Characteristics of muscle contraction of the rectus femoris using tensiomyography by sex in healthy college students: a cross-sectional study.

Background: Tensiomyography (TMG) is a non-invasive instrument for measuring mechanical muscle contraction characteristics and measuring the maximum displacement of the muscle belly in the radial direction with respect to the muscle and the time needed to achieve this from electrical stimulation. There have been only been a reports of TMG in healthy adults. A systematic review of TMG reported a low proportion of female participants, with a small sample size. Therefore, it is unclear whether there is a difference in TMG parameters according to sex and between dominant and non-dominant feet. Furthermore, the relationship between TMG parameters and evaluations commonly used in clinical practice has not been clarified. This study aimed to clarify the characteristics of muscle contraction of the rectus femoris using TMG according to sex among healthy college students and its relationship with muscle function evaluation, such as lower limb muscle mass and muscle strength. Methods: This cross-sectional study included 91 healthy university students (18-24 years). Five tools were used: TMG, lower-limb muscle mass, rectus femoris thickness, isometric knee joint extension torque, and thigh circumference. Each parameter was compared by the generalized linear mixed model (GLMM) and Bonferroni's multiple comparison test, with sex as the without-subject factor and dominant/non-dominant foot as the within-subject factor. The correlation between the TMG parameters and other parameters was examined using Pearson's correlation coefficient for both males and females. Results: The results of the GLMM, in terms of the TMG parameters, an interaction was observed for maximum displacement (Dm); in the results of the multiple comparison test, Dm for the non-dominant leg was significantly lower in females than in males. A main effect and interaction were not observed for delay time (Td) and contraction time (Tc) by sex, dominant foot, or non-dominant foot. There was a main effect of sex on muscle function evaluation parameters (ρ ≤ 0.05). The correlation between TMG parameters for males and females and lower limb muscle mass, muscle thickness, joint torque, and thigh circumference were significantly correlated with some TMG parameters, lower limb muscle mass and muscle thickness (ρ ≤ 0.05). The absolute value of the correlation coefficient was low overall (0.20-0.38). Conclusion: In healthy college students, TMG parameters for the rectus femoris showed sex differences in Dm, and there was a weak correlation between TMG parameters and lower limb muscle mass. TMG parameter evaluation may indicate a different function compared to the traditional muscle function assessment used in clinical practice. When using the Dm of the TMG as an evaluation battery for the rectus femoris muscle, it is important to consider sex-related differences.

High-performance combinatorial optimization based on classical mechanics.

Quickly obtaining optimal solutions of combinatorial optimization problems has tremendous value but is extremely difficult. Thus, various kinds of machines specially designed for combinatorial optimization have recently been proposed and developed. Toward the realization of higher-performance machines, here, we propose an algorithm based on classical mechanics, which is obtained by modifying a previously proposed algorithm called simulated bifurcation. Our proposed algorithm allows us to achieve not only high speed by parallel computing but also high solution accuracy for problems with up to one million binary variables. Benchmarking shows that our machine based on the algorithm achieves high performance compared to recently developed machines, including a quantum annealer using a superconducting circuit, a coherent Ising machine using a laser, and digital processors based on various algorithms. Thus, high-performance combinatorial optimization is realized by massively parallel implementations of the proposed algorithm based on classical mechanics.

Allometric Scaling of Mutual Information in Complex Networks: A Conceptual Framework and Empirical Approach.

Complexity and information theory are two very valuable but distinct fields of research, yet sharing the same roots. Here, we develop a complexity framework inspired by the allometric scaling laws of living biological systems in order to evaluate the structural features of networks. This is done by aligning the fundamental building blocks of information theory (entropy and mutual information) with the core concepts in network science such as the preferential attachment and degree correlations. In doing so, we are able to articulate the meaning and significance of mutual information as a comparative analysis tool for network activity. When adapting and applying the framework to the specific context of the business ecosystem of Japanese firms, we are able to highlight the key structural differences and efficiency levels of the economic activities within each prefecture in Japan. Moreover, we propose a method to quantify the distance of an economic system to its efficient free market configuration by distinguishing and quantifying two particular types of mutual information, total and structural.

Genetic consequences of plant edaphic specialization to solfatara fields: Phylogenetic and population genetic analysis of Carex angustisquama (Cyperaceae).

Edaphic specialization is one of the main drivers of plant diversification and has multifaceted effects on population dynamics. Carex angustisquama is a sedge plant growing only on heavily acidified soil in solfatara fields, where only extremophytes can survive. Because of the lack of closely related species in similar habitats and its disjunct distribution, the species offers ideal settings to investigate the effects of adaptation to solfatara fields and of historical biogeography on the genetic consequences of plant edaphic specialization to solfatara fields. Here, genome-wide single nucleotide polymorphisms were used to reveal the phylogenetic origin of C. angustisquama, and 16 expressed sequence tag-simple sequence repeat markers were employed to infer population demography of C angustisquama. Molecular phylogenetic analysis strongly indicated that C. angustisquama formed a monophyletic clade with Carex doenitzii, a species growing on nonacidified soil in the sympatric subalpine zone. The result of population genetic analysis showed that C. angustisquama has much lower genetic diversity than the sister species, and notably, all 16 loci were completely homozygous in most individuals of C. angustisquama. Approximate Bayesian computation analysis supported the model that assumed hierarchical declines of population size through its evolutionary sequence. We propose that the edaphic specialist in solfatara fields has newly attained the adaptation to solfatara fields in the process of speciation. Furthermore, we found evidence of a drastic reduction in genetic diversity in C. angustisquama, suggesting that the repeated founder effects associated with edaphic specialization and subsequent population demography lead to the loss of genetic diversity of this extremophyte in solfatara fields.

Dynamics of essential interaction between firms on financial reports.

Companies tend to publish financial reports in order to articulate strategies, disclose key performance measurements as well as summarise the complex relationships with external stakeholders as a result of their business activities. Therefore, any major changes to business models or key relationships will be naturally reflected within these documents, albeit in an unstructured manner. In this research, we automatically scan through a large and rich database, containing over 400,000 reports of companies in Japan, in order to generate structured sets of data that capture the essential features, interactions and resulting relationships among these firms. In doing so, we generate a citation type network where we empirically observe that node creation, annihilation and link rewiring to be the dominant processes driving its structure and formation. These processes prompt the network to rapidly evolve, with over a quarter of the interactions between firms being altered within every single calendar year. In order to confirm our empirical observations and to highlight and replicate the essential dynamics of each of the three processes separately, we borrow inspiration from ecosystems and evolutionary theory. Specifically, we construct a network evolutionary model where we adapt and incorporate the concept of fitness within our numerical analysis to be a proxy real measure of a company's importance. By making use of parameters estimated from the real data, we find that our model reliably replicates degree distributions and motif formations of the citation network, and therefore reproducing both macro as well as micro, local level, structural features. This is done with the exception of the real frequency of bidirectional links, which are primarily formed as a result of an entirely separate and distinct process, namely the equity investments from one company into another.

Assembling real networks from synthetic and unstructured subsets: the corporate reporting case.

The analysis of interfirm business transaction networks provides invaluable insight into the trading dynamics and economic structure of countries. However, there is a general scarcity of data available recording real, accurate and extensive information for these types of networks. As a result, and in common with other types of network studies - such as protein interactions for instance - research tends to rely on partial and incomplete datasets, i.e. subsets, with less certain conclusions. Here, we make use of unstructured financial and corporate reporting data in Japan as the base source to construct a financial reporting network, which is then compared and contrasted to the wider real business transaction network. The comparative analysis between these two rich datasets - the proxy, partially derived network and the real, complete network at macro as well as local structural levels - provides an enhanced understanding of the non trivial relationships between partial sampled subsets and fully formed networks. Furthermore, we present an elemental agent based pruning algorithm that reconciles and preserves key structural differences between these two networks, which may serve as an embryonic generic framework of potentially wider use to network research, enabling enhanced extrapolation of conclusions from partial data or subsets.

Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems.

Combinatorial optimization problems are ubiquitous but difficult to solve. Hardware devices for these problems have recently been developed by various approaches, including quantum computers. Inspired by recently proposed quantum adiabatic optimization using a nonlinear oscillator network, we propose a new optimization algorithm simulating adiabatic evolutions of classical nonlinear Hamiltonian systems exhibiting bifurcation phenomena, which we call simulated bifurcation (SB). SB is based on adiabatic and chaotic (ergodic) evolutions of nonlinear Hamiltonian systems. SB is also suitable for parallel computing because of its simultaneous updating. Implementing SB with a field-programmable gate array, we demonstrate that the SB machine can obtain good approximate solutions of an all-to-all connected 2000-node MAX-CUT problem in 0.5 ms, which is about 10 times faster than a state-of-the-art laser-based machine called a coherent Ising machine. SB will accelerate large-scale combinatorial optimization harnessing digital computer technologies and also offer a new application of computational and mathematical physics.

Development and characterization of EST-SSR markers for Carex angustisquama (Cyperaceae), an extremophyte in solfatara fields.

PREMISE OF THE STUDY: Expressed sequence tag-simple sequence repeat (EST-SSR) markers were developed for Carex angustisquama (Cyperaceae) to investigate the evolutionary history of this plant that is endemic to solfatara fields in northern Japan. METHODS AND RESULTS: Using RNA-Seq data generated by the Illumina HiSeq 2000, 20 EST-SSR markers were developed. Polymorphisms were assessed in C. angustisquama and the closely related species C. doenitzii and C. podogyna. In C. angustisquama, many loci were monomorphic within populations; the average number of alleles ranged from one to five, and levels of expected heterozygosity ranged from 0.000 to 0.580, while all markers were polymorphic in a population of C. doenitzii. This indicates that low genetic polymorphism of C. angustisquama is likely due to the species' population dynamics, rather than to null alleles at the developed markers. CONCLUSIONS: These markers will be used to assess genetic diversity and structure and to investigate evolutionary history in future studies of C. angustisquama and related species.

Boltzmann sampling from the Ising model using quantum heating of coupled nonlinear oscillators.

A network of Kerr-nonlinear parametric oscillators without dissipation has recently been proposed for solving combinatorial optimization problems via quantum adiabatic evolution through its bifurcation point. Here we investigate the behavior of the quantum bifurcation machine (QbM) in the presence of dissipation. Our numerical study suggests that the output probability distribution of the dissipative QbM is Boltzmann-like, where the energy in the Boltzmann distribution corresponds to the cost function of the optimization problem. We explain the Boltzmann distribution by generalizing the concept of quantum heating in a single nonlinear oscillator to the case of multiple coupled nonlinear oscillators. The present result also suggests that such driven dissipative nonlinear oscillator networks can be applied to Boltzmann sampling, which is used, e.g., for Boltzmann machine learning in the field of artificial intelligence.

Erratum: CORRIGENDUM: Fault-tolerant quantum computation with a soft-decision decoder for error correction and detection by teleportation.

This corrects the article DOI: 10.1038/srep05771.

Estimating risk propagation between interacting firms on inter-firm complex network.

We derive a stochastic function of risk propagation empirically from comprehensive data of chain-reaction bankruptcy events in Japan from 2006 to 2015 over 5,000 pairs of firms. The probability is formulated by firm interaction between the pair of firms; it is proportional to the product of α-th power of the size of the first bankrupt firm and ß-th power of that of the chain-reaction bankrupt firm. We confirm that α is positive and ß is negative throughout the observing period, meaning that the probability of cascading failure is higher between a larger first bankrupt firm and smaller trading firm. We additionally introduce a numerical model simulating the whole ecosystem of firms and show that the interaction kernel is a key factor to express complexities of spreading bankruptcy risks on real ecosystems.

Appearance of Unstable Monopoly State Caused by Selective and Concentrative Mergers in Business Networks.

Recently, growth mechanism of firms in complex business networks became new targets of scientific study owing to increasing availability of high quality business firms' data. Here, we paid attention to comprehensive data of M&A events for 40 years and derived empirical laws by applying methods and concepts of aggregation dynamics of aerosol physics. It is found that the probability of merger between bigger firms is bigger than that between smaller ones, and such tendency is enhancing year by year. We introduced a numerical model simulating the whole ecosystem of firms and showed that the system is already in an unstable monopoly state in which growth of middle sized firms are suppressed.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network.

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence.

Minimizing resource overheads for fault-tolerant preparation of encoded states of the Steane code.

The seven-qubit quantum error-correcting code originally proposed by Steane is one of the best known quantum codes. The Steane code has a desirable property that most basic operations can be performed easily in a fault-tolerant manner. A major obstacle to fault-tolerant quantum computation with the Steane code is fault-tolerant preparation of encoded states, which requires large computational resources. Here we propose efficient state preparation methods for zero and magic states encoded with the Steane code, where the zero state is one of the computational basis states and the magic state allows us to achieve universality in fault-tolerant quantum computation. The methods minimize resource overheads for the fault-tolerant state preparation, and therefore reduce necessary resources for quantum computation with the Steane code. Thus, the present results will open a new possibility for efficient fault-tolerant quantum computation.

Cavity-enhanced spectroscopy of a rare-earth-ion-doped crystal: observation of a power law for inhomogeneous broadening: erratum.

We report an erratum regarding the polarization of the probe in the experiment reported in our paper [Opt. Express21, 24332-24343 (2013)]. Although we wrote in the paper that the polarization of the probe is set to be parallel to the D2 axis of YSO crystal, we found that the polarization was parallel to the D1 axis of YSO crystal. However, this fact does not affect the two main results of the work: observation of very small absorption and the power law for the inhomogeneous broadening.

Step-by-step magic state encoding for efficient fault-tolerant quantum computation.

Quantum error correction allows one to make quantum computers fault-tolerant against unavoidable errors due to decoherence and imperfect physical gate operations. However, the fault-tolerant quantum computation requires impractically large computational resources for useful applications. This is a current major obstacle to the realization of a quantum computer. In particular, magic state distillation, which is a standard approach to universality, consumes the most resources in fault-tolerant quantum computation. For the resource problem, here we propose step-by-step magic state encoding for concatenated quantum codes, where magic states are encoded step by step from the physical level to the logical one. To manage errors during the encoding, we carefully use error detection. Since the sizes of intermediate codes are small, it is expected that the resource overheads will become lower than previous approaches based on the distillation at the logical level. Our simulation results suggest that the resource requirements for a logical magic state will become comparable to those for a single logical controlled-NOT gate. Thus, the present method opens a new possibility for efficient fault-tolerant quantum computation.

Cavity-enhanced spectroscopy of a rare-earth-ion-doped crystal: observation of a power law for inhomogeneous broadening.

We experimentally demonstrate cavity-enhanced spectroscopy of a rare-earth-ion-doped crystal (Pr³âº:Y2SiO5). We succeeded in observing very small absorption due to the ions appropriately prepared by optical pumping, which corresponds to the single-pass absorption of 4 × 10-6. We also observed a power law for the inhomogeneous broadening of optical transitions of ions in the crystal. Compared with a theoretical model, the result of the power law indicates that the dominant origin of the inhomogeneous broadening may be some charged defects.

Fault-tolerant quantum computation with a soft-decision decoder for error correction and detection by teleportation.

Fault-tolerant quantum computation with quantum error-correcting codes has been considerably developed over the past decade. However, there are still difficult issues, particularly on the resource requirement. For further improvement of fault-tolerant quantum computation, here we propose a soft-decision decoder for quantum error correction and detection by teleportation. This decoder can achieve almost optimal performance for the depolarizing channel. Applying this decoder to Knill's C4/C6 scheme for fault-tolerant quantum computation, which is one of the best schemes so far and relies heavily on error correction and detection by teleportation, we dramatically improve its performance. This leads to substantial reduction of resources.