Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear sensory cortex response to simultaneous tactile stimuli in writer's cramp

Writer's cramp is a task‐specific dystonia that leads to involuntary hand postures during writing. Abnormalities of sensory processing may play a pathophysiological role in this disorder. Electrophysiology studies in a monkey model of focal dystonia have revealed de‐differentiation of sensory maps and the existence of single cells in hand regions of area 3b with enlarged receptive fields that extend to the surfaces of more than one digit. These changes may lead to abnormal processing of simultaneous sensory inputs. To study abnormal processing of simultaneous sensory information in adult humans with writer's cramp, we used functional magnetic resonance imaging to compare the response in primary sensory cortex with simultaneous tactile stimulation of the index and middle finger, with the response to stimulation of each finger alone. We tested five patients with writer's cramp and seven unaffected (normal) subjects. In the normal subjects, a linear combination of the activation patterns for individual finger stimulation predicts the pattern of activity for combined stimulation with 12% error. In writer's cramp patients, the linear combination predicted the combined stimulation pattern with 30% error. Results indicate a nonlinear interaction between the sensory cortical response to individual finger stimulation in writer's cramp. This altered interaction may contribute to the motor abnormalities. © 2001 Movement Disorder Society
Private authentication with controllable measurement

We consider the problem of secret key-based authentication under a privacy constraint on the enrolled source data. The user's measurement in the authentication phase is assumed to be controllable via a cost-constrained “action” sequence. We provide a single-letter characterization of the optimal tradeoff among the secret key rate, storage rate, leakage rate, and action cost. The result can be relevant for several user-authentication scenarios including hardware-based and biometric authentication with multiple measurements. Moreover, our result includes, as a special case, a new result for secret-key generation with action-dependent side information where there is no privacy constraint on the source sequence.
Nanomaterials and neurodegeneration

The increasing application of nanotechnology in various industrial, environmental, and human settings raises questions surrounding the potential adverse effects induced by nanosized materials to human health, including the possible neurotoxic and neuroinflammatory properties of those substances and their capability to induce neurodegeneration. In this review, a panel of metal oxide nanoparticles (NPs), namely titanium dioxide, silicon dioxide, zinc oxide, copper oxide, iron NPs, and carbon nanotubes have been focused. An overview has been provided of the in vitro and in vivo evidence of adverse effects to the central nervous system. Research indicated that these nanomaterials (NMs) not only reach the brain, but also can cause a certain degree of brain tissue damage, including cytotoxicity, genotoxicity, induction of oxidative stress, and inflammation, all potentially involved in the onset and progression of neurodegeneration. Surface chemistry of the NMs may play an important role in their localization and subsequent effects on the brain of rodents. In addition, NM shape differences may induce varying degrees of neurotoxicity. However, one of the potential biomedical applications of NMs is nanodevices for early diagnostic and novel therapeutic approaches to counteract age related diseases. In this context, engineered NMs were promising vehicles to carry diagnostic and therapeutic compounds across the blood–brain barrier, thereby representing very timely and attractive theranostic tools in neurodegenerative diseases. Therefore, a careful assessment of the risk–benefit ratio must be taken into consideration in using nanosized materials. Environ. Mol. Mutagen. 56:149–170, 2015. © 2015 Wiley Periodicals, Inc.
Timing control of utterance and body motion in human-robot interaction

Towards developing robots that are capable of communicating in dasianaturalpsila ways with humans, we believe that it is important to study, and note any important interrelation between, both verbal and non-verbal information in human communication. The model of a timing control system was developed based on a previous study that analyzed the utterance and body motions in the context of human-human communication. This paper presents the realization of this timing control system for the purpose of human-robot interaction, implemented on the Wakamaru robot platform.
Cleaning Crowdsourced Labels Using Oracles For Supervised Learning

Nowadays, crowdsourcing is being widely used to collect training data for supervised learning. However, crowdsourced labels are often noisy, and there is a performance gap between learning with noisy labels and learning with true labels. In this paper, we consider how to apply oracle-based label cleaning to reduce the gap. We propose TARS, a label-cleaning advisor that can provide two pieces of valuable advice for data scientists when they need to train or/and test a model using noisy labels. Firstly, in the model testing stage, given a test dataset with noisy labels, and a classification model, TARS can use the test data to estimate how well the model will perform w.r. t. true labels. Secondly, in the model training stage, given a training dataset with noisy labels, and a supervised-learning algorithm, TARS can determine which label should be sent to an oracle to clean such that the model can be improved the most. For the first advice, we propose an effective estimation technique, and study how to compute confidence intervals to bound its estimation error. For the second advice, we propose a new cleaning strategy along with two optimization techniques, and illustrate that it is superior to the existing cleaning strategies. We evaluate the effectiveness of TARS on both simulated and real-world datasets. The results show that (1) TARS can use noisy test data to accurately estimate a model’s true performance for various evaluation metrics (e.g., Accuracy, FScore); and (2) TARS can improve the model accuracy by a larger margin than the existing cleaning strategies, for the same cleaning budget.
Voice activity detection with array signal processing in the wavelet domain

In many conventional voice activity detection (VAD) methods, speech signal is assumed to be acquired in high quality. However, human-machine interface based on speech is usually employed in indoor environment where various interferences exist, therefore, the VAD performance is seriously deteriorated. In this paper, we propose a novel VAD method with array signal processing on wavelet domain, in which we utilize the time, frequency and space information in the speech signal to separate interferences. In the proposed method, speech signal acquired by microphone array is at first decomposed into appropriate subbands with wavelet packet, and then array signal processing is executed on each subbands to realize VAD system for speech signal arriving from particular direction.
Beneficial effects of n-3 polyunsaturated fatty acids on adiponectin levels and AdipoR gene expression in patients with type 2 diabetes mellitus: a randomized, placebo-controlled, double-blind clinical trial

Introduction There is evidence that n-3 polyunsaturated fatty acids (n-3 PUFAs) exert beneficial effects to improve type 2 diabetes mellitus (T2DM), but its complications remain poorly understood. Hypoadiponectinemia is one of the important mechanisms responsible for T2DM which necessitates developing novel therapeutic strategies. We aimed to determine the effect of n-3 PUFA supplementation on circulating adiponectin and mRNA expression of adiponectin receptors (AdipoR1, AdipoR2) and Sirt-1 in T2DM patients. Material and methods A randomized, double-blind, placebo-controlled trial of 10-week follow-up of n-3 PUFAs (2.7 g/day) vs. placebo in T2DM patients (n = 88) was conducted. In detail, T2DM patients (n = 44) were treated with n-3 PUFAs and the remainder received placebo. Anthropometric and metabolic characteristics were assessed in all participants. Circulating level of adiponectin and mRNA expression of AdipoR1, AdipoR2 and Sirt-1 were measured in peripheral blood mononuclear cells (PBMC) using real-time polymerase chain reaction before and after the intervention. Results It was found that n-3 PUFAs increased AdipoR1 gene expression (fold change = 1.321 in n-3 PUFAs vs. 1.037 in placebo) and AdipoR2 mRNA (fold change = 1.338 in n-3 PUFAs vs. 1.034 in placebo). No significant changes were observed for Sirt-1 expression. The serum level of adiponectin significantly (p = 0.035) increased in n-3 PUFAs (5.09 to 5.58 μg/ml) but remained unchanged in the placebo group. Conclusions Daily supplementation with n-3 PUFAs (2.7 g) was effective to significantly improve gene expression of AdipoR1 and AdipoR2 and the serum level of adiponectin in T2DM patients. Therefore, n-3 PUFAs might emerge as an adjuvant for current antidiabetic therapies. However, confirmatory long-term studies are required.
Transcending paradox: A metaphor of movement for sustaining high performance

Extensive research has been conducted to define the characteristics of high performance \ far less has been done to determine what enables it to be sustained. This study explores that very question; what supports the sustainability of high performance? In reviewing a three year period of data from 2002-2004, twelve hospital facilities in a large US healthcare system were identified as high performers based on consistently strong results in employee engagement, patient satisfaction, employee turnover, internal productivity measures, and superior performance in both financial and quality outcomes. In following these high performers for a second three year period from 2005-2007, a subset of nine facilities continued to outperform the system, while three struggled to maintain consistent results. Using a combination of grounded and generative theory methods, this study explores the intricacies, forces and factors that enabled this group of high performers to sustain their performance. The findings reveal sustained high performance is not a permanent state that an organization simply achieves. Rather, sustaining high performance is an ongoing effort based on continuous action. Through engaging in three critical "movements": collective/individualism, agile/consistency, and informative/inquiry—as active polarities, the facilities in the study transcended common organization paradoxes that often act as impediments to progress. Ultimately, the study suggests sustaining performance is realized through an organization's willingness and ability to be in perpetual movement around these three polarities. This movement is grounded in an i intricate and dynamic balancing that eclipses either/or solutions and instead holds the possibility for a state of both/and. It is in transcending paradox—through movement and in the dynamic balancing of these key polarities—that sustaining high performance is possible. The dissertation concludes by offering implications for future research and recommendations for practice in sustaining high performance.
Ad Hoc Gatherings for Informal Problem Solving: Ordinary Conversation with Co-Workers as Labor for the Company.

AUTHOR Mangrum, Faye Gothard; Wieder, D. Lawrence TITLE Ad Hoc Gatherings for Informal Problem Solving: Ordinary Conversation with Co-Workers as Labor for the Company. PUB DATE 1998-04-00 NOTE 53p. ; Paper presented at the Annual Meeting of the Central States Communication Association (Chicago, IL, April 2-5, 1998) . PUB TYPE Reports Evaluative (142) -Speeches/Meeting Papers (150) EDRS PRICE MF01/PC03 Plus Postage. DESCRIPTORS Communication Research; Discourse Analysis; Ethnography; *Interpersonal Communication; *Organizational Communication; *Problem Solving; Training IDENTIFIERS Conversation
Memory-based local search for simplified protein structure prediction

Protein structure prediction is one of the most challenging problems in computational biology. Given a protein's amino acid sequence, a simplified version of the problem is to find an on-lattice self-avoiding walk that minimizes the interaction energy among the amino acids. In this paper, we present a memory-based local search method for the simplified problem using Hydrophobic-Polar energy model and Face Centered Cubic lattice. By memorizing local minima and then avoiding their neighbohood, our approach significantly improves the state-of-the-art local search method for protein structure prediction on a set of standard benchmark proteins.
Fighting authorship linkability with crowdsourcing

Massive amounts of contributed content -- including traditional literature, blogs, music, videos, reviews and tweets -- are available on the Internet today, with authors numbering in many millions. Textual information, such as product or service reviews, is an important and increasingly popular type of content that is being used as a foundation of many trendy community-based reviewing sites, such as TripAdvisor and Yelp. Some recent results have shown that, due partly to their specialized/topical nature, sets of reviews authored by the same person are readily linkable based on simple stylometric features. In practice, this means that individuals who author more than a few reviews under different accounts (whether within one site or across multiple sites) can be linked, which represents a significant loss of privacy. In this paper, we start by showing that the problem is actually worse than previously believed. We then explore ways to mitigate authorship linkability in community-based reviewing. We first attempt to harness the global power of crowdsourcing by engaging random strangers into the process of re-writing reviews. As our empirical results (obtained from Amazon Mechanical Turk) clearly demonstrate, crowdsourcing yields impressively sensible reviews that reflect sufficiently different stylometric characteristics such that prior stylometric linkability techniques become largely ineffective. We also consider using machine translation to automatically re-write reviews. Contrary to what was previously believed, our results show that translation decreases authorship linkability as the number of intermediate languages grows. Finally, we explore the combination of crowdsourcing and machine translation and report on results.
Effective Transport Equations and Enhanced Backscattering in Random Waveguides

In this paper we derive a general system of transport equations for the moments of reflected and transmitted mode amplitudes in a randomly perturbed waveguide, in a regime where backscattering is significant. The derivation is based on a limit theorem for the system of coupled differential equations for the mode amplitudes, in the limit where the amplitude of the random fluctuations of the medium is small, the correlation lengths in the transverse and longitudinal directions are of the same order of the wavelength, and the waveguide is long. Using this system we derive several results in specific regimes, including the enhanced backscattering phenomenon for the reflected wave: when an incoming monochromatic wave with a specific incidence angle is present, the mean reflected power has a local maximum in the backward direction twice as large as the mean reflected power in the other directions.
Study guide for the practice of nursing research : conduct, critique and utilization

This popular study guide follows the text chapter-by-chapter. It includes the following student activities to enhance learning: relevant terms activities, key ideas exercises, making connections activities, puzzles, exercises in critique, an answer key, and a published studies appendix. Also, a free CD-ROM containing additional review questions is included with each copy.
Inverse shade trees for non-parametric material representation and editing

Recent progress in the measurement of surface reflectance has created a demand for non-parametric appearance representations that are accurate, compact, and easy to use for rendering. Another crucial goal, which has so far received little attention, is editability: for practical use, we must be able to change both the directional and spatial behavior of surface reflectance (e.g., making one material shinier, another more anisotropic, and changing the spatial "texture maps" indicating where each material appears). We introduce an Inverse Shade Tree framework that provides a general approach to estimating the "leaves" of a user-specified shade tree from high-dimensional measured datasets of appearance. These leaves are sampled 1- and 2-dimensional functions that capture both the directional behavior of individual materials and their spatial mixing patterns. In order to compute these shade trees automatically, we map the problem to matrix factorization and introduce a flexible new algorithm that allows for constraints such as non-negativity, sparsity, and energy conservation. Although we cannot infer every type of shade tree, we demonstrate the ability to reduce multi-gigabyte measured datasets of the Spatially-Varying Bidirectional Reflectance Distribution Function (SVBRDF) into a compact representation that may be edited in real time.
A Trading System for Flexible VWAP Executions as a Design Artifact

Volume Weighted Average Price (VWAP) is widely used by institutional investors as benchmark for the execution of large equity orders. To meet the benchmark, investors have the possibility to either cross their orders in a non-intermediated electronic system or to submit a VWAP agency order to a broker. A design artifact addressing and solving the flexibility restrictions present in today’s VWAP crossing is the flexible VWAP crossing model. This work extends the model presenting the rescaling and carrying functions and demonstrating a prototype trading system utilizing the model. Pilot runs show the crossing ratio of the system using random data.
Environmental Risk Factors Associated with H5N1 HPAI in Ramsar Wetlands of Europe

Abstract The objective of this study was to identify environmental characteristics of European Ramsar wetlands, which are natural habitats for waterbirds, that could have contributed as risk factors for H5N1 HPAI (highly pathogenic avian influenza) in water birds (2006–2009). Ramsar wetlands in which H5N1 outbreaks were reported were considered infected (positive), and a case-control study was conducted using a logistic regression model in order to identify environmental risk factors associated with disease. Forestry (odds ratio, OR = 6.90) and important area for water birds with mixosaline water (OR = 6.31), as well as distance to the nearest positive wetland (OR = 0.66), which was included into the model to adjust for spatial dependence, were associated with status of the wetlands. The model was used to estimate the risk for H5N1 HPAI on each European Ramsar wetland. Results will help to identify wetlands at high risk for H5N1 HPAI infection, wetlands that could be selectively targeted as part of a surveillance program aimed at early detection and prevention of future H5N1 HPAI epidemics.
Chapter 1 Fundamental Statistical Techniques 1.1 Binary Linear Classification

The statistical approach to natural language processing (NLP) has become more and more important in recent years. This chapter gives an overview of some fundamental statistical techniques that have been widely used in different NLP tasks. Methods for statistical NLP mainly come from machine learning, which is a scientific discipline concerned with learning from data. That is, to extract information, discover patterns, predict missing information based on observed information, or more generally construct probabilistic models of the data. Machine learning techniques covered in this chapter can be divided into two types: supervised and unsupervised. Supervised learning is mainly concerned with predicting missing information based on observed information. For example, predicting part-of-speech based on sentences. It employs statistical methods to construct a prediction rule from labeled training data. Supervised learning algorithms discussed in this chapter include Naive Bayes, support vector machines, and logistic regression. The goal of unsupervised learning is to group data into clusters. The main statistical techniques are mixture models and the expectation max-imization algorithm. This chapter will also cover methods used in sequence analysis, such as hidden Markov model (HMM), conditional random field, and the Viterbi decoding algorithm. The goal of binary classification is to predict an unobserved binary label y ∈ {−1, 1}, based on an observed input vector x ∈ R d. A classifier h(x) maps x ∈ R d to {−1, 1}. If it agrees with the label y, the error is zero. If it does not agree with label y, we suffer a loss of one.
Cell-free selection of RNA-binding proteins using in vitro compartmentalization

RNA-binding proteins (RBPs) perform many essential functions in the post-transcriptional control of gene expression. If we were able to engineer RBPs with new specificity, it would also become possible to develop new tools to control and investigate gene expression pathways. Molecular evolution methods such as phage display have been introduced to achieve this goal, but the large interface between these proteins and RNA relative to the size of library that can be constructed limits the efficacy of this method. In order to increase the diversity of libraries used for selection of RBPs, we applied the emulsion-based in vitro compartmentalization (IVC) method to select RBPs with defined specificity. A new approach was developed to link genotype and phenotype by fusing the target RBP to zinc finger proteins (ZFPs) that bind to a cognate DNA sequence inserted upstream of the promoter. The expressed fusion protein (ZFP–RBP) binds to its encoding DNA with high affinity via the ZFP target-binding site. After breaking the emulsion, the RBP can be selected based on its affinity for a biotinylated RNA bait. We demonstrate the effectiveness of this method that should enable the selection of RBPs with new specificity or improved affinity.