Miracle-dz/UniFAR-FTUs huggingface dataset:
Explaining Variations in the Fight against Unemployment in Times of the Global Financial Crisis: A Mixed-Methods Approach

The global economic and financial crisis that commenced in 2008 has triggered massive increases in unemployed in almost all Western industrialized nations. Among the OECD nations, about half have reacted - inter alia - by introducing or expanding temporary, public sector jobs in the so-called "second labour market". This had also been a preferred option in the 1980s, following the oil shocks. Since then, however, these programs have increasingly been seen as ineffective and their use remains highly controversial. What then explains that numerous OECD countries have opted for this type of intervention, while others have not? By applying a mixed-methods approach, we first identify through the application of a discriminant analysis that the financial room for manoeuvre coupled with a rapid rise in youth unemployment are the best predictors for the introduction of direct job-creation measures. Subsequently we carefully trace the political events in three most different systems, including Germany, Sweden and the UK, thus elaborating on the how and why these two factors are crucial explanatory variables.
Tractable algorithms for chance-constrained combinatorial problems

This paper aims at proposing tractable algorithms to find effectively good solutions to large size chance-constrained combinatorial problems. A new robust model is introduced to deal with uncertainty in mixed-integer linear problems. It is shown to be strongly related to chance-constrained programming when considering pure 0-1 problems. Furthermore, its tractability is highlighted. Then, an optimization algorithm is designed to provide possibly good solutions to chance-constrained combinatorial problems. This approach is numerically tested on knapsack and multi-dimensional knapsack problems. The results obtained outperform many methods based on earlier literature.
Vent discrimination at Stromboli Volcano , Italy April

Eruptive activity at Stromboli Volcano was significantly elevated over background levels in May 2001. During 63 h of observation, eight vents produced, on average, 17 explosions/h with an average repose interval of 3 min. During this period, the Stromboli vents exhibited consistent seismic and acoustic signatures, based on cross-correlation cluster analysis. Dendrogram clustering, based on waveform cross-correlation, was used to illustrate the complexity of the near surface plumbing system of Stromboli’s multi-vent edifice. Cross-correlations of displacement seismograms produced by explosions at specific craters, such as the Northeast crater (NEC), form dense waveform clusters with correlation coefficients between 0.96 and 0.99, while displacement waveforms from other craters, such as the Southwest crater (SWC), exhibit loose clusters with correlations between 0.88 and 0.96. The inconsistency of SWC events, as compared to the NEC, suggests that the vent system there is more heterogeneous. Cluster linkage distance between the NEC cluster and the Central crater (CC) cluster is shorter than the linkage distance between the NEC and SWC clusters, indicating that NEC and CC are more closely related. Infrasonic observations were used to locate vent explosions confirming that the clusters of events are associated with specific vents or craters. Qualitative analyses of acoustic waveforms from approximately 500 explosions reveal that impulsive acoustic signals were associated with short, mechanically simple ground displacement responses. These events may correspond to the bursting of an individual gas slug. Similar degassing mechanisms from vents in the NEC and the CC show common characteristics in their displacement waveforms. D 2004 Published by Elsevier B.V.
Facial expression recognition for speaker using thermal image processing and speech recognition system

I investigated a method for facial expression recognition for a human speaker by using thermal image processing and a speech recognition system. In this study, we improved our speech recognition system to save thermal images at the three timing positions of just before speaking, and just when speaking the phonemes of the first and last vowels. With this method, intentional facial expressions of "angry", "happy", "neutral", "sad", and "surprised" were discriminable with good recognition accuracy.
Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi

Introduction In the context of malaria elimination, interventions will need to target high burden areas to further reduce transmission. Current tools to monitor and report disease burden lack the capacity to continuously detect fine-scale spatial and temporal variations of disease distribution exhibited by malaria. These tools use random sampling techniques that are inefficient for capturing underlying heterogeneity while health facility data in resource-limited settings are inaccurate. Continuous community surveys of malaria burden provide real-time results of local spatio-temporal variation. Adaptive geostatistical design (AGD) improves prediction of outcome of interest compared to current random sampling techniques. We present findings of continuous malaria prevalence surveys using an adaptive sampling design. Methods We conducted repeated cross sectional surveys guided by an adaptive sampling design to monitor the prevalence of malaria parasitaemia and anaemia in children below five years old in the communities living around Majete Wildlife Reserve in Chikwawa district, Southern Malawi. AGD sampling uses previously collected data to sample new locations of high prediction variance or, where prediction exceeds a set threshold. We fitted a geostatistical model to predict malaria prevalence in the area. Findings We conducted five rounds of sampling, and tested 876 children aged 6–59 months from 1377 households over a 12-month period. Malaria prevalence prediction maps showed spatial heterogeneity and presence of hotspots—where predicted malaria prevalence was above 30%; predictors of malaria included age, socio-economic status and ownership of insecticide-treated mosquito nets. Conclusions Continuous malaria prevalence surveys using adaptive sampling increased malaria prevalence prediction accuracy. Results from the surveys were readily available after data collection. The tool can assist local managers to target malaria control interventions in areas with the greatest health impact and is ready for assessment in other diseases.
AMES: Towards an Agile Method for ERP Selection

Conventional on-premise installations of ERP are now rapidly being replaced by ERP as service. Although ERP becomes more accessible and no longer requires local infrastructure, current selection methods do not take full advantage of the provided agility. In this paper we present AMES (Agile Method for ERP Selection), a novel method for ERP selection which better utilizes the strengths of service oriented ERP. AMES is designed to shorten lead time for selection, support identification of essential system requirements, increase learning during the selection process and increase control over the subsequent ERP implementation. These properties of the method will help user organizations to make better and faster decisions when selecting ERP.
Capturing technical terms in spoken CLIL

Content and language integrated learning (CLIL), an educational approach using a foreign language to teach non-language subjects, has been consistently gaining in popularity. Despite an increasing research base suggesting its benefits for general language proficiency, the contribution made to learning and using subject-specific target language elements is largely under-researched. This paper addresses one aspect of this, i.e. students’ use of subject-specific vocabulary in CLIL classroom communication. We propose a holistic model for identifying both single and multi-word lexical units specific to the school subject in oral classroom data, integrating corpus-linguistic and qualitative data analysis. The method is trialled using a data set of 16 hours of secondary-school CLIL classroom data within the subject of European economics and politics in Year 12. Findings show that a holistic definition of subject-specific vocabulary is vital, and that the model constitutes an adequate and flexible tool for specifying CLIL terminology in oral classroom discourse.
HPA AXIS RELATED GENES AND RESPONSE TO PSYCHOLOGICAL THERAPIES: GENETICS AND EPIGENETICS

Hypothalamic–pituitary–adrenal (HPA) axis functioning has been implicated in the development of stress‐related psychiatric diagnoses and response to adverse life experiences. This study aimed to investigate the association between genetic and epigenetics in HPA axis and response to cognitive behavior therapy (CBT).
A SVM for GPCR Protein Prediction Using Pattern Discovery

Machines learning techniques have been applied in several different problems in bioinformatics. Similarly, pattern discovery algorithms have also been used to uncover hidden motifs in protein sequences, contributing greatly to the understanding of the problem of protein classification. G-protein coupled receptors (GPCRs) represent one of the largest protein families in Human Genome. Most of these receptors are major target for drug discovery and development. Therefore, they are of interest to the pharmaceutical industry. The technique used in this paper combine machine learning and pattern discovery methods to develop a protein prediction procedure in relation to its functional class, more specifically to predict GPCR protein class. Vilo[2]proposed an algorithm in order to extract pattern of regular expressions from known protein GPCR sequences and used them to predict coupling specificity of G protein coupled receptors to their G proteins. We analyze these patterns and combine them as features for feeding a SVM to predict the GPCR super class. We demonstrate the results using ROC curves, which are well-indicated to evaluate the performance of this kind of classifiers. The experiments, based on the GPCRDB database, also showed that we were able to find some novel GPCR sequences that were not described in the PROSITE database.
EXCHANGE MARKET PRESSURE AND REGIONAL PRICE SPILLOVERS IN RUSSIA, UKRAINE, AND BELARUS

The economies of Russia, Ukraine, and Belarus have long been undergoing an uneven process of regional integration, but at the same time face the lasting effects of the 2008 Global Financial Crisis. This study examines different measures of Exchange Market Pressure (EMP), which captures currency depreciations and central-bank measures to offset them, for these three countries. We then enter them into vectors that include Russian and foreign stock prices and commodity prices. Impulse response functions and variance decompositions uncover a number of spillovers, particularly when our “benchmark” EMP measure is used. We find evidence of one-way transmission from Russia to Ukraine and Belarus, and from Russian stock prices to the ruble.
COMPUTATIONAL PREDICTION OF FLOW-GENERATED SOUND

AbstractThis article provides a critical review of computational techniques for flow-noise prediction and the underlying theories. Hybrid approaches, in which the turbulent noise source field is computed and/or modeled separately from the far-field calculation, are afforded particular attention. Numerical methods and modern flow simulation techniques are discussed in terms of their suitability and accuracy for flow-noise calculations. Other topics highlighted include some important formulation and computational issues in the application of aeroacoustic theories, generalized acoustic analogies with better accounts of flow-sound interaction, and recent computational investigations of noise-control strategies. The review ends with an analysis of major challenges and key areas for improvement in order to advance the state of the art of computational aeroacoustics.
Compliant humanoid robot control by the torque transformer

This paper presents a new control architecture for compliant motion control and safe physical interaction between humanoid robot and human. One of the key technologies in this framework is the Torque Transformer, which enables the implementation of joint torque control on the traditional joint position controlled robots. In this framework, the torque control is accomplished by converting desired joint torque command into instantaneous increments of joint velocity command. Through the transformer, the Operational Space Formulation was applied to account for the dynamics of the system on the current joint position controlled robots. This approach was experimentally implemented on the physical humanoid robot, HONDA ASIMO's upper body control. The ZMP based stable balance controller of ASIMO was integrated to control the lower body of the robot. In this framework, dynamics control by the torque transformer and stable position based balance controller were connected and coordinated together on the current position controlled humanoid robot. The paper presents modeling process of the torque transformer, whole body controller and the results of the implementation which demonstrate the effectiveness of this approach.
Implementation of multilisp: Lisp on a multiprocessor

Multilisp is an extension of Lisp (more specifically, of the Lisp dialect Scheme [15]) with additional operators and additional semantics to deal with parallel execution. It is being implemented on the 32-processor Concert multiprocessor. The current implementation is complete enough to run the Multilisp compiler itself, and has been run on Concert prototypes including up to four processors. Novel techniques are used for task scheduling and garbage collection. The task scheduler helps control excessive resource utilization by means of an unfair scheduling policy: the garbage collector uses a multiprocessor algorithm modeled after the incremental garbage collector of Baker [2]. A companion paper [9] discusses language design issues relating to Multilisp.
The internal logic of Bell's states

We investigate the internal logic of a quantum computer with two qubits, in the two particular cases of non-entanglement (separable states) and maximal entanglement (Bell's states). To this aim, we consider an internal (reversible) measurement which preserves the probabilities by mirroring the states. We then obtain logical judgements for both cases of separable and Bell's states.
A Study of the Performance Potential of DHT-based Overlays

We use simulation to study whether overlays based on the recent distributed hash tables (DHTs) have the potential to deliver performance comparable to that of overlays based on measurements. Our work is motivated by the use of DHTs for services such as multicast, which is already targeted by measurement-based overlays; there is currently little understanding of how the two approaches compare at scales where both are viable. We compare three DHT-based overlays (CAN, Chord and Pastry) with two measurement-based overlays (Narada and NICE), as well as power-law random graphs (PLRGs) that represent Gnutella. To enable comparisons, we configure the overlays with the same average out-degree and focus on moderate scale. To gauge potential, we look at current and idealized DHT algorithms. We find that basic versions of DHTs have a latency stretch that is at least twice that of NICE and Narada, but similar performance in terms of bandwidth hotspots. However, DHT performance can be improved considerably with routing heuristics and topology-aware overlay construction, which have the potential to bring DHT performance at par with NICE. We also report on performance of overlays with power-law structure and the impact of hierarchy on performance.
A commercial EM solver using the BI-RME method

In this paper, we present FEST3D, a powerful software tool capable of efficiently analyzing most passive components commonly used in space and ground applications. By combining different approaches of the Boundary Integral - Resonant Mode Expansion (BI-RME) method, this tool is able to perform an accurate EM modeling of components with complicated geometries in extremely short computational times (orders of magnitude less than software tools based on 3D segmentation techniques).
Lid Restraint Evokes Two Types of Motor Adaptation

Unilateral reduction in eyelid motility produced two modes of blink adaptation in humans. The first adaptive modification affected both eyelids. Stimulation of the supraorbital branch of the trigeminal nerve (SO) ipsilateral to the upper eyelid with reduced motility evoked bilateral, hyperexcitable reflex blinks, whereas contralateral SO stimulation elicited normally excitable blinks bilaterally. The probability of blink oscillations evoked by stimulation of the ipsilateral SO also increased with a reduction in lid motility. The increased probability of blink oscillations correlated with the enhanced trigeminal reflex blink excitability. Thus, the trigeminal complex ipsilateral to the restrained eyelid coordinated an increase in excitability and blink oscillations independent of the eyelid experiencing reduced motility. The second type of modification appeared only in the eyelid experiencing reduced motility. When tested immediately after removing lid restraint, blink amplitude increased in this eyelid relative to the normal eyelid regardless of the stimulated SO. A patient with seventh nerve palsy exhibited the same two patterns of blink adaptation. These results were consistent with two forms of adaptation, presumably because unilateral lid restraint produced two error signals. The corneal irritation caused by reduced blink amplitude generated abnormal corneal inputs. The difference between proprioceptive feedback from the blink and expected blink magnitude signaled an error in blink amplitude. The corneal irritation appeared to drive an adaptive process organized through the trigeminal complex, whereas the proprioceptive error signal drove an adaptive process involving just the motoneurons controlling the restrained eyelid.
Post-processing of data generated by a chaotic pipelined ADC for the robust generation of perfectly random bitstreams

We review a true random number generator which internally exploits a pipeline analog-to-digital converter modified to operate in chaotic mode. Contrarily to other true random number generators it is not based on the explicit observation of noisy physical quantities, freeing the designer from subtle technology-dependent details. In ideal conditions the model can be formally proven to deliver perfectly uncorrelated output sequences by itself. Here we thoroughly investigate the effects of implementation errors and we introduce a data-postprocessing methodology suitable for their compensation and for assuring robust behavior.
Modular mechanisms for Bayesian optimization

The design of methods for Bayesian optimization involves a great number of choices that are often implicit in the overall algorithm design. In this work we argue for a modular approach to Bayesian optimization and present a Python implementation, pybo, that allows us to easily vary these choices. In particular this includes selection of the acquisition function, kernel, and hyperpriors as well as less-discussed components such as the recommendation and initialization strategies. Ultimately this approach provides us a straightforward mechanism to examine the effect of each choice both individually and in combination.
Relay Path Selection Approaches in Peer-to-Peer VoIP Systems

Multipath overlay routing technologies are seen as alternative solutions for VoIP because they inherit path diversity from peer-to-peer overlay networks. We discuss and compare the performances of two relay path selection approaches proposed for VoIP overlay systems through extensive simulations. We propose a new method for relay path computation that takes into account both path disjointness and other network quality factors (such as packet delay or loss). We further apply our method in different overlay network scenarios by varying the supernode distribution. It is found that there is a considerable improvement of path performance when relaying traffic through highly connected ASs using the new method.
A Fine-Grained Analysis of the Performance and Power Benefits of Compiler Optimizations for Embedded Devices

In this study we examine the performance and power benefits resulting from many traditional and aggressive compiler optimizations. Examples of early and loop optimizations were translated from classic compiler textbooks into PowerPC assembly and executed in the Dynamic SuperScalar Wattch simulation environment. Each optimization was applied in an isolated manner which resulted in an overall average improvement in performance of 4.8% and a 6.2% decrease in power consumption for the early optimizations. The loop optimizations yielded greater performance and power improvements with an average speed-up of 17.0% and a 15.3% reduction in power consumption. The decrease in power consumption of the early optimizations was found to correspond closely to the execution time. In contrast, the improvements from the loop optimizations were found to correspond to the number of instructions committed. The average decrease in the number of instructions committed was found to be 6.2% and 14.1% for the early and loop optimizations, respectively. The results of this study should aid a compiler writer in selecting which optimizations should be applied at an early optimization phase inside of an adaptive dynamic optimizer if power consumption is of importance.
S-Petasin, the Main Sesquiterpene of Petasites formosanus, Inhibits Phosphodiesterase Activity and Suppresses Ovalbumin-Induced Airway Hyperresponsiveness

S-Petasin is the main sesquiterpene of Petasites formosanus, a traditional folk medicine used to treat hypertension, tumors and asthma in Taiwan. The aim of the present study was to investigate its inhibitory effects on phosphodiesterase (PDE) 1–5, and on ovalbumin (OVA)-induced airway hyperresponsiveness (AHR) in a murine model of allergic asthma. S-Petasin concentration-dependently inhibited PDE3 and PDE4 activities with 50% inhibitory concentrations (IC50) of 25.5, and 17.5 μM, respectively. According to the Lineweaver-Burk analysis, S-petasin competitively inhibited PDE3 and PDE4 activities with respective dissociation constants for inhibitor binding (K i) of 25.3 and 18.1 μM, respectively. Both IC50 and K i values for PDE3 were significantly greater than those for PDE4. S-Petasin (10–30 μmol/kg, administered subcutaneously (s.c.)) dose-dependently and significantly attenuated the enhanced pause (P enh) value induced by methacholine (MCh) in sensitized and challenged mice. It also significantly suppressed the increases in total inflammatory cells, lymphocytes, neutrophils, eosinophils and levels of cytokines, including interleukin (IL)-2, IL-4 and IL-5, tumor necrosis factor (TNF)-α and interferon (IFN)-γ in bronchoalveolar lavage fluid (BALF) of these mice. In addition, S-petasin (10–30 μmol/kg, s.c.) dose-dependently and significantly attenuated total and OVA-specific immunoglobulin E (IgE) levels in the serum and BALF, and enhanced the IgG2a level in serum of these mice. The PDE4H value of S-petasin was >300 μM; therefore, its PDE4H/PDE4L value was calculated to be >17. In conclusion, the present results for S-petasin at least partially explain why Petasites formosanus is used as a folk medicine to treat asthma in Taiwan.