Miracle-dz/UniFAR-FTUs huggingface dataset:
Bitexts as Semantic Mirrors

The importance of parallel corpora in machine translation research is widely recognized and undisputed. The amount of research on data-driven techniques in MT has grown tremendously since the introduction of the first automatic alignment techniques in the early 90’s that finally allowed to create large and reasonably clean bitexts from scratch without human interventions. Nowadays, it is impossible to think of an era before statistical machine translation and Google Translate is at everybody’s hands. However, there is more to it than just translation. Enthusiastic researchers in the early days came up with ever new ideas of using parallel data in problems of natural language understanding and processing. Some of these ideas almost disappear in the flood of SMT papers coming out every year. This paper tries to remind us of some other applications that illustrate the amazing utility of parallel corpora.
Mining Personal Data Collections to Discover Categories and Category Labels

This paper describes the text mining of personal document collections in order to learn the categories of the documents in the collection, and to assign a suitable text label to each category. In the first experiment we make use of a pre­ classified collection of documents from which we extract a text label for each category. In the second experiment we use the k­means clustering algorithm to automatically learn which categories are present in a collection, then generate short text labels to describe each category. The technique, which is essentially a form of automatic indexing, can be used whenever class exemplars are generated as part of the document clustering process. 1 Background Whilst much research has been undertaken in the area of mining large, public data collections organised by trained information scientists, typified by the MUC and TREC conferences, the increasing use of digital technology has led to growing personal data collections which are poorly organised and continually changing in content. Typical collections of this sort are collections of images from digital cameras, videos, voicemail and music files as well as bodies of emails. Electronic text documents, such as emails, project notes, favourite articles, are now widely used by office workers, administrators and everyone. The amount of these kinds of documents used and processed is rapidly increasing, which leads to difficulties in managing them. These personal collections of documents often have categories of various sizes, are likely to be poorly structured and individualised and will therefore need to be categorised in a unique manner for each user in order to be able to be searched meaningfully by them (Whittaker & Hirschberg 01). A number of authors have described methods of automatically labelling document clusters. Such methods are necessary for personal document collections where the clusters must be constantly updated. The LabelSOM approach (Rauber & Merkl 99) automatically labels every node of a trained Self­ Organising Map (SOM). The SOM differs from the clustering structures described in this paper in that the resulting clusters are arranged in a lattice, where neighbouring clusters are similar to each other. For each cluster, LabelSOM finds the square of the difference between the value of every feature (word) of every input document and the weight vector of the cluster. The sums of these squared differences for each word are stored in a "quantisation vector". To create a set of n labels for each cluster, LabelSOM …
An Econometric Model for Identifying Value in South African Red Wine

This article develops an econometric valuation methodology that is applied to identifying value in South African red wines. It is found that quality, as simultaneously measured by Wine magazine and Platter star ratings, is the dominant factor in explaining the cross‐section of prices. However, together with a varietal dummy these factors are only able to explain about 40% of the variation in wine prices. This implies that there is considerable value that may be gleaned through informed bargain seeking using this tool. Indeed, at certain levels of value there is more than a 50% differential in price.
Construction of a frameless camera-based stereotactic neuronavigator

We built an infrared vision system to be used as the real time 3D motion sensor in a prototype low cost, high precision, frameless neuronavigator. The objective of the prototype is to develop accessible technology for increased availability of neuronavigation systems in research labs and small clinics and hospitals. We present our choice of technology including camera and IR emitter characteristics. We describe the methodology for setting up the 3D motion sensor, from the arrangement of the cameras and the IR emitters on surgical instruments, to triangulation equations from stereo camera pairs, high bandwidth computer communication with the cameras and real time image processing algorithms. We briefly cover the issues of camera calibration and characterization. Although our performance results do not yet fully meet the high precision, real time requirements of neuronavigation systems we describe the current improvements being made to the 3D motion sensor that will make it suitable for surgical applications.
Voice activity detection from the breathing pattern of the speaker

In this paper, we propose a method to perform voice activity detection using only the breathing signal of a speaker. Human breathing and speech production go hand in hand. Normal respiration and respiration during speech have a different profile. The former is generally symmetric as compared to an asymmetric profile in the case of respiration during speech. Impedance pneumography provides a mechanism to capture chest expansions and compressions due to breathing. We have recorded the breathing signal along with the speech audio for 44 subjects while they were speaking and quiet. We have classified cycles of breathing into two classes, namely during speech and normal, using the cycle-synchronous discrete cosine transform coefficients of the breathing signal with different classifiers. The best accuracy of 96.4% is obtained using the k-nearest neighbor classifier. From the classified breathing cycles, we determine the intervals when a subject is quiet and when he is speaking. We use the corresponding timeframes on the simultaneously recorded audio and achieve a good accuracy in voice activity detection. Compared to the earlier reported time resolution of 30 sec, we obtain a decision for every breathing cycle, which works out to an average resolution of about 3 sec.
The Political Economy of Japanese Monetary and Exchange Rate Policy

This study analyzes the political economy of Japanese monetary and exchange rate policy, with particular emphasis on the Japanese position regarding East Asian monetary cooperation and integration. We try to disentangle the factors and interest structures behind the polices taken in order to infer how the Japanese position regarding regional monetary cooperation might evolve over time. The analysis shows that while the current incentive structure within the Japanese economic and political system gives little room for a far reaching commitment of the Japanese government to engage in regional monetary cooperation, a further integration of the Japanese economy into the regional economy and a growing dependency on the East Asian market are likely to shift the equilibrium in favor of regional cooperation.
Objective Estimates Improve Risk Stratification for Primary Graft Dysfunction after Lung Transplantation

Primary graft dysfunction (PGD) is a major cause of early mortality after lung transplant. We aimed to define objective estimates of PGD risk based on readily available clinical variables, using a prospective study of 11 centers in the Lung Transplant Outcomes Group (LTOG). Derivation included 1255 subjects from 2002 to 2010; with separate validation in 382 subjects accrued from 2011 to 2012. We used logistic regression to identify predictors of grade 3 PGD at 48/72 h, and decision curve methods to assess impact on clinical decisions. 211/1255 subjects in the derivation and 56/382 subjects in the validation developed PGD. We developed three prediction models, where low‐risk recipients had a normal BMI (18.5–25 kg/m2), chronic obstructive pulmonary disease/cystic fibrosis, and absent or mild pulmonary hypertension (mPAP<40 mmHg). All others were considered higher‐risk. Low‐risk recipients had a predicted PGD risk of 4–7%, and high‐risk a predicted PGD risk of 15–18%. Adding a donor‐smoking lung to a higher‐risk recipient significantly increased PGD risk, although risk did not change in low‐risk recipients. Validation demonstrated that probability estimates were generally accurate and that models worked best at baseline PGD incidences between 5% and 25%. We conclude that valid estimates of PGD risk can be produced using readily available clinical variables.
Performance comparison of visible light communication systems based on ACO-OFDM, DCO-OFDM and ADO-OFDM

We compared the performance of the asymmetric and direct current bias limiting optical orthogonal frequency division multiplexing (ADO-OFDM), asymmetric limiting optical orthogonal frequency division multiplexing (ACO-OFDM), and the direct current bias limiting optical orthogonal frequency division multiplexing (DCO-OFDM) in visible light communication (VLC) systems. We optimize the power ratio between ACO and DCO parts in ADO-OFDM. The results show that ADO-OFDM has better performance than DCO-OFDM at small bias value, which indicate higher power spectral efficiency. It is also shown that the BER of ACO-OFDM with 16-QAM format is smaller than that of ADO-OFDM with 4-QAM format.
Temperament of juvenile delinquents with history of substance abuse.

BACKGROUND The etiological factors and interrelations of juvenile delinquents, with psychiatric morbidity and substance abuse have been continuously debated. Cloninger's Tridimensional Theory of Temperament has been reported to predict patterns of substance abuse and comorbidity. In the current study, we aimed to examine the usability of the theory in predicting juvenile delinquency and substance abuse. METHODS Sixty consecutive and newly incarcerated male delinquents with history of substance abuse were recruited from a juvenile correctional facility in northwestern Taiwan from January 2002 through December 2003. All subjects were assessed of their temperament, behavioral problems, and psychiatric disorders on an individual base. RESULTS The juvenile delinquent subjects with childhood history of attention deficit and hyperactivity disorder (ADHD) were significantly younger, consumed less betel nuts, and had more siblings with history of drug abuse. CONCLUSION Consistent with the results of Cloninger's studies, novelty seeking positively correlated to the amount of substance abuse, while harm avoidance inversely correlated in juvenile delinquents. Endemic trend of choice of substance abuse needs to be taken into consideration in future research projects.
Enhancement of Cancer-Specific Protoporphyrin IX Fluorescence by Targeting Oncogenic Ras/MEK Pathway

Protoporphyrin IX (PpIX) is an endogenous fluorescent molecule that selectively accumulates in cancer cells treated with the heme precursor 5-aminolevulinic acid (5-ALA). This cancer-specific accumulation of PpIX is used to distinguish tumor from normal tissues in fluorescence-guided surgery (FGS) and to destroy cancer cells by photodynamic therapy (PDT). In this study, we demonstrate that oncogenic Ras/mitogen-activated protein kinase kinase (MEK) pathway can modulate PpIX accumulation in cancer cells. Methods: To identify Ras downstream elements involved in PpIX accumulation, chemical inhibitors were used. To demonstrate the increase of PpIX accumulation by MEK inhibition, different human normal and cancer cell lines, BALB/c mice bearing mammary 4T1 tumors and athymic nude mice bearing human tumors were used. To identify the mechanisms of PpIX regulation by MEK, biochemical and molecular biological experiments were conducted. Results: Inhibition of one of the Ras downstream elements, MEK, promoted PpIX accumulation in cancer cells treated with 5-ALA, while inhibitors against other Ras downstream elements did not. Increased PpIX accumulation with MEK inhibition was observed in different types of human cancer cell lines, but not in normal cell lines. We identified two independent cellular mechanisms that underlie this effect in cancer cells. MEK inhibition reduced PpIX efflux from cancer cells by decreasing the expression level of ATP binding cassette subfamily B member 1 (ABCB1) transporter. In addition, the activity of ferrochelatase (FECH), the enzyme responsible for converting PpIX to heme, was reduced by MEK inhibition. Finally, we found that in vivo treatment with MEK inhibitors increased PpIX accumulation (2.2- to 2.4-fold) within mammary 4T1 tumors in BALB/c mice injected with 5-ALA without any change in normal organs. Similar results were also observed in a human tumor xenograft model. Conclusion: Our study demonstrates that inhibition of oncogenic Ras/MEK significantly enhances PpIX accumulation in vitro and in vivo in a cancer-specific manner. Thus, suppressing the Ras/MEK pathway may be a viable strategy to selectively intensify PpIX fluorescence in cancer cells and improve its clinical applications in FGS.
'Delta': a Measure of Stylistic Difference and a Guide to Likely Authorship

This paper is a companion to my 'Questions of authorship: attribution and beyond', in which I sketched a new way of using the relative frequencies of the very common words for comparing written texts and testing their likely authorship. The main emphasis of that paper was not on the new procedure but on the broader consequences of our increasing sophistication in making such comparisons and the increasing (although never absolute) reliability of our inferences about authorship. My present objects, accordingly, are to give a more complete account of the procedure itself; to report the outcome of an extensive set of trials; and to consider the strengths and limitations of the new procedure. The procedure offers a simple but comparatively accurate addition to our current methods of distinguishing the most likely author of texts exceeding about 1,500 words in length. It is of even greater value as a method of reducing the field of likely candidates for texts of as little as 100 words in length. Not unexpectedly, it works least well with texts of a genre uncharacteristic of their author and, in one case, with texts far separated in time across a long literary career. Its possible use for other classificatory tasks has not yet been investigated.
Consensus, Dispersion and Security Prices

This study establishes and tests, within the framework of a noisy rational expectations equilibrium model, a formal linear relationship between the price of a risky asset and the average (consensus) and the dispersion of agents' expectations. Difficulties raised by the estimation of this relationship, as well as institutional aspects of the financial analysis industry are examined. The main results are the following: 1) the most important changes in consensus (in absolute value) coincide with the most important changes in dispersion of analysts' forecasts; 2) changes in the consensus and the dispersion of forecasts are respectively positively and negatively related to Canadian security returns; and 3) the effect of variations in the consensus on security returns dominates the effect of variations in forecasts' dispersion. Consequently, the impact of information arrival on security prices does not only depend on the fact that expectations are revised upward (good news) or downward (bad news) but also depends on the direction and the magnitude of the change in expectations' dispersion.
Individual responsibility and voluntary action on climate change

In addressing climate change mitigation, matters of responsibility are core. It is widely acknowledged that individuals and households need to contribute to efforts to significantly reduce greenhouse gas emissions in order to meet international reduction targets (Pachauri 2007; Stern 2007). However, the role of individual responsibility for climate change mitigation in policy, discourse and practice, concomitant with the State and international regimes, remains largely undertheorised. Thereby the mechanisms that determine in what ways individuals should reduce their emissions and how actions taken at the local level link to the global level are not fully understood. Recent debate concerning the lack of provisions for voluntary measures by individuals and householders in the Australian Government's proposed Carbon Pollution Reduction Scheme (which includes an emissions trading scheme) illustrates that voluntary mitigation efforts may be poorly integrated at the national and hence the international level. This has important implications for achieving the deep global cuts in greenhouse emissions required to avoid dangerous climate change. Moreover individual responsibility for climate change implies that actors have authority not only over their " personal, private sphere " (Stern 2005) behaviour and lifestyles but that this authority extends to influence broader structural change. This paper will consider individual responsibility for climate change mitigation as it is expressed through forms of voluntary action; how perceptions of agency may contribute to broader level change; and the implications for linking local level climate change action with the global level.
On the fundamental groups of trees of manifolds

We consider limits of inverse sequences of closed manifolds, whose consecutive terms are obtained by connect summing with closed manifolds, which are in turn trivialized by the bonding maps. Such spaces, which we refer to as trees of manifolds, need not be semilocally simply connected at any point and can have complicated fundamental groups. Trees of manifolds occur naturally as visual boundaries of standard nonpositively curved geodesic spaces, which are acted upon by right-angled Coxeter groups whose nerves are closed PL-manifolds. This includes, for example, those Coxeter groups that act on Davis' exotic open contractible manifolds. Also, all of the homogeneous cohomology manifolds constructed by Jakobsche are trees of manifolds. In fact, trees of manifolds of this type, when constructed from PL-homology spheres of common dimension at least 4, are boundaries of negatively curved geodesic spaces. We prove that if Z is a tree of manifolds, the natural homomorphism φ: π 1 (Z) → π 1 (Z) from its fundamental group to its first shape homotopy group is injective. If Z = bdy X is the visual boundary of a nonpositively curved geodesic space X, or more generally, if Z is a Z-set boundary of any ANR X, then the first shape homotopy group of Z coincides with the fundamental group at infinity of X: π 1 (Z) = π 1 ∞ (X). We therefore obtain an injective homomorphism ψ: π 1 (Z) → π 1 ∞ (X), which allows us to study the relationship between these groups. In particular, if Z = bdy r is the boundary of one of the Coxeter groups Γ mentioned above, we get an injective homomorphism ψ: π 1 (bdy F) → π 1 ∞ (Γ).
Does staff–patient agreement on needs for care predict a better mental health outcome? A 4-year follow-up in a community service

Background Patients treated in primary care settings report better mental outcomes when they agree with practitioners about the nature of their core presenting problems. However, no study has examined the impact of staff–patient agreement on treatment outcomes in specialist mental health services. We investigated whether a better staff–patient agreement on needs for care predicts more favourable outcome in patients receiving community-based psychiatric care. Method A 3-month prevalence cohort of 188 patients with the full spectrum of psychiatric conditions was assessed at baseline and at 4 years using the Camberwell Assessment of Need (CAN), both staff (CAN-S) and patient versions (CAN-P), and a set of standardized outcome measures. Baseline staff–patient agreement on needs was included among predictors of outcome. Both clinician-rated (psychopathology, social disability, global functioning) and patient-rated (subjective quality of life and satisfaction with services) outcomes were considered. Results Controlling for the effect of sociodemographics, service utilization and changes in clinical status, better staff–patient agreement makes a significant additional contribution in predicting treatment outcomes not only on patient-rated but also on clinician-rated measures. Conclusions Mental health care should be provided on the basis of a negotiation process involving both professionals and service users to ensure effective interventions; every effort should be made by services to implement strategies aiming to increase consensus between staff and patients.
The Role of Financial Variables in Predicting Economic Activity

Previous research has shown that the US business cycle leads the European cycle by a few quarters, and can therefore help predicting euro area GDP. We investigate whether financial variables provide additional predictive power. We use a VAR model of the US and the euro area GDPs and extend it to take into account common global shocks and information provided by selected combinations of financial variables. In-sample analysis shows that shocks to financial variables influence real activity with a peak around 4 to 6 quarters after the shock. Out-of-sample Root-Mean- Squared Forecast Error (RMFE) shows that adding financial variables yields smaller errors in fore-casting US economic activity, especially at a five- quarter horizon, but the gain is overall tiny in economic terms. This link is even less prominent in the euro area, where financial indicators do not improve short and medium term GDP forecasts even when their timely availability, relative to a given GDP release, is exploited. The same conclusion is reached with a dataset of quarterly industrial production indices, although financial variables marginally improve fore- casts of monthly industrial production. We argue that the findings that financial variables have no predictive power for future activity in the euro area relate to the unconditional nature of the RMFE metric. When forecasting ability is assessed as if in real time (i.e. conditionally on the information available at the time when forecasts are made), we find that models using financial variables would have been preferred in many episodes, and in particular between 1999 and 2002. Results from the historical decomposition of a VAR model indeed suggest that in that period shocks were predominantly of financial nature. JEL Classification: F30, F42, F47
Optical MEMS-scale multipass white cell for onchip gas sensing

Spectroscopy-based gas sensing has become a major concern for scientists in different domains due to its diverse applications in environmental monitoring, industrial productions and healthcare applications. For sensing in a confined space, multipass optical gas cells are used to multiply the light-gas interaction length, and thus provide improved sensitivity. In this work, we propose a White-type gas cell for integration with optical MEMS systems such as tunable lasers and FTIR spectrometer. The cell is based on a confocal arrangement of curved micro mirrors. Analytical expression for the total path length is derived in terms of the cell dimensions and the maximum input angle of the light is obtained. The performance of the cell is studied using optical ray tracing for cylindrical and spherical mirrors with aperture size of 250–500 μm and different light excitation conditions. Promising results are obtained with about 2 dB insertion loss and optical path of about 4 mm that could be achieved with a cell volume of about 0.125 mm3.