Miracle-dz/UniFAR-FTUs huggingface dataset:
Exposé : Single-Step Extraction of Protein-Protein Interactions with Support Vector Machines

Most of the information about protein-protein interactions (PPIs) can only be found in unstructured natural language texts (Ono et al., 2001). PubMed, a publicly accessible database for biomedical literature, nowadays consists of over 20 million citations and is still growing fast. Thus, methods that extract PPIs automatically are of great importance. The extraction of PPIs requires the recognition of relevant entities, in this case proteins, and the relations between them.
Transmission Efficiency Optimization for the operation of double-circuit Overhead Lines

Nowadays the question of improving overhead-line (OHL) operation efficiency is more than ever considered as a very critical issue. This is because power losses have recently acquired an extra cost due to the CO2 release penalty. It is well known that a good portion of the electricity required to operate a power grid is spent as OHL power losses. In this paper the key points of the maximum OHL transmission-efficiency theory are reviewed. OHL loading enabling the maximum transmission efficiency is given. With a case study it is then shown how to optimize the double-circuit OHL transmission-efficiency for the periods of OHL off-peak loading. The OHL transmission-efficiency vs. OHL loading curves of the OHL is presented and the change in the character from capacitive to inductive with an increasing OHL load is illustrated. Potential transmissionefficiency gains in percentage points are calculated. Conclusions of practical importance are drawn both for OHL design purposes as well as for its operation optimization.
Insecurity of an Dynamic User Revocation and Key Refreshing for Attribute-Based Encryption Scheme

Cloud computing has generated a major impact on the global IT ecosystem, which promises economic advantages, speed, agility, flexibility, virtually infinite elasticity and innovation. However, data security and privacy remain the biggest barriers to widespread adoption of cloud services. To address the problem of fine-grained access control over encrypted data that is faced by cloud services, ciphertext-policy attribute-based encryption (CP-ABE) technology was proposed in recent years and has aroused great concern of researchers. Although CP-ABE schemes provide the ability for data owner-centric protection in cloud services, they are not very practical with the respect to the efficiency and scalability of access right revocation and key refreshing. Recently Xu and Martin proposed a dynamic user revocation and key refreshing model for CP-ABE schemes, and presented a concrete construction based on Bethencourt et al.'s CP-ABE scheme. They claimed that their construction is efficient and provable secure. However, after revisiting the construction, we demonstrate that cloud service provider can not perform data retrieval task in their construction, and their construction cannot achieve one-to-many encryption.
MeiKe: Influence-based Communities in Networks

Given a social network, how to find communities of nodes based on their diffusive characteristics? There exist two important types of nodes, for information propagation: nodes that are influential (“kernel nodes”), and nodes that serve as “bridges” to boost the diffusion (“media nodes”). How to find these nodes and uncover connections between them? In addition, it is also important to discover the hidden community structure of these nodes, which can help study their interactions, predict links and also understand the information flow in such networks. In this paper, we give an intuitive and novel optimization-based formulation for this task, which aims to discover media nodes as well as community structures of kernel nodes. We prove our task is computationally challenging, and develop an effective and practical algorithm MeiKe (pronounced as ‘Mike’). It first obtains media nodes via a new successive summarization based approach, and then finds kernel nodes including their community structures. Experimental results show that MeiKe finds high-quality media and kernel communities which match our expectations and ground-truth (outperforming non-trivial baselines by 40% in F1-score). Our case studies also demonstrate the applicability of MeiKe on a variety of datasets.
FFT-Based Audio Watermarking Method with a Gray Image for Copyright Protection

Many effective watermarking algorithms have been proposed and implemented for multimedia. Human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). For this reason, a few algorithms have been proposed for audio watermarking. In this paper, a new method of embedding gray image data into the audio signal and additive audio watermarking algorithm based on Fast Fourier Transformation (FFT) domain is proposed. First, the original audio is transformed into FFT domain. The FFT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from gray image. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, requantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Similarity (SIM) and Signal to Noise ratio (SNR) are conducted.
A hybrid intelligent system clonart for short and mid-term forecasting for the Brazilian Energy Distribution System

The present work describes an application of Clonart (Clonal Adaptive Resonance Theory) for forecasting of amount of precipitation for the Brazilian Energy Distribution System. The effectiveness of the Brazilian electricity system directly depends on the difference between hydroelectric energy production and consumer use. Production depends upon the volume of water stored in the reservoirs. A forecasting system for the amount of rainfall throughout the year contributes significantly to the analysis. The plasticity of the Clonart ensures that a new piece of knowledge does not overshadow previous knowledge. This is especially important for forecast problems because this type of problem needs constants training.
Recovery of vision and pupil responses in optic neuritis and multiple sclerosis

The recovery of visual performance and pupil responses were investigated in patients with demyelinating optic neuritis (ON) and multiple sclerosis (MS). The pupil constriction amplitude and the time delay (latency) of the pupil response were measured in 14 patients with a history of unilateral ON in response to either achromatic (luminance) or chromatic (isoluminant) stimulus modulation. Five of these subjects were diagnosed later with MS. In addition, we measured detection thresholds for achromatic stimuli using standard visual field perimetry and chromatic thresholds using a new colour assessment and diagnosis (CAD) test that isolates the use of colour signals. The results show that, despite significant improvements in visual function following the acute phase (as assessed using visual acuity and fields), significant pupil response deficits remain. The findings also demonstrate that accurate measurements of pupil responses and chromatic thresholds can reveal deficits that remain undetected with more conventional techniques. These preliminary findings suggest that the techniques described here can provide useful information about remitting and relapsing demyelinative phases, often observed during MS and ON.
Developing Biomass Equations for Western Hemlock and Red Alder Trees in Western Oregon Forests

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameter- and height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg. ) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass equations was fitted simultaneously with a constrained seemingly unrelated regression. Additionally, a linear model that predicts total aboveground biomass as a function of DBH and height was also fitted. The predicted total biomass was then apportioned to different components according to the predicted proportions from beta, Dirichlet, and multinomial log-linear regressions. Accuracy of these methods differed between species with higher root mean squared error (RMSE) being produced in red alder trees. Within species, the accuracy of the equation for bole biomass was better than the equations for other components. None of these methods stood out as a clear winner, but the multinomial log-linear regression produced marginally better results compared to other methods in terms of RMSE, except for Western hemlock bark biomass and red alder bole and branch biomass. The equations based on a seemingly unrelated regression provided lower RMSEs for those species-component combinations.
3D Face Recognition by Matching Shape Descriptors

Face is an important biometric for the identification and authentication of individuals. 2D face recognition techniques have been investigated for a long time. However, 3D face recognition is a relatively niche area of research. We propose a novel algorithm for 3D face recognition. A gallery of 3D faces is generated and saved along with their tensor representation (shape descriptors) during an offline phase. During online recognition, a tensor is generated for the range image of a probe face and matched with the tensors of gallery faces using a weighted linear correlation coefficient as the matching criterion. The gallery face with the maximum correlation is declared to be the recognized face. Preliminary experiments on a gallery of 20 faces has shown that our algorithm has a recognition rate of 95%.
自由意志・決定論尺度（The Free Will and Determinism Plus Scale：FAD＋）日本語版の作成

自由意志とは自分の理由や欲求にそって行為を選択する 能力を意味している。 自由意志に関する確立した尺度は日 本にまだ存在しないが,海外では複数の尺度が作成されて いる(e.g., Paulhus & Carey, 2011; Rakos, Laurene, Skala, & Slane, 2008)。 なかでも,Paulhusらの自由意志・決定論尺 度(The Free Will and Determinism Plus Scale:FAD+) は自由意志と決定論の信念を弁別し,信頼性・妥当性が十 分に検討されているという利点がある。 そこで,本研究は 自由意志・決定論尺度の日本語版を作成し,尺度の因子構 造を検証する。 原版の尺度は自由意志,科学的決定論,運 命的決定論,予測不可能性の4つの下位尺度から構成され, 自由意志の信念が強いほどLocus of Control (LOC)や協調 性が高い,また正当世界信念や懲罰傾向が強いことが示さ れている(Carey & Paulhus, 2013; Paulhus & Carey, 2011)。 本研究でもLOCと信頼感,正当世界信念を測定し,尺度 の信頼性・妥当性を検証する。 自由意志は統制感と概念的 に重複しているため,科学的・運命的決定論ではなく自由 意志を信じる人ほど,物事の原因は自分自身にあり (LOC),自分や他者を信頼できる(信頼感)と予測される。 また,自由意志は統制感だけでなく,道徳的責任とも密接 に関連する。 行為に責任を問うためには自由意志が前提と なり,両者の関係は不可分である。 そこで,自由意志を信 じている人ほど道徳的責任を強く,人々が受けるに値する ものを受けていると認知する(正当世界信念)と予測でき る。 自由意志の信念はわれわれの行為選択の可能性と連関 するため,道徳的責任だけでなく懲罰判断の根拠となりう るものである。 それゆえ,自由意志の信念を測定する日本 語版尺度の開発は,近年隆盛が目覚ましい道徳心理学研究 を日本で進めるために不可欠であると同時に,心理学的知 見の意義をわれわれの道徳実践や人間観とのかかわりから 考察していく道を開くものとしても意義があるといえよう。 研 究 1
IS THERE A COMMUNITY OF INNOVATION SCHOLARS

Although innovation is not a new topic for scholarly research, the academic literature on innovation was, for a long time, not very voluminous. However, more recently innovation has become a major focus among scholars of different backgrounds, and this change is also reflected in an increasing number of academic publications in this area. In parallel with this we have seen the emergence of a number of new journals and professional associations devoted to the subject. The research reported in this paper is motivated by these trends. We wish to find an answer to the question to what extent it now exists a unified community of innovation scholars that identify themselves with innovation studies as a field rather than particular sub-fields within other, more traditional disciplines. Moreover, we want to explore the factors (sources of inspiration, academic leadership, professional societies, publishing outlets etc.) that bind scholars together or – alternatively – continue to keep them divided. The research reported in this paper is based on a web-survey carried out in during 2004 and 2005. The results suggest that a global innovation studies community exists as a collection of a large number of relatively small groups (characterized dense internal relationships) defined along geographical and disciplinary lines. Although the field has spread over many countries and disciplines, it is particularly developed in Europe and among scholars with a background in economics. These smaller groups, however, are embedded in larger transnational groups or clusters that are kept together by what is commonly referred to as “weak ties”. Leading scholars, professional associations and journals all play an important role in keeping these larger groups together (as well as distinguishing them from each other).
Real Time Text-to-Emotion Engine for Expressive Internet Communications

In this work we focus on demonstrating a real time communication interface which enhances text communication by detecting from real time typed text, the extracted emotions, and displaying on the screen appropriate facial expression images in real time. The displayed expressions are represented in terms of expressive images or sketches of the communicating persons. This interface makes uses of a developed real time emotion extraction engine from text. The emotion extraction engine and extraction rules are discussed together with a description of the interface, its limits and future direction of such interface. The extracted emotions are mapped into displayed facial expressions. Such interface can be used as a platform for a number of future CMC experiments. The developed online communication interface brings together remotely located collaborating parties in a shared electronic space for their communication. In its current state the interface allows the participant to see at a glance all other online participants and all those who are engaged in communications. An important aspect of the interface is that for two users engaged in communication, the interface locally extracts emotional states from the content of typed textual sentences automatically. Subsequently it displays discrete expressions mapped from extracted emotions to the remote screen of the other person. It also analyses/extracts the intensity/duration of the emotional state. At the same time the users can also control their expression, if they wish, manually. The interface also uses text to speech synthesis, which allows the user to glance on other tasks while at the same time listening to the communication. A shared whiteboard also allows the users to engage in collaborative work. Finally it is also possible to view your own expression (feedback) which is displayed and viewed by the other user, an add on feature not possible with face to face communication between two people.
Scaling Up: Developing an Approach to Measuring Progress on girls' education in Commonwealth Countries in Africa

in 2004 and 2005 on measurement issues in Africa.No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording or otherwise without the permission of the publisher.The views expressed in this publication do not necessarily reflect the officialviews of the Commonwealth SecretariatWherever possible, the Commonwealth Secretariat uses paper sourced from sustainable forests or from sources that minimise a destructive impact on the environment.Published by the Commonwealth SecretariatDesigned by WayzgoosePrinted by Copies of this publication may be ordered direct from:The Publications ManagerCommunications and Public Affairs DivisionCommonwealth SecretariatMarlborough HousePall Mall, London SW1Y 5HXUnited KingdomTel: +44 (0) 20 7747 6342 Fax: +44 (0) 20 7839 9081E-mail: CPAD@commonwealth.intWebsites: www.thecommonwealth. orgwww.csdrms. org
Cohort Profile: the Born in Bradford multi-ethnic family cohort study.

Bradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust, Bradford, UK, School of Health Studies, University of Bradford, Bradford, UK, Edinburgh Ethnicity and Health Research Group, Centre for Population Health Sciences, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK, School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, UK, Medical Research Council Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol, UK, Paediatric Epidemiology Group, Centre for Epidemiology and Biostatistics, Leeds Institute of Genetics, Health and Therapeutics, Faculty of Medicine and Health, University of Leeds, Leeds, UK and Department of Health Sciences, University of York, York, UK
Control of General Nonlinear Systems Using a Novel Dynamic Structure Neural Network

In this paper, dynamic structure neural network controller based on feedback linearization is proposed. The proposed method can adapt the neural network structure dynamically while it can guarantee the stability and tracking precision of system. The dynamic structure wavelet network controller is introduced in the system simulation and the performance of the controller on a system with nonlinear dynamics is demonstrated by simulation results. Key-Words: Neural networks, dynamic structure, control systems, nonlinear systems.
A single-degenerate model for the progenitor of the Type Ia supernova 2002ic

Supernova 2002ic was an atypical Type Ia supernova (SN Ia) with evidence for substantial amounts of hydrogen associated with the system. Contrary to previous claims, we show that its unusual properties can be understood within the framework of one of the most favoured progenitor models, the so-called supersoft channel. This requires that the donor star was initially relatively massive (similar to 3 M(circle dot)) and that the system experienced a delayed dynamical instability, leading to a large amount of mass-loss from the system in the last few 10(4) yr before the explosion. This can produce the inferred hydrogen-rich circumstellar environment, most likely with a disc-like geometry. However, in order for this model to be feasible, it requires a larger accretion efficiency on to the white dwarf than is assumed in present parametrizations. If this is confirmed, it would most likely increase estimates for the frequency of the single-degenerate channel. Based on population synthesis simulations we estimate that not more than 1 in 100 SNe Ia should belong to this subgroup of SNe Ia.
An alive electroencephalogram analysis system to assist the diagnosis of epilepsy

Computer assisted electroencephalograph analysis tools are trained to classify the data based upon the “ground truth” provided by the clinicians. After development and delivery of these systems there is no simple mechanism for these clinicians to improve the system's classification while encountering any false classification by the system. So the improvement process of the system's classification after initial training (during development) can be termed as `dead'. We consider neurologist as the best available benchmark for system's learning. In this article, we propose an `alive' system, capable of improving its performance by taking clinician's feedback into consideration. The system is based on taking DWT transform which has been shown to be very effective for EEG signal analysis. PCA is applied on the statistical features which are extracted from DWT coefficients before classification by an SVM classifier. After corrective marking of few epochs the initial average accuracy of 94.8% raised to 95.12.
Making contour trees subdomain-aware

time, where is the size of the input mesh and is the total number of critical points of the scalar field and of the restriction of to . We show how to use our algorithm to label the edges of the contour tree of a 3D scalar field with complete information on the topology of the corresponding contours in time. Contour trees (CTs) are considered an important tool allowing one to concisely describe the structure of isosurfaces in volume data as well as the way they evolve and interact as the isovalue is varied. A CT can be defined as a quotient space where is the domain of a scalar field and, for , if and only if and belong to the same contour, i.e. a connected component of a set of the form for some scalar . A scalar field is typically represented as a simplicial complex with values at vertices or a regular (rectilinear) grid of samples. Linear or multilinear interpolation is used to obtain values at points other than the samples. Most scalar fields that appear in applications are define d on simply connected domains. In this case the CT is indeed a tree. Contour trees been used as a tool to enhance scalar field visualization [1], speed up certain types of queries in geographical information systems [2] and facilitate isosurface extraction from volume datasets by helping to compute small seed sets [5, 6]. These applications motivated efforts to develop increasingly simpler, faster and more general algorithms for computing contour trees. An algo
Facilitating Discourse Analysis with Interactive Visualization

A discourse parser is a natural language processing system which can represent the organization of a document based on a rhetorical structure tree-one of the key data structures enabling applications such as text summarization, question answering and dialogue generation. Computational linguistics researchers currently rely on manually exploring and comparing the discourse structures to get intuitions for improving parsing algorithms. In this paper, we present DAViewer, an interactive visualization system for assisting computational linguistics researchers to explore, compare, evaluate and annotate the results of discourse parsers. An iterative user-centered design process with domain experts was conducted in the development of DAViewer. We report the results of an informal formative study of the system to better understand how the proposed visualization and interaction techniques are used in the real research environment.