Passively Q-switched side pumped monolithic ring laser

Disclosed herein are systems and methods for generating a side-pumped passively Q-switched non-planar ring oscillator. The method introduces a laser into a cavity of a crystal, the cavity having a round-trip path formed by a reflection at a dielectrically coated front surface, a first internal reflection at a first side surface of the crystal at a non-orthogonal angle with the front, a second internal reflection at a top surface of the crystal, and a third internal reflection at a second side surface of the crystal at a non-orthogonal angle with the front. The method side pumps the laser at the top or bottom surface with a side pump diode array beam and generates an output laser emanating at a location on the front surface. The design can include additional internal reflections to increase interaction with the side pump. Waste heat may be removed by mounting the crystal to a heatsink

Inflation from Geometrical Tachyons

We propose an alternative formulation of tachyon inflation using the geometrical tachyon arising from the time dependent motion of a BPS $D3$-brane in the background geometry due to $k$ parallel $NS$5-branes arranged around a ring of radius $R$. Due to the fact that the mass of this geometrical tachyon field is $\sqrt{2/k}$ times smaller than the corresponding open-string tachyon mass, we find that the slow roll conditions for inflation and the number of e-foldings can be satisfied in a manner that is consistent with an effective 4-dimensional model and with a perturbative string coupling. We also show that the metric perturbations produced at the end of inflation can be sufficiently small and do not lead to the inconsistencies that plague the open string tachyon models. Finally we argue for the existence of a minimum of the geometrical tachyon potential which could give rise to a traditional reheating mechanism.Comment: Latex, 20 pages, 4 figures; correction of algebraic errors in section 5 concerning the tachyon potential near its minimum. Conclusions unchange

A study on fault diagnosis in nonlinear dynamic systems with uncertainties

In this draft, fault diagnosis in nonlinear dynamic systems is addressed. The objective of this work is to establish a framework, in which not only model-based but also data-driven and machine learning based fault diagnosis strategies can be uniformly handled. Instead of the well-established input-output and the associated state space models, stable image and kernel representations are adopted in our work as the basic process model forms. Based on it, the nominal system dynamics can then be modelled as a lower-dimensional manifold embedded in the process data space. To achieve a reliable fault detection as a classification problem, projection technique is a capable tool. For nonlinear dynamic systems, we propose to construct projection systems in the well-established framework of Hamiltonian systems and by means of the normalised image and kernel representations. For nonlinear dynamic systems, process data form a non-Euclidean space. Consequently, the norm-based distance defined in Hilbert space is not suitable to measure the distance from a data vector to the manifold of the nominal dynamics. To deal with this issue, we propose to use a Bregman divergence, a measure of difference between two points in a space, as a solution. Moreover, for our purpose of achieving a performance-oriented fault detection, the Bregman divergences adopted in our work are defined by Hamiltonian functions. This scheme not only enables to realise the performance-oriented fault detection, but also uncovers the information geometric aspect of our work. The last part of our work is devoted to the kernel representation based fault detection and uncertainty estimation that can be equivalently used for fault estimation. It is demonstrated that the projection onto the manifold of uncertainty data, together with the correspondingly defined Bregman divergence, is also capable for fault detection

Investor Overconfidence and Trading Activity in the Asia Pacific REIT Markets

Overconfidence is one of the most robust behavioral anomalies in financial markets. By attributing investment gains to their ability, investors become overconfident and trade aggressively in subsequent periods. Evidence from stock markets shows that overconfidence leads to excessive trading and, subsequently, inferior investment performance. However, studies on overconfidence effect are lacking in the real estate sector, which is particularly true for Asia Pacific real estate investment trust (REIT) markets. Thus, this study examines the overconfidence effect in six Asia Pacific REIT markets, namely, Australia, Hong Kong, Japan, Singapore, South Korea, and Taiwan. The study finds that the overconfidence effect is more conspicuous during market boom periods or in inefficient market conditions. In addition, simulation analysis demonstrates that overconfidence could lead to rather large volumes of excessive trading activities in certain markets. Findings are robust across the alternative measures of control variables. Moreover, the policy implications of the research are also discussed

Glycolytic Reprogramming Through PCK2 Regulates Tumor Initiation of Prostate Cancer Cells

Tumor-initiating cells (TICs) play important roles in tumor progression and metastasis. Identifying the factors regulating TICs may open new avenues in cancer therapy. Here, we show that TIC-enriched prostate cancer cell clones use more glucose and secrete more lactate than TIC-low clones. We determined that elevated levels of phosphoenolpyruvate carboxykinase isoform 2 (PCK2) are critical for the metabolic switch and the maintenance of TICs in prostate cancer. Information from prostate cancer patient databases revealed that higher PCK2 levels correlated with more aggressive tumors and lower survival rates. PCK2 knockdown resulted in low TIC numbers, increased cytosolic acetyl-CoA and cellular protein acetylation. Our data suggest PCK2 promotes tumor initiation by lowering acetyl-CoA level through reducing the mitochondrial tricarboxylic acid (TCA) cycle. Thus, PCK2 is a potential therapeutic target for aggressive prostate tumors

Control theoretically explainable application of autoencoder methods to fault detection in nonlinear dynamic systems

This paper is dedicated to control theoretically explainable application of autoencoders to optimal fault detection in nonlinear dynamic systems. Autoencoder-based learning is a standard method of machine learning technique and widely applied for fault (anomaly) detection and classification. In the context of representation learning, the so-called latent (hidden) variable plays an important role towards an optimal fault detection. In ideal case, the latent variable should be a minimal sufficient statistic. The existing autoencoder-based fault detection schemes are mainly application-oriented, and few efforts have been devoted to optimal autoencoder-based fault detection and explainable applications. The main objective of our work is to establish a framework for learning autoencoder-based optimal fault detection in nonlinear dynamic systems. To this aim, a process model form for dynamic systems is firstly introduced with the aid of control and system theory, which also leads to a clear system interpretation of the latent variable. The major efforts are devoted to the development of a control theoretical solution to the optimal fault detection problem, in which an analog concept to minimal sufficient statistic, the so-called lossless information compression, is introduced for dynamic systems and fault detection specifications. In particular, the existence conditions for such a latent variable are derived, based on which a loss function and further a learning algorithm are developed. This learning algorithm enables optimally training of autoencoders to achieve an optimal fault detection in nonlinear dynamic systems. A case study on three-tank system is given at the end of this paper to illustrate the capability of the proposed autoencoder-based fault detection and to explain the essential role of the latent variable in the proposed fault detection system

Replay Attack Detection Based on Parity Space Method for Cyber-Physical Systems

The replay attack detection problem is studied from a new perspective based on parity space method in this paper. The proposed detection methods have the ability to distinguish system fault and replay attack, handle both input and output data replay, maintain certain control performance, and can be implemented conveniently and efficiently. First, the replay attack effect on the residual is derived and analyzed. The residual change induced by replay attack is characterized explicitly and the detection performance analysis based on two different test statistics are given. Second, based on the replay attack effect characterization, targeted passive and active design for detection performance enhancement are proposed. Regarding the passive design, four optimization schemes regarding different cost functions are proposed with optimal parity matrix solutions, and the unified solution to the passive optimization schemes is obtained; the active design is enabled by a marginally stable filter so as to enlarge the replay attack effect on the residual for detection. Simulations and comparison studies are given to show the effectiveness of the proposed methods

In-Flight Performance of the Mercury Laser Altimeter Laser Transmitter

The Mercury Laser Altimeter (MLA) is one of the payload instruments on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft, which was launched on August 3, 2004. MLA maps Mercury's shape and topographic landforms and other surface characteristics using a diode-pumped solid-state laser transmitter and a silicon avalanche photodiode receiver that measures the round-trip time of individual laser pulses. The laser transmitter has been operating nominally during planetary flyby measurements and in orbit about Mercury since March 2011. In this paper, we review the MLA laser transmitter telemetry data and evaluate the performance of solid-state lasers under extended operation in a space environment