The Reasoning Engine: A Satisfiability Modulo Theories-Based Framework for Reasoning About Discrete Biological Models.

The traditional models of distributed computing systems employ the mathematical formalisms of discrete event dynamical systems along with Petri Nets. However, such models are complex to analyze and computationally expensive. Interestingly, the evolving distributed computing systems closely resemble the discrete dynamical systems. This paper constructs and analyzes the model of distributed computing systems by applying mathematical formalisms of the discrete dynamical systems. The proposed model embeds the partial ordering of states under happened-before relation in the set of globally observable states. The stability of the proposed model is analyzed using the first order linear approximation.

Practical pursuit in stem cell biology: Innovation, translation, and incomplete theorization

Consider a discrete dynamical system given by a square matrix $M \in \mathbb{Q}^{d \times d}$ and a starting point $s \in \mathbb{Q}^d$. The orbit of such a system is the infinite trajectory $\langle s, Ms, M^2s, \ldots\rangle$. Given a collection $T_1, T_2, \ldots, T_m \subseteq \mathbb{R}^d$ of semialgebraic sets, we can associate with each $T_i$ an atomic proposition $P_i$ which evaluates to true at time $n$ if, and only if, $M^ns \in T_i$. This gives rise to the LTL Model-Checking Problem for discrete linear dynamical systems: given such a system $(M,s)$ and an LTL formula over such atomic propositions, determine whether the orbit satisfies the formula. The main contribution of the present paper is to show that the LTL Model-Checking Problem for discrete linear dynamical systems is decidable in dimension 3 or less.

With the rapid development of computer science, there are more and more kinds of discrete dynamic systems. Computer integrated system CIMS, network communication database administrator system, and human behavior analysis system are all discrete dynamic systems. At present, many researchers have studied by adding human behavior data to discrete dynamic systems. This paper aims to study the behavior data of English learners by using the discrete dynamic modeling technology of complex systems and the discrete dynamic system modeling method of Petri nets. By adding the behavior data of learners to the discrete dynamic system of fuzzy Petri nets, the system is diagnosed and optimized. The experimental results show that the complex discrete dynamic system in this paper has achieved good experimental results according to the performance indicators selected in theory. Based on the combination of the above technologies and systems, the fuzzy Petri net discrete dynamic system studied in this paper improves the processing speed of English learners' behavior data.

This textbook provides a broad introduction to continuous and discrete dynamical systems. With its hands-on approach, the text leads the reader from basic theory to recently published research material in nonlinear ordinary differential equations, nonlinear optics, multifractals, neural networks, and binary oscillator computing. Dynamical Systems with Applications Using Python takes advantage of Python’s extensive visualization, simulation, and algorithmic tools to study those topics in nonlinear dynamical systems through numerical algorithms and generated diagrams. After a tutorial introduction to Python, the first part of the book deals with continuous systems using differential equations, including both ordinary and delay differential equations. The second part of the book deals with discrete dynamical systems and progresses to the study of both continuous and discrete systems in contexts like chaos control and synchronization, neural networks, and binary oscillator computing. These later sections are useful reference material for undergraduate student projects. The book is rounded off with example coursework to challenge students’ programming abilities and Python-based exam questions. This book will appeal to advanced undergraduate and graduate students, applied mathematicians, engineers, and researchers in a range of disciplines, such as biology, chemistry, computing, economics, and physics. Since it provides a survey of dynamical systems, a familiarity with linear algebra, real and complex analysis, calculus, and ordinary differential equations is necessary, and knowledge of a programming language like C or Java is beneficial but not essential.

We describe the destabilizing (in the sense of a decrease in the reserve of mean-square asymptotic stability) effect of random parametric perturbations of the white-noise type in quasilinear continuous and discrete dynamical systems (Lur’e-Postnikov systems of automatic control with nonlinear feedback). We use stochastic Lyapunov functions in the form of linear combinations of the types “a quadratic form of phase coordinates plus the integral of a nonlinearity” (continuous systems) and “a quadratic form of phase coordinates plus the integral sum for a nonlinearity” (discrete systems) and the matrix algebraic Sylvester equations associated with stochastic Lyapunov functions of this form.

At present, most cases of unresectable cancer cannot be cured. Genetic mutations, EMT, and cancer stem cells are three major issues linked to poor prognosis in such cases, all connected by inter- and intra-tumor heterogeneity. Issues on inter-/intra-tumor heterogeneity of genetic mutation could be resolved with recent and future technologies of deep sequencers, whereas, regarding such issues as the "same genome, different epigenome/phenotype", we expect to solve many of these problems in the future through further research in stem cell biology. We herein review and discuss the three major issues in the biology of cancers, especially from the standpoint of stem cell biology.

Multiple unique aspects of liver biology make this organ an excellent paradigm for novel cell and gene therapy applications. In recent years, insights were obtained into how transplanted cells engraft and proliferate in the liver, including in the context of pre-existing disease. Also, a variety of animal models were studied to establish the basis of cell and gene therapy applications in specific disorders. Through ongoing research activity, additional mechanisms in liver repopulation have been uncovered, where manipulation of specific cell compartments and cellular processes,e.g., those aimed at extracellular matrix component receptors or soluble signals in transplanted and native cells can be exploited for enhancing cell engraftment and proliferation. Such studies demonstrate the possibility of applying biotechnology and/or bioengineering principles to organ replacement aimed at cell and gene therapy. Joining of these disciplines with research in stem cell biology, particularly in efforts concerning targeting of transplanted stem cells to given organs with achievement of lineage-specific cell differentiation and function, will be particularly important for future cell and gene therapy applications. This review offers an overview of relevant mechanisms in liver repopulation.

Although recent studies have suggested the feasibility of integrating workflow and rule technology in a Clinical Decision Support System (CDSS), their implementation has not been verified yet. This paper proposes a knowledge engine which integrates workflow and rule engine as a tool for interpretation and execution of computer interpretable clinical guidelines. The objective of this paper is to validate its feasibility in two perspectives: clinical knowledge coverage and execution performance. The two open source engines which were selected and integrated were chosen due to their reliability and consistency. Implementation of workflow and rule engine integration has shown that the integrated knowledge engine (uBrain) is an effective CDSS for the execution of clinical guidelines.

Hybrid system is a dynamic system that involves continuous, discrete behaviors, and the interactions between continuous physical components and discrete controllers. In this paper a hybrid modeling language (called HML) for hybrid systems is extended with templates to achieve code reuse. For the formal analysis of the corresponding hybrid system models in this modeling language, these models are translated into SMT (satisfiability modulo theories) formulas as the input to an SMT solver dReal which retains the capability of bounded reachability analysis for non-linear hybrid systems. Moreover, dReal can produce data for potential traces of hybrid systems, thus it can be employed to simulate on hybrid systems. In this paper the simulation and reachability analysis are integrated in a prototype tool (open source). We present a case study for an inverted pendulum with PID (Proportional-Integral-Derivative) controllers and a rod reactor system for temperature control, both are verified to demonstrate the efficiency of the prototype tool. We conclude that, this modeling language is capable of modeling and verification of hybrid systems based on simulation and bounded reachability analysis.

Advances in cell therapy for renal failure

Polymeric microcavities functionalized with extracellular matrix components were used as an experimental in vitro model to investigate principles of hematopoietic stem and progenitor cell (HSPC) fate control. Using human CD133+ HSPC we could demonstrate distinct differences in HSPC cycling and differentiation dependence on the adhesion ligand specificity (i.e., heparin, collagen I) and cytokine levels. The presented microcavity platform provides a powerful in vitro approach to explore the role of exogenous cues in HSPC fate decisions and can therefore be instrumental to progress in stem cell biology and translational research toward new therapies.

Network translation gateways can provide seamless interoperability among different airborne, ground and maritime domains. Effective interconnection between waveforms and protocols through the gateways requires manual intensive development and specialized protocol expertise. Therefore, enabling building versatile gateways that can effectively translate those protocols across different network domains is of utmost importance to improve system interoperability. High-level domain specific languages have been utilized to support agnostic protocol interoperability. However, protocol-specific knowledge specification, the core of protocol translation, is still left to protocol experts with manual coding without advanced tools in support of simplification, guidance or verification. Such a manual and unsupervised method of generating translation logic is complex, time-consuming and error-prone. In order to overcome these problems with much more productive gateway development, we present a novel, visual protocol-agnostic translation toolkit in this paper. This toolkit offers three advanced features: 1) simple, intuitive visualized specification of protocol-specific knowledge, 2) graph-based translation logic verification, and 3) automatic gateway generation. The first two features have not been addressed in currently available protocol translation solutions.

Network simulation plays a crucial role in the field of network research, education, and industry. However, before conducting a simulation on traditional network simulators, operators need to develop a simulative behavioral model, which requires intimate knowledge of the simulator implementation. Besides, the behavioral model cannot be migrated directly into real-world devices due to its tight coupling with the simulator platform, resulting in redundant and error-prone codes rewriting. Recently, P4, a high-level domain specific language (DSL), has attracted great attention from both academia and industry for its advantages of enabling operators to define behaviors of the programmable data plane. Inspired by the idea of DSL, we present NS4, a P4-driven network simulator supporting simulation of P4-enabled networks to address the problems existing in traditional simulators. Taking advantage of P4, NS4 simplifies the development of a behavioral model and bridges the gap between simulation and deployment. Furthermore, to the best of our knowledge, NS4 is the first research effort to enable simulation of a P4-enabled network, providing a useful tool for P4 research and development. In this paper, we designed and implemented NS4, consisting of data plane models integrated with ns-3, the state-of-the-art network simulator, and control plane models to interact with the P4 pipeline. Then we evaluated its effectiveness and efficiency by simulating several representative P4 programs. Results show that NS4 can simulate large-scale P4-enabled networks at a low cost.

Editorial introductions