Understanding the role of network for epidemic spread is a major concern in the study of complex network and disease spread. Localization of Principal EigenVector (PEV) of the network’s adjacency matrix has been explored in recent past by many researchers. Most of the previous works suggest the localization of PEV through maximization of inverse participation ratio (IPR). The network with maximum IPR

Synesthesia is a neurological phenomenon in which stimulation of one sensory or cognitive pathway leads to automatic, involuntary experiences in a second sensory or cognitive pathway. Many synesthetes used their capabilities as inspiration for their works. Drawing on this phenomenon, this paper presents a model able to create chord progressions using colors as the synesthetic input. In particular,

Semantic textual similarity methods are becoming increasingly crucial in text mining research areas such as text retrieval and summarization. Existing methods of text similarity have often been computed by their shallow or syntactic representation rather than considering their semantic content and meanings. This paper focuses mainly on computing the similarity between sentences without a supervised

The article “Special Issue on Molecular Robotics”, written by Satoshi Murata was originally published electronically on the publisher's internet portal (currently SpringerLink) on 18th May 2020 with open access.

Chemical reactions in small-volume reactors such as biological cells are highly variable due to the stochastic collision events of the small number of molecules. To analyze and design these stochastic biomolecular reactions, computational tools have been developed based on rigorous mathematical foundations. This paper reviews fundamental theory and computational tools for the modeling, analysis, and

In this tutorial, recent development of pattern generation algorithms based on DNA computing will be overviewed. Natural pattern generation, especially in biological organisms, are often driven by spatio-temporal chemical reactions. Various reaction–diffusion systems have been proposed to generate artificial patterns out of DNA sequences. To program DNA reaction–diffusion systems, in addition to the

This paper investigates the control of multi-agent systems inspired by chemotaxis of microorganisms. Chemotaxis is a biological phenomenon wherein organisms in an environment are attracted to food but move away from toxins. The problem addressed here is a formation control problem, i.e., a design problem of distributed controllers wherein the relative positions of agents become the desired positions

Distributed computation consists of local computations and their interactions. We consider a molecular robot system as a distributed system composed of mobile computing entities with very weak capabilities, i.e., computing entities are anonymous (indistinguishable), oblivious (memory-less), and uniform (following a common local computation rule). The key property of such a distributed system is self-organization

Owing to the absolute significance of the business process management, companies have become thoroughly oriented toward a good modeling of the business processes. Although the business process modeling is a substantial part in workflow automation, business process designers often misunderstand domain concepts or relationships due to their lack of precise business knowledge. Such a semantic equivocation

Language designers usually need to implement parsers and printers. Despite being two closely related programs, in practice they are often designed separately, and then need to be revised and kept consistent as the language evolves. It will be more convenient if the parser and printer can be unified and developed in a single program, with their consistency guaranteed automatically. Furthermore, in certain

The editorial board would like to introduce a new area editor, Shinnosuke Seki, who is establishing a new area for the journal: “Theory of Natural Computing”. He welcomes theoretical studies on internationally accepted models of computation, including cellular automata, chemical reaction networks, Lindenmayer (L-) systems, Nubot models, Oritatami systems, P systems (membrane computing), reaction systems

Practical design of the XOR gate is an important milestone in the field of DNA computing. In this study, we aim to develop an enzyme-free XOR gate driven by a toehold-mediated strand displacement mechanism possessing the true detection property. The advantages of our design are as follows: dual-rail logic is not required, the explicit use of the NOT gate is avoided, the circuit structure is simple

This tutorial paper focuses on the design, simulation, and optimization of polymerase–exonuclease–nickase (PEN) toolbox systems. The PEN toolbox is a molecular programming framework that relies on the interaction between DNA molecules and enzymes to produce highly non-linear dynamic systems. The flip side of that expressivity is that the design of systems relies heavily on trial-and-error, thus calling

In this paper, we propose Knowledge Graph (KG), an articulated underlying semantic structure, as a semantic bridge between humans, systems, and scientific knowledge. To illustrate our proposal, we focus on KG-based intelligent survey systems. In state-of-the-art systems, information is hard-coded or implicit, making it hard for researchers to reuse, customise, link, or transmit structured knowledge

Although several RDF knowledge bases are available through the Linked Open Data (LOD) initiative, the ontology schema of such linked datasets is not very rich. In particular, they lack object properties. The problem of finding new object properties between any two given classes has not been investigated in detail in the context of Linked Data. In the first part of this paper, we present DARO (Detecting

To provide robots with the flexibility they need to cope with various environments, motion generation techniques using deep learning have been proposed. Generalization in deep learning is expected to enable flexible processing in unknown situations and flexible motion generation. Motion generation models have been proposed to realize specific robot tasks, and their operation successes in unknown situations

This paper describes a framework for the development of an integrative cognitive system based on probabilistic generative models (PGMs) called Neuro-SERKET. Neuro-SERKET is an extension of SERKET, which can compose elemental PGMs developed in a distributed manner and provide a scheme that allows the composed PGMs to learn throughout the system in an unsupervised way. In addition to the head-to-tail

Recently, attention mechanisms have significantly boosted the performance of natural language processing using deep learning. An attention mechanism can select the information to be used, such as by conducting a dictionary lookup; this information is then used, for example, to select the next utterance word in a sentence. In neuroscience, the basis of the function of sequentially selecting words is

The technologies for collecting and analyzing data are developing significantly, enabling us to gain new knowledge from various types of data. Recently, the considerably increasing expectation for cross-domain data exchange and cooperation has attracted attention from data markets. However, as we lack data-utilization knowledge, an accurate evaluation of data is difficult; a non-price indicator for

Language is a complex evolving system and it is not a trivial task to model the dynamics of processes occurring during its evolution. Therefore, modeling language evolution has attracted the interest of several researchers giving rise to a lot of models in the literature of the last millennium. This work reviews the literature devoted to computationally represent the evolution of human language through

High-utility itemset mining (HUIM) is an emerging data mining topic. It aims to find the high-utility itemsets by considering both the internal (i.e., quantity) and external (i.e., profit) utilities of items. High-average-utility itemset mining (HAUIM) is an extension of the HUIM, which provides a more fair measurement named average-utility, by taking into account the length of itemsets in addition

In recent years, there has been an increasing interest in numerical semantic labeling, in which the meaning of an unknown numerical column is assigned by the label of the most relevant columns in predefined knowledge bases. Previous methods used the p value of a statistical hypothesis test to estimate the relevance and thus strongly depend on the distribution and data domain. In other words, they are

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current

A method of representing algebraic age word problems for automated solving has been proposed. Schemas pertinent to the domain have been represented as logical predicates and functions and used as an intermediate representation. Though data-driven methods have dominated the paradigm for solving word problems recently, we demonstrate that representing these word problems formally has advantages. We illustrate

We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechanism along with logical ordering and physical ordering of nodes’ keys. We initially study the throughput

One of the major tasks involved in the development of a knowledge-based problem solver is domain knowledge representation and reasoning. In this paper, we address this task for a knowledge-based kinematics word problem solver that solves problems from the domain of kinematics automatically, where solving each problem involves identifying the value of a specific unknown quantity referred to, within

Ontology-based visual query formulation is a viable alternative to textual query editors in the Semantic Web domain for extracting data from structured data sources in terms of the skills and knowledge required. A visual query system is at any moment responsible for providing the user with query extension suggestions; however, suggestions leading to empty results are often not useful. To this end,

The evolutionary behavior of temporal networks has gained the attention of researchers with its ubiquitous applications in a variety of real-world scenarios. Learning evolutionary behavior of networks is directly related to link prediction problem, as the addition or removal of new links or edges over time leads to the network evolution. With the rise of large-scale temporal networks such as social

Gaining knowledge and engineering of biological systems require comprehensive models of cellular physiology with 100% predictability. The whole-cell models direct experiments in molecular biological science and empower simulation and computer-aided design in synthetic biology. Whole-cell modeling and simulation help in personalized medical treatment building a biological system through cell interactions