Miracle-dz/UniFAR-FTUs huggingface dataset:
Pycnodysostosis with Multi-Segmental Spinal Canal Stenosis due to Ossification of the Yellow Ligament

Pycnodysostosis is an autosomal recessive disorder characterized by osteosclerosis, small stature, acro-osteolysis of the distal phalanges, loss of the mandibular angle, separated cranial sutures with open fontanels, and frequent fractures. One identified cause of the disease is reduced activity of the cysteine protease cathepsin K. A 48-year-old woman with a history of frequent fractures presented with a severe gait disturbance. Radiography, computed tomography, magnetic resonance imaging, and gene analysis were performed. Physical examination revealed open fontanels, and radiographs showed increased bone density. DNA sequence analysis revealed a deletion mutation of the cathepsin K gene. We diagnosed pycnodysostosis based on these findings. The magnetic resonance and computed tomography images demonstrated multilevel spinal canal stenosis due to ossification of the yellow ligament. We performed a laminectomy, and the patient's neurological signs and symptoms improved. To our knowledge, this is the first case of pycnodysostosis with ossification of the yellow ligament.
Supervoxel using random walks

In this paper, we present a supervoxel generation algorithm based on partially absorbing random walks to get more accurate supervoxels in these regions. A novel spatial-temporal framework is introduced by making full use of the appearance features and motion cues, which effectively exploits the temporal consistency in the video sequence. Moreover, we build a new Laplacian optimization structure with two adjacent frames, which makes our approach to be a more efficient algorithm. Experimental results demonstrate that our method achieves better performance compared to the state-of-the-art supervoxel algorithms.
Biologically Plausible Neural Circuits for Realization of Maximum Operations

Abstract Object recognition in the visual cortex is based on a hierarchical architecture, in which specialized brainregions along the ventral pathway extract object features of increasing levels of complexity, accompaniedby greater invariance in stimulus size, position, and orientation. Recent theoretical studies postulate anon-linear pooling function such as the maximum (MAX) operation could be fundamental in achievingsuch invariance. In this paper, we are concernedwith neurally plausible mechanisms that may be involvedin realizing the MAX operation. Four canonical circuits are proposed, each based on neural mechanismsthat have been previously discussed in the context of cortical processing. Through simulations and math-ematical analysis, we examine the relative performance and robustness of these mechanisms. We deriveexperimentally veriﬁable predictions for each circuit and discuss their respective physiological consider-ations. This report describes research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciencesand in the Artiﬁcial Intelligence Laboratory at the Massachusetts Institute of Technology.This research is sponsored by a grant from the Ofﬁce of Naval Research under contract No. N00014-93-1-3085, Ofﬁce of Naval Researchunder contract No. N00014-95-1-0600, National Science Foundation under contract No. IIS-9800032, National Science Foundation under contractNo. DMS-9872936, National Science Foundation under Graduate Research Fellowship Program, Massachusetts Institute of Technology under theUROP program, and a grant to the Gatsby Computational Neuroscience Unit from the Gatsby Charitable Foundation.
A Stereo Vision-based Mixed Reality System with Natural Feature Point Tracking

This paper proposes a method to extend a registration range of a vision-based mixed reality system. We propose to use natural feature points contained in images captured by a pair of stereo cameras in conjunction with pre-defined fixed fiducial markers. The system also incorporates an inertial sensor to achieve a robust registration method which can handle user’s fast head rotation and movement. The system first uses pre-defined fiducial markers to estimate a projection matrix between real and virtual coordinate systems. At the same time, the system picks up and tracks a set of natural feature points from the initial image. As a user moves around in MR environment, the initial markers fall out from the camera frame and natural features are then used to recover a projection matrix. Experiments evaluating the feasibility of the method are carried out and show the potential benefits of the method.
Locally Weighted Least Squares Temporal Difference Learning

This paper introduces locally weighted temporal difference learning for evaluation of a class of policies whose value function is non- linear in the state. Least squares temporal difference learning is used for training local models according to a distance metric in state-space. Empirical evaluations are reported demonstrating learning performance on a number of strongly non-linear value functions, without the need for prior knowledge of features or a specific functional form.
Formal Verification of Self-Assembling Systems

This paper introduces the theory and practice of formal verification of self-assembling systems. We interpret a well-studied abstraction of nanomolecular self assembly, the Abstract Tile Assembly Model (aTAM), into Computation Tree Logic (CTL), a temporal logic often used in model checking. We then consider the class of "rectilinear" tile assembly systems. This class includes most aTAM systems studied in the theoretical literature, and all (algorithmic) DNA tile self-assembling systems that have been realized in laboratories to date. We present a polynomial-time algorithm that, given a tile assembly system T as input, either provides a counterexample to T's rectilinearity or verifies whether T has a unique terminal assembly. Using partial order reductions, the verification search space for this algorithm is reduced from exponential size to O(n^2), where n x n is the size of the assembly surface. That reduction is asymptotically the best possible. We report on experimental results obtained by translating tile assembly simulator files into a Petri net format manipulable by the SMART model checking engines devised by Ciardo et al. The model checker runs in O(|T| x n^4) time, where |T| is the number of tile types in tile assembly system T, and n x n is the surface size. Atypical for a model checking problem -- in which the practical limit usually is insufficient memory to store the state space -- the limit in this case was the amount of memory required to represent the rules of the model. (Storage of the state space and of the reachability graph were small by comparison.) We discuss how to overcome this obstacle by means of a front end tailored to the characteristics of self-assembly.
The devil is not only in the details: gist and detail elaboration in intoxicated witnesses’ reports of interpersonal violence

ABSTRACT The empirical base relating to alcohol’s effects on underlying memory mechanisms among witnesses is sparse. Therefore, the effect of alcohol intoxication on memory mechanisms was investigated, as well as how degree of intoxication and interview delay affected gist and detail elaboration in these witnesses’ reports. Participants (n = 136) were randomized to an alcohol group (men: 0.8 g/kg, women: 0.75 g/kg) (n = 70) or a control group (n = 66), given juice. After consumption, they witnessed an intimate partner violence-scenario, and performed tasks assessing memory mechanisms. Half of the intoxicated and sober groups were interviewed immediately. The remaining participants were interviewed one week later. Inter alia, intoxication decreased total gist recall and elaboration capacity. In general, high intoxication (BAC = 0.08–0.15) made witnesses report fewer gist categories, and also to elaborate them less, but there were differences in gist/detail elaboration between levels of intoxication due to emotional context. Less reported information among intoxicated witnesses was caused both by omitting parts of the scenario and to less detailed elaboration. Emotional context influenced reporting among intoxicated witnesses on a gist and detail level. However, intoxication had less impact on gist/detail-elaboration than did a one week delay before interview, suggesting that witnesses should be interviewed immediately, despite intoxication.
Document-specific context plsa language model for speech recognition

In this paper, we introduce a document-specific context probabilistic latent semantic analysis (DCPLSA) model for speech recognition. This is an extension of a CPLSA model [1] where the probability of word is conditioned only on topics. The CPLSA model uses the bigram counts that are the number of appearances of the bigrams in the corpus. These counts are the sum of the bigram counts in different documents where they could appear to describe different topics. We encounter this problem in the CPLSA model and introduce the document-specific CPLSA model (DCPLSA) where the probability of a word is conditioned on both topic and document. We carried out experiments on a continuous speech recognition (CSR) task using the Wall Street Journal (WSJ) corpus and have seen that the proposed DCPLSA approach yields significant reduction in both perplexity and word error rate (WER) measurements over the other approaches used in the literature.
Word Embedding and Topic Modeling Enhanced Multiple Features for Content Linking and Argument / Sentiment Labeling in Online Forums

Multiple grammatical and semantic features are adopted in content linking and argument/sentiment labeling for online forums in this paper. There are mainly two different methods for content linking. First, we utilize the deep feature obtained from Word Embedding Model in deep learning and compute sentence similarity. Second, we use multiple traditional features to locate candidate linking sentences, and then adopt a voting method to obtain the final result. LDA topic modeling is used to mine latent semantic feature and K-means clustering is implemented for argument labeling, while features from sentiment dictionaries and rule-based sentiment analysis are integrated for sentiment labeling. Experimental results have shown that our methods are valid.
USFD’s Phrase-level Quality Estimation Systems

We describe the submissions of the University of Sheffield (USFD) for the phraselevel Quality Estimation (QE) shared task of WMT16. We test two different approaches for phrase-level QE: (i) we enrich the provided set of baseline features with information about the context of the phrases, and (ii) we exploit predictions at other granularity levels (word and sentence). These approaches perform closely in terms of multiplication of F1-scores (primary evaluation metric), but are considerably different in terms of the F1scores for individual classes.
Channel capacity of magnetic induction based Wireless Underground Sensor Networks under practical constraints

Wireless Underground Sensor Networks (WUSNs) present a variety of new research challenges. Recently a magneto-inductive (MI) waveguide technique has been proposed to overcome the very harsh propagation conditions in WUSNs. In this approach, several resonant relay circuits are deployed between the two nodes to be connected. This technique allows for an extension of the transmission range, which can be quite limited, if relays are not deployed. In this paper, channel and noise models for MI-WUSNs using MI-waveguides are developed. Results of a numerical evaluation of the channel capacity under practical constraints are provided and the influence of the system parameters on the performance is discussed.
Evaluating working memory deficits on writing in youth with Autism Spectrum Disorder (ASD)

Few studies have researched writing difficulties in individuals with Autism Spectrum Disorder (ASD) and the factors responsible for such difficulties. The current study sought to examine writing difficulties in individuals with ASD and the contribution of working memory (WM) difficulties. The investigation consisted of five youth formally diagnosed with ASD (under DSM-IV-TR, higher functioning Autistic Disorder or Asperger’s Disorder), and five youth with no formal diagnosis. Participants completed a counterbalanced battery of tests that assessed their written expression and WM abilities. Due to challenges in recruiting enough participants for purposes of quantitative research, the study mainly used a case-study analysis. The study showed that participants with ASD (group with ASD) had more difficulty with writing and WM tasks than participates without ASD (traditionally developing [TD] group). Nonparametric analyses revealed that writing and WM were not related; however, these findings are cautionary due to very low participation numbers in the investigation. Case-study analysis showed that the group with ASD had underdeveloped writing skills notably in the areas of word count, vocabulary, spelling and grammar. Regarding WM abilities, the group with ASD showed variable patterns of difficulty; some had strengths in verbal WM while others did not. Unfortunately, the study could not determine if writing difficulties were specific due to WM or other causes, although it does provide useful information for further investigation. Additional studies investigating the relationship between writing and WM, particularly in individuals with ASD, are encouraged.
Brain dynamics of Arabic reading: a magnetoencephalographic study

Arabic writing differs greatly from western scripts. To evaluate the influence of written Arabic on the pattern of language-related brain activation, a group of native Arab speakers and a control group of native Spanish speakers were scanned with magnetoencephalography during a reading task. In both groups, brain activity was strongly left lateralized during the time window between 200 and 500 ms after stimulus onset. During late latencies (beyond 500 ms), however, the right and the left hemispheres reached a similar activation level in the Arabic but not in the Spanish group. This suggests a time-dependent role of both hemispheres during Arabic language reading.
Hip-muscle activation during the lunge, single-leg squat, and step-up-and-over exercises.

CONTEXT Functional exercises are often used in strengthening programs after lower extremity injury. Activation levels of the stabilizing hip muscles have not been documented. OBJECTIVE To document the progression of hip-muscle activation levels during 3 lower extremity functional exercises. DESIGN Cross-sectional. SETTING Laboratory. PARTICIPANTS 44 healthy individuals, 22 women and 22 men. INTERVENTION Subjects, in 1 testing session, completed 3 trials each of the lunge (LUN), single-leg squat (SLSQ), and step-up-and-over (SUO) exercise. MAIN OUTCOME MEASURES Root-mean-square muscle amplitude (% reference voluntary muscle contraction) was measured for 5 muscles during the 3 exercises: rectus femoris (RF), dominant and nondominant gluteus medius (GMed_D and GMed_ND), adductor longus (ADD), and gluteus maximus (GMX). RESULTS The RF, GMAX, and GMed_D were activated in a progression from least to greatest during the SUO, LUN, and SLSQ. The progression for the GMed_ND activation was from least to greatest during the SLSQ, SUO, and then LUN. Activation levels of the ADD showed no progression. CONCLUSION Progressive activation levels were documented for muscles acting on the hip joint during 3 functional lower extremity exercises. The authors recommend using this exercise progression when targeting the hip muscles during lower extremity strengthening.
National survey of colistin resistance among carbapenemase-producing Enterobacteriaceae and outbreak caused by colistin-resistant OXA-48-producing Klebsiella pneumoniae, France, 2014

From January 2014 to December 2014, 972 consecutive non-replicate carbapenemase-producing Enterobacteriaceae isolates from colonised or infected patients were collected at the Associated French National Reference Centre as part of the French national survey on antimicrobial resistance. It included 577 Klebsiella spp. (59%), 236 Escherichia coli (24%), 108 Enterobacter spp. (11%), 50 Citrobacter spp. (5%), and a single Salmonella spp. isolate (0.1%). Of 561 K. pneumoniae isolates, 35 were found to be resistant to colistin (6.2%). PFGE analysis revealed a clonal outbreak involving 15 K. pneumoniae isolates belonging to sequence type ST11, recovered in a single hospital in the Picardie region in northern France. Those clonally related isolates showed variable levels of resistance to colistin, ranging from 4 to 64 mg/L. They harboured the blaOXA-48 carbapenemase gene and the blaCTX-M-15 extended-spectrum beta-lactamase gene. Among the 91 Enterobacter cloacae isolates, seven were resistant to colistin and produced different types of carbapenemases. Surprisingly, none of the E. coli and Citrobacter spp. isolates showed resistance to colistin. This national survey including carbapenemase-producing isolates recovered in 2014 reported a high rate of colistin resistance in K. pneumoniae and E. cloacae (6.2% and 7.7%, respectively) in France.
Attentional functions in speech fluency disorders

This study focused on attentional functions in fluency disorders. Nine persons who stuttered, eight persons who cluttered, and nine fluent controls, executed a set of attention tasks while psychophysiological indices of activation (heart rate variability and skin conductance) were recorded. The results indicated that the stutter group had a significantly longer response time on the Posner Test of Covert Attention Shifts than the other two groups, and the effect was most obvious when the target appeared in the right visual field. There were no significant differences between groups in the physiological activation as measured by heart rate, skin conductance and heart rate variability. The present results support the hypotheses that stuttering may be associated with impaired skills to focus attention, while cluttering did not seem to be associated with impaired focused attentional skills. However, the sample available within the study period was limited, and due to small samples care should be taken before making firm conclusions.
Monocular Motion Detection Using Spatial Constraints in a Unified Manner

The knowledge about moving objects plays an important role in robot navigation and driver assistance systems. Several motion detection techniques based on the optical flow were developed in the past. To our knowledge none of them exploit the available constraint envelope of a 3D point. In this paper a two-view algorithm is proposed taking advantage of the epipolar, the positive depth, and the positive height constraint, allowing the detection of independent motion and most collinear motions. The constraints are combined in a unified manner resulting in a scalar error function. This enables a direct weighting of the error with the certainty of the measured optical flow. Furthermore, the detection limit of objects moving collinear with the camera and with identical speed is investigated. Experimental results in traffic and indoor scenarios demonstrate the effectiveness of the proposed algorithm
Mental Object Rotation and Egocentric Body Transformation: Two Dissociable Processes?

An important question in studies on mental rotation is whether the mental object rotation and the egocentric body transformation rely on dissociable mechanisms. We tested non-dancers and professional dancers as experts in the mental object rotation task (MORT, 3D-cubes used by Shepard & Metzler, 1971) and the mental body transformation task (MBRT, line drawings of human bodies similar to those used by Parsons, 1987). The cubes and body figures were presented in exactly the same rotation conditions; in the picture plane, 0 degree, 45 degrees, 90 degrees, 135 degrees, and 180 degrees, and in combination with a rotation in depth, 0 degree (the stimuli are rotated in the picture plane only) and 180 degrees. We could replicate the linear increase in RT with increasing angle for the cubes whereas the RT for rotated body figures increased for not depth-rotated bodies only (back view). Though, the RTs for inverted body figures were faster when they were rotated in depth (front view) compared to when they were rotated in the picture plane only (back view). This finding suggests that participants use different strategies depending on the perceived orientation of the stimulus. The results indicate impaired performance in the MORT for the experts.
Seiberg-Witten Map for Superfields on Canonically Deformed N=1, d=4 Superspace

In this paper we construct Seiberg-Witten maps for superfields on canonically deformed N = 1, d = 4 Minkowski and euclidean superspace. On Minkowski superspace we show that the Seiberg-Witten map is not compatible with locality, (anti)chirality and supersymmetry at the same time. On euclidean superspace we show that there exists a local, chiral and supersymmetric Seiberg-Witten map for chiral superfields if we take the noncommutativity parameter to be selfdual, and a local, antichiral and supersymmetric Seiberg-Witten map for antichiral superfields if we take the noncommutativity parameter to be antiselfdual, respectively.
Subunit-Specific Modulation of KCNQ Potassium Channels by Src Tyrosine Kinase

We studied regulation by c-Src tyrosine kinase (Src) of KCNQ1–5 channels heterologously expressed in Chinese hamster ovary (CHO) cells and of native M current in rat sympathetic neurons. Using whole-cell patch clamp, we found that Src modulates currents from KCNQ3, KCNQ4, and KCNQ5 homomultimers, KCNQ2/3 heteromultimers and native M current, but not currents from KCNQ1 or KCNQ2 homomultimers. Src overexpression had two effects: a decrease of current amplitude (4- to 15-fold for cloned channels and ∼3-fold for M current) and a slowing of activation kinetics by 2-fold. Both Src actions were mostly reversed by bath application of the Src inhibitors erbstatin (20 μm) and PP2 (200 nm), and mimicked by the tyrosine phosphatase inhibitor sodium vanadate (100 μm). Immunoprecipitation and immunoblot analysis showed Src-dependent phosphotyrosine signals associated with KCNQ3, KCNQ4, and KCNQ5 but not with KCNQ1 or KCNQ2 that may be tyrosine phosphorylation of the channel subunits. Expression of a dominant negative Src that cannot phosphorylate substrates had no effect on the current and did not induce phosphotyrosine signals associated with KCNQ3–5 subunits, further indicating that Src actions on KCNQ currents are mediated by tyrosine phosphorylation. Immunostaining and confocal analysis showed no effect of Src overexpression on the abundance of KCNQ3 protein in CHO cells. Finally, experiments using cloned KCNQ2/3 channels, Src and M1 muscarinic receptors, and sympathetic neurons demonstrated that the actions on KCNQ channels by Src and by muscarinic agonists use distinct mechanisms.