Perceptions "present" objects as red, as round, etc.-- in general as possessing some property. This is the "perceptual content" of the title, And the article attempts to answer the following question: what is a materialistically adequate basis for assigning content to what are, after all, neurophysiological states of biological organisms? The thesis is that a state is a perception that presents its object as "F" if the "biological function" of the state is to detect the presence of objects that are (...) "F". The theory contrasts with causal/informational theories, and with internalist theories, for example those which assign content on the basis of introspected feel. Its advantages are that it permits perceptual error while at the same time allowing content to be expressed in terms of external properties. The argument of the paper is illustrated throughout by examples from biology and computational psychology. (shrink)

One standard criterion for there being objectivity in an area of discourse is that there is conceptual space between what someone thinks to be the case and what actually is the case. That is, participants can be mistaken. This article explores one aspect of the objectivity debate as regards law: does it make sense to say that all legal officials or practitioners in a jurisdiction are mistaken (over a significant period of time) about some legal proposition? The possibility of (...) legal error is important to discourse within and about the law. In contrast to the views of some American legal realists, it is important to deny that law is only what the officials declare it to be. However, as this article argues, claims of long-term global error in law are more problematic. The truth of legal propositions seems to be a complex function of official actions and the meaning of the terms used in authoritative legal texts. Because of the conventional nature of law, there are problems with claiming global error regarding propositions of (within) law, the existence of legal norms, and structural priorities among types of legal norms. At times, the law may in fact simply be what officials (collectively) say it is, over the long term. However, the article also notes areas where claims of long-term global error are more sustainable: where the law incorporates a term from another discourse, or where the law purports to interpret an authoritative text. (shrink)

For successful goal-directed behavior, a performance monitoring system is essential. It detects behavioral errors and initiates behavioral adaptations to improve performance. Two electrophysiological potentials are known to follow errors in reaction time tasks: the error-related negativity, which is linked to error processing, and the error positivity, which is associated with subjective error awareness. Furthermore, the correct-related negativity is linked to uncertainty about the response outcome. Here we attempted to identify the involvement of the nucleus accumbens (...) in the aforementioned performance monitoring processes. To this end, we simultaneously recorded cortical activity and local field potentials during a flanker task performed by four patients with severe opioid abuse disorder who underwent electrode implantation in the NAc for deep brain stimulation. We observed significant accuracy-related modulations in the LFPs at the time of the ERN/CRN in two patients and at the time of Pe in three patients. These modulations correlated with the ERN in 2/8, with CRN in 5/8 and with Pe in 6/8, recorded channels, respectively. Our results demonstrate the functional interrelation of striatal and cortical processes in performance monitoring specifically related to error processing and subjective error awareness. (shrink)

The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series and in time series of satellite images. Here, the functional properties of the quantization error in SOM are explored further to show that the metric is capable of reliably discriminating between the finest differences in local contrast intensities and contrast signs. While this (...) capability of the QE is akin to functional characteristics of a specific class of retinal ganglion cells (the so-called Y-cells) in the visual systems of the primate and the cat, the sensitivity of the QE surpasses the capacity limits of human visual detection. Here, the quantization error in the SOM is found to reliably signal changes in contrast or colour when contrast information is removed from or added to the image, but not when the amount and relative weight of contrast information is constant and only the local spatial position of contrast elements in the pattern changes. While the RGB Mean reflects coarser changes in colour or contrast well enough, the SOM-QE is shown to outperform the RGB Mean in the detection of single-pixel changes in images with up to five million pixels. This could have important implications in the context of unsupervised image learning and computational building block approaches to large sets of image data (big data). (shrink)

Low heart rate causes a risk of death, heart disease, and cardiovascular diseases. Therefore, monitoring the heart rate is critical because of the heart’s function to discover its irregularity to detect the health problems early. Rapid technological advancement allows healthcare sectors to consolidate and analyze massive health-based data to discover risks by making more accurate predictions. Therefore, this work proposes a real-time prediction system for heart rate, which helps the medical care providers and patients avoid heart rate risk in (...) real time. The proposed system consists of two phases, namely, an offline phase and an online phase. The offline phase targets developing the model using different forecasting techniques to find the lowest root mean square error. The heart rate time-series dataset is extracted from Medical Information Mart for Intensive Care. Recurrent neural network, long short-term memory, gated recurrent units, and bidirectional long short-term memory are applied to heart rate time series. For the online phase, Apache Kafka and Apache Spark have been used to predict the heart rate in advance based on the best developed model. According to the experimental results, the GRU with three layers has recorded the best performance. Consequently, GRU with three layers has been used to predict heart rate 5 minutes in advance. (shrink)

Barbieri introduced and developed the concept of organic codes. The most basic of them is the genetic code, a set of correspondence rules between otherwise unrelated sequences: strings of nucleotides on the one hand, polypeptidic chains on the other hand. Barbieri noticed that it implies ‘coding by convention’ as arbitrary as the semantic relations a language establishes between words and outer objects. Moreover, the major transitions in life evolution originated in new organic codes similarly involving conventional rules. Independently, dealing with (...) heredity as communication over time and relying on information theory, we asserted that the conservation of genomes over the ages demands that error-correcting codes make them resilient to casual errors. Moreover, the better conservation of very old parts of the genome demands that they result from combining successively established nested codes such that the older an information, the more numerous component codes protect it. Barbieri’s concept of organic code and that of genomic error-correcting code may seem unrelated. We show however that organic codes actually entail error-correcting properties. Error-correcting, in general, results from constraints being imposed on a set of sequences. Mathematical equalities are conveniently used in communication engineering for expressing constraints but error correction only needs that constraints exist. Biological sequences are similarly endowed with error-correcting ability by physical-chemical or linguistic constraints, thus defining ‘soft codes’. These constraints are moreover presumably efficient for correcting errors. Insofar as biological sequences are subjected to constraints, organic codes necessarily involve soft codes, and their successive onset results in the nested structure we hypothesized. Organic codes are generated and maintained by means of molecular ‘semantic feedback loops’. Each of these loops involves genes which code for proteins, the enzymatic action of which controls a function needed for the protein assembly. Taken together, thus, they control the assembly of their own structure as instructed by the genome and, once closed, these loops ensure their own conservation. However, the semantic feedback loops do not prevent the genome lengthening. It increases both the redundancy of the genome and the information quantity it bears, thus improving the genome reliability and the specificity of the enzymes, which enables further evolution. (shrink)

The Heisenberg-Gabor uncertainty principle defines the limits of information resolution in both time and frequency domains. The limit of resolution discloses unique properties of a time series by frequency decomposition. However, classical methods such as Fourier analysis are limited by spectral leakage, particularly in longitudinal data with shifting periodicity or unequal intervals. Wavelet transformation provides a workable compromise by decomposing the signal in both time and frequency through translation and scaling of a basis function followed by correlation (...) or convolution with the original signal. This study aimed to compare the accuracy of predictive models in mental arithmetic in time and frequency domains. Analysis of the author's response time at mental arithmetic using a soroban was modeled for two periods, an initial period, and a return period both separated by an interval of 370 days. The median response times in seconds was longer for all tasks during the TI compared to the TR period, for addition [CTAdd 62 vs 50 s] and summation [CTSum 68 vs 57 s]. Response times were longer for errors regardless of the study period or task. There was an increasing phase difference for the addition and summation tasks during the TI period toward the end of the series 49.65o compared to the TR period where the phase difference between the two tasks was only 2.05o, indicating that both tasks are likely demonstrating similar learning rates during the latter study period. A comparison between time and time/frequency domain forecasts for an additional 100 tasks demonstrated higher accuracy of the maximum overlap discrete wavelet transform model, where the mean absolute percentage error ranged between 5.48 and 8.19% and that for the time domain models [autoregressive integrated moving average, generalized autoregressive conditional heteroscedasticity ] was 6.16–10.80%. (shrink)

This work investigates the finite-time control problem for a nonlinear four-tank cross-coupled liquid level system by the port-controlled Hamiltonian model. A fixed-free methodology is exhibited which can be used to simplify the controller design procedure. To get an adjustable convergent gain of the finite-time control, a feasible technique named damping normalization is proposed. A novel parameter autotuning algorithm is given to clarify the principle of choosing parameters of the PCH method. Furthermore, a finite-time controller is designed by (...) a state-error desired Hamiltonian function, and the relationship between the settling time and a parameter is given, which can be applied in practical engineering easily to adjust the settling time according to the industrial need. Finally, simulation and experimental results verify the effectiveness of the proposed algorithm. (shrink)

The problem of finite-time tracking control is discussed for a class of uncertain nonstrict-feedback time-varying state delay nonlinear systems with full-state constraints and unmodeled dynamics. Different from traditional finite-control methods, a C 1 smooth finite-time adaptive control framework is introduced by employing a smooth switch between the fractional and cubic form state feedback, so that the desired fast finite-time control performance can be guaranteed. By constructing appropriate Lyapunov-Krasovskii functionals, the uncertain terms produced by time-varying state (...) delays are compensated for and unmodeled dynamics is coped with by introducing a dynamical signal. In order to avoid the inherent problem of “complexity of explosion” in the backstepping-design process, the DSC technology with a novel nonlinear filter is introduced to simplify the structure of the controller. Furthermore, the results show that all the internal error signals are driven to converge into small regions in a finite time, and the full-state constraints are not violated. Simulation results verify the effectiveness of the proposed method. (shrink)

This paper studies the adaptive event-triggered finite-time tracking of output-constrained high-order nonlinear systems with time-varying powers. Due to the presence of multiple unknown powers and the consideration of event-triggered control, all the existing control methods of output-constrained nonlinear systems are inapplicable. By introducing nonlinear mappings, finite-time performance functions, and low-power and high-power terms into adding a power integrator technique and the relative threshold strategy, an adaptive state-feedback controller is designed to eliminate the effects caused by the (...) output constraint and time-varying powers. It is proved that all the closed-loop signals are bounded, the asymmetric time-varying output constraint is not violated, and the tracking error converges to a prescribed arbitrarily small region around zero in a preassigned finite time. Furthermore, the Zeno phenomenon can be avoided. Two simulation examples demonstrate the effectiveness of this control scheme. (shrink)

This article is related to the issue of fixed-time synchronization of different dimensional complex network systems with unknown parameters. Two suitable adaptive controllers and dynamic parameter estimations are proposed such that the complex network driving and response systems can be synchronized in the settling time. Based on fixed-time control theory and Lyapunov functional method, novel sufficient conditions are provided to guarantee the synchronization within the fixed times, and the settling times are explicitly evaluated, which are independent of (...) the initial synchronization errors. Finally, a numerical example is given to illustrate the effectiveness of the proposed control algorithms. (shrink)

This paper empirically investigates the contention that the folk concept of time is a functional concept: a concept according to which time is whatever plays a certain functional role or roles. This hypothesis could explain why, in previous research, surprisingly large percentages of participants judge that there is time at worlds that contain no one-dimensional substructure of ordered instants. If it seems to participants that even in those worlds the relevant functional role is played, then this could (...) explain why they judge that there is time in those worlds. While our experiment supported the finding that participants are reticent to judge that there is no time, actually, we found no evidence that this is because they deploy a functionalist concept, at least of the kind proposed in recent research. Our findings are, however, consistent with the folk deploying a much more minimal functionalist concept according to which time is just whatever it is—regardless of its nature—that plays the role of grounding our temporal phenomenology. (shrink)

BackgroundAdults with ADHD exhibit a neuropsychological profile that may present deficits in many cognitive domains, particularly attention and executive functions. However, some authors do not consider executive disfunction as an important part of the clinical profile of the syndrome; this could be related to the use of inappropriate neuropsychological tests, probably not adapted and not sufficiently ecological. Moreover, new data are required on specific correlation of attentive-executive symptoms with socio-demographic factors. Therefore, the aim of this study is to analyze (...) the neuropsychological performance of a group of adults with ADHD, also evaluating the influence of gender, age and education level.MethodsWe retrospectively collected health-related personal data of 40 adult ADHD patients, clinically diagnosed and evaluated via a battery of 4 neuropsychological tests and 1 self-administered questionnaire. Gender, age and years of education differences were assessed.ResultsAttention and EFs deficits have been highlighted mainly on the d2-R and 5-point neuropsychological tests, which therefore seem to be more sensitive in measuring the attention-executive dysfunction in an adult ADHD population, than TAP Go/No-go and ROCFT. ADHD patients also manifested subjective behavioral impulsivity disorders on BIS-11. There were no statistically significant gender differences in cognitive performance. On the contrary, younger patients performed worse on subscales TAP Go/No-go errors and 5-points number of drawings, while participants with a higher education level performed better on subscales d2-R speed of execution and d2-R errors. This supports a reduction in the number of errors and the execution time as a function of older age and a higher level of education. Finally, patients with higher education also self-reported greater impulsivity in planning.ConclusionOur preliminary findings suggest that adult ADHD is not a lifelong stable disorder, but it may change over time. Moreover, attention-executive deficits may be influenced and partially counterbalanced by experience and a higher level of education. This could underlie the development of specific psycho-behavioral and cognitive compensatory strategies. The use of self-administered questionnaires is therefore recommended to highlight attentional and executive difficulties that may not result in neuropsychological tests. (shrink)

Background: There are few standardized measures available to assess executive function in a naturalistic setting for children. The Children’s Cooking Task is a complex test that has been specifically developed to assess EF in a standardized open-ended environment. The aim of the present study was to evaluate the internal consistency, inter-rater reliability, sensitivity and specificity, and also convergent and divergent validity of the Norwegian version of CCT among children with pediatric Acquired Brain Injury and healthy controls.Methods: The present study has (...) a cross-sectional design, based on baseline data derived from a multicenter RCT. Seventy-five children with pABI from two university hospitals with parent-reported executive dysfunction and minimum of 12 months since injury/completed cancer therapy, as well as 59 HCs aged 10–17 years, were assessed with CCT using total errors as the main outcome measure. The pABI group completed tests assessing EF on the impairment level within the ICF framework, and on the participation level. In addition, they completed tests of intellectual ability, processing speed, attention, learning, and memory. Finally, overall functional outcome was evaluated for the children with pABI.Results: Acceptable internal consistency and good inter-rater reliability were found for the CCT. Children with pABI performed significantly worse on the CCT than the HCs. The CCT identified group membership, but the sensitivity and specificity were overall classified as poor. Convergent validity was demonstrated by associations between the CCT and performance-based tests assessing inhibition, cognitive flexibility, and working memory, as well as teacher-reported executive dysfunction. Divergent validity was supported by the lack of association with performance-based measures of learning and memory, attention, and verbal intellectual ability. However, there was a moderate association between the CCT and performance-based tests of processing speed. Lastly, better performance on the CCT was associated with a better functional outcome.Conclusion: Our study with a relatively large sample of children with pABI and HC’s demonstrated good psychometric properties of the CCT. CCT performance was associated with the overall level of disability and function, suggesting that CCT is related to the level of activity in everyday life and participation in society. Hence, our study suggests that the CCT has the potential to advance the assessment of EF by providing a valid analysis of real-world performance. Nevertheless, further research is needed on larger samples, focusing on predictors of task performance, and evaluating the ability of CCT to detect improvement in EF over time. The patterns of error and problem-solving strategies evaluated by the CCT could be used to inform neuropsychological rehabilitation treatmentand represent a more valid outcome measure of rehabilitation interventions. (shrink)

It will be settled out for the open problem of designing an r-order finite-time state observer for reaction-diffusion genetic regulatory networks with time-varying delays. By assuming the Dirichlet boundary conditions, aiming to estimate the mRNA and protein concentrations via available network measurements. Firstly, sufficient F-T stability conditions for the filtering error system have been investigated via constructing an appropriate Lyapunov–Krasovskii functional and using several integral inequalities and convex technique simultaneously. These conditions are delay-dependent and reaction-diffusion-dependent and can (...) be checked by MATLAB toolbox. Furthermore, a method is proposed to design an r-order F-T state observer, and the explicit expressions of observer gains are given. Finally, a numerical example is presented to illustrate the effectiveness of the proposed method. (shrink)

This paper develops an adaptive fixed-time trajectory tracking controller of an underactuated hovercraft with a prescribed performance in the presence of model uncertainties and unknown time-varying environment disturbances. It is the first time that the proposed method is applied to the motion control of the hovercraft. To begin with, based on the hovercraft's four degrees of freedom model, the virtual control laws are designed using an error transforming function and the fixed-time stability theory to guarantee (...) that the position tracking errors are constrained within the prescribed convergence rates and minimum overshoot. In addition, by combining the Lyapunov direct method and the adaptive radial basis function neural network, the actual control laws are designed to ensure that the velocity tracking errors converge to a small region containing zero while handling model uncertainties and external disturbances effectively. Finally, all tracking errors of the closed-loop system are uniformly ultimately bounded and fixed-time convergent. Results from a comparative simulation study verify the effectiveness and advantage of the proposed method. (shrink)

This paper reports an experimental comparison of attitudes toward time and toward money in experience-based decisions. Preferences were elicited under rank-dependent utility for prospects with two or three consequences expressed either in time or in monetary units. Probabilities were unknown but learned through sampling. More specifically, time and money were compared under two conditions. In a first experiment, both consequences and probabilities of prospects were unknown and learned through sequential sampling. In a second experiment, the possible consequences (...) were revealed after the sampling. A real incentive system was implemented for both time and money. The heterogeneity of preferences was assessed for time and for money through individual and mixed modeling estimations. We observe that the nature of consequences (time or money) modifies probability weighting in terms of elevation and sensitivity. Subjects exhibit more optimism and less sensitivity to probability changes when deciding about time than about money. Revealing the consequences impacts the shape of the utility function and leaves probability weighting unchanged. We also observe that the real incentives have no effect except for the reduction in decision errors. This effect is stronger for money than for time. (shrink)

Classification learning is a preeminent human ability within the animal kingdom but the key mechanisms of brain networks regulating learning remain mostly elusive. Recent neuroimaging advancements have depicted human brain as a complex graph machinery where brain regions are nodes and coherent activities among them represent the functional connections. While long-term motor memories have been found to alter functional connectivity in the resting human brain, a graph topological investigation of the short-time effects of learning are still not widely investigated. (...) For instance, classification learning is known to orchestrate rapid modulation of diverse memory systems like short-term and visual working memories but how the brain functional connectome accommodates such modulations is unclear. We used publicly available repositories (openfmri.org) selecting three experiments, two focused on short-term classification learning along two consecutive runs where learning was promoted by trial-by-trial feedback errors, while a further experiment was used as supplementary control. We analyzed the functional connectivity extracted from BOLD fMRI signals, and estimated the graph information processing in the cerebral networks. The information processing capability, characterized by complex network statistics, significantly improved over runs, together with the subject classification accuracy. Instead, null-learning experiments, where feedbacks came with poor consistency, did not provoke any significant change in the functional connectivity over runs. We propose that learning induces fast modifications in the overall brain network dynamics, definitely ameliorating the short-term potential of the brain to process and integrate information, a dynamic consistently orchestrated by modulations of the functional connections among specific brain regions. (shrink)

Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential in biological (...) research and reflects the nature of biology itself. Annotation systems, rather than being repositories of facts, should be tools that support multiple modes of inference. By combining deduction, induction and abduction, investigators can generate hypotheses when accurate knowledge is extracted from model databases. A key stance is to depart from ‘the sequence tells the structure tells the function’ fallacy, placing function first. We illustrate our approach with examples of critical or unexpected pathways, using MicroScope to demonstrate how tools can be implemented following the principles we advocate. We end with a challenge to the reader. (shrink)

We ask what cerebellum and basal ganglia arguing that cerebellum tunes motor schemas and their coordination. We argue for a synthesis of models addressing the real-time role and error signaling roles of climbing fibers. bridges between regional and neuro-physiological studies, while relates the neurochemis-try of learning to neural and behavioral levels. [CRÉPEL et al.; HOUK et al.; KANO; LINDEN; SIMPSON et al.; SMITH; THACH; VINCENT].

Human multitasking suffers from a central attentional bottleneck preventing parallel performance of central mental operations, leading to profound deferments in task performance. While previous research assumed that the deferment is caused by a mere waiting time, we show that the bottleneck requires executive functions accounting for a profound part of the deferment. Three participant groups with EF impairments showed worse multitasking performance than respective control groups. Three further groups with EF improvements showed improved multitasking. Finally, three groups performed (...) a dual-task and different measures of EF and showed significant correlations between multitasking performance and working memory capacity. Demands on EF during multitasking may cause more errors, mental fatigue and stress, with parts of the population being considerably more prone to this. (shrink)

In this paper, we mainly investigate the coordinated tracking control issues of multiple Euler–Lagrange systems considering constant communication delays and output constraints. Firstly, we devise a distributed observer to ensure that every agent can get the information of the virtual leader. In order to handle uncertain problems, the neural network technique is adopted to estimate the unknown dynamics. Then, we utilize an asymmetric barrier Lyapunov function in the control design to guarantee the output errors satisfy the time-varying output constraints. (...) Two distributed adaptive coordinated control schemes are proposed to guarantee that the followers can track the leader accurately. The first scheme makes the tracking errors between followers and leader be uniformly ultimately bounded, and the second scheme further improves the tracking accuracy. Finally, we utilize a group of manipulator networks simulation experiments to verify the validity of the proposed distributed control laws. (shrink)

The Fist-Edge-Palm task, a manual hand task, has been used to detect frontal dysfunctions in clinical situations: its performance failures are observed in various prefrontal cortex -related disorders, including schizophrenia. However, previous imaging studies reported that the performance of the FEP task activated motor-related areas, but not the PFC. Here, we aimed to investigate the relationships between the performance of the FEP task and PFC functions. Hemodynamic activity in the PFC, including the dorsolateral PFC and frontal pole, was recorded. (...) Healthy young subjects performed the FEP task as well as a palm tapping task three times. The subjects also completed a Wisconsin Card Sorting Test and Schizotypal Personality Scale questionnaire. We found that hemodynamic activity in the PFC increased in the first trial of the FEP task but decreased considerably in the second and third trials compared to the PT task. The number of performance errors in the FEP task also decreased in the second and third trials. Error reduction in the FEP task between the first and second trials was negatively correlated with schizotypal trait and the number of perseveration errors in the WCST. Furthermore, changes in the PFC hemodynamic activity between the first and second trials were positively correlated with error reduction in the FEP task between the first and second trials, and negatively correlated with the number of perseveration errors in the WCST. These results suggest that learning in the FEP task requires PFC activation, which is negatively associated with perseveration errors in the WCST. The results further suggest that the FEP task, in conjunction with near-infrared spectroscopy, may be useful as a diagnostic method for various disorders with PFC dysfunction. (shrink)

An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, (...) when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness. (shrink)

The large scale, time varying, and diversification of physically coupled networked infrastructures such as power grid and transportation system lead to the complexity of their controller design, implementation, and expansion. For tackling these challenges, we suggest an online distributed reinforcement learning control algorithm with the one-layer neural network for each subsystem or called agents to adapt the variation of the networked infrastructures. Each controller includes a critic network and action network for approximating strategy utility function and desired control law, (...) respectively. For avoiding a large number of trials and improving the stability, the training of action network introduces supervised learning mechanisms into reduction of long-term cost. The stability of the control system with learning algorithm is analyzed; the upper bound of the tracking error and neural network weights are also estimated. The effectiveness of our proposed controller is illustrated in the simulation; the results indicate the stability under communication delay and disturbances as well. (shrink)

This article examines mixed ℋ -infinity and passivity synchronization of Markovian jumping neutral-type complex dynamical network models with randomly occurring coupling delays and actuator faults. The randomly occurring coupling delays are considered to design the complex dynamical networks in practice. These delays complied with certain Bernoulli distributed white noise sequences. The relevant data including limits of actuator faults, bounds of the nonlinear terms, and external disturbances are available for designing the controller structure. Novel Lyapunov–Krasovskii functional is constructed to verify the (...) stability of the error model and performance level. Jensen’s inequality and a new integral inequality are applied to derive the outcomes. Sufficient conditions for the synchronization error system are given in terms of linear matrix inequalities, which can be analyzed easily by utilizing general numerical programming. Numerical illustrations are given to exhibit the usefulness of the obtained results. (shrink)

We deal with the design problem of nonfragile state estimator for discrete-time genetic regulatory networks with time-varying delays and randomly occurring uncertainties. In particular, the norm-bounded uncertainties enter into the GRNs in random ways in order to reflect the characteristic of the modelling errors, and the so-called randomly occurring uncertainties are characterized by certain mutually independent random variables obeying the Bernoulli distribution. The focus of the paper is on developing a new nonfragile state estimation method to estimate the (...) concentrations of the mRNA and the protein for considered uncertain delayed GRNs, where the randomly occurring estimator gain perturbations are allowed. By constructing a Lyapunov-Krasovskii functional, a delay-dependent criterion is obtained in terms of linear matrix inequalities by properly using the discrete-time Wirtinger-based inequality and reciprocally convex combination approach as well as the free-weighting matrix method. It is shown that the proposed method ensures that the estimation error dynamics is globally asymptotically stable and the desired estimator parameter is designed via the solutions to certain LMIs. Finally, we provide two numerical examples to illustrate the feasibility and validity of the proposed estimation results. (shrink)

This paper presents an adaptive neural tracking control approach for a two-joint robotic manipulator with unknown time-varying delays. In order to work out the effect of unknown time-varying delays on the two-joint robotic manipulator, the appropriate Lyapunov–Krasovskii functionals and separation technology are chosen to settle this matter. The neural networks work as an approximator that has the advantage of estimating the unknown function in the system. In this paper, Lyapunov stability analysis can prove that all signals of the (...) closed-loop system are semiglobal uniformly ultimately bounded and the tracking error can converge to a compact neighborhood with respect to zero. The simulation consequences demonstrate the availability of the feedforward control approach. (shrink)

Developing novices’ proficiency in skilful activities is central to the reproduction of human societies. The interactional practices through which instruction is accomplished have provided a rich focus for ethnomethodological and conversation analytic studies examining classroom settings, and, more recently, non-classroom environments of instruction in practical and manual skills. This paper examines the work of instruction in basketball training and in particular the correction of player performances, which are a ubiquitous and central feature of instruction in basketball training sessions. A central (...) part of this instructional action relies on the coach observing training activities to determine players’ competencies and to extract relevant correctables from the players’ embodied displays, which are in turn embedded within complex arrangements of rapidly moving bodies situated in material environments. In this paper we examine the visual-analytic work involved in both organizing and observing a basketball training activity, demonstrating the sequential layering of multiple membership categorization devices drawn upon in producing and recognizing actions in this setting. We argue that the coach deploys spatial orientations which function analogously to membership categorization devices, with players’ bodily positions relative to one another and the material structure of the surround generating category-like sets of rights, responsibilities, and sequential relevancies. As we demonstrate, these orientations provide crucial resources for the identification of players’ errors and thereby for the organization of instruction in interaction in this setting. (shrink)

Multi-time wave functions are wave functions for multi-particle quantum systems that involve several time variables. In this paper we contrast them with solutions of wave equations on a space–time with multiple timelike dimensions, i.e., on a pseudo-Riemannian manifold whose metric has signature such as \ or \, instead of \. Despite the superficial similarity, the two behave very differently: whereas wave equations in multiple timelike dimensions are typically mathematically ill-posed and presumably unphysical, relevant Schrödinger equations (...) for multi-time wave functions possess for every initial datum a unique solution on the spacelike configurations and form a natural covariant representation of quantum states. (shrink)

The origin of the genetic code has been attributed in part to an accidental assignment of codons to amino acids. Although several lines of evidence indicate the subsequent expansion and improvement of the genetic code, the hypothesis of Francis Crick concerning a frozen accident occurring at the early stage of genetic code evolution is still widely accepted. Considering Crick’s hypothesis, mathematical descriptions of hypothetical scenarios involving a huge number of possible coexisting random genetic codes could be very important to explain (...) the origin and evolution of a selected genetic code. This work aims to contribute in this regard, that is, it provides a theoretical framework in which statistical parameters of error functions are calculated. Given a genetic code and an amino acid property, the functional code robustness is estimated by means of a known error function. In this work, using analytical calculations, general expressions for the average and standard deviation of the error function distributions of completely random codes with standard stop codons were obtained. As a possible biological application of these results, any set of amino acids and any pure or mixed amino acid properties can be used in the calculations, such that, in case of having to select a set of amino acids to create a genetic code, possible advantages of natural selection of the genetic codes could be discussed. (shrink)

This paper considers the interpretive significance of the intersecting relationships between different conceptions of responsibility as they shift over space and time. The paper falls into two main sections. The first gives an account of several conceptions of responsibility: two conceptions founded in ideas of capacity; two founded in ideas of character, and one founded in the relationship between an agent and the outcome which she causes. The second main section uses this differentiated conceptual account to analyse and interpret (...) certain aspects of the contemporary criminal law of England and Wales. In conclusion, the paper considers a number of hypotheses about what the evidence of certain shifts in the relationship between the three families of responsibility-conception can tell us about the current state and significance of criminal law among other systems of social governance. (shrink)