The Prospect of Extracting Brain-Region-Specific Exosomes in the Human Bloodstream

Exosomes are small vesicles, secreted by eukaryotic cells, containing molecular cargo that reflects the biochemical composition of the origin cell, including protein and RNA. Once secreted, exosomes can enter the circulatory system and be found in blood, urine, and saliva. It has been hypothesized that because exosomes contain transmembrane proteins unique to their cell of origin, specific populations of exosomes could be non-invasively extracted from the bloodstream. The protein L1CAM may serve as a marker of neuronal exosomes. However, although “neuron-derived-exosomes'' could offer some specific information about in-vivo molecular neurobiology, this population of exosomes still provides a relatively noisy signal, including data on protein expression from a variety of different neuronal subpopulations. We argue that it may be possible to isolate brain-region-specific exosomes, and that data derived from these exosomes would provide a superior diagnostic tool.

Auditing versus monitoring and the role of commitment

This paper studies the effect of timing and commitment of verification in a principal-agent relationship with moral hazard. To acquire additional information about the agent’s behavior, the principal possesses a costly technology that produces a noisy signal about the agent’s effort choice. The precision of this signal is affected by the principal’s verification effort. Two verification procedures are discussed: monitoring where the principal verifies the agent’s behavior simultaneously with his effort choice and auditing where the principal can condition her verification effort on the realized outcome. As it is well known, the principal prefers to audit the agent’s behavior if she can commit to her verification effort at the time of contracting. The main contribution of this paper is to highlight the importance of commitment by the principal to her verification effort. In particular, I show that, when the principal cannot commit to her verification effort ex-ante, the principal strictly prefers monitoring to auditing if the gains from choosing high effort are sufficiently high.

Pulse Identification Using SVM

This paper is about dealing with a noisy signal containing pulses from a detector of X-ray photons. We are designing algorithms to detect pulses, separate them when overlapping, and measure the energy of photons and separation between pulses. In this paper, we present the detection of pulses using SVM.

Absolute Versus Relative Success: Why Overconfidence Creates an Inefficient Equilibrium

Overconfidence is one of the most ubiquitous biases in the social sciences, but the evidence regarding its overall costs and benefits is mixed. To test the possibility that overconfidence might yield important relative benefits that offset its absolute costs, we conducted an experiment ( N = 298 university students) in which pairs of participants bargained over the unequal allocation of a prize that was earned through a joint effort. We manipulated confidence using a binary noisy signal to investigate the causal effect of negotiators’ beliefs about their relative contribution to the outcome of the negotiation. Our results provide evidence that high levels of confidence lead to relative benefits (how much one earns compared with one’s partner) but absolute costs (how much money one receives overall). These results suggest that overconfidence creates an inefficient equilibrium whereby overconfident negotiators benefit over their partners even as they bring about joint losses.

Mishearing as a Side Effect of Rational Language Comprehension in Noise

Language comprehension in noise can sometimes lead to mishearing, due to the noise disrupting the speech signal. Some of the difficulties in dealing with the noisy signal can be alleviated by drawing on the context – indeed, top-down predictability has shown to facilitate speech comprehension in noise. Previous studies have furthermore shown that strong reliance on the top-down predictions can lead to increased rates of mishearing, especially in older adults, which are attributed to general deficits in cognitive control in older adults. We here propose that the observed mishearing may be a simple consequence of rational language processing in noise. It should not be related to failure on the side of the older comprehenders, but instead would be predicted by rational processing accounts. To test this hypothesis, we extend earlier studies by running an online listening experiment with younger and older adults, carefully controlling the target and direct competitor in our stimuli. We show that mishearing is directly related to the perceptibility of the signal. We furthermore add an analysis of wrong responses, which shows that results are at odds with the idea that participants overly strongly rely on context in this task, as most false answers are indeed close to the speech signal, and not to the semantics of the context.

TECHNOLOGIES FOR CALCULATING THE CORRELATION COEFFICIENT BETWEEN THE USEFUL SIGNAL AND THE NOISE USING THE ESTIMATE OF THEIR RELAY CROSS-CORRELATION FUNCTION

It is shown that when noisy signals are formed, the condition for the absence of correlation between the useful signal and the noise is often violated. This causes certain errors of correlation analysis of these signals, resulting in the inadequacy of the results obtained. In addition, the existing correlation analysis technologies do not allow using the noise as a carrier of valuable information. Therefore, the full use of the colossal information potential of noisy signals requires new technologies that would exclude the loss of valuable information, both when the known classical conditions are met and when they are not. Algorithms are developed for determining the estimate of the correlation coefficient between the useful signal and the noise, which cannot be measured directly or isolated from a noisy signal. For this purpose, the normalized cross-correlation function between the useful signal and the noise is used. An algorithm for calculating the estimates of the normalized cross-correlation function between the useful signal and the noise is developed using the estimates of the relay correlation function of the noisy signal. It is shown that the value of this estimate, calculated at a zero time shift, is an estimate of the correlation coefficient between the useful signal and the noise. A technology for conducting computational experiments is proposed, a comparative analysis is carried out, and the reliability of the proposed algorithms and technologies is confirmed. It is shown that under the normal technical condition of the object, the estimates of the relay cross-correlation function and the correlation coefficient between the useful signal and the noise will be close to zero. With the emergence of various defects preceding malfunctions at the object, these estimates will change depending on the degree of damage. Therefore, it is the estimates of the cross-correlation function and the correlation coefficient between the useful signal and the noise that should be used in monitoring and control systems as informative attributes for signaling and monitoring the beginning of changes in the technical condition of objects and the dynamics of their malfunctions. The use of these new effective informative attributes makes it possible to increase the degree of accuracy and reliability of operation of modern information systems.

Single-channel speech enhancement based on joint constrained dictionary learning

To improve the performance of speech enhancement in a complex noise environment, a joint constrained dictionary learning method for single-channel speech enhancement is proposed, which solves the “cross projection” problem of signals in the joint dictionary. In the method, the new optimization function not only constrains the sparse representation of the noisy signal in the joint dictionary, and controls the projection error of the speech signal and noise signal on the corresponding sub-dictionary, but also minimizes the cross projection error and the correlation between the sub-dictionaries. In addition, the adjustment factors are introduced to balance the weight of constraint terms to obtain the joint dictionary more discriminatively. When the method is applied to the single-channel speech enhancement, speech components of the noisy signal can be more projected onto the clean speech sub-dictionary of the joint dictionary without being affected by the noise sub-dictionary, which makes the quality and intelligibility of the enhanced speech higher. The experimental results verify that our algorithm has better performance than the speech enhancement algorithm based on discriminative dictionary learning under white noise and colored noise environments in time domain waveform, spectrogram, global signal-to-noise ratio, subjective evaluation of speech quality, and logarithmic spectrum distance.

Algorithms for Determining the Probability of Risks of Accidents in Tunnels Based on the Characteristics of the Noise of Noisy Signals

The paper covers creating the algorithms for calculating the probability of various types of defects in tunnels, the development of which can lead to accidents. Tunnels are an important and complex part of the transport and communication system, through which heavy traffic is carried out. Determining the probability of defects in the latent period of their initiation in individual sections of tunnels is an important problem. The formation of defects is accompanied by the appearance of noise that distorts the useful signals coming from sensors and measuring instruments installed to control the stability of the tunnel and the reliability of its structures. Traditionally measuring instruments register noisy signals, and the technical condition of the tunnels is assessed on the basis of the values of their characteristics. It is shown in the paper that the more reliable indicators of fixing the onset of dangerous changes in the latent period of initiation are the characteristics of the noise, which cannot be extracted from the noisy signal. It is noted that the probability with which the noise takes on admissible and critical values is an indicator of changes in the technical condition of tunnels. Algorithms have been developed for calculating the probabilities of the noise values getting in the given intervals. These probabilities are stored as reference sets for the initiation of tunnel defects. After the training has been carried out, the values of the probabilities with which the noise takes on the given values at different time instants are matched to the type of defect and one of the possible technical states: serviceable, operational, partially operational, inoperable; pre-emergency; emergency, etc. It is also shown that the differences in the probabilities with which the noise takes on the same values at different times are indicators of the dynamics of changes in the malfunction in the tunnels. A database ofinformative attributes of the intensity of the development of failures is also created in the paper. For this database, the indicators of the dynamics of the development of a defect are determined, such as insignificant, slow, significant, intensive.