Miracle-dz/UniFAR-FTUs huggingface dataset:
The evolution of the Milky Way from its earliest phases: Constraints on stellar nucleosynthesis

We computed the evolution of the abundances of O, Mg, Si, Ca, K, Ti, Sc, Ni, Mn, Co, Fe and Zn in the Milky Way. We made use of the most widely adopted nucleosynthesis calculations and compared the model results with observational data with the aim of imposing constraints upon stellar yields. To best fit the data in the solar neighborhood, when adopting the Woosley & Weaver (1995, ApJS, 101, 181) yields for massive stars and the Iwamoto et al. (1999, ApJS, 125, 439) ones for type Ia SNe, it is required that: i) the Mg yields should be increased in stars with masses from 11 to 20 Mand decreased in masses larger than 20 M� . The Mg yield should be also increased in SNe Ia. ii) The Si yields should be slightly increased in stars above 40 M� , whereas those of Ti should be increased between 11 and 20 Mand above 30 M� . iii) The Cr and Mn yields should be increased in stars with masses in the range 11-20 M� ; iv) the Co yields in SNe Ia should be larger and smaller in stars in the range 11-20 M� ; v) the Ni yield from type Ia SNe should be decreased; vi) the Zn yield from type Ia SNe should be increased. vii) The yields of O (metallicity dependent SN models), Ca, Fe, Ni, and Zn (the solar abundance case) in massive stars from Woosley & Weaver (1995) are the best to fit the abundance patterns of these elements since they do not need any changes. We also adopted the yields by Nomoto et al. (1997, Nucl. Phys. A, 621, 467) and Limongi & Chieffi (2003, ApJ, 592, 404) for massive stars and discuss the corrections required in these yields in order to fit the observations. Finally, the small spread in the (el/Fe) ratios in the metallicity range from (Fe/H) = − 4.0 up to−3.0 dex (Cayrel et al. 2004, A&A, 416, 1117) is a clear sign that the halo of the Milky Way was well mixed even in the earliest phases of its evolution.
Notice of RetractionDynamic relationship between oil price and China stock market

The paper takes the data from 1996:1 to 2009:12 as the research sample to deeply investigate the linkages between the oil price and China stock market. Empirical results show that there exists long term cointegration between oil price and China stock market. In the meanwhile, with economic situation changing and time passing, the correlation between oil price and China stock market changes at different periods. The impact of oil price on China stock market mainly concentrates in short-term. According to the oil price fluctuations, policy makers and financial investors can avoid the financial risks in China stock market which are caused by the fluctuations of oil price by adjusting portfolios timely.
COMPARING NN PARADIGMS IN HYBRID NN/H

Hybrid NN/HMM acoustic modeling is nowadays an established alternative approach in automatic speech recognition technology. A comparison of feed-forward and recurrent neural network topologies integrated in the tied-posteriors framework is presented. We give some insights in the training process of the networks estimating class posterior probabilities and show how the net’s quality can be determined by introducing a new measurement prior to evaluating the complete ASR system. Finally we demonstrate the flexibility of the tied-posteriors framework by showing results for different context independent and context dependent acoustic models all based on the same system structure.
BuildingSherlock : Fault Management Framework for HVAC Systems in Commercial Buildings

HVAC systems constitute ∼ 40% of energy in commercial buildings, and faults in HVAC account for 5% to 20% of its energy consumption. Typically, HVAC in modern buildings are managed using Building Managing Systems (BMS), and fault detection is one of the essential services provided by BMS to keep HVAC operational. We study the fault management practices followed in real commercial buildings, and find that current techniques used for fault detection fail to detect large number of efficiency related faults. Based on our findings, we developed BuildingSherlock (BDSherlock), which is a web service based fault management framework that exposes building information to automatically detect faults using useful algorithms. We deploy BDSherlock in a 145000 sqft building at UC San Diego, successfully detected 87 faults using data driven analysis.
How We Choose One over Another: Predicting Trial-by-Trial Preference Decision

Preference formation is a complex problem as it is subjective, involves emotion, is led by implicit processes, and changes depending on the context even within the same individual. Thus, scientific attempts to predict preference are challenging, yet quite important for basic understanding of human decision making mechanisms, but prediction in a group-average sense has only a limited significance. In this study, we predicted preferential decisions on a trial by trial basis based on brain responses occurring before the individuals made their decisions explicit. Participants made a binary preference decision of approachability based on faces while their electrophysiological responses were recorded. An artificial neural network based pattern-classifier was used with time-frequency resolved patterns of a functional connectivity measure as features for the classifier. We were able to predict preference decisions with a mean accuracy of 74.3±2.79% at participant-independent level and of 91.4±3.8% at participant-dependent level. Further, we revealed a causal role of the first impression on final decision and demonstrated the temporal trajectory of preference decision formation.
Reflecting the Choice and Usage of Communication Tools in GSD Projects with Media Synchronicity Theory

Global software development projects use a variety of communication media, such as teleconferences, email and instant messaging to overcome the challenges caused by the distances. Each communication media has different properties and capabilities to mediate the communication on different software engineering tasks. The use of different tools imply different communication practices. In this paper, we report our findings on communication in twelve distributed software projects: which communication tools were used, how they were used, and how communication tool use was related to different tasks in the project studied. We analyze the tool use and articulated rationale for choosing the communication tools for various tasks in distributed software development based on communicative processes and medium properties. We found evidence supporting applicability of media synchronicity theory in selecting communication tools for GSD projects.
Early recognition of gait initiation and termination using wearable sensors

This paper presents an approach for early recognition of gait initiation and termination using wearable inertial measurement units and pressure-sensitive insoles. Body joint angles, ground reaction force and center of plantar pressure of each foot are obtained from these sensors and input into a supervised learning algorithm. For gait initiation, the algorithm detects two events: gait onset (the first detectable change from the baseline state) and toe-off. For gait termination, the algorithm segments gait into different steps, measures the signals over a window at the beginning of each step, and determines whether the measurement belongs to the final step. The approach is validated with 10 subjects at two different gait speeds, with both within-subject and subject-independent crossvalidation. Results show that the inertial measurement units are generally more useful than insoles during both gait initiation and termination, though combining both types of sensors results in better onset detection and easier segmentation of gait into different steps. However, for best performance the algorithms should be trained for each subject separately, and the gait termination recognition algorithm is not very robust with regard to gait speed.
Modelling the probabilistic neural activation in deep brain stimulation: Influence of uncertainty in the parameters of the electrode-tissue-interface

Deep brain stimulation (DBS) is a neurosurgical method of stimulating deep brain areas with electrical pulses to treat symptoms of neurodegenerative disorders. To date in human DBS, these pulses are commonly voltage controlled resulting in a formation of an electrical double layer at the electrode-tissue-interface, which influences the time-dependent voltage response and neural activation in the proximity of the stimulated target. The aim of this study was to investigate the effect of uncertainties in these parameters. A probabilistic method based on a multi-dimensional polynomial expansion in combination with computationally efficient sparse grid integration technique was used. The results suggested that the influence of uncertainty in the parameters of the electrical double layer on the investigated quantities is negligible in volume conductor models of DBS.
Effect of electron-beam irradiation on electrospinning produced scaffolds

The influence of electron beam irradiation on the stiffness, stability and biocompatibility of electrospun scaffolds, produced from Nylon 6, polycaprolactone (PCL) and poly(DL-lactic-co-glicolic acid) (PLGA) was investigated. It was shown that irradiation of the matrices with an electron beam generated by the electron beam accelerator ILA-6 (2.2 MeV, 400 mA 10 Hz, “Radiochemical technologies Ltd”) can potentially be used for sterilization of the matrices (irradiation by a dose of 25 kGy does not interfere with the mechanical properties of all studied matrices). Irradiation of the matrices produced from PCL by a dose of 100 kGy increases the proportional limit of the material and allowed us to introduce durable regions into the vascular grafts by irradiating the graft through the template with open areas. Electron beam irradiation of the matrices does not interfere with the capacity of the matrices to support adhesion and viability of primary human endotheliocytes at the surfaces of these matrices, as it was shown using Alamar Blue assay.
Tension Analysis in Survivor Interviews: A Computational Approach

This study aims to develop computational techniques to analyze and identify points of tensions in interviews with survivors of the 1994 Rwandan genocide. Oral history interviews are a dialogical source composed of questions and answers, producing a conversational narrative Yet survivor testimony is often approached as though the questions did not exist. This article examines a digital tool that helps us visualize and better understand the underlying interview dynamic that is the heart of oral history and qualitative research more generally. Our tension detection tool identities those moments in the interview when the interviewer and interviewee are trying to pull the conversation in different directions. This is part of the natural give-and- take of the interview. Hedging, detection, hesitation, and boosting are all critical components of this interviewer-interviewee tension. By making the interview dynamic central to our analysis, we aim to better understand how the interview dynamic shapes was is being said and what is left unsaid. In this study, we address key components of interview tension and propose a natural language processing model that can efficiently incorporate these components in text- based oral history interviews to identify tension points. With experiments on an annotated transcript, we verify the efficacy of our model. This model provides a framework which can be utilized in future research on the dialogic of the interview.
Additive manufacturing for agile legged robots with hydraulic actuation

Agile and versatile legged robots are expected to become useful machines for applications in unstructured environments where traditional vehicles with wheels and tracks cannot go. Hydraulic actuation has proven to be a suitable actuation technology due to its high power density, robustness against impacts and high stiffness for high bandwidth control. In this paper we demonstrate how additive manufacturing (AM) can produce highly integrated hydraulic components with reduced weight and higher complexity when compared to traditionally manufactured manifolds. To the best knowledge of the authors, this is the first time a successful implementation of direct metal laser sintering (DMLS) of hydraulic manifolds made in aluminium alloy AlSiMg is presented. AlSiMg has several advantages for the construction of hydraulic components when compared to the commonly used Titanium alloys (e.g. Ti64): lower cost, higher thermal conductivity, lower density and easier to post-process. This paper first explains the build process with DMLS of AlSiMg and a pre-study of a pressure-tested hydraulic tube that demonstrated the suitability of AlSiMg for AM hydraulic components. Then, we discuss part orientation and support material during the build process of a highly-integrated hydraulic manifold for the legs of IIT's new hydraulic quadruped robot HyQ2Max. A comparison of this manifold with a traditionally manufactured alternative concludes the paper.
Algorithm of Ensemble Pulsar Time

An algorithm of the ensemble pulsar time based on the Wiener filtration method has been constructed. This algorithm has allowed the separation of the contributions of an atomic clock and a pulsar itself to the post-fit pulsar timing residuals. The method has been applied to the timing data of the millisecond pulsars PSR B1855+09 and PSR B1937+21 and allowed to filter out the atomic scale component from the pulsar phase variations. Direct comparison of the terrestrial time TT(BIPM96) and the ensemble pulsar time PTens has displayed that the difference TT(BIPM96) – PTens is within ±0.4 μs range. A new limit of gravitational wave background based on the difference TT(BIPM96) – PTens was established to be Ωgh2~10−10.
Pedometers to enhance physical activity in COPD: a randomised controlled trial

Physical inactivity is a cardinal feature of chronic obstructive pulmonary disease (COPD), and is associated with increased morbidity and mortality. Pedometers, which have been used in healthy populations, might also increase physical activity in patients with COPD. COPD patients taking part in a 3-month individualised programme to promote an increase in their daily physical activity were randomised to either a standard programme of physical activity encouragement alone, or a pedometer-based programme. Assessments were performed by investigators blinded to treatment allocation. Change in average 1-week daily step count, 6-min walking distance (6MWD), modified Medical Research Council scale, St George’s respiratory questionnaire (SGRQ) and COPD assessment test (CAT) were compared between groups. 102 patients were recruited, of whom 97 completed the programme (pedometer group: n=50; control group: n=47); 60.8% were male with a mean±sd age of 68.7±8.5 years, and forced expiratory volume in 1 s (FEV1) 66.1±19.4% and FEV1/forced vital capacity 55.2±9.5%. Both groups had comparable characteristics at baseline. The pedometer group had significantly greater improvements in: physical activity 3080±3254 steps·day−1 versus 138.3±1950 steps·day−1 (p<0.001); SGRQ −8.8±12.2 versus −3.8±10.9 (p=0.01); CAT score −3.5±5.5 versus −0.6±6.6 (p=0.001); and 6MWD 12.4±34.6 versus −0.7±24.4 m (p=0.02) than patients receiving activity encouragement only. A simple physical activity enhancement programme using pedometers can effectively improve physical activity level and quality of life in COPD patients. Pedometer-based programme produced clinically important improvements in physical activity and health status in COPD http://ow.ly/AmcCO
Interleaver design for spectrally-efficient bit-interleaved LDPC-coded modulation

A design methodology for interleavers in bit-interleaved coded modulation systems deploying (binary irregular) low-density parity-check (LDPC) codes and higher-order modulation is presented. The interleaver is introduced to balance unequal error protection characteristics inherent in coding and modulation. For this purpose, mapping distributions are used to describe the interleaver configuration. Furthermore, an optimization procedure is applied to derive good mapping distributions for practical block lengths in the order of 102-103 bits. Exemplary numerical results are presented for higher-order modulation and LDPC codes as defined in the IEEE standard 802.11n.
Why there is no statistical test for confounding, why many think there is, and why they are almost right

WHY THERE IS NO STATISTICAL TEST FOR CONFOUNDING, WHY MANY THINK THERE IS, AND WHY THEY ARE ALMOST RIGHT Judea Pearl January 30, 1998 1 INTRODUCTION Confounding is a simple concept. If we undertake to estimate the e ect of one variable X on another Y by examining the statistical association between the two, we ought to ensure that the association is not produced by factors other than the e ect under study. The presence of spurious association, due for example to the in uence of extraneous variables, is called confounding as it tends to confound our reading and to bias our estimate of the e ect studied. Conceptually, therefore, we can say that X and Y are confounded when there is a third variable Z that in uences both X and Y ; such a variable is then called a confounder of X and Y . As simple as this concept is, it has resisted formal treatment for several decades, and for a good reason: The very notions of e ect and in uence , relative to which spu- rious association is to be de ned, has resisted mathematical formulation. The empirical de nition of e ect as an association that would prevail in a controlled randomized exper- iment, cannot easily be expressed in the standard language of probability theory, because that theory deals with static conditions, and does not permit us to predict, even from a full speci cation of a population density function, what relationships would prevail if conditions were to change, say from observational to controlled studies. Such predictions require extra information, in the form of causal or counterfactual assumptions Greenland and Robins 1986; Wickramaratne and Holford 1987 , which is not discernible from density functions. These di culties notwithstanding, epidemiologists, biostatisticians, social scientists and economists 1 have made numerous attempts to express confounding in statistical terms, partly because statistical de nitions, free of theoretical terms of e ect or in uence, can be expressed in conventional mathematical form, and partly because such de nitions may lead to Technical Report R-256, January 1998. Draft copy comments welcome. In econometrics, the problem is mirrored by decades-long di culties in de ning exogeneity , Engle et al., 1983; Leamer, 1985; Aldrich 1993 which stands essentially for no confounding . According to Aldrich 1993 and Imbens 1997 the di culties are still unsettled.
Synthesis, Electric Transport, Mössbauer Spectroscopy, Specific Heat and Induction of Superconductivity in ReFeAsO (Re=La, Pr, Gd and Sm) †

We report an easy and versatile route of synthesis for ReFeAsO (Re = La, Gd, Pr and Sm) by both single step and precursor based double step solid-state reaction routes. The studied ground state compounds of the new FeAs based superconductor family crystallize in tetragonal P4/nmm structure, with lattice parameters variation following their ionic radii. The resistivity measurements exhibit clearly the appearance of a metallic step below say 150-130 K, which is reminiscent of the SDW (Spin Density Wave) magnetic character. Also, It is observed that oxygen stoichiometric ReFeAsO is not formed and rather the same is slightly oxygen deficient. The Mossbauer spectroscopy (MS) carried out on some of them at 290 K and 90 K i.e. both above and below the SDW temperature exhibits the Fe ordered state at 90 K. Further the MS is proved to be the most efficient technique in picking up the FeAs based impurities in these materials. The heat capacity measurements on SmFeAsO, clearly demonstrates the SDW temperature with a hump in Cp(T) at around 130 K. Further Sm spins are ordered anti-ferro-magnetically (AFM) at 4.5 K. Superconductivity is also induced in SmFeAsO with Co substitution at Fe site with Tc = 14 K. The general behavior of the ReFeAsO is discussed and it is concluded that (a) they can be synthesized by an easy and versatile methods, (b) their ground state is not oxygen stoichiometric, but deficient and (c) MS is the most efficient technique to pick up the Fe based impurities in these materials, that is yet rampant in this new class of superconductors.
The redshift evolution of the distribution of star formation among dark matter halos as seen in the infrared

Recent studies have revealed a strong correlation between the star formation rate (SFR) and stellar mass of the majority of star-forming galaxies, the so-called star-forming main sequence. An empirical modeling approach (the 2-SFM framework) that distinguishes between the main sequence and rarer starburst galaxies is capable of reproducing most statistical properties of infrared galaxies, such as number counts, luminosity functions, and redshift distributions. In this paper, we extend this approach by establishing a connection between stellar mass and halo mass with the technique of abundance matching. Based on a few simple assumptions and a physically motivated formalism, our model successfully predicts the (cross-)power spectra of the cosmic infrared background (CIB), the cross-correlation between CIB and cosmic microwave background (CMB) lensing, and the correlation functions of bright, resolved infrared galaxies measured by Herschel, Planck, ACT, and SPT. We use this model to infer the redshift distribution of CIB-anisotropies and of the CIB × CMB lensing signal, as well as the level of correlation between CIB-anisotropies at different wavelengths. We study the link between dark matter halos and star-forming galaxies in the framework of our model. We predict that more than 90% of cosmic star formation activity occurs in halos with masses between 1011.5 and 1013.5 M⊙. If taking subsequent mass growth of halos into account, this implies that the majority of stars were initially (at z > 3) formed in the progenitors of clusters (Mh(z = 0) > 1013.5 M⊙), then in groups (1012.5 < Mh(z = 0) < 1013.5 M⊙) at 0.5 < z < 3, and finally in Milky-Way-like halos (1011.5 < Mh(z = 0) < 1012.5 M⊙) at z < 0.5. At all redshifts, the dominant contribution to the SFR density stems from halos of mass ~1012 M⊙, in which the instantaneous star formation efficiency – defined here as the ratio between SFR and baryonic accretion rate – is maximal (~70%). The strong redshift-evolution of SFR in the galaxies that dominate the CIB is thus plausibly driven by increased accretion from the cosmic web onto halos of this characteristic mass scale. Material (effective spectral energy distributions, differential emissivities of halos, relations between Mh and SFR) associated to this model is available at http://irfu.cea. fr/Sap/Phocea/Page/index.php? id=537.
COMPARISON OF LANDCOVER CLASSIFICATION METHODS IN THE BRAZILIAN AMAZON BASIN

Numerous classifiers have been developed and different classifiers have their own characteristics. Controversial results often occurred depending on the landscape complexity of the study area and the data used. Therefore, this paper aims to find a suitable classifier for the tropical land cover classification. Five classifiers – minimum distance classifier (MDC), maximum likelihood classifier (MLC), fisher linear discriminant (FLD), extraction and classification of homogeneous objects (ECHO), and linear spectral mixture analysis (LSMA) – were tested using Landsat Thematic Mapper (TM) data in the Amazon basin using the same training sample data sets. Seven land cover classes – mature forest, advanced succession forest, initial secondary succession forest, pasture, agricultural lands, bare lands, and water – were classified. Overall classification accuracy and kappa analysis were calculated. The results indicate that LSMA and ECHO classifiers provided better classification accuracies than the MDC, MLC, and FLD in the moist tropical region. The overall accuracy of LSMA approach reaches 86% associated with 0.82 kappa coefficient.