Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Strategy to Improve Reading Comprehension

Reading comprehension is a task that is sufficiently close to information extraction applications such as question answering. A reading comprehension (RC) system attempts to understand a document and returns an answer sentence when posed with a question. This paper proposes an RC system which utilizes different techniques, including pattern matching, semantic relation inference and the context assistance rule set. This approach gave improved RC performances for the Remedia corpus. We give the deep performance analysis across the experimental results, such as the performance impact by different techniques, performance impact by the technique of co-reference resolution, and we also ran pairwise t-tests that show the significance on performance improvements.
Editorial Decisions May Perpetuate Belief in Invalid Research Findings

Social psychology and related disciplines are seeing a resurgence of interest in replication, as well as actual replication efforts. But prior work suggests that even a clear demonstration that a finding is invalid often fails to shake acceptance of the finding. This threatens the full impact of these replication efforts. Here we show that the actions of two key players – journal editors and the authors of original (invalidated) research findings – are critical to the broader public’s continued belief in an invalidated research conclusion. Across three experiments, we show that belief in an invalidated finding falls sharply when a critical failed replication is published in the same – versus different – journal as the original finding, and when the authors of the original finding acknowledge that the new findings invalidate their conclusions. We conclude by discussing policy implications of our key findings.
MSWIM demo abstract: direct code execution: increase simulation realism using unmodified real implementations

We propose to demonstrate Direct Code Execution (DCE), a ns-3 simulation framework that enables reproducible network experiments using real Linux kernel space protocol stacks along with POSIX socket based protocol implementations. In addition to increased experimentation realism, it offers a highly configurable topology environment and allows easy debugging of communication protocols distributed other multiple nodes. Our demonstration will showcase two typical use cases of DCE: information-centric networking over mobile ad hoc network using the PARC CCNx code, and a seamless handoff experiment based on a Linux Multipath TCP (MPTCP) implementation.
Concurrent JavaScript Parsing for Faster Loading of Web Apps

JavaScript is a dynamic language mainly used as a client-side web script. Nowadays, web is evolving into an application platform with its web apps, and JavaScript increasingly undertakes complex computations and interactive user interfaces, requiring a high-performance JavaScript engine. There have been many optimizations for efficient JavaScript engines, but one component that has not been optimized much is JavaScript parsing. A JavaScript function needs to be parsed before being executed, and the parsing overhead takes a substantial portion of JavaScript execution time for web apps, especially during app loading. This article proposes concurrent parsing of JavaScript, which performs the parsing of JavaScript functions in advance on different threads, while the main thread is executing the parsed JavaScript functions. This can hide the parsing overhead from the main execution thread, reducing the JavaScript execution time, thus reducing the overall app loading time. More specifically, we separated JavaScript parsing and made it run on different threads without violating the execution semantics of JavaScript. We also designed an efficient multi-threaded parsing architecture, which reduces the synchronization overhead and schedules the parsing requests appropriately. Finally, we explored two methods of choosing the target functions for concurrent parsing: one based on profiled information and the other based on speculative heuristics. We performed experiments on the WebKit browser with the JSC engine for real web apps. The result shows that the proposed concurrent parsing can improve the JavaScript performance during app loading by as much as 64% and by 39.7% on average. This improves the whole app loading performance tangibly, by as much as 32.7% and by 18.2%, on average.
No evidence for decreased foreign language effect in highly proficient and acculturated bilinguals: a commentary on Čavar and Tytus (2018)

ABSTRACT Bilinguals who consider moral problems in their foreign language tend to endorse causing harm to others if that leads to good outcomes more than they do in their native language. Čavar and Tytus [2018. “Moral Judgement and Foreign Language Effect: When the Foreign Language Becomes the Second Language. ” Journal of Multilingual and Multicultural Development 39 (1): 17–28] reported that this effect disappears when the decision maker is highly acculturated. We challenge the latter conclusion. Specifically, the experiment reported by Čavar and Tytus (2018) utilised unvalidated and potentially unreliable materials, was underpowered, and lacked a control group. Moreover, a re-analysis of their statistical test shows that it fails to convincingly support the reported null finding. We conclude that further examination of the moral foreign language effect is needed to test its boundaries.
Igusa integrals and volume asymptotics in analytic and adelic geometry

We establish asymptotic formulae for volumes of height balls in analytic varieties over local fields and in adelic points of algebraic varieties over number fields, relating the Mellin transforms of height functions to Igusa integrals and to global geometric invariants of the underlying variety. In the adelic setting, this involves the construction of general Tamagawa measures.
Clustering for closely similar recipes to extract spam recipes in user-generated recipe sites

Nowadays, many user-generated recipe sites are accessible on the internet. On user-generated recipe sites, however, are various spam recipe pages that describe closely similar recipes requiring special cooking equipment, with no preparation explanations. These spam recipes are not useful for users. In fact, they impede user's recipe searches. In this paper, we target closely similar recipes as a first step in extracting spam recipes. If user search results could be classified to identify closely similar recipes, user's recipe searches would be easier and more productive. Clustering tools of many kinds are proposed, but it is difficult to cluster closely similar recipes using only existing clustering tools because recipe sites have a unique page structure comprising a title, ingredients, directions (preparation instructions), and comments. The importance of words from each part differs. We propose a clustering method for user-generated recipe sites based on page structure and important words. Next, we conducted an experiment to measure the benefits of our proposed method. The result of experiment presents the benefits of our proposed method which classify the closely similar recipes.
Efficiency of Peptide Nucleic Acid-Directed PCR Clamping and Its Application in the Investigation of Natural Diets of the Japanese Eel Leptocephali

Polymerase chain reaction (PCR)-clamping using blocking primer and DNA-analogs, such as peptide nucleotide acid (PNA), may be used to selectively amplify target DNA for molecular diet analysis. We investigated PCR-clamping efficiency by studying PNA position and mismatch with complementary DNA by designing PNAs at five different positions on the nuclear rDNA internal transcribed spacer 1 of the Japanese eel Anguilla japonica in association with intra-specific nucleotide substitutions. All five PNAs were observed to efficiently inhibit amplification of a fully complementary DNA template. One mismatch between PNA and template DNA inhibited amplification of the template DNA, while two or more mismatches did not. DNA samples extracted from dorsal muscle and intestine of eight wild-caught leptochephalus larvae were subjected to this analysis, followed by cloning, nucleotide sequence analysis, and database homology search. Among 12 sequence types obtained from the intestine sample, six were identified as fungi. No sequence similarities were found in the database for the remaining six types, which were not related to one another. These results, in conjunction with our laboratory observations on larval feeding, suggest that eel leptocephali may not be dependent upon living plankton for their food source.
An Adaptive Controller for Bilateral Teleoperators: Variable Time-Delays Case

Abstract It is well known that in most bilateral teleoperation systems, variable time-delays arise in the communications. Motivated by this fact, the present work reports the extension to the (asymmetric) variable time-delays case of the adaptive controller for bilateral teleoperators with uncertain parameters and constant time-delays, reported in Nuno et al (2010) [Nuno, E. , Ortega, R. and Basanez, L. (2010). An adaptive controller for nonlinear teleoperators. Automatica, 46(1), 155–159]. Compared to the previous work, the stability analysis does not rely on the cascade interconnection structure of the local and remote nonlinear dynamics and the linear interconnection map. Instead, the paper employs a different Lyapunov candidate function that incorporates a strictly positive term, the local and remote position error. With the only assumption that a bound of the time-delays is known, the paper also presents a sufficient condition that ensures the asymptotic convergence of position errors and velocities to zero. Some simulations, in free space and interacting with a stiff wall, illustrate the performance of the proposed control scheme in the presence of variable time–delays.
Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair.
Pressure and Free Flight Time Effects on Glow Discharge Characteristics

this work, a model for a DC glow discharge at low pressure, used in many applications has been developed. This model allows the determination of plasma characteristics distributions in 2D geometry. The proposed theoretical model is applied to collisional argon plasma at low pressure in a reactor consisting of two plane parallel electrodes where the cathode is heated to a voltage of -250 V. The proposed code is based on solving the continuity equation coupled with Poisson's equation and electrons mean energy's equation. The particles trajectories simulation requires the knowledge of all collisional processes through their collision cross sections. The probability of collision during a free flight time can not be known without performing integrations of non-analytical cross sections. The proposed solution to this problem consists in the application of the "null collision" concept. The simulation results are shown in terms of spatial distribution of charged particles, potential, electric field, electrons energy and velocity. The study of the pressure (0.1-1Torr) and the free flight time (5.11x10 -9 to 1.46 x10 - 7 s) effect, on the
Facial Action Unit Event Detection by Cascade of Tasks

Automatic facial Action Unit (AU) detection from video is a long-standing problem in facial expression analysis. AU detection is typically posed as a classification problem between frames or segments of positive examples and negative ones, where existing work emphasizes the use of different features or classifiers. In this paper, we propose a method called Cascade of Tasks (CoT) that combines the use of different tasks (i.e., frame, segment and transition) for AU event detection. We train CoT in a sequential manner embracing diversity, which ensures robustness and generalization to unseen data. In addition to conventional frame based metrics that evaluate frames independently, we propose a new event-based metric to evaluate detection performance at event-level. We show how the CoT method consistently outperforms state-of-the-art approaches in both frame-based and event-based metrics, across three public datasets that differ in complexity: CK+, FERA and RU-FACS.
ISOCAM view of the starburst galaxies M 82, NGC 253 and NGC 1808

We present results of mid-infrared $\lambda = 5.0$–$16.5~\mathrm{\mu m}$ spectrophotometric imaging of the starburst galaxies M 82, NGC 253, and NGC 1808 from the ISOCAM instrument on board the Infrared Space Observatory . The mid-infrared spectra of the three galaxies are very similar in terms of features present. The $\lambda \ga 11~\mathrm{\mu m}$ continuum attributed to very small dust grains (VSGs) exhibits a large spread in intensity relative to the short-wavelength emission. We find that the 15$\,\mu$m dust continuum flux density correlates well with the fine-structure [$\ion{Ar}{ii}$] 6.99$\,\mu$m line flux and thus provides a good quantitative indicator of the level of star formation activity. By contrast, the $\lambda = 5$–$11~\mathrm{\mu m}$ region dominated by emission from polycyclic aromatic hydrocarbons (PAHs) has a nearly invariant shape. Variations in the relative intensities of the PAH features are nevertheless observed, at the $20\%$–$100\%$ level. We illustrate extinction effects on the shape of the mid-infrared spectrum of obscured starbursts, emphasizing the differences depending on the applicable extinction law and the consequences for the interpretation of PAH ratios and extinction estimates. The relative spatial distributions of the PAH, VSG, and [$\ion{Ar}{ii}$] 6.99$\,\mu$m emission between the three galaxies exhibit remarkable differences. The $\la$ $1~\mathrm{kpc}$ size of the mid-infrared source is much smaller than the optical extent of our sample galaxies and $70\%$–$100\%$ of the IRAS 12$\,\mu$m flux is recovered within the ISOCAM $\leq 1.5~\mathrm{arcmin^{2}}$ field of view, indicating that the nuclear starburst dominates the total mid-infrared emission while diffuse light from quiescent disk star formation contributes little.
Split-Awards and Disputes: An Experimental Study of a Strategic Model of Litigation

This paper studies experimentally the impact of the split-award statute, where the state takes a share of the plaintiff's punitive damage award, on litigation outcomes. Our findings indicate that dispute rates are significantly lower when bargaining is performed under the split-award institution. Defendants' litigation losses and plaintiffs' net compensation are significantly reduced by the split-award statute.
Teaching Rigid Body Mechanics Using Student-Created Virtual Environments

This paper describes a recent effort to use student- created virtual environments to teach rigid body dynamics to electrical and computer engineering senior-level undergraduates and first-year graduate students. Many of these students have no background in dynamics except for their freshman year physics course. The approach described here relies on students creating their own virtual environments, takes roughly four to five weeks of instruction, and therefore fits within the scope of other courses that may require electrical and computer engineering students to be familiar with dynamics. The background required only consists of basic linear algebra and ordinary differential equations. By the end of the pilot class, the majority of students were able to expertly model and animate high degree-of-freedom systems, such as slip-steered vehicles, helicopters, submarines, balancing unicycles, motorcycles, and puppets. A core component of the learning philosophy is that by providing students with a venue for creating their own virtual labs, they are able to promote their own learning. This paper summarizes the basic material presented to students, some of the virtual environments they chose to implement with only minimal guidance, and three instruments used to assess the effectiveness of the class architecture.
A 25.6 dBm wireless transmitter using RF-PWM with carrier switching in 130-nm CMOS

A wireless transmitter using RF pulse-width-modulation (PWM) with carrier switching is introduced. The proposed approach overcomes the dynamic range limitation of PWM at radio frequencies by utilizing carrier switching between fundamental and half-fundamental frequencies, depending on the signal level to be transmitted. This allows for transmission of signals with large peak-to-average power ratio (PAPR) such as OFDM. The efficiency is also improved in the power back-off region due to reduced switching losses in the half-fundamental mode. The transmitter has been implemented in a 130-nm CMOS process. The measured peak output power and power-added-efficiency (PAE) are 25.6 dBm and 34%, respectively. While driving 802.11g 64-QAM OFDM signals, the average output power is 18.3 dBm and the PAE is 16% with an EVM of -25.5 dB.
SCE: A Fully Integrated Software Tool for Beowulf Cluster System

One of the problems with the wide adoption of clusters for mainstream high performance computing is the difficulty in building and managing the system. There are many efforts in solving this problem by building fu lly automated, integrated software distribution from several open source software. However, these sets of software come from many sources and never been designed to work together as a truly integrated system. So, some problem is still remaining unsolved. With the experiences and tools developed to build many clusters on our site, we decided to build an integrate software tool that is easy to use for cluster user community. This software tool, called SCE (Scalable Computing Environment), consists of a cluster builder tool, complex system management tool (SCMS), scalable real-time monitoring, web base monitoring software (KCAP), parallel Unix command, and batch scheduler (SQMS). This software run on top of our cluster middleware that provides cluster wide process control and many services. MPICH are also included. SCE are truly integrated since our group builds all tool but MPICH. SCE also provides more than 30 APIs to access system resources information, control remote process execution, ensemble management and more. These APIs and the interaction among software components allow user to extends and enhance SCE in many ways. To make things easy, the installation and configuration in SCE are fully automated completely by GUI. This paper will discuss the current SCE design, implementation, and experiences. SCE is expected to be available as a developer version in June.
Time-variant modeling for general surface appearance

Describing time-variant appearance of object surface is still an open problem. With intricate environmental factors and different material characteristics over time, no researcher did tackle the principal problem: how to formulate time-variant change on general surface appearance? In this paper, we attempt to solve this challenging issue. Using multilinear algebra representation, we propose a novel appearance model and characterize the surface-specific and time-variant properties. When given an unknown sample, we propose a robust method to estimate its aging degree. In addition, we also propose an approach to synthesize its realistic appearance changes even when the material of this given sample does not exist in our database. Experimental results demonstrate the feasibility and effectiveness of our proposed approach. To the best of our knowledge, this challenging issue is first explored in image processing applications.
Smart Eyewear for Interaction and Activity Recognition

vice class with a lot of possibilities for user interac- tion design and unobtrusive activity tracking. In this paper we show applications using an early prototype of J! NS MEME, smart glasses with integrated electrodes to detect eye movements (Electrooculography, EOG) and motion sensors (accelerometer and gyroscope) to monitor head motions. We present several demonstrations: We show a simple eye movement visualization, detecting left/right eye motion and blink. Additionally, users can play a game, "Blinky Bird". They need to help a bird avoid obstacles using eye movements. We implemented online detection of reading and talking behavior using a combination of blink, eye movement and head motion. We can give people a long term view of their reading, talking, and also walking activity over the day.
BEwT-E for TAC 2009's AESOP Task

This paper describes BEwT-E (Basic Elements with Transformations for Evaluation), an automatic system for summarization evaluation. BEwT-E is a newer, more sophisticated implementation of the BE framework that uses transformations to match BEs (minimal-length syntactically well-formed units) that are semantically similar but are lexically and/or syntactically different. We present BEwTE's results on DUC and TAC datasets from 2005 to 2009 and are pleased to report that, of the systems that participated in AESOP, BEwT-E was one of the strongest performers, achieving the best performance using the Spearman metric when evaluated on the TAC 2009 update summaries.
A Note on Conjugate Natural Gradient Training of Multilayer Perceptrons

Natural gradient has been shown to greatly accelerate on-line multilayer perceptron (MLP) training. It also improves standard batch gradient descent, as it gives a Gauss-Newton approximation to quasi-Newton mean square error minimization, but now it should be slower than other superlinear minimization methods, such as the full Gaussian-quasi Newton method or the less complex but equally effective conjugate gradient descent method. In this work we shall investigate how to use natural gradients in a conjugate gradient setting, showing numerically that when applied to batch MLP learning, they can lead to faster convergence to better minimae than what is achieved by standard euclidean conjugate gradient descent.