Miracle-dz/UniFAR-FTUs huggingface dataset:
The undecidability of second order linear logic without exponentials

Abstract Recently, Lincoln, Scedrov and Shankar showed that the multiplicative fragment of second order intuitionistic linear logic is undecidable, using an encoding of second order intuitionistic logic. Their argument applies to the multiplicative-additive fragment, but it does not work in the classical case, because second order classical logic is decidable. Here we show that the multiplicative-additive fragment of second order classical linear logic is also undecidable, using an encoding of two-counter machines originally due to Kanovich. The faithfulness of this encoding is proved by means of the phase semantics.
Dynamic Autonomy for Mobile Manipulation

Emergency response demands a very different kind of robotic solution than those created for known environments (e.g. factory robots) and well understood tasks (e.g. power plant maintenance). This paper discusses efforts undertaken by the Idaho National Laboratory (INL) to develop highly mobile, highly dexterous robots that can function autonomously or semi-autonomously as a human surrogate in critical emergency situations. This paper reports progress made on two projects pursued under the auspices of the INL mobile manipulation initiative. The first involves collaboration with NASA Johnson Space Center (JSC) to merge an autonomous mobile robot base running the INL Intelligence Kernel, a behavior based robot control architecture, with the NASA Robonaut torso. The Robonaut torso was originally developed for use on the International Space Station, but also has strong potential to be used across a variety of national security, homeland defense, energy and search and rescue applications. The second capability pursued under the INL mobile manipulation initiative involves merging autonomous reaching and grasping behaviors developed at the University of Texas with the INL Intelligence Kernel to carry out tasks such as autonomously opening doors and retrieving objects within cluttered indoor settings. The ability of these systems to exploit environments and tools designed for humans allow them to be used in emergency situations where there is no time to develop a niche-specific robot, such as time critical threats involving Chemical/Biological/Radiological Nuclear (CBRN) hazards.
Orthogonal multiple access over time- and frequency-selective channels

Suppression of multiuser interference (MUI) and mitigation of time- and frequency-selective (doubly selective) channel effects constitute major challenges in the design of third-generation wireless mobile systems. Relying on a basis expansion model (BEM) for doubly selective channels, we develop a channel-independent block spreading scheme that preserves mutual orthogonality among single-cell users at the receiver. This alleviates the need for complex multiuser detection, and enables separation of the desired user by a simple code-matched channel-independent block despreading scheme that is maximum-likelihood (ML) optimal under the BEM plus white Gaussian noise assumption on the channel. In addition, each user achieves the maximum delay-Doppler diversity for Gaussian distributed BEM coefficients. Issues like links with existing multiuser transceivers, existence, user efficiency, special cases, backward compatibility with direct-sequence code-division multiple access (DS-CDMA), and error control coding, are briefly discussed.
Is the Sum Greater than Its Parts? Reflections on the Agenda of Integrating Analyses of Cognition and Learning

This symposium springs from an ongoing effort to bring together contrasting methodological perspectives for the study of human knowing and learning. Specifically, we build bridges between two significant process-oriented approaches: Interaction Analysis (IA) and Knowledge Analysis (KA), to study how individual cognitive dynamics interacts with complex social dynamics. We demonstrate the kind of insights and outcomes of such integration, by zooming in, and explore two specific efforts to bridge KA and IA. Both focal pairs of analyses in this symposium make central use of the theoretical construct of coordination class, a theory is associated with KA usually used for analyzing the structure and dynamics of an individual conceptual system. Coordination class theory is used to extend an IA analysis in the first pair of analyses, and is elaborated on using IA methodology in the second pair. The presentations aim to stimulate discussions about the merits and constraints of such integrations.
The Use of Emotionally-ffocused Couples Therapy (EFT) for Survivors of Acquired Brain Injury With Social Cognition and Executive Functioning Impairments, and Their Partners: a Case Series Analysis

A breakdown of intimacy and familiarity in close romantic relationships is common and characteristic of life following acquired brain injury (ABI), yet is not commonly addressed in neuro-rehabilitation services. Recent conceptual, qualitative, and quantitative studies highlight the role of emotional and intentional misattunement in relationship breakdown and associated psychological distress of both partners, alongside the emotional withdrawal and/or critical responses of the non-injured partner. Emotionally-focused couples therapy (EFT) is an evidenced-based couples therapy that is widely used around the world for similar themes in couples’ relationships unaffected by brain injury. Its use in ABI has only been reported anecdotally to date. This paper presents four couples’ cases post-ABI, with both qualitative therapy process description and single case quantitative pre-post therapy comparison on a range of relationship and individual psychological distress measures. Every survivor of ABI was eighteen months post-injury or more, and identified to have an enduring mixture of social cognition and executive functioning impairments upon neuropsychological assessment, among other difficulties. The couples are presented as three therapeutic successes, contrasted with a case characterised by mixed outcomes. The applications, contributions, and limitations of EFT in brain injury services is considered.
A Distributed Beam-Forming Algorithm for Single Frequency Networks Supporting Broadcast and Multicast Applications

Single Frequency Networks (SFN) in combination with a multi-carrier transmission scheme such as OFDM are often proposed as a means to provide continuous coverage of broadcast applications over a large area. In this paper, we propose a distributed beam-forming algorithm that makes use of channel state information fed back by receivers to improve the performance of the weaker connections. The distributed nature of the proposed algorithm makes it easier to implement when compared to its centralized counterparts. Simulation studies show that the proposed algorithm results in a significant improvement in the performance of SFNs supporting broadcast or multicast applications.
Fixing the Locally Optimized RANSAC

The paper revisits the problem of local optimization for RANSAC. Improvements of the LO-RANSAC procedure are proposed: a use of truncated quadratic cost function, an introduction of a limit on the number of inliers used for the least squares computation and several implementation issues are addressed. The implementation is made publicly available. Extensive experiments demonstrate that the novel algorithm called LO + -RANSAC is (1) very stable (almost non-random in nature), (2) very precise in a broad range of con- ditions, (3) less sensitive to the choice of inlier-outlier threshold and (4) it offers a sig- nificantly better starting point for bundle adjustment than the Gold Standard method advocated in the Hartley-Zisserman book.
Internal noise reduction combining microphones and a piezoelectric device under blind condition

This paper introduces internal noise reduction combining microphones and a piezoelectric device attached to the internal noise source under blind condition. An acoustical array combining microphones and piezoelectric devices is an acoustical sensor fusion to reduce the internal noise coming from the inside of the system such as machines, vehicles or robots. It can reduce the internal noise effectively, while it is difficult to reduce the internal noise by employing the conventional microphone array and blind source separation (BSS) algorithms such as ICA or sparseness approach because the internal noise is extremely close to the microphone and not always stationary, statistically independent or sparse. However, when the acoustical array combining microphones and piezoelectric devices are utilized, it is necessary to estimate the gains of microphones and piezoelectric devices concerning the internal noise source in advance. Our aim is to simplify this process. In this paper, we formulate the problem and show the methodology of the proposed method. Experimental results are also demonstrated to confirm the effectiveness of the proposed method.
Finite Element Analysis of the Landau--de Gennes Minimization Problem for Liquid Crystals

This paper describes the Landau--de Gennes free-energy minimization problem for computing equilibrium configurations of the tensor order parameter field that characterizes the molecular orientational properties of liquid crystal materials. Analytical and numerical issues are addressed. Conditions guaranteeing well-posedness (existence, regularity) of the problem are given, as is a nonlinear finite element convergence analysis.
High-Frequency Distortion Analysis of Analog Integrated Circuits

An approach is presented for the analysis of the nonlinear behavior of analog integrated circuits. The approach is based on a variant of the Volterra series approach for frequency domain analysis of weakly nonlinear circuits with one input port, such as amplifiers, and with more than one input port, such as analog mixers and multipliers. By coupling numerical results with symbolic results, both obtained with this method, insight into the nonlinear operation of analog integrated circuits can be gained. For accurate distortion computations, the accuracy of the transistor models is critical. A MOS transistor model is discussed that allows us to explain the measured fourth-order nonlinear behavior of a 1 GHz CMOS upconverter. Further, the method is illustrated with several examples, including the analysis of an operational amplifier up to its gain-bandwidth product. This example has also been verified experimentally.
Whole-body cryostimulation as an effective way of reducing exercise-induced inflammation and blood cholesterol in young men

Inflammation may accompany obesity and a variety of diseases, or result from excessive exercise. The aim of this study was to investigate the anti-inflammatory effect of whole-body cryostimulation on the inflammatory response induced by eccentric exercise under laboratory conditions. The study also sought to establish if cold treatment changes the lipid profile and modifies energy expenditure in young people. Eighteen healthy and physically active, college-aged men volunteered to participate in the experiment. They were divided into two subgroups: CRYsubmitted to whole-body cryostimulation, and CONT- a control group. Both groups performed eccentric work to induce muscle damage. Blood samples were collected before and 24 h after the exercise. Over the five days that followed, the CRY group was exposed to a series of 10 sessions in a cryogenic chamber (twice a day, for 3 min, at a temperature of −110°C). After this period of rest, both groups repeated a similar eccentric work session, following the same schedule of blood collection. The perceived pain was noted 24h after each session of eccentric workout. A 30-minute step up/down work-out induced delayed-onset muscle soreness in both groups. The five-day recovery period accompanied by exposure to cold significantly enhanced the concentration of the anti-inflammatory cytokine IL-10. It also led to a pronounced reduction in levels of the pro-inflammatory cytokine IL-1β, and reduced muscle damage. The values for IL-10 before the second bout of eccentric exercise in the CRY group were 2.0-fold higher in comparison to baseline, whereas in the CONT group, the concentration remained unchanged. Furthermore, blood concentrations of the pro-inflammatory cytokine IL-1β fell significantly in the CRY group. The main finding of this study was that a series of 10 sessions of whole body cryostimulation significantly reduced the inflammatory response induced by eccentric exercise. The lipid profile was also improved, but there was no effect on energy expenditure during the exercise.
Quality Assessment of Software as a Service on Cloud Using Fuzzy Logic

Cloud computing is a business model which provides on demand services on the pay-per-use premise. Software as a Service (SaaS) is one of the delivery models for cloud computing, where software ownership by the SaaS provider is isolated from its use by the SaaS customer. The notion of quality is central to any service provision. Also, it is important to evaluate the quality of SaaS in order to be able to improve it. Traditional software engineering quality models are not effusively suitable for this purpose due to difference in the nature of software and service. In the past, a few approaches to service quality estimation have been proposed. Some of these approaches extend quality characteristics from existing quality models and even devise SaaS quality metrics, while others discuss quality around Service Level Agreement (SLA) and Quality of Service (QoS) parameters. In this paper, some representative quality factors have been identified by analyzing literature and a model based on fuzzy logic has been proposed to assess SaaS quality. Such a model of quality criteria may provide a ground for more comprehensive quality model which may assist a SaaS customer to choose a higher quality service from available services on cloud; the quality model may also serve as a guideline to SaaS provider to improve the quality of service provided.
Reconstruction of damaged spectrographic features for robust speech recognition

We present two missing-feature based algorithms that recover noise-corrupted regions of spectrographic representations of speech for noise-robust speech recognition. These algorithms modify the incoming feature vector without any changes to the speech recognition system, in contrast to previously-described approaches. The ﬁrst approach clusters the feature vectors representing clean speech. Missing data are recovered by estimating the spectral cluster in each analysis frame based on the uncorrupted feature values. The second approach uses MAP procedures to estimate the values of missing data elements based on their correlations with the features that are present. Both methods take into account bounds on the clean spectrogram implied by the noisy spectrogram. Large improvements in recognition accuracy are observed when these methods are used on speech corrupted by non-stationary noise when the locations of the corrupt regions of the spectrogram are known. We also present a new method of estimating the locations of corrupt regions in spectrograms that treats the problem of identifying these regions as one of Bayesian classiﬁcation. This method, when used along with the best method to reconstruct them, results in recognition accuracies comparable with the best previous data compensation algorithm on speech corrupted by white noise. It also provides signiﬁcant improvement on speech corrupted by music when the global SNR of the corrupted signal is known a priori .
Losing to Win: Reputation Management of Online Sellers

Reputation is generally considered an asset, especially in e-commerce markets. Any reputation system, however, elicits strategic responses from the sellers. Using panel data on a large random sample of online sellers from Chinaâ€™s largest e-commerce platform, Taobao.com, we study how reputation affects revenue, prices, transaction volume, and survival likelihood as well as how sellers manage their reputation. We find that seller reputation has a substantial positive impact on established sellers, but new sellers fail to reap such benefits. Pursuing the long-run returns to reputation, new sellers actively manage their reputation by engaging in costly activities such as sales and switching product categories. In this "losing to win" process, new sellers may have spent too much resource to survive to next stage. Our results provide empirical support for the theory of career concern and reputation dynamics.
Ventral Tegmental Dopamine Dysregulation Prevents Appetitive Memory Destabilization

Through the process of reconsolidation, memories can be updated to maintain their relevance. To reconsolidate, a memory must first be destabilized in a process that we have hypothesized is initiated by a prediction error signal. Here we demonstrate that dysregulation of ventral tegmental area (VTA) signaling, which is thought to mediate prediction errors, prevented the destabilization of an appetitive goal-tracking memory in rats. We additionally show that intra-VTA infusion of either the competitive NMDA antagonist AP5 or the noncompetitive NMDA antagonist MK-801 does not selectively disrupt reconsolidation, indicating that the VTA may not be an important neural locus of reconsolidation-related neural plasticity.
Enabling massively multi-player online gaming applications on a P2P architecture

Recent advances in Peer-to-Peer (P2P) technologies have enabled the use of P2P architectures for developing complex applications such as, Massively Multi-Player Online Games (MMOG). In this paper we address a challenging research problem related to P2P MMOGs; efficient entity maintenance and interaction. We have identified two opposing software engineering approaches to address this problem. The first approach assumes that the entire virtual world and the game logic are implemented using database techniques, e.g., with a distributed index over all the peers and the game semantics built into data query/update functions. The second approach is to separate the entities into completely independent processes, using agentoriented programming techniques. In our work, we propose a combination of these two approaches; the use of a distributed spatial index to facilitate the discovery and querying of relevant entities and an agent-based approach to facilitate real time interactions between the entities. We show the relevant factors for dynamic optimization and the use of a new software architecture with existing game libraries to implement the system.
iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression.
Uniqueness of solutions of stochastic differential equations

It follows from a theorem of Veretennikov [4] that (1) has a unique strong solution, i.e. there is a unique process x(t), adapted to the filtration of the Brownian motion, satisfying (1). Veretennikov in fact proved this for a more general equation. Here we consider a different question, posed by N. V. Krylov [2]: we choose a Brownian path W and ask whether (1) has a unique solution for that particular path. The main result of this paper is the following affirmative answer:
Eliminating Excessive Tariffs on Exports of Least Developed Countries

Although average oecd tariffs on imports from the least developed countries are very low; tariffs above 15 percent (peaks) have a disproportional effect on their exports. Products subject to tariff peaks tend to be heavily concentrated in agriculture and food products and labor-intensive sectors, such as apparel and footwear. Although the least developed countries benefit from preferential access, preferences tend to be smallest for tariff peak products. A major exception is the European Union, so that the recent European initiative to grant full duty-free and quota-free access for the least developed countries (the so-called Everything But Arms initiative) will result in only a small increase in their exports of tariff peak items (less than 1 percent of total exports). However, as preferences are less significant in other major oecd countries, a more general emulation of the European Union initiative would increase the least developed countries' total exports of peak products by US$2.5 billion (11 percent of total exports). Although almost half of this increase is at the expense of other developing country exports, this represents less than 0.05 percent of their total exports. This trade diversion can be avoided by reducing tariff peaks to a uniform 5 percent applied on a nondiscriminatory basis. However, such a reform would imply no gains for the least developed countries, suggesting that the globally welfare-superior policy of nondiscriminatory elimination of tariff peaks should be complemented by greater direct assistance to poor countries. Copyright 2002, Oxford University Press.
Altered neurotransmitter function in CO2-exposed stickleback (Gasterosteus aculeatus): a temperate model species for ocean acidification research

Behavioural changes in the stickleback caused by near-future CO2 levels can be restored by treatment with gabazine, revealing an involvement of the GABAA receptor ion. Importantly, these effects can be conveniently studied in the stickleback, with a sequenced and annotated genome and exceptionally well-characterized behaviour and physiology
A decoupled control method based on MIMO system for flexible manipulators with FS-SEA

A novel decoupled control method based on MIMO system is proposed for FS-SEA (force sourced series elastic actuator) flexible manipulators. The joint output angles of the flexible manipulator and the deformation angles of the flexible mechanisms are chosen as the state quantities of the system, and a new decoupled control law is designed, which makes the proposed method achieve high tracking accuracy and very strong disturbance rejection ability. The simulations are carried out to verify the control method proposed in this paper that is compared with DLR's control method proposed in 2011 and PD feedback computed torque method respectively. The comparison results illustrate that the control method proposed in this paper has an outstanding performance.