Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Cross-National Transferability of Policy Measures for Tackling Undeclared Work

This working paper is part of a series of deliverables within the project entitled GREY – Out of the shadows: developing capacities and capabilities for tackling undeclared work in Bulgaria, Croatia and FYR Macedonia’ (‘GREY’), funded by the European Commission’s Framework 7 Industry-Academia Partnerships Programme (IAPP). The objective of this project is to provide concrete policy recommendations about what policies may work better in tackling the undeclared economy in two new EU Member States (Bulgaria and Croatia) and a candidate country (FYR Macedonia). In particular, the objectives of our project are to: Conduct a comprehensive review of the policy approaches and measures being used to tackle undeclared work. Empirically evaluate the measures for facilitating the shift of undeclared work into the declared economy in the selected target region. Based on the results of the first two objectives, to recommend possible new policy approaches and measures (or endorse old ones) that will facilitate the shift of undeclared work into the declared economy.The aim of this Working Paper No. 5 is to provide a preliminary assessment of the appropriateness of possible policy approaches for tackling undeclared work as well as their transferability to three target countries: Bulgaria (BG), Croatia (HR) and FYR Macedonia (FYROM). This assessment results in the provision of a set of promising policy practices for tackling undeclared work in these three countries. Grounded in an institutional theory perspective, these seek to create symmetry between the codified laws and regulations of formal institutions in these countries and the codes, norms and values of the informal institutions, in order to reduce participation in undeclared work. This is argued to require changes in not only the informal but also formal institutions in each of these countries. How this can be achieved is then considered for each country.
The Changing Cyclical Variability of Economic Activity in the United States

This paper examines the changing cyclical variability of economic activity in the United States. It first shows that the decline in variability since World War II cannot be explained by changes in the composition of economic activity or by the avoidance of financial panics. We then show that increased automatic stabilization by the government, and the increased availability of private credit after World War II combined to stabilize consumption and reduce the variability of aggregate demand. The main argument of the paper holds that greater price rigidity in recent times may have contributed to economic stability by preventing destabilizing deflations and inflations. Empirical evidence is presented to support this proposition.
Bayesian, Geometric Subspace Tracking

We address the problem of tracking the time-varying linear subspaces (of a larger system) under a Bayesian framework. Variations in subspaces are treated as a piecewise-geodesic process on a complex Grassmann manifold and a Markov prior is imposed on it. This prior model, together with an observation model, gives rise to a hidden Markov model on a Grassmann manifold, and admits Bayesian inferences. A sequential Monte Carlo method is used for sampling from the time-varying posterior and the samples are utilized to estimate the underlying process. Simulation results are presented for principal subspace tracking in array signal processing.
Visual Object Tracking via Joint Learning Method

A novel visual object tracking algorithm Using Spatio-Temporal Contextual reasoning via joint learning method is proposed. The schema extracts the rectangle and high-dimensional features at different scales of samples, then constructs a measurement matrix to map high-dimensional features to lower-dimensional image space using a prior knowledge of sparse video frame, and formulates the spatio-temporal relationships between the object of interest and its local context based on a joint method combining feature and deformation handling with classification model. Experimental results on some publicly available benchmark video sequences show that the proposed algorithm can handle occlusion efficiently, and be robust to pose and illumination variations over other approaches.
A Framework for the Design Configuration of Accountable Selfish-Resilient Peer-to-Peer Systems

A challenge in designing a peer-to-peer (P2P) system is to ensure that the system is able to tolerate selfish nodes that strategically deviate from their specification whenever doing so is convenient. In this paper, we propose RACOON, a framework for the design of P2P systems that are resilient to selfish behaviours. While most existing solutions target specific systems or types of selfishness, RACOON proposes a generic and semi-automatic approach that achieves robust and reusable results. Also, RACOON supports the system designer in the performance-oriented tuning of the system, by proposing a novel approach that combines Game Theory and simulations. We illustrate the benefits of using RACOON by designing two P2P systems: a live streaming and an anonymous communication system. In simulations and a real deployment of the two applications on a testbed comprising 100 nodes, the systems designed using RACOON achieve both resilience to selfish nodes and high performance.
Managing Presence Information for Online 2D Games

Children can play computer games to learn languages or numbers. There are many educational social games on the Internet. Most of these games are online 2 Dimensional games based on the Web 2.0 and Flash technology to make the game simple and easily understandable. On this game, presence plays on important role that players sense they are being in the virtual world. Therefore, the sense of presence is very important to give entertainment to the players. This paper presents a game platform for the presence information which provides emotional 2D images of the players to the gamming server. Game developers can have benefit from the platform since it provides diverse 2D emotional images of the players automatically. Also, players do not have to set up their presence information on all gamming servers. The paper describes the architecture of the platform and the call flows to use the platform.
DNCA: An efficient channel assignment for multi-interface multi-channel Ad Hoc wireless networks

The capacity of an IEEE 802.11-based multi-hop wireless network is limited. By effectively utilizing multiple non-overlapping channels and multiple interfaces, collision and co-channel interference can be reduced. This allows more concurrent transmissions and thus enhances the network throughput. In this paper, we introduce an efficient distributed negotiated channel assignment protocol, called DNCA. At each node, DNCA conducts a local optimization by greedy balancing the number of neighbors on each interface. By using DNCA, it does not require changes to higher-level protocols. We describe the design and implementation of DNCA, and analyze its performance using ns-3 network simulator. Our results show that DNCA provides much higher system capacity and lower end-to-end packet delay.
In-Line Service Measurements: Exploiting IPv6 Extension Headers

The ability to measure, monitor and control the service quality experienced by network traffic is becoming increasingly important as multiple traffic types are aggregated onto IP networks. This paper introduces a novel measurement technique for assessing performance metrics (e.g. one-way packet loss, delay, delay variation, and ‘goodput’) of IPv6 network flows. By exploiting native IPv6 extension headers, measurement triggers and measurement data are carried in the same packets as the payload data itself, providing a high level of probability that the behaviour of the real user traffic flows is being observed. A prototype implementation of this technique has been constructed and used to measure numerous properties of different application flows, over both wireline and wireless IPv6 environments. End-to-end, oneway delay and delay variation of real-time video streams have been measured, as well as the goodput of services operating on top of reliable transport. This measurement technique can be the basis for low-overhead, scalable, transparent and reliable measurement of individual and aggregate network flows that can be dynamically deployed where and when required in a multi-service IP environment.
Effects of acetaminophen on morphine side-effects and consumption after major surgery: meta-analysis of randomized controlled trials.

BACKGROUND Acetaminophen is commonly used for the management of perioperative pain. However, there is a marked discrepancy between the extent to which acetaminophen is used and the available evidence for an analgesic effect after major surgery. The aim of this systematic review is to determine the morphine-sparing effect of acetaminophen combined with patient-controlled analgesia (PCA) with morphine and to evaluate its effects on opioid-related adverse effects. METHODS MEDLINE and the Cochrane Library were searched to select randomized controlled trials which compared PCA morphine alone with PCA morphine plus acetaminophen administered orally or intravenously. Studies were evaluated for their quality based on the Oxford Quality Scale. Outcome measures were morphine consumption over the first 24 h after surgery, patient satisfaction and the incidence of morphine side-effects, including nausea and vomiting, sedation, urinary retention, pruritus and/or respiratory depression. RESULTS Seven prospective randomized controlled trials, including 265 patients in the group with PCA morphine plus acetaminophen and 226 patients in the group with PCA morphine alone, were selected. Acetaminophen administration was not associated with a decrease in the incidence of morphine-related adverse effects or an increase in patient satisfaction. Adding acetaminophen to PCA was associated with a morphine-sparing effect of 20% (mean, -9 mg; CI -15 to -3 mg; P=0.003) over the first postoperative 24 h. CONCLUSION Acetaminophen combined with PCA morphine induced a significant morphine-sparing effect but did not change the incidence of morphine-related adverse effects in the postoperative period.
New Practices to Structure and Elicit Improvement Opportunities in Scientific Software Development Teams

This paper presents ongoing research on a new approach to structure and elicit improvement opportunities in the software development process followed by technical-scientific teams. The bottom-up approach has been proved as more effective in process improvement applied to technical and scientific environments, in opposition to standard improvement models such as ISO or CMMI. However, when bottom-up is applied to elicit improvement areas, the method is usually limited to the use of surveys that miss many of the root causes and structural deficiencies. To complement the elicitation process, we propose the use of requirement-gathering techniques such as Card Sorting, Kelly Grid and Multi-Voting. Initial results are discussed in this paper.
Semi-supervised dimensionality reduction based on global and local scatter

Recently, semi-supervised learning, which uses unlabeled samples and supervised information together in learning process, has received much attention. Compared with class labels, pairwise constraints is a kind of supervised information which are more easily to obtain. In this paper, a new algorithm is proposed, called as SSGL, which preserves both the global (intrinsic) and local structure of the original data (both labeled and unlabeled data) and incorporates the structure of the pairwise constraints in the projected low-dimensional space. In this way, the novel algorithm intends to find a better discriminative projection. Experiment results on Yale and ORL face databases show its effectiveness.
Muscarinic Activation of a Voltage-Dependent Cation Nonselective Current in Rat Association Cortex

The ionic mechanism underlying the acetylcholine-induced depolarization of layer V pyramidal neurons of rat prefrontal cortex was examined using whole-cell recording in in vitro rat brain slices. Consistent with previous results, pressure application of acetylcholine to layer V pyramidal neurons elicited a strong depolarization. Pharmacological analysis of this response indicated that it was mediated by the stimulation of muscarinic receptors as it was mimicked by muscarinic agonists, but not by nicotine, and was blocked by atropine. The inward current responsible for the depolarization resulted from the activation of a voltage-dependent, cation nonselective current. Thus, the amplitude of the current was critically dependent on extracellular sodium concentration but not on extracellular potassium or chloride concentration. Examination of the I–Vrelationship for the muscarinic current using voltage clamp revealed that the current reversed near −15 mV and exhibited a strong voltage dependence, turning off rapidly in the subthreshold range. The voltage dependence of the current led to the appearance of a current associated with a conductance decrease when examined using steady-state voltage- or current-clamp measurements. This might have led to earlier misidentification of this response as mediated by a decrease in potassium conductance. These results question the traditional interpretation that muscarinic depolarization in cortex is mediated by a decrease in potassium conductance. They indicate that the fundamental mechanism responsible for muscarinic depolarization in prefrontal cortex involves the activation of a voltage-dependent, cation nonselective current. This current might represent a previously unsuspected mechanism capable of mediating slow depolarization in the central nervous system.
A Note on (Spin-) Coherent-State Path Integral

It is pointed out that there are some fundamental difficulties with the frequently used continuous-time formalism of the spin-coherent-state path integral. They arise already in a single-spin system and at the level of the "classical action" not to speak of fluctuations around the "classical path". Similar difficulties turn out to be present in the case of the (boson-)coherent-state path integral as well; although partially circumventable by an ingenious trick (Klauder's $\epsilon$-prescription) at the "classical level", they manifest themselves at the level of fluctuations. Detailed analysis of the origin of these difficulties makes it clear that the only way of avoiding them is to work with the proper discrete-time formalism. The thesis is explicitly illustrated with a harmonic oscillator and a spin under a constant magnetic field.
Disentangling invasion processes in a dynamic shipping–boating network

The relative importance of multiple vectors to the initial establishment, spread and population dynamics of invasive species remains poorly understood. This study used molecular methods to clarify the roles of commercial shipping and recreational boating in the invasion by the cosmopolitan tunicate, Botryllus schlosseri. We evaluated (i) single vs. multiple introduction scenarios, (ii) the relative importance of shipping and boating to primary introductions, (iii) the interaction between these vectors for spread (i.e. the presence of a shipping‐boating network) and (iv) the role of boating in determining population similarity. Tunicates were sampled from 26 populations along the Nova Scotia, Canada, coast that were exposed to either shipping (i.e. ports) or boating (i.e. marinas) activities. A total of 874 individuals (c. 30 per population) from five ports and 21 marinas was collected and analysed using both mitochondrial cytochrome c oxidase subunit I gene (COI) and 10 nuclear microsatellite markers. The geographical location of multiple hotspot populations indicates that multiple invasions have occurred in Nova Scotia. A loss of genetic diversity from port to marina populations suggests a stronger influence of ships than recreational boats on primary coastal introductions. Population genetic similarity analysis reveals a dependence of marina populations on those that had been previously established in ports. Empirical data on marina connectivity because of boating better explains patterns in population similarities than does natural spread. We conclude that frequent primary introductions arise by ships and that secondary spread occurs gradually thereafter around individual ports, facilitated by recreational boating.
A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature

Summary: Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. Availability and implementation: The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). Contact: reecehart@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
The Role of Gut Microbiota on Insulin Resistance

The development of obesity and insulin resistance has been extensively studied in the last decades, but the mechanisms underlying these alterations are still not completely understood. The gut microbiota has been identified as a potential contributor to metabolic diseases. It has been shown that obese individuals present different proportions of bacterial phyla compared with lean individuals, with an increase in Firmicutes and Actinobacteria and a decrease in Bacteroidetes. This alteration seems to interfere with intestinal permeability, increasing the absorption of lipopolysaccharide (LPS), which reaches circulation and initiates activation of Toll-like receptor (TLR) 4 and 2 and LPS receptor CD14, leading to increased activation of inflammatory pathways. With these activations, an impairment of the insulin signaling is observed, with decreased phosphorylation of the insulin receptor, insulin receptor substrate (IRS) and Akt, as well as increased inhibitory serine phosphorylation of IRS-1. Altered proportions of bacterial phyla have also been demonstrated to interfere with host’s biochemical pathways, increasing energy extraction and depot in adipose tissue. Therefore, understanding the mechanisms by which the alteration in the gut microbiota produces different signaling activations and phenotype changes may offer an interesting opportunity for the treatment of obesity and type 2 diabetes.
Is the Franc Zone an Optimal Currency Area

In this paper we modify the method of Blanchard and Quah (1989) in order to estimate a structural VAR model appropriate for a small open economy. In this way we identify shocks to output and prices in the members of the two monetary unions that make up the African CFA Franc Zone. The costs of monetary union membership will depend on the extent to which price and output shocks are correlated across countries, and the degree of similarity in the long run effects of the shocks on the macro-economy. The policy conclusions depend on the relative importance of different macroeconomic variables to policymakers, and the speed with which a policymaker is able to respond to a shock.
Analysis of Various Evaluation Measures for Diversity

Evaluation measures play a vital role in analyzing the performance of a system, comparing two or more systems, and optimizing systems to perform some task. In this paper, we analyze and highlight the strengths and weaknesses of commonly used measures for evaluating the diversity in search results. We compare MAP-IA, α-nDCG, and ERR-IA using data from TREC’09 web track diversity runs and simulated data. We describe a class of test sets that could be used to compare evaluation measure and systems used for diversifying search results.
Ontologies on demand? : A description of the state-of-the-art, applications, challenges and trends for ontology learning from text

Ontologies are nowadays used for many applications requiring data, services and resources in general to be interoperable and machine understandable. Such applications are for example web service discovery and composition, information integration across databases, intelligent search, etc. The general idea is that data and services are semantically described with respect to ontologies, which are formal specifications of a domain of interest, and can thus be shared and reused in a way such that the shared meaning specified by the ontology remains formally the same across different parties and applications. As the cost of creating ontologies is relatively high, different proposals have emerged for learning ontologies from structured and unstructured resources. In this article we examine the maturity of techniques for ontology learning from textual resources, addressing the question whether the state-of-the-art is mature enough to produce ontologies'on demand'.
Detecting Anomalies by Benford's Law

Benford's law gives expected patterns of the digits in numerical data. It can be used as a tool to detect outliers for example in as a test for the authenticity and reliability of transaction level accounting data. Based on Benford's law tests for first two digits, first three digits, last digits, last digit, last two digits have been derived as an additional analytical tool. Benford's law is known as a 'first digit law', 'digit analysis' or 'Benford-Newcomb phenomenon'. The second order test is an analysis of the digit frequencies of the differences between the ordered (ranked) values in a data set. The digit frequencies of these differences approximates the frequencies of Benford's law for most distributions of the original data. From some auditor's point of view it is very important if it is possible to use Benford's law to trace siginificant changes in data in some period of time or detect some trends within them.
Learning Stochastic Logic Programs

Stochastic Logic Programs (SLPs) have been shown be a generalisation of Hidden Markov Models (HMMs), stochastic context-free grammars, and directed Bayes’ nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first-order range-restricted definite clause. This paper summarises the syntax, distributional semantics and proof techniques for SLPs and then discusses how a standard Inductive Logic Programming (ILP) system, Progol, has been modified to support learning of SLPs. The resulting system 1) finds an SLP with uniform probability labels on each definition and near-maximal Bayes posterior probability and then 2) alters the probability labels to further increase the posterior probability. Stage 1) is implemented within CProgol4.5, which differs from previous versions of Progol by allowing user-defined evaluation functions written in Prolog. It is shown that maximising the Bayesian posterior function involves finding SLPs with short derivations of the examples. Search pruning with the Bayesian evaluation function is carried out in the same way as in previous versions of CProgol. The system is demonstrated with worked examples involving the learning of probability distributions over sequences as well as the learning of simple forms of uncertain knowledge.