Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying the “demon whale-biter”: Patterns of scarring on large whales attributed to a cookie-cutter shark Isistius sp

The presence of crater-like wounds on cetaceans and other large marine vertebrates and invertebrates has been attributed to various organisms. We review the evidence for the identity of the biting agent responsible for crater wounds on large whales, using data collected from sei (Balaenoptera borealis), fin (B. physalus), inshore and offshore Bryde’s (B. brydeii sp) and sperm whales (Physeter macrocephalus) examined at the Donkergat whaling station, Saldanha Bay, South Africa between March and October 1963. We then analyse the intensity and trends in its predation on large whales. Despite the scarcity of local records, we conclude that a cookie-cutter shark Isistius sp is the most likely candidate. We make inferences about the trends in (1) total counts of unhealed bitemarks, and (2) the proportion of unhealed bitemarks that were recent. We use day of the year; reproductive class, social grouping or sex; depth interval and body length as candidate covariates. The models with highest support for total counts of unhealed bitemarks involve the day of the year in all species. Depth was an important predictor in all species except offshore Bryde’s whales. Models for the proportion of recent bites were only informative for sei and fin whales. We conclude that temporal scarring patterns support what is currently hypothesized about the distribution and movements of these whale species, given that Isistius does not occur in the Antarctic and has an oceanic habitat. The incidence of fresh bites confirms the presence of Isistius in the region. The lower numbers of unhealed bites on medium-sized sperm whales suggests that this group spends more time outside the area in which bites are incurred, providing a clue to one of the biggest gaps in our understanding of the movements of mature and maturing sperm males.
Shortening the Libert-Peters-Yung Revocable Group Signature Scheme by Using the Random Oracle Methodology

In EUROCRYPT 2012, Libert, Peters and Yung (LPY) proposed the first scalable revocable group signature (R-GS) scheme in the standard model which achieves constant signing/verification costs and other costs regarding signers are at most logarithmic in N , where N is the maximum number of group members. However, although the LPY R-GS scheme is asymptotically quite efficient, this scheme is not sufficiently efficient in practice. For example, the signature size of the LPY scheme is roughly 10 times larger than that of the RSA signature (in 160-bit security). In this paper, we propose a compact R-GS scheme secure in the random oracle model that is efficient not only in the asymptotic sense but also in practical parameter settings. We achieve the same efficiency as the LPY scheme in an asymptotic sense, and the signature size is nearly equal to that of the RSA signature (in 160-bit security). It is particularly worth noting that our R-GS scheme has the smallest signature size compared to those of previous R-GS schemes which enable constant signing/verification costs. Our technique, which we call parallel Boneh–Boyen–Shacham group signature technique, helps to construct a R-GS scheme without following the technique used in LPY, i.e., we directly apply the Naor–Naor–Lotspiech framework without using any identity-based encryption. keywords: group signature, revocation, scalability.
Feature extraction , selection and classifier design in automated time-lapse fluorescence microscope image analysis

Using automated time-lapse fluorescence microscope imaging to measure drug response, e.g. using taxanes and the vinca alkaloids to cancers, has become a common practice in cancer research ands drug discovery. A mature system usually consists of the following subsystems: image acquisition subsystems, image pre-processing subsystems, image analysis subsystems, database subsystems and data analysis subsystems. Particularly, the image analysis subsystems play a key role in determining the overall performance of this system. The image analysis subsystems comprise of a dynamic cellular segmentation module, a feature extraction, a cell-cycle phase identification module, a tracking module and a descriptor quantification module. In this chapter, we will systematically introduce the feature extraction/selection and cell-cycle phase identification module. To illustrate the general techniques mentioned above, an applied laboratorial system which includes the many descriptors representing nuclei, feature selections techniques and online-SVM will be introduced. These techniques can easily be applied for users’ own research purposes.
Exemplar-Based Image Inpainting Using Color Distribution Analysis

This paper proposes a novel exemplar-based inpianting algorithm based upon the color distribution analysis. A novel priority scheme is designed to assign priority and guide the filling-in order, which is a crucial step for the performance of the inpainted results. Color distribution is proposed to determine the confidence of the target patches situated on the boundary of the missing region by measuring the variation of variances of neighboring source patches. Our experiments on the natural images and the comparisons with the representative existing approaches show that our proposed scheme can more robustly assign high priority to the structures and enables the salient structures, to which human visual system is sensitive, to be consistent with the surrounding regions.
What accuracy statistics really measure

Provides the software estimation research community with a better understanding of the meaning of, and relationship between, two statistics that are often used to assess the accuracy of predictive models: the mean magnitude relative error (MMRE) and the number of predictions within 25% of the actual, pred(25). It is demonstrated that MMRE and pred(25) are, respectively, measures of the spread and the kurtosis of the variable z, where z=estimate/actual. Thus, z is considered to be a measure of accuracy, and statistics such as MMRE and pred(25) to be measures of properties of the distribution of z. It is suggested that measures of the central location and skewness of z, as well as measures of spread and kurtosis, are necessary. Furthermore, since the distribution of z is non-normal, non-parametric measures of these properties may be needed. For this reason, box-plots of z are useful alternatives to simple summary metrics. It is also noted that the simple residuals are better behaved than the z variable, and could also be used as the basis for comparing prediction systems.
Subsethood measure for single valued neutrosophic sets

The main aim of this paper is to introduce a neurosophic subsethood measure for single valued neutrosophic sets. For this purpose, we rst introduce a system of axioms for subsethood measure of single valued neutrosophic sets. Then we give a simple subsethood mea- sure based to distance measure. Finally, to show eectiveness of intended subsethood measure, an application is presented in multicriteria decision making problem and results obtained are discussed. Though having a simple measure for calculation, the subsethood measure presents a new approach to deal with neutrosophic information.
How to Draw a Sequence Diagram

In this paper, we consider the aesthetic criteria and constraints related to the layouts of UML sequence diagrams. We consider the applicability of the traditional graph drawing aesthetics in drawing sequence diagrams. Because of the special nature of sequence diagrams, many of these aesthetics are not applicable. Based on our view on how these diagrams are read or viewed, we propose some new aesthetics. We also take into account the presence of usually adopted conventions and constraints. The basic choice in producing a drawing for a sequence diagram is the linear order of the participating objects. Based on this finding and the identified aesthetics criteria, we formulate some related computational problems.
Kernel Selection of SVM for Commerce Image Classification

Content-based image classification refers to associating a given image to a predefined class merely according to the visual information contained in the image. In this study, we employ SVM (Support Vector Machine) and presented a few kernels specifically designed to deal with the problem of content-based image classification. Several common kernel functions are compared for commerce image classification with the PHOW (Pyramid Histogram of visual Words) descriptors. The experiment results illustrate that chi-square kernel and histogram intersection kernel are more effective with the histogram based image descriptor for commerce image classification.
HS 0705+6700: A new eclipsing sdB binary

We report the discovery of an eclipsing binary { HS 0705+6700 { being an sdB star with a faint companion. From its light curve the orbital period of 8263.87 s, the mass ratio of the system q =0 :28, the inclination of 84:4 and other system parameters are derived. The companion does not contribute to the optical light of the system except through a strong reflection eect. The semi-amplitude of the radial velocity curve K1 =8 5: 8k m s 1 and a mass function of f(m )=0 :00626 M are determined. A spectroscopic analysis of the blue spectra results in Te = 28 800 K, log g =5 :40, and log(nHe=nH )= 2:68. These characteristics are typical for sdB stars, as is its mass of 0.48 M. According to its mass (0.13 M) and radius (0.19 R), the companion is an M dwarf. The primary is in a core helium burning phase of evolution, and the system must have gone through a common envelope stage when the primary was near the tip of the red giant branch.
Native Students and the Gains from Exporting Higher Education: Evidence from Australia

This paper proposes a general equilibrium model with non-profit publicly subsidized universities to show that native applicants do not have to lose from exporting higher education, as suggested by standard trade models. The gains from exporting higher education that initially accrue to universities will be redistributed to natives through increased investment in research and teaching. With Australian university-level data from 2001 to 2007, the empirical investigation identifies the impact of exporting higher education on native enrollment using the instrumental variable approach: the enrollment of one more foreign student leads to the enrollment of about 0.75 more Australian native students.
MIMO Two-Way Relaying: A Space-Division Approach

Multi-antenna two-way relaying, in which two multi-antenna users exchange information via a multiantenna relay, has attracted much research interest recently. How to approach the capacity of a multipleinput multiple-output (MIMO) two-way relay channel (TWRC) remains a challenging issue. In this work, we propose a novel space-division based network-coding scheme for MIMO two-way relaying. In the proposed scheme, the overall signal space at the relay is divided into two subspaces. In one subspace, the spatial streams of the two users have nearly orthogonal directions, and are completely decoded at the relay. In the other subspace, the signal directions of the two users are nearly parallel, and linear functions of the spatial streams are computed at the relay, following the principle of physical-layer network coding (PNC). Based on the recovered messages and message-functions, the relay generates and forwards network-coded messages to the two users. We show that, at high signal-to-noise ratio (SNR), the proposed scheme achieves the asymptotic sum-rate capacity of MIMO TWRCs within 1/2log(5/4)0.161 bits per user-antenna for any antenna configuration and channel realization. We further perform large-system analysis to derive the average sum-rate of the proposed scheme over Rayleigh-fading MIMO TWRCs. We show that the average asymptotic sum-rate gap to the capacity upper bound is at most 0.053 bits per relay-antenna. It is demonstrated that the proposed scheme significantly outperforms the existing schemes. Biography Xiaojun Yuan received the B.S. degree in electronic and information systems from Shanghai Jiaotong University, the M.S. degree in circuit and systems from Fudan University, and the Ph.D. degree in electrical engineering from City University of Hong Kong. During 2009-2010, he was working as a visiting post-doc fellow at the University of Hawaii at Manoa. He is now a research assistant professor at the Institute of Network Coding, The Chinese University of Hong Kong. His research interest falls into the general area of signal processing, communications, and information theory, including channel coding and coded modulation, wireless multi-antenna and multi-user communications, and physical-layer network coding (PNC), etc. He has published over 40 refereed journal and conference papers in the related areas. He is a member of IEEE, and has also served as the Technical Program Committee (TPC) members for many international conferences including WCNC, PIMRC, ICC, etc. ** All ARE WELCOME ** Host: Professor Raymond W.H. Yeung (Tel: 3943-8375, Email: whyeung@ie.cuhk.edu.hk) Enquiries: Department of Information Engineering, CUHK (Tel.: 3943-8388)
Performance Control Driven Violin Timbre Model Based on Neural Networks

The objective of this research is to model the relationship between actions performed by a violinist and the sound which these actions produce. Violinist actions and audio are captured during real performances by means of a newly developed sensing system from which bowing and audio descriptors are computed. A database is built with this data and used to train a generative model based on neural networks. The model is driven by a continuous sequence of bowing and fingering controls and is able to generate their corresponding sequence of spectral envelopes. The model is used for synthesis, either alone as a purely spectral model, by filling the predicted envelopes with harmonic and noisy components, or coupled with a concatenative synthesizer, where the predicted envelopes are used as time-varying filters to transform the concatenated samples. The combination of sample concatenation with the timbre model allows for the preservation of sound quality inherent in samples, while providing a high level of control. Additionally, we perform an analysis of the violinist control space and the influence of the controls on the timbre.
Acid-Sensing Ion Channel-1a in the Amygdala, a Novel Therapeutic Target in Depression-Related Behavior

No animal models replicate the complexity of human depression. However, a number of behavioral tests in rodents are sensitive to antidepressants and may thus tap important underlying biological factors. Such models may also offer the best opportunity to discover novel treatments. Here, we used several of these models to test the hypothesis that the acid-sensing ion channel-1a (ASIC1a) might be targeted to reduce depression. Genetically disrupting ASIC1a in mice produced antidepressant-like effects in the forced swim test, the tail suspension test, and following unpredictable mild stress. Pharmacologically inhibiting ASIC1a also had antidepressant-like effects in the forced swim test. The effects of ASIC1a disruption in the forced swim test were independent of and additive to those of several commonly used antidepressants. Furthermore, ASIC1a disruption interfered with an important biochemical marker of depression, the ability of stress to reduce BDNF in the hippocampus. Restoring ASIC1a to the amygdala of ASIC1a−/− mice with a viral vector reversed the forced swim test effects, suggesting that the amygdala is a key site of ASIC1a action in depression-related behavior. These data are consistent with clinical studies emphasizing the importance of the amygdala in mood regulation, and suggest that ASIC1a antagonists may effectively combat depression.
Overview of assistive technologies for the blind: Navigation and shopping

One of the major driving forces behind technology development is the establishment of equality among everyone. It is intended that the strategic use of technology complements competencies or diminished capacities, improving self confidence and autonomy. Blind and partially sighted people often deal with this inequality in the performance of tasks or daily activities. The presented work reviews some of the proposed technologies to assist visually impaired people in common activities, specifically navigation and going shopping.
Spatiotemporally resolved black carbon concentration, schoolchildren's exposure and dose in Barcelona

Abstract At city level, personal monitoring is the best way to assess people's exposure. However, it is usually estimated from a few monitoring stations. Our aim was to determine the exposure to black carbon (BC) and BC dose for 45 schoolchildren with portable microaethalometers and to evaluate the relationship between personal monitoring and fixed stations at schools (indoor and outdoor) and in an urban background (UB) site. Personal BC concentra‐tions were 20% higher than in fixed stations at schools. Linear mixed‐effect models showed low R 2 between personal measurements and fixed stations at schools (R 2 ≤ 0.28), increasing to R 2 ≥ 0.70 if considering only periods when children were at schools. For the UB station, the respective R 2 were 0.18 and 0.45, indicating the importance of the distance to the monitoring station when assessing exposure. During the warm season, the fixed stations agreed better with personal measurements than during the cold one. Children spent 6% of their time on commuting but received 20% of their daily BC dose, due to co‐occurrence with road traffic rush hours and the close proximity to the source. Children received 37% of their daily‐integrated BC dose at school. Indoor environments (classroom and home) were responsible for the 56% BC dose.
Frequency-domain robust control toolbox

A new frequency-domain robust control toolbox is introduced and compared with the robust control toolbox of Matlab. A summary of the theoretical background for H∞ controller design using the spectral models is given. The main advantage of this toolbox is that almost all types of model uncertainties like unmodelled dynamics, multimodel uncertainty, spectral uncertainty and parametric uncertainty can be taken into account without conservatism. As a result, the uncertain parametric or frequency-domain models identified by the identification toolbox of Matlab can be used directly for computing robust controllers. The main commands of the new toolbox are briefly explained and the performance of the designed controllers are illustrated via some sand experimental results.
Image Repurposing for Gifar-Based Attacks

In this paper we present a light-weight and effective tool to pr tect against a type of repurposing attack vector, which exploits weaknesses in Web applications, referred to as the Gifar. A Gifar -based attack relies on a form of steganography, combining images o r any other file types (such as word file or flash etc) with Jar files. Th e modified file is used to carry the payloads of various attacks, that can be triggered when posted on Web portals. In the paper, we e xplore the capabilities of Gifar-based attacks, expose the e fficacy and the state of the art of the existing protection mechanisms ag ainst these type of attacks. We show that despite some initial step s taken by many Web portals to prevent from similar attacks, Gifar at tacks can be launched from any sites, and can be used as carriers of a variety of disruptive attacks, such as denial of service, comm and and control, and data theft. We present the AntiGifar, a lightweight system that addresses this deficiency by detecting and stopping these attacks at the client end. As demonstrated by our test result s, our solution promptly detects a number of possible Gifar-based attacks launched by any Web site. The AntiGifar provides an effective solution to this subtle threat while adding no overhead to the u sers local machine or browser where it resides, and it does not invas ively monitor the user interactions with the browser.
Bioactivity-Directed Isolation and Identification of Novel Alkaloid from Jatropha curcas (Linn.)

The study reports bioactivity-assisted identification of potent alkaloid from Jatropha curcas (Linn). The isolation was carried out using acid-base shakeout method. The identification was conducted using various spectroscopic and chromatographic studies including IR, 1H and 13C NMR, mass spectrometry (MS) and HPTLC. The elemental composition was found to be N=2.1%; C=73.5%; H=8.5% and O=15.5%. The m/z (M+H+) of the compound is 413.5. The probable empirical formula of the compound is C25H35O4N. The compound showed significant inhibition In vitro against selected pathogenic microbes and fungus. The inhibitory potential of the compound over human leukemia cell line (Jurkat J6) was also significant with IC50 less than 10µg/ml. The alkaloids showed 2-3fold of inhibition potential over the standard 5flourouracil. Thus, this bioassay-guided method for identification and characterization of such biologically active molecule is reliable for further biopharmaceutics and biotechnological studies on the compound.
Study on the detection of locomotive driver fatigue based on image

In order to overcome the traditional shortcomings of the contact-type fatigue detection for locomotive drivers, this paper presents a system that detects face in images collected by the CCD,then establishes the eye's position in the region of the detected face, to determine the degree of the driver's fatigue through the analysis of the state of the human eye. In this paper, AdaBoost method based on Haar features is applied to detect the face, on the basis of which, through the four templates matching method, to ultimately identify the position and status of the human eyes. Experiments show that, AdaBoost algorithm combined with the template matching method can be carried out with high detection accuracy and high speed, meanwhile, has good robustness for the changes of environmental conditions, and can meet the requirements of real time and accuracy in the fatigue detection.
Scalable byzantine computation

Byzantine agreement is arguably one of the most fundamental problems in distributed computing. The basic idea of the problem is this: n players each vote on one of two choices, and the players want to hold an election to decide which choice wins. The problem is made more interesting by the fact that there is no leader, i.e. no single player who everyone knows is trustworthy and can be counted on to tabulate all the votes accurately. We now give a more precise statement of the problem that was first defined in [53]. Each of n players starts with either a 0 or a 1 as input. A certain fraction of the players (say some fraction less than 1/3) are bad, and will collude to thwart the remaining good players. Unfortunately, the good players have no idea who the bad players are. The goal is to create an algorithm for the good players that ensures that
The Emotional and Chromatic Layers of Urban Smells

People are able to detect up to 1 trillion odors. Yet, city planning is concerned only with a few bad odors, mainly because odors are currently captured only through complaints made by urban dwellers. To capture both good and bad odors, we resort to a methodology that has been recently proposed and relies on tagging information of geo-referenced pictures. In doing so for the cities of London and Barcelona, this work makes three new contributions. We study 1) how the urban smellscape changes in time and space; 2) which emotions people share at places with specific smells; and 3) what is the color of a smell, if it exists. Without social media data, insights about those three aspects have been difficult to produce in the past, further delaying the creation of urban restorative experiences.