Extreme eigenvalues of sample covariance matrices under generalized elliptical models with applications

We consider the extreme eigenvalues of the sample covariance matrix $Q=YY^*$ under the generalized elliptical model that $Y=\Sigma^{1/2}XD.$ Here $\Sigma$ is a bounded $p \times p$ positive definite deterministic matrix representing the population covariance structure, $X$ is a $p \times n$ random matrix containing either independent columns sampled from the unit sphere in $\mathbb{R}^p$ or i.i.d. centered entries with variance $n^{-1},$ and $D$ is a diagonal random matrix containing i.i.d. entries and independent of $X.$ Such a model finds important applications in statistics and machine learning. In this paper, assuming that $p$ and $n$ are comparably large, we prove that the extreme edge eigenvalues of $Q$ can have several types of distributions depending on $\Sigma$ and $D$ asymptotically. These distributions include: Gumbel, Fr\'echet, Weibull, Tracy-Widom, Gaussian and their mixtures. On the one hand, when the random variables in $D$ have unbounded support, the edge eigenvalues of $Q$ can have either Gumbel or Fr\'echet distribution depending on the tail decay property of $D.$ On the other hand, when the random variables in $D$ have bounded support, under some mild regularity assumptions on $\Sigma,$ the edge eigenvalues of $Q$ can exhibit Weibull, Tracy-Widom, Gaussian or their mixtures. Based on our theoretical results, we consider two important applications. First, we propose some statistics and procedure to detect and estimate the possible spikes for elliptically distributed data. Second, in the context of a factor model, by using the multiplier bootstrap procedure via selecting the weights in $D,$ we propose a new algorithm to infer and estimate the number of factors in the factor model. Numerical simulations also confirm the accuracy and powerfulness of our proposed methods and illustrate better performance compared to some existing methods in the literature.Comment: 90 pages, 6 figures, some typos are correcte

Tourism crises and impacts on destinations: a systematic review of the tourism and hospitality literature

Tourism crises are important events affecting the development of destinations. However, the academic community lacks adequate knowledge from the accumulated literature on the classification attributes, spatial distribution, and impact structure of global tourism crises. This research analyzed 302 articles related to tourism crises from 1991 to 2020 drawn from the Social Sciences Citation Index database. Bibliometric and content analyses were conducted to identify the event types, regional distribution, impact structure, and synergistic factors of tourism crises. The results showed that the extant research on tourism crises has event-driven characteristics. The types of tourism crises are diverse and have multiple sub-categories. The tourism crises featured in academic research are mainly events affecting Asia, Europe and North America, reflecting their real-world distribution. The impacts of tourism crises on destinations are at three levels: macro, meso, and micro. Synergistic factors can enhance or weaken the degree of crisis impacts, which include positive, negative and interactive factors. Research on tourism crises has substantial future scope and this investigation puts forward an agenda for this work

Detecting number processing and mental calculation in patients with disorders of consciousness using a hybrid brain-computer interface system

Background: For patients with disorders of consciousness such as coma, a vegetative state or a minimally conscious state, one challenge is to detect and assess the residual cognitive functions in their brains. Number processing and mental calculation are important brain functions but are difficult to detect in patients with disorders of consciousness using motor response-based clinical assessment scales such as the Coma Recovery Scale-Revised due to the patients' motor impairments and inability to provide sufficient motor responses for number- and calculation-based communication. Methods: In this study, we presented a hybrid brain-computer interface that combines P300 and steady state visual evoked potentials to detect number processing and mental calculation in Han Chinese patients with disorders of consciousness. Eleven patients with disorders of consciousness who were in a vegetative state (n = 6) or in a minimally conscious state (n = 3) or who emerged from a minimally conscious state (n = 2) participated in the brain-computer interface-based experiment. During the experiment, the patients with disorders of consciousness were instructed to perform three tasks, i.e., number recognition, number comparison, and mental calculation, including addition and subtraction. In each experimental trial, an arithmetic problem was first presented. Next, two number buttons, only one of which was the correct answer to the problem, flickered at different frequencies to evoke steady state visual evoked potentials, while the frames of the two buttons flashed in a random order to evoke P300 potentials. The patients needed to focus on the target number button (the correct answer). Finally, the brain-computer interface system detected P300 and steady state visual evoked potentials to determine the button to which the patients attended, further presenting the results as feedback. Results: Two of the six patients who were in a vegetative state, one of the three patients who were in a minimally conscious state, and the two patients that emerged from a minimally conscious state achieved accuracies significantly greater than the chance level. Furthermore, P300 potentials and steady state visual evoked potentials were observed in the electroencephalography signals from the five patients. Conclusions: Number processing and arithmetic abilities as well as command following were demonstrated in the five patients. Furthermore, our results suggested that through brain-computer interface systems, many cognitive experiments may be conducted in patients with disorders of consciousness, although they cannot provide sufficient behavioral responses. © 2015 Li et al

DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics

The Federated Learning (FL) paradigm is known to face challenges under heterogeneous client data. Local training on non-iid distributed data results in deflected local optimum, which causes the client models drift further away from each other and degrades the aggregated global model's performance. A natural solution is to gather all client data onto the server, such that the server has a global view of the entire data distribution. Unfortunately, this reduces to regular training, which compromises clients' privacy and conflicts with the purpose of FL. In this paper, we put forth an idea to collect and leverage global knowledge on the server without hindering data privacy. We unearth such knowledge from the dynamics of the global model's trajectory. Specifically, we first reserve a short trajectory of global model snapshots on the server. Then, we synthesize a small pseudo dataset such that the model trained on it mimics the dynamics of the reserved global model trajectory. Afterward, the synthesized data is used to help aggregate the deflected clients into the global model. We name our method Dynafed, which enjoys the following advantages: 1) we do not rely on any external on-server dataset, which requires no additional cost for data collection; 2) the pseudo data can be synthesized in early communication rounds, which enables Dynafed to take effect early for boosting the convergence and stabilizing training; 3) the pseudo data only needs to be synthesized once and can be directly utilized on the server to help aggregation in subsequent rounds. Experiments across extensive benchmarks are conducted to showcase the effectiveness of Dynafed. We also provide insights and understanding of the underlying mechanism of our method

Osteoporosis guidelines on TCM drug therapies: a systematic quality evaluation and content analysis

ObjectiveThe aims of this study were to evaluate the quality of osteoporosis guidelines on traditional Chinese medicine (TCM) drug therapies and to analyze the specific recommendations of these guidelines.MethodsWe systematically collected guidelines, evaluated the quality of the guidelines using the Appraisal of Guidelines Research and Evaluation (AGREE) II tool, and summarized the recommendations of TCM drug therapies using the Patient-Intervention-Comparator-Outcome (PICO) model as the analysis framework.Results and conclusionsA total of 20 guidelines were included. Overall quality evaluation results revealed that four guidelines were at level A, four at level B, and 12 at level C, whose quality needed to be improved in the domains of “stakeholder involvement”, “rigor of development”, “applicability” and “editorial independence”. Stratified analysis suggested that the post-2020 guidelines were significantly better than those published before 2020 in the domains of “scope and purpose”, “stakeholder involvement” and “editorial independence”. Guidelines with evidence systems were significantly better than those without evidence systems in terms of “stakeholder involvement”, “rigor of development”, “clarity of presentation” and “applicability”. The guidelines recommended TCM drug therapies for patients with osteopenia, osteoporosis and osteoporotic fracture. Recommended TCM drugs were mainly Chinese patent medicine alone or combined with Western medicine, with the outcome mainly focused on improving bone mineral density (BMD)

Effect of intelligent logistics policy on shareholder value: evidence from Chinese logistics companies

This paper empirically investigates the effects of intelligent logistics policies (ILPs) on shareholder value of the 149 listed logistics companies from 2013-2018 in China. The research shows that ILPs will result in a positive stock market reaction, and this effect is increasing along with the increase of policy contents related to intelligent logistics or the decrease of company service breadth. The market reaction will be affected by the way that policies are issued and type of company. The logistics service providers are more positive when their financial performances are better, while the opposite result is observed for logistics equipment manufacturers

Ion Channel Targeted Mechanisms of Anti-arrhythmic Chinese Herbal Medicine Xin Su Ning

Xin Su Ning (XSN) is a China patented and certified herbal medicine used to treat premature ventricular contractions (PVCs) since 2005. A recent completed clinical trial of 861 patients showed that XSN had similar PVC inhibition rate to the class I antiarrhythmic drug mexiletine, at 65.85% for XSN and 63.10% for mexiletine. We have previously reported that XSN prolongs action potential duration (APD) and suppresses action potential amplitude (APA) of the cardiac ventricular myocytes. In this report we aim to reveal the effect of XSN on the ionic channels that govern APD and APA, which would help to explain the cellular electrophysiological mechanism of XSN. Our main findings are: (1) On ECG recorded in isolated rat, in the presence of XSN the amplitude of R wave was significantly decreased and the amplitude of T wave was increased significantly; (2) XSN blocked hNaV1.5 channel stably transfected cell line in a dose-dependent manner with an IC50 of 0.18 ± 0.02 g/L; and (3) XSN suppresses hERG channels in a dose-dependent manner with an IC50 of 0.34 ± 0.01 g/L. In conclusion, the clinical antiarrhythmic efficacy of XSN is based on its class I and Class III antiarrhythmic properties by suppression hNaV1.5 channel and hERG channels, which are directly responsible for XSN’s effect on APA suppression and APD prolongation