Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding speaking styles of internet speech data with LSTM and low-resource training

Speech are widely used to express one's emotion, intention, desire, etc. in social network communication, deriving abundant of internet speech data with different speaking styles. Such data provides a good resource for social multimedia research. However, regarding different styles are mixed together in the internet speech data, how to classify such data remains a challenging problem. In previous work, utterance-level statistics of acoustic features are utilized as features in classifying speaking styles, ignoring the local context information. Long short-term memory (LSTM) recurrent neural network (RNN) has achieved exciting success in lots of research areas, such as speech recognition. It is able to retrieve context information for long time duration, which is important in characterizing speaking styles. To train LSTM, huge number of labeled training data is required. While for the scenario of internet speech data classification, it is quite difficult to get such large scale labeled data. On the other hand, we can get some publicly available data for other tasks (such as speech emotion recognition), which offers us a new possibility to exploit LSTM in the low-resource task. We adopt retraining strategy to train LSTM to recognize speaking styles in speech data by training the network on emotion and speaking style datasets sequentially without reset the weights of the network. Experimental results demonstrate that retraining improves the training speed and the accuracy of network in speaking style classification.
Variability in TDCS electric fields: Effects of electrode size and configuration

Variability in the efficacy of transcranial direct-current stimulation (TDCS) may be affected by variations in electric fields, which depend on both experimental parameters and individual anatomical features of the head and brain. Electrode configurations that minimize inter-subject differences in electric fields would be useful for controlling variability in experimental TDCS studies. This study investigated the effects of electrode size and configuration on the variability in the electric fields. Individual MRI-based models of 44 subjects and the finite-element method were used. Motor cortical TDCS was modelled for four electrode montages.
The Araucaria Project: The Effect of Blending on the Cepheid Distance to NGC 300 from Advanced Camera for Surveys Images

We have used the Advanced Camera for Surveys aboard the Hubble Space Telescope (HST) to obtain F435W, F555W, and F814W single-epoch images of six fields in the spiral galaxy NGC 300. Taking advantage of the superb spatial resolution of these images, we have tested the effect that blending of the Cepheid variables studied from the ground with close stellar neighbors, unresolved on the ground-based images, has on the distance determination to NGC 300. Out of the 16 Cepheids included in this study, only three are significantly affected by nearby stellar objects. After correcting the ground-based magnitudes for the contribution by these projected companions to the observed flux, we find that the corresponding period-luminosity relations in V, I, and the Wesenheit magnitude WI are not significantly different from the relations obtained without corrections. We fix an upper limit of 0.04 mag to the systematic effect of blending on the distance modulus to NGC 300. As part of our HST imaging program, we present improved photometry for 40 blue supergiants in NGC 300.
Discriminative Alignment Training without Annotated Data for Machine Translation

In present Statistical Machine Translation (SMT) systems, alignment is trained in a previous stage as the translation model. Consequently, alignment model parameters are not tuned in function of the translation task, but only indirectly. In this paper, we propose a novel framework for discriminative training of alignment models with automated translation metrics as maximization criterion. In this approach, alignments are optimized for the translation task. In addition, no link labels at the word level are needed. This framework is evaluated in terms of automatic translation evaluation metrics, and an improvement of translation quality is observed.
Optimal tracking control for a peltier refrigeration system based on PSO

Peltier refrigeration system is a typical nonlinear control affine system with unknown bounded perturbations. An optimal tracking control scheme based on PSO is proposed for the refrigeration system. Firstly, the mathematical model of the Peltier refrigeration system is built. Secondly, operator-based robust controller is designed to ensure robust stability of the system by using robust right coprime factorization method. Then, a tracking compensator operator is presented by using PSO (Particle Swarm Optimization) method to satisfy the tracking performance of the system. Finally, numerical simulation and experimental results are given to confirm the effectiveness of the proposed approach.
Evaluating coverage based intention selection

The Belief Desire Intention (BDI) agent paradigm provides a powerful basis for developing complex systems based on autonomous intelligent agents. These agents have, at any point in time, a set of intentions, the various tasks the agent is working on which represent the agent's multiple focus of attention. Despite its importance for intelligent behaviour, the problem of selecting which intention to progress at any point in time has received almost no attention and has been left to the programmer to resolve in an application-dependent manner. In this paper we implement and evaluate a previous proposal for domain-independent intention selection using the notion of plan ``coverage,'' as well as a slight variation which we predicted to perform better. We compare these with the commonly used intention selection mechanisms of First-In-First-Out FIFO and Round Robin RR. We show that the coverage-based technique performs better under all circumstances, but particularly with low coverage and volatile environments. Interestingly, we found that a simple one-step look-ahead applicability check is responsible for the largest part of the improvement. This is important in that this can readily be applied to FIFO and RR, giving an extremely simple and effective mechanism to be added to existing BDI frameworks.
Real-time audio-visual voice activity detection for speech recognition in noisy environments

Voice activity detection (VAD) is one of the most critical issues on performance degradation of speech recognition in noisy environment applications. A real-time VAD was developed by using face parameters (eye and lip contours) as a front-end for the traditional speech and noise (audio) GMMbased method. Speech recognition performance of the audiovisual VAD is shown to be comparable with audio-only VAD, for a shopping mall background noise. Advantages and limitations of introducing the visual information are discussed.
Multi-component Word Sense Disambiguation

This paper describes the system MC-WSD presented for the English Lexical Sample task. The system is based on a multicomponent architecture. It consists of one classiﬁer with two components. One is trained on the data provided for the task. The second is trained on this data and, additionally, on an external training set extracted from the Wordnet glosses. The goal of the additional component is to lessen sparse data problems by exploiting the information encoded in the ontology.
EVALUATION OF DIFFERENT SUTURING TECHNIQUES FOR CYSTOTOMY CLOSURE IN CANINES

The experimental cystotomy was performed on 24 mongrel dogs, divided in to four groups i.e. group A, B, C and D comprising 6 dogs in each group. In group-A, cystotomy wound was closed in one layer by simple continues suturing pattern, in group-B, closure was made in two layers by simple continues and lembert suturing pattern and in group-C, cystomy incision was closed by one layer simple continues suturing pattern and two layers of inverting suturing patterns . Group-D was kept as control group. All three closure techniques were evaluated for leakage with the help of contrast radiography, ultrasonography, renal function tests and physi ological parameters. Comparison of three techniques concluded that single-layer cystotomy closure is preferable in small animals because it ensure water tight closure with a good quality of wound healing and requires shorter time.
Human Cerebellum: Surface-Assisted Cortical Parcellation and Volumetry with Magnetic Resonance Imaging

We describe a system of surface-assisted parcellation (SAP) of the human cerebellar cortex derived from neural systems functional and behavioral anatomy. This system is based on MRI and preserves the unique morphologic and topographic features of the individual cerebellum. All major fissures of the cerebellum were identified and traced in the flattened representation of the cerebellar cortex using the program Free Surfer. Parcellation of the cerebellar cortex followed using the fissure information in conjunction with landmarks using the program Cardviews to create 64 gyral-based cerebellar parcellation units. Computer-assisted algorithms enable the execution of the cerebellar parcellation procedure as well as volumetric measurements and topographic localization. The SAP technique makes it possible to represent multimodal structural and functional imaging data on the flattened surface of the cerebellar cortex as illustrated in one functional MRI experiment.
A Review of Thin Layer Drying of Foods: Theory, Modeling, and Experimental Results

Drying is a complicated process with simultaneous heat and mass transfer, and food drying is especially very complex because of the differential structure of products. In practice, a food dryer is considerably more complex than a device that merely removes moisture, and effective models are necessary for process design, optimization, energy integration, and control. Although modeling studies in food drying are important, there is no theoretical model which neither is practical nor can it unify the calculations. Therefore the experimental studies prevent their importance in drying and thin layer drying equations are important tools in mathematical modeling of food drying. They are practical and give sufficiently good results. In this study first, the theory of drying was given briefly. Next, general modeling approaches for food drying were explained. Then, commonly used or newly developed thin layer drying equations were shown, and determination of the appropriate model was explained. Afterwards, effective moisture diffusivity and activation energy calculations were expressed. Finally, experimental studies conducted in the last 10 years were reviewed, tabulated, and discussed. It is expected that this comprehensive study will be beneficial to those involved or interested in modeling, design, optimization, and analysis of food drying.
Differential Modulation of Neuron Survival during Development by Nerve Growth Factor Binding to the p75 Neurotrophin Receptor*

Nerve growth factor (NGF) supports the survival and differentiation of distinct populations of peripheral and central neurons. NGF binds to two classes of cell-surface receptors, the protein tyrosine kinase TrkA and the smaller p75 receptor lacking intrinsic catalytic activity. It has been suggested that both receptors are required for NGF high affinity binding, although TrkA appears to be sufficient for transducing most of the biological effects of NGF. Some evidence suggests that p75 could play a modulatory role on TrkA activation by an as yet unknown mechanism. In this study, we have investigated functional roles of p75 using a purified triple mutant NGF (triNGF) deficient in p75 binding but retaining significant TrkA binding and activation. The mutant was found to be as potent as wild type NGF at promoting survival of serum-deprived TrkA-expressing fibroblasts. On developing chick sensory neurons, survival responses to mutant and native NGF were indistinguishable when assayed at nanomolar concentrations. However, triNGF was 3- to 4-fold less potent than wild type NGF at lower concentrations (i.e. 10−11 m). Interestingly, in PC12 cells coexpressing TrkA and p75, no high affinity binding sites for triNGF could be detected. The reduced responsiveness to triNGF in sensory neurons was increasingly evident at later developmental stages; late embryonic neurons did not respond at all to concentrations of triNGF that were saturating at earlier developmental stages. Likewise, although no difference could be seen between wild type and mutant NGF on the survival responses of embryonic rat superior cervical ganglion sympathetic neurons, the mutant was much less potent than native NGF on postnatal sympathetic neurons. In sensory neurons, the decrease in responsiveness to triNGF correlated with a developmental reduction in the expression of both p75 and TrkA. Thus, NGF binding to p75 enhances responsiveness to ligand, particularly when this is present at limiting concentrations. During development, p75 modulates responsiveness to NGF so that binding to p75 becomes increasingly important in neurons undergoing a down-regulation of NGF receptors. These results support a ligand-dependent modulatory role for p75 in NGF-mediated neuron survival consistent with p75 functioning as a TrkA regulator and/or signaling receptor.
From Journals to Journalism: Tracing Trajectories of Literate Development

Drawn from a longitudinal ethnographic study, this article elaborates the trajectories linking one undergraduates extracurricular journaling to her school writing and her emerging identity as a journalist. This portrait of literate development highlights how our sense of ourselves as literate persons is forged in the interplay of multiple encounters with literacy, private as well as public, and how authoring a literate life means engaging in the ongoing work of reconciling the conflicts and synergies among them.
Dimension affective de la relation enseignant-élève : effet sur l’adaptation psychosociale des adolescents (motivations, empathie, adaptation scolaire et violence) et rôle déterminant de l’amour compassionnel des enseignants

A l'etranger, nombre de travaux longitudinaux en psychologie de l'education montrent que la relation affective enseignant-eleve (RAEE) est benefique tant a l'ecole (reussite, perseverance, comportement, etc.) qu'en dehors (baisse de depression, anxiete, delinquance, etc.) (Fortin, Plante & Bradley, 2011). En revanche, ses determinants ont ete peu etudies et le role de l'engagement affectif des enseignants sur la RAEE n'a pas ete evalue. Le present travail, inspire de la theorie de l'attachement (Bowlby, 1969), vise a combler cette lacune en mobilisant le concept d'amour compassionnel (Underwood, 2008). En France, ou aucune etude quantitative sur le sujet n'a ete realisee jusque la, la RAEE est polemique, voire tabou. Ses effets ne pourraient-ils pas etre testes empiriquement ? La theorie des trois systemes de motivation (Favre & Favre, 1993) permet ici de comprendre et de mesurer l'effet de la RAEE sur les adolescents.Apres validation aupres d'enseignants (N = 275) d'une version francaise de l'echelle d'amour compassionnel (Sprecher & Fehr, 2005) envers les eleves, il apparait que celle-ci est predictive de la RAEE (STRS, Pianta, 2001). Cette these valide aussi aupres de collegiens (N = 145) un outil psychometrique visant a evaluer trois systemes de motivation. Complete par d'autres instruments evaluant l'adaptation psychosociale (empathie, variables scolaires et violence), il est soumis a deux echantillons (113 collegiens et 104 collegiens de SEGPA) : la RAEE favorise la motivation d'innovation, l'empathie et l'adaptation scolaire tout en protegeant contre la motivation de securisation parasitee (ou d'addiction), l'indiscipline scolaire et la violence. Cela plaide pour une approche relationnelle, telle que promue par les theoriciens du care en education, et, au-dela, pour une psychologie positive de l'education.
On the Relation between Maximum Spectra Boundaries

Earlier research has shown that the maximum spectral transition positions are related with the perceptual critical points that contain the most important information for consonant and syllable perception. This paper presents a quantitative analysis of the relation, in time, between the maximum spectral transition positions and the phone boundaries in fluent read speech. This analysis is based on the training part of the TIMIT American English database which contains both phone boundaries and labels manually-determined by a group of experts. The results of this analysis show that there is a significant correlation between the maximum spectral transition positions and the manually selected phone boundaries. This, in turn, suggests that there is an important relation between the commonly accepted phone boundaries and the perceptual critical points.
Wisdom and the Context of Knowledge: Knowing that One Doesn’t Know

The question raised is whether the traditional model of intelligence is adequate for understanding the course of intellectual development in adulthood and old age and, in particular, for capturing that quality of adult thought referred to as wisdom. In the first of two sections, a brief historical survey of changing conceptions of intelligence is provided, concluding with a critique of the traditional, accumulation model of intelligence. This traditional model neglects uncertainties, doubts, and questions and the role of social transactions in the construction of knowledge. In the second section, a definition of wisdom is advanced and illustrated. An alternative model of growth and development of knowledge is referred to as a knowledge-context model, in order to emphasize that the meaning and value of any knowledge depends upon the context within which that knowledge is known. The context includes not only other knowledge, but also gaps in the framework of knowledge. Wisdom is defined as a balance between increases in the amount that one knows and simultaneous increases in the recognition that there is much that one does not know. The challenge of wisdom is to maintain this balance between acquiring more knowledge, on the one hand, and discovering new uncertainties, doubts, and questions, on the other.
Genetic Regulatory Network Identification Using Monotone Functions Decomposition

Abstract We present a method for identification of gene regulatory network topology using a time series of gene expression data. The underlying assumption in our method is that the functions that describe regulatory relations must be continuous, nonnegative and monotonic. This assumption is very general, as it is satisfied by virtually all existing regulatory models. Our method is based on refuting all regulation hypotheses that cannot meet this assumption. This procedure takes the form of a Linear Programming (LP) feasibility problem. We also present two conditions where the regulation hypotheses are irrefutable.
The Stan Math Library: Reverse-Mode Automatic Differentiation in C++

As computational challenges in optimization and statistical inference grow ever harder, algorithms that utilize derivatives are becoming increasingly more important. The implementation of the derivatives that make these algorithms so powerful, however, is a substantial user burden and the practicality of these algorithms depends critically on tools like automatic differentiation that remove the implementation burden entirely. The Stan Math Library is a C++, reverse-mode automatic differentiation library designed to be usable, extensive and extensible, efficient, scalable, stable, portable, and redistributable in order to facilitate the construction and utilization of such algorithms. Usability is achieved through a simple direct interface and a cleanly abstracted functional interface. The extensive built-in library includes functions for matrix operations, linear algebra, differential equation solving, and most common probability functions. Extensibility derives from a straightforward object-oriented framework for expressions, allowing users to easily create custom functions. Efficiency is achieved through a combination of custom memory management, subexpression caching, traits-based metaprogramming, and expression templates. Partial derivatives for compound functions are evaluated lazily for improved scalability. Stability is achieved by taking care with arithmetic precision in algebraic expressions and providing stable, compound functions where possible. For portability, the library is standards-compliant C++ (03) and has been tested for all major compilers for Windows, Mac OS X, and Linux.
CrossStitch: An Efﬁcient Transaction Processing Framework for Geo-Distributed Systems Technical Report - CS-2015-08

Current transaction systems for geo-distributed datastores either have high transaction processing latencies or are unable to support general transactions with dependent operations. In this paper, we introduce CrossStitch, an efﬁcient transaction processing framework that reduces latency by re-structuring each transaction into a chain of state transitions, where each state consists of a key operation and computation. Transaction states are processed sequentially, and the transaction code and data is sent directly to the next hop in the chain. CrossStitch transactions can be organized such that all states in a location are processed before transitioning to a state in a different location. This allows CrossStitch to signiﬁcantly reduce the number of inter-location crossings compared to transaction systems that retrieve remote data to a single location for processing. To provide transactional properties while preserving the chain communication pattern, CrossStitch introduces a pipelined commit protocol that executes in parallel with the transaction and does not require any centralized coordination. Our evaluation results show that CrossStitch can reduce the latency of geo-distributed transactions when compared to a traditional 2PC-based distributed transaction system. We demonstrate that CrossStitch can reduce the number of round trips by more than half for TPC-C-like transactions.
Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes

Collaborative beamforming has been recently introduced in the context of wireless sensor networks (WSNs) to increase the transmission range of individual sensor nodes. The challenge in using collaborative beamforming in WSNs is the uncertainty regarding the sensor node locations. However, the actual sensor node spatial distribution can be modeled by a properly selected probability density function (pdf). In this paper, we model the spatial distribution of sensor nodes in a cluster of WSN using Gaussian pdf. Gaussian pdf is more suitable in many WSN applications than, for example, uniform pdf which is commonly used for flat ad hoc networks. The average beampattern and its characteristics, the distribution of the beampattern level in the sidelobe region, and the distribution of the maximum sidelobe peak are derived using the theory of random arrays. We show that both the uniform and Gaussian sensor node deployments behave qualitatively in a similar way with respect to the beamwidths and sidelobe levels, while the Gaussian deployment gives wider mainlobe and has lower chance of large sidelobes.