Effects of back extensor strengthening exercises on postural alignment,physical function and performance,self-efficacy,and quality of life in Japanese community-dwelling older adults: A controlled clinical trial

Objective: To examine the changes in postural alignment and kyphosis-correlated factors after 6 months of back extensor strengthening exercise in a group of community-dwelling older adults aged ≥65 years. Methods: We quasi-randomized 29 subjects into an intervention group treated with a back extensor strengthening program and a control group treated with a full-body exercise program. These groups completed 20-30 minutes of exercise directed by a physical therapist one or more times per week and were instructed to exercise at home as well. The participants were assessed prior to and after the intervention using the following criteria: postural alignment of “usual” and “best” posture, physical function, physical performance, self-efficacy, and quality of life. The differences between two factors (group and period) were compared for each of the measurement variables. Results: Subjects who adequately completed the exercises were analyzed. A reduced knee flexion angle was noted in the “best” posture of both groups, as were improved physical function and performance with the exception of one-leg standing time. Verifying the effect size in the post-hoc analysis, the body parts that showed changes to postural alignment after the intervention differed between groups. Conclusions: Back extensor strengthening exercises improved physical function and performance, but did not improve spinal alignment. The changes due to these interventions were not significantly different from changes observed in the full-body exercise group. However, post-hoc analysis revealed that the effect size of posture change was different, possible indicating that the two groups experienced different changes in the postural alignment.     

Associations between Neurocardiovascular Signal Entropy and Physical Frailty

In this cross-sectional study, the relationship between noninvasively measured neurocardiovascular signal entropy and physical frailty was explored in a sample of community-dwelling older adults from The Irish Longitudinal Study on Ageing (TILDA). The hypothesis under investigation was that dysfunction in the neurovascular and cardiovascular systems, as quantified by short-length signal complexity during a lying-to-stand test (active stand), could provide a marker for frailty. Frailty status (i.e., “non-frail”, “pre-frail”, and “frail”) was based on Fried’s criteria (i.e., exhaustion, unexplained weight loss, weakness, slowness, and low physical activity). Approximate entropy (ApEn) and sample entropy (SampEn) were calculated during resting (lying down), active standing, and recovery phases. There was continuously measured blood pressure/heart rate data from 2645 individuals (53.0% female) and frontal lobe tissue oxygenation data from 2225 participants (52.3% female); both samples had a mean (SD) age of 64.3 (7.7) years. Results revealed statistically significant associations between neurocardiovascular signal entropy and frailty status. Entropy differences between non-frail and pre-frail/frail were greater during resting state compared with standing and recovery phases. Compared with ApEn, SampEn seemed to have better discriminating power between non-frail and pre-frail/frail individuals. The quantification of entropy in short length neurocardiovascular signals could provide a clinically useful marker of the multiple physiological dysregulations that underlie physical frailty.     

Wigner’s Friend Scenarios and the Internal Consistency of Standard Quantum Mechanics

Wigner’s friend scenarios involve an Observer, or Observers, measuring a Friend, or Friends, who themselves make quantum measurements. In recent discussions, it has been suggested that quantum mechanics may not always be able to provide a consistent account of a situation involving two Observers and two Friends. We investigate this problem by invoking the basic rules of quantum mechanics as outlined by Feynman in the well-known “Feynman Lectures on Physics”. We show here that these “Feynman rules” constrain the a priori assumptions which can be made in generalised Wigner’s friend scenarios, because the existence of the probabilities of interest ultimately depends on the availability of physical evidence (material records) of the system’s past. With these constraints obeyed, a non-ambiguous and consistent account of all measurement outcomes is obtained for all agents, taking part in various Wigner’s Friend scenarios.     

Coupled Criticality Analysis of Inflation and Unemployment

In this paper, we focus on the critical periods in the economy that are characterized by unusual and large fluctuations in macroeconomic indicators, like those measuring inflation and unemployment. We analyze U.S. data for 70 years from 1948 until 2018. To capture their fluctuation essence, we concentrate on the non-Gaussianity of their distributions. We investigate how the non-Gaussianity of these variables affects the coupling structure of them. We distinguish “regular” from “rare” events, in calculating the correlation coefficient, emphasizing that both cases might lead to a different response of the economy. Through the “multifractal random wall” model, one can see that the non-Gaussianity depends on time scales. The non-Gaussianity of unemployment is noticeable only for periods shorter than one year; for longer periods, the fluctuation distribution tends to a Gaussian behavior. In contrast, the non-Gaussianities of inflation fluctuations persist for all time scales. We observe through the “bivariate multifractal random walk” that despite the inflation features, the non-Gaussianity of the coupled structure is finite for scales less than one year, drops for periods larger than one year, and becomes small for scales greater than two years. This means that the footprint of the monetary policies intentionally influencing the inflation and unemployment couple is observed only for time horizons smaller than two years. Finally, to improve some understanding of the effect of rare events, we calculate high moments of the variables’ increments for various q orders and various time scales. The results show that coupling with high moments sharply increases during crises.     

Association Between Social Network and Physical Function in Community-Dwelling Older Adults in Japan

Objective: A poor social network and the decline of physical function are known to be critical risk factors for functional decline in older adults. The aim of this study was to investigate the relationships between social network and physical function in Japanese community-dwelling older adults. Methods: Participants were 339 adults aged 65 years or older (mean age : 73.0 years, women :70.2%), living independently in their communities. A self-reported questionnaire was used to assess social network on two different scales―the 6-item Lubben Social Network Scale (6LSNS) and frequency of contact with other people. Handgrip strength, knee extension strength, gait speed, Timed Up and Go Test (TUG) results, and 5-repetition chair stand test (CST) scores were used to determine physical function. A multiple regression analysis that adjusted for confounding factors was used to analyze the relationship between the social network scales and each physical function test. Results: According to the results of a multiple regression analysis, a high 6LSNS score was significantly associated with greater handgrip strength (B = 0.63, p = 0.03), faster CST (B = −0.23, p = 0.01), and faster TUG (B = −0.12, p = 0.03), and high frequency of contact was significantly associated with greater handgrip strength (B = 1.08, p = 0.01). Conclusions: Social network was associated with muscle strength and physical performance. Consequently, older adults with poor social networks require an assessment of physical function, since their physical functions have possibly deteriorated.     

Conditional Action and Imperfect Erasure of Qubits

We consider state changes in quantum theory due to “conditional action” and relate these to the discussion of entropy decrease due to interventions of “intelligent beings” and the principles of Szilard and Landauer/Bennett. The mathematical theory of conditional actions is a special case of the theory of “instruments”, which describes changes of state due to general measurements and will therefore be briefly outlined in the present paper. As a detailed example, we consider the imperfect erasure of a qubit that can also be viewed as a conditional action and will be realized by the coupling of a spin to another small spin system in its ground state.     

The Systematic Bias of Entropy Calculation in the Multi-Scale Entropy Algorithm

Entropy indicates irregularity or randomness of a dynamic system. Over the decades, entropy calculated at different scales of the system through subsampling or coarse graining has been used as a surrogate measure of system complexity. One popular multi-scale entropy analysis is the multi-scale sample entropy (MSE), which calculates entropy through the sample entropy (SampEn) formula at each time scale. SampEn is defined by the “logarithmic likelihood” that a small section (within a window of a length m) of the data “matches” with other sections will still “match” the others if the section window length increases by one. “Match” is defined by a threshold of r times standard deviation of the entire time series. A problem of current MSE algorithm is that SampEn calculations at different scales are based on the same matching threshold defined by the original time series but data standard deviation actually changes with the subsampling scales. Using a fixed threshold will automatically introduce systematic bias to the calculation results. The purpose of this paper is to mathematically present this systematic bias and to provide methods for correcting it. Our work will help the large MSE user community avoiding introducing the bias to their multi-scale SampEn calculation results.     

A Narrative Review of Alternate Gait Training Using Knee-ankle-foot Orthosis in Stroke Patients with Severe Hemiparesis

Impairments resulting from stroke lead to persistent difficulties with walking. Subsequently, an improved walking ability is one of the highest priorities for people living with stroke. The degree to which gait can be restored after a stroke is related to both the initial impairment in walking ability and the severity of paresis of the lower extremities. However, there are some patients with severe motor paralysis and a markedly disrupted corticospinal tract who regain their gait function. Recently, several case reports have described the recovery of gait function in stroke patients with severe hemiplegia by providing alternate gait training. Multiple studies have demonstrated that gait training can induce “locomotor-like” coordinated muscle activity of paralyzed lower limbs in people with spinal cord injury. In the present review, we discuss the neural mechanisms of gait, and then we review case reports on the restoration of gait function in stroke patients with severe hemiplegia.     

Integrated Information in the Spiking–Bursting Stochastic Model

Integrated information has been recently suggested as a possible measure to identify a necessary condition for a system to display conscious features. Recently, we have shown that astrocytes contribute to the generation of integrated information through the complex behavior of neuron–astrocyte networks. Still, it remained unclear which underlying mechanisms governing the complex behavior of a neuron–astrocyte network are essential to generating positive integrated information. This study presents an analytic consideration of this question based on exact and asymptotic expressions for integrated information in terms of exactly known probability distributions for a reduced mathematical model (discrete-time, discrete-state stochastic model) reflecting the main features of the “spiking–bursting” dynamics of a neuron–astrocyte network. The analysis was performed in terms of the empirical “whole minus sum” version of integrated information in comparison to the “decoder based” version. The “whole minus sum” information may change sign, and an interpretation of this transition in terms of “net synergy” is available in the literature. This motivated our particular interest in the sign of the “whole minus sum” information in our analytical considerations. The behaviors of the “whole minus sum” and “decoder based” information measures are found to bear a lot of similarity—they have mutual asymptotic convergence as time-uncorrelated activity increases, and the sign transition of the “whole minus sum” information is associated with a rapid growth in the “decoder based” information. The study aims at creating a theoretical framework for using the spiking–bursting model as an analytically tractable reference point for applying integrated information concepts to systems exhibiting similar bursting behavior. The model can also be of interest as a new discrete-state test bench for different formulations of integrated information.     

Recent Advances in the Neural Control of Movements: Lessons for Functional Recovery

We review the current views on the control and coordination of movements following the traditions set by Nikolai Bernstein. In particular, we focus on the theory of neural control of effectors - from motor units to individual muscles, to joints, limbs, and to the whole body - with spatial referent coordinates organized into a hierarchy with multiple few-to-many mappings. Further, we discuss synergies ensuring stability of natural human movements within the uncontrolled manifold hypothesis. Synergies are organized within the neural control hierarchy based on the principle of motor abundance. Movement disorders are discussed as consequences of an inability to use the whole range of changes in referent coordinates (as in spasticity) and an inability to ensure controlled stability of salient variables as reflected in indices of multi-element synergies and their adjustments in preparation to actions (as in brain disorders, including Parkinson''s disease, multiple-system atrophy, and stroke). At the end of the review, we discuss possible implications of this theoretical approach to peripheral disorders and their rehabilitations using, as an example, osteoarthritis. In particular, “joint stiffening” is viewed as a maladaptive strategy, which can compromise stability of salient variables during walking.     

A Study on Consumers’ Visual Image Evaluation of Wrist Wearables

This study aimed to investigate consumers’ visual image evaluation of wrist wearables based on Kansei engineering. A total of 8 representative samples were screened from 99 samples using the multidimensional scaling (MDS) method. Five groups of adjectives were identified to allow participants to express their visual impressions of wrist wearable devices through a questionnaire survey and factor analysis. The evaluation of eight samples using the five groups of adjectives was analyzed utilizing the triangle fuzzy theory. The results showed a relatively different evaluation of the eight samples in the groups of “fashionable and individual” and “rational and decent”, but little distinction in the groups of “practical and durable”, “modern and smart” and “convenient and multiple”. Furthermore, wrist wearables with a shape close to a traditional watch dial (round), with a bezel and mechanical buttons (moderate complexity) and asymmetric forms received a higher evaluation. The acceptance of square- and elliptical-shaped wrist wearables was relatively low. Among the square- and rectangular-shaped wrist wearables, the greater the curvature of the chamfer, the higher the acceptance. Apparent contrast between the color of the screen and the casing had good acceptance. The influence of display size on consumer evaluations was relatively small. Similar results were obtained in the evaluation of preferences and willingness to purchase. The results of this study objectively and effectively reflect consumers’ evaluation and potential demand for the visual images of wrist wearables and provide a reference for designers and industry professionals.     

Introduction and Analysis of a Method for the Investigation of QCD-like Tree Data

The properties of decays that take place during jet formation cannot be easily deduced from the final distribution of particles in a detector. In this work, we first simulate a system of particles with well-defined masses, decay channels, and decay probabilities. This presents the “true system” for which we want to reproduce the decay probability distributions. Assuming we only have the data that this system produces in the detector, we decided to employ an iterative method which uses a neural network as a classifier between events produced in the detector by the “true system” and some arbitrary “test system”. In the end, we compare the distributions obtained with the iterative method to the “true” distributions.     

Water demand-supply analysis in a large spatial area based on the processes of evapotranspiration and runoff

To estimate the amount of evapotranspiration in a river basin, the “short period water balance method” was formulated. Then, by introducing the “complementary relationship method,” the amount of evapotranspiration was estimated seasonally, and with reasonable accuracy, for both small and large areas. Moreover, to accurately estimate river discharge in the low water season, the “weighted statistical unit hydrograph method” was proposed and a procedure for the calculation of the unit hydrograph was developed. Also, a new model, based on the “equivalent roughness method,” was successfully developed for the estimation of flood runoff from newly reclaimed farmlands. Based on the results of this research, a “composite reservoir model” was formulated to analyze the repeated use of irrigation water in large spatial areas. The application of this model to a number of watershed areas provided useful information with regard to the realities of water demand-supply systems in watersheds predominately dedicated to paddy fields, in Japan.     

From Quantum Probabilities to Quantum Amplitudes

The task of reconstructing the system’s state from the measurements results, known as the Pauli problem, usually requires repetition of two successive steps. Preparation in an initial state to be determined is followed by an accurate measurement of one of the several chosen operators in order to provide the necessary “Pauli data”. We consider a similar yet more general problem of recovering Feynman’s transition (path) amplitudes from the results of at least three consecutive measurements. The three-step histories of a pre- and post-selected quantum system are subjected to a type of interference not available to their two-step counterparts. We show that this interference can be exploited, and if the intermediate measurement is “fuzzy”, the path amplitudes can be successfully recovered. The simplest case of a two-level system is analysed in detail. The “weak measurement” limit and the usefulness of the path amplitudes are also discussed.     

Mammalian-specific genomic functions: Newly acquired traits generated by genomic imprinting and LTR retrotransposon-derived genes in mammals

Mammals, including human beings, have evolved a unique viviparous reproductive system and a highly developed central nervous system. How did these unique characteristics emerge in mammalian evolution, and what kinds of changes did occur in the mammalian genomes as evolution proceeded? A key conceptual term in approaching these issues is “mammalian-specific genomic functions”, a concept covering both mammalian-specific epigenetics and genetics. Genomic imprinting and LTR retrotransposon-derived genes are reviewed as the representative, mammalian-specific genomic functions that are essential not only for the current mammalian developmental system, but also mammalian evolution itself. First, the essential roles of genomic imprinting in mammalian development, especially related to viviparous reproduction via placental function, as well as the emergence of genomic imprinting in mammalian evolution, are discussed. Second, we introduce the novel concept of “mammalian-specific traits generated by mammalian-specific genes from LTR retrotransposons”, based on the finding that LTR retrotransposons served as a critical driving force in the mammalian evolution via generating mammalian-specific genes.     

Plotting the Words of Econophysics

Text mining is applied to 510 articles on econophysics to reconstruct the lexical evolution of the discipline from 1999 to 2020. The analysis of the relative frequency of the words used in the articles and their “visualization” allow us to draw some conclusions about the evolution of the discipline. The traditional areas of research, financial markets and distribution of wealth, remain central, but they are flanked by other strands of research—production, currencies, networks—which broaden the discipline by pushing towards a dialectical application of traditional concepts and tools drawn from statistical physics.     

A New Family of Continuous Probability Distributions

In this paper, a new parametric compound G family of continuous probability distributions called the Poisson generalized exponential G (PGEG) family is derived and studied. Relevant mathematical properties are derived. Some new bivariate G families using the theorems of “Farlie-Gumbel-Morgenstern copula”, “the modified Farlie-Gumbel-Morgenstern copula”, “the Clayton copula”, and “the Renyi’s entropy copula” are presented. Many special members are derived, and a special attention is devoted to the exponential and the one parameter Pareto type II model. The maximum likelihood method is used to estimate the model parameters. A graphical simulation is performed to assess the finite sample behavior of the estimators of the maximum likelihood method. Two real-life data applications are proposed to illustrate the importance of the new family.     

Neural Adaptive Funnel Dynamic Surface Control with Disturbance-Observer for the PMSM with Time Delays

This paper suggests an adaptive funnel dynamic surface control method with a disturbance observer for the permanent magnet synchronous motor with time delays. An improved prescribed performance function is integrated with a modified funnel variable at the beginning of the controller design to coordinate the permanent magnet synchronous motor with the output constrained into an unconstrained one, which has a faster convergence rate than ordinary barrier Lyapunov functions. Then, the specific controller is devised by the dynamic surface control technique with first-order filters to the unconstrained system. Therein, a disturbance-observer and the radial basis function neural networks are introduced to estimate unmatched disturbances and multiple unknown nonlinearities, respectively. Several Lyapunov-Krasovskii functionals are constructed to make up for time delays, enhancing control performance. The first-order filters are implemented to overcome the “complexity explosion” caused by general backstepping methods. Additionally, the boundedness and binding ranges of all the signals are ensured through the detailed stability analysis. Ultimately, simulation results and comparison experiments confirm the superiority of the controller designed in this paper.