scholarly journals Neurophysiological Characterization of Posteromedial Hypothalamus in Anaesthetized Patients

2021 ◽  
Vol 12 (1) ◽  
pp. 43
Author(s):  
Jesús Pastor ◽  
Lorena Vega-Zelaya ◽  
Elena Martín-Abad
Keyword(s):  
General Anesthesia ◽  
Action Potentials ◽  
Mass Function ◽  
Probability Mass Function ◽  
Pooled Data ◽  
Potential Map ◽  
Probability Mass ◽  
First Time ◽  
Deep Brain

Deep brain stimulation (DBS) requires a precise localization, which is especially difficult at the hypothalamus, because it is usually performed in anesthetized patients. We aimed to characterize the neurophysiological properties posteromedial hypothalamus (PMH), identified by the best neurophysiological response to electrical stimulation. We obtained microelectrode recordings from four patients with intractable aggressivity operated under general anesthesia. We pooled data from 1.5 mm at PMH, 1.5 mm upper (uPMH) and 1.5 mm lower (lPMH). We analyzed 178 units, characterized by the mean action potential (mAP). Only 11% were negative. We identified the next types of units: P1N1 (30.9%), N1P1N2 (29.8%), P1P2N1 (16.3%), N1P1 and N1N2P1 (6.2%) and P1N1P2 (5.0%). Besides, atypical action potentials (amAP) were recorded in 11.8%. PMH was highly different in cell composition from uPMH and lPMH, exhibiting also a higher percentage of amAP. Different kinds of cells shared similar features for the three hypothalamic regions. Although features for discharge pattern did not show region specificity, the probability mass function of inter-spike interval were different for all the three regions. Comparison of the same kind of mAP with thalamic neurons previously published demonstrate that most of cells are different for derivatives, amplitude and/or duration of repolarization and depolarization phases and also for the first phase, demonstrating a highly specificity for both brain centers. Therefore, the different properties described for PMH can be used to positively refine targeting, even under general anesthesia. Besides, we describe by first time the presence of atypical extracellular action potentials.

scholarly journals Modified Recursions for a Class of Compound Distributions

1996 ◽  
Vol 26 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Karl-Heinz Waldmann
Keyword(s):  
Distribution Function ◽  
Cumulative Distribution Function ◽  
Mass Function ◽  
Cumulative Distribution ◽  
Probability Mass Function ◽  
Initial Value ◽  
Compound Distributions ◽  
Claim Frequency ◽  
Probability Mass ◽  
Stop Loss

AbstractRecursions are derived for a class of compound distributions having a claim frequency distribution of the well known (a,b)-type. The probability mass function on which the recursions are usually based is replaced by the distribution function in order to obtain increasing iterates. A monotone transformation is suggested to avoid an underflow in the initial stages of the iteration. The faster increase of the transformed iterates is diminished by use of a scaling function. Further, an adaptive weighting depending on the initial value and the increase of the iterates is derived. It enables us to manage an arbitrary large portfolio. Some numerical results are displayed demonstrating the efficiency of the different methods. The computation of the stop-loss premiums using these methods are indicated. Finally, related iteration schemes based on the cumulative distribution function are outlined.

Quantification of Low-Cycle Fatigue Life for a Gas Turbine Compressor Vane Carrier Under Varying Operating Conditions

2020 ◽  
Author(s):  
Zixi Han ◽  
Zixian Jiang ◽  
Sophie Ehrt ◽  
Mian Li
Keyword(s):  
Low Cycle Fatigue ◽  
Computational Cost ◽  
Mass Function ◽  
Operating Conditions ◽  
Probability Mass Function ◽  
Assessment Approach ◽  
Probability Mass ◽  
Gas Turbine Compressor ◽  
Operating Cycles ◽  
Operational Data

Abstract The design of a gas turbine compressor vane carrier (CVC) should meet mechanical integrity requirements on, among others, low-cycle fatigue (LCF). The number of cycles to the LCF failure is the result of cyclic mechanical and thermal strain effects caused by operating conditions on the components. The conventional LCF assessment is usually based on the assumption on standard operating cycles — supplemented by the consideration of predefined extreme operations and safety factors to compensate a potential underestimate on the LCF damage caused by multiple reasons such as non-standard operating cycles. However, real operating cycles can vary significantly from those standard ones considered in the conventional methods. The conventional prediction of LCF life can be very different from real cases, due to the included safety margins. This work presents a probabilistic method to estimate the distributions of the LCF life under varying operating conditions using operational fleet data. Finite element analysis (FEA) results indicate that the first ramp-up loading in each cycle and the turning time before hot-restart cycles are two predominant contributors to the LCF damage. A surrogate model of LCF damage has been built with regard to these two features to reduce the computational cost of FEA. Miner’s rule is applied to calculate the accumulated LCF damage on the component and then obtain the LCF life. The proposed LCF assessment approach has two special points. First, a new data processing technique inspired by the cumulative sum (CUSUM) control chart is proposed to identify the first ramp-up period of each cycle from noised operational data. Second, the probability mass function of the LCF life for a CVC is estimated using the sequential convolution of the single-cycle damage distribution obtained from operational data. The result from the proposed method shows that the mean value of the LCF life at a critical location of the CVC is significantly larger than the calculated result from the deterministic assessment, and the LCF lives for different gas turbines of the same class are also very different. Finally, to avoid high computational cost of sequential convolution, a quick approximation approach for the probability mass function of the LCF life is given. With the capability of dealing with varying operating conditions and noises in the operational data, the enhanced LCF assessment approach proposed in this work provides a probabilistic reference both for reliability analysis in CVC design, and for predictive maintenance in after-sales service.

ON SEVERAL PROPERTIES OF A CLASS OF PREFERENTIAL ATTACHMENT TREES—PLANE-ORIENTED RECURSIVE TREES

2020 ◽  
pp. 1-19
Author(s):  
Panpan Zhang
Keyword(s):  
Continuous Time ◽  
Preferential Attachment ◽  
Mass Function ◽  
Probability Mass Function ◽  
Zagreb Index ◽  
Exact Probability ◽  
Probability Mass ◽  
Proper Scaling ◽  
Recursive Trees ◽  
Degree Variable

In this paper, several properties of a class of trees presenting preferential attachment phenomenon—plane-oriented recursive trees (PORTs) are uncovered. Specifically, we investigate the degree profile of a PORT by determining the exact probability mass function of the degree of a node with a fixed label. We compute the expectation and the variance of degree variable via a Pólya urn approach. In addition, we study a topological index, Zagreb index, of this class of trees. We calculate the exact first two moments of the Zagreb index (of PORTs) by using recurrence methods. Lastly, we determine the limiting degree distribution in PORTs that grow in continuous time, where the embedding is done in a Poissonization framework. We show that it is exponential after proper scaling.

scholarly journals A Novel Belief Entropy for Measuring Uncertainty in Dempster-Shafer Evidence Theory Framework Based on Plausibility Transformation and Weighted Hartley Entropy

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 163 ◽  
Author(s):  
Qian Pan ◽  
Deyun Zhou ◽  
Yongchuan Tang ◽  
Xiaoyang Li ◽  
Jichuan Huang
Keyword(s):  
Evidence Theory ◽  
Mass Function ◽  
Probability Mass Function ◽  
Main Work ◽  
Basic Probability ◽  
Open Issue ◽  
Belief Entropy ◽  
Probability Mass ◽  
Hartley Entropy ◽  
Theory Framework

Dempster-Shafer evidence theory (DST) has shown its great advantages to tackle uncertainty in a wide variety of applications. However, how to quantify the information-based uncertainty of basic probability assignment (BPA) with belief entropy in DST framework is still an open issue. The main work of this study is to define a new belief entropy for measuring uncertainty of BPA. The proposed belief entropy has two components. The first component is based on the summation of the probability mass function (PMF) of single events contained in each BPA, which are obtained using plausibility transformation. The second component is the same as the weighted Hartley entropy. The two components could effectively measure the discord uncertainty and non-specificity uncertainty found in DST framework, respectively. The proposed belief entropy is proved to satisfy the majority of the desired properties for an uncertainty measure in DST framework. In addition, when BPA is probability distribution, the proposed method could degrade to Shannon entropy. The feasibility and superiority of the new belief entropy is verified according to the results of numerical experiments.

scholarly journals Neurophysiological Characterization of Thalamic Nuclei in Epileptic Anaesthetized Patients

2019 ◽  
Vol 9 (11) ◽  
pp. 312 ◽  
Author(s):  
Vega-Zelaya ◽  
Torres ◽  
Navas ◽  
Pastor
Keyword(s):  
General Anesthesia ◽  
Interspike Interval ◽  
The Other ◽  
Electrode Placement ◽  
Thalamic Nuclei ◽  
Mean Frequency ◽  
The Mean ◽  
Tonic Pattern ◽  
Deep Brain

Deep brain stimulation (DBS) requires precise localization, which is especially difficult at the thalamus, and even more difficult in anesthetized patients. We aimed to characterize the neurophysiological properties of the ventral intermediate (V.im), ventral caudal (V.c), and centromedian parvo (Ce.pc) and the magnocellular (Ce.mc) thalamic nuclei. We obtained microelectrode recordings from five patients with refractory epilepsy under general anesthesia. Somatosensory evoked potentials recorded by microelectrodes were used to identify the V.c nucleus. Trajectories were reconstructed off-line to identify the nucleus recorded, and the amplitude of the action potential (AP) and the tonic (i.e., mean frequency, density, probability of interspike interval) and phasic (i.e., burst index, pause index, and pause ratio) properties of the pattern discharges were analyzed. The Mahalanobis metric was used to evaluate the similarity of the patterns. The mean AP amplitude was higher for the V.im nucleus (172.7 ± 7.6 µV) than for the other nuclei, and the mean frequency was lower for the Ce.pc nucleus (7.2 ± 0.8 Hz) and higher for the V.c nucleus (11.9 ± 0.8 Hz) than for the other nuclei. The phasic properties showed a bursting pattern for the V.c nucleus and a tonic pattern for the centromedian and V.im nuclei. The Mahalanobis distance was the shortest for the V.im/V.c and Ce.mp/Ce.pc pairs. Therefore, the different properties of the thalamic nuclei, even for patients under general anesthesia, can be used to positively define the recorded structure, improving the exactness of electrode placement in DBS.

scholarly journals Accurate and Practical Energy Detection over α-μ Fading Channels

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 754 ◽  
Author(s):  
Kaitian Cao ◽  
Ping Qian ◽  
Jing An ◽  
Li Wang
Keyword(s):  
Sample Size ◽  
Fading Channels ◽  
Small Sample Size ◽  
Energy Detection ◽  
Mass Function ◽  
Detection Performance ◽  
Small Sample ◽  
Closed Form Expression ◽  
Probability Mass Function ◽  
Probability Mass

In this study, a novel and exact closed-form expression for detection probability of energy detection (ED) in terms of Meijer’s G-function over α-μ generalized fading channels was derived. It is more accurate and practical than the existing exact expressions and has wide application prospects in the performance evaluations in various areas of wireless communications, especially in the wireless sensor network (WSN) and the cognitive radio network (CRN). Furthermore, an exact and simple analytical solution for the sample size meeting the desired detection performance in terms of the probability mass function of a Poisson distribution was also solved. Simulations verified the detection performance and accuracy of our derived expressions with a small sample size compared to the existing exact expressions and approximations.

Analysis of generalized Poisson distributions associated with higher Landau levels

2015 ◽  
Vol 18 (04) ◽  
pp. 1550028 ◽  
Author(s):  
Nizar Demni ◽  
Zouhair Mouayn
Keyword(s):  
Probability Distribution ◽  
Characteristic Function ◽  
Poisson Distribution ◽  
Landau Level ◽  
Mass Function ◽  
Probability Mass Function ◽  
Lévy Measure ◽  
Infinitely Divisible ◽  
Generalized Poisson ◽  
Probability Mass

To a higher Landau level corresponds a generalized Poisson distribution arising from generalized coherent states. In this paper, we write down the atomic decomposition of this probability distribution and express its probability mass function as a [Formula: see text]-hypergeometric polynomial. Then, we prove that it is not infinitely divisible in contrast with the Poisson distribution corresponding to the lowest Landau level. We also derive a Lévy–Khintchine-type representation of its characteristic function when the latter does not vanish and deduce that the representative measure is a quasi-Lévy measure. By considering the total variation of this last measure, we obtain the characteristic function of a new infinitely divisible discrete probability distribution for which we also compute the probability mass function.

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