Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Human Decision-Making with Machine Learning

A key aspect of human intelligence is their ability to convey their knowledge to others in succinct forms. However, current machine learning models are largely blackboxes that are hard for humans to learn from. We study the problem of whether we can design machine learning algorithms capable of conveying their insights to humans in the context of a sequential decision making task. In particular, we propose a novel machine learning algorithm for extracting inter-pretable tips from a policy trained to solve the task using reinforcement learning. In particular, it searches over a space of interpretable decision rules to identify the one that most improves human performance. Then, we perform an extensive user study to evaluate our approach, based on a virtual kitchen-management game we designed that requires the participant to make a series of decisions to minimize overall service time. Our experiments show that (i) the tips generated by our algorithm are effective at improving performance, (ii) they signiﬁcantly outperform the two baseline tips, and (iii) they successfully help participants build on their own experience to discover additional strategies and overcome their resistance to exploring counterintuitive strategies.
An inductive logic programming approach to the classification of phases in business cycles

A workbench for knowledge acquisition and data analysis is presented and its use for the classi cation of business cycles is investigated. Inductive Logic Programming (ILP) allows to model relations between intervals, e.g. time or value intervals. Moreover, the user of the workbench is supported in inspecting the learned rules, not only with respect to their coverage, accuracy, and redundancy, but also regarding consistency (i.e., logical contradictions). The application of ILP requires pre-processing in order to establish time and value intervals. To this end, top-down induction of decision trees is used. This paper describes the workbench MOBAL, its learning algorithm RDT, the preprocessing of data, and the rst encouraging results on business cycle data from Germany.
3 Fully Character-Level Translation 3 . 1 Why Character-Level ?

Most existing machine translation systems operate at the level of words, relying on explicit segmentation to extract tokens. We introduce a neural machine translation (NMT) model that maps a source character sequence to a target character sequence without any segmentation. We employ a character-level convolutional network with max-pooling at the encoder to reduce the length of source representation, allowing the model to be trained at a speed comparable to subword-level models while capturing local regularities. Our character-to-character model outperforms a recently proposed baseline with a subwordlevel encoder on WMT’15 DE-EN and CSEN, and gives comparable performance on FIEN and RU-EN. We then demonstrate that it is possible to share a single characterlevel encoder across multiple languages by training a model on a many-to-one translation task. In this multilingual setting, the character-level encoder significantly outperforms the subword-level encoder on all the language pairs. We observe that on CS-EN, FI-EN and RU-EN, the quality of the multilingual character-level translation even surpasses the models specifically trained on that language pair alone, both in terms of BLEU score and human judgment.
Reconnecting instabilities in JT-60SA during current ramp-up with off-axis N-NB injection

We report results of global resistive magnetohydrodynamic (MHD) simulations, which predict that wide-spread reconnecting instabilities may cause an internal disruption when 5 MW off-axis negative-ion-based neutral beam (N-NB) injection is used during the current ramp-up phase of a JT-60SA plasma. The simulations include fast ions as passive test particles and were initialized with plasma profiles obtained from an integrated transport simulation. The beam-driven current produces a nonmonotonic safety factor profile with three q = 2 rational surfaces. The resulting double or multiple kink-tearing instabilities redistribute both the bulk and fast particles in the inner half of the plasma. While the radial profiles appear to be flattened, the actual field topology and particle distributions are found to saturate in helical states. Moreover, because magnetic drifts are still large during the current ramp-up phase, there is a large difference between the topology of the magnetic field and 500 keV deuteron orbits. Fast ion phase space islands may thus appear and overlap at different times and in different regions than their magnetic counterparts.
Matrix Completion From a Few Entries

Let M be an n¿ × n matrix of rank r, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm, which we call OptSpace, that reconstructs M from |E| = O(rn) observed entries with relative root mean square error 1/2 RMSE ¿ C(¿) (nr/|E|)1/2 with probability larger than 1 - 1/n3. Further, if r = O(1) and M is sufficiently unstructured, then OptSpace reconstructs it exactly from |E| = O(n log n) entries with probability larger than 1 - 1/n3. This settles (in the case of bounded rank) a question left open by Candes and Recht and improves over the guarantees for their reconstruction algorithm. The complexity of our algorithm is O(|E|r log n), which opens the way to its use for massive data sets. In the process of proving these statements, we obtain a generalization of a celebrated result by Friedman-Kahn-Szemeredi and Feige-Ofek on the spectrum of sparse random matrices.
A new approach for SAR baseband Doppler centroid estimation

In synthetic aperture radar (SAR), many of the biased baseband Doppler centroid estimates are caused by partial exposures of bright targets. To avoid this problem, this paper proposes a new estimation algorithm to remove the effects of partial exposures under non-homogeneous environment. This algorithm is implemented by three steps. Firstly, concentrate the energy of each target into a few pixels through azimuthal compression using frequency domain matched filter. Then, extract the homogeneous environment through the spectral distortion and contrast, and eliminate the strong interference target. Finally, estimate the centroid of the averaged extracted power spectrum using a circular convolution method. Theoretical analysis and experimental results show that the proposed method can effectively eliminate the interference targets and accurately find the Doppler centroid under non-homogeneous environment with strong interference. Moreover, the operations of the proposed algorithm need no iterations, thus the computational load is greatly reduced compared with the traditional iterative methods.
PGTRNet: Two-phase Weakly Supervised Object Detection with Pseudo Ground Truth Refining

Weakly Supervised Object Detection (WSOD), aiming to train detectors with only image-level annotations, has arisen increasing attention. Current state-of-the-art approaches mainly follow a two-stage training strategy which integrates a fully supervised detector (FSD) with a pure WSOD model. There are two main problems hindering the performance of the two-phase WSOD approaches, i.e., in-sufﬁcient learning problem and strict reliance between the FSD and the pseudo ground truth (PGT) generated by the WSOD model. This paper proposes pseudo ground truth re-ﬁnement network (PGTRNet), a simple yet effective method without introducing any extra learnable parameters, to cope with these problems. PGTRNet utilizes multiple bounding boxes to establish the PGT, mitigating the insufﬁcient learning problem. Besides, we propose a novel online PGT re-ﬁnement approach to steadily improve the quality of PGT by fully taking advantage of the power of FSD during the second-phase training, decoupling the ﬁrst and second-phase models. Elaborate experiments are conducted on the PASCAL VOC 2007 benchmark to verify the effectiveness of our methods. Experimental results demonstrate that PGTRNet boosts the backbone model by 2.074% mAP and achieves the state-of-the-art performance, showing the signiﬁcant potentials of the second-phase training.
Externalizing and internalizing problems in relation to autonomic function: a population-based study in preadolescents.

OBJECTIVE To investigate whether externalizing and internalizing problems are related to lower and higher heart rate (HR), respectively, and to explore the relationship of these problems with respiratory sinus arrhythmia (RSA) and baroreflex sensitivity (BRS). Moreover, to study whether problems present at both preschool and preadolescent age show stronger associations with autonomic function than those that were not. METHOD In a population cohort of 10- to 13-year-old children (N = 931; 11.6 +/- 0.5 years; 47% boys), autonomic measurements in supine and standing position were performed at school. RSA and BRS were determined by spectral analysis. Current externalizing and internalizing problems were assessed by the Child Behavior Checklist and problems at age 4 to 5 retrospectively by the Preschool Behavior Questionnaire. RESULTS At supine rest, current externalizing problems were associated with lower HR and higher RSA, but not with BRS and current internalizing problems with higher HR and lower RSA, but not with BRS. These results were specifically found in children with problems that were retrospectively reported to have been also present at preschool age. Standing-induced changes in autonomic parameters were unrelated to the behavioral dimensions. CONCLUSIONS Externalizing and internalizing problems are associated with divergent autonomic patterns, suggesting autonomic underarousal and overarousal, respectively. Problems starting early in life may specifically account for this. This should be confirmed in prospective studies.
How brokers can optimally plot against traders

Traders buy and sell financial instruments in hopes of making profit, and brokers are responsible for the transaction. Some brokers, known as market-makers, take the position opposite to the trader's. If the trader buys, they sell; if the trader sells, they buy. Said differently, brokers make money whenever their traders lose money. From this somewhat strange mechanism emerge various conspiracy theories, notably that brokers manipulate prices in order to maximize their traders' losses. In this paper, our goal is to perform this evil task optimally. Assuming total control over the price of an asset (ignoring the usual aspects of finance such as market conditions, external influence or stochasticity), we show how in cubic time, given a set of trades specified by a stop-loss and a take-profit price, a broker can find a maximum loss price movement. We also study the same problem under a model of probabilistic trades. We finally look at the online trade setting, where broker and trader exchange turns, each trying to make a profit. We show that the best option for the trader is to never trade.
Prognostic nutritional index before adjuvant chemotherapy predicts chemotherapy compliance and survival among patients with non-small-cell lung cancer

Background: Adjuvant chemotherapy after the complete resection of non-small-cell lung cancer (NSCLC) is now the standard of care. To improve survival, it is important to identify risk factors for the continuation of adjuvant chemotherapy. In this study, we analyzed chemotherapy compliance and magnitude of the prognostic impact of the prognostic nutritional index (PNI) before adjuvant chemotherapy. Methods: We conducted a retrospective review of data from 106 patients who had received adjuvant chemotherapy. The adjuvant chemotherapy consisted of an oral tegafur agent (OT) or platinum-based chemotherapy (PB). The correlations between the PNI values and recurrence-free survival (RFS) were then evaluated. Results: In the PB group, the percentage of patients who completed the four planned cycles of chemotherapy was not correlated with the PNI. In the OT group, however, a significant difference was observed in the percentage of patients who completed the planned chemotherapy according to the PNI before adjuvant chemotherapy. The RFS of patients with a PNI , 50 before adjuvant chemotherapy was significantly poorer than that of the patients with a PNI $ 50. A multivariate analysis showed that nodal metastasis and PNI before chemotherapy were independent predictors of the RFS. However, PNI before surgery was not a predictor of the RFS. In the subgroup analysis, PNI before chemotherapy was independent predictor of the RFS in the OT group ( P = 0.019), but not in the PB group ( P = 0.095). Conclusion: The PNI before adjuvant chemotherapy influenced the treatment compliance with the planned chemotherapy in the OT group, but not the PB group. In addition, a low PNI before adjuvant chemotherapy was associated with a poor RFS in a multivariate analysis, especially in the OT group.
Material : On the Equivalence of Holographic and Complex Embeddings for Link Prediction

1.2 Datasets and Evaluation Protocol We used a benchmark dataset FB15k1, which is a large subgraph of Freebase where all entities are present in Wikilinks database. The FB15k dataset consists of 483,142 training, 50,000 development, and 59,071 testing triples, containing 14,951 entities and 1,345 relation types. We adopt the same evaluation protocol used in previous studies. For each test triple (r, s,o), we corrupt it by replacing the object o (or the subject s) with every entity e in the knowledge graph and calculate a score of this corrupted triple (r, s,e) (or (r,e,o)). Then, we rank all these triples by their scores in decreasing order. To measure the quality of the ranking, we use the mean reciprocal rank (MRR). In this paper, we report its filtered version: for some testing sample (r, s,o), if we calculate the metric for the subject s (or the object o),
Thermo-Hydrodynamics of a Helical Coil Heat Exchanger Operated with a Phase-Change Ice Slurry as a Refrigerant

ABSTRACT The thermal performance of helical-coil heat exchangers can be significantly enhanced when operated with ice slurry as a phase-change refrigerant. It is essential to also consider the hydrodynamics of ice slurry flow to determine the overall performance of the heat exchanger. This study presents a detailed numerical investigation of the thermo-hydrodynamic performance of a helical coil heat exchanger operated with a laminar and non-Newtonian flow of ethyl-alcohol ice slurry subject to phase change. The Bingham plastic model is used to reflect the non-Newtonian behavior of ice slurry. The phase change of ice slurry is modelled using the enthalpy-porosity method. The pressure drop and heat transfer of ice slurry in a double-turn helical coil are determined in terms of ice mass fraction and Dean number. The results show that an increase in the ice mass fraction and Dean number results in an increase of the heat transfer rate. This is, however, associated with an increase in pressure drop. The entropy generation analysis is introduced to evaluate the overall performance of the heat exchanger, taking into account the opposing effects of heat transfer and pressure drop. It is evident that, at certain ice mass fractions, there exists an optimal value of the Dean number that leads to minimum irreversibility and maximum overall performance.
Numerical simulation of long rods impacted by particle beams

Analytical solutions detailing the propagation of longitudinal waves in slender rods subjected to a sudden increase of internal energy provide simple tools for the calculation of the temperature distribution in impacted rods as well as the resulting mechanical response. The topic is of great interest in particle accelerator technology, especially with regards to collimation systems, where beam intercepting devices can be generally approximated to one-dimensional (1D) elements potentially subjected, in accidental scenarios, to abrupt thermal energy depositions induced by the impacting particles. In this study, two finite element numerical models are presented and compared to the analytical solutions by Bertarelli, Dallocchio and Kurtyka, discussing the rapid temperature increase in slender rods due to particle beam impacts and the resulting dynamic longitudinal response. The first model is a sequentially coupled thermomechanical analysis; the second is based on a modal analysis to find the harmonic response of the system. The results indicate that phenomena neglected in analytical solutions, primarily dispersion of the longitudinal wave due to interactions with the free external surface of the rod, can be included in numerical models and can be observed in simulation results. The study further shows how numerical methods can be utilized to predict the frequencies and amplitudes of high-frequency disturbances in the longitudinal wave signal, and how these effects can be mitigated in preparation for experimental scenarios by fine-tuning the geometry of the rod and varying the duration of the pulse. This is especially useful with regards to experiments conducted in the HiRadMat facility at CERN, such as the recently conducted HRMT36 experiment, where high-frequency components can distort the signal to be observed.
Absorption lines from magnetically driven winds in X-ray binaries II: high resolution observational signatures expected from future X-ray observatories

In our self-similar, analytical, magneto-hydrodynamic (MHD) accretion-ejection solution, the density at the base of the outflow is explicitly dependent on the disk accretion rate - a unique property of this class of solutions. We had earlier found that the ejection index $p >\sim 0.1 (\dot{M}_{acc} \propto r^p )$ is a key MHD parameter that decides if the flow can cause absorption lines in the high resolution X-ray spectra of black hole binaries. Here we choose 3 dense warm solutions with p = 0.1, 0.3, 0.45 and carefully develop a methodology to generate spectra which are convolved with the Athena and XRISM response functions to predict what they will observe seeing through such MHD outflows. In this paper two other external parameters were varied - extent of the disk, $\rm {r_o|_{max}} = 10^5, \, 10^6 \, \, \rm {r_G}$, and the angle of the line of sight, i ∼ 10 − 25○. Resultant absorption lines (H and He-like Fe, Ca, Ar) change in strength and their profiles manifest varying degrees of asymmetry. We checked if a) the lines and ii) the line asymmetries are detected, in our suit of synthetic Athena and XRISM spectra. Our analysis shows that Athena should detect the lines and their asymmetries for a standard 100 ksec observation of a 100 mCrab source - lines with equivalent width as low as a few eV should be detected if the 6-8 keV counts are larger than 104 − 105 even for the least favourable simulated cases.
Modal matters in interpretability logics

In this paper we expose a method for building models for interpretability logics. The method can be compared to the method of taking unions of chains in classical model theory. Many applications of the method share a common part. We isolate this common part in a main lemma. Doing so, many of our results become applications of this main lemma. We also briefly describe how our method can be generalized to modal logics with a different signature. With the general method, we prove completeness for the interpretability logics IL, ILM, ILM0 and ILW*. We also apply our method to obtain a classification of the essential Σ1-sentences of essentially reflexive theories. We briefly comment on such a classification for finitely axiomatizable theories. As a digression we proof some results on self-provers. Towards the end of the paper we concentrate on modal matters con- cerning IL(All), the interpretability logic of all reasonable arithmetical theories. We prove the modal incompleteness of the logic ILW*P0. We put forward a new principle R, and show it to be arithmetically sound in any reasonable arithmetical theory. Finally we make some general remarks on the logics ILRW and IL(All).
Rotational Spectra in 29 Vibrationally Excited States of Interstellar Aminoacetonitrile

We report a detailed spectroscopic investigation of the interstellar aminoacetonitrile, a possible precursor molecule of glycine. Using a combination of Stark and frequency-modulation microwave and millimeter wave spectroscopies, we observed and analyzed the room-temperature rotational spectra of 29 excited states with energies up to 1000 cm−1. We also observed the 13C isotopologues in the ground vibrational state in natural abundance (1.1%). The extensive data set of more than 2000 new rotational transitions will support further identifications of aminoacetonitrile in the interstellar medium.
On the Effect of Rotation on Populations of Classical Cepheids II. Pulsation Analysis for Metallicities 0.014, 0.006, and 0.002

Classical Cepheid variable stars are high-sensitivity probes of stellar evolution and fundamental tracers of cosmic distances. While rotational mixing significantly affects the evolution of Cepheid progenitors (intermediate-mass stars), the impact of the resulting changes in stellar structure and composition on Cepheids on their pulsational properties is hitherto unknown. Here we present the first detailed pulsational instability analysis of stellar evolution models that include the effects of rotation, for both fundamental mode and first overtone pulsation. We employ Geneva evolution models spanning a three-dimensional grid in mass (1.7 - 15 $M_\odot$), metallicity (Z = 0.014, 0.006, 0.002), and rotation (non-rotating, average & fast rotation). We determine (1) hot and cool instability strip (IS) boundaries taking into account the coupling between convection and pulsation, (2) pulsation periods, and (3) rates of period change. We investigate relations between period and (a) luminosity, (b) age, (c) radius, (d) temperature, (e) rate of period change, (f) mass, (g) the flux-weighted gravity-luminosity relation (FWGLR). We confront all predictions aside from those for age with observations, finding generally excellent agreement. We tabulate period-luminosity relations (PLRs) for several photometric pass-bands and investigate how the finite IS width, different IS crossings, metallicity, and rotation affect PLRs. We show that a Wesenheit index based on H, V, and I photometry is expected to have the smallest intrinsic PLR dispersion. We confirm that rotation resolves the Cepheid mass discrepancy. Period-age relations depend significantly on rotation (rotation increases Cepheid ages), offering a straightforward explanation for evolved stars in binary systems that cannot be matched by conventional isochrones assuming a single age. Finally, we show that Cepheids obey a tight FWGLR.
Octopus: A multi-job scheduler for Graphlab

Graphlab, which is a framework for large graph processing currently does not support multiple job scheduling simultaneously. However, for efficient use of the cluster resources, it may be required to share the cluster among multiple jobs. The challenges in multi-job scheduling in the case of graph processing are different from other frameworks such as Hadoop. In Hadoop, it is possible to schedule multiple jobs by fairly allocating resources to the jobs. We show in this paper that such an approach does not provide optimal results in the case of graph processing. We propose Octopus, a fair multi-job scheduler for Graphlab. The scheduler uses two different algorithms viz., First Fit with round robin Filling (FFF) and First In First Out with round robin Filling (FIFOF) to schedule large jobs of a user. We compare the performance of both the algorithms on a 20-node cluster. Preliminary results show that non-preemptive time sharing approach among users exhibits significant gain in turnaround time when compared to spatial resource sharing.