Miracle-dz/UniFAR-FTUs huggingface dataset:
Credit assignment in movement-dependent reinforcement learning

Significance Thorndike's Law of Effect states that when an action leads to a desirable outcome, that action is likely to be repeated. However, when an action is not rewarded, the brain must solve a credit assignment problem: Was the lack of reward attributable to a bad decision or poor action execution? In a series of experiments, we find that salient motor error signals modulate biases in a simple decision-making task. This effect is independent of the participant’s sense of control, suggesting that the error information impacts behavior in an implicit and automatic manner. We describe computational models of reinforcement learning in which execution error signals influence, or gate, the updating of value representations, providing a novel solution to the credit assignment problem. When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the key press condition, participants exhibited a strong risk aversion bias; strikingly, this bias reversed in the reaching condition. This result can be explained by a reinforcement model wherein movement errors influence decision-making, either by gating reward prediction errors or by modifying an implicit representation of motor competence. Two further experiments support the gating hypothesis. First, we used a condition in which we provided visual cues indicative of movement errors but informed the participants that trial outcomes were independent of their actual movements. The main result was replicated, indicating that the gating process is independent of participants’ explicit sense of control. Second, individuals with cerebellar degeneration failed to modulate their behavior between the key press and reach conditions, providing converging evidence of an implicit influence of movement error signals on reinforcement learning. These results provide a mechanistically tractable solution to the credit assignment problem.
Automatic inference of cross-modal nonverbal interactions in multiparty conversations: "who responds to whom, when, and how?" from gaze, head gestures, and utterances

A novel probabilistic framework is proposed for analyzing cross-modal nonverbal interactions in multiparty face-to-face conversations. The goal is to determine "who responds to whom, when, and how" from multimodal cues including gaze, head gestures, and utterances. We formulate this problem as the probabilistic inference of the causal relationship among participants' behaviors involving head gestures and utterances. To solve this problem, this paper proposes a hierarchical probabilistic model; the structures of interactions are probabilistically determined from high-level conversation regimes (such as monologue or dialogue) and gaze directions. Based on the model, the interaction structures, gaze, and conversation regimes, are simultaneously inferred from observed head motion and utterances, using a Markov chain Monte Carlo method. The head gestures, including nodding, shaking and tilt, are recognized with a novel Wavelet-based technique from magnetic sensor signals. The utterances are detected using data captured by lapel microphones. Experiments on four-person conversations confirm the effectiveness of the framework in discovering interactions such as question-and-answer and addressing behavior followed by back-channel responses.
“An Unusual Urological Tumour”: Above the Collar and below the Belt

Bladder lymphomas are rarely primary tumours and more commonly associated with systemic lymphoma, either as nonlocalised bladder lymphoma or as secondary bladder lymphoma. Primary bladder lymphomas (PBL) tend to be low-grade mucosa-associated lymphoid tissue (MALT) type, contrasting with diffuse large cell or follicular centre cell types more commonly seen in secondary bladder lymphoma. Bladder involvement by systemic lymphoma infers poor prognosis and patients often have no localising symptoms (typically a postmortem diagnosis). Other treatments are preferred over surgery for all bladder lymphomas, except where diagnosis is uncertain or for relief of irritative bladder symptoms. We describe a unique case of systemic high-grade B-cell lymphoma with simultaneous cutaneous renal and bladder lesions at presentation.
Parallel Hierarchical Matrices with Adaptive Cross Approximation on Symmetric Multiprocessing Clusters

: We discuss a scheme for hierarchical matrices with adaptive cross approximation on symmetric multipro-cessing clusters. We propose a set of parallel algorithms that are applicable to hierarchical matrices. The proposed algorithms are implemented using the ﬂat-MPI and hybrid MPI + OpenMP programming models. The performance of these implementations is evaluated using an electric ﬁeld analysis computed on two symmetric multiprocessing cluster systems. Although the ﬂat-MPI version gives better parallel scalability when constructing hierarchical matrices, the speed-up reaches a limit in the hierarchical matrix-vector multiplication. We succeeded in developing a hybrid MPI + OpenMP version to improve the parallel scalability. In numerical experiments, the hybrid version exhibits a better parallel speed-up for the hierarchical matrix-vector multiplication up to 256 cores.
Data Programming: Creating Large Training Sets, Quickly

Large labeled training sets are the critical building blocks of supervised learning methods and are key enablers of deep learning techniques. For some applications, creating labeled training sets is the most time-consuming and expensive part of applying machine learning. We therefore propose a paradigm for the programmatic creation of training sets called data programming in which users express weak supervision strategies or domain heuristics as labeling functions, which are programs that label subsets of the data, but that are noisy and may conflict. We show that by explicitly representing this training set labeling process as a generative model, we can "denoise" the generated training set, and establish theoretically that we can recover the parameters of these generative models in a handful of settings. We then show how to modify a discriminative loss function to make it noise-aware, and demonstrate our method over a range of discriminative models including logistic regression and LSTMs. Experimentally, on the 2014 TAC-KBP Slot Filling challenge, we show that data programming would have led to a new winning score, and also show that applying data programming to an LSTM model leads to a TAC-KBP score almost 6 F1 points over a state-of-the-art LSTM baseline (and into second place in the competition). Additionally, in initial user studies we observed that data programming may be an easier way for non-experts to create machine learning models when training data is limited or unavailable.
Odour intensity learning in fruit flies

Animals' behaviour towards odours depends on both odour quality and odour intensity. While neuronal coding of odour quality is fairly well studied, how odour intensity is treated by olfactory systems is less clear. Here we study odour intensity processing at the behavioural level, using the fruit fly Drosophila melanogaster. We trained flies by pairing a MEDIUM intensity of an odour with electric shock, and then, at a following test phase, measured flies' conditioned avoidance of either this previously trained MEDIUM intensity or a LOWer or a HIGHer intensity. With respect to 3-octanol, n-amylacetate and 4-methylcyclohexanol, we found that conditioned avoidance is strongest when training and test intensities match, speaking for intensity-specific memories. With respect to a fourth odour, benzaldehyde, on the other hand, we found no such intensity specificity. These results form the basis for further studies of odour intensity processing at the behavioural, neuronal and molecular level.
In-Treatment Resolution or Absence of Electrocardiographic Left Ventricular Hypertrophy Is Associated With Decreased Incidence of New-Onset Diabetes Mellitus in Hypertensive Patients: The Losartan Intervention for Endpoint Reduction in Hypertension (LIFE) Study

Treatment of hypertensive patients with electrocardiographic left ventricular hypertrophy with losartan-based therapy is associated with lower incidence of diabetes mellitus and greater regression of hypertrophy than atenolol-based therapy. However, whether in-treatment resolution or continued absence of electrocardiographic hypertrophy is independently associated with decreased incidence of diabetes is unclear. Electrocardiographic hypertrophy was evaluated over time in 7998 hypertensive patients without diabetes at baseline in the Losartan Intervention For Endpoint reduction in hypertension (LIFE) study who were treated with losartan- or atenolol-based regimens and followed with serial electrocardiograms and blood pressure determinations. Electrocardiographic hypertrophy was defined using gender-adjusted Cornell voltage-duration product criteria >2440 mm·ms. During mean follow-up of 4.6±1.2 years, diabetes developed in 562 patients (7.0%). In a Cox model adjusting for treatment assignment, in-treatment resolution or continued absence of Cornell product hypertrophy was associated with a 38% lower risk of new diabetes (HR 0.62, 95% CI 0.50 to 0.78). After adjusting for the association of new diabetes with prior antihypertensive treatment, baseline glucose, and Framingham risk score, baseline and in-treatment systolic and diastolic pressure, HDL, uric acid, and body mass index, and the decreased incidence associated with losartan-based therapy, in-treatment continued absence, or resolution of Cornell product hypertrophy remained associated with a 26% lower risk of new diabetes (HR 0.74, 95% CI 0.58 to 0.93). Thus, compared with presence of hypertrophy by Cornell product criteria during antihypertensive treatment, resolution or continued absence of Cornell product hypertrophy is associated with a lower incidence of diabetes, even after adjusting for the impact of treatment with losartan and other risk factors for diabetes.
MarioQA: Answering Questions by Watching Gameplay Videos

We present a framework to analyze various aspects of models for video question answering (VideoQA) using customizable synthetic datasets, which are constructed automatically from gameplay videos. Our work is motivated by the fact that existing models are often tested only on datasets that require excessively high-level reasoning or mostly contain instances accessible through single frame inferences. Hence, it is difficult to measure capacity and flexibility of trained models, and existing techniques often rely on adhoc implementations of deep neural networks without clear insight into datasets and models. We are particularly interested in understanding temporal relationships between video events to solve VideoQA problems; this is because reasoning temporal dependency is one of the most distinct components in videos from images. To address this objective, we automatically generate a customized synthetic VideoQA dataset using Super Mario Bros. gameplay videos so that it contains events with different levels of reasoning complexity. Using the dataset, we show that properly constructed datasets with events in various complexity levels are critical to learn effective models and improve overall performance.
Adaptive FEC-Based Error Control for Interactive Audio in the Internet

Excessive packet loss rates can dramatically decrease the audio quality perceived by users of Internet telephony applications. Recent results suggest that error control schemes using forward error correction (FEC) are good candidates for decreasing the impact of packet loss on audio quality. With FEC schemes, redundant information is transmitted along with the original information so that the lost original data can be recovered at least in part from the redundant information. Clearly, sending additional redundancy increases the probability of recovering lost packets, but it also increases the bandwidth requirements and thus the loss rate of the audio stream. This means that the FEC scheme must be coupled to a rate control scheme. Furthermore, the amount of redundant information used at any given point in time should also depend on the characteristics of the loss process at that time (it would make no sense to send much redundant information when the channel is loss free), on the end to end delay constraints (destination typically have to wait longer to decode the FEC as more FEC information is used), on the quality of the redundant information, etc. However, it is not clear how to choose the ”best” possible redundant information given all the constraints mentioned above. We address this issue in the paper, and illustrate our approach using a FEC scheme for packet audio recently standardized in the IETF. We find that the problem best redundant information can be expressed mathematically as a constrained optimization problem for which we give explicit solutions. We obtain from these solutions a simple algorithm with very interesting features: i) it optimizes a subjective measure of quality (such as the perceived audio quality at a destination) as opposed to a non subjective measure (such as the packet loss rate at a destination), ii) it incorporates the constraints of rate control and playout delay adjustment schemes, and iii) it adapts to varying (and estimated on line with RTCP) loss conditions in the network. We have been using the algorithm, together with a TCP-friendly rate control scheme, for a few months now and we have found it to provide very good audio quality even with high and varying loss rates. We present simulation and experimental results to illustrate its performance. Submitted to IEEE Infocom ’99.
UNITED STATES Nationa 1 Oceanic and AtDI)spheric Alilinistration National Weather Service ~

This document describes the development and operational performance of the statistical-dynamical NHC83 model. NHC83 was developed at the National Hurricane Center (NHC) in the early 1980 I S and introduced operationally for the 1983 Atlantic hurricane season. The model was developed in the "perfect-prog'I mode with principal predictors being deep-layer-mean geopotential heights as derived from u.s. National Meteorological Center (NMC) operational analyses for the years 1962-1982. In the operational mode, NHC83 derives these deeplayer-mean forecast geopotential heights (through 72 h) from the NMC Medium Range Forecast (MRF) model. Additional predictors are derived from the output of the NHC CUPER (CLImatology and PERsistence) model as well as from the current NMC initial analysis or a "first-guess" to the initial analysis. Based on five years of operational verification statistics, 1983-1987, NHC83 has outperformed other NHC track prediction models by a rather wide margin. In addition, the model has other utilitarian features such as being available to forecasters four times daily in ample time to meet operational advisory schedules. Also, output from the NHC83 model is available in a graphical format which portrays both the numerically forecast height fields through 72 h and the forecast tropical cyclone track. 1.0 INTRODUCTION 1.1 TROPICAL CYCLONE PREDICTION MODELS The National Hurricane Center (NHC) uses a number of computer models as objective guidance preparatory to the issuance of tropical cyclone advisories. The great majority of these models, including the NHC83 model, the focus of this paper, concern themselves with forecasts of tropical cyclone motion. Other models provide forecasts of tropical cyclone intensity while still others provide the forecaster with diagnostic information relative to the given forecast situation. Tropical cyclone prediction models are either statistical or dynamical and both types of modelst each having distinct spatialt temporal and utilitarian advantages and disadvantagest are in use at the major tropical cyclone forecast centers. Depending on the type of developmental data and how this information is processedt statistical models are classified as being ~1.2. &t CLIPER-class, statistical-synoptic or statistical-dynamical while the dynamical modelst depending on the basic physical assumptionst are classified as being baroclinic or barotropic. Further discussion of the models in use at the NHC is provided by Neumann and Pelissier (1981at 1981b). A more general discussion of tropical cyclone prediction models is provided by McBride and Holland (1987) and Elsberry et al. (1987). : I 1 Prepared for the National Hurricane Centert Coral Gablest FL 33146: Contract No. SO-DGNC-6-00209 -1I I , ,
Do Field Dependence-Independence Differences of Game Players Affect Performance and Behaviour in Cultural Heritage Games?

Stimulated by a large number of different theories on human cognitive processing, suggesting that individuals have different habitual approaches in retrieving, recalling, processing and storing information, this paper investigates the effect of field dependence/independence with regards to game players' performance in the context of a cultural heritage game. Thirty two participants took part in an in-lab study and were classified as field dependent or independent based on a cognitive style elicitation instrument. Quantitative analysis methods were used to examine gaming performance in terms of game completion time, information seeking and items collection. The results revealed statistically significant differences in task completion time and in crucial information retrieval situations. Findings are expected to provide useful insights for practitioners and researchers with the aim to design more user--centric cultural heritage games.
Nonlinear integral sliding mode fault tolerant longitudinal aircraft control

This paper presents a nonlinear fault tolerant scheme for longitudinal control of an aircraft. The proposed approach uses an integral sliding mode control allocation scheme which can be built around any existing controller. In nominal fault free conditions, only the baseline controller and the primary control surface associated with it will be active. When faults/failures occur in the control surfaces, the proposed sliding mode control allocation scheme becomes active to provide extra robustness, and to redistribute the control signals to the redundant secondary control surfaces. In this paper the baseline controller considered is an existing backstepping one from the literature, designed for flight path angle tracking based on the nonlinear equations of motion. The simulations on a high fidelity aircraft benchmark model show good results for nominal and fault/failure conditions even in the presence of unmodelled dynamics.
PLA2G6-associated Dystonia–Parkinsonism: Case Report and Literature Review

Background Phospholipase-associated neurodegeneration (PLAN) caused by PLA2G6 mutations is a recessively inherited disorder with three known phenotypes: the typical infantile onset neuroaxonal dystrophy (INAD); an atypical later onset form (atypical NAD); and the more recently recognized young-onset dystonia–parkinsonism (PLAN-DP). Case Report We report the clinical, radiological, and genetic findings of a young Pakistani male with PLAN-DP. We review 11 previously published case reports cited in PubMed, and summarize the demographic, clinical, genetic, and radiological data of the 23 patients described in those articles. Discussion PLAN-DP presents with diverse motor, autonomic, and neuropsychiatric features and should be considered in the differential diagnosis of patients with young-onset neurodegenerative disorders.
The selectivity of the Na+/K+-pump is controlled by binding site protonation and self-correcting occlusion

The Na+/K+-pump maintains the physiological K+ and Na+ electrochemical gradients across the cell membrane. It operates via an 'alternating-access' mechanism, making iterative transitions between inward-facing (E1) and outward-facing (E2) conformations. Although the general features of the transport cycle are known, the detailed physicochemical factors governing the binding site selectivity remain mysterious. Free energy molecular dynamics simulations show that the ion binding sites switch their binding specificity in E1 and E2. This is accompanied by small structural arrangements and changes in protonation states of the coordinating residues. Additional computations on structural models of the intermediate states along the conformational transition pathway reveal that the free energy barrier toward the occlusion step is considerably increased when the wrong type of ion is loaded into the binding pocket, prohibiting the pump cycle from proceeding forward. This self-correcting mechanism strengthens the overall transport selectivity and protects the stoichiometry of the pump cycle. DOI: http://dx.doi. org/10.7554/eLife.16616. 001
A Conversation Robot with Back-channel Feedback Function based on Linguistic and Nonlinguistic Information

A conversation robot which can generate a back-channel feedback appropriately to the user is developed. The contents of these feedbacks depend on the contents of the dialogue partner’s utterance, which are provided by the speech recognition. In order to determine the content of the feedback earlier than the end of the utterance, we used ﬁnite state transducer based speech recognizer which outputs the content of the feedback. And we used prosody information, especially the fundamental frequency(F0) and the power of the utterance, to extract the proper timing of the feedback. We implemented these modules and applied them to the spoken dialogue system on the humanoid robot ROBISUKE. Experimental results show the effectiveness of our methods.
Human-Robot Handshaking using Neural Oscillators

In this study we propose a framework using neural oscillators for human-robot physical interaction such as “handshaking”. Neural oscillators are used for synchronization and entrainment between human and robot motions. Passiveness of the handshake can be changed by adjusting strength of the synchronization. Joint torque information is taken as an input signal for the neural oscillators, and the neural oscillator generates the desired trajectory of a robot joint. This paper addresses a model structure of the neural oscillator for human-robot physical interaction. The computer simulations of handshaking show the synchronization and the entrainment. Also the experiments with a joint torque sensing robot arm show that a handshake between a robot and a human being is realized by the proposed method. Lastly the validity of the proposed method is examined by a psychological evaluation with a paired comparison method, and it is found that the proposed method is better than conventional impedance control in terms of “Flexible”, “Natural”, “Kind” and “Affinity”.