Symbolic Signal Research Articles

Fluorescence sensor array of a multiplexing probe with three/four excitations/emissions for rapid and highly sensitive discrimination of foodborne pathogenic bacteria

Development of sensitive, accurate yet simplified fluorescence sensor array is crucial for rapid, multi-bacterial, on-site sensing applications. A fluorescence sensor array based on a multiplexing fluorescence probe (MFP, excitations/emissions with 278 nm/558 nm, 290 nm/364 nm, 362 nm/592 and 616 nm) was constructed. The positive MFP equipped with rich quinoline and pyridine groups can combine with the negative charge groups and electron-rich groups of bacterial surfaces, which causes the symbolic signal response in the sensing channels (four emissions and three excitations). The sensor array displayed sensitive response to bacteria even at a lower level (102 cfu mL−1) and high identification accuracy (100%) for drug-resistant bacteria, inactivated bacteria, and blends of bacteria. Furthermore, the developed sensor array demonstrated a high-throughput bacterial identification (92.1% accuracy) in real samples (pork and milk) with high sensitivity, rapid response, easy-to-operate, and independence of specific recognition elements, which would brighten the development of fluorescence sensor array.

Does renting luxury make me shine? The mediating role of perceived signals

AbstractWhether rented luxury creates symbolic meaning for consumers who cannot afford it, thus, providing them with an effective way to construct their identity, similar to owned luxury, and strengthen their willingness to rent. Drawing on implicit self‐theories, we find that compared with entity theorists, incremental theorists have lower willingness to rent luxury products (Studied 1, 2, and 3), but they do not exhibit significant differences in self‐brand connection (Studied 2 and 3). We show that incremental theorists (vs. entity theorists) perceive more authentic signal than symbolic signal regarding their inability to afford luxury goods when using rented luxury products (Study 3). Neither in ownership‐based luxury consumption (Study 4, where there is no authentic signal), nor in access‐based nonluxury consumption (Study 5, where there is no symbolic signal), consumers with different implicit beliefs no longer differentiate in buying/renting intentions. Our work suggests that not all consumers who desire unaffordable luxuries are willing to rent them. Therefore, managers should consider how to reduce the negative impacts of authentic signals on incremental theorists' renting intentions.

Symbolic Signal Use in Wild Chimpanzee Gestural Communication?: A Theoretical Framework.

Symbolic communication is not obvious in the natural communicative repertoires of our closest living relatives, the great apes. However, great apes do show symbolic competencies in laboratory studies. This includes the understanding and the use of human-provided abstract symbols. Given this evidence for the underlying ability, the apparent failure to make use of it in the wild is puzzling. We provide a theoretical framework for identifying basic forms of symbolic signal use in chimpanzee natural communication. In line with the laboratory findings, we concentrate on the most promising domain to investigate, namely gesture, and we provide a case study in this area. We suggest that evidence for basic symbolic signal use would consist of the presence of two key characteristics of symbolic communication, namely arbitrariness and conventionalization. Arbitrariness means that the linkage between the form of the gesture and its meaning shows no obvious logical or otherwise motivated connection. Conventionalization means that the gesture is shared at the group-level and is thus socially learned, not innate. Further, we discuss the emergence and transmission of these gestures. Demonstrating this basic form of symbolic signal use would indicate that the symbolic capacities revealed by laboratory studies also find their expression in the natural gestural communication of our closest living relatives, even if only to a limited extent. This theoretical article thus aims to contribute to our understanding of the developmental origins of great ape gestures, and hence, arguably, of human symbolic communication. It also has a very practical aim in that by providing clear criteria and by pointing out potential candidates for symbolic communication, we give fieldworkers useful prerequisites for identifying and analyzing signals which may demonstrate the use of great apes’ symbolic capacities in the wild.

Pursuing Firm Economic Sustainability through Debt Restructuring Agreements in Italy: An Empirical Analysis

Corporate restructuring has become a central topic for both academics and practitioners, particularly following the global financial crisis. In particular, there is increasing interest in understanding the effectiveness of turnaround strategies, which are defined as attempts to restore the performance of firms after periods of downfall. However, despite the relevance of this issue, there is a shortage of empirical evidence regarding the effectiveness of turnaround strategies related specifically to financial interventions. Through the support of an empirical analysis among Italian firms, this paper seeks to fill this significant gap in the available literature. In particular, we conducted an in-depth analysis of 262 debt restructuring agreement (DRA) plans that occurred between 2005 and 2013 in 16 bankruptcy courts. Our study confirms the positive effect of changes in the top management team. This measure can be both a symbolic signal of genuine willingness to modify the strategy of the firm, and a real manifestation of the necessity to have new skills to complete the turnaround. In addition, the adoption of operational and strategic/asset measures increase the likelihood of turnaround success.

A novel numerical mapping method based on entropy for digitizing DNA sequences

Recently, digital signal processing has been widely applied in the study of genomics. One of the genomic studies is identification of protein-coding regions. Where is a protein coded? How much is encoded? Where are growth and development regulated? The answer to these questions is possible by DNA sequences that can be classified as the exon and intron. In signal processing application, numerical signals are used due to symbolic signal nature of DNA sequence; yet, it must be converted from symbolic sequence to numeric sequence prior the analysis in data preprocessing. The bases in a DNA sequence are represented with four letters A, G, C and T. Each letter corresponds to a numeric value. In the literature, several numerical mapping techniques exist. In this paper, a novel numerical mapping approach has been proposed for converting string to numerical values. Each codon is mapped by improved fractional derivative of Shannon equation in this approach. For exon regions prediction, three methods have been used. These methods are singular value decomposition (SVD), discrete Fourier transform (DFT) and short-time Fourier transform (STFT). The performance of the proposed mapping technique has been evaluated based on the above-mentioned three classification methods. The proposed novel technique has showed more success in the identification of protein-coding regions as compared to the predominant existing mapping techniques SVD, DFT and STFT methods.

Simple Symbolic Dynamic of Heart Rate Variability Identify Patient with Congestive Heart Failure

Symbolic dynamics allows representing the heart rate variability signal into a common symbol that has been determined to ease the calculation process. The application of existing symbolic analysis can eliminate the information contained in those signals. This paper proposes a method of symbolic analysis by taking into account the size of symbolic signal changes. Symbols are divided into two groups: that for the increasing signal and decreasing one. To store the signal amplitude information, three groups of divisions are proposed i.e., amplitude less than one times standard deviation, that is more than or equal to one times standard deviation to less than two times standard deviation and more than two times standard deviation. The probability of each symbol in a series of data is calculated. Besides, Shannon entropy of all the data on each sample was also calculated. The result suggests that the probability of each symbol has a significant difference between the normal subject and patients with congestive heart failure.

Rational instrument or symbolic signal? Explaining coordination structures in the Directorate-General for Fisheries and Maritime Affairs of the European Commission

This article examines the reorganization of formal coordination structures in the Directorate-General for Fisheries and Maritime Affairs of the European Commission. While rational approaches in organization theory emphasize functional efficiency as an explanation for organizational design and coordination structures, the findings of this study indicate that the reorganization was not driven primarily for reasons of efficiency and to increase the coordination capacity of the organization. The study demonstrates that, even in a highly technical policy area such as fisheries management in the European Union, the (re-)design of formal organizational structures does not follow primarily a technical–instrumental rationale. Instead, the formal coordination structures have also been adapted to live up to changing expectations in the institutional environment, to modern management concepts in marine governance, and to ensure the legitimacy of the organization. However, although the empirical findings of this study substantiate the theoretical assumptions of an institutional perspective, institutional explanations alone are insufficient to comprehensively understand why organizational structures are reorganized and changed.

Honesty, Lemons, and Symbolic Signals

Under asymmetric information, dishonest sellers lead to market unraveling in the lemons model. An additional cost of dishonesty is that language becomes cheap talk. We develop instead a model where people derive utility from actions (what they say), as well as from outcomes, so talk is costly. We find that the existence of honest agents that mean what they say is not enough to make trade more likely, unless a traceability condition that prevents arbitrage is met. When we introduce a continuum of misrepresentation cost types and qualities, full market unraveling is not possible and babbling equilibria are eliminated. More generally, costly talk is a special kind of signal, a symbolic signal that presupposes linguistic conventions, otherwise truth and falsehood, as well as misrepresentation costs, are undefined.

A three-level architecture for bridging the image semantic gap

Image retrieval systems face the problem of dealing with the different ways to apprehend the content of images and in particular the difficulty to characterize the visual semantics. To address this issue, we examine the use of three abstract levels of representation, namely Signal, Object and Semantic. At the Signal Level, we propose a framework mapping the extracted low-level features to symbolic signal descriptors. The Object Level features a statistical model considering the joint distribution of object concepts (such as mountains, sky?) and the symbolic signal descriptors. At the Semantic Level, signal and object characterizations are coupled within a logic-based framework. The latter is instantiated by a knowledge representation formalism allowing to define an expressive query language consisting of several boolean and quantification operators. Our architecture therefore makes it possible to process topic-based queries. Experimentally, we evaluate our theoretical proposition on a corpus of real-world photographs and the TRECVid corpus.

Mapping Equivalence for Symbolic Sequences: Theory and Applications

Processing of symbolic sequences represented by mapping of symbolic data into numerical signals is commonly used in various applications. It is a particularly popular approach in genomic and proteomic sequence analysis. Numerous mappings of symbolic sequences have been proposed for various applications. It is unclear however whether the processing of symbolic data provides an artifact of the numerical mapping or is an inherent property of the symbolic data. This issue has been long ignored in the engineering and scientific literature. It is possible that many of the results obtained in symbolic signal processing could be a byproduct of the mapping and might not shed any light on the underlying properties embedded in the data. Moreover, in many applications, conflicting conclusions may arise due to the choice of the mapping used for numerical representation of symbolic data. In this paper, we present a novel framework for the analysis of the equivalence of the mappings used for numerical representation of symbolic data. We present strong and weak equivalence properties and rely on signal correlation to characterize equivalent mappings. We derive theoretical results which establish conditions for consistency among numerical mappings of symbolic data. Furthermore, we introduce an abstract mapping model for symbolic sequences and extend the notion of equivalence to an algebraic framework. Finally, we illustrate our theoretical results by application to DNA sequence analysis.

Symbolic signal processing and system analysis

We present new software in MATLAB and Mathematica for symbolic signal processing and system analysis. Our mission is to encapsulate high-tech engineering and sophisticated mathematical knowledge into easy-to-use software that effectively solves practical problems.

Algorithm-driven synthesis of data conversion architectures

A new, algorithm-driven methodology is introduced for the synthesis of data conversion systems. It employs a combination of symbolic signal flow graph techniques to generate a canonical representation of the algorithm description, together with pattern recognition techniques, to determine the appropriate functional building blocks for the converter architecture and knowledge-based rules to instantiate such building blocks by electrical subcircuits. By allowing the synthesis process to move to higher levels of abstraction the proposed methodology provides a computer-based framework for the systematic and uniform treatment of various types of conversion systems, including the search for new conversion algorithms and/or new implementation architectures.

Analyse und Synthese einfacher hybrider Regelsysteme

In a hybrid system, continuous and discrete-event components interact. In this contribution, we consider a particularly simple class of hybrid control problems: a purely continuous plant is to be controlled via symbolic measurement and control signals. The controller «sees» only a discretized, or symbolic, version of the continuous plant output (such as «water level in tank A is too high», «too low», or «ok»); it generates a symbolic control signal (such as «open» or «close valve»), which is then mapped into the plant input

Symbolic representation of process monitoring signals

Abstract This paper introduces a generalized symbolic signal representation capable of capturing the physical appearance of process monitoring signals. The signals are decomposed into simpler subcomponents described by different parametric models and combined under an object-oriented hybrid signal model. These subcomponents are modeled by a piecewise spline function approximation. This model represents the signal patterns in purely mathematical terms and can be viewed as an extension of syntactic signal modeling approaches used in electrocardiogram (ECG) analysis. Furthermore, a robust event-synchronous system capable of transcribing given signals into the proposed symbolic representation is described. Using event-synchronous analysis makes the system specifically useful for process monitoring applications.

Uniqueness of the Gaussian Kernel for Scale-Space Filtering

Scale-space filtering constructs hierarchic symbolic signal descriptions by transforming the signal into a continuum of versions of the original signal convolved with a kernal containing a scale or bandwidth parameter. It is shown that the Gaussian probability density function is the only kernel in a broad class for which first-order maxima and minima, respectively, increase and decrease when the bandwidth of the filter is increased. The consequences of this result are explored when the signal¿or its image by a linear differential operator¿is analyzed in terms of zero-crossing contours of the transform in scale-space.

The signal representation language SRL

The signal representation language (SRL) is a Lisp-based language for representing discrete-time signals as abstract data objects. SRL is based on a symbolic signal representation which explicitly records information about the ancestry of each signal. Central to this representation is the organization of signals into a hierarchy of signal types. A signal type is a collection of signals which share a parameterized procedure for computing the values of their samples. Use of an explicit signal representation allows SRL to provide elegant solutions to programming problems, such as array storage management and the use of multiple-output algorithms. The concepts and facilities of SRL are described in the context of numerous examples, including an extended example illustrating the implementation of overlap-add convolution.

On the dialectics of human evolution

On the dialectics of human evolution