Miracle-dz/UniFAR-FTUs huggingface dataset:
Extraction of regulatory gene/protein networks from Medline

MOTIVATION We have previously developed a rule-based approach for extracting information on the regulation of gene expression in yeast. The biomedical literature, however, contains information on several other equally important regulatory mechanisms, in particular phosphorylation, which we now expanded for our rule-based system also to extract. RESULTS This paper presents new results for extraction of relational information from biomedical text. We have improved our system, STRING-IE, to capture both new types of linguistic constructs as well as new types of biological information [i.e. (de-)phosphorylation]. The precision remains stable with a slight increase in recall. From almost one million PubMed abstracts related to four model organisms, we manage to extract regulatory networks and binary phosphorylations comprising 3,319 relation chunks. The accuracy is 83-90% and 86-95% for gene expression and (de-)phosphorylation relations, respectively. To achieve this, we made use of an organism-specific resource of gene/protein names considerably larger than those used in most other biology related information extraction approaches. These names were included in the lexicon when retraining the part-of-speech (POS) tagger on the GENIA corpus. For the domain in question, an accuracy of 96.4% was attained on POS tags. It should be noted that the rules were developed for yeast and successfully applied to both abstracts and full-text articles related to other organisms with comparable accuracy. AVAILABILITY The revised GENIA corpus, the POS tagger, the extraction rules and the full sets of extracted relations are available from http://www.bork. embl.de/Docu/STRING-IE
Improving Service Quality in the New Public Sector

This timely collection of cutting-edge articles offers a complete overview of marketing in the nonprofit sector. Written by a leading team of international experts, it examines the issues faced by public and nonprofit organizations in marketing and raising funds, and provides a comprehensive review of the latest research. An introductory section reviews the history of ideas in nonprofit marketing and examines those fundamental marketing principles of special relevance to nonprofit organizations. The book then explores in-depth the latest thinking in each of the most important nonprofit arenas, including: voluntary sector marketing fundraising arts marketing education marketing political marketing social marketing volunteer recruitment, management and retention public sector marketing and e-government. Containing real-world examples and case study material throughout, The Routledge Companion to Nonprofit Marketing makes an important contribution to our understanding of marketing theory and practice in the nonprofit sector. It is an essential reference for all students, researchers and practitioners working in nonprofit marketing, fundraising or philanthropy
Line tracking algorithm for scribbled drawings

This paper describes a line tracking algorithm that may be used to extract lines from paper based scribbles. The proposed algorithm improves the performance of existing sparse-pixel line tracking techniques that are used in vectorization by introducing perceptual saliency and Kalman filtering concepts to the line tracking. Furthermore, an adaptive sampling size is used such that it is possible to adjust the size of the tracking step to reflect the stroke curvature.
The Use of Artificially Intelligent Agents with Bounded Rationality in the Study of Economic Markets

The concepts of 'knowledge' and 'rationality' are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories of market behavior have been advanced. The prevailing theory holds that an asset's current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.
Joint turbo equalization for relaying schemes over frequency-selective fading channels

We propose a single carrier joint frequency domain equalization and interference cancellation (FDE-IC) with diversity combining for different relaying schemes. We consider amplify-and-forward (AF) and ACK/NACK-aided decode-and-forward (DF) modes over multiple-input multiple-output (MIMO) frequency selective relay channels. During the first time slot, the source transmits to both the relay and destination. In the second slot, the relay transmits the signal packet to the destination in the case of AF mode, while in DF the data block is transmitted either by the relay or the source depending on the ACK/NACK feedback. By deriving an equivalent source-relay-destination (S → R → D) channel for the AF mode, we propose an integrated iterative minimum mean square error (MMSE)-FDE-IC-aided transmission combining scheme where reception over multiple slots is viewed as virtual antennas. We also derive the joint combining scheme in the case of ACK/NACK-aided DF. Block error rate (BLER) performance is evaluated for different system settings.
Absorptive Capacities for Sustainability Technologies: Perspectives from the BRICS and China

Abstract For the development process in the rapidly growing economies, knowledge transfer and technology cooperation are becoming important issues. Research and technological competences are key indicators for the absorptive capacity of sustainability technologies and for the ability to export them. These issues are analyzed empirically for Brazil, Russia, India, China and South Africa (BRICS). Sustainability related research in BRICS is mostly carried out within broader, more sector oriented programmes. Specialization patterns of international patents and in foreign trade indicate various strengths and weaknesses of the BRICS countries. The differences within the countries imply that the analysis must proceed at a technology specific level. China has considerable capabilities in technologies such as photovoltaics, solar thermal or buildings. There is a strong need for strategic positioning of the countries and for coordination of the various policy fields involved.
Optimum and Sub-Optimum Lattice-Reduction-Aided Detection and Precoding for MIMO Communications

In the original work on latticereduction-aided detection by Yao and Wornell [1] only 2 × 2 systems were considered, while the extension to higher-dimensional settings was shown to be possible by means of the so-called LLL algorithm in [2]. In the present paper we show that the performance obtained from the suboptimum LLL algorithm is comparable to that achievable with the “optimum” and high-complexity Korkine-Zolotareff reduction algorithm for practical dimensionalities of the system.
Hovac: A Configurable Fault Injection Framework for Benchmarking the Dependability of C/C++ Applications

The increasing usage of third-party software and complexity of modern software systems makes dependability, in particular robustness against faulty code, an ever more important concern. To compare and quantitatively assess the dependability of different software systems, dependability benchmarks are needed. We present a configurable tool for dependability benchmarking, Hovac, which uses DLL API hooking to inject faults into third party library calls. Our fault classes are implemented based on the Common Weakness Enumeration (CWE) database, a community maintained source of real life software faults and errors. Using two example applications, we discuss a detailed and systematic approach to benchmarking the dependability of C/C++ applications using our tool.
Calcium-Dependent Paired-Pulse Facilitation of Miniature EPSC Frequency Accompanies Depression of EPSCs at Hippocampal Synapses in Culture

Two forms of evoked neurotransmitter release at excitatory synapses between cultured hippocampal neurons have been described. After an action potential, it has been shown that transmitter initially is released synchronously, and this is followed by a period of “slow” asynchronous release. The “fast” synchronous component of release at these synapses has been found routinely to demonstrate paired-pulse and tetanic depression, whereas the short-term plasticity of asynchronous release has not been investigated. In the present experiments, we have used the whole-cell patch-clamp technique to record from pairs of neurons in a low-density hippocampal culture preparation to determine both the properties and underlying mechanisms of short-term plasticity of asynchronous release. It was found that an increase in miniature EPSC (mEPSC) frequency accompanied both single and multiple stimuli, and this mEPSC increase was facilitated during paired stimuli, even when the evoked synchronous release was depressed. In addition, both the activity-dependent depression of evoked EPSCs and facilitation of asynchronous mEPSC release were dependent on Ca accumulation in the nerve terminal. However, the Ca-dependent mechanisms underlying these two processes could be distinguished by the differential effects of two membrane-permeant calcium chelators, BAPTA-AM and EGTA-AM. Frequency-dependent depression of evoked EPSCs involves a rapid rise in intraterminal Ca, which likely triggers a process that proceeds in a Ca-independent manner, whereas the asynchronous release may be linked more directly to a sustained increase in intraterminal Ca.
Glass ceiling and sticky floors: hurdles for Mauritian working women

Purpose – The purpose of this paper is to analyse the gender wage differential at different points of the wage distribution. It investigates the existence of glass ceilings and sticky floors in the Mauritian labour market. There is no previous empirical work studying gender inequality in the labour market for the small island economy of Mauritius. Design/methodology/approach – To investigate whether wage differentials are higher at the top or bottom ends of the wage distribution, the authors examine the wage disparities across different quantiles of the wage distribution. The gender wage disparities are assessed using quantile regression and decomposition techniques at the 10th, 25th, 50th, 75th and 90th quantiles. Survey data from the Continuous Multi-Purpose Household Survey from 2006 to 2013 is used. Findings – The results reveal that sticky floors are more pronounced than glass ceilings over the years. Further, for the years 2008, 2010 and 2012, it is noted that at the 75th quantiles, the gender wage .
Forward-secure signatures in untrusted update environments: efficient and generic constructions

Forward-secure signatures (FSS) prevent forgeries for past time periods when an attacker obtains full access to the signer's storage. To simplify the integration of these primitives into standard security architectures, Boyen, Shacham, Shen and Waters recently introduced the concept of forward-secure signatures with untrusted updates where private keys are additionally protected by a second factor (derived from a password). Key updates can be made on encrypted version of signing keys so that passwords only come into play for signing messages. The scheme put forth by Boyen et al. relies on bilinear maps and does not require the random oracle. The latter work also suggested the integration of untrusted updates in the Bellare-Miner forward-secure signature and left open the problem of endowing other existing FSS systems with the same second factor protection. This paper solves this problem by showing how to adapt the very efficient generic construction of Malkin, Micciancio and Miner (MMM) to untrusted update environments. More precisely, our modified construction - which does not use random oracles either - obtains a forward-secure signature with untrusted updates from any 2-party multi-signature in the plain public key model. In combination with Bellare and Neven's multi-signatures, our generic method yields implementations based on standard assumptions such as RSA, factoring or the hardness of computing discrete logarithms. Like the original MMM scheme, it does not require to set a bound on the number of time periods at key generation.
Overcoming intrinsic inhibitory pathways to augment the antineoplastic activity of adoptively transferred T cells

Effector T cells become rapidly inactivated after antigen exposure due to extracellular as well as intrinsic signals. We have recently demonstrated that the deletion of diacylglycerol kinases, intrinsic inhibitors of T-cell signaling, enhances the activity of adoptively transferred T cells expressing a chimeric antigen receptor (CAR) specific for a tumor-associated antigen.
A graphical framework to detect and categorize diverse opinions from online news

This paper proposes a graphical framework to extract opinionated sentences which highlight different contexts within a given news article by introducing the concept of diversity in a graphical model for opinion detection.We conduct extensive evaluations and find that the proposed modification leads to impressive improvement in performance and makes the final results of the model much more usable. The proposed method (OP-D) not only performs much better than the other techniques used for opinion detection as well as introducing diversity, but is also able to select opinions from different categories (Asher et al. 2009). By developing a classification model which categorizes the identified sentences into various opinion categories, we find that OP-D is able to push opinions from different categories uniformly among the top opinions.
Low Investment and Large LDC Debt in the 1980's

This paper aims at disentangling the correlation between LDC debt and investment in the 1980s. The author shows that a large debt was not an unconditional predictor of low investment in the 1980s, nor was investment abnormally low when compared to a 'financial-autarky' rate calculated in the text. He does find, however, that the actual service of the debt crowded out investment. For the rescheduling countries, he shows that 1 percent of GDP paid abroad reduced domestic investment by 0.3 percent of GDP. This is identical to the correlation between investment and foreign finance observed in the 1960s. Copyright 1993 by American Economic Association.
From "Events" to "Activities": Creating Abstraction Techniques for Mining Students' Model-Based Inquiry Processes

In this paper, we present a technique that we have developed to transform sequences of technical events into more abstract actions and semantic activities. The sequences of more abstract units are then used for discovering patterns of students’ interaction with computer models using heuristic miner. Our proposed approach automatically segments sequences of technical events that occurred during model runs and pauses and, on the basis of the nature of technical events that occurred during model runs and pauses, clusters them into actions. Then, using heuristic rules, it classifies actions into activities. We demonstrate the usefulness of our multilevel abstraction for extracting and exploring characteristic patterns of students’ interaction with computer models. Our study shows that each abstraction level could help to identify distinct characteristics of students’ interaction.
Person Re-identification Based on Group Context Strategy

In this paper, we focus on small group context and propose a group context strategy for the person re-identification. We consider the small group context information as a robust cue that used for the non-overlapping surveillance cameras re-identity work. More precisely, we exploit the small group context information by the group context strategy to improve the re-identity work performance. Experimental results demonstrate that group affiliation information is a robust cue and the group context strategy can improve re-identity performance, and our proposed works substantially better than other current state-of-the-art person re-identification methods.
An Object-Oriented Approach of Extracting Special Land use Classification by using Quick Bird Image

The ability to extract the special land use type of environment, and associated temporal changes, has important societal and economic meaning. This paper uses the high spatial resolution of the image---QuickBird to extract greenhouse in agriculture of Hexian region, ANHUI province in China. The paper uses software package eCognition to process data and extract information. The software adopted object-oriented image segmentation and classification which is based on fuzzy logic. In this study the greenhouse is a special land cover type in agricultural land, we use not only image object's attributes, but also the relationship between networked image objects; it can perform sophisticated classification and get satisfied classification result, allows the integration of a broad spectrum of different object features, such as spectral values, shape and texture. The aim of this work was to develop an object-oriented segmentation and classification approach for extracting special land cover type.
Effect of Grape Polyphenols on Blood Pressure: A Meta-Analysis of Randomized Controlled Trials

Background The effect of grape polyphenols on blood pressure remains unclear, which we aimed to address via a meta-analysis study. Methods We conducted study trial searches in PubMed, Embase, and the Cochrane Library databases. Summary estimates of weighted mean differences and 95% confidence intervals were obtained by using fixed-effects models. Subgroup analyses were performed to identify the source of heterogeneity. The protocol details of our meta-analysis have been submitted to the international database of prospectively registered systematic reviews (registration number CRD42015019196). Results Ten studies were included in the present meta-analysis. Our results showed daily grape polyphenol intake could significantly reduce systolic blood pressure by 1.48 mmHg when compared to control subjects (12 comparisons; -1.48 [-2.79 to -0.16] mmHg; P = 0.03). Subgroup analyses indicated larger reduction was identified in the intake of low-dose of grape polyphenols (< 733 mg/day, median level of the included studies) or patients with metabolic syndrome. Contrarily, diastolic blood pressure was not significantly decreased in the grape polyphenols group as compared to controls. No significant heterogeneity or publication bias was detected in the meta-analysis of either systolic or diastolic blood pressure. Conclusions Daily grape polyphenol intake can significantly reduce the systolic blood pressure in humans, although the reduction is modest when compared with anti-hypertensive medications. Larger, better designed trials, that specifically include hypertensive subjects, are required to verify our results in the future.
Policy Learning with Continuous Memory States for Partially Observed Robotic Control

Policy learning for partially observed control tasks requires policies that have the ability to store information from past observations. In this paper, we present a method for learning policies with memory for high-dimensional, continuous systems. Our approach does not assume a known state representation and does not attempt to explicitly model the belief over the unobserved state. Instead, we directly learn a policy that can read and write from an internal continuous-valued memory. This type of policy can be interpreted as a type of recurrent neural network (RNN). However, our approach avoids many of the common problems that plague RNNs, such as the vanishing and exploding gradient issues, by instead representing the memory as state variables. The policy is then optimized by using a guided policy search algorithm that alternates between optimizing trajectories through state space (including both physical and memory states), and training a policy with supervised learning to match these trajectories. We evaluate our method on tasks involving continuous control in manipulation and navigation settings, and show that our method can learn complex policies that successfully complete a range of tasks that require memory.
Multipath Mitigation for Bridge Deformation Monitoring

GPS carrier phase multipath with varying amplitudes of up to several centimetres and periods of couple of minutes is a major error source, which affects the correct interpretation of bridge deformation. In this paper, a recursive adaptive filtering (AF) algorithm has been employed to mitigate multipath signature in the coordinate time series of GPS solutions. In order to maximise the suppression of the multipath signature, exact alignment of the input time series into the AF system is crucial. An algorithm using the cross-correlation coefficient of day-to-day GPS coordinate time series is presented to align GPS coordi-nates. To isolate multipath from the contaminated GPS coordinate time series, relative displacements cal-culated from the accelerations sensed simultaneously with GPS receiver by a triaxial accelerometer housed in a specially designed cage is used as the reference signal sequence within the AF system. Associated al-gorithm for the relative velocity and displacement calculation is also introduced in the paper. It demon-strates that it is possible to achieve millimetre positioning accuracy by the AF approach and an integrated sensor system of GPS receiver and triaxial accelerometer.
Currency Management: Overlay and Alpha Trading

CONTENTS PART 1 - Introduction to FX Markets and Modelling CHAPTER 1 - Market History and Structure - Neil Record (Record Currency Management) CHAPTER 2 - The Electronic Revolution in Foreign Exchange - James van der Heule (Citigroup) CHAPTER 3 - Risks and Rewards - Jessica James (Citigroup) CHAPTER 4 - Where Overlay Comes In - Arun Muraldihar (FX Concepts, Inc.) CHAPTER 5 - The Case for Currency Management - Brian Strange (JPMorgan Fleming Investment Management) PART 2 - Currency Risk and Hedging CHAPTER 6 - FX Risk - Jessica James (Citigroup) CHAPTER 7 - Traditional Hedging Methods - Chris Attfield (PaR Asset Management LLP) CHAPTER 8 - Active vs Passive Hedging - Henrik H. Pedersen (CitiFX Risk Advisory Group) CHAPTER 9 - A Framework to Determine a Currency Hedge Ratio for an International Portfolio - Eric Busay (Fixed Income Unit CalPERS) PART 3 - Designing and Implementing a Trading Strategy CHAPTER 10 - Trading for Profit - Jessica James (Citigroup) CHAPTER 11 - Trading Models - James Binny (ABN AMRO) CHAPTER 12 - Model building and testing - Gerben J. de Zwart (Robeco Quantitative Research) CHAPTER 13 - Practical Strategy Implementation - Ron Liesching (Pareto) PART 4 - Case Studies CHAPTER 14 - A Case Study on Bringing FX Prime Brokerage to Currency Overlay - Philip Simotas (FX Concepts) CHAPTER 15 - Currency Risk vs Return in Global Bond Portfolios: A Policy, not a Benchmark Issue - Charles Dolan (Pareto)