Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing emotional speech synthesizers with limited speech database

This paper describes an emotional speech synthesis system based on HMMs and related modeling techniques. For concatenative speech synthesis, we require all of the concatenation units that will be used to be recorded beforehand and made available at synthesis time. To adopt this approach for synthesizing the wide variety of human emotions possible in speech, implies that this process should be repeated for every targeted emotion making this task challenging and time consuming. In this paper, we propose an emotional speech synthesis technique based on HMMs, especially for the case where only limited amount of training data is available, directly incorporating subjective evaluation results performed on the training data. Listening results performed on the synthesized speech suggest that the proposed technique helps to improve the emotional content of synthesized speech.
Soil Aggregate Stability and Grassland Productivity Associations in a Northern Mixed-Grass Prairie

Soil aggregate stability data are often predicted to be positively associated with measures of plant productivity, rangeland health, and ecosystem functioning. Here we revisit the hypothesis that soil aggregate stability is positively associated with plant productivity. We measured local (plot-to-plot) variation in grassland community composition, plant (aboveground) biomass, root biomass, % water-stable soil aggregates, and topography. After accounting for spatial autocorrelation, we observed a negative association between % water-stable soil aggregates (0.25–1 and 1–2 mm size classes of macroaggregates) and dominant graminoid biomass, and negative associations between the % water-stable aggregates and the root biomass of a dominant sedge (Carex filifolia). However, variation in total root biomass (0–10 or 0–30 cm depths) was either negatively or not appreciably associated with soil aggregate stabilities. Overall, regression slope coefficients were consistently negative thereby indicating the general absence of a positive association between measures of plant productivity and soil aggregate stability for the study area. The predicted positive association between factors was likely confounded by variation in plant species composition. Specifically, sampling spanned a local gradient in plant community composition which was likely driven by niche partitioning along a subtle gradient in elevation. Our results suggest an apparent trade-off between some measures of plant biomass production and soil aggregate stability, both known to affect the land’s capacity to resist erosion. These findings further highlight the uncertainty of plant biomass-soil stability associations.
Vitamin D Status and Glucose Homeostasis in the 1958 British Birth Cohort

OBJECTIVE—Obesity is a well-known risk factor for vitamin D deficiency. We evaluated the interrelationship between vitamin D status, body size, and glucose homeostasis, measured by HbA1c (A1C). RESEARCH DESIGN AND METHODS—Data are from the survey of the 45-year-old 1958 British birth cohort (2002–2004). Information on A1C, 25-hydroxyvitamin D [25(OH)D; an indicator of vitamin D status], and BMI was collected from 7,198 Caucasian subjects. RESULTS—25(OH)D was <75 nmol/l in 80% of the obese subjects (BMI ≥30 kg/m2) versus 68% of the other subjects (P < 0.0001). Serum 25(OH)D decreased and A1C increased by increasing BMI (P < 0.0001 for both comparisons). There was a nonlinear association between 25(OH)D and A1C: a steep linear decrease in A1C by 25(OH)D until 65 nmol/l and only smaller decreases with further increases. There was evidence for effect modification by BMI in the association between 25(OH)D and A1C (P < 0.0001), and differences appeared stronger for participants with higher compared with lower BMIs. After adjustment for sex, season, geographical location, physical activity, and social class, percent change in A1C by 10-nmol/l increase in 25(OH)D was −0.21 (95% CI −0.31 to −0.11) for BMI <25 kg/m2, −0.25 (−0.37 to −0.13) for BMI 25–29.9 kg/m2, −0.65 (−0.95 to −0.34) for BMI 30–34.9 kg/m2, and −1.37 (−2.09 to −0.64) for BMI ≥35 kg/m2. CONCLUSIONS—Body size was a strong determinant for 25(OH)D, with concentrations being suboptimal in most obese participants. Randomized controlled trials [using dosages sufficient to improve 25(OH)D also for the obese] are required to determine whether clinically relevant improvements in glucose metabolism can be obtained by vitamin D supplementation.
Evaluating Information Content by Factoid Analysis: Human annotation and stability

We present a new approach to intrinsic sum-mary evaluation, based on initial experiments in van Halteren and Teufel (2003), which combines two novel aspects: comparison of information content (rather than string similarity) in gold standard and system summary, measured in shared atomic information units which we call factoids , and comparison to more than one gold standard summary (in our data: 20 and 50 summaries respectively). In this paper, we show that factoid annotation is highly re-producible, introduce a weighted factoid score, estimate how many summaries are required for stable system rankings, and show that the factoid scores cannot be su–ciently approximated by unigrams and the DUC information overlap measure.
Representing Languages in UML - A UML Profile for Language Engineering

Abstract: In this paper a UML profile for textual concrete syntax specification is described. The profile provides the necessary elements to associate the concrete syntax of a language L to an abstract syntax model of L. Such augmented abstract syntax model is called the language model of L. This language model avoids keeping the abstract and concrete syntaxes synchronized. We take advantage of the similarities between object oriented modeling and BNF-based language specification, and use a profile to specify the dissimilarities.
Applying a component-based framework to develop multi-agent environments: case study

This paper introduces an infrastructure for engineering environments for multi-agent systems. Such an infrastructure is based on a component model specification, named CMS, which promotes dynamic unanticipated evolution of software. We propose an Agent Model Specification (AMS), focusing on environment engineering issues. Moreover, we present a Java framework that implements AMS and a case study to exemplify the application of our approach.
Bayesian Network Automata for Modelling Unbounded Structures

This paper proposes a framework which unifies graphical model theory and formal language theory through automata theory. Specifically, we propose Bayesian Network Automata (BNAs) as a formal framework for specifying graphical models of arbitrarily large structures, or equivalently, specifying probabilistic grammars in terms of graphical models. BNAs use a formal automaton to specify how to construct an arbitrarily large Bayesian Network by connecting multiple copies of a bounded Bayesian Network. Using a combination of results from graphical models and formal language theory, we show that, for a large class of automata, the complexity of inference with a BNA is bounded by the complexity of inference in the bounded Bayesian Network times the complexity of inference for the equivalent stochastic automaton. This illustrates that BNAs provide a useful framework for developing and analysing models and algorithms for structure prediction.
Automatic extraction signature sequence of unknown network application

This paper presents a novel approach to automatically extract network application signature sequence from sessions of any application to identify the application accurately. Performance metrics such as identification rate and precision rate are applied to verity the extracted signature sequences. Experiment results show that this method is effective and the extracted signature sequences are subtle. Therefore it can be used to accurately identify the corresponding application.
TRPA1 Channels Mediate Cold Temperature Sensing in Mammalian Vagal Sensory Neurons: Pharmacological and Genetic Evidence

Cold thermoreceptors have been described in different territories of the vagus nerve. Application of cold temperature to these visceral afferents can evoke major protective reflexes and thermoregulatory responses. However, virtually nothing is known about the transduction mechanisms underlying cold sensitivity in vagal afferents. Here, we investigated the effects of cold stimulation on intracellular calcium responses and excitability of cultured vagal sensory neurons in the rat nodose ganglion. A large fraction of vagal neurons were activated by cold, with a mean threshold of ∼24°C. Cooling was accompanied by development of a small inward current and the firing of action potentials. Most cold-sensitive neurons were also activated by heat and capsaicin, suggesting a nociceptive function. The pharmacological response to TRPM8 and TRPA1 agonists and antagonists suggested that, unlike results observed in somatic tissues, TRPA1 is the major mediator of cold-evoked responses in vagal visceral neurons. Thus, most cold-evoked responses were potentiated by cinnamaldehyde, menthol, icilin, and BCTC [4-(3-chloro-pyridin-2-yl)-piperazine-1-carboxylic acid (4-tert-butyl-phenyl)-amide], agonists of TRPA1, and were inhibited by ruthenium red, camphor, and HC03001 [2-(1,3-dimethyl-2,6-dioxo-1,2,3,6-tetrahydro-7H-purin-7-yl)-N-(4-isopropylphenyl)acetamide]. Results in mouse nodose neurons revealed a similar pharmacological profile of cold-evoked responses. Furthermore, experiments in TRPA1 knock-out mice showed a large reduction in the percentage of cold-sensitive neurons compared with wild-type animals. Together, these results support an important role of TRPA1 channels in visceral thermosensation and indicate major differences in the transduction of temperature signals between somatic and visceral sensory neurons.
Secure and Privacy-Preserving , Timed Vehicular Communication

In this paper we consider the problem of privacy and security in vehicular (V2V) communication, in particular securing routine safety messages . Traditional public key mechanisms are not appropriate for such applications because of the large number of safety messages that have to be transmitted by each vehicle, typically one message every 100−300 ms. We first show that a recently proposed V2V communication scheme, TSVC, based on the Time Efficient Stream Loss-tolerant Authentication (TESLA) scheme is subject to an impersonation attack in which the adversary can distribute misleading safety information to vehicles, and propose a modification that secures it against such attacks. We then address general concerns regarding the inappropriateness of TESLA for vehicular applications (caused by the delayed authentication, and buffer overflow issues), and propose a V2V communication scheme based on a variant of TESLA, TESLA , in which packets are self-authenticating. This scheme is appropriate for applications in which vehicles are in close proximity. Finally we consider a hybrid protocol that combines both schemes and addresses in a more flexible way the mobility requirements of V2V communications.
Prefrontal Cholinergic Mechanisms Instigating Shifts from Monitoring for Cues to Cue-Guided Performance: Converging Electrochemical and fMRI Evidence from Rats and Humans

We previously reported involvement of right prefrontal cholinergic activity in veridical signal detection. Here, we first recorded real-time acetylcholine release in prefrontal cortex (PFC) during specific trial sequences in rats performing a task requiring signal detection as well as rejection of nonsignal events. Cholinergic release events recorded with subsecond resolution (“transients”) were observed only during signal-hit trials, not during signal-miss trials or nonsignal events. Moreover, cholinergic transients were not observed for consecutive hits; instead they were limited to signal-hit trials that were preceded by factual or perceived nonsignal events (“incongruent hits”). This finding suggests that these transients mediate shifts from a state of perceptual attention, or monitoring for cues, to cue-evoked activation of response rules and the generation of a cue-directed response. Next, to determine the translational significance of the cognitive operations supporting incongruent hits we used a version of the task previously validated for use in research in humans and blood oxygenation level-dependent (BOLD)-functional magnetic resonance imaging. Incongruent hits activated a region in the right rostral PFC (Brodmann area 10). Furthermore, greater prefrontal activation was correlated with faster response times for incongruent hits. Finally, we measured tissue oxygen in rats, as a proxy for BOLD, and found prefrontal increases in oxygen levels solely during incongruent hits. These cross-species studies link a cholinergic response to a prefrontal BOLD activation and indicate that these interrelated mechanisms mediate the integration of external cues with internal representations to initiate and guide behavior.
Comprehensive Analysis of Edge Detection in Color Image Processing

Various approaches to edge detection for color images, including techniques extended from monochrome edge detection as well as vector space approaches, are examined. In particular, edge detection techniques based on vector order statistic operators and difference vector operators are studied in detail. Numerous edge detectors are obtained as special cases of these two classes of operators. The effect of distance measures on the performance of different color edge detectors is studied by employing distance measures other than the Euclidean norm. Variations are introduced to both the vector order statistic opera-tors and the difference vector operators to improve noise performance. They both demonstrate the ability to attenuate noise with added algorithm complexity. Among them, the difference vector operator with adaptive filtering shows the most promising results. Other vector directional filtering techniques are also introduced and utilized for color edge detection. Both quantitative and subjective tests are performed in evaluating the performance of the edge detectors, and a detailed comparison is presented.Copyright 1999 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
Is the Core of M87 the Source of Its TeV Emission? Implications for Unified Schemes

M87 has recently been shown to be a TeV source that is likely to be variable. Based on this and on contemporaneous optical and X-ray monitoring, we argue that the source of the TeV emission is the core of M87 and not one of two jet knots (HST-1 and A), with an X-ray brightness comparable to that of the core. We model the TeV emission in the core as inverse Compton (IC) emission from the base of the jet. Homogeneous models fail to reproduce the spectral energy distribution (SED) and, in particular, the TeV flux. They also fail to comply with the unified scheme of BL Lacertae (BL) objects and FR I radio galaxies. A jet that decelerates from a Lorentz factor Γ ~ 20 down to Γ ~ 5 over a length of ~0.1 pc reproduces the observed SED of the M87 core and, when aligned with the line of sight, produces a SED similar to those of TeV BLs. The TeV flux in the decelerating jet model is successfully reproduced as upstream Compton (UC) scattering, a recently identified emission mechanism, in which energetic electrons of the upstream faster flow upscatter the low-energy photons produced in the slower downstream part of the flow.
Estimating incremental dimensional algorithm with sequence data set

Recently, there has been enormous growth in the amount of commercial and scientific data, such as protein sequences, retail transactions, and web-logs. In this paper, the scholar proposes a new approach for robust hierarchical clustering based on the distance function between each data object and the cluster centers. This method avoids the need to compute the distance of each data object to the cluster center. It saves running time. The experimental results showed that the best clusters were obtained using EIDA method, this suggests that this similarity measure would be applicable to sequence data sets.
Revitalizing Peale's Museum as a digital interactive learning environment

This paper raises awareness about Charles Willson Peale's late 18th and early 19th century Philadelphia Museum of Art and Science and describes a project that reimagines it as a 21st century digital interactive learning environment for cultural heritage and Science Technology Engineering Art Mathematics (STEAM) learning. The project seeks to establish 3 sites of engagement and discuses ongoing research towards automating experience management in interactive learning environments (TAEMILE) a necessary step in operationalizing the Peale Museum's K-12 site of engagement.
A Meta-cognitive Interval Type-2 fuzzy inference system classifier and its projection based learning algorithm

In this paper, we present a Meta-cognitive Interval Type-2 neuro-Fuzzy Inference System (McIT2FIS) classifier and its projection based learning algorithm. McIT2FIS consists of two components, namely, a cognitive component and a meta-cognitive component. The cognitive component is an Interval Type-2 neuro-Fuzzy Inference System (IT2FIS) represented as a six layered adaptive network realizing Takagi-Sugeno-Kang type inference mechanism. IT2FIS begins with zero rules, and rules are added and updated depending on the relative knowledge represented by the sample in comparison to that represented by the cognitive component. The knowledge representation ability of IT2FIS is controlled by a self-regulatory learning mechanism that forms the meta-cognitive component. As each sample is presented to the network, the meta-cognitive component monitors the hinge-loss error and class-specific spherical potential of the current sample to decide what-to-learn, when-to-learn and how-to-learn them, efficiently. When a new rule is added or when an existing rule is updated, a Projection Based Learning (PBL) algorithm uses class specific criterion and sample overlap criterion to estimate the network parameters corresponding to the minimum energy point of the error function. The performance of McIT2FIS is evaluated on a set of benchmark classification problems from UCI machine learning repository. The statistical performance comparison with other algorithms available in the literature indicates improved performance of McIT2FIS.
A TSK-Type-Based Self-Evolving Compensatory Interval Type-2 Fuzzy Neural Network (TSCIT2FNN) and Its Applications

In this paper, a Takagi-Sugeno-Kang (TSK)-type-based self-evolving compensatory interval type-2 fuzzy neural network (FNN) (TSCIT2FNN) is proposed for system modeling and noise cancellation problems. A TSCIT2FNN uses type-2 fuzzy sets in an FNN in order to handle the uncertainties associated with information or data in the knowledge base. The antecedent part of each compensatory fuzzy rule is an interval type-2 fuzzy set in the TSCIT2FNN, where compensatory-based fuzzy reasoning uses adaptive fuzzy operation of a neural fuzzy system to make the fuzzy logic system effective and adaptive, and the consequent part is of the TSK type. The TSK-type consequent part is a linear combination of exogenous input variables. Initially, the rule base in the TSCIT2FNN is empty. All rules are derived according to online type-2 fuzzy clustering. For parameter learning, the consequent part parameters are tuned by a variable-expansive Kalman filter algorithm to the reinforce parameter learning ability. The antecedent type-2 fuzzy sets and compensatory weights are learned by a gradient descent algorithm to improve the learning performance. The performance of TSCIT2FNN for the identification is validated and compared with several type-1 and type-2 FNNs. Simulation results show that our approach produces smaller root-mean-square errors and converges more quickly.
Dihydrodaidzein-producing Clostridium-like intestinal bacterium, strain TM-40, affects in vitro metabolism of daidzein by fecal microbiota of human male equol producer and non-producers

Much attention has been focused on the biological effects of equol, a metabolite of daidzein produced by intestinal microbiota. However, little is known about the role of isoflavone metabolizing bacteria in the intestinal microbiota. Recently, we isolated a dihydrodaidzein (DHD)-producing Clostridium-like bacterium, strain TM-40, from human feces. We investigated the effects of strain TM-40 on in vitro daidzein metabolism by human fecal microbiota from a male equol producer and two male equol non-producers. In the fecal suspension from the male equol non-producer and DHD producer, DHD was detected in the in vitro fecal incubation of daidzein after addition of TM-40. The DHD concentration increased as the concentration of strain TM-40 increased. In the fecal suspension from the equol producer, the fecal equol production was increased by the addition of strain TM-40. The occupation ratios of Bifidobacterium and Lactobacillales were higher in the equol non-producers than in the equol producer. Adding isoflavone-metabolizing bacteria to the fecal microbiota should facilitate the estimation of the metabolism of isoflavonoids by fecal microbiota. Studies on the interactions among equol-producing microbiota and DHD-producing bacteria might lead to clarification of some of the mechanisms regulating the production of equol by fecal microbiota.
Exploring Chance in NCAA Basketball

There seems to be an upper limit to predicting the outcome of matches in (semi-)professional sports. Recent work has proposed that this is due to chance and attempts have been made to simulate the distribution of win percentages to identify the most likely proportion of matches decided by chance. We argue that the approach that has been chosen so far makes some simplifying assumptions that cause its result to be of limited practical value. Instead, we propose to use clustering of statistical team profiles and observed scheduling information to derive limits on the predictive accuracy for particular seasons, which can be used to assess the performance of predictive models on those seasons. We show that the resulting simulated distributions are much closer to the observed distributions and give higher assessments of chance and tighter limits on predictive accuracy.
S 1904 Social Networks in Emergency Response Social Networks in Emergency Response

Dashun Wang1; 2, Yu-Ru Lin3; 4, and James P. Bagrow5; 6 1Center for Complex Network Research, Northeastern University, Boston, MA, USA 2Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA, USA 3College of Computer and Information Science, Northeastern University, Boston, MA, USA 4Institute for Quantitative Social Science, Harvard University, Cambridge, MA, USA 5Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA 6Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL, USA
LEPSCAN - a web server for searching latent periodicity in DNA sequences

UNLABELLED A web server for searching latent periodicity based on the method of modified profile analysis has been developed. This method allows searching latent periodicity in presence of insertions and deletions. During searching process, the periodicity classes are used which were found by us earlier for various groups of organisms. Period length belongs to the range 2-20 nt, not including the triplet periodicity. The results obtained are subjected to various filtration steps to ensure their statistical significance. AVAILABILITY The use of web server is free for non-commercial users. No registration is required. URL of the server is http://victoria.biengi. ac.ru/lepscan. Current software version is 1.06.