Miracle-dz/UniFAR-FTUs huggingface dataset:
Vocal interactions at the dawn of communication: The emergence of mutuality and complementarity in mother-infant interaction

Continuous interaction of mother and infant in the first weeks and months of an infant's life entrains the infant on many crucial aspects of how to do things together. Contingencies of gaze, vocalizations, and other movements are slowly routinized; this scaffolds directing of attention to each other and the world and gives to such multimodal interactions meaning. It is within these continuous interactions with caregivers that language emerges, starting from the first non-reflexive vocalizations that infants produce. The response that caregivers promptly give to these vocalizations informs infants of their relevance and helps shape them. We explored this systematicity by observing the coupling of infants' and mothers' vocalizations in unconstrained interactions longitudinally. While at three months, mothers seem to answer consistently to any speech related vocalization within the first two seconds, this pattern fades away at six and eight months. What remains stable across age is a structure in which overlapping vocalizations are rare and give way to a sequential pattern of vocal reciprocity — an embryonic turn-taking behavior. Discussion relates this finding to early coordination in other modalities in an attempt to sketch a more holistic account of emerging co-action.
Synoptic to Microscale Processes Affecting the Evolution of a Cold-Air Pool in a Northern New England Forested Mountain Valley

The formation of katabatic winds and pooling of cold air in mountain valleys impact air quality, precipitation type, and local ecosystem functions. Much is still poorly understood about the multiscale interaction of processes in a mature mixed-hardwood forest that cause the formation and evolution of cold-air pools (CAPs). Processes involved in the evolution of a CAP in the Hubbard Brook Experimental Forest valley in New Hampshire were investigated during a field campaign on 4–5 November 2015. Vertical profiles of temperature and humidity were measured along a 150-m-long tethered balloon in the center of the valley and were compared with temperature and wind observations on the surrounding slopes to identify and assess the impacts of multiscale processes on a CAP. A CAP formed rapidly during the afternoon of 4 November and attained its maximum depth of ~150 m by sunset. This maximum depth is likely a result of the topography of the valley. Warm-air advection (WAA) occurred during the second half of the night at high elevations, and warm air mixed downward into the valley. As a result, the vertical thermal gradient strengthened and static stability increased, which allowed the lowest part of the CAP to continue to radiatively cool while the upper part of the CAP was warmed and eroded by the WAA. Results suggest that the canopy acts as the primary cooling surface for air at night, which causes split katabatic flow: cold and fast flow above canopy and warmer and slower flow below canopy. Understanding these processes in sloped forests has implications for eddy covariance research and montane microclimates.
Stimulus timing for a stimulating medical device

Methods and systems are disclosed for determining the timing of applied stimulation using a medical device. In embodiments, the medical device filters a received signal to obtain a plurality of band-pass filtered signals, each corresponding to one or more stimulation channels. The medical device then determines the envelopes of these band-pass filtered signals. Next, the medical device determines the stimulation timing (i.e., the pulse times) for the corresponding stimulation channel based on the timing of a particular phase (e.g., a peak, a minimum, etc.) of the envelope. A pulse amplitude for the stimulation channel may then be determined, and applied stimulation is determined by using the determined amplitude and pulse time.
Uncertainty quantification in vehicle dynamics

ABSTRACT This paper presents a review of various works that highlight the importance of introducing the variability of the road-track/vehicle system into dynamic simulations as soon as this latter is meant to be predictive. The first section of the paper presents the Uncertainty Quantification, Verification and Validation method (UQ-VV). This latter proposes tools to model uncertainties, to associate a confidence to the prediction of quantities of interest and to estimate the probability of occurrence of different scenarios. The method is illustrated by various examples mainly from the rail domain but also from the road sector. The second section summarises application examples of predictive modelling, robust optimisation and calibration.
Power quality disturbances classification by ensemble and hybrid Neural networks

A novel ensemble neural network structure is presented for automatic classification of power quality disturbances. Power quality (PQ) disturbances analysis is the focus of power quality control. The characteristics of PQ disturbances include short duration, variety of types and so on. Power quality disturbances classification is the foundation of power quality control automation. Different types of Neural network, such as BP neural networks, RBF neural networks and probabilistic neural network etc, is already applied in the area of PQ disturbances classification and recognition. The researches about the neural network for PQ disturbances recognition are mainly focused on the optimizing for the signal type of neural network. But the accuracy rate of the classification is still needed to be improved. Ensemble and hybrid algorithms research is currently flourishing in pattern classification machine learning and decision sciences. Compare to traditional NN, the ensemble and hybrid NN classifier achieves higher classification rate. In this paper, a novel PQ classification system using S-transform and ensemble and hybrid NN is designed. There are 2 stages in the novel system. Firstly, the PQ disturbances signals are transformed by S-transform and the subset of features extracted from the result of S-transform is used as the input vector of the ensemble and hybrid NN. Secondly in the pattern classification process, BP network and RBF neural network are utilized as two classification agents. Through choosing different parameters and different samples, every agent includes a group of neural networks. The classification results, generated by different agents, are fuzzified into fuzzy numbers. The centroid of all fuzzy numbers is compared with the threshold. Finally we obtain the classification results. In the simulation, 6 types of disturbances signals which are simulated by Matlab 7.0 use for test the new classification system. Simulation result shows that when the new system has better classification rate especially at the high noising environment.
Efficiently Patrolling Hamiltonian and Two-Connected Graphs

We present two probabilistic patrolling strategies for a single agent patrolling an undirected graph. A single ant-like agent with very low capabilities is considered, the agent have small memory and he can sense only its neighborhood. However, he may mark the graph vertices with pheromone stamps which can later be sensed. These markings are used as a primitive form of distributed memory. The first algorithm presented is designed to patrol Hamiltonian graphs. By executing the proposed algorithm, the agent finds a Hamilton cycle and follows it. By following the cycle, the agent performs an optimal patrol. The second algorithm we present aims to patrol graphs whose square is Hamiltonian. Using the algorithm, the agent finds a cycle of length at most 2|G| and follows it. The maximum time lag between two successive visits to any vertex using the proposed strategy is at most twice the optimal so the patrol quality is at least half the optimal.
Analyzing Peer Specific Power Saving in IEEE 802.11s Through Queuing Petri Nets: Some Insights and Future Research Directions

The IEEE 802.11s wireless mesh networking standard supports power save mode where a mesh station can switch from the awake state to the doze state when there is no data to transmit. In the standard, the doze state is peer specific and has two different modes of operations - light sleep mode and deep sleep mode. This paper analytically evaluates the performance of a mesh basic service set under the operation of different power save modes, with the help of a queuing Petri net modeling. The analytical model gives several insights of the power save mode operations, which are further validated using simulation results as well as results from a practical mesh networking testbed. Our analysis reveals that there exists interesting performance tradeoffs among light sleep mode and deep sleep mode, that can be explored to design an efficient power profile for mesh networks.
Preschool Children's Performance in Task Switching on the Dimensional Change Card Sort Task: Separating the Dimensions Aids the Ability to Switch

Fifty-seven children (53% female) at 3 ages (2 1/2, 3, and 3 1/2 years) were tested on the standard Dimensional Change Card Sort (DCCS) task with integrated stimuli (e.g., a red truck) and on a separated-dimensions version where colorless shapes were presented on a colored background (e.g., a black truck on a red background). Roughly twice as many children successfully switched sorting dimensions when color was a property of the background than when color was a property of the shape itself. Children succeeded 6 months earlier in switching sorting criteria when the dimensions were separated. When evidence of both indecision and accuracy was taken into account, a clear and rich developmental progression emerged. These results support an inhibitory control interpretation of preschoolers' problems on the DCCS task. Diamond theorized that young children can have difficulty integrating features not part of a single object and separating features of a single object so that the object can be categorized first by one attribute and then by another. Preschoolers remain stuck in thinking about objects according to the objects' initially relevant attribute (attentional inertia; Kirkham, Cruess, & Diamond, 2003). To switch perspectives, the old way of thinking about the objects must be inhibited. Separating color and shape reduced the need for such inhibition; a truck was always a truck, and the background was always red.
The dominant role of surface functionalization in carbon dots’ photo-activated antibacterial activity

Background: Carbon dots (CDots) have recently been demonstrated their effective visible light-activated antimicrobial activities toward bacteria. This study was to evaluate and understand the roles of the surface functionalities in governing the antimicrobial activity of CDots. Methods: Using the laboratory model bacteria Bacillus subtilis, the photo-activated antimicrobial activities of three groups of CDots with specifically selected different surface functionalization moieties were evaluated and compared. The first group consisting of CDots with surface functionalization by 2,2-(ethylenedioxy)bis(ethylamine) (EDA) vs. 3-ethoxypropylamine (EPA), was evaluated to determine the effect of different terminal groups/charges on their photo-activated antibacterial activities. The second group consisting of CDots functionalized with oligomeric polyethylenimine (PEI) and those prepared by the carbonization of PEI – citric acid mixture, was to evaluate the effects of dot surface charges vs. fluorescent quantum yields on their antimicrobial activities. The third group consisting of CDots functionalized with PEI of 1,200 vs. 600 in average molecular weight was evaluated for the effect of molecular weight of surface passivation molecular on their antimicrobial activities. Results: The results indicated the EDA-CDots in the first group was more effective and was attributed to the positive charges from the protonation of the amino groups (–NH2) being more favorable to interactions with bacterial cells. The evaluation of the second group CDots suggested the same surface charge effect dominating the antibacterial performance over the fluorescent quantum yields. The evaluation of the third group CDots functionalized with PEI of 1,200 vs. 600 in average molecular weight, indicated the latter was significantly more effective. Conclusions: The results from this study highlighted the dominant role of surface functionalities in governing CDots’ light activated antimicrobial activity and should have significant implications to the further design and development of CDots as a new class of visible light-activated antibacterial agents.
Stochastically Constrained Simulation Optimization On Integer Lattices : The cgR-SPLINE Algorithm

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A Sociomaterial View of the Scaffolding of Work Practices with Information Technology

This paper builds on the concept of sociomateriality to investigate different modalities by which information technology may scaffold work practices. Taking into account the constitutive entanglement of both the social and the material, the authors identify a model to map emergent work practices through which IT use unfolds. An investigation of mobile IT usage in 10 companies indicates a model of four modalities of behaviors: (1) When people perceive that the mobile technology supports their local needs, they will use it in the prescribed way; (2) when they perceive that the mobile technology can produce additional advantages, they augment its use beyond that prescribed; (3) when possible, people use unprescribed technologies to complement their prescribed mobile technology; and (4) people use unprescribed mobile technology to scaffold their work and limit their use of the prescribed IT as much as possible.
Information Theoretic Exemplification of the Impact of Transmitter-Receiver Cognition on the Channel Capacity

In this paper, we study, information theoretically, the impact of transmitter and or receiver cognition on the channel capacity. The cognition can be described by state information, dependent on the channel noise and or input. Specifically, as a new idea, we consider the receiver cognition as a state information dependent on the noise and we derive a capacity theorem based on the Gaussian version of the Cover-Chiang capacity theorem for two-sided state information channel. As intuitively expected, the receiver cognition increases the channel capacity and our theorem shows this increase quantitatively. Also, our capacity theorem includes the famous Costa theorem as its special cases.
ALLEVIATION OF ANTI-NUTRITIVE COMPONENTS OF BAMBOO SHOOT THROUGH FERMENTATION

The increasing trends of health consciousness among consumers have stimulated the field of functional foods. The plant based functional foods or food constituents have been investigated for their role in disease prevention and have dazzled the scientific community with its potentiality and “Bamboo” is one of them. Bamboo is not popular as food but is consumed fresh, fermented or canned. The young shoots are rich in nutrients and nutraceuticals which make it an important food with numerous health benefits. Keeping in view the unexplored and unutilized potential of bamboo shoot as food, an attempt has been made for biochemical profiling of raw bamboo shoot and its fermented product. An increase in non reducing sugar, total starch and cellulose content was observed in the fermented product whereas a significant decrease in antinutritive factors phytic acid, tannins and cyanogens was observed as a result of fermentation. The decreases in antinutritive factors suggest that fermented products are more suitable for consumption. * Corresponding author KEYWORDS
A Homogenized Energy Model for Hysteresis in Ferroelectric Materials: General Density Formulation

In this article, we construct a framework for modeling hysteresis and constitutive nonlinearities in ferroelectric compounds based on energy analysis at mesoscopic scales in combination with stochastic homogenization techniques to construct macroscopic models. In the first step of the development, previous analysis is used to construct Helmholtz and Gibbs energy relations at the lattice level. This provides local polarization relations that can be extrapolated to provide constitutive models for certain homogeneous, single crystal compounds. To incorporate material and field nonhomogeneities, as well as the effects of polycrystallinity, certain parameters in the local models are assumed to be manifestations of underlying distributions having densities which must be identified for a given compound. Two techniques for estimating the unknown densities are presented, and the accuracy of the resulting model is illustrated for both symmetric major loops and biased minor loops through fits and predictions with experimental PZT4 and PZT5H data.
Recurrent Neural Networks for Decoding Lip Read Speech

The success of automated lip reading has been constrained by the inability to distinguish between homopheme words, which are words have different characters and produce the same lip movements (e.g. ”time” and ”some”), despite being intrinsically different. One word can often have different phonemes (units of sound) producing exactly the viseme or visual equivalent of phoneme for a unit of sound. Through the use of a Long-Short Term Memory Network with word embeddings, we can distinguish between homopheme words or words that produce identical lip movements. The neural network architecture achieved a character accuracy rate of 77.1% and a word accuracy rate of 72.2%.
Mining User Queries for Image Search using Click-through Approach

The analysis of user serach for a query can be useful in improving search engine performance. Although the text search has received much importance but a little attention has been proposed for image search. In this paper, we propose influencing advantage of click session information, Click-through logs maintain clicked images information. The visual information of clicked images is used to infer user-image search goals. The Click session information can be used as past users’ implicit guidance for clustering the images, more precise user search goals can be obtained. “Classification” based approach is proposed for autoclassification of user image search. Experimental results demonstrate the effectiveness of the proposed method.
Bioclimatic Analysis and Spatial Distribution of Livestock Fascioliasis in Iran

Background: This study aimed to investigate the prevalence of fascioliasis and to perform a climatological analysis of different regions of Iran based on the current situation of the parasite and its intermediate host using Geographical Information System (GIS). Methods: Meteorological data were obtained from Iran Meteorological Organization. Risk map of fascioliasis transmission was prepared based on this data and using forecasting indices. Further, the number of fascioliasis cases from 31 provinces reported to the Iran Veterinary Organization were collected and prevalence maps of livestock fascioliasis were drawn. Results: The main risk hotspots were found in Northern provinces like Golestan, Mazandaran and Gilan as well as some Southern provinces such as Kohgiluyeh and Boyer-Ahmad and Chaharmahal and Bakhtiari and Fars, which have ideal conditions for completion of the parasite life cycle. Moreover, Gilan Province with 10.83% had the highest rate of fascioliasis infection in slaughtered animal. Conclusion: Iran is one of the most important foci of fascioliasis globally. Several provinces of Iran have appropriate conditions for evolution of parasite life cycle and presence of its intermediate host. These regions require special attention and serious determination in order to control fascioliasis in human and animals.
Risk factors for and influence of bloodstream infections on mortality: a 1-year prospective study in a Greek intensive-care unit

SUMMARY To determine the incidence, risk factors for, and the influence of bloodstream infections (BSIs) on mortality of patients in intensive-care units (ICUs), prospectively collected data from all patients with a stay in an ICU >48 h, during a 1-year period, were analysed. Of 572 patients, 148 developed a total of 232 BSI episodes (incidence 16·3 episodes/1000 patient-days). Gram-negative organisms with high level of resistance to antibiotics were the most frequently isolated pathogens (157 strains, 67·8%). The severity of illness on admission, as estimated by APACHE II score (OR 1·07, 95% CI 1·04–1·1, P<0·001), the presence of acute respiratory distress syndrome (OR 3·57, 95% CI 1·92–6·64, P<0·001), and a history of diabetes mellitus (OR 2·37, 95% CI 1·36–4·11, P=0·002) were risk factors for the occurrence of BSI whereas the development of an ICU-acquired BSI was an independent risk factor for death (OR 1·76, 95% CI 1·11–2·78, P=0·015). Finally, the severity of organ dysfunction on the day of the first BSI episode, as estimated by SOFA score, and the level of serum albumin, independently affected the outcome (OR 1·44, 95% CI 1·22–1·7, P<0·001 and OR 0·47, 95% CI 0·23–0·97, P=0·04 respectively).
Finite Time Blow-up for the 3D Incompressible Euler Equations

We prove the finite time blow-up for solutions of the 3D incompressible Euler equations, which happens along the fluid particle trajectories starting from a set of points. This set is specified by the relation between the deformation tensor and the Hessian of pressure both coupled with the vorticity directions, associated with the initial data. As a corollary of this result we prove the finite time blow-up of the Taylor-Green vortex solution. AMS Subject Classification Number: 35Q35, 76B03
Large‐Scale Gene‐Centric Analysis Identifies Polymorphisms for Resistant Hypertension

Background Resistant hypertension (RHTN), defined by lack of blood pressure (BP) control despite treatment with at least 3 antihypertensive drugs, increases cardiovascular risk compared with controlled hypertension. Yet, there are few data on genetic variants associated with RHTN. Methods and Results We used a gene‐centric array containing ≈50 000 single‐nucleotide polymorphisms (SNPs) to identify polymorphisms associated with RHTN in hypertensive participants with coronary artery disease (CAD) from INVEST‐GENES (the INnternational VErapamil‐SR Trandolapril STudy—GENEtic Substudy). RHTN was defined as BP≥140/90 on 3 drugs, or any BP on 4 or more drugs. Logistic regression analysis was performed in European Americans (n=904) and Hispanics (n=837), using an additive model adjusted for age, gender, randomized treatment assignment, body mass index, principal components for ancestry, and other significant predictors of RHTN. Replication of the top SNP was conducted in 241 European American women from WISE (Women's Ischemia Syndrome Evaluation), where RHTN was defined similarly. To investigate the functional effect of rs12817819, mRNA expression was measured in whole blood. We found ATP2B1 rs12817819 associated with RHTN in both INVEST European Americans (P‐value=2.44×10−3, odds ratio=1.57 [1.17 to 2.01]) and INVEST Hispanics (P=7.69×10−4, odds ratio=1.76 [1.27 to 2.44]). A consistent trend was observed at rs12817819 in WISE, and the INVEST‐WISE meta‐analysis result reached chip‐wide significance (P=1.60×10−6, odds ratio=1.65 [1.36 to 1.95]). Expression analyses revealed significant differences in ATP2B1 expression by rs12817819 genotype. Conclusions The ATP2B1 rs12817819 A allele is associated with increased risk for RHTN in hypertensive participants with documented CAD or suspected ischemic heart disease. Clinical Trial Registration URL: www.clinicaltrials. gov; Unique identifiers: NCT00133692 (INVEST), NCT00000554 (WISE).