitive advantage and generating new value for customers by expanding the offer with addi-tional services related to the product. Product-Service System (PSS) draws attention to the life cycle of products and services and the circular economy, which supports sustainable development. All the time, practitioners and theorists report the need to develop new Product-Service System (PSS) for other industries. Until now, a number of practical and methodological aspects related to design remain unresolved. The paper presents issues related to the Product-Service System (PSS) and PSS design. A literature review and gaps in available methods are presented. A conceptual frame-work for Product-Service System (PSS) design that has been used in the logistics industry is presented. By referring to the design of a selected process from the logistics industry, it was presented how to analyze the process during design and what methods of design support to use. Reference is made to mathematical modeling based on the optimization function and computer modeling with the use of a simulation model. Attention was also paid to the importance of knowledge of the industry and having expert knowledge about the designed processes in the systems. It is also extremely important to have the appropriate data set for a given case. In addition to the general mathematical and computer model, reference was also made to a chosen element of Product-Service System (PSS). The mathematical and simulation model included in the study refer to the process of completing customer orders in a logistics company. It is one of the most laborious and time-consuming processes. The FlexSim simulation environment was used to perform the computer simulation. A total of 15 variants were considered, which differ in terms of the scope of services provided during the process. The scope of services significantly affects the cost, time and profit. The purpose of the constructed model is to find a variant for the adopted data in which the profits will be maximized while maintaining the constraints imposed on the system.

Synthesis of Parallel Software from Heterogeneous Dataflow Models

Dataflow process networks (DPNs) are intrinsically data-driven, i.e., node actions are not synchronized among each other and may fire whenever sufficient input operands arrived at a node. While the general model of computation (MoC) of DPNs does not impose further restrictions, many different subclasses of DPNs representing different dataflow MoCs have been considered over time. These classes mainly differ in the kinds of behaviors of the processes. A DPN may be heterogeneous in that different processes in the network belong to different classes of DPNs. A heterogeneous DPN can therefore be effectively used to model and to implement different components of a system with different kinds of processes and, therefore, different dataflow MoCs. This paper presents a model-based design based on different dataflow MoCs including their heterogeneous combinations. In particular, it covers the automatic software synthesis of systems from DPN models. The main objective is to validate, evaluate and compare the artifacts exhibited by different dataflow MoCs at the implementation level of systems under the supervision of a common design tool. Moreover, this work also offers an efficient synthesis method that targets and exploits heterogeneity in DPNs by generating implementations based on the kinds of behaviors of the processes. The proposed synthesis method provides a tool chain including different specialized code generators for specific dataflow MoCs, and a runtime system that finally maps models using a combination of different dataflow MoCs on cross-vendor target hardware.

Verification of agent navigation in partially-known environments

This paper establishes a framework based on logic and automata theory in which to model and automatically verify systems of multiple mobile agents moving in environments with partially-known topologies, i.e., ones which are not completely known at design time. Examples include physical agents designed to be used in many spatial environments and not tailored for a specific one, robots in environments not reachable by humans, and software exploring partially-mapped networks. We model spatial environments as graphs whose edges are labelled with directions. We model agents as finite-state machines that move on the graphs by issuing commands of the form “go in direction X”, that can communicate their internal state to other agents, and that can sense agent positions (including current and visited positions). We treat the incomplete information about the spatial environment by studying the decision problem that asks whether a given collection of agents achieve their tasks on all graphs from a class of graphs — this is called the parameterised verification problem. The framework also introduces a new logical language based on Linear Temporal Logic that is tailored for expressing agent navigation tasks in such environments.Although the parameterised verification problem is undecidable, we identify two key dimensions that need to be limited in order to regain decidability, namely, the set of graph-environments and the amount of sensing and communication between agents. In particular, one should limit the families of graphs to exclude grids, and there should be a bound on the number of times an agent senses the position of another agent or communicates its own state to another agent. We prove that dropping either of these assumptions results in undecidability, even for agents with severe restrictions on their abilities (e.g., with very limited sensing abilities and no communication abilities). The importance of this work is that a) it provides a general computational model for mobile multi-agent systems in environments with partially-known topologies, b) it identifies, for the first time, the precise causes of undecidability of these systems and presents minimal restrictions to alleviate this problem, and c) it provides a generic sound and complete procedure for solving the parameterised verification problem over a broad range of spatial-environments and for agents with very powerful sensing and communication abilities.

Separate processing mechanisms for spatial-numerical compatibility and numerical-size congruity.

Across two experiments, the numerical magnitude and the physical size of single digits presented in either two (Experiment 1) or four (Experiment 2) different font sizes were judged using either horizontally and vertically (Experiment 1) or just horizontally (Experiment 2) aligned manual responses. Such a design allowed for the simultaneous examination of the size congruity effect (SiCE), the spatial-numerical association of response codes (SNARC) effect, and the more novel spatial-size association of response codes (SSARC) effect. In Experiment 1, SiCEs and SNARC effects were found that operated independently of one another but no SSARC effect occurred. In Experiment 2, separate SiCEs and SNARC effects were found when judging numerical magnitude whereas separate SiCEs and SSARC effects were found when judging physical size. As will be discussed, such findings provide important constraints on the manner in which the full set of congruency and compatibility effects between stimulus and response dimensions in such tasks may be modeled. To illustrate this point, four different versions of a general computational processing model of these effects are considered. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

From Affect Theoretical Foundations to Computational Models of Intelligent Affective Agents

The links between emotions and rationality have been extensively studied and discussed. Several computational approaches have also been proposed to model these links. However, is it possible to build generic computational approaches and languages so that they can be “adapted” when a specific affective phenomenon is being modeled? Would these approaches be sufficiently and properly grounded? In this work, we want to provide the means for the development of these generic approaches and languages by making a horizontal analysis inspired by philosophical and psychological theories of the main affective phenomena that are traditionally studied. Unfortunately, not all the affective theories can be adapted to be used in computational models; therefore, it is necessary to perform an analysis of the most suitable theories. In this analysis, we identify and classify the main processes and concepts which can be used in a generic affective computational model, and we propose a theoretical framework that includes all these processes and concepts that a model of an affective agent with practical reasoning could use. Our generic theoretical framework supports incremental research whereby future proposals can improve previous ones. This framework also supports the evaluation of the coverage of current computational approaches according to the processes that are modeled and according to the integration of practical reasoning and affect-related issues. This framework is being used in the development of the GenIA3 architecture.

Extended Mulliken–Hush Method with Applications to the Theoretical Study of Electron Transfer

A novel adiabatic-to-diabatic (ATD) transformation strategy, namely, the extended Mulliken-Hush (XMH) method, is proposed to evaluate diabatic properties including electronic couplings, potential energy surfaces, and their crossings. The XMH method is developed by adopting our recently proposed ATD transformation formula of a general vectorial physical observable, in which a useful ATD transformation is further determined by using an auxiliary dipole between localized frontier orbitals as a simple approximation of the diabatic transition dipole. The XMH method is simple and practical that provides a flexible way to construct diabatic states. To some extent, it can be regarded as an extension of the generalized Mulliken-Hush (GMH) method since the latter takes a stronger approximation, in which the diabatic transition dipole is assumed to be vanishing. Test calculations on the HeH2+ system show that the electronic couplings predicted by the XMH method are closer to the ones calculated by the valence bond block-diagonalization approach than the GMH ones since the XMH method takes into account both the magnitude and direction of the diabatic transition dipole, which is consistent with the properties of this molecule. In the study of electron transfer in the two kinds of donor-bridge-acceptor systems, the XMH method maintains the simplicity of the GMH method and gives reasonable results even when the latter fails, wherein the diabatic transition dipole is nearly perpendicular to the difference of the initial and final adiabatic dipoles. More importantly, the XMH method can be easily combined with high-level electronic structure methods, in which the properties of the ground and excited states may be more accurately calculated, and hence, one may expect that further development of the XMH method would result in a general computational model for studying electron transfer reactions.

COMPUTER SIMULATION OF PARTICLE VELOCITY IN A CYCLONE

The article sets the goal of determining and calculating the speed of accelerated movement of particles in the gas-dust flow of an air cyclone, depending on the size of the cyclone, the physical properties of the particle and the gas-dust flow. A method for constructing a computer model of the motion of a particle in a roaring gas-dust flow of a cyclone is presented. The sequence of formalization of the computer model of the process of sedimentation of particles of a gas-dust flow of a cyclone unit is based on the theoretical foundations of aerodynamics and touches on the most significant aspects of the development of a cyclone. Attention paid to the analysis of the dynamics of particle motion in a centrifugal field, accelerated motion and a realistic estimate of the particle velocity. The mutual influences of five forces are considered. This is the centrifugal force, the force of resistance of the gas-dust flow, the forces of gravity, the Archimedean force and the force of inertia, acting on the accelerating motion of the particle in the flow. On the basis of the block principle, a general computer model of the cycloning process is built, which makes it possible to calculate the uneven velocity of a particle in a gas-dust flow. Analytical methods for evaluating the acceleration parameters and the main methods of numerical analysis of the dynamics of particle motion, shows that the main advantage of up to 0.8 seconds is the accelerated motion of a particle in a gas-dust flow under the given conditions. During this time, most of the particles reach the cyclone wall. This shows that the determination of the accelerating motion of a particle plays an important role in cyclones.

Inference on homeostatic belief precision

Interoception and homeostatic/allostatic control are intertwined branches of closed-loop brain-body interactions (BBI). Given their importance in mental and psychosomatic disorders, establishing computational assays of BBI represents a clinically important but methodologically challenging endeavor. This technical note presents a novel approach, derived from a generic computational model of homeostatic/allostatic control that underpins (meta)cognitive theories of affective and psychosomatic disorders. This model views homeostatic setpoints as probability distributions (“homeostatic beliefs”) whose parameters determine regulatory efforts and change dynamically under allostatic predictions. In particular, changes in homeostatic belief precision, triggered by anticipated threats to homeostasis, are thought to alter cerebral regulation of bodily states. Here, we present statistical procedures for inferring homeostatic belief precision from measured bodily states and/or regulatory (action) signals. We analyze the inference problem, derive two alternative estimators of homeostatic belief precision, and apply our method to simulated data. Our proposed approach may prove useful for assessing BBI in individual subjects.

Modelling palliative and end-of-life resource requirements during COVID-19: implications for quality care

ObjectivesThe WHO estimates that the COVID-19 pandemic has led to more than 1.3 million deaths (1 377 395) globally (as of November 2020). This surge in death necessitates identification of...

Creative Destruction: A Basic Computational Model of Cortical Layer Formation.

One of the most characteristic properties of many vertebrate neural systems is the layered organization of different cell types. This cytoarchitecture exists in the cortex, the retina, the hippocampus, and many other parts of the central nervous system. The developmental mechanisms of neural layer formation have been subject to substantial experimental efforts. Here, we provide a general computational model for cortical layer formation in 3D physical space. We show that this multiscale, agent-based model, comprising two distinct stages of apoptosis, can account for the wide range of neuronal numbers encountered in different cortical areas and species. Our results demonstrate the phenotypic richness of a basic state diagram structure. Importantly, apoptosis allows for changing the thickness of one layer without automatically affecting other layers. Therefore, apoptosis increases the flexibility for evolutionary change in layer architecture. Notably, slightly changed gene regulatory dynamics recapitulate the characteristic properties observed in neurodevelopmental diseases. Overall, we propose a novel computational model using gene-type rules, exhibiting many characteristics of normal and pathological cortical development.