Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Cell-DEVS Methodology for Modeling the Environment

Recent research efforts have focused on the analysis of environmental systems using cellular models. Although most of the existing solutions are based on the cellular automata formalism, this technique has some problems that constrain its power, usability and feasibility for studying large complex systems. Instead, combining cellular automata with discrete event systems specifications (DEVS) showed excellent results in terms of quality and performance. Despite these encouraging results, the environmental science/engineering community still prefers more traditional approaches, as DEVS-based techniques require a fundamental change of the modeling and simulation paradigm, while entailing expertise in advanced programming, distributed computing, etc. Cell-DEVS and the CD++ toolkit were created to address these problems: they simplify the construction of complex cellular models by allowing simple and intuitive model specification. The discrete event nature of the formalism provides better precision and performance, and models can run in different simulation environments (single user, real-time, distributed/parallel) without special expertise required. Environmental applications can be easily constructed, making it possible for users with basic training in the techniques and software tools to face the study of complex problems. We present the definition of different models of environmental applications, including the pollution on a basin, fire spreading, watershed formation and viability of a population, focusing on how to define such applications using Cell-DEVS methodology, using an approach that facilitates this paradigm shift.
A review of validation research on structured employment interviews : exploring the threats to validity.

The main purpose of this study was to explore the threats to internal and external validity that international research on structured employment interviews may have been prone to. On the basis of this exploration, suggestions were rendered on how the perceived threats to internal validity could have been managed. In addition, commentary was offered on whether or not the threats to external validity appear to have been actualised in the international studies that were compared. These constituted the secondary aims of the study. In order to accomplish the primary aim of the study a qualitative approach was employed. Using the literature on the thr~~ts to internal and external validity as a fundamental point of departure, studies on the two main variants of structured employment interviews (viz. behaviour description interviews and situational interviews) were analysed. This analysis yielded an insight into the potential threats that are likely to have impacted on the validity findings that were obtained in these studies. On the basis of these insights, suggestions, pertaining to how the threats to internal validity could have been managed, were proposed. In addition, a meta-analytic technique, for comparing the findings across multiple studies, was employed to comment on whether or not the threats to external validity appear to have manifested in the studies in question. These combined insights served as the foundation for offering a South African perspective on the threats to internal and external validity, which included recommendations on how they could be effectively managed in validation research in the South African context.
GTPA: A Generative Model For Online Mentor-Apprentice Networks

There is a large body of work on the evolution of graphs in various domains, which shows that many real graphs evolve in a similar manner. In this paper we study a novel type of network formed by mentor-apprentice relationships in a massively multiplayer online role playing game. We observe that some of the static and dynamic laws which have been observed in many other real world networks are not observed in this network. Consequently well known graph generators like Preferential Attachment, Forest Fire, Butterfly, RTM, etc., cannot be applied to such mentoring networks. We propose a novel generative model to generate networks with the characteristics of mentoring networks.
A comparative study of HITS vs PageRank algorithms for Twitter users analysis

Social Networks such as Facebook, Twitter, Google+ and LinkedIn have millions of users. These networks are constantly evolving and it is a good source of information, both explicitly and implicitly. The analysis of Social Network mainly focuses on the aspect of social networking with an emphasis on mapping relationships, patterns of interaction between user and content information. One of the common research topics focuses on the centrality measures where useful information of the connected people in the social network is represented in a graph. In this paper, we employed two link-based ranking algorithms to analyze the ranking of the users: HITS (Hyperlink-Induced Topic Search) and PageRank. We constructed Twitter user retweet-relationship graph using 21 days worth of data. Lastly, we compared the ranking sequence of the users in addition to their followers count against the average and also whether they are verified Twitter accounts. From the results obtained, both HITS and PageRank showed a similar trend, and more importantly highlighted the importance of the direction of the edges in this work.
The Transatlantic Exoplanet Survey (TrES): A Review

The TrES project is designed to search for exoplanetary transits using three wide-field optical telescopes of 10-cm in diameter, in three different observatories. We describe the instruments and strategies used by the team, which has been working as a network since 2003. We summarize the major findings and difficulties faced during these years, which include the discovery of two transiting planets, a pair of eclipsing M stars, and many configurations of stars that mimic the signal of transiting planets.
Monetary and Financial Interactions in the Business Cycle

This paper develops a computable general equilibrium model in which endogenous agency costs can potentially alter business cycle dynamics. The model resembles the influential theoretical work of Ben Bernanke and Mark Gertler (1989). Two sources of shocks are considered: productivity shocks and monetary shocks. The model is parametrized to match key features of U.S. aggregate activity. The principal result of the analysis is that agency costs add very little to the basic business cycle dynamics. Copyright 1995 by Ohio State University Press.
Trade, Climate Policy and Carbon Leakage - Theory and Empirical Evidence

Die vorliegende Arbeit wurde von Rahel Aichele wahrend ihrer Tatigkeit am ifo Institut erstellt. Sie wurde im Dezember 2012 abgeschlossen und als Dissertation von der volkswirtschaftlichen Fakultat der Universitat Munchen (LMU) akzeptiert. Die Arbeit besteht aus funf eigenstandigen Kapiteln. Die Kapitel untersuchen wie in einer globalisierten Welt Handelsstrome und die Auslagerung von Emissionen durch die internationale Klimapolitik einer begrenzten Lander-Koalition beeinflusst wird. Die Forschungsfrage besteht darin zu klaren, ob Carbon Leakage empirisch festzustellen ist. In diesem Fall wurde die Effektivitat unilateraler Klimapolitik unterminiert. Diese Doktorarbeit stellt neue empirische Tests fur Carbon Leakage bereit. Sie baut auf einem eigens entwickelten Paneldatensatz zum CO2-Gehalt bilateraler Handelsstrome und den CO2-Footprints von 40 Landern in den Jahren 1995-2007 auf. Das Kyoto-Protokoll stellt ein quasi-naturliches Experiment der internationalen Klimapolitik dar. Wir verwenden Methoden der Politikevaluierung um seine Effekte auf Emissionen (Kapitel 1), CO2-Footprints (Kapitel 2), Handelsstrome (Kapitel 3) und CO2-Gehalt von Handel (Kapitel 4) zu untersuchen. Die Problematik von Selbstselektion wird durch Fixeffekt-, Instrumentenvariablen- und Matchingokonometrieansatze addressiert. Wir finden empirische Evidenz fur Carbon Leakage in den Daten. Die Quantifizierung des Ausmases von Leakage erfolgt mit Hilfe eines strukturell geschatzten Ausenhandelsmodells (Kapitel 5). Die Simulation von kontrafaktischen Klimapolitikszenarien zeigt moderate, aber nicht vernachlassigbare Leakage-Raten auf.
Range-based Obstructed Nearest Neighbor Queries

In this paper, we study a novel variant of obstructed nearest neighbor queries, namely, range-based obstructed nearest neighbor (RONN) search. A natural generalization of continuous obstructed nearest-neighbor (CONN), an RONN query retrieves the obstructed nearest neighbor for every point in a specified range. To process RONN, we first propose a CONN-Based (CONNB) algorithm as our baseline, which reduces the RONN query into a range query and four CONN queries processed using an R-tree. To address the shortcomings of the CONNB algorithm, we then propose a new RONN by R-tree Filtering (RONN-RF) algorithm, which explores effective filtering, also using R-tree. Next, we propose a new index, called O-tree, dedicated for indexing objects in the obstructed space. The novelty of O-tree lies in the idea of dividing the obstructed space into non-obstructed subspaces, aiming to efficiently retrieve highly qualified candidates for RONN processing. We develop an O-tree construction algorithm and propose a space division scheme, called optimal obstacle balance (OOB) scheme, to address the tree balance problem. Accordingly, we propose an efficient algorithm, called RONN by O-tree Acceleration (RONN-OA), which exploits O-tree to accelerate query processing of RONN. In addition, we extend O-tree for indexing polygons. At last, we conduct a comprehensive performance evaluation using both real and synthetic datasets to validate our ideas and the proposed algorithms. The experimental result shows that the RONN-OA algorithm outperforms the two R-tree based algorithms significantly. Moreover, we show that the OOB scheme achieves the best tree balance in O-tree and outperforms two baseline schemes.
Mutational analysis of centrin: an EF-hand protein associated with three distinct contractile fibers in the basal body apparatus of Chlamydomonas

Centrin, a 20-kD phosphoprotein with four calcium-binding EF-hands, is present in the centrosome/basal body apparatus of the green alga Chlamydomonas reinhardtii in three distinct locations: the nucleus- basal body connectors, the distal striated fibers, and the flagellar transition regions. In each location, centrin is found in fibrous structures that display calcium-mediated contraction. The mutant vfl2 has structural defects at all of these locations and is defective for basal body localization and/or segregation. We show that the vfl2 mutation is a G-to-A transition in the centrin structural gene which converts a glutamic acid to a lysine at position 101, the first amino acid of the E-helix of the protein's third EF-hand. This proves that centrin is required to construct the nucleus-basal body connectors, the distal striated fibers, and the flagellar transition regions, and it demonstrates the importance of amino acid 101 to normal centrin function. Based on immunofluorescence analysis using anti-centrin antibodies, it appears that vfl2 centrin is capable of binding to the basal body but is incapable of polymerizing into filamentous structures. 19 phenotypic revertants of vfl2 were isolated, and 10 of them, each of which had undergone further mutation at codon 101, were examined in detail. At the DNA level, 1 of the 10 was wild type, and the other 9 were pseudorevertants encoding centrins with the amino acids asparagine, threonine, methionine, or isoleucine at position 101. No ultrastructure defects were apparent in the revertants with asparagine or threonine at position 101, but in those with methionine or isoleucine at position 101, the distal striated fibers were found to be incomplete, indicating that different amino acid substitutions at position 101 can differentially affect the assembly of the three distinct centrin-containing fibrous structures associated with the Chlamydomonas centrosome.
Charles A . Dice Center for Research in Financial Economics Why Did Some Banks Perform Better during the Credit Crisis ? A Cross-Country Study of the Impact of Governance and Regulation

Though overall bank performance from July 2007 to December 2008 was the worst since at least the Great Depression, there is significant variation in the cross-section of stock returns of large banks across the world during that period. We use this variation to evaluate the importance of factors that have been discussed as having contributed to the poor performance of banks during the credit crisis. More specifically, we investigate whether bank performance is related to bank-level governance, country-level governance, country-level regulation, and bank balance sheet and profitability characteristics before the crisis. Banks that the market favored in 2006 had especially poor returns during the crisis. Using conventional indicators of good governance, banks with more shareholder-friendly boards performed worse during the crisis. Banks in countries with stricter capital requirement regulations and with more independent supervisors performed better. Though banks in countries with more powerful supervisors had worse stock returns, we provide some evidence that this may be because these supervisors required banks to raise more capital during the crisis and that doing so was costly for shareholders. Large banks with more Tier 1 capital and more deposit financing at the end of 2006 had significantly higher returns during the crisis. After accounting for country fixed effects, banks with more loans and more liquid assets performed better during the month following the Lehman bankruptcy, and so did banks from countries with stronger capital supervision and more restrictions on bank activities.
Fast and effective visual place recognition using binary codes and disparity information

We present a novel approach for place recognition and loop closure detection based on binary codes and disparity information using stereo images. Our method (ABLE-S) applies the Local Difference Binary (LDB) descriptor in a global framework to obtain a robust global image description, which is initially based on intensity and gradient pairwise comparisons. LDB has a higher descriptiveness power than other popular alternatives such as BRIEF, which only relies on intensity. In addition, we integrate disparity information into the binary descriptor (D-LDB). Disparity provides valuable information which decreases the effect of some typical problems in place recognition such as perceptual aliasing. The KITTI Odometry dataset is mainly used to test our approach due to its varied environments, challenging situations and length. Additionally, a loop closure ground-truth is introduced in this work for the KITTI Odometry benchmark with the aim of standardizing a robust evaluation methodology for comparing different previous algorithms against our method and for future benchmarking of new proposals. Attending to the presented results, our method allows a fast and more effective visual loop closure detection compared to state-of-the-art algorithms such as FAB-MAP, WI-SURF and BRIEF-Gist.
Hexokinase–mitochondrial interactions regulate glucose metabolism differentially in adult and neonatal cardiac myocytes

In mammalian tumor cell lines, localization of hexokinase (HK) isoforms to the cytoplasm or mitochondria has been shown to control their anabolic (glycogen synthesis) and catabolic (glycolysis) activities. In this study, we examined whether HK isoform differences could explain the markedly different metabolic profiles between normal adult and neonatal cardiac tissue. We used a set of novel genetically encoded optical imaging tools to track, in real-time in isolated adult (ARVM) and neonatal (NRVM) rat ventricular myocytes, the subcellular distributions of HKI and HKII, and the functional consequences on glucose utilization. We show that HKII, the predominant isoform in ARVM, dynamically translocates from mitochondria and cytoplasm in response to removal of extracellular glucose or addition of iodoacetate (IAA). In contrast, HKI, the predominant isoform in NRVM, is only bound to mitochondria and is not displaced by the above interventions. In ARVM, overexpression of HKI, but not HKII, increased glycolytic activity. In neonatal rat ventricular myocytes (NVRM), knockdown of HKI, but not HKII, decreased glycolytic activity. In conclusion, differential interactions of HKI and HKII with mitochondria underlie the different metabolic profiles of ARVM and NRVM, accounting for the markedly increased glycolytic activity of NRVM.
A Multilayer Method of Schema Matching Based on Semantic and Functional Dependencies

Determing matching schemas enables queries on heterogeneous data space to be formulated and facilitates data integration. Current schema matching techniques most focus on mining mappings using elements' own information. This paper proposes to introduce semantic and functional dependencies into matching process to achieve multilayer schema matching results. It calculates semantic similarity with the help of Word Net and generates candidate mapping sets. By introducing functional dependency to formulize structural information, it can get structural similarities between element pairs. A probabilistic factor is considered to select mapping pairs. Through experimental evaluation on real data, the superiority of our method is verified.
Fuzzy Tracker with Self-Tuning PID and Identifier Design Using Conditional-LMI and Improved Random Optimal Algorithm

This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.
Interest-Based Self Organization in Group-Structured P2P Networks

Peer-to-Peer (P2P) Networks are becoming very popular these days. The scattered environment in P2P networks makes it different from the traditional networks. Each member in P2P network can act as a client as well as a server, which is different from its traditional counterpart such as internet, where a central server is required to control the network. Finding resources in P2P systems is a major issue. Extensive search may be needed to resolve queries in the network. In traditional P2P search algorithms such as in Gnutella protocol V0.4 search is via query flooding with significant exploration cost. In this paper, a group-structured P2P network is proposed. The group-based search provides well-organized searching technique by targeting particular group or community. We propose a new protocol for building and repairing of overlay topologies based on the formation of interest-based superpeers. An interest-based superpeer algorithm creates groups or societies that have common interests. Simulations indicate that the proposed protocol is highly capable and powerful even in the dynamic nature of P2P networks, where nodes are continually joining and leaving the network and the protocol supports restoration of the network even after the catastrophic failure of interest-based superpeers.
Unsupervised Approach for Automatic Keyword Extraction from Arabic Documents

In this paper, we present an unsupervised two-phase approach to extract keywords from Arabic documents that combines statistical analysis and linguistic information. The first phase detects all the N-grams that may be considered keywords. In the second phase, the N-grams are analyzed using a morphological analyzer to replace the words of the N-grams with their base forms that are the roots for the derived words and the stems for the non-derivative words. The N-grams that have the same base forms are regrouped and their counts accumulated. The ones that appear more frequently are then selected as keywords. An experiment is conducted to evaluate the proposed approach by comparing the extracted keywords with those manually selected. The results show that the proposed approach achieved an average precision of 0.51.
Human-Interaction Challenges in UAV-Based Autonomous Surveillance

Abstract Autonomous UAVs provide a platform for intelligent surveillance in application domains ranging from security and military operations to scientific information gathering and land management. Surveillance tasks are often long duration, requiring that any approach be adaptive to changes in the environment or user needs. We descriie a decision- theoretic model of surveillance, appropriate for use on our autonomous helicopter, that provides a basis for optimizing the value of information returned by the UAV. From this approach arise a range of challenges in making this iiamework practical for use by human operators lacking specialized knowledge of autonomy and mathematics. This paper describes our platform and approach, then descriies human-interaction khallenges arising hn this approach that we have . I identified and begun to address. UAV-based Surveillance One of the earliest applications of powered air vehicles was to gather information about conditions on the ground, exploiting the relatively high speed and broad view offered by these machines to, e.g., provide guidance to World War I artillery units and track enemy movements. Similar applications quickly emerged in other areas such as security, land management and scientific research. Unmanned aerial vehicles (UAVs) have the potential to dramatically increase the availability and usefulness of aircraft
Mechanisms of Cannabinoid Inhibition of GABAASynaptic Transmission in the Hippocampus

The localization of cannabinoid (CB) receptors to GABAergic interneurons in the hippocampus indicates that CBs may modulate GABAergic function and thereby mediate some of the disruptive effects of marijuana on spatial memory and sensory processing. To investigate the possible mechanisms through which CB receptors may modulate GABAergic neurotransmission in the hippocampus, whole-cell voltage-clamp recordings were performed on CA1 pyramidal neurons in rat brain slices. Stimulus-evoked GABAA receptor-mediated IPSCs were reduced in a concentration-dependent manner by the CB receptor agonist WIN 55,212–2 (EC50 of 138 nm). This effect was blocked by the CB1 receptor antagonist SR141716A (1 μm) but not by the opioid antagonist naloxone. In contrast, evoked GABAB-mediated IPSCs were insensitive to the CB agonist. WIN 55,212–2 also reduced the frequency of spontaneous, action potential-dependent IPSCs (sIPSCs), without altering action potential-independent miniature IPSCs (mIPSCs), measured while sodium channels were blocked by tetrodotoxin (TTX). Blockade of voltage-dependent calcium channels (VDCCs) by cadmium also eliminated the effect of WIN 55,212–2 on sIPSCs. Depolarization of inhibitory terminals with elevated extracellular potassium caused a large increase in the frequency of mIPSCs that was inhibited by both cadmium and WIN 55,212–2. The presynaptic effect of WIN 55,212–2 was also investigated using the potassium channel blockers barium and 4-aminopyridine. Neither of these agents significantly altered the effect of WIN 55,212–2 on evoked IPSCs. Together, these data suggest that presynaptic CB1 receptors reduce GABAA- but not GABAB-mediated synaptic inhibition of CA1 pyramidal neurons by inhibiting VDCCs located on inhibitory nerve terminals.