Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Other Learner Corpora in the 2013 NLI Shared Task

Our efforts in the 2013 NLI shared task focused on the potential benefits of external corpora. We show that including training data from multiple corpora is highly effective at robust, cross-corpus NLI (i.e. open-training task 1), particularly when some form of domain adaptation is also applied. This method can also be used to boost performance even when training data from the same corpus is available (i.e. open-training task 2). However, in the closed-training task, despite testing a number of new features, we did not see much improvement on a simple model based on earlier work.
Distributed Local Search for Minimizing Envy

The allocation of indivisible resources to multiple agents typically generate envy among the agents. An Envy Free allocation may not exist in general and one can search for a minimal envy allocation. The search problem of minimizing envy for indivisible resource allocation is presented and a negotiation based transfer algorithm for solving it is proposed. The proposed algorithm performs a distributed any time local search for minimal envy solutions. The algorithm is composed of two phases. One phase performs hill climbing by the transfer of a single good among agents. The other phase of search uses elimination of open-end envy cycles, thereby utilizing the transfer of whole bundles. An extensive experimental evaluation of the proposed algorithm demonstrates the advantage of using the combined two phase algorithm.
Computational Modeling and Simulation of Biomolecular Motors

Molecular motors can be considered as biological molecular devices that are indispensable agents or machines for movement in living organisms. The most common motor proteins are Myosin, Kinesin and Dynein which are responsible for nanoscale cellular and molecular movement. In this work, the above mentioned protein molecules have been subjected to structural and sequence analysis, modeling and molecular dynamics simulation to study their properties and control aspects. Structural and sequence studies, interactional analysis and thermodynamic characterization effectively support the possibility for designing of biomolecular systems with these molecular motors as the source of driving force. Most of these protein molecules are found to be thermodynamically stable keeping active sites for interaction with ligands. It was also found that most of the protein molecules from the kinesin family possessed an appreciably high stability even after the temperature evolution of the molecule. This suggests the possibility for designing kinesin-based biomolecular systems.
Pseudobattering in Vietnamese children.

Until recently the presence of linear bruising on children in America was synonymous with child abuse.1 With the large influx of Vietnamese children, physicians should be aware of the practice of coin-rubbing.2 While providing medical care for Vietnamese children at Fort Indiantown Gap, Pennsylvania, we commonly saw petechiae and frank purpura of the chest and back. These lesions were often linear and resembled trauma. Indeed, we received one report of alleged trauma from an outside physician who was not familiar with the condition. The lay practice of Cäo Gió is quite commonly used among the Vietnamese for several symptoms including fever, chills, and headaches.
High-speed arithmetic coder/decoder architectures

The authors combine the techniques of interval tree search, look-ahead and redundant arithmetic to design high-speed architectures for arithmetic decoders. The decoder can be modeled as a FSM (finite state machine), enabling the application of the look-ahead technique to achieve higher speeds. The look-ahead approach leads to slight degradation in performance (in terms of the adder/subtractor delay in the coder/decoder due to increased word lengths). The performance of the decoder is improved by using redundant arithmetic. The tree search method combined with redundant arithmetic and look-ahead leads to desired speedups without any degradation in performance. <<ETX>>
Memory States and Transitions between Them in Attractor Neural Networks

Human memory is capable of retrieving similar memories to a just retrieved one. This associative ability is at the base of our everyday processing of information. Current models of memory have not been able to underpin the mechanism that the brain could use in order to actively exploit similarities between memories. The current idea is that to induce transitions in attractor neural networks, it is necessary to extinguish the current memory. We introduce a novel mechanism capable of inducing transitions between memories where similarities between memories are actively exploited by the neural dynamics to retrieve a new memory. Populations of neurons that are selective for multiple memories play a crucial role in this mechanism by becoming attractors on their own. The mechanism is based on the ability of the neural network to control the excitation-inhibition balance.
Crossing Borders

Abstract This study explores how interracial couples experience their life together and negotiate race and gender in their relationships. Ten black-white couples were interviewed individually and conjointly and the descriptive data was analyzed using the method of constant comparison. Results reflect the ways in which interracial couples struggle to employ, resist, and transform the discourse of homogamy in their relationship. Black spouses compared to white spouses demonstrated a greater awareness of and sensitivity to social resistance to the constitution of their relationship, and black spouses' familial and personal histories were sometimes relegated to silence in the couple relationship. Implications for family therapists working with interracial couples are discussed.
Current and Emerging Therapeutic Regimens for Patients with Chronic Hepatitis C Infection

With 5.2 million people living with Hepatitis C, it is the most common blood-borne infection in the United States. Untreated chronic HCV infection may result in adverse consequences such as cirrhosis, portal hypertension, hepatic failure and hepatocellular carcinoma. Previously approved treatments include Pegylated-interferon alpha-2a/2b plus ribavirin, Boceprevir and Telaprevir. Recently approved medications include Sofosbuvir (SOF), Simeprevir (SMV), Ledispavir-Sofosbuvir (Harvoni®) and Ombitasvir-paritaprevir-ritonavir with dasabuvir tablets (Viekira Pak). Here we review the literature describing the current and emerging therapies for chronic hepatitis C.
A Dynamic Subspace Method for Hyperspectral Image Classification

Many studies have demonstrated that multiple classifier systems, such as the random subspace method (RSM), obtain more outstanding and robust results than a single classifier on extensive pattern recognition issues. In this paper, we propose a novel subspace selection mechanism, named the dynamic subspace method (DSM), to improve RSM on automatically determining dimensionality and selecting component dimensions for diverse subspaces. Two importance distributions are proposed to impose on the process of constructing ensemble classifiers. One is the distribution of subspace dimensionality, and the other is the distribution of band weights. Based on the two distributions, DSM becomes an automatic, dynamic, and adaptive ensemble. The real data experimental results show that the proposed DSM obtains sound performances than RSM, and that the classification maps remarkably produce fewer speckles.
Exploring social interaction between robots and people

Robots are rapidly advancing toward becoming autonomous and skilled entities in a wide range of environments, and it is likely that more and more people will soon be interacting with robots in their everyday lives. As this happens, we believe that it is crucial that robots are designed to be easy to use and understand, reducing the requirement for people and environments to adapt to the robot. Emerging research in Human-Robot Interaction (HRI) suggests that people have a strong natural tendency to treat robots as social entities, anthropomorphizing, zoomorphizing, and generally attributing them with social characteristics and roles. Our approach to HRI is to explicitly focus on the social layers of interaction, building robotic interfaces that use people’s existing skill sets, and that explicitly attempt to integrate into familiar social structures. We refer to this approach of directly considering HRI in the context of the social human world as social HRI. The field of social HRI is only just emerging: there is little general discussion which explains why social HRI is important or what exactly social HRI means, there is no methodology for approaching the specific consideration of designing and implementing social HRI interfaces, and there is no structured methodology for evaluating and studying social HRI. There are few social HRI interface designs and implementations—those that focus on social interaction between people and robots—and the scope of social HRI interaction possibilities is still relatively unexplored. In this dissertation we present what we believe is the first thorough exploration of the theory, design, implementation, and evaluation of social HRI. We present a detailed analysis of social HRI, drawing particularly from selected works in social psychology and philosophy, and compose a social HRI-targeted theory that addresses why people tend toward social interaction with robots, how robots can leverage this, and what the implications are for both users and designers. We present a set of social HRI interfaces we designed, implemented and evaluated as a means to demonstrate and reflect on the practical and technical feasibility of applying social HRI principles to robot interface designs. We present the results from several extensive user studies, which we conducted as a means to learn from our interfaces, and to test, reflect on and further develop our social HRI theories. Finally, we distill our overall efforts into a set of some of the very first social HRI-specific design heuristics. Overall, our work highlights the importance of considering the broad landscape of social interaction between people and robots, and the usefulness of explicitly considering social aspects for robotic interaction design. We hope that by establishing the foundational social HRI groundwork, this dissertation will lead to and support continuing development of social HRI theory and new social HRI interface designs as this emerging domain evolves and grows.
NFYA1 Is Involved in Regulation of Postgermination Growth Arrest Under Salt Stress in Arabidopsis

The nuclear factor Y (NF-Y), which is a ubiquitous transcription factor found in eukaryotes, is composed of three distinct subunits, namely, NF-YA, NF-YB, and NF-YC. Here, we firstly characterized the detailed function of the Arabidopsis NFYA1 factor. It is found that the 35S::AtNFYA1-overexpressed lines were hypersensitive to salt stress and Abscisic acid (ABA) during the early-postgermination growth stages. The transgenic lines exhibited a severe postgermination growth arrest compared with the wild-type (WT) under salt stress and ABA treatment. Interestingly, sodium tungstate, which is an ABA synthesis inhibitor, restored the salt-sensitive phenotype of the 35S::AtNFYA1 lines. Results of the qRT-PCR analysis showed that the mRNA levels of ABI3 and ABI5, as well as their downstream genes AtEM1 and AtEM6, were more greatly upregulated under salt stress during seed germination in the transgenic lines compared with those in WT. On the other hand, the NFYA1-RNAi lines were found to be insensitive to salt stress and exhibited decreased levels of ABI3, ABI5, EM1, and EM6 transcripts. Our results provide clear evidence supporting a role of AtNFYA1 in regulating postgermination growth arrest under salt stress.
An explorative comparison of magic lens and personal projection for interacting with smart objects

One shortcoming of self-describing smart objects augmented with digital resources is the limitation of output modalities due to their long established physical appearances. To overcome this drawback intangible representations e.g., sound, video projection etc. are usually coupled with the tangible representations of smart objects that enable access and interaction with their value added features. In this paper, we explore two mobile interaction techniques that associate such intangible representation to smart objects using a pico projector augmented camera phone. The first technique utilizes a Magic Lens metaphor applying mobile augmented reality (contextual information is overlaid while looking at a smart object through camera) to uncover and interact with smart objects. The second technique, Personal Projection follows similar mechanisms in discovery and interaction, except information is projected onto the nearest surface. We report the implementation of these two techniques and a comparative qualitative study with three prototype smart object applications. The findings give us deeper insights on the positive and negative aspects of these two techniques and open up a range of stimulating research issues that we discuss in the paper.
Exploring differences in adiposity in two U.S. Hispanic populations of Mexican origin using social, behavioral, physiologic and genetic markers: the IRAS Family Study.

OBJECTIVE The census classification of Hispanic origin is used in epidemiological studies to group individuals, even though there is geographical, cultural, and genetic diversity within Hispanic Americans of purportedly similar backgrounds. We observed differences in our measures of adiposity between our two Mexican American populations, and examined whether these differences were attributed to social, behavioral, physiologic or genetic differences between the two populations. RESEARCH DESIGN AND METHODS In the IRAS Family Study, we examined 478 Hispanics from San Antonio, Texas and 447 Hispanics from the San Luis Valley, Colorado. Associations with body mass index (BMI), visceral adipose tissue area (VAT), and subcutaneous adipose tissue area (SAT) using social, behavioral, physiologic and genetic variables were examined. RESULTS Hispanics of Mexican origin in our clinic population in San Antonio had significantly higher mean BMI (31.09 vs. 28.35 kg/m2), VAT (126.3 vs. 105.5 cm2), and SAT (391.6 vs. 336.9 cm2), than Hispanics of Mexican origin in the San Luis Valley. The amount of variation in adiposity explained by clinic population was 4.5% for BMI, 2.8% for VAT, and 2.7% for SAT. After adjustment, clinic population was no longer associated with VAT and SAT, but remained associated with BMI, although the amount of variation explained by population was substantially less (1.0% for BMI). CONCLUSION Adiposity differences within this population of Mexican origin can be largely explained by social, behavioral, physiologic and genetic differences.
An active charge-cancellation system for switched-capacitor sensor interface circuits

Interface circuits determine the performance of microsensors in growing automotive, medical, and process control applications. Currently available interface systems implement a capacitive measurement bridge in bipolar technology. Continued expansion of MEMS applications requires development of enhanced resolution interfaces in low-cost digital CMOS technology with switched capacitor (SC) methods. The active charge cancellation system (ACCS), an interface circuit architecture implemented in submicron CMOS, uses a feedback to directly sense and cancel the charge injected by MOSFET switch at the amplifier input. Unlike conventional methods that rely on component matching for charge injection compensation, the ACCS employs feedback compensation to provide more than two orders of magnitude reduction in charge injection error without requirement on component matching.
Multi-Input Sliding Mode Control of Nonlinear Uncertain Non-Affine Systems With Mono-Directional Actuation

In this paper the multi-input Sliding Mode control of nonlinear uncertain non-affine systems with mono-directional actuators is considered. The geometric properties of the regular simplices of vectors are exploited by the mono-directional actuation system. The proposed full-state feedback control method introduces integrators in the input channel and suitably modifies the sliding output to be steered to zero. The resulting high frequency gain matrix (HFGM), which is the matrix multiplying the control vector, turns out to be affected by time and state dependent uncertainties. An effective use of the integral Sliding Mode method in connection with a non-conventional simplex based switching logic is introduced. The proposed simplex control procedure is adequately designed to avoid any possible unbounded increment of the control actions despite the presence of integrators in the input channel and the exploitation of mono-directional devices.
Decentralizing Policy-Hiding Attribute-Based Encryption

Attribute-based encryption (ABE) enables limiting access to encrypted data to users who possess certain attributes. Different aspects of ABE have been studied, such as the multi-authority setting (MA-ABE), and policy hiding, meaning the access policy is unknown to unauthorized parties, as in predicate encryption (PE). However, no practical scheme so far provided both properties, which are often desirable in real-world applications: supporting decentralization, while hiding the access policy. We present the first practical decentralized attribute-based encryption scheme which is policy-hiding. Our construction is based on a decentralized inner-product predicate encryption scheme, introduced in this paper, which hides the encryption policy. It results in an ABE scheme supporting conjunctions, disjunctions and threshold policies, that protects the access policy from parties that are not authorized to decrypt the content. Further, we address the issue of receiver privacy. By using our scheme in combination with vector commitments, we hide the overall set of attributes possessed by the receiver from individual authorities, only revealing the attribute that the authority is controlling. Finally, we propose randomizing-polynomial encodings that immunize the scheme in the presence of corrupt authorities.
ERUPT: Energy-efficient trustworthy provenance trees for wireless sensor networks

Sensor nodes are inherently unreliable and prone to hardware or software faults. Thus, they may report untrustworthy or inconsistent data. Assessing the trustworthiness of sensor data items can allow reliable sensing or monitoring of physical phenomena. A provenance-based trust framework can evaluate the trustworthiness of data items and sensor nodes based on the intuition that two data items with similar data values but with different provenance (i.e., forwarding path) can be considered more trustworthy. Forwarding paths of data items generated from redundantly deployed sensors should consist of trustworthy nodes and remain dissimilar. Unfortunately, operating many sensors with dissimilar paths consumes significant energy. In this paper, we formulate an optimization problem to identify a set of sensor nodes and their corresponding paths toward the base station that achieve a certain trustworthiness threshold, while keeping the energy consumption of the network minimal. We prove the NP-hardness of this problem and propose ERUPT, a simulated annealing solution. Testbed and simulation results show that ERUPT achieves high trustworthiness, while reducing total energy consumption by 32-50% with respect to current approaches.
Constructing and Evaluating Bipolar Weighted Argumentation Frameworks for Online Debating Systems

Discussions on social Web platforms carry a lot of information which is more and more difficult to analyze. Given a virtual community of users that discuss a particular topic of interest, an important task is to extract a model of the whole debate in order to automatically evaluate what are the most reliable claims. This paper proposes to approach this task using abstract argumentation, and define a new argument system, called Bipolar Weighted Argumentation Framework. It is able to capture all the useful information from a discussion thread, including the strength of positive (i.e., supports) and negative (i.e., attacks) relations between arguments. It also provides a way to assess an acceptability degree for each argument by means of the strength propagation of indirect relations ending to it, and a strategy to build such a framework from an online debate with a hierarchical structure. A model obtained from a real life discussion (a Reddit thread) is discussed and qualitatively evaluated.
FPGA based architecture for real-time SAR processing with integrated motion compensation

In this paper, an FPGA based hardware architecture for airborne real-time SAR image generation with integrated first-order motion compensation (MoCom) is presented. By sharing the same FPGA resources for image generation and correction of highly squinted flight path deviations, only marginal overhead in terms of additional hardware resources is required when compared to an implementation without resource sharing. The proposed architecture has been implemented and evaluated on a Xilinx Virtex-6 ML-605 Evaluation Kit for different flight path deviation and squint parameter settings. An average throughput rate of 25 MSamples/s (32-bit/sample) is reached while the FPGA resource allocation does not exceed 50% of the LUT slices (logic), 45% of the BRAM36 (memory) and less than 8% of the DSP48 slices.
A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.