Miracle-dz/UniFAR-FTUs huggingface dataset:
Sublexical Properties of Spoken Words Modulate Activity in Broca's Area but Not Superior Temporal Cortex: Implications for Models of Speech Recognition

Many models of spoken word recognition posit that the acoustic stream is parsed into phoneme level units, which in turn activate larger representations [McClelland, J. L. , & Elman, J. L. The TRACE model of speech perception. Cognitive Psychology, 18, 1–86, 1986], whereas others suggest that larger units of analysis are activated without the need for segmental mediation [Greenberg, S. A multitier theoretical framework for understanding spoken language. In S. Greenberg & W. A. Ainsworth (Eds.), Listening to speech: An auditory perspective (pp. 411–433). Mahwah, NJ: Erlbaum, 2005; Klatt, D. H. Speech perception: A model of acoustic-phonetic analysis and lexical access. Journal of Phonetics, 7, 279–312, 1979; Massaro, D. W. Preperceptual images, processing time, and perceptual units in auditory perception. Psychological Review, 79, 124–145, 1972]. Identifying segmental effects in the brain's response to speech may speak to this question. For example, if such effects were localized to relatively early processing stages in auditory cortex, this would support a model of speech recognition in which segmental units are explicitly parsed out. In contrast, segmental processes that occur outside auditory cortex may indicate that alternative models should be considered. The current fMRI experiment manipulated the phonotactic frequency (PF) of words that were auditorily presented in short lists while participants performed a pseudoword detection task. PF is thought to modulate networks in which phoneme level units are represented. The present experiment identified activity in the left inferior frontal gyrus that was positively correlated with PF. No effects of PF were found in temporal lobe regions. We propose that the observed phonotactic effects during speech listening reflect the strength of the association between acoustic speech patterns and articulatory speech codes involving phoneme level units. On the basis of existing lesion evidence, we interpret the function of this auditory–motor association as playing a role primarily in production. These findings are consistent with the view that phoneme level units are not necessarily accessed during speech recognition.
Economics of photovoltaic solar power and uptake in New Zealand

Responding to the global challenges of maintaining energy security while combatting climate change, the New Zealand government has issued a target of generating 90% of the country’s electricity needs from renewable sources by 2025. With much of New Zealand’s generation already provided by hydro, geothermal and wind, questions remain as to whether this target should be achieved by more widely adopting solar photovoltaics (PV) into the energy mix. Following from previous GREEN Grid research into the uptake of solar PV in New Zealand, this paper considers the economics of PV generation at a variety of scales: residential rooftop; commercial rooftop; and ground-mount utility. For each scale, discounted cash-flows were used to assess system costs and financial returns, and levelized cost of energy used to compare with other sources of generation. In the case of residential generation, there is a significant difference in the value of energy which is locally consumed versus that which is grid-exported. Consequently the value of PV to a household depends on the consumption patterns of a particular household. To understand the value across different households, typical residential load profiles were found by clustering load profiles from over 2,000 houses, and resulting representative load profiles used to estimate financial returns based on the energy consumption patterns. The paper concludes that PV is now a commercially attractive investment for some types of households, but that household load makes a major difference to the returns. In the commercial sector PV is also commercially attractive to the company making the investment in some cases, and for both residential and commercial, returns are very sensitive to discount rate, location, and type of retail tariff. However for both residential and commercial, improving energy efficiency is a lower cost option than PV, and should be considered first. At the utility scale PV is not yet commercially attractive, even excluding transmission and distribution charges and opportunity cost of land. However if the cost of PV continues to fall,
Effect of diet and individual dietary guidance on gastrointestinal endocrine cells in patients with irritable bowel syndrome (Review)

Irritable bowel syndrome (IBS) is a common chronic gastrointestinal (GI) disorder that is characterized by a combination of abdominal pain or discomfort, bloating and alterations in bowel movements. This review presents recent developments concerning the roles of diet and GI endocrine cells in the pathophysiology of IBS and of individual dietary guidance in the management of IBS. Patients with IBS typically report that food aggravates their IBS symptoms. The interactions between specific types of foodstuffs rich in fermentable oligosaccharides, disaccharides, monosaccharides and polyols (FODMAPs) and GI endocrine cells induce changes in cell densities. Providing individual dietary guidance about a low FODMAP intake, high soluble-fiber intake, and changing the proportions of protein, fat and carbohydrates helps to reduce the symptoms experienced by patients with IBS and to improve their quality of life. These improvements are due to restoring the densities of the GI endocrine cells back to normal. The reported observations emphasize the role of GI endocrine cells in the pathophysiology of IBS and support the provision of dietary guidance as a first-line treatment for managing IBS.
Flexible Droplet Routing in Active Matrix–Based Digital Microfluidic Biochips

The active matrix (AM)-based architecture offers many advantages over conventional digital electrowetting-on-dielectric (EWOD) microfluidic biochips, such as the capability of handling variable-size droplets, more flexible droplet movement, and precise control over droplet navigation. However, a major challenge in choosing the routing paths is to decide when the droplets are to be reshaped depending on the congestion of the intended path, or split- and route sub droplets,and merging them at their respective destinations. As the number of microelectrodes in AM-EWOD chips is large, the path selection problem becomes further complicated. In this article, we propose a negotiation-guided flow based on routing of subdroplets that obviates the explicit need for deciding when the droplets are to be manipulated, yet fully utilizing the power of droplet reshaping, splitting, and merging them to facilitate their journey. The proposed algorithm reduces routing cost and provides more freedom in deadlock avoidance in the presence of multiple routing tasks by assigning certain congestion penalty for sibling subdroplets and fluidic penalty for heterogeneous droplets. Compared to existing techniques, it reduces latest arrival time by an average of 29% for several benchmark and random test suites. Furthermore, our method is observed to provide 100% routability of nets for all test cases, whereas existing and baseline routers fail to produce feasible solutions in many instances. We also propose a reliable mode droplet routing strategy where the number of unreliable splitting operations can be reduced by paying a small penalty on latest arrival time.
An ISO-surface folding analysis method applied to premature neonatal brain development

In this paper we describe the application of folding measures to tracking in vivo cortical brain development in premature neonatal brain anatomy. The outer gray matter and the gray-white matter interface surfaces were extracted from semi-interactively segmented high-resolution T1 MRI data. Nine curvature- and geometric descriptor-based folding measures were applied to six premature infants, aged 28-37 weeks, using a direct voxelwise iso-surface representation. We have shown that using such an approach it is feasible to extract meaningful surfaces of adequate quality from typical clinically acquired neonatal MRI data. We have shown that most of the folding measures, including a new proposed measure, are sensitive to changes in age and therefore applicable in developing a model that tracks development in premature infants. For the first time gyrification measures have been computed on the gray-white matter interface and on cases whose age is representative of a period of intense brain development.
Data Extraction and Annotation Methods Using Tag Value Structure

: The World Wide Web generates search result pages which is based . On the user’s input query. It is very crucial for many applications like data integration which requires combining more databases to automatically extract the data from the search results. A unique method for extracting the data and then aligning is implemented which uses Unsupervised duplicate detection algorithm which identifies and segments the result records first and then aligns the segmented results in a table , in which data values of similar attributes are put in same column. The new technique is implemented so as to handle the case when the search results are not adjoining which might happen because of auxiliary data such as advertisements ,comments etc. and also to handle nested tag structure which might be present in the search results. The result shows that the implemented algorithm performs well than existing methods.
Crowdsourcing the character of a place: Character‐level convolutional networks for multilingual geographic text classification

This article presents a new character‐level convolutional neural network model that can classify multilingual text written using any character set that can be encoded with UTF‐8, a standard and widely used 8‐bit character encoding. For geographic classification of text, we demonstrate that this approach is competitive with state‐of‐the‐art word‐based text classification methods. The model was tested on four crowdsourced data sets made up of Wikipedia articles, online travel blogs, Geonames toponyms, and Twitter posts. Unlike word‐based methods, which require data cleaning and pre‐processing, the proposed model works for any language without modification and with classification accuracy comparable to existing methods. Using a synthetic data set with introduced character‐level errors, we show it is more robust to noise than word‐level classification algorithms. The results indicate that UTF‐8 character‐level convolutional neural networks are a promising technique for georeferencing noisy text, such as found in colloquial social media posts and texts scanned with optical character recognition. However, word‐based methods currently require less computation time to train, so currently are preferable for classifying well‐formatted and cleaned texts in single languages.
Facebook Reaction-Based Emotion Classifier as Cue for Sarcasm Detection

Online social media users react to content in them based on context. Emotions or mood play a significant part of these reactions, which has filled these platforms with opinionated content. Different approaches and applications to make better use of this data are continuously being developed. However, due to the nature of the data, the variety of platforms, and dynamic online user behavior, there are still many issues to be dealt with. It remains a challenge to properly obtain a reliable emotional status from a user prior to posting a comment. This work introduces a methodology that explores semi-supervised multilingual emotion detection based on the overlap of Facebook reactions and textual data. With the resulting emotion detection system we evaluate the possibility of using emotions and user behavior features for the task of sarcasm detection. More than 1 million English and Chinese comments from over 62,000 public Facebook pages posts have been collected and processed, conducted experiments show acceptable performance metrics.
A simulation model for space-time-frequency variant fading channels

We apply the Monte-Carlo simulation model to a frequency selective fading channel including space-variance. This model is suited to simulate the performance of a multi-antenna system for a moving receiver (or transmitter). It takes into account that the time-variance of the channel due to this motion has its origin in the space-variance. We emphasize that for such a channel, time and frequency correlations cannot be separated.
Background complexity and the detectability of camouflaged targets by birds and humans

Remaining undetected is often key to survival, and camouflage is a widespread solution. However, extrinsic to the animal itself, the complexity of the background may be important. This has been shown in laboratory experiments using artificially patterned prey and backgrounds, but the mechanism remains obscure (not least because ‘complexity’ is a multifaceted concept). In this study, we determined the best predictors of detection by wild birds and human participants searching for the same cryptic targets on trees in the field. We compared detection success to metrics of background complexity and ‘visual clutter’ adapted from the human visual salience literature. For both birds and humans, the factor that explained most of the variation in detectability was the textural complexity of the tree bark as measured by a metric of feature congestion (specifically, many nearby edges in the background). For birds, this swamped any effects of colour match to the local surroundings, although for humans, local luminance disparities between the target and tree became important. For both taxa, a more abstract measure of complexity, entropy, was a poorer predictor. Our results point to the common features of background complexity that affect visual search in birds and humans, and how to quantify them.
Detecting Decision Ambiguity from Facial Images

In situations when potentially costly decisions are being made, faces of people tend to reflect a level of certainty about the appropriateness of the chosen decision. This fact is known from the psychological literature. In the paper, we propose a method that uses facial images for automatic detection of the decision ambiguity state of a subject. To train and test the method, we collected a large-scale dataset from "Who Wants to Be a Millionaire? " -- a popular TV game show. The videos provide examples of various mental states of contestants, including uncertainty, doubts and hesitation. The annotation of the videos is done automatically from on-screen graphics. The problem of detecting decision ambiguity is formulated as binary classification. Video-clips where a contestant asks for help (audience, friend, 50:50) are considered as positive samples; if he (she) replies directly as negative ones. We propose a baseline method combining a deep convolutional neural network with an SVM. The method has an error rate of 24%. The error of human volunteers on the same dataset is 45%, close to chance.
Completeness of death-count coverage and adult mortality (45q15) for Brazilian states from 1980 to 2010.

Objective: Assess the completeness of the DataSUS SIM death-count registry, by sex and Brazilian state, and estimate the probability of adult mortality (45q15), by sex and state, from 1980 to 2010. Methods: The study was based on mortality data obtained in the DataSUS Mortality Information System, from 1980 to 2010, and on population data from the 1980, 1991, 2000, and 2010 demographic censuses. The quality assessment of the registry data was conducted using traditional demographic and death distribution methods, and death probabilities were calculated using life-table concepts. Results: The results show a considerable improvement in the completeness of the death-count coverage in Brazil since 1980. In the southeast and south, we observed the complete coverage of the adult mortality registry, which did not occur in the previous decade. In the northeast and north, there were still places with a low coverage from 2000 to 2010, although there was a clear improvement in the quality of data. For all Brazilian states, there was a decline in the probability of adult mortality; we observed, however, that the death probability for males is much higher than that for females throughout the whole analysis period. Conclusion: The observed improvements seem to be related to investments in the public health care system and administrative procedures to improve the recording of vital events.
Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images

Computer-aided Diagnosis (CAD) systems for the automatic identification of abnormalities in retinal images are gaining importance in diabetic retinopathy screening programs. A huge amount of retinal images are collected during these programs and they provide a starting point for the design of machine learning algorithms. However, manual annotations of retinal images are scarce and expensive to obtain. This paper proposes a dynamic CAD system based on active learning for the automatic identification of hard exudates, cotton wool spots and drusen in retinal images. An uncertainty sampling method is applied to select samples that need to be labeled by an expert from an unlabeled set of 4000 retinal images. It reduces the number of training samples needed to obtain an optimum accuracy by dynamically selecting the most informative samples. Results show that the proposed method increases the classification accuracy compared to alternative techniques, achieving an area under the ROC curve of 0.87, 0.82 and 0.78 for the detection of hard exudates, cotton wool spots and drusen, respectively.
Radiodensitometric study for evaluation of bone mineral density around dental implants after zoledronic acid treatment in ovariectomized rats

Background The purpose of this study was to evaluate the effects of intravenous zoledronic acid applied systemically on osseointegration of dental implants and the surrounding bone mineral density (BMD) in the ovariectomized rats. Material and Methods 36 rats were divided into three groups: control (CTRL), ovariectomy (OVX), and ovariectomy-zoledronic acid (OVX/ZOL). The rats in the CTRL group underwent sham surgery, while rats in OVX and OVX / ZOL group underwent ovariectomy. After 12 weeks, rats from OVX / ZOL were injected with 0.04 mg/kg ZOL intravenously once a week for 6 weeks. The rats from CTRL and OVX groups were injected with 0.9% NaCl. Implants were placed in the left tibia. After 8 weeks, rats were sacrificed and tibia bones were removed for radiodensitometric examination. Digital radiographs of bones’ lateral surface were taken. The BMD was measured by using radiographic analysis software. Results Statistically significant differences were found between all groups (p<0.05). While highest mean BMD values were observed in the CTRL group, the lowest were in the OVX group. Conclusions The systemic use of ZOL has increased the bone density around the implants inserted osteoporotic rat tibia. Key words:Bisphosphonate, bone density, dental implants, osteoporosis.
Nanoelectromechanical systems

Nanoelectromechanical systems (NEMS) are nano-to-micrometer scale mechanical resonators coupled to electronic devices of similar dimensions. NEMS show promise for fast, ultrasensitive force microscopy and for deepening our understanding of how classical dynamics arises by approximation to quantum dynamics. This article begins with a survey of NEMS and then describes certain aspects of their classical dynamics. In particular, we show that for weak coupling the action of the electronic device on the mechanical resonator can be effectively that of a thermal bath, this despite the device being a driven, far-from-equilibrium system.
You Tweet What You Speak: A City-Level Dataset of Arabic Dialects

Arabic has a wide range of varieties or dialects . Although a number of pioneering works have targeted some Arabic dialects, other dialects remain largely without investigation. A serious bottleneck for studying these dialects is lack of any data that can be exploited in computational models. In this work, we aim to bridge this gap: We present a considerably large dataset of > 1 / 4 billion tweets representing a wide range of dialects. Our dataset is more nuanced than previously reported work in that it is labeled at the ﬁne-grained level of city. More speciﬁcally, the data represent 29 major Arab cities from 10 Arab countries with varying dialects (e
Orthogonal frequency division multiple access with cyclic delay diversity

Cyclic delay diversity is a simple transmit diversity technique for coded OFDM systems with multiple transmit antennas. It does neither require an extended guard interval nor modifications of the standard OFDM receiver. We discuss the problem of choosing the cyclic delays and propose a solution which enables to exploit the full spatial diversity in flat fading and frequency-selective channels with unknown delay spread. As a result, the spatial diversity is transformed into frequency diversity between neighbouring subcarriers. This imposes certain restrictions to the channel coding and interleaving scheme. Furthermore, we address multi user aspects and propose an interleaving and multiple access strategy which guarantees that all users obtain the maximum possible diversity advantage using FEC codes with a limited constraint length. A performance comparison shows that space-time block codes outperform cyclic delay diversity on the expense of higher complexity and lower flexibility.
Factors in fl uencing industrial carbon emissions and strategies for carbon mitigation in the Yangtze River Delta of China

The Yangtze River Delta is one of the most industrialized regions in China. This study characterizes the spatial and temporal patterns of industrial carbon emissions (ICE) produced by secondary industry sectors in the region from 2000 to 2014. The scale and nature of ICE is measured from five aspects (involving 12 factors): gross industrial output value (GIOV), energy intensity (EI), energy structure (ES), industrial structure (IS) and the structure of industrial enterprises (the number and scale). The study establishes three panel models to analyze the effects of 12 factors on ICE at the county level. The results show that ICE increased dramatically, being 2.1 times the 2000 level (135.94 Mt CO2) in this region by 2014. The major carbon sources are the consumptions of raw coal and electricity, accounting for more than three quarters of the total ICE during the 2000e2014 period. ICE presents great spatial disparities across 66 counties in the region, being highly coincident with the Z-shaped distribution of the urban clusters in the delta. The GIOV is a major contributor to ICE growth in this region, increasing by 84.1 tC for an increase of one million yuan of GIOV. The adjustment of ES, EI and the structure of industrial enterprises can largely abate ICE. Regulating industrial structure and energy structure, reducing energy intensity and optimizing the structure of industrial enterprises are suggested as imperative measures for carbon mitigation in the region. © 2016 Elsevier Ltd. All rights reserved.