Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the Benefits of Traffic Calming on Through Routes: A Choice Experiment Approach

Excessive speed is a major contributory factor in a large proportion of deaths and serious injuries on British roads. One approach to tackling the speeding problem is the use of traffic calming measures as a means of enforcing speed restrictions along roads running through populated areas. But speed reduction is only one of the benefits of traffic calming. This paper reports the results from a choice experiment used to investigate the willingness to pay (WTP) of a sample of local residents in three English towns for traffic calming measures that would achieve a range of reductions in speed, noise and community severance. Estimations from the responses revealed that local people had a positive willingness to pay for a reduction in the negative impacts of road traffic and for more attractive, rather than basic, designs of the traffic calming measures. © The London School of Economics and the University of Bath 2002
Invariant bundles on B-fibered Calabi-Yau spaces and the Standard Model

We derive the Standard model gauge group together with chiral fermion generations from the heterotic string by turning on a Wilson line on a non-simply connected Calabi-Yau threefold with an SU(5) gauge group. For this we construct stable ${\bf Z_2}$-invariant $SU(4)\times U(1)$ bundles on an elliptically fibered cover Calabi-Yau threefold of special fibration type (the $B$-fibration). The construction makes use of a modified spectral cover approach giving just invariant bundles.
Rebuilding Phrase Table Scores from Monolingual Resources Using Neural Networks Vector Representations

In this paper, we propose two new features for estimating phrase based machine translation parameters. We only use monolingual data with the assumption that the phrase table is given to us, but all of its scores have been removed. Our method is based on two recently introduced neural network vector representation models for words and sentences. It is the first use of these models in an end to end phrase based machine translation system. Scores obtained from our method can recover more than 80% of BLEU loss caused by removing phrase table probabilities. We also show that our features combined with the phrase table probabilities improve the BLEU score by 0.74 points.
Linkages between Stock Prices and Exchange Rates in the EU and the United States

This paper investigates the nature of the causal relationship between stock prices and effective exchange rates in four old EU-member countries (Austria, France, Germany, and the UK), four new EU-member countries (Czech Republic, Hungary, Poland, and Slovakia) and in the USA. Both the long-run and short run causalities between these variables are explored using monthly data. The paper also tries to answer the question whether the linkages between analyzed economic variables are of the similar intensity and direction in the old and new part of the EU and how has been the relationship changing over the analyzed period. The results show much stronger causality in countries with developed capital and foreign exchange markets (old EU-member countries and the USA) than in the new-comes. Evidence also suggests more powerful long-run as well as short-run causal relations in the period 1993-2003 than during 1970- 1992. Causalities seem to be predominantly unidirectional with a direction running from stock prices to exchange rates. Finally, we also detected the real effective exchange rate as a more suitable variable than nominal effective exchange rate for such kind of analysis.
Assessing the Evolution of Gene Expression Using Microarray Data

Classical studies of the evolution of gene function have predominantly focused on mutations within protein coding regions. With the advent of microarrays, however, it has become possible to evaluate the transcriptional activity of a gene as an additional characteristic of function. Recent studies have revealed an equally important role for gene regulation in the retention and evolution of duplicate genes. Here we review approaches to assessing the evolution of gene expression using microarray data, and discuss potential influences on expression divergence. Currently, there are no established standards on how best to identify and quantify instances of expression divergence. There have also been few efforts to date that incorporate suspected influences into mathematical models of expression divergence. Such developments will be crucial to a comprehensive understanding of the role gene duplications and expression evolution play in the emergence of complex traits and functional diversity. An integrative approach to gene family evolution, including both orthologous and paralogous genes, has the potential to bring strong predictive power both to the functional annotation of extant proteins and to the inference of functional characteristics of ancestral gene family members.
Generalization Error of Invariant Classifiers

This paper studies the generalization error of invariant classifiers. In particular, we consider the common scenario where the classification task is invariant to certain transformations of the input, and that the classifier is constructed (or learned) to be invariant to these transformations. Our approach relies on factoring the input space into a product of a base space and a set of transformations. We show that whereas the generalization error of a non-invariant classifier is proportional to the complexity of the input space, the generalization error of an invariant classifier is proportional to the complexity of the base space. We also derive a set of sufficient conditions on the geometry of the base space and the set of transformations that ensure that the complexity of the base space is much smaller than the complexity of the input space. Our analysis applies to general classifiers such as convolutional neural networks. We demonstrate the implications of the developed theory for such classifiers with experiments on the MNIST and CIFAR-10 datasets.
High-performance error amplifier for fast transient DC-DC converters

A new error amplifier is presented for fast transient response of dc-dc converters. The amplifier has low quiescent current to achieve high power conversion efficiency, but it can supply sufficient current during large-signal operation. Two comparators detect large-signal variations, and turn on extra current supplier if necessary. The amount of extra current is well controlled, so that the system stability can be guaranteed in various operating conditions. The simulation results show that the new error amplifier achieves significant improvement in transient response than the conventional one.
Agricultural Productivity in the United States

Increased productivity is a key to a healthy and thriving economy. Consequently, the trend in productivity, economywide, is one of the most closely watched of our common economic performance indicators. Agriculture, in particular, has been a very successful sector of the U.S. economy in terms of productivity growth. The U.S. farm sector has provided an abundance of output while using inputs efficiently. Agricultural productivity growth has been an important source of U.S. economic growth throughout the century, but the years since 1940 have seen an even faster growth in agricultural productivity. The annual average increase in productivity from 1948 to 1994 was 1.94 percent. This reflects an annual growth in output of 1.88 percent per year and an actual decline in agricultural inputs of 0.06 percent per year. This report describes changes in U.S. agricultural productivity, and its output and input components, for 1948-94. The report also discusses factors that have affected productivity trends and provides detailed, technical information about the USDA system for calculating productivity.
Real-time self-calibrating stereo person tracking using 3-D shape estimation from blob features

We describe a method for estimation of 3D geometry from 2D blob features. Blob features are clusters of similar pixels in the image plane and can arise from similarity of color, texture, motion and other signal-based metrics. The motivation for considering such features comes from recent successes in real-time extraction and tracking of such blob features in complex cluttered scenes in which traditional feature finders fail, e.g. scenes containing moving people. We use nonlinear modeling and a combination of iterative and recursive estimation methods to recover 3D geometry from blob correspondences across multiple images. The 3D geometry includes the 3D shapes, translations, and orientations of blobs and the relative orientation of the cameras. Using this technique, we have developed a real-time wide-baseline stereo person tracking system which can self-calibrate itself from watching a moving person and can subsequently track people's head and hands with RIMS errors of 1-2 cm in translation and 2 degrees in rotation. The blob formulation is efficient and reliable, running at 20-30 Hz on a pair of SGI Indy R4400 workstations with no special hardware.
P-Centre Extraction from Speech: the need for a more reliable measure

P-Centres represent the perceptual moments of occurrence of acoustic signals and are an important parameter for duration modelling in speech synthesis applications. While a number of algorithms have been proposed previously to achieve P- Centre extraction it is shown in this paper that none yield reliable measures or are robust in implementation. A software only solution is presented which enables the rhythm setting experiment to be carried out in a reliable and flexible manner. Keywords - P-Centre, Speech rhythm, Psychoacoustics.
SPARQL Query Answering on a Shared-nothing Architecture

The amount of Semantic Web data is outgrowing the capacity of Semantic Web stores. Similar to traditional databases, scaling up RDF stores is faced with a design dilemma: increase the number of nodes at the cost of increased complexity or use sophisticated, and expensive, hardware that can support large amounts of memory, high disk bandwidth and low seek latency. In this paper, we propose a technique to do distributed and join-less RDF query answering based on query pattern-driven indexing. To this end, we rst propose an extension of SPARQL to specify query patterns. These patterns are used to build a query-specic indexes using MapReduce, which are later queried using a NoSQL store. We provide a preliminary evaluation of our results using Hadoop and HBase, indicating that, for a predened query pattern, our system oers very high query throughput and fast response times.
A NoC Simulation and Verification Platform Based on SystemC

This paper presents a NoC (network-on-chip) simulation and verification platform (NSVP) based on SystemC. A general NoC node structure is first realized under SystemC, and then connected to form the network. NSVP supports an arbitrary size of mesh and torus topology, and adopts two classic routing algorithms - XY and TXY as the routing algorithm. Users also can develop their own network topology and routing algorithm by modifying the corresponding modules. Then they can verify their design by loading different network traffic patterns to run the simulation. NSVP provides a fast and convenient platform for researching and verification of NoC architecture and routing algorithm.
Investigation of fast reroute mechanisms in an optical testbed environment

In this paper, we investigate and evaluate the performance of two fast reroute mechanisms in packet switched core networks. Such mechanisms enable, in the case of a network fault, the fast switchover of protected traffic onto pre-established backup paths within minimal time (typically below 50 ms) to minimize traffic loss. Our research testbed consists of both real and emulated IP/MPLS Label Switching Routers (LSRs). Using empirical tests, we compare the two fast protection mechanisms MPLS Traffic Engineering (TE) Fast Reroute (FRR), and IP FRR to protect MPLS LDP traffic. In our tests, we consider single link failures protected with pre-provisioned backup paths using TE-FRR tunnels, or IP Fast Reroute (IP-FRR) alternate paths. We compare the two techniques in terms of traffic loss and network time convergence obtained by repeating the tests multiple times.
Detecting Document-level Context Triggers to Resolve Translation Ambiguity

Most current machine translation systems translate each sentence independently, ignoring the context from previous sentences. This discourse unawareness can lead to incorrect translation of words or phrases that are ambiguous in the sentence. For example, the German term Typen in the phrase diese Typen can be translated either into English types or guys. However, knowing that it co-refers to the compound K¨ (“body types”) in the previous sentence helps to disambiguate the term and translate it into types. We propose a method of automatically detecting document-level trigger words (like K¨ orpertypen), whose presence helps to disambiguate translations of ambiguous terms. In this preliminary study we analyze the method and its limitations, and outline future work directions.
Relationship between R&D and innovation: implications for the Scottish Innovation Strategy

It is widely accepted that innovation is precursor to competitiveness and growth. It is also believed that the innovative performance of a country is linked with its investments in R&D. Driven by such thinking, the devolved government of Scotland, spends considerable resources on promoting R&D in Scotland. This paper examines wide-ranging evidence, including that published by the Scottish Government, to show that innovation performance of businesses in Scotland is independent of its R&D expenditure and that Scotland cannot hope to become a more competitive region by spending more on R&D. There is thus a need of rethinking on innovation strategy in Scotland.
Descriptive study of the implementation and impact of the directly observed treatment, short-course strategy in the São José do Rio Preto municipal tuberculosis control program (1998-2003).

OBJECTIVE To describe treatment outcomes (cure, noncompliance or death) after the implementation of the Directly Observed Treatment, Short-course (DOTS) strategy for tuberculosis control in the city of São José do Rio Preto, Brazil, between 1998 and 2003. METHODS A descriptive study, based on secondary data (National Case Registry database, Tuberculosis Epidemiology database, and the 'Black Book' Registry), was conducted using a specific instrument. The data were analyzed using descriptive statistics. RESULTS After the implementation of the DOTS strategy, there was a decrease in noncompliance and case detection rates as well as an increase in cure and death rates. The increase in the number of tuberculosis-related deaths might be attributable to three factors: the predominance of the disease in individuals over 50 years of age, tuberculosis/HIV co-infection, and the presence of accompanying diseases. CONCLUSION The implementation of the DOTS strategy strengthened the decentralization of the tuberculosis control plans as well as the integration of the Basic Health Care Clinic teams with the Tuberculosis Control Program team. Political commitment of the administrator to tuberculosis control, in conjunction with the policy of benefits and incentives, is essential for the sustainability of the DOTS strategy.
Computing with Oscillators

We study neuro-computational properties of non-linear oscillatory systems. Since we use the canonical phase models approach, our results do not depend on the physical nature of each oscillator or the detailed form of mathematical equations that describe its dynamics. In particular, we show that anything that can oscillate can also compute, the only problem is how to couple the oscillators. We apply this theory to detailed models of electrical, optical, and mechanical oscillators and we investigate the possibility to use such oscillators to build an oscillatory neurocomputer having autocorrelative associative memory. It stores and retrieves complex oscillatory patterns as synchronized states having appropriate phase relations between neurons.
Adapting MAC 802.11 Adapting MAC 802.11 for Performance Optimization of MANET using Cross Layer Interaction

In this research, we study the optimization challenges of MANET and cross-layer technique to improve its performance. We propose an adaptive retransmission limits algorithm for IEEE 802.11 MAC to reduce the false link failures and predict the node mobility. We implemented cross layer interaction between physical and MAC layers. The MAC layer utilizes the physical layer information for differentiating false link failure from true link failure. The MAC layer adaptively selects a retransmission limit (short and long) based on the neighbour signal strength and sender node speed information from the physical layer. The proposed approach tracks the signal strength of each node in network and, while transmitting to a neighbour node, if it's received signal strength is high and is received recently then Adaptive MAC persists in its retransmission attempts. As there is high probability that neighbour node is still in transmission range and may be not responding due to some problems other then mobility. In this paper, we evaluate the performance of MANET and show that how our Adaptive MAC greatly improves it. The simulation is done using Network Simulator NS-2.
Why cancer cells have a more hyperpolarised mitochondrial membrane potential and emergent prospects for therapy

Cancer cells have a more hyperpolarised mitochondrial membrane potential (ΨIM) than normal cells. ΨIM = ∼−220 mV in cancer cells as compared to ∼−140 mV in normal cells. Until now it has not been known why. This paper explains this disparity, in a mathematical framework, and identifies molecular targets and operations unique to cancer cells. These are thence prospective cancer drug targets. BMS-199264 is proposed as an anti-cancer drug. It inhibits the reverse, proton-pumping mode of ATP synthase, which this paper identifies as crucial to cancer cells but not to healthy, normal adult cells. In the cancer cell model, the adenine nucleotide exchanger (ANT) is inversely orientated in the mitochondrial inner membrane as compared to normal cells. This predicts it to have a different drug interaction profile, which can be leveraged for cancer therapy. Uncouplers, which dissipate the proton motive force, are proposed as anti-cancer medicines e.g. 2,4-dinitrophenol.
"Innere Abwertung" in Südeuropa: Erwartungen, Ergebnisse und Folgen

In dealing with the crisis in the Southern European countries Greece, Italy, Portugal and Spain, the Troika pushes for internal devaluation: Putting downward pressure on wages and prices in the South of the Eurozone is expected to cause improvements in price competitiveness and adjustments in current account balances via the export channel. As a consequence of demand-driven deflation tendencies, the Southern European countries are in danger of falling further into a vicious cycle of debt deflation. Over the last couple of years, the Troika has underestimated the negative effects of internal devaluation on economic growth and employment. Current developments in Southern Europe are broadly consistent with deflation experiences of European gold bloc countries during the 1930s. To a significant extent, drastic adjustments in current account balances between 2010 and 2013 are due to the slump in aggregate demand and the corresponding effects on imports.
Direct state-to-action mapping for high DOF robots using ELM

Methods of optimizing a single trajectory are mature enough for planning in many applications. Yet such optimization methods applied to high Degree-Of-Freedom robots either consume too much time to be real-time or approximate the dynamics such that they lack physical consistency. In this paper, we present a method of precomputing optimized trajectories and compressing the information to get a compact representation of the optimal policy function. By varying the initial configuration of a robot and optimizing multiple trajectories, the controller gains knowledge about the optimal policy function. Such computation can be performed on a powerful workstation or even supercomputers instead of an onboard computer of the robot. The precomputed optimal trajectories are stored in a Single-hidden Layer Feedforward neural Network (SLFN) using Optimally Pruned Extreme Learning Machine (OP-ELM). This ensures minimal representation of the model and fast evaluation of the SLFN. We first explain our method using a simple time-optimal control problem with an analytical solution. We then demonstrate how this method can work even for high dimensional state by optimizing a foothold strategy of a full quadruped robot in simulation.
Migration with endogenous moving costs.

The authors study a dynamic model of labor migration in which moving costs decrease with the number of migrants already settled in the destination. This assumption is supported by sociological studies of migrant networks. With endogenous moving costs, migration occurs gradually over time. Once it starts, it develops momentum and migratory flows may increase even as wage differentials narrow. In addition, migration tends to follow geographical channels and low-moving-cost individuals migrate first. These patterns are consistent with historical evidence from the Great Black Migration of 1915-60, much of which cannot be reconciled with existing migration models. Copyright 1996 by American Economic Association.
Subsidies for resident passengers in air transport markets

In this work, we analyse from a theoretical perspective the efficiency of an ad valorem and a lump sum subsidy for resident passengers. In particular, we consider passengers with high and low willingness to pay that may be residents in a given area (and therefore entitled to a subsidy). All passengers are served by a monopoly air carrier that wants to get as much of their willingness to pay as possible. We show that if the proportion of resident passengers is high enough, non-resident passengers may be expelled from the market. Taken into account this undesirable situation we compare ad valorem and lump sum subsidies. We conclude that if the proportion of passengers with high willingness to pay is low (high) enough applying a lump sum (ad valorem) subsidy for resident passengers is better in social terms. We apply these results to a specific case study in the Canary Islands where ad valorem subsidies for resident passengers have been extensively used. We conclude that in most routes the lump sum subsidy is undoubtedly better in social terms.
HMM-based Mandarin Singing Voice Synthesis Using Tailored Synthesis Units and Question Sets

Fluency and continuity properties are essential in synthesizing a high quality singing voice. In order to synthesize a smooth and continuous singing voice, the Hidden Markov Model-based synthesis approach is employed in this study to construct a Mandarin singing voice synthesis system. The system is designed to generate Mandarin songs with arbitrary lyrics and melody in a certain pitch range. In this study, a singing voice database is designed and collected, considering the phonetic converge of Mandarin singing voices. Synthesis units and a question set are defined carefully and tailored the meet the minimum requirement for Mandarin singing voice synthesis. In addition, pitch-shift pseudo data extension and vibrato creation are applied to obtain more natural synthesized singing voices.The evaluation results show that the system, based on tailored synthesis units and the question set, can improve the quality and intelligibility of the synthesized singing voice. Using pitch-shift pseudo data and vibrato creation can further improve the quality and naturalness of the synthesized singing voices.