Miracle-dz/UniFAR-FTUs huggingface dataset:
Uma estratégia para predição da taxa de aprendizagem do gradiente descendente para aceleração da fatoração de matrizes.

Sugerir os produtos mais apropriados aos diversos tipos de consumidores nao e uma tarefa trivial, apesar de ser um fator chave para aumentar satisfacao e lealdade destes. Devido a esse fato, sistemas de recomendacao tem se tornado uma ferramenta importante para diversas aplicacoes, tais como, comercio eletronico, sites personalizados e redes sociais. Recentemente, a fatoracao de matrizes se tornou a tecnica mais bem sucedida de implementacao de sistemas de recomendacao. Os parâmetros do modelo de fatoracao de matrizes sao tipicamente aprendidos por meio de metodos numericos, tal como o gradiente descendente. O desempenho do gradiente descendente esta diretamente relacionada a conﬁguracao da taxa de aprendizagem, a qual e tipicamente conﬁgurada para valores pequenos, com o objetivo de nao perder um minimo local. Consequentemente, o algoritmo pode levar varias iteracoes para convergir. Idealmente,e desejada uma taxa de aprendizagem que conduza a um minimo local nas primeiras iteracoes, mas isto e muito dificil de ser realizado dada a alta complexidade do espaco de valores a serem pesquisados. Comecando com um estudo exploratorio em varias bases de dados de sistemas de recomendacao, observamos que, para a maioria das bases, ha um padrao linear entre a taxa de aprendizagem e o numero de iteracoes necessarias para atingir a convergencia. A partir disso, propomos utilizar modelos de regressao lineares simples para predizer, para uma base de dados desconhecida, um bom valor para a taxa de aprendizagem inicial. A ideia e estimar uma taxa de aprendizagem que conduza o gradiente descendenteaumminimolocalnasprimeirasiteracoes. Avaliamosnossatecnicaem8bases desistemasderecomendacaoreaisecomparamoscomoalgoritmopadrao,oqualutilizaum valorﬁxoparaataxadeaprendizagem,ecomtecnicasqueadaptamataxadeaprendizagem extraidas da literatura. Nos mostramos que conseguimos reduzir o numero de iteracoes ate em 40% quando comparados a abordagem padrao.
On the nature of basal vascular tone in cat skeletal muscle and its dependence on transmural pressure stimuli.

The aim of the present study was to elucidate in some detail the characteristics of the intrinsic basal vascular tone in the adrenergically blocked skeletal muscle with regard to its extent and site along the vascular bed, its dependence on arterial pressure via static and dynamic transmural pressure stimuli, and its sensitivity to local metabolic influence. Basal tone, which apparently is of myogenic nature, was pronounced in 'proximal arterial vessels' (greater than 25 mmicrometer i.d.) and in the 'microvessels' (less than 25 micrometers), but low in 'large veins'. Its functional characteristics, however, were different in the 'proximal arterial vessels' and the 'microvessels'. Normal basal tone in the 'microvessels' thus seemed to be intimately dependent on the arterial blood pressure level and, at least partly, initiated by its static mean pressure distension effect as well as by its dynamic pulse pressure oscillations. It could be virtually abolished by a transmural pressure decrease applied at fast rate ('strong inhibitory dynamic transmural pressure stimulus'). Basal tone in the 'proximal arterial vessels', on the other hand, was little affected by arterial pressure and almost irresponsive to transmural pressure stimuli. Basal tone in the 'microvessels' was much more sensitive to metabolic stimuli than that in the 'proximal arterial vessels'. The present results, viewed in the light of some recent electrophysiological studies on vascular smooth muscle, suggest that smooth muscle in the 'microvessels' is mainly of the spike-generating type, whereas that in the 'proximal arterial vessels' seems to be of different nature, possibly of the non-spike-generating type.
d-Band catalysis in electrochemistry.

We have developed the first theory for electrochemical electron transfer reaction that can account for specific catalytic effects. By abandoning the wide-band approximation, we have been able to introduce specific interactions with d-bands, which lower the activation energy. We have applied this model to the breaking of a bond in a diatomic molecule; this is a particularly important case, since generally bond breaking requires a strong catalytic effect of the electrode. When this molecule is far from the electrode, its bonding orbital is filled and its antibonding orbital is empty; during the reaction the antibonding orbital is filled and the bond is broken. The final states consist of two ions, which strongly interact with the polar molecules of the solvent. As is well-known from the theory of Marcus for simple electron transfer, this interaction stabilizes the ions, and the electron transfer generally involves a reorganization, or fluctuation, of the solvent. Our theory permits the calculation of potential energy surfaces V(q,r) as a function of the solvent coordinate q and the bond distance r. An example is shown below.
A RAPIDLY SPINNING BLACK HOLE POWERS THE EINSTEIN CROSS

Observations over the past 20 yr have revealed a strong relationship between the properties of the supermassive black hole lying at the center of a galaxy and the host galaxy itself. The magnitude of the spin of the black hole will play a key role in determining the nature of this relationship. To date, direct estimates of black hole spin have been restricted to the local universe. Herein, we present the results of an analysis of ∼0.5 Ms of archival Chandra observations of the gravitationally lensed quasar Q 2237+305 (aka the “Einstein-cross”), lying at a redshift of z = 1.695. The boost in flux provided by the gravitational lens allows constraints to be placed on the spin of a black hole at such high redshift for the first time. Utilizing state of the art relativistic disk reflection models, the black hole is found to have a spin of at the 90% confidence level. Placing a lower limit on the spin, we find a* ⩾ 0.65 (4σ). The high value of the spin for the ∼109 M☉ black hole in Q 2237+305 lends further support to the coherent accretion scenario for black hole growth. This is the most distant black hole for which the spin has been directly constrained to date.
Acoustic modeling using deep belief network for Bangla speech recognition

Most of the Speech Recognition (SR) systems use Hidden Markov Model (HMM) for acoustic modeling and Gaussian Mixture Model (GMM) for state modeling. Artificial Neural Network (ANN) based methods are also found as a good replacement of GMMs in SR system development. This paper presents a method for Bangla SR using Deep Belief Network (DBN) which is probabilistic generative ANN composed by multiple layers of restricted Boltzmann machine along with HMM. At first Mel Frequency Cepstral Coefficients is used extract features from the speech data. Then DBN is trained with these feature vectors to calculate each of the phoneme states. After that Viterbi decoder is used to determine the resulting hidden state sequence that generates the word. The training of DBN is performed in two steps. At first generative pre-training is used to train the network layer by layer. In the second step, enhanced gradient is used to slightly adjust the model parameters to make it more accurate. Total 840 utterances (20 utterances for each of 42 speakers) of the words are used in this study. The proposed method is shown satisfactory recognition accuracy and outperformed other prominent existing methods.
KQA: A Knowledge Quality Assessment Model for Clinical Decision Support Systems

Informatics researchers have developed many methods for using computers to utilize knowledge in decision making in the form of clinical decision support systems (CDSSs). These systems can enhance human decision making in the healthcare domain. The knowledge acquisition bottleneck is one of the well-known issues in developing knowledge-based systems such as CDSS. It can be considered as a flow of knowledge from different knowledge sources to the main system. Most existing methods for extracting knowledge from knowledge resources suffer from the lack of a proper mechanism for extracting high-quality knowledge. In this paper, we propose a framework to discover high-quality knowledge by utilizing Semantic Web technologies.
Uma Análise da Evasão em Cursos de Graduação Apoiado por Métricas e Visualização de Dados

Evasão escolar é a interrupção do estudo em qualquer nível de educação, ocorrendo muito a nível de cursos de graduação. No entanto, é difícil obter dados sobre a evasão no ensino superior, assim como seu cálculo para análise e identificação de suas causas. Neste contexto, pode-se utilizar visualização de dados para uma melhor análise e tomada de decisão sobre as causas da evasão. O objetivo deste trabalho é analisar a evasão em cursos de graduação por meio de métricas, apoiada por visualização de dados. Um estudo de caso foi realizado com dados de dois semestres de um curso de graduação. Os resultados indicaram que métricas e técnicas de visualização facilitam a análise da evasão e a identificação de suas causas para tomada de decisões.
Comparison of diazepam and flunitrazepam for sedation during local anaesthesia for bronchoscopy.

Diazepam and flunitrazepam were compared as amnesic and sedative adjuncts to local anaesthesia for diagnostic bronchoscopy in 92 patients. After local anaesthesia of the pharynx, larynx and trachea with lignocaine, atropine plus diazepam of flunitrazepam was injected i.v. The co-operation of the patients and the technical circumstances under which the bronchoscopy was performed were good in each group. None of the treatments significantly modified arterial pressure or heart rate. Two hours after the injection, flunitrazepam 0.01 mg kg-1 more frequently caused amnesia for pictures shown to the patients during the first 15 min after injection (failure to recall 42--75%, and for bronchoscopy 67%), than did diazepam 0.125 mg kg-1 (failure to recall 21--67%; bronchoscopy 38%). Double doses of the drugs caused amnesic actions similar to those of flunitrazepam 0.01 mg kg-1. When failure to recall was assessed on the following day, 29% and 5% of the patients remembered bronchoscopy after flunitrazepam 0.01 and 0.02 mg kg-1 respectively; after diazepam 0.125 and 0.25 mg kg-1 the corresponding percentages was 59% and 30% (P less than 0.05% v. fluintrazepam). The ability to stand and walk on a stright line was similar after the smaller doses of both drugs, but after the larger doses recovery was slower after flunitrazepam. Psychomotor performance was still distinctly impaired 2 h after the injection of the larger doses.
Impact of Nitrogen Deposition on the Species Richness of Grasslands

A transect of 68 acid grasslands across Great Britain, covering the lower range of ambient annual nitrogen deposition in the industrialized world (5 to 35 kg Nha–1 year–1), indicates that long-term, chronic nitrogen deposition has significantly reduced plant species richness. Species richness declines as a linear function of the rate of inorganic nitrogen deposition, with a reduction of one species per 4-m2 quadrat for every 2.5 kg Nha–1 year–1 of chronic nitrogen deposition. Species adapted to infertile conditions are systematically reduced at high nitrogen deposition. At the mean chronic nitrogen deposition rate of central Europe (17 kg Nha–1 year–1), there is a 23% species reduction compared with grasslands receiving the lowest levels of nitrogen deposition.
Min / Max-Poly Weighting Schemes and the NL vs UL Problem ∗

For a graph G(V,E) (|V | = n) and a vertex s ∈ V , a weighting scheme (w : E → N) is called a min-unique (resp. max-unique) weighting scheme, if for any vertex v of the graph G, there is a unique path of minimum (resp. maximum) weight from s to v. Instead, if the number of paths of minimum (resp. maximum) weight is bounded by n for some constant c, then the weighting scheme is called a min-poly (resp. max-poly) weighting scheme. In this paper, we propose an unambiguous non-deterministic log-space (UL) algorithm for the problem of testing reachability graphs augmented with a min-poly weighting scheme. This improves the result due to Allender and Reinhardt[12] where a UL algorithm was given for the case when the weighting scheme is min-unique. Our main technique involves triple inductive counting, and generalizes the techniques of [8, 13] and [12], combined with a hashing technique due to [6] (also used in [7]). We combine this with a complementary unambiguous verification method, to give the desired UL algorithm. At the other end of the spectrum, we propose a UL algorithm for testing reachability in layered DAGs augmented with max-poly weighting schemes. To achieve this, we first reduce reachability in layered DAGs to the longest path problem for DAGs with a unique source, such that the reduction also preserves the max-unique and max-poly properties of the graph. Using our techniques, we generalize the double inductive counting method in [9] where UL algorithm was given for the longest path problem on DAGs with a unique sink and augmented with a max-unique weighting scheme. An important consequence of our results is that, to show NL = UL, it suffices to design log-space computable min-poly (or max-poly) weighing schemes for layered DAGs.
TinyModules: Code module exchange in TinyOS

The ability to update or exchange the program code running on sensor nodes is a core requirement in many wireless sensor network scenarios. Such code update mechanisms must take the specific resource limitations of wireless sensor nodes into account since both the transmission and the processing of updates consume considerable amounts of time and energy. We present TinyModules, a novel code update mechanism for TinyOS-based sensor networks whose idea is to divide the program code into a static part and an exchangeable TinyModule. TinyModules is highly configurable with the system developer being able to freely define which parts of the application should be exchangeable. We show that the use of TinyModules can achieve considerable savings in terms of code update size and update time with only negligible additional processing required on the nodes.
EEG analysis of frontal hemispheric asymmetry for learning styles

Learning style had become an importance researched subject for understanding how individual learns. Apart from that, personality traits such as emotions, moods and self-motivation of the learners were also being actively studied. In this research, the learners' learning style and their personality traits were investigated by Electroencephalogram (EEG) Frontal Asymmetry. First, The participants (N=41) learning styles were classified using Kolb's Learning Style Inventory (KLSI) which grouped them into either Diverger, Assimilator, Converger or Accommodator style. Subsequently, their brain signal was recorded using EEG and the Frontal Asymmetry was determined using the Asymmetry Relation Ratio (ARR) formula. The result shows that Converger and Diverger were related to Right Frontal Asymmetry while Assimilator and Accommodator were associated with Left Frontal Asymmetry.
FORMEETING RECOGNITION IN NOISY AND REVERBERANT ENVIRONMENTS

Here we propose online adaptive beamforming for automatic speech recognition (ASR) in meetings in noisy, reverberant environments. The proposed method is based on recently developed mask-based beamforming, in which accurate mask estimation and diarization are paramount. Real-world experiments have shown that mask-based beamforming enables accurate ASR in meetings in small noise and reverberation with a signal-to-noise ratio (SNR) of 15–25 dB and a reverberation time (RT) of 120–350ms. In this paper, we deal with a more adverse condition: meetings in large noise and reverberation with an SNR of 3–15 dB and an RT of 500ms. To this end, we exploit a probabilistic spatial dictionary, a dictionary that consists of a pre-trained probability distribution of source location features for each potential speaker location. This dictionary enables us to perform mask estimation and diarization for beamforming accurately, even in the above adverse condition. The proposed method reduced the word error rate (WER) on real meeting data by 54.8% relative to our previous beamforming method.
Intravenous calcitriol versus paricalcitol in haemodialysis patients with severe secondary hyperparathyroidism

Aim: Secondary hyperparathyroidism (SHPT) is common among haemodialysis patients. Intensive treatment with calcitriol is often complicated by hypercalcaemia, hyperphosphataemia and elevated calcium phosphorus (Ca X PO4) product. Paricalcitol is a vitamin D analogue developed to overcome some of the limitations of calcitriol therapy. The study objectives were to compare the response of intact parathyroid hormone (iPTH) and the incidence of hypercalcaemia, hyperphosphataemia and elevated Ca X PO4 product in patients with severe SHPT treated with either i.v. calcitriol or i.v. paricalcitol.
Lived Data: Tinkering With Bodies, Code, and Care Work

Human–computer interaction research on personal informatics in health care has focused on systems that aim to support patient empowerment and enable better health outcomes with data monitoring and tracking. Through examining the lived experience of personal data used to manage chronic illness, we show how such technology design is also the site of radical dependencies, collaborative care arrangements, and wider sociopolitical concerns tied to new forms of technical labor and shifts in medical expertise. Drawing from ethnographic research with open source, do-it-yourself collectives engaged in opening up corporate-controlled type 1 diabetes devices and data, we propose the analytical lens of lived data. Lived data emphasize data as an integral way of living, enacted through a multiplicity of things, relations, and practices, from bodies and needles, social media support groups, and legal processes to writing code, making visualizations, and hacking devices. Building on critical and feminist scholarship of human–machine relations, we articulate the work that goes into producing and living personal data, the physical and emotional costs of data tracking, and the consequences of do-it-yourself as a form of individual empowerment in health and wellness.
Using contracts to induce cooperation in large scale P2P communication networks: algorithms, stability and applications

Embedding incentive mechanisms into networking applications (e.g., P2P) is becoming more important for large-scale networking applications since incentive mechanisms can encourage nodes, either end hosts or routers, to cooperate so as to provide a high performance and scalable service. In this paper, we consider a new and novel paradigm of using 'contract' (e.g., an agreement between two communicating parties) to encourage and maintain cooperation. We formally define the notion of contract in a network setting and illustrate its dynamics. We formally show under what conditions a 'balanced' and 'stable' contract can be formed so all participating nodes will have the incentive to contribute. We also propose both centralised and distributed algorithms to find and implement a stable and balanced contract with fairness and security constraints. To illustrate, we show how contracts can be applied to P2P-VoD systems and ISPs networks. In summary, contract can serve as a new genre of incentive mechanism for large scale networking applications.
In vitro investigation of renal epithelial injury suggests that primary cilium length is regulated by hypoxia‐inducible mechanisms

Primary cilia are non‐motile sensory organelles that project from cells in many tissues. The role of renal primary cilium‐based signalling in regulating epithelial cell proliferation and differentiation is highlighted by studies showing that defects of the cilium lead to epithelial de‐differentiation, over proliferation and polycystic kidney disease. Recent studies show that renal primary cilia may also play a role in controlling epithelial differentiation during renal repair. After injury, renal cilium length increases dramatically and then undergoes a normalization that coincides with structural and functional repair in both human patients and mouse models of renal injury. These changes in cilium length are likely to modulate cilium‐based signalling, but the injury‐related factors that influence renal primary cilium length have yet to be determined. Here, we investigated the effect of three factors commonly associated with renal injury on renal cilium length in an in vitro setting. MDCK (Madin Darby canine kidney) cell cultures bearing primary cilia were treated with BSA to simulate albuminuria, cobalt chloride to simulate hypoxia and the inflammation‐related cytokine tumour necrosis factor α. Primary cilium length was only increased in cultures treated with cobalt chloride. Our results suggest a role for hypoxia and the induction of HIF‐1α (hypoxia‐inducible factor 1α) in increasing renal primary cilium length following renal injury.
Foreign Direct Investment and Economic Growth in Developing Countries: How Relevant are Host-Country and Industry Characteristics?

Conclusive evidence supporting the widely held view that developing countries should draw on foreign direct investment (FDI) to spur economic development is surprisingly hard to come by. We raise the proposition that results on the growth impact of FDI are ambiguous because highly aggregated FDI data, used in virtually all previous empirical studies, blur the differences between resourceseeking, market-seeking and efficiency-seeking FDI and ignore the compatibility of different types of FDI with economic conditions prevailing in the host country. Analysing US FDI stocks in major sectors and specific manufacturing industries in a large number of developing countries, we show that positive growth effects of FDI are anything but guaranteed. Rather, hostcountry and industry characteristics as well as the interplay between both sets of characteristics have an important say on the growth impact of FDI in developing countries.
Fetal myosin immunoreactivity in human dystrophic muscle

We report immunofluorescence observations on normal and dystrophic human muscle using an antibody (anti‐bF) raised against bovine fetal myosin and specific for fetal myosin heavy chains. In rat skeletal muscle, anti‐bF was previously found to react selectively with myosin isoforms expressed during fetal and early postnatal development and in regenerating muscles.11 Anti‐bF stained most fibers in human fetal and neonatal muscle, whereas only nuclear chain fibers of muscle spindles were labeled in normal adult muscle. In muscle biopsies from patients with Duchenne's muscular dystrophy, numerous extrafusal fibers were stained: some were small regenerating fibers, others were larger fibers presumably resulting from previous regenerative events. Fetal myosin immunoreactivity in Duchenne's dystrophy appears to reflect the reexpression of fetal‐specific myosin isoforms and provides a new valuable tool for identifying regenerating fibers and following their destiny in dystrophic muscle.