Miracle-dz/UniFAR-FTUs huggingface dataset:
Unifying Text and Link Analysis

This position paper presents a simple yet profound idea. By thinking about the relationships between and within terms and documents, we can generate a richer representation that encompasses aspects of Web link analysis as well as text analysis techniques from information retrieval. This paper shows one path to this unified representation, and demonstrates the use of eigenvector calculations from Web link analysis by stepping through a simple example. We further speculate that this general approach, which we term relationship analysis, can apply to other domains as well.
Effective Performance Management with the Balanced Scorecard Technical Report

The publishers of this document consider that it is a worthwhile contribution to discussion, without necessarily sharing the views expressed. No responsibility for loss occasioned to any person acting or refraining from action as a result of any material in this publication can be accepted by the authors or the publishers. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means method or device, electronic (whether now or hereafter known or developed), mechanical, photocopying, recorded or otherwise, without the prior permission of the publishers. This report focuses on one such framework: the balanced scorecard. Of the tools designed to improve corporate performance, the balanced scorecard has probably been the most popular. Originally developed as a performance measurement tool, the scorecard is now associated increasingly with strategy implementation. It acts as a management framework with the potential to identify and exploit organisations' key value drivers to their best strategic advantage. This report considers the more recent developments in scorecard thinking, in particular the key role of strategy mapping. It outlines how, through wide application, and facing ever-changing operating conditions, the scorecard has developed over the last ten years, to support different organisational 'missions' – from profit maximisation, to service delivery or resource optimisation. For example, many organisations are realising increasingly that much of their strategic value lies in their people, systems, processes and ability to innovate – this report includes an explanation of how organisations can integrate the potential of these intangibles in their scorecard. The scorecard has been used successfully by organisations (public, private and not-for-profit) to realise and integrate the strategic contribution of all relevant organisational value drivers for two key reasons: First, it helps to ensure consistency and alignment between the non-financial and the financial measures, (this helps to facilitate the alignment of the measures and strategy). Second, it helps to identify and measure the specific value drivers that underpin performance. This allows managers to test their hypotheses on what is driving organisational outcomes. The report considers the use of the balanced scorecard to link strategy to resources and then to performance measures, and offers guidance on the strategy mapping process to ensure robust cause-and-effect linkage. New approaches to bridging the gap between strategy and the balanced scorecard such as value-creation mapping and the value dynamics framework are profiled. To help organisations' scorecard …
mAKAP assembles a protein kinase A/PDE4 phosphodiesterase cAMP signaling module

Spatiotemporal regulation of protein kinase A (PKA) activity involves the manipulation of compartmentalized cAMP pools. Now we demonstrate that the muscle‐selective A‐kinase anchoring protein, mAKAP, maintains a cAMP signaling module, including PKA and the rolipram‐inhibited cAMP‐specific phosphodiesterase (PDE4D3) in heart tissues. Functional analyses indicate that tonic PDE4D3 activity reduces the activity of the anchored PKA holoenzyme, whereas kinase activation stimulates mAKAP‐associated phosphodiesterase activity. Disruption of PKA–mAKAP interaction prevents this enhancement of PDE4D3 activity, suggesting that the proximity of both enzymes in the mAKAP signaling complex forms a negative feedback loop to restore basal cAMP levels.
A proposed multi-agent based platform for monitoring and control of Active Power Distribution Systems

Giving the current integration of large numbers of small distributed generation units connected to the medium and low voltage power distribution grid, may lead to multiple problems, that limits network’s capacity. To overcome those challenges, the concept of Smart Grid implements the required characteristics to ensure voltage stability, minimize power losses supply/demand balance, etcetera. Because of the time constraints, the decentralized control seems to be the solution, which can be achieved by the multi agent-system technology. To test the applications of multi-agent system in the monitoring and control of active power distribution systems, this paper proposes an intelligent platform architecture. The used technologies are presented, with the reasons behind the selections, resulting in an architecture composed of Matlab – MySQL – JADE. At the level of Matlab, the modeling and simulation modules are developed, under the form of graphical user interface. A study case is presented, who will refer to a 15 bus medium voltage power distribution grid, which is modelled with the graphical module, and analyzed with the real time simulation module.
A Hardware-In-the-Loop Simulation Platform for Prototyping and Testing of Wind Generator Controllers

SUMMARY To meet the growing demand for integration of renewable energy sources onto today’s power grids, many engineers from different specialized fields must be involved since various types of studies need to be conducted. The integration of distributed generation (DG) sources significantly changes the characteristics of an entire network. Such interconnection projects will require analysis of power quality, transient response to fault occurrences, protection coordination studies and controller interaction studies. The first considerable challenge is related to power electronic converters, which are increasing in number and found on most DG sources. Accurately simulating fast switching devices requires the use of very small time steps to solve the system’s equations. Off-line simulation is widely used in the field but it is time consuming if no precision compromise has been made on models (i.e. the use of average models). Moreover, off-line simulation tools do not offer the wide range of possibilities available with state-of-the-art distributed real-time simulators. Such tools combine, for instance, the efforts of control engineers and specialists from wind turbine manufacturers, who need to test their controllers using hardware-in-the-loop (HIL), together with those of network planning engineers from public utilities, who will conduct interconnection, interaction and protection studies. The eMEGAsim simulation platform is fully integrated with Simulink/SimPowerSystems (SPS) from The MathWorks and EMTPRV. This makes eMEGAsim a valuable solution for engineers who already have models built with these off-line simulation applications, as well as for less experienced users. This paper focuses on the prototyping and testing of DG controllers using hardware-in-the-loop simulation. The model described in this paper is a 10-turbine wind farm connected to a single feeder, simulated using an eMEGAsim real-time simulator equipped with 8-processor cores. One of the wind turbines is controlled using an externally emulated controller. The emulated controller model consists of a replica of all other wind turbine controllers, which are locally simulated in the plant model. It is modeled and simulated using a dual-processor core real-time simulator, which interacts with the plant model via analog and fast digital inputs and outputs. This paper validates the proposed real-time simulator for the study of wind-farm electromagnetic disturbance studies with HIL-connected DFIG controllers, particularly that the simulator can be interfaced with high-frequency PWM controllers without distortions caused by the sampling time of the simulator.
Resource Allocation and Scheduling in Heterogeneous Cloud Environments

Recently, there has been a dramatic increase in the popularity of cloud computing systems that rent computing resources on-demand, bill on a pay-as-you-go basis, and multiplex many users on the same physical infrastructure. These cloud computing environments provide an illusion of infinite computing resources to cloud users so that they can increase or decrease their resource consumption rate according to the demands. At the same time, the cloud environment poses a number of challenges. Two players in cloud computing environments, cloud providers and cloud users, pursue different goals; providers want to maximize revenue by achieving high resource utilization, while users want to minimize expenses while meeting their performance requirements. However, it is difficult to allocate resources in a mutually optimal way due to the lack of information sharing between them. Moreover, ever-increasing heterogeneity and variability of the environment poses even harder challenges for both parties. In this thesis, we address "the cloud resource management problem", which is to allocate and schedule computing resources in a way that providers achieve high resource utilization and users meet their applications' performance requirements with minimum expenditure. We approach the problem from various aspects, using MapReduce as our target application. From provider's perspective, we propose a topology-aware resource placement solution to overcome the lack of information sharing between providers and users. From user's point of view, we present a resource allocation scheme to maintain a pool of leased resources in a cost-effective way and a progress share-based job scheduling algorithm that achieves high performance and fairness simultaneously in a heterogeneous cloud environment. To deal with variability in resource capacity and application performance in the Cloud, we develop a method to predict the job completion time distribution that is applicable to making sophisticated trade-off decisions in resource allocation and scheduling. Our evaluation shows that these methods can improve efficiency and effectiveness of cloud computing systems.
Host Dependent Evolutionary Patterns and the Origin of 2009 H1N1 Pandemic Influenza

The origin of H1N1pdm constitutes an unresolved mystery, as its most recently observed ancestors were isolated in pigs nearly a decade before it emerged in humans. One theory suggests imperfect surveillance of swine viruses caused the virus to be missed in swine herds. Other hypotheses point to the possibility of laboratory error or an avian intermediary. We show substitution bias classification identifies the host where a virus has been evolving. Comparing the evolution of H1N1pdm ancestors with other influenza viruses, we show the evolutionary history in unsampled years is similar to the evolution of other swine viruses, presenting evidence it emerged from unsampled herds.
Extremely High Mutation Rate of HIV-1 In Vivo

Rates of spontaneous mutation critically determine the genetic diversity and evolution of RNA viruses. Although these rates have been characterized in vitro and in cell culture models, they have seldom been determined in vivo for human viruses. Here, we use the intrapatient frequency of premature stop codons to quantify the HIV-1 genome-wide rate of spontaneous mutation in DNA sequences from peripheral blood mononuclear cells. This reveals an extremely high mutation rate of (4.1 ± 1.7) × 10−3 per base per cell, the highest reported for any biological entity. Sequencing of plasma-derived sequences yielded a mutation frequency 44 times lower, indicating that a large fraction of viral genomes are lethally mutated and fail to reach plasma. We show that the HIV-1 reverse transcriptase contributes only 2% of mutations, whereas 98% result from editing by host cytidine deaminases of the A3 family. Hypermutated viral sequences are less abundant in patients showing rapid disease progression compared to normal progressors, highlighting the antiviral role of A3 proteins. However, the amount of A3-mediated editing varies broadly, and we find that low-edited sequences are more abundant among rapid progressors, suggesting that suboptimal A3 activity might enhance HIV-1 genetic diversity and pathogenesis.
Hybrid Machine Aided Translation System based on Constraint Synchronous Grammar and Translation Corresponding Tree

As the demand of translating large volume of material between Portuguese and Chinese is increasing rapidly nowadays, especially in the city of Macau, the translation work becomes impractical without the support of effective tools. In order to fulfill this gap and build up a translation workbench environment for translators, a Machine Aided Translation System between these languages, PCTAssist, is introduced. It is a hybrid system that applies not only Translation Memory technology but also Machine Translation methodologies, including the annotation schema of Translation Corresponding Tree (TCT) in the representation of bilingual examples, and the language formalism Constraint Synchronous Grammar (CSG) in analyzing the syntactic structure between the languages to accomplish the translation task.
SVM-based clause-dependency determination in syntactic analysis

In syntactic analysis of a long sentence, it is difficult to determine the dependency among clauses. To handle such syntactic ambiguity among clauses, this paper proposes a machine learning-based determination method of clause-dependency. We extract various features from clauses, and experiment using SVM machine learning algorithm. Our experimental results showed that the proposed SVM-based method outperformed the previous methods.
The Model of PK/PD for Danhong Injection Analyzed by Least Square Method

The correlation of PK/PD for Danhong Injection (DHI) was investigated by the least square method in a rat model of cerebral ischemia/reperfusion. [Methods] Sprague-Dawley rats were randomly divided into 4 equal groups (each n = 6) (sham group), cerebral IR damage alone (model group), IR model treated with DHI (treatment group), and IR model treated with nimodipine (positive group). The drugs concentration of Danshensu (DSS) and Hydroxysafflor yellow A (HSA) in Plasma were measured by HPLC at 5, 15, 30, 60, 120, 180, 240, and 360 min. The levels of IL-1β in Plasma were measured by method of enzyme-linked immunosorbent assay. Curves were fit using nonlinear least squares methods. The results showed that levels of IL-1β were decreased after 60, 120, 180, 240, and 360 min (P <; 0.05) and infarct volume (%) was reduced compared to the model group (P <; 0.01). Regression equation of DSS and HSA showed that IL-1β and DSS were better fit than those for HSA. DHI reduces inflammation in cerebral ischemic injury. And the DSS in DHI mainly reduce IL-1β in a rat model of cerebral ischemia/reperfusion.
Applying Universal Dependency to the Arapaho Language

This paper discusses the use of Universal Dependency for annotations of a Native North American language Arapaho (Algonquian). While some relations of the universal dependency perfectly correspond with those in Arapaho, language specific annotations of verbal arguments elucidate problems of assuming certain syntactic categories across languages. By critiquing the influence of grammatical structures of major European and Asian languages in establishing the UD framework, this paper develops guidelines for annotating a polysynthetic agglutinating language and sets a path to developing a more comprehensive cross-linguistic approach to syntactic annotations of language data.
Experimental performance analysis of two-hop aerial 802.11 networks

Small-scale multicopters operating as autonomous teams in the air are envisioned for aerial monitoring and transport of goods in a variety of applications, including disaster management and environmental monitoring. For such applications to become reality, a high-throughput wireless network is needed. This paper presents experimental performance results with commercially available quadrocopters communicating via IEEE 802.11a. In particular, we compare the infrastructure and mesh modes of 802.11 for one-hop and two-hop communications, thus analyzing network layer versus MAC layer relaying. Results illustrate that changes are required in the mesh mode to support applications demanding high throughput with low jitter.
What moves GNP

This paper aims at identifying the main shocks, which cause movements in real GNP. It does so by searching for two shocks in the context of a VAR model, which explain the majority of the k-step ahead prediction error variances in real GNP for horizons between 0 and 5 years. We find that two shocks can typically explain more than 90\% of the variance at all horizons for real GNP. While one shock looks like a productivity shock in the line of the real business cycle literature, the other one seems to be wage-push or inflationary shock, unrelated to consumption or government spending and not induced by monetary policy. While the first shock can be viewed as a ''supply shock'', the second shock does not have an obvious ''demand shock'' interpretation.
A report on design and implementation of protected searchable data in IaaS

In the first part of this report we present a survey of the state of the art in searchable encryption and its relevance for cloud computing. In particular we focus on the OpenStack open-source cloud platform and investigate which searchable encryption schemes are more amenable for adoption in conjunction with platforms based on OpenStack. Based on that survey we chose one of the schemes to implement and test if it is practical enough to deploy in real systems. On the second part of this report we discuss the results of the implementation.
The Theory of Triangle Type-2 Fuzzy Sets

Interval Type-2 Fuzzy Set is the most popular kind of Type-2 Fuzzy Set, its characteristic is that all the secondary membership functions equal to 1. Though Interval Type-2 Fuzzy Sets can reduce the calculation complexity than other Type-2 Fuzzy Sets, it loses much fuzzy information simultaneously. In order to solve this problem we propose a novel theory of Triangle Type-2 Fuzzy Sets, the formulas for union, intersection and complement of Triangle Type-2 Fuzzy Sets are derived and proven in detail. In addition, the relationship and the conversion between Triangle Type-2 Fuzzy Sets and Interval Type-2 Fuzzy Sets are discussed.
Link suggestions in terrorists networks using Semi Discrete Decomposition

Recently several terrorist acts have created disruptions in the airline industries, tourism as well as the financial markets. It is believed just like the World War II had accelerated the development of nuclear energy, the longer-term impact of the current war on terrorism could lead to the allocation of major resources (manpower, funding etc.) towards dealing with this. In this paper, we present a social network concept to visualize a terrorist network. Visualization is very important part for analyzing a network since it can quickly provide good insight into the network structure, major members, and their properties. We used a matrix factorization methods called Semi Discrete Decomposition, which is highly suitable for dealing with huge networks. Empirical results using the 9–11 network data illustrate the efficiency of the proposed approach.
A Memory-Based Alternative for Connectionist Shift-Reduce Parsing

In this paper we present memory-based learning (mbl) as a psychologically plausible model of natural language processing. Mbl shows a state-of-the-art performance on real-world language tasks, such as word pronunciation , word sense disambiguation and parsing. We compare mbl to a neural network model, SardSrn (May-berry & Miikkulainen, 1999) on a parsing task, and we show that mbl has a better generalisation accuracy on the test set. Mbl has a solid foundation in the psychological literature within theories on human categorisa-tion and reasoning. We argue that mbl is an alternative psychologically plausible model for human parsing, next to neural network models.
Ataxia Telangiectasia Mutated and Rad3 Related (ATR) Protein Kinase Inhibition Is Synthetically Lethal in XRCC1 Deficient Ovarian Cancer Cells

Introduction Ataxia telangiectasia mutated and Rad3 Related (ATR) protein kinase is a key sensor of single-stranded DNA associated with stalled replication forks and repair intermediates generated during DNA repair. XRCC1 is a critical enzyme in single strand break repair and base excision repair. XRCC1-LIG3 complex is also an important contributor to the ligation step of the nucleotide excision repair response. Methods In the current study, we investigated synthetic lethality in XRCC1 deficient and XRCC1 proficient Chinese Hamster ovary (CHO) and human ovarian cancer cells using ATR inhibitors (NU6027). In addition, we also investigated the ability of ATR inhibitors to potentiate cisplatin cytotoxicity in XRCC1 deficient and XRCC1 proficient CHO and human cancer cells. Clonogenic assays, alkaline COMET assays, γH2AX immunocytochemistry, FACS for cell cycle as well as FITC-annexin V flow cytometric analysis were performed. Results ATR inhibition is synthetically lethal in XRCC1 deficient cells as evidenced by increased cytotoxicity, accumulation of double strand DNA breaks, G2/M cell cycle arrest and increased apoptosis. Compared to cisplatin alone, combination of cisplatin and ATR inhibitor results in enhanced cytotoxicity in XRCC1 deficient cells compared to XRCC1 proficient cells. Conclusions Our data provides evidence that ATR inhibition is suitable for synthetic lethality application and cisplatin chemopotentiation in XRCC1 deficient ovarian cancer cells.
A CRITICAL REALIST APPROACH TO ORGANIZATIONAL INNOVATION RESEARCH Submission to 4 th International Critical Management Studies Conference Critical Realism : Progress and Challenges Stream

Current perspectives on innovation processes in organizations agree that innovation is a complex, dynamic, and multi-level phenomenon. Yet, few substantive theoretical accounts exist which adequately integrate multiple levels of analysis and explain innovation and change in terms of the interconnections between structural influences and individual action. Addressing this challenge requires an explanatory framework that takes into account both micro and macro perspectives. In this study, a microanalysis drawing from the sociology of translation was situated within Archer’s Realist Morphogenetic framework in order to provide a more holistic explanation of the innovation development process. The resulting model depicts the development of Six Sigma as a multilayered process occurring via socio-ideational-political cycles involving the complex interaction of cultural, agential and structural influences over time.
Towards load balancing in SDN-networks during DDoS-attacks

Software Defined Networks (SDN) are becoming a trending technology in modern Internet. This technology helps to solve a significant number of well-known engineering problems in a effective and elegant way as they provide software-defined centralized network control. An SDN controller can be extended with application that effectively serve for concrete purposes and provide flexible management of network flows. This opens a great number of opportunities for a lot of network security problems such as maintaining of privileges in a proper way, splitting control and data planes, and attacks detection and mitigation. In this work we consider the opportunities of SDN for a “survival” mitigation during DDoS attacks, the load balancing problem. We propose two-level balancing solution in SDN networks, which includes traditional balancing between servers and load balancing between network devices as well. Experiments show that our solution increase “survival” time of a system during DDoS attack in times compared to existing balancing solution in SDN networks.