Miracle-dz/UniFAR-FTUs huggingface dataset:
Title Rapid extraction of lexical tone phonology in chinesecharacters : a visual mismatch negativity study

Background: In alphabetic languages, emerging evidence from behavioral and neuroimaging studies shows the rapid and automatic activation of phonological information in visual word recognition. In the mapping from orthography to phonology, unlike most alphabetic languages in which there is a natural correspondence between the visual and phonological forms, in logographic Chinese, the mapping between visual and phonological forms is rather arbitrary and depends on learning and experience. The issue of whether the phonological information is rapidly and automatically extracted in Chinese characters by the brain has not yet been thoroughly addressed. Methodology/Principal Findings: We continuously presented Chinese characters differing in orthography and meaning to adult native Mandarin Chinese speakers to construct a constant varying visual stream. In the stream, most stimuli were homophones of Chinese characters: The phonological features embedded in these visual characters were the same, including consonants, vowels and the lexical tone. Occasionally, the rule of phonology was randomly violated by characters whose phonological features differed in the lexical tone. Conclusions/Significance: We showed that the violation of the lexical tone phonology evoked an early, robust visual response, as revealed by whole-head electrical recordings of the visual mismatch negativity (vMMN), indicating the rapid extraction of phonological information embedded in Chinese characters. Source analysis revealed that the vMMN was involved in neural activations of the visual cortex, suggesting that the visual sensory memory is sensitive to phonological information embedded in visual words at an early processing stage. Citation: Wang X-D, Liu A-P, Wu Y-Y, Wang P (2013) Rapid Extraction of Lexical Tone Phonology in Chinese Characters: A Visual Mismatch Negativity Study. PLoS ONE 8(2): e56778. doi:10.1371/journal.pone. 0056778 Editor: Jacob Engelmann, Universität Bielefeld, Germany Received August 30, 2012; Accepted January 14, 2013; Published February 20, 2013 Copyright: 2013 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The authors have no support or funding to report. Competing Interests: The authors have declared that no competing interests exist. * E-mail: XD-Wang@ntu.edu. sg
Wearable therapist: sensing garments for supporting children improve posture

This paper introduces a sensing garment to support posture coaching in children. The system measures back bending postures using acceleration sensors embedded in the garment. We present a sensing garment architecture and the evaluation of garments of different sizes in a study with 21 children. A vision-based reference system was used to evaluate sensor positions and measurement accuracy for 54 back bending postures and related head positions. Then, we asked eight physiotherapists to rate the children's back postures in this study. Ratings of experts correlated significantly with the back bending measurements obtained from the garment. The garment enables an objective assessment of back postures and could form the basis of a system that provides coaching feedback to improve postural control in children.
Real-world particle filtering-based speech enhancement

This paper presents a viable particle filtering (PF) solution for single microphone speech enhancement in real-world conditions, i.e., operating at low SNR in nonstationary noise environments, while remaining computationally tractable. The enhancement takes place in the subband domain with elementary PFs in each band. To efficiently handle complex noise situations, the noise spectrum is modelled in each band as a white Gaussian noise sequence with a time-varying gain. Two solutions are proposed to estimate these time-varying average subband noise levels: they are either drawn internally by the PFs, or they are obtained by external dedicated noise power spectral density estimation - both methods are found to yield very close results. Several subband decompositions are tested, and a robust way of incorporating perceptual constraining is introduced. The assembled PF-based architecture is then compared with state-of-the-art enhancement algorithms in various conditions, and is found to outperform them according to seven objective speech quality measures.
New Anti-Nodal Monoclonal Antibodies Targeting the Nodal Pre-Helix Loop Involved in Cripto-1 Binding

Nodal is a potent embryonic morphogen belonging to the TGF-β superfamily. Typically, it also binds to the ALK4/ActRIIB receptor complex in the presence of the co-receptor Cripto-1. Nodal expression is physiologically restricted to embryonic tissues and human embryonic stem cells, is absent in normal cells but re-emerges in several human cancers, including melanoma, breast, and colon cancer. Our aim was to obtain mAbs able to recognize Nodal on a major CBR (Cripto-Binding-Region) site and to block the Cripto-1-mediated signalling. To achieve this, antibodies were raised against hNodal(44–67) and mAbs generated by the hybridoma technology. We have selected one mAb, named 3D1, which strongly associates with full-length rhNodal (KD 1.4 nM) and recognizes the endogenous protein in a panel of human melanoma cell lines by western blot and FACS analyses. 3D1 inhibits the Nodal-Cripto-1 binding and blocks Smad2/3 phosphorylation. Data suggest that inhibition of the Nodal-Cripto-1 axis is a valid therapeutic approach against melanoma and 3D1 is a promising and interesting agent for blocking Nodal-Cripto mediated tumor development. These findings increase the interest for Nodal as both a diagnostic and prognostic marker and as a potential new target for therapeutic intervention.
Carbon Nanotubes As Scanning Probe Tips

We have constructed a device for manipulating carbon nanotubes inside a transmission electron microscope. This setup allows us to select an individual nanotube of our choice and to attach it to an AFM probe tip. This way we obtain a tool which is useful for diverse applications. It can be used as a “classical AFM probe” yet with enhanced resolution due to the small size of the nanotube ending and mechanical properties of carbon nanotubes. Employing a conductive layer as “glue” between the nanotube and the probe enables us to make transport measurements on a single nanotube. Biasing the nanotube, electron and light emission occurs at the tip of the nanotube. This light emission is the basis of constructing a Scanning Near‐field Optical Microscope (SNOM) with carbon nanotubes.
Finding legally relevant passages in case opinions

Thii paper presents a hybrid case-based reasoning (CBR) and information retrieval (IR.) system, called SPIRE, that locates passages likely to contain information about legally relevant features of cases found in full-text court opinions. SPIRE uses an example base of excerpts from past opinions to form queries, which are run by the INQUERY IR text retrieval engine on individual case opinions. These opinions can be those found by SPIRE in a prior stage of processing, which also employs a hybrid CBR-IR approach to retrieve relevant texts from large document corpora. (This aspect of SPIRE was reported on at ICAIL95.) We present an overview of SPIRE, run through an extended example, and give results comparing SPIRE’s with human performance.
University of Pennsylvania Working Papers in Linguistics Lithuanian Passive-like Impersonals and Regular Passives Lithuanian Passive-like Impersonals and Regular Passives Lithuanian Passive-like Impersonals and Regular Passives

This study provides evidence for microvariations in VoiceP (Legate 2014) by contrasting two Lithuanian constructions, the passive-like-ma/-ta construction with an accusative theme grammatical object and the canonical passive with a nominative theme grammatical subject. The-ma/-ta construction is cognate with the Polish and Ukrainian-no/-to construction. The Polish construction is an impersonal active, whereas the Ukrainian construction is a passive with an accusative object (Lavine 2005, 2013; Legate 2014). Although the Lithuanian construction patterns with the Ukrainian one in allowing an auxiliary, it patterns with the Polish in exhibiting a PRO subject and demonstrating that these two properties are dissociable (contra Lavine 2005). To encode the difference between the impersonal and the passive, I argue for the presence of a functional head VoiceP originating above a vP. The impersonal has a PRO subject in VoiceP, while the passive lacks the thematic subject. This study is extended to passives with causative morphology showing that VoiceP and vP are independent of each other: the former introduces external argument and the latter causative semantics
A Video-Based Method for Objectively Rating Ataxia

For many movement disorders, such as Parkinson's disease and ataxia, disease progression is visually assessed by a clinician using a numerical disease rating scale. These tests are subjective, time-consuming, and must be administered by a professional. This can be problematic where specialists are not available, or when a patient is not consistently evaluated by the same clinician. We present an automated method for quantifying the severity of motion impairment in patients with ataxia, using only video recordings. We consider videos of the finger-to-nose test, a common movement task used as part of the assessment of ataxia progression during the course of routine clinical checkups. Our method uses neural network-based pose estimation and optical flow techniques to track the motion of the patient's hand in a video recording. We extract features that describe qualities of the motion such as speed and variation in performance. Using labels provided by an expert clinician, we train a supervised learning model that predicts severity according to the Brief Ataxia Rating Scale (BARS). The performance of our system is comparable to that of a group of ataxia specialists in terms of mean error and correlation, and our system's predictions were consistently within the range of inter-rater variability. This work demonstrates the feasibility of using computer vision and machine learning to produce consistent and clinically useful measures of motor impairment.
On the formation and maintenance of the stratospheric surf zone as inferred from the zonally averaged potential vorticity distribution

The diagnostic relation between eddy potential vorticity flux and Eliassen–Palm flux convergence in the transformed Eulerian mean shallow‐water system is used to infer the flux convergence needed to establish a stratospheric surf zone comprising a single region of perfectly homogenized potential vorticity, or to maintain the surf zone in steady state against the restoring effect of radiative relaxation. In the transient case, and when wave breaking is assumed to mix potential vorticity on time‐scales shorter than the radiative time‐scale, the required flux convergence is an order of magnitude larger than that required to maintain the flow in steady state away from radiative equilibrium.
Comparative Genomics of Saccharomyces cerevisiae Natural Isolates for Bioenergy Production

Lignocellulosic plant material is a viable source of biomass to produce alternative energy including ethanol and other biofuels. However, several factors—including toxic byproducts from biomass pretreatment and poor fermentation of xylose and other pentose sugars—currently limit the efficiency of microbial biofuel production. To begin to understand the genetic basis of desirable traits, we characterized three strains of Saccharomyces cerevisiae with robust growth in a pretreated lignocellulosic hydrolysate or tolerance to stress conditions relevant to industrial biofuel production, through genome and transcriptome sequencing analysis. All stress resistant strains were highly mosaic, suggesting that genetic admixture may contribute to novel allele combinations underlying these phenotypes. Strain-specific gene sets not found in the lab strain were functionally linked to the tolerances of particular strains. Furthermore, genes with signatures of evolutionary selection were enriched for functional categories important for stress resistance and included stress-responsive signaling factors. Comparison of the strains’ transcriptomic responses to heat and ethanol treatment—two stresses relevant to industrial bioethanol production—pointed to physiological processes that were related to particular stress resistance profiles. Many of the genotype-by-environment expression responses occurred at targets of transcription factors with signatures of positive selection, suggesting that these strains have undergone positive selection for stress tolerance. Our results generate new insights into potential mechanisms of tolerance to stresses relevant to biofuel production, including ethanol and heat, present a backdrop for further engineering, and provide glimpses into the natural variation of stress tolerance in wild yeast strains.
A Geometric Feature Detection Approach to Particle Picking in Electron Micrographs

Accurate and automatic particle detection from cryo-electron microscopy (cryo-EM) images is very important for high-resolution reconstruction of large macromolecular structures. In this paper, we present a novel method, based on feature detection, for particle picking. Two fundamental concepts of computational geometry, namely, distance transform and Voronoi diagram, are used for detection of critical features as well as for accurate location of particles from the micrographs. Unlike the conventional template-matching methods, our approach detects the particles based on their boundary features instead of intensities. The geometric features derived from the boundaries provide an efficient way for locating particles quickly and accurately, which avoids a brute-force searching for the best position/orientation. Our approach is fully automatic and has been successfully applied to detect particles with roughly circular or rectangular shapes. Particle detection can be enhanced by multiple sets of parameters used in edge detection and/or by anisotropic filtering. We will also discuss the extension of this approach to other types of particles with certain geometric features.
Accumulation of desirable alleles for southern leaf blight (SLB) in maize (Zea mays L.) under the epiphytotic of Helminthosporium maydis.

To accumulate desirable alleles for southern leaf blight (SLB) resistance and for grain yield, 76 inbred lines were evaluated under the epiphytotic of Helminthosporium maydis. Highly significant differences (P<0.01) were observed among the lines for SLB severity, area under disease progress curve (AUDPC) and grain yield. The broad sense heritability (hBS) obtained for SLB was 0.59, whereas it was 0.91 and 0.61 for AUDPC and grain yield, respectively. Selection differential (S) was positive for grain yield (835 kg ha -1 ) and was negative for SLB severity (-0.61) and AUDPC (-164.7), indicating a declining trend for these two disease parameters. On the other hand regression analysis also showed a negative effect for disease severity on the total grain yield and R 2 value was 0.1933. A negative correlation was observed for yield and SLB showing the importance of increase resistance to boost up the production of maize crop. The cycle of recurrent selection (RS) showed a reliable gain from selection while the expected response showed the extent of improvement in the next generation for SLB, AUDPC and other related parameters. On the basis of frequency distribution curve, the desirable lines for SLB resistance have been shown in different categories. This study revealed the effectiveness of RS for enhancing resistance against SLB and improvement of grain yield in maize crop. Using these parameters sufficient evidence were found for required variability in maize germplasm that can be manipulated in desirable direction for the welfare of humanity.
Understanding the mechanical response of double-stranded DNA and RNA under constant stretching forces using all-atom molecular dynamics

Significance The mechanical properties of nucleic acids regulate multiple biological processes ranging from complex chromosome packing to replication of a plasmid. Single-molecule experiments have reported puzzling differences between the mechanical properties of double-stranded DNA (dsDNA) and double-stranded RNA (dsRNA) subjected to force and torque. This study investigates these differences using constant-force, all-atom, microsecond-long molecular dynamics. We provide a physical mechanism that explains the nonintuitive opposite twist-stretch response of these molecules based on the change of the interstrand distance with the stretching force. Changes in interstrand distance are ultimately related to differences in the chemical structure of dsDNA and dsRNA molecules. The methodology and results shown here open the field to explore larger forces to test experimental measurements, and to challenge the predictions given by our simulations. Multiple biological processes involve the stretching of nucleic acids (NAs). Stretching forces induce local changes in the molecule structure, inhibiting or promoting the binding of proteins, which ultimately affects their functionality. Understanding how a force induces changes in the structure of NAs at the atomic level is a challenge. Here, we use all-atom, microsecond-long molecular dynamics to simulate the structure of dsDNA and dsRNA subjected to stretching forces up to 20 pN. We determine all of the elastic constants of dsDNA and dsRNA and provide an explanation for three striking differences in the mechanical response of these two molecules: the threefold softer stretching constant obtained for dsRNA, the opposite twist-stretch coupling, and its nontrivial force dependence. The lower dsRNA stretching resistance is linked to its more open structure, whereas the opposite twist-stretch coupling of both molecules is due to the very different evolution of molecules’ interstrand distance with the stretching force. A reduction of this distance leads to overwinding in dsDNA. In contrast, dsRNA is not able to reduce its interstrand distance and can only elongate by unwinding. Interstrand distance is directly correlated with the slide base-pair parameter and its different behavior in dsDNA and dsRNA traced down to changes in the sugar pucker angle of these NAs.
A Framework for Recognizing Hand Gestures

Traditional methods for user input, consisting of fixed key input and point-click devices, are slowly being supplemented and enhanced by touch technologies and their associated touch gestures. While these methods have proven effective, they are limited in scope in that they require a physical object or surface with which a user must interact. The use of hand gestures in free space is often seen as an intuitive next step in the progression of user input technologies. A system that takes cues from such gestures would unshackle a user from physical devices. Using such systems, a user only needs their body motion to signal specific actions that can be picked up by a camera and interpreted by appropriate computer vision algorithms. In this paper, we explore the use of machine learning to process and interpret image sequences in order to correctly recognize and classify a couple simple hand gestures. Our work is part of a larger body of research by computer science Ph.D. student Hendrik Dahlkamp and computer science Postdoctoral researcher Christian Plagemann to create a gesture-based UI that allows users to manipulate virtual objects in 3D space. An active infrared camera is used to capture both infrared intensity data as well as depth information. Unlike a passive RGB camera, the depth information captured by the infrared camera greatly simplifies segmentation of foreground objects. Existing components of Dahlkamp’s vision system can track the movement of a hand once it has been recognized as such, crop out the region around the hand, and perform the necessary background subtraction to produce the training sets we use. Recognizing a hand gesture, then, requires that we be able to 1) differentiate a “hand image” from a “nonhand image”, and 2) correlate a sequence of hand images with a specific gesture. This paper comprises the development of these two functional blocks using machine learning techniques.
A Full Wave Voltage Multiplier for RFID Transponders

A full wave voltage multiplier for passive RFID transponders is presented. The current driving capability of the proposed rectifier is remarkably improved at the cost of only a small increase in layout area compared to the widely used conventional half wave voltage multiplier. The communication distance of RFID systems can be extended due to the improved RF carrier to DC power conversion capability of the proposed voltage multiplier.
IL-33 Enhances Lipopolysaccharide-Induced Inflammatory Cytokine Production from Mouse Macrophages by Regulating Lipopolysaccharide Receptor Complex1

Bacterial LPS triggers monocytes and macrophages to produce several inflammatory cytokines and mediators. However, once exposed to LPS, they become hyporesponsive to a subsequent endotoxin challenge. This phenomenon is defined as LPS desensitization or tolerance. Previous studies have identified some components of the biochemical pathways involved in negative modulation of LPS responses. In particular, it has been shown that the IL-1R-related protein ST2 could be implicated in LPS tolerance. The natural ligand of ST2 was recently identified as IL-33, a new member of the IL-1 family. In this study, we investigated whether IL-33 triggering of ST2 was able to induce LPS desensitization of mouse macrophages. We found that IL-33 actually enhances the LPS response of macrophages and does not induce LPS desensitization. We demonstrate that this IL-33 enhancing effect of LPS response is mediated by the ST2 receptor because it is not found in ST2 knockout mice. The biochemical consequences of IL-33 pretreatment of mouse macrophages were investigated. Our results show that IL-33 increases the expression of the LPS receptor components MD2 (myeloid differentiation protein 2) and TLR-4, the soluble form of CD14 and the MyD88 adaptor molecule. In addition, IL-33 pretreatment of macrophages enhances the cytokine response to TLR-2 but not to TLR-3 ligands. Thus, IL-33 treatment preferentially affects the MyD88-dependent pathway activated by the TLR.