On An Entropy Estimator Based On a Non-parametric Density Estimator For Non-negative Data

In the recent decades, entropy has become more and more essential in statistics and machine learning. It features in many applications involving data transmission, cryptography, signal processing, network theory, bio-informatics, and so on. A large number of estimators for entropy have been proposed in the past ten years. Here we focus on entropy estimation for non-negative random variables. Specifically, the use of entropy estimator based on Poisson-weights density estimator is found to be of interest. We establish some asymptotic properties of the resulting estimators and present a simulation study comparing these with well known estimators in literature

Some Fluctuation Results Related to Draw-down Times for Spectrally Negative Levy processes And On Estimation of Entropy and residual Entropy for Nonnegative Random Variable

Part I In this thesis, we first introduce and review some fluctuation theory of Levy processes, especially for general spectrally negative Levy processes and for spectrally negative Levy taxed processes. Then we consider a more realistic model by introducing draw-down time, which is the first time a process falls below a predetermined draw-down level which is a function of the running maximum. Particularly, we present the expressions for the classical two-sided exit problems for these processes with draw-down times in terms of scale functions. We also find the expressions for the discounted present values of tax payments with draw-down time in place of ruin time. Finally, we obtain the expression of the occupation times for the general spectrally negative Levy processes to spend in draw-down interval killed on either exiting a fix upper level or a draw-down lower level. Part II Entropy has become more and more essential in statistics and machine learning. A large number of its applications can be found in data transmission, cryptography, signal processing, network theory, bio-informatics, and so on. Therefore, the question of entropy estimation comes naturally. Generally, if we consider the entropy of a random variable knowing that it has survived up to time $t$, then it is defined as the residual entropy. In this thesis we focus on entropy and residual entropy estimation for nonnegative random variable. We first present a quick review on properties of popular existing estimators. Then we propose some candidates for entropy and residual entropy estimator along with simulation study and comparison among estimators

Some Fluctuation Identities of Hyper-Exponential Jump-Diffusion Processes

Meromorphic L´evy processes have attracted the attention of a lot of researchers recently due to its special structure of the Wiener-Hopf factors as rational functions of infinite degree written in terms of poles and roots of the Laplace exponent, all of which are real numbers. With these Wiener-Hopf factors in hand, we can explicitly derive the expression of fluctuation identities that concern the first passage problems for finite and infinite intervals for the meromorphic L´evy process and the resulting process reflected at its infimum. In this thesis, we consider some fluctuation identities of some classes of meromorphic jump-diffusion processes with either the double exponential jumps or more general the hyper-exponential jumps. We study solutions to the one-sided and two-sided exit problems, and potential measure of the process killed on exiting a finite or infinite intervals. Also, we obtain some results to the process reflected at its infimum

A Numerical Study of Entropy and Residual Entropy Estimators Based on Smooth Density Estimators for Non-negative Random Variables

In this paper, we are interested in the entropy of a non-negative random variable. Since the underlying probability density function is unknown, we propose the use of Poisson smoothed histogram density estimator in order to estimate the entropy. To study the performance of our estimator, we run simulations on a wide range of densities and compare our entropy estimators with the existing estimators that based on different approaches such as spacing estimators. Furthermore, we extend our study to residual entropy estimators which is the entropy of a random variable given that it has been survived up to time t

Factors Affecting Consumers’ Impulsive Purchasing Behavior in Circle K Convenience Stores in Hanoi, Vietnam

Impulsive purchasing behavior has been observed as one of the important studies conducted by marketers and researchers, as impulse buying has become a prevalent phenomenon in every retail format. The study was conducted to assess factors affecting consumers’ impulsive purchasing behavior in Circle K convenience stores in Hanoi, Vietnam. After reviewing a group of previous studies, the authors indicated 05 factors that affected consumers' impulsive purchasing behavior including impulsiveness, instant gratification, visual appeal, promotions and money availability. The study had selected 05 experts in the field of economics to conduct the expert interview. Moreover, the research team had also handed out the questionnaire and received 310 observations. Specifically, Impulsiveness had the strongest influence on the impulsive purchasing behavior of Circle K’s consumers in Hanoi. Keywords: factors, Impulsive purchasing behavior, Circle K convenience stores DOI: 10.7176/JESD/14-8-03 Publication date: April 30th 2023

A Large-Scale Study of a Sleep Tracking and Improving Device with Closed-loop and Personalized Real-time Acoustic Stimulation

Various intervention therapies ranging from pharmaceutical to hi-tech tailored solutions have been available to treat difficulty in falling asleep commonly caused by insomnia in modern life. However, current techniques largely remain ill-suited, ineffective, and unreliable due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, an ability to keep people asleep during the night, and a large-scale effectiveness evaluation. Here, we introduce a novel sleep aid system, called Earable, that can continuously sense multiple head-based physiological signals and simultaneously enable closed-loop auditory stimulation to entrain brain activities in time for effective sleep promotion. We develop the system in a lightweight, comfortable, and user-friendly headband with a comprehensive set of algorithms and dedicated own-designed audio stimuli. We conducted multiple protocols from 883 sleep studies on 377 subjects (241 women, 119 men) wearing either a gold-standard device (PSG), Earable, or both concurrently. We demonstrate that our system achieves (1) a strong correlation (0.89 +/- 0.03) between the physiological signals acquired by Earable and those from the gold-standard PSG, (2) an 87.8 +/- 5.3% agreement on sleep scoring using our automatic real-time sleep staging algorithm with the consensus scored by three sleep technicians, and (3) a successful non-pharmacological stimulation alternative to effectively shorten the duration of sleep falling by 24.1 +/- 0.1 minutes. These results show that the efficacy of Earable exceeds existing techniques in intentions to promote fast falling asleep, track sleep state accurately, and achieve high social acceptance for real-time closed-loop personalized neuromodulation-based home sleep care.Comment: 33 pages, 8 figure

Chemical profile and antibacterial activity of acetone extract of Homalomena cochinchinensis Engl. (Araceae)

Homalomena cochinchinensis Engl. is a rare species which is found in Southern China, Cambodia, Laos and Vietnam and its chemical constituents and bioactivity have not been determined yet. In this study, we identified 32 and 38 compounds in acetone extracts of H. cochinchinensis aerial part and rhizome, respectively via gas chromatography mass spectrometry (GC/MS). The main constituents of acetone extract of the aerial part were 3-((4Z,7Z)-Heptadeca-4,7-dien-1-yl)phenol (18.73%); cis-9,cis-12-Octadecadienoic acid (12.04%); linolenic acid (11.08%); n-Hexadecanoic acid (10.13%); (Z)-3-(Heptadec-10-en-1-yl)phenol (7.09%); ?-Sitosterol (5.58%) and linalool (5.56%). On the other hand, acetone extract of rhizome contained linalool (28.42%); 1,2,3-Propanetriol, 1-acetate (10.13%); 3-((4Z,7Z)-Heptadeca-4,7-dien-1-yl)phenol (5.28%); 3-Buten-2-one, 3-methyl-4-(1,3,3-trimethyl-7-oxabicyclo[4.1.0]heptan-1-yl)- (5.28%) and 4-(2,6,6-Trimethyl-cyclohex-1-enyl)-butyric acid (4.54%). Furthermore, this study has also proved the antibacterial activity of acetone extracts from the aerial part and the rhizome of this species for the first time using disk diffusion method. The results showed that the extract of the aerial part could inhibit the growth of 5 out of a total 6 bacterial strains, including Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Salmonella enteritidis and Staphylococcus aureus; while the susceptible strains to the rhizome extract were 5 strains, such as B. cereus, E. coli, P. aeruginosa, Salmonella typhimurium and S. aureus. The findings suggest the further application of this species in pharmacology and medicine

A comprehensive study on the efficacy of a wearable sleep aid device featuring closed-loop real-time acoustic stimulation

Difficulty falling asleep is one of the typical insomnia symptoms. However, intervention therapies available nowadays, ranging from pharmaceutical to hi-tech tailored solutions, remain ineffective due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, and an ability to keep people asleep during the night. This paper aims to enhance the efficacy of such an intervention by proposing a novel sleep aid system that can sense multiple physiological signals continuously and simultaneously control auditory stimulation to evoke appropriate brain responses for fast sleep promotion. The system, a lightweight, comfortable, and user-friendly headband, employs a comprehensive set of algorithms and dedicated own-designed audio stimuli. Compared to the gold-standard device in 883 sleep studies on 377 subjects, the proposed system achieves (1) a strong correlation (0.89 ± 0.03) between the physiological signals acquired by ours and those from the gold-standard PSG, (2) an 87.8% agreement on automatic sleep scoring with the consensus scored by sleep technicians, and (3) a successful non-pharmacological real-time stimulation to shorten the duration of sleep falling by 24.1 min. Conclusively, our solution exceeds existing ones in promoting fast falling asleep, tracking sleep state accurately, and achieving high social acceptance through a reliable large-scale evaluation

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type