Performance of Photosensors in the PandaX-I Experiment

We report the long term performance of the photosensors, 143 one-inch R8520-406 and 37 three-inch R11410-MOD photomultipliers from Hamamatsu, in the first phase of the PandaX dual-phase xenon dark matter experiment. This is the first time that a significant number of R11410 photomultiplier tubes were operated in liquid xenon for an extended period, providing important guidance to the future large xenon-based dark matter experiments.Comment: v3 as accepted by JINST with modifications based on reviewers' comment

Doping dependence of heat transport in the iron-arsenide superconductor Ba(Fe1−x_{1-x}Cox_x)2_2As2_2: from isotropic to strongly kk-dependent gap structure

The temperature and magnetic field dependence of the in-plane thermal conductivity $\kappa$ of the iron-arsenide superconductor Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$ was measured down to $T \simeq 50$ mK and up to $H = 15$ T as a function of Co concentration $x$ in the range 0.048 $\leq x \leq$ 0.114. In zero magnetic field, a negligible residual linear term in $\kappa/T$ as $T \to 0$ at all $x$ shows that there are no zero-energy quasiparticles and hence the superconducting gap has no nodes in the $ab$-plane anywhere in the phase diagram. However, the field dependence of $\kappa$ reveals a systematic evolution of the superconducting gap with doping $x$, from large everywhere on the Fermi surface in the underdoped regime, as evidenced by a flat $\kappa (H)$ at $T \to 0$, to strongly $k$-dependent in the overdoped regime, where a small magnetic field can induce a large residual linear term, indicative of a deep minimum in the gap magnitude somewhere on the Fermi surface. This shows that the superconducting gap structure has a strongly $k$-dependent amplitude around the Fermi surface only outside the antiferromagnetic/orthorhombic phase.Comment: version accepted for publication in Physical Review Letters; new title, minor revision, revised fig.1, and updated reference

An Introduction to Machine Learning in Quantitative Finance

In this book, the authors provide a systematic and rigorous introduction to supervised, unsupervised and reinforcement learning by establishing essential definitions and theorems

Attack and Defence of Ethereum Remote APIs

© 2018 IEEE. Ethereum, as the first Turing-complete blockchain platform, provides various application program interfaces for developers. Although blockchain has highly improved security, faulty configuration and usage can result in serious vulnerabilities. In this paper, we focus on the security vulnerabilities of the official Go-version Ethereum client (geth). The vulnerabilities are because of the insecure API design and the specific Ethereum wallet mechanism. We demonstrate attacks exploiting these vulnerabilities in an Ethereum testbed. The vulnerabilities are confirmed by the scanning results on the public Internet. Finally, corresponding countermeasures against attacks are provided to enhance the security of the Ethereum platform

Documentation of a new hypotrich species in the family Amphisiellidae, Lamtostyla gui n. sp. (Protista, Ciliophora) using a multidisciplinary approach

An integrated approach considering both morphologic and molecular data is now required to improve biodiversity estimations and provide more robust systematics interpretations in hypotrichs, a highly differentiated group of ciliates. In present study, we document a new hypotrich species, Lamtostyla gui n. sp., collected from Chongming wetland, Shanghai, China, based on investigations using living observation, protargol staining, scanning and transmission electron microscopy, and gene sequencing. The new species is mainly recognized by having a short amphisiellid median cirral row composed of four cirri, three frontoventral cirri, three dorsal kinetids, four to eight macronuclear nodules, and small colorless cortical granules distributed as rosettes around dorsal bristles. Transmission electron microscope observation finds the associated microtubules of cirri and pharyngeal discs of L. gui are distinct from those in other hypotrichs. Morphogenesis of this species indicates that parental adoral membranelles retained intact or partial renewed is a potential feature to separate Lamtostyla granulifera-group and Lamtostyla lamottei-group. Phylogenetic analysis based on small subunit ribosomal RNA (rRNA) gene shows that this molecular marker is not useful to resolve phylogenetic relationships of the genus Lamtostyla, as well as many other hypotrichous taxa. We additionally characterize the internal transcribed spacers (ITS) region and the almost complete large subunit rRNA, which will be essential for future studies aimed at solving phylogenetic problems of Lamtostyla, or even the family Amphisiellidae. As a final remark, the critical screening of GenBank using ITS genes of our organism allows us to recognize a large amount of hypotrichous sequences have been misclassified as fungi. This observation suggests that hypotrichs could be frequently found in fungi-rich environment and overlooked by fungal specialists

Siamese Verification Framework for Autism Identification During Infancy Using Cortical Path Signature Features

Autism spectrum disorder (ASD) is a complex neurodevelopmental disability, which is lack of biologic diagnostic markers. Therefore, exploring the ASD Identification directly from brain imaging data has been an important topic. In this work, we propose the Siamese verification model to identify ASD using 6 and 12 months cortical features. Rather than directly classifying a testing subject is ASD or not, we determine whether it has the same or different label with the reference subject who has been successfully diagnosed. Then, based on the comparison to all the reference subjects, we can predict the label of the testing subject. The advantage of modeling the classification problem as a verification framework is that it can greatly enlarge the training data size and enable us to train a more accurate and reliable model in an end-to-end manner. In addition, to further improve the classification performance, we introduce the path signature (PS) features, which can capture the dynamic longitudinal information of the brain development for the ASD Identification. Experiments showed that our proposed method reaches the best result, i.e., 87% accuracy, 83% sensitivity and 90% specificity comparing to the state-of-the-art methods

PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras

We present the first purely event-based, energy-efficient approach for object detection and categorization using an event camera. Compared to traditional frame-based cameras, choosing event cameras results in high temporal resolution (order of microseconds), low power consumption (few hundred mW) and wide dynamic range (120 dB) as attractive properties. However, event-based object recognition systems are far behind their frame-based counterparts in terms of accuracy. To this end, this paper presents an event-based feature extraction method devised by accumulating local activity across the image frame and then applying principal component analysis (PCA) to the normalized neighborhood region. Subsequently, we propose a backtracking-free k-d tree mechanism for efficient feature matching by taking advantage of the low-dimensionality of the feature representation. Additionally, the proposed k-d tree mechanism allows for feature selection to obtain a lower-dimensional dictionary representation when hardware resources are limited to implement dimensionality reduction. Consequently, the proposed system can be realized on a field-programmable gate array (FPGA) device leading to high performance over resource ratio. The proposed system is tested on real-world event-based datasets for object categorization, showing superior classification performance and relevance to state-of-the-art algorithms. Additionally, we verified the object detection method and real-time FPGA performance in lab settings under non-controlled illumination conditions with limited training data and ground truth annotations.Comment: Accepted in ACCV 2018 Workshops, to appea