Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of multilingual and semi-supervised training for under-resourced languages

Multilingual training of neural networks for ASR is widely studied these days. It has been shown that languages with little training data can beneﬁt largely from the multilingual resources for training. The use of unlabeled data for the neural network training in semi-supervised manner has also improved the ASR system performance. Here, the combination of both methods is presented. First, multilingual training is performed to obtain an ASR system to automatically transcribe the unlabeled data. Then, the automatically transcribed data are added. Two neural networks are trained - one from random initialization and one adapted from multilingual network - to evaluate the effect of multilingual training under presence of larger amount of training data. Further, the CMLLR transform is applied in the middle of the stacked Bottle-Neck neural network structure. As the CMLLR rotates the features to better ﬁt given model, we evaluated whether it is better to adapt the existing NN on the CMLLR features or if it is better to train it from random initialization. The last step in our training procedure is the ﬁne-tuning on the original data.
The genomic regulatory control of skeletal morphogenesis in the sea urchin

A central challenge of developmental and evolutionary biology is to understand how anatomy is encoded in the genome. Elucidating the genetic mechanisms that control the development of specific anatomical features will require the analysis of model morphogenetic processes and an integration of biological information at genomic, cellular and tissue levels. The formation of the endoskeleton of the sea urchin embryo is a powerful experimental system for developing such an integrated view of the genomic regulatory control of morphogenesis. The dynamic cellular behaviors that underlie skeletogenesis are well understood and a complex transcriptional gene regulatory network (GRN) that underlies the specification of embryonic skeletogenic cells (primary mesenchyme cells, PMCs) has recently been elucidated. Here, we link the PMC specification GRN to genes that directly control skeletal morphogenesis. We identify new gene products that play a proximate role in skeletal morphogenesis and uncover transcriptional regulatory inputs into many of these genes. Our work extends the importance of the PMC GRN as a model developmental GRN and establishes a unique picture of the genomic regulatory control of a major morphogenetic process. Furthermore, because echinoderms exhibit diverse programs of skeletal development, the newly expanded sea urchin skeletogenic GRN will provide a foundation for comparative studies that explore the relationship between GRN evolution and morphological evolution.
Common and Distinct Brain Regions Support Numerical and Non-numerical Magnitude Processing: A Functional Neuroimaging Meta-Analysis

ii Acknowledgments iii Table of Contents iv List of Tables vi List of Figures vii Chapter 1 1 1 Introduction 1 1.1 Numerical Magnitude Processing 1 1.2 Non-numerical Magnitude Processing 5 1.3 Qualitative Meta-Analyses 9 1.4 The Current Study 11 Chapter 2 13 2 Method 13 2.1 Literature Search and Article Selection 13 2.2 Analysis Procedure 14 2.3 Single Dataset ALE Maps 15 2.4 Conjunction and Contrast Analyses 16 Chapter 3 24 3 Results 24 3.1 Single Dataset Meta Analysis 24 3.1.1 Symbolic Numerical Magnitude Processing 24 3.1.2 Nonsymbolic Numerical Magnitude Processing 25 3.1.3 Non-numerical Magnitude Processing 25
The VELA pulsar `jet': a companion-punctured bubble of fallback material

Markwardt & Ogelman used ROSAT to reveal a 12 by 45 arcmin^2 structure in 1-keV X-rays around the Vela pulsar, which they interpret as a jet emanating from the pulsar. Here we present an alternative view of the nature of this feature, namely that it consists of material from very deep inside the exploding star, close to the mass cut between material that became part of the neutron star and material that was ejected. The initial radial velocity of the inner material was lower than the bulk velocity of the ejecta, and this formed a bubble of slow material that started expanding again owing to heating by the spindown energy of the young pulsar. The expansion is mainly in one direction, and to explain this we speculate that the presupernova system was a binary. The explosion caused the binary to unbind, and the former companion of the pulsar carved a lower density channel into the main ejecta. The resulting puncture of the edge of the bubble greatly facilitated expansion along its path relative to other directions. If this is the case, we can estimate the current speed of the former binary companion and from this reconstruct the presupernova binary orbit. It follows that the exploding star was a helium star and hence that the supernova was of Type Ib. Since the most likely binary companion is another neutron star, the evolution of the Vela remnant and its surroundings has been rather more complicated than the simple expansion of one supernova blast wave into unperturbed interstellar material.
Fabrication of photonic crystals using holography and study for the lattice constant changes

A simple optical path for fabricating photonic crystals is presented. It is convenient to change the number of beams and its angles. Then photonic crystals of different lattices can be gotten. Recording material is home-made water-resisting photopolymer. The fabrication of photonic crystals with holography is simulated by matlab. By changing the number of beams and its angles, triangular, square and circular structures of photonic crystals are obtained. When polarization states of beams are changed, photonic crystals of different refractive index modulation are obtained. Via the simulation, the refractive index modulation of linearly polarized light is the highest. In the experiment, different exposures are set. And the best exposure is 20s, which is less than before. In this paper, photonic crystals using four light beams and five light beams are fabricated. Then, compare simulated results with experimental results and they are in substantial agreement.
SITUATION CALCULUS WITH CONCURRENT EVENTS AND NARRATIVE

Concurrent events are treated merely by not forbidding them. Narrative is treated as a collection of situations and events and relations among them. Narrative is easier than planning, because it does not require that the eects of events be guaranteed. Prediction is harder than planning, because it requires that the actions be inferred from the motives of the actors.
Privacy-leakage codes for biometric authentication systems

In biometric privacy-preserving authentication systems that are based on key-binding, two terminals observe two correlated biometric sequences. The first terminal selects a secret key, which is independent of the biometric data, binds this secret key to the observed biometric sequence and communicates it to the second terminal by sending a public message. This message should only contain a negligible amount of information about the secret key, but also leak as little as possible about the biometric data. Current approaches to realize such biometric systems use fuzzy commitment with codes that, given a secret-key rate, can only achieve the corresponding privacy-leakage rate equal to one minus this secret-key rate. However, the results in Willems and Ignatenko [2009] indicate that lower privacy leakage can be achieved if vector quantization is used at the encoder. In this paper we study the use of convolutional and turbo codes applied in fuzzy commitment and its modifications that realize this.
Remarkable longevity and stress resistance of nematode PI3K‐null mutants

The great majority of lifespan‐augmenting mutations were discovered in the nematode Caenorhabditis elegans. In particular, genetic disruption of insulin‐like signaling extends longevity 1.5‐ to 3‐fold in the nematode, and to lesser degrees in other taxa, including fruit flies and mice. C. elegans strains bearing homozygous nonsense mutations in the age‐1 gene, which encodes the class‐I phosphatidylinositol 3‐kinase catalytic subunit (PI3KCS), produce progeny that were thought to undergo obligatory developmental arrest. We now find that, after prolonged developmental times at 15–20 °C, they mature into extremely long‐lived adults with near‐normal feeding rates and motility. They survive to a median of 145–190 days at 20 °C, with nearly 10‐fold extension of both median and maximum adult lifespan relative to N2DRM, a long‐lived wild‐type stock into which the null mutant was outcrossed. PI3K‐null adults, although a little less thermotolerant, are considerably more resistant to oxidative and electrophilic stresses than worms bearing normal or less long‐lived alleles. Their unprecedented factorial gains in survival, under both normal and toxic environments, are attributed to elimination of residual and maternally contributed PI3KCS or its products, and consequent modification of kinase signaling cascades.
WordNet Website Development And Deployment using Content Management Approach

The WordNets for many official Indian languages are being developed by the members of the IndoWordNet Consortium in India. It was decided that all these WordNets be made open for public use and feedback to further improve their quality and usage. Hence each member of the IndoWordNet Consortium had to develop their own website and deploy their WordNets online. In this paper, the Content Management System (CMS) based approach used to speed up the WordNet website development and deployment activity is presented. The CMS approach is database driven and dynamically creates the websites with minimum input and effort from the website creator. This approach has been successfully used for the deployment of WordNet websites with friendly user interface and all desired functionalities in very short time for many Indian languages.
A Promising method for fast evaluating protein structure similarity

According to a ligand binding site, screening protein structural database may provide the lead information to accelerate drug discovery research. In this study we propose a novel approach MIIF based on the method protein folding shape code (PFSC), is applied to discover the similar binding site area of a protein related to the known drug target area of a ligand.
Polymer Characterization: Laboratory Techniques and Analysis

This volume provides an overview of polymer characterization test methods. The methods and instrumentation described represent modern analytical techniques useful to researchers, product development specialists, and quality control experts in polymer synthesis and manufacturing. Engineers, polymer scientists and technicians will find this volume useful in selecting approaches and techniques applicable to characterizing molecular, compositional, rheological, and thermodynamic properties of elastomers and plastics.
Major depression following smoking cessation.

OBJECTIVE The authors examined the incidence and predictors of major depression following successful smoking cessation treatment, with special attention to the influence of past major depression. METHOD Three-month follow-up data were obtained from 126 subjects who successfully completed a 10-week smoking cessation program. RESULTS The 3-month incidence of new major depression following treatment for nicotine dependence was 2%, 17%, and 30% among subjects with histories of no major depression, single major depression, and recurrent major depression, respectively. A history of major depression and persistent withdrawal symptoms independently predicted posttreatment major depression. CONCLUSIONS Continued patient care beyond the 2-4-week period associated with the nicotine withdrawal syndrome is indicated when abstinence is attempted by smokers with prior major depression.
Reward Prediction Error Computation in the Pedunculopontine Tegmental Nucleus Neurons

Abstract: In this article, we address the role of neuronal activity in the pathways of the brainstem–midbrain circuit in reward and the basis for believing that this circuit provides advantages over previous reinforcement learning theory. Several lines of evidence support the reward‐based learning theory proposing that midbrain dopamine (DA) neurons send a teaching signal (the reward prediction error signal) to control synaptic plasticity of the projection area. However, the underlying mechanism of where and how the reward prediction error signal is computed still remains unclear. Since the pedunculopontine tegmental nucleus (PPTN) in the brainstem is one of the strongest excitatory input sources to DA neurons, we hypothesized that the PPTN may play an important role in activating DA neurons and reinforcement learning by relaying necessary signals for reward prediction error computation to DA neurons. To investigate the involvement of the PPTN neurons in computation of reward prediction error, we used a visually guided saccade task (VGST) during recording of neuronal activity in monkeys. Here, we predict that PPTN neurons may relay the excitatory component of tonic reward prediction and phasic primary reward signals, and derive a new computational theory of the reward prediction error in DA neurons.
The effects of development parameter on line edge roughness in sub-0.20 /spl mu/m line patterns

As a pattern size decreases, CD control gets more important. However, the line edge roughness consumes the error budget of critical dimension and has obstructed the development of the high contrast resist to extend the resolution limit of KrF lithography. To investigate the effect of the development parameter on line edge roughness, we observed the profile of the exposed and developed top surface. In the early state of development, the protrusion and extraction of clusters affect dominantly on surface roughness. And then the effect of intrinsic aggregate gradually gets larger as the development time increases. For this reason the linewidth fluctuation decreased as development time increased. The clusters/aggregates are extracted in full dissolution of surrounding polymers and partially dissolved, then these partially dissolved clusters/aggregates are precipitated in DI rinse and rebond on patterns.
Retrospective Multicenter Study of Solitaire FR for Revascularization in the Treatment of Acute Ischemic Stroke

Background and Purpose— The purpose of this study was to evaluate safety and efficacy of the Solitaire FR device in the treatment of patients with acute ischemic stroke secondary to large artery occlusion. Methods— We conducted a retrospective study of consecutive patients presenting with acute ischemic stroke treated with Solitaire FR as the first-line device to restore blood flow in 6 experienced European centers. This study was entirely funded and supported by Coviden Neurovascular. An independent Corelab determined modified Thrombolysis in Cerebral Infarction scores on the preprocedure and postprocedure angiograms. Complete revascularization was defined as modified Thrombolysis in Cerebral Infarction 2b or 3 post-Solitaire FR device use. Symptomatic intracranial hemorrhage was defined as parenchymal hemorrhage Type 2 associated with a decline of ≥4 points in the National Institutes of Health Stroke Scale score within 24 hours or causing death. Favorable functional outcome was considered as modified Rankin Scale score ⩽2 at Day 90. Results— We studied 141 patients (mean age, 66 years; median National Institutes of Health Stroke Scale, 18); 74 patients received intravenous tissue-type plasminogen activator before endovascular treatment. Complete revascularization was achieved in 120 of 142 occlusion sites (85%) and good outcome in 77 of 141 (55%) patients. Good outcome was more frequent in patients treated with intravenous tissue-type plasminogen activator than in those without (66% versus 42%; P<0.01). Symptomatic intracranial hemorrhage was reported in 5 patients (4%) and 29 of 141 (20%) patients died or were lost during follow-up (3 cases). Conclusions— This retrospective study with centralized evaluation shows that the use of Solitaire FR is safe and achieves good revascularization rates and functional outcomes in patients with acute ischemic stroke and large artery occlusion.
Stress adaptation in a pathogenic fungus

Candida albicans is a major fungal pathogen of humans. This yeast is carried by many individuals as a harmless commensal, but when immune defences are perturbed it causes mucosal infections (thrush). Additionally, when the immune system becomes severely compromised, C. albicans often causes life-threatening systemic infections. A battery of virulence factors and fitness attributes promote the pathogenicity of C. albicans. Fitness attributes include robust responses to local environmental stresses, the inactivation of which attenuates virulence. Stress signalling pathways in C. albicans include evolutionarily conserved modules. However, there has been rewiring of some stress regulatory circuitry such that the roles of a number of regulators in C. albicans have diverged relative to the benign model yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe. This reflects the specific evolution of C. albicans as an opportunistic pathogen obligately associated with warm-blooded animals, compared with other yeasts that are found across diverse environmental niches. Our understanding of C. albicans stress signalling is based primarily on the in vitro responses of glucose-grown cells to individual stresses. However, in vivo this pathogen occupies complex and dynamic host niches characterised by alternative carbon sources and simultaneous exposure to combinations of stresses (rather than individual stresses). It has become apparent that changes in carbon source strongly influence stress resistance, and that some combinatorial stresses exert non-additive effects upon C. albicans. These effects, which are relevant to fungus–host interactions during disease progression, are mediated by multiple mechanisms that include signalling and chemical crosstalk, stress pathway interference and a biological transistor.
Left-Luggage Detection from FiniteStateMachine FiniteStateMachine FiniteStateMachine StateMachine StateMachine Analysis in StaticCamera StaticCamera StaticCamera Videos

We present an abandoned object detection system in this paper. A finite-state-machine model is introduced to extract stationary foregrounds in a scene for visual surveillance, where the state value of each pixel is inferred via the cooperation of short-term and long-term background models constructed in the proposed approach. To identify the left-luggage event, we then verify whether the static foregrounds are abandoned objects through the analysis of owner’s moving trajectory back-tracked to the static foreground locations. Experimental results reveal that the proposed approach tackles the problem well on publicly available datasets. Keywords—Abandoned object detection; finite state machine; background subtraction; object tracking; visual surveillance.
Can the feel of the haptic interaction modify a user's emotional state?

Haptic perception constitutes an important component of our everyday interaction with many products. At the same time, several studies have, in recent years, demonstrated the importance of involving the emotions in the user-product interaction process. The present study was designed to investigate whether haptic interactions can affect, or modulate, people's responses to standardized emotional stimuli. 36 participants completed a self-assessment test concerning their emotional state utilizing as a pointer either a PHANToM device simulating a viscous force field while they moved the stylus, or else a stylus with no force field. During the presentation of the emotional pictures, various physiological parameters were recorded from participants. The results revealed a significant difference in the self-reported arousal associated with the pictures but no significant difference in the physiological measures. The behavioural findings are interpreted in terms of an effect of the haptic feedback on participants' perceived/interpreted emotional arousal. These results suggest that haptic feedback could, in the future, be used to modify participants' interpretation of their physiological states.
COMBINATION OF N-GRAMS AND STOCHASTIC CONTEXT-FREE GRAMMARS FOR LANGUAGE MODELING

This paper describes a hybrid proposal to combine n-grams and Stochastic Context-Free Grammars (SCFGs) for language modeling. A classical n-gram model is used to capture the local relations between words, while a stochastic grammatical model is considered to represent the long-term relations between syntactical structures. In order to de ne this grammatical model, which will be used on large-vocabulary complex tasks, a category-based SCFG and a probabilistic model of word distribution in the categories have been proposed. Methods for learning these stochastic models for complex tasks are described, and algorithms for computing the word transition probabilities are also presented. Finally, experiments using the Penn Treebank corpus improved by 30% the test set perplexity with regard to the classical n-gram models.
Modeling human behavior during touchscreen interaction in mobile situations

As mobile devices are becoming more ubiquitous, it is common for users to interact with them in many different situations. In our research, we focus on modeling human behavior during touchscreen interaction in mobile situations. Resulting models do not only increase our understanding of human behavior but also predict or infer intended user interaction. This enables us to design interfaces suited for one-handed interaction and to derive new interaction possibilities. In our work, we will collect data in lab studies as well as on a large scale to create models with high external validity.
On The Accuracy of TCP Throughput Prediction for Opportunistic Wireless Networks

The increasing density of WiFi Access Points (APs) in metropolitan areas is enabling an opportunistic model of wireless networking, whereby a "guest" user within range of one or more wireless APs can gain temporary Internet access through these APs. In this paper, we address the problem of TCP throughput prediction for opportunistic networks. Applications of opportunistic networking can benefit from such predictions by adapting to prevailing network conditions. Our approach is different from prior efforts to model wireless network throughput in that only the two communicating endpoints participate in the prediction, and no information about network topology or traffic loads generated by interfering sources is required. Our goal is to understand how accurate throughput predictions can be under the above assumptions. The physical environment considered in our study includes varying degrees of interference, indoor and outdoor networks, and nodes that are stationary or moving at walking or driving speeds. We use throughput predictors based on time series analysis and machine learning techniques, as they are well-suited to predicting phenomena with unknown variables. The prediction accuracy that our methods yield is cause for cautious optimism. We find that 80% to 100% of predictions are within a factor of two of actual throughput. This bound on accuracy means that predictions are useful for certain applications, because this bound (a) can be achieved by measurements lasting for as little as 0.3 seconds, and (b) holds even when nodes are driving at speeds of 15-25 mph.