Miracle-dz/UniFAR-FTUs huggingface dataset:
Layered TPOT: Speeding up Tree-based Pipeline Optimization

With the demand for machine learning increasing, so does the demand for tools which make it easier to use. Automated machine learning (AutoML) tools have been developed to address this need, such as the Tree-Based Pipeline Optimization Tool (TPOT) which uses genetic programming to build optimal pipelines. We introduce Layered TPOT, a modification to TPOT which aims to create pipelines equally good as the original, but in significantly less time. This approach evaluates candidate pipelines on increasingly large subsets of the data according to their fitness, using a modified evolutionary algorithm to allow for separate competition between pipelines trained on different sample sizes. Empirical evaluation shows that, on sufficiently large datasets, Layered TPOT indeed finds better models faster.
Modulation of apoptosis by caprine herpesvirus 1 infection in a neuronal cell line

Caprine herpesvirus type 1 (CpHV‐1), like other members of the alpha subfamily of herpesviruses, establishes latent infections in trigeminal ganglion neurons. Our groups previously demonstrated that CpHV‐1 induces apoptosis in goat peripheral blood mononuclear cells and in an epithelial bovine cell line, but the ability of CpHV‐1 to induce apoptosis in neuronal cells remains unexplored. In this report, the susceptibility of Neuro 2A cells to infection by CpHV‐1 was examined. Following infection of cultured cells with CpHV‐1, expression of cell death genes was evaluated using real‐time PCR and Western blot assays. Analysis of virus‐infected cells revealed activation of caspase‐8, a marker for the extrinsic pathway of apoptosis, and caspase‐9, a marker for the intrinsic pathway of apoptosis at 12 and 24 h post‐infection. Significant increase in the levels of cleaved caspase‐3 was also observed at the acme of cytopathic effect at 24 h post‐infection. In particular, at 3 and 6 h post‐infection, several proapototic genes were under‐expressed. At 12 h post‐infection several proapototic genes such as caspases, TNF, Cd70, and Traf1 were over expressed while Bcl2a1a, Fadd, and TNF genes were underexpressed. In conclusion, the simultaneous activation of caspase‐8 and caspase‐9 suggests that CpHV‐1 can trigger the death‐receptor pathway and the mitochondrial pathway separately and in parallel. Our findings are significant because this is the first published study showing the effect of CpHV‐1 infection in neuronal cells in terms of gene expression and apoptosis modulation. J. Cell. Biochem. 114: 2809–2822, 2013. © 2013 Wiley Periodicals, Inc.
The Synthetic Cannabinoid WIN 55,212-2 Sensitizes Hepatocellular Carcinoma Cells to Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL)-Induced Apoptosis by Activating p8/CCAAT/Enhancer Binding Protein Homologous Protein (CHOP)/Death Receptor 5 (DR5) Axis

In this article, we demonstrate that the synthetic cannabinoid R-(+)-(2,3-dihydro-5-methyl-3-[(4-morpholinyl)methyl]pyrol[1,2,3-de]-1,4-benzoxazin-6-yl)-(1-naphthalenyl) methanone mesylate (WIN 55,212-2) sensitizes human hepatocellular carcinoma (HCC) cells to apoptosis mediated by tumor necrosis-related apoptosis inducing ligand (TRAIL). The apoptotic mechanism induced by treatment with WIN/TRAIL combination involved the loss of the mitochondrial transmembrane potential and led to the activation of caspases. In HCC cells, WIN treatment induced the up-regulation of TRAIL death receptor DR5, an effect that seemed to be related to the increase in the level of p8 and CHOP, two factors implicated in cellular stress response and apoptosis. This relationship was suggested by the observation that the down-regulation of p8 or CHOP by specific small interfering RNAs attenuated both WIN-mediated DR5 up-regulation and the cytotoxicity induced by WIN/TRAIL cotreatment. Moreover, WIN induced a significant decrease in the levels of some survival factors (survivin, c-inhibitor of apoptosis protein 2, and Bcl-2) and in particular in that of the active phosphorylated form of AKT. This event seemed to be dependent on the transcription factor peroxisome proliferator-activated receptor-γ whose level significantly increased after WIN treatment. Therefore, both the induction of DR5 via p8 and CHOP and the down-regulation of survival factors seem to be crucial for the marked synergistic effects induced by the two drugs in HCC cells. Taken together, the results reported in this article indicate that WIN/TRAIL combination could represent a novel important tool for the treatment of HCC.
Glass dynamics in confinement examined with quasi-elastic nuclear resonant forward scattering

Since Adam and Gibbs proposed their theory of cooperatively rearranging regions in 1965 [AG65] our understanding of the liquid-glass transition is connected to the concept of cooperativity. This theory implies a temperaturedependent radius of cooperativity, which diverges at the glass transition, the so-called divergent length scale. While the necessity of a divergent time scale for the glass transition is widely accepted nowadays (e.g. in advanced theories like mode-coupling theory), the existence of the divergent length scale is still subject to controversy. The principal question of its existence can be addressed by experiments concerning glass forming liquids in confinement, since the dynamics of a confined glass is expected to deviate strongly from the dynamics of a bulk glass as soon as the confining radius approximately matches the length scale of cooperativity. Nuclear resonant scattering is an experimental method suited to study the fast and slow dynamics of a glass with atomic resolution. First experiments on the model glass-former dibutylphthalate:ferrocene confined in controlled pore glasses yielded evidence for a shift of the glass transition to higher temperatures, but were unable to discern whether this was caused by the surface-glass interaction or induced by the geometrical confinement [ASF01]. In this work nuclear resonant scattering experiments were performed using the oriented channels of mesoporous silicon as a confining matrix; Mosbauer spectroscopy is applied as a complementary experimental method. The temperature dependencies of experimental parameters like the relaxation time and the Lamb-Mosbauer factor yielded new insights into the glass transition and the connected molecular dynamics. In all cases shifts of the modecoupling critical temperature TC to higher temperatures were observed. The
RC3: Consistency Directed Cache Coherence for x86-64 with RC Extensions

The recent convergence towards programming language based memory consistency models has sparked renewed interest in lazy cache coherence protocols. These protocols exploit synchronization information by enforcing coherence only at synchronization boundaries via self-invalidation. In effect, such protocols do not require sharer tracking which benefits scalability. On the downside, such protocols are only readily applicable to a restricted set of consistency models, such as Release Consistency (RC), which expose synchronization information explicitly. In particular, existing architectures with stricter consistency models (such as x86-64) cannot readily make use of lazy coherence protocols without either: changing the architecture's consistency model to (a variant of) RC at the expense of backwards compatibility, or adapting the protocol to satisfy the stricter consistency model, thereby failing to benefit from synchronization information. We show an approach for the x86-64 architecture, which is a compromise between the two. First, we propose a mechanism to convey synchronization information via a simple ISA extension, while retaining backwards compatibility with legacy codes and older microarchitectures. Second, we propose RC3, a scalable hardware cache coherence protocol for RCtso, the resulting memory consistency model. RC3 does not track sharers, and relies on self-invalidation on acquires. To satisfy RCtso efficiently, the protocol reduces self-invalidations transitively using per-L1 timestamps only. RC3 outperforms a conventional lazy RC protocol by 12%, achieving performance comparable to a MESI directory protocol for RC optimized programs. RC3's storage overhead per cache line scales logarithmically with increasing core count, and reduces on-chip coherence storage overheads by 45% compared to a related approach specifically targeting TSO.
Global physiology and pathophysiology of cough: ACCP evidence-based clinical practice guidelines.

OBJECTIVE The anatomy and neurophysiology of cough has been reviewed in the preceding section. The objective of this section is to describe how the varied anatomic components of the respiratory system work in concert to produce an effective cough. METHODS This was accomplished by reviewing (1) the factors needed to produce effective cough pressures and gas velocity in the airways, and (2) the salient features of the interaction between the airflow generated during a cough and the mucus that lines the tracheobronchial tree. The MEDLINE database was searched for this review, and the search consisted of studies published in English between 1960 and April 2004. Search terms were "cough mechanics" and "cough physiology. " RESULTS Inhaling to high lung volumes and glottic closure prior to the expiratory phase of cough facilitate the generation of high intrathoracic pressures. These high intrathoracic pressures (1) provide the driving force for airstream flow during cough and (2) dynamically compress the central airways, which further enhances the cough airstream velocity. CONCLUSIONS High intrathoracic pressures are needed to generate the requisite cough expiratory flows and airstream velocities. However, cough may be effective in individuals with mild-to-moderate degrees of respiratory muscle weakness, as only modest increases in intrathoracic pressure are needed to dynamically compress the large intrathoracic airways and increase cough flow velocity.
Sequential release of milk protein-derived bioactive peptides in the jejunum in healthy humans.

BACKGROUND The digestive hydrolysis of dietary proteins leads to the release of peptides in the intestinal tract, where they may exert a variety of functions, but their characterization and quantification are difficult. OBJECTIVES We aimed to characterize and determine kinetics of the formation of peptides present in the jejunum of humans who ingested casein or whey proteins by using mass spectrometry and to look for and quantify bioactive peptides. DESIGN Subjects were equipped with a double-lumen nasogastric tube that migrated to the proximal jejunum. A sample collection was performed for 6 h after the ingestion of 30 g (15)N-labeled casein (n = 7) or whey proteins (WPs; n = 6). Nitrogen flow rates were measured, and peptides were identified by using mass spectrometry. RESULTS After casein ingestion, medium-size peptides (750-1050 kDa) were released during 6 h, whereas larger peptides (1050-1800 kDa) were released from WPs in the first 3 h. A total of 356 and 146 peptides were detected and sequenced in the jejunum after casein and WP ingestion, respectively. β-casein was the most important precursor of peptides, including bioactive peptides with various activities. The amounts of β-casomorphins (β-casein 57-, 58-, 59-, and 60-66) and β-casein 108-113 released on the postprandial window were sufficient to elicit the biological action of these peptides (ie, opioid and antihypertensive, respectively). CONCLUSIONS Clear evidence is shown of the presence of bioactive peptides in the jejunum of healthy humans who ingested casein. Our findings raise the question about the physiologic conditions under which these peptides can express their bioactivity in humans. This trial was registered at clinicaltrials.gov as NCT00862329.
Preclinical ROC studies of digital stereomammography

Reports the diagnostic performance of observers in detecting abnormalities in computer-generated mammogram-like images. A mathematical model of the human breast is defined in which breast tissues are simulated by spheres of different sizes and densities. Images are generated by casting rays from a specified source, through the model, and onto an image plane. Observer performance when using two viewing modalities (stereo versus mono) is compared. In the stereo viewing mode, images are presented to the observer (wearing liquid-crystal display glasses), such that the left eye sees the left image only and the right eye sees the right image only. In this way, the images can be fused by the observer to obtain a sense of depth. In the mono viewing mode, identical images are presented to the left and right eyes so that no binocular disparities will be produced by the images. Observer response data are evaluated using receiver operating characteristic (ROC) analysis to characterize any difference in detectability of abnormalities (in either the density or the arrangement of simulated tissue densities) using the two viewing modes. The authors' experimental results indicate the clear superiority of stereo viewing for detection of arrangement abnormalities. For detection of density abnormalities, the performance of the two viewing modes is similar. These preliminary results suggest that stereomammography may permit easier detection of certain tissue abnormalities, perhaps providing a route to earlier tumor detection in cases of breast cancer.
Dynamic Bayesian modeling of the cerebral activity

Conventional methods used for the interpretation of activation data provided by functional neuroimaging techniques provide useful insights on what the networks of cerebral structures are, and when and how much they activate. However, they do not explain how the activation of these large-scale networks derives from the cerebral information processing mechanisms involved in cognitive functions. At this global level of representation, the human brain can be considered as a dynamic biological system. Dynamic Bayesian networks seem currently the most promising modeling paradigm. Our modeling approach is based on the anatomical connectivity of cerebral regions, the information processing within cerebral areas and the causal influences that connected regions exert on each other. The capabilities of the formalism's current version are illustrated by the modeling of a phonemic categorization process, explaining the different cerebral activations in normal and dyslexic subjects. The simulation data are compared to experimental results [Ruff et al, 2001].
Alternating direction method of multipliers with variable stepsize for partially parallel MR image reconstruction

The alternating direction multiplier method is an effective method to solve partial parallel imaging (PPI) based on the total variation model, but research results show that the inversion matrix is large and ill-conditioned. In view of the limitation that fixed stepsize of alternating direction multiplier method, the paper presents an adaptive alternating direction multiplier method. The new algorithm combines the traditional alternating direction multiplier method and Barzilai-Borwein (BB) method to deal with non-convex total variation regularization. The experimental results show that the new algorithm not only has obtained better segmentation effect, but also has better convergence and stability.
CHAPTER FOUR PROTACTINIUM

Protactinium, element 91, is one of the most rare of the naturally occurring elements and may well be the most difficult of all to extract from natural sources. Protactinium is, formally, the third element of the actinide series and the first having a 5f electron. The superconducting properties of protactinium metal provide clear evidence that Pa is a true actinide element (Smith et al., 1979). Its chemical behavior in aqueous solution, however, would seem to place it in group VB of the Mendeleev’s table, below Ta and Nb. The predominant oxidation state is 5þ. Pa(V) forms no simple cations in aqueous solution and, like Ta, it exhibits an extraordinarily high tendency to undergo hydrolysis, to form polymers, and to be adsorbed on almost any available surface. These tendencies undoubtedly account for the many reports of erratic and irreproducible behavior of protactinium as well as for its frustrating habit of disappearing in the hands of inexperienced or unwary investigators. A useful review of the chemical properties of Pa important in an analytical context has been made by Pal’shin et al. (1970) and Myasoedov et al. (1978). The most important natural isotope is Pa, but the industrial importance of Pa stems chiefly from the role of its artificial isotope, Pa, as an intermediate in the production of fissile U in thorium breeder reactors. It was, in fact, the need for a relatively stable isotope that could be used for macroscopic chemical studies, which was responsible for the revival of interest in the recovery of Pa from natural sources (Katzin, 1952). The result has been a rapid growth in our 4.
PixelSNE: Visualizing Fast with Just Enough Precision via Pixel-Aligned Stochastic Neighbor Embedding

Embedding and visualizing large-scale high-dimensional data in a two-dimensional space is an important problem since such visualization can reveal deep insights out of complex data. Most of the existing embedding approaches, however, run on an excessively high precision, ignoring the fact that at the end, embedding outputs are converted into coarse-grained discrete pixel coordinates in a screen space. Motivated by such an observation and directly considering pixel coordinates in an embedding optimization process, we accelerate Barnes-Hut tree-based t-distributed stochastic neighbor embedding (BH-SNE), known as a state-of-the-art 2D embedding method, and propose a novel method called PixelSNE, a highly-efficient, screen resolution-driven 2D embedding method with a linear computational complexity in terms of the number of data items. Our experimental results show the significantly fast running time of PixelSNE by a large margin against BH-SNE, while maintaining the minimal degradation in the embedding quality. Finally, the source code of our method is publicly available at this https URL
A wavelet multiscale denoising algorithm for magnetic resonance (MR) images

Based on the Radon transform, a wavelet multiscale denoising method is proposed for MR images. The approach explicitly accounts for the Rician nature of MR data. Based on noise statistics we apply the Radon transform to the original MR images and use the Gaussian noise model to process the MR sinogram image. A translation invariant wavelet transform is employed to decompose the MR ‘sinogram’ into multiscales in order to effectively denoise the images. Based on the nature of Rician noise we estimate noise variance in different scales. For the final denoised sinogram we apply the inverse Radon transform in order to reconstruct the original MR images. Phantom, simulation brain MR images, and human brain MR images were used to validate our method. The experiment results show the superiority of the proposed scheme over the traditional methods. Our method can reduce Rician noise while preserving the key image details and features. The wavelet denoising method can have wide applications in MRI as well as other imaging modalities.
Incorporating advanced language models into the P300 speller using particle filtering

Objective. The P300 speller is a common brain–computer interface (BCI) application designed to communicate language by detecting event related potentials in a subject’s electroencephalogram signal. Information about the structure of natural language can be valuable for BCI communication, but attempts to use this information have thus far been limited to rudimentary n-gram models. While more sophisticated language models are prevalent in natural language processing literature, current BCI analysis methods based on dynamic programming cannot handle their complexity. Approach. Sampling methods can overcome this complexity by estimating the posterior distribution without searching the entire state space of the model. In this study, we implement sequential importance resampling, a commonly used particle filtering (PF) algorithm, to integrate a probabilistic automaton language model. Main result. This method was first evaluated offline on a dataset of 15 healthy subjects, which showed significant increases in speed and accuracy when compared to standard classification methods as well as a recently published approach using a hidden Markov model (HMM). An online pilot study verified these results as the average speed and accuracy achieved using the PF method was significantly higher than that using the HMM method. Significance. These findings strongly support the integration of domain-specific knowledge into BCI classification to improve system performance.
Basement Membrane and Repair of Injury to Peripheral Nerve: Defining a Potential Role for Macrophages, Matrix Metalloproteinases, and Tissue Inhibitor of Metalloproteinases-1

Injury to a peripheral nerve is followed by a remodeling process consisting of axonal degeneration and regeneration. It is not known how Schwann cell–derived basement membrane is preserved after injury or what role matrix metalloproteinases (MMPs) and their inhibitors play in axonal degeneration and regeneration. We showed that the MMPs gelatinase B (MMP-9), stromelysin-1 (MMP-3), and the tissue inhibitor of MMPs (TIMP)-1 were induced in crush and distal segments of mouse sciatic nerve after injury. TIMP-1 inhibitor activity was present in excess of proteinase activity in extracts of injured nerve. TIMP-1 protected basement membrane type IV collagen from degradation by exogenous gelatinase B in cryostat sections of nerve in vitro. In vivo, during the early phase (1 d after crush) and later phase (4 d after crush) after injury, induction of TNF-α and TGF-β1 mRNAs, known modulators of TIMP-1 expression, were paralleled by an upregulation of TIMP-1 and gelatinase B mRNAs. At 4 days after injury, TIMP-1, gelatinase B, and TNF-α mRNAs were localized to infiltrating macrophages and Schwann cells in the regions of nerve infiltrated by elicited macrophages. TIMP-1 and cytokine mRNA expression was upregulated in undamaged nerve explants incubated with medium conditioned by macrophages or containing the cytokines TGF-β1, TNF-α, and IL-1α. These results show that TIMP-1 may protect basement membrane from uncontrolled degradation after injury and that cytokines produced by macrophages may participate in the regulation of TIMP-1 levels during nerve repair.
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms

The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrate worst-case upper bounds on the absolute loss for the perceptron algorithm and an exponentiated update algorithm related to the Weighted Majority algorithm. The bounds characterize the behavior of the algorithms over any sequence of trials, where each trial consists of an example and a desired outcome interval (any value in the interval is an acceptable outcome). The worstcase absolute loss of both algorithms is bounded by: the absolute loss of the best linear function in the comparison class, plus a constant dependent on the initial weight vector, plus a per-trial loss. The per-trial loss can be eliminated if the learning algorithm is allowed a tolerance from the desired outcome. For concept learning, the worst-case bounds lead to mistake bounds that are comparable to previous results.
Interfacial Contact and Bonding in Autohesion I-Contact Theory

Abstract A two stage theory, consisting of contact establishment as the first, and bond formation as the second stage, is proposed for autohesion. A viscoelastic contact theory is worked out based on the shape of the surfaces, the contact pressure, and the temperature. Contact of two spheres of polystyrene and a practical surface consisting of cylinders and flats are analyzed mathematically by extending the classical Hertz elastic contact problem by employing elastic-viscoelastic analogy developed by Alfrey and Gurnee. Karam's fourteen element generalized Voigt model is used for computations.