Miracle-dz/UniFAR-FTUs huggingface dataset:
Análise do conteúdo e aparência do protocolo de acompanhamento fonoaudiológico - aleitamento materno

RESUMO Objetivo Analisar conteúdo e aparência do Protocolo de Acompanhamento Fonoaudiológico – Aleitamento Materno e elaborar um guia instrucional para o instrumento. Métodos Estudo do tipo exploratório, de natureza quantitativa. Participaram cinco avaliadores especialistas, com ampla experiência em atuação fonoaudiológica relacionada à Neonatologia, que analisaram conteúdo e aparência do protocolo, que abordam aspectos maternos, neonatais e da díade mãe/recém-nascido, além de orientações gerais e específicas da Fonoaudiologia, relacionadas à amamentação, A análise estatística foi realizada por meio do Índice de Validade de Conteúdo, com nível de concordância de 70%. Na segunda rodada, o instrumento foi analisado pelos mesmos especialistas, por meio da escala de Likert, com cinco posições (concordo plenamente, concordo, indiferente, discordo e discordo totalmente). Resultados Foram 15 itens acrescentados, sete modificados, cinco excluídos e um tópico adicionado. Obteve-se alto nível de concordância, sendo as respostas distribuídas em “concordo” e “concordo plenamente” (92% - conteúdo e 100% - aparência). A descrição do guia instrucional foi realizada a partir da versão analisada do protocolo. Conclusão A análise do conteúdo e aparência do protocolo, bem como a elaboração do seu guia instrucional, pretendem possibilitar sua utilização de modo consistente e sistemático no campo fonoaudiológico relacionado ao aleitamento materno, abordando tanto o registro da avaliação, como do acompanhamento da díade mãe/recém-nascido, na situação de amamentação. Ressalta-se a importância de serem realizadas as próximas etapas da validação do protocolo.
Computers and Mathematics with Applications the Evaluation of Barrier Option Prices under Stochastic Volatility

Keywords: Barrier option Stochastic volatility Continuously monitored Discretely monitored Free boundary problem Method of lines a b s t r a c t This paper considers the problem of numerically evaluating barrier option prices when the dynamics of the underlying are driven by stochastic volatility following the square root process of Heston (1993) [7]. We develop a method of lines approach to evaluate the price as well as the delta and gamma of the option. The method is able to efficiently handle both continuously monitored and discretely monitored barrier options and can also handle barrier options with early exercise features. In the latter case, we can calculate the early exercise boundary of an American barrier option in both the continuously and discretely monitored cases.
The relationship between episodic memory and context: clues from memory errors made while under stress.

In a series of studies in the late 1950s and early 1960s, Jan Bures introduced cortical spreading depression to the field of behavioral neuroscience (eg. Bures 1960). This technique offered a unique way to study the role of cortex in learning and memory, and attracted the attention of many who began their graduate studies at that time, including one of us (LN, cf. Nadel 1966). An NIH postdoctoral fellowship to study with the master himself brought LN to Prague in September 1967. Thus began a relationship that included science, politics, and personal life, and has lasted over 30 years1,2. The first scientific exchange began with Jan pulling a piece of paper from his desk with a long list of possible experiments written on it -- “pick one”, he said. This led to a series of studies on interhemispheric transfer of learning under conditions of monocular input, demonstrating, amongst other things, that such transfer is not a uniform process. Depending on the kind of trials given with both hemispheres intact, and the eye which remained open to input, transfer can either be non-specific, likely involving some kind of procedural knowledge, or highly specific, likely involving knowledge about the trained discrimination itself (Nadel and Buresova, 1970). These studies anticipated LN’s future work on multiple memory systems, a research enterprise pursued in the following decades by many labs (including LN’s: e.g. Nadel and O’Keefe 1974, O’Keefe et al. 1975). In this paper we focus on several scientific issues that Jan has been thinking about for the past 25 years. In particular, we consider spatial learning, the hippocampus, and memory. To this mix we add stress, something well known to anyone living in Prague in 1968. LN left Prague after the 1968 invasion and stayed in London for seven months, during which time arrangements were made for an eventual return to the Medical Research Council Cerebral Functions Research Group in 1970. Thus it was that LN happened to be down the hall when John O’Keefe and Jonathan Dostrovsky discovered place cells (O’Keefe and Dostrovsky 1971) and began the program of research leading to the cognitive map theory of hippocampal function (O’Keefe and Nadel 1978).
Quantization and Reconstruction of Sources with Memory

A fundamental problem in telecommunications is the reliable transmission of a source over a noisy channel. As an important result of the Shannon’s celebrated paper [1], the problem can be theoretically separated, without loss of optimality, into two parts: source coding and channel coding. However, in practise, due to the strict design constraints, such as the limitations on complexity of the systems involved, the joint design of source and channel coders has found increasing interest. This thesis deals with the design of efficient reliable communication systems with a particular emphasis on practical issues such as complexity and delay. A low bit-rate low complexity Block-based Trellis Quantization (BTQ) scheme is proposed for the quantization of speech spectrum in speech coding applications. The proposed scheme is based on the modeling of the LSF intraframe dependencies with a trellis structure. The BTQ search and design algorithms are discussed and an efficient algorithm for the index generation is proposed. Extensive comparisons with several other techniques from the literature are provided. Efficient source decoding schemes are presented, which take advantage of the residual redundancy in the source coder output stream as a bandwidth efficient way to combat the noisy channel degradations. This falls into the category of joint source channel (de)coding. In this part, a family of solutions is proposed for the asymptotically optimum Minimum Mean Squared Error (MMSE) reconstruction of a source over memoryless noisy channels when the residual redundancy is exploited by use of a γ-order Markov model (γ ≥ 1) and a delay of δ is allowed in the decoding process. Considering the same problem setup, several other simplified MMSE and maximum a posteriori symbol and sequence decoders are also presented. The problem of reconstruction of the predictively quantized signals over a noisy iv channel is also considered. As well, methods for the reconstruction of speech encoded with the Enhanced Full Rate Codec (EFRC, IS-641) and transmitted over a noisy channel are presented. A methodology to efficiently approximate and store the a priori probabilities characterizing the residual redundancies is introduced. Numerical results are presented which demonstrate the efficiency of the proposed algorithms.
How do Educators of Students With Disabilities in Specialist Settings Understand and Apply the Australian Curriculum Framework?

Despite aspirations to be a world-class national curriculum, the Australian Curriculum (AC) has been criticised as ‘manifestly deficient’ (Australian Government Department of Education and Training, 2014 p. 5) as an inclusive curriculum, failing to meet the needs of all students with disabilities (SWD) and their teachers. There is a need for research into the daily attempts of educators to navigate the tension between a ‘top-down’ system-wide curriculum and a ‘bottom-up’ regard for individual student needs, with a view to informing both policy and practice. This article is the first of two research papers in which we report the findings from a national online Research in Special Education (RISE) Australian Curriculum Survey of special educators in special schools, classes, and units regarding their experience using the AC to plan for and teach SWD. Survey results indicated (a) inconsistent use of the AC as the primary basis for developing learning objectives and designing learning experiences, (b) infrequent use of the achievement standards to support assessment and reporting, and (c) considerable supplementation of the AC from other resources when educating SWD. Overall, participants expressed a lack of confidence in translating the AC framework into a meaningful curriculum for SWD. Implications for policy, practice, and future research are discussed.
Infected Dendritic Cells Facilitate Systemic Dissemination and Transplacental Passage of the Obligate Intracellular Parasite Neospora caninum in Mice

The obligate intracellular parasite Neospora caninum disseminates across the placenta and the blood-brain barrier, to reach sites where it causes severe pathology or establishes chronic persistent infections. The mechanisms used by N. caninum to breach restrictive biological barriers remain elusive. To examine the cellular basis of these processes, migration of different N. caninum isolates (Nc-1, Nc-Liverpool, Nc-SweB1 and the Spanish isolates: Nc-Spain 3H, Nc-Spain 4H, Nc-Spain 6, Nc-Spain 7 and Nc-Spain 9) was studied in an in vitro model based on a placental trophoblast-derived BeWo cell line. Here, we describe that infection of dendritic cells (DC) by N. caninum tachyzoites potentiated translocation of parasites across polarized cellular monolayers. In addition, powered by the parasite's own gliding motility, extracellular N. caninum tachyzoites were able to transmigrate across cellular monolayers. Altogether, the presented data provides evidence of two putative complementary pathways utilized by N. caninum, in an isolate-specific fashion, for passage of restrictive cellular barriers. Interestingly, adoptive transfer of tachyzoite-infected DC in mice resulted in increased parasitic loads in various organs, e.g. the central nervous system, compared to infections with free parasites. Inoculation of pregnant mice with infected DC resulted in an accentuated vertical transmission to the offspring with increased parasitic loads and neonatal mortality. These findings reveal that N. caninum exploits the natural cell trafficking pathways in the host to cross cellular barriers and disseminate to deep tissues. The findings are indicative of conserved dissemination strategies among coccidian apicomplexan parasites.
An Equilibrium Model of Investment in Restructured Electricity Markets

In this paper, we describe a framework modeling for investment in restructured electricity markets. This framework is extremely flexible, and is designed to be able to capture many of the key considerations that distinguish investment in deregulated electricity markets from both investment in regulated markets, and investment in competitive markets for other commodities. The model is composed of two distinct elements: a detailed model of short-run, or ‘spot market’ competition in electricity markets, and a dynamic long-run equilibrium model of investment decisions of firms. The investment choices by firms will be driven by the underlying profits implied by the short-term markets under different investment paths. Firms will choose the investment paths that lead them to more profitable states of short-term markets. We implement the framework for a representative electricity market and several qualitative insights can be demonstrated. First, the incentives of individual firms to invest very much depends upon their position in the market. Second, the impact of market structure on investment incentives is also influenced by the firms’ contractual or retail obligations in the market. Just as long-term contracts or retail obligations change a firm’s incentives in the short-term markets, so do they influence investment decisions. Third, increased uncertainty – in our case in demand growth – can delay investment. This is a demonstration of the option value of waiting for further information before making an irreversible investment.
Functional Validation of Transcription Factor to Gene Interactions by Statistical Learning of Gaussian Bayesian networks from SNP and Expression data .

Understanding gene regulation is an important step to understanding how essential mechanisms are controlled in biological systems. One of the central goals of biology is to identify which transcription factors (TFs) regulate the transcription of which target genes and what are their downstream effects. Functional assays such as ChIP-seq and DNase I together can provide a TF binding map of TF binding sites on DNA. However, the binding alone may not result in changing the target gene expression. Thus, functional validation is necessary to show that the binding influences target gene expression. The standard approach to functional validation is to perform artificial TF knockdown experiments and declare the differentially expressed genes as validated target genes. Instead of artificial perturbation, we propose to leverage the naturally-occurring genetic variations as the source of perturbations that vary gene expressions and to analyze population SNP and geneexpression data in order to validate the TF binding map. Compared to the standard approach that perturbs TF concentration for a single TF at a time, our approach is potentially more powerful, because any aspects of the TF-target interaction, including TF concentration and TF binding affinity, can be perturbed by a large number of SNPs found across the genome. In addition, we are able to leverage existing SNP and gene expression data, which is available from the popular expression quantitative trait locus mapping studies. We introduce a statistical approach, based on conditional Gaussian Bayesian networks, that integrates population SNP and gene expression data with TF binding data to validate the TF binding map. We develop an efficient learning algorithm for learning the gene regulatory network by using the TF binding data as prior knowledge and selecting the TF-target interactions that are validated based on population SNP and gene-expression data. Given the estimated network, we perform inference on the estimated probabilistic graphical models to determine downstream genes that are affected by the TF-target interactions. We demonstrate our method on ENCODE ChIP-seq and DNase I data, and on population SNP and expression data from lymphoblastoid cells, originally collected for the 1000 Genomes and HapMap 3 projects respectively. Finally, we apply our approach to validate the TF binding map of ER and its coregulators in breast cancer using ENCODE ChIP-seq and DNase I data, and population SNP and expression data from the TCGA project.
Facebook Mediating – Peer Assessment Activities In Students’ Writing At English Department Unila

Penelitian ini bertujuan untuk mencari tahu apa efek Facebook group close penilaian rekan pada prestasi menulis siswa, aspek mana dari tulisan yang paling meningkat setelah uji coba tindakan, apa persepsi siswa tentang perlakuan dan bagaimana siswa melanjutkan Facebook – mediasi kepenilaian rekan. Penelitian ini bersifat kuantitatif dan kualitatif. Ini menggunakan desain pretest-posttest satu – kelompok sebagai pengukuran kuantitatif. Kemudian, pengukuran kualitatif melibatkan analisis pada peningkatan siswa dari setiap aspek, persepsidan proses penilaian. Hasilnya menunjukkan bahwa ada peningkatan yang signifikan dalam prestasi menulis mereka setelah uji coba tindakan dan aspek yang paling banyak diperbaiki adalah konten. Ini juga menunjukkan bahwa siswa menyukai pembelajaran semacam itu, dengan kata lain, mereka memiliki persepsi positif terhadap pembelajaran menulis. Singkatnya, implementasi penilaian mediasi - rekan Facebook di kelas menulis mengarah pada elaborasi ide siswa yang lebih baik yang berakhir dengan tulisan yang lebih baik dan lebih logis. This research aimed at finding out what the effects of Facebook closed group peer assessment on students’ writing achievement are, which aspect of writing improves the most after the treatment, what students’ perceptions of the treatment are and how students proceed Facebook-mediating to peer assessment. This research was quantitative and qualitative. It used the one-group pretest-posttest design as the quantitative measurement. Then, the qualitative measurement involved the analyses on the students' improvement of each aspect, perceptions and assessment process. The result indicates that there was a significant improvement in their writing achievement after the treatment and the aspect which improved the most was content. It also indicates that the students favored such learning, in other words, they had positive perceptions on it. In short, the implementation of Facebook mediating-peer assessment in writing class leads to students’ better idea elaboration that ends up in their better-organized and more logical writing. Keywords: Facebook, peer assessment, writing, writing achievment.
Methods for improving open cluster fundamental parameters applied to M 52 and NGC 3960

Aims. We derive accurate parameters related to the CMD, structure and dynamical state of M 52 and NGC 3960, whose fields are affected by differential reddening. Previous works estimated their ages in the ranges 35-135 Myr and 0.5-1.0 Gyr, respectively. Methods. J, H and K, 2MASS photometry with errors <0.2 mag is used to build CMDs, radial density profiles, luminosity and mass functions, and correct for differential reddening. Field-star decontamination is applied to uncover the cluster's intrinsic CMD morphology, and colour-magnitude filters are used to isolate stars with high probability of being cluster members. Results. The differential-reddening corrected radial density profile of M52 follows King's law with core and limiting radii of R core = 0.91 ± 0.14 pc and R lim = 8.0 ± 1.0 pc. NGC 3960 presents an excess of the stellar density over King's profile (R core = 0.62 ± 0.11 pc and R lim = 6.0 ± 0.8 pc) at the center. The tidal radii of M52 and NGC 3960 are R tidal = 13.1 ± 2.2 pc and R tidal = 10.7 ± 3.7 pc. Cluster ages of M52 and NGC 3960 derived with Padova isochrones are constrained to 60 ± 10 Myr and 1.1 ± 0.1 Gyr. In M 52 the core MF (Χ core = 0.89 ± 0.12) is flatter than the halo's (Χ halo = 1.65 ± 0.12). In NGC 3960 they are Χ core = -0.74 ± 0.35 and Χ halo = 1.26 ± 0.26. The mass locked up in MS/evolved stars in M52 is ∼1200 M ⊙ , and the total mass (extrapolated to 0.08 M ⊙ ) is ∼3800 M ⊙ . The total mass in NGC 3960 is ∼ 1300 M ⊙ . Conclusions. Compared to open clusters in different dynamical states studied with similar methods, the core and overall parameters of M 52 are consistent with an open cluster more massive than 1000 M ⊙ and ∼60 Myr old, with some mass segregation in the inner region. The core of NGC 3960 is in an advanced dynamical state with strong mass segregation in the core/halo region, while the somewhat flat overall MF (Χ ≈ 1.07) suggests low-mass star evaporation. The excess stellar density in the core may suggest post-core collapse. The dynamical evolution of NGC 3960 may have been accelerated by the tidal Galactic field, since it lies ≈0.5 kpc inside the Solar circle.
TNFα Transport Induced by Dynamic Loading Alters Biomechanics of Intact Intervertebral Discs

Objective Intervertebral disc (IVD) degeneration is an important contributor to the development of back pain, and a key factor relating pain and degeneration are the presence of pro-inflammatory cytokines and IVD motion. There is surprisingly limited understanding of how mechanics and inflammation interact in the IVD. This study investigated interactions between mechanical loading and pro-inflammatory cytokines in a large animal organ culture model to address fundamental questions regarding (i.) how inflammatory mediators arise within the IVD, (ii.) how long inflammatory mediators persist, and (iii.) how inflammatory mediators influence IVD biomechanics. Methods Bovine caudal IVDs were cultured for 6 or 20-days under static & dynamic loading with or without exogenous TNFα in the culture medium, simulating a consequence of inflammation of the surrounding spinal tissues. TNFα transport within the IVD was assessed via immunohistochemistry. Changes in IVD structural integrity (dimensions, histology & aggrecan degradation), biomechanical behavior (Creep, Recovery & Dynamic stiffness) and pro-inflammatory cytokines in the culture medium (ELISA) were assessed. Results TNFα was able to penetrate intact IVDs when subjected to dynamic loading but not static loading. Once transported within the IVD, pro-inflammatory mediators persisted for 4–8 days after TNFα removal. TNFα exposure induced changes in IVD biomechanics (reduced diurnal displacements & increased dynamic stiffness). Discussion This study demonstrated that exposure to TNFα, as might occur from injured surrounding tissues, can penetrate healthy intact IVDs, induce expression of additional pro-inflammatory cytokines and alter IVD mechanical behavior. We conclude that exposure to pro-inflammatory cytokine may be an initiating event in the progression of IVD degeneration in addition to being a consequence of disease.
Short-term Feature Space and Music Genre Classification

Abstract In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.
Probability distributions, trading strategies and leverage: an application of Gaussian mixture models

The purpose of this paper is twofold. Firstly, to assess the merit of estimating probability density functions rather than level or classification estimations on a one-day-ahead forecasting task of the EUR|USD time series. This is implemented using a Gaussian mixture model neural network, benchmarking the results against standard forecasting models, namely a naive model, a moving average convergence divergence technical model (MACD), an autoregressive moving average model (ARMA), a logistic regression model (LOGIT) and a multi-layer perceptron network (MLP). Secondly, to examine the possibilities of improving the trading performance of those models with confirmation filters and leverage. While the benchmark models perform best without confirmation filters and leverage, the Gaussian mixture model outperforms all of the benchmarks when taking advantage of the possibilities offered by a combination of more sophisticated trading strategies and leverage. This might be due to the ability of the Gaussian mixture model to identify successfully trades with a high Sharpe ratio. Copyright © 2004 John Wiley & Sons, Ltd.