gebhart/patrepeval huggingface dataset:
AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest (2018)

Antimicrobial peptides (AMPs) are promising candidates in the fight against multidrug-resistant pathogens owing to AMPs' broad range of activities and low toxicity. Nonetheless, identification of AMPs through wet-lab experiments is still expensive and time consuming. Here, we propose an accurate computational method for AMP prediction by the random forest algorithm. The prediction model is based on the distribution patterns of amino acid properties along the sequence. Using our collection of large and diverse sets of AMP and non-AMP data (3268 and 166791 sequences, respectively), we evaluated 19 random forest classifiers with different positive:negative data ratios by 10-fold cross-validation. Our optimal model, AmPEP with the 1:3 data ratio, showed high accuracy (96%), Matthew's correlation coefficient (MCC) of 0.9, area under the receiver operating characteristic curve (AUC-ROC) of 0.99, and the Kappa statistic of 0.9. Descriptor analysis of AMP/non-AMP distributions by means of Pearson correlation coefficients revealed that reduced feature sets (from a full-featured set of 105 to a minimal-feature set of 23) can result in comparable performance in all respects except for some reductions in precision. Furthermore, AmPEP outperformed existing methods in terms of accuracy, MCC, and AUC-ROC when tested on benchmark datasets.
Automatic feature point detection using deep convolutional networks for quantitative evaluation of facial paralysis (2016)

Feature point detection is an important pre-processing step for quantitative evaluation of facial paralysis. Since the conventional methods such as active shape model (ASM) or active appearance model (AAM) are trained by using normal face and they are not possible to detect the feature points accurately for the face with paralysis. In this paper, we propose an automatic and accurate feature point detection method for quantitative evaluation of facial paralysis using deep convolutional neural networks (DCNN). The proposed method consists of two steps. We first use AAM for initial feature point detection. In the second step, a patch with the detected point at the center is used as an input of DCNN for refinement. Experiments demonstrated that the proposed method can significantly improve the detection accuracy of the conventional AAM.
Pinocchio (2016)

To instill greater confidence in computations outsourced to the cloud, clients should be able to verify the correctness of the results returned. To this end, we introduce Pinocchio, a built system for efficiently verifying general computations while relying only on cryptographic assumptions. With Pinocchio, the client creates a public evaluation key to describe her computation; this setup is proportional to evaluating the computation once. The worker then evaluates the computation on a particular input and uses the evaluation key to produce a proof of correctness. The proof is only 288 bytes, regardless of the computation performed or the size of the IO. Anyone can check the proof using a public verification key. Crucially, our evaluation on seven applications demonstrates that Pinocchio is efficient in practice too. Pinocchio's verification time is a fixed 10 ms plus 0.4--15 μs per IO element: 5--7 orders of magnitude less than previous work; indeed Pinocchio is the first general-purpose system to demonstrate verification cheaper than native execution (for some apps). The worker's proof effort is still expensive, but Pinocchio reduces it by 19×--60× relative to prior work. As an additional feature, Pinocchio allows the worker to include private inputs in the computation and prove that she performed the computation correctly without revealing any information about the private inputs to the client. Finally, to aid development, Pinocchio provides an end-to-end toolchain that compiles a subset of C into programs that implement the verifiable computation protocol.<!-- END_PAGE_1 -->
Model structures of thermoplastic polyesters having regularly alternated aromatic and fluorinated segments (1998)

Linear segmented polyesters containing soft perfluoropolyether (PFPE) and hard aromatic segments are obtained by an interfacial polycondensation reaction of an acyl chloride-ended fluorinated prepolymer with various aromatic diphenols in the presence of phase transfer catalysts (PTC) as accelerators. Experimental conditions for reaching high molecular weights are discussed. The calorimetric analysis (DSC) of all the polyesters synthesized shows a typical biphasic morphology, where a very low Tg (< −110°C) corresponding to the segregated PFPE moiety, is always accompanied by another Tg or a higher melting temperature, depending on the nature of the hard phase. Dynamic-mechanical analysis (DMA) has been carried out confirming the DSC results and suggesting diversified mechanical behaviors at the various temperatures in line with the amorphous or semicrystalline nature of the polymer. Chemical resistance was finally tested by dipping in several solvents and chemicals. The new polyesters show high contact angles, a moderate swelling in many organic solvents and excellent stability in aggressive hydrolytic environments. © 1998 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 36: 939–947, 1998
The Recent Trend of Mortality in Great Britain (1968)

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Novel Dynamic Spectrum Allocation Algorithm for Cognitive Radio (2010)

Dynamic spectrum allocation is a key technology of the cognitive radio.In this paper,a new spectrum allocation algorithm for cognitive radio is proposed based on the analysis of the OFDM based cognitive radio system.For this system that the constant rate users and the variable rate users were coexistence with each other,the proposed algorithm is minimizing the transmitted power per bit,allocating the free spectrum in the cognitive radio cell dynamically in a sense of fair maximization.The system object function is simplified by using the min-max criterion and the multi-step method.Simulation results are presented to confirm the performance of the proposed algorithm.It’s achieves not only the fair allocation of the spectrum resource but also the balance between the power minimization of the constant rate users and the throughput maximization of the variable rate users,it’s suitable for the situation that there exist two kinds of users in the cognitive radio system.
Chiral Polymers (2009)

Abstract A number of chiral polymers are comprehensively described in this paper. The syntheses and characteristic features of various chiral polymers are introduced according to the origin of their chirality. The structure and synthetic methodology of polymers with a configurational chirality are systematically described, which includes enantiomer‐selective polymerization, asymmetric synthesis polymerization, and chirality induction. Helical polymers are described as one of the main issues in this article. Thus, helix‐sense‐selective polymerization, helicity induction, and chiral amplification are discussed in detail. This article also further includes the function and application of chiral polymers involving polymer‐supported chiral catalyst, chiral stationary phase for high‐performance liquid chromatography, a stimulus‐responsive polymer, and a scaffold for constructing three‐dimensionally well‐defined functionality arrays.
A 1V supply 50nV/Hz noise PSD CMOS amplifier using noise reduction technique of autozeroing and chopper stabilization (2005)

A low-noise CMOS amplifier operating at a low supply voltage is developed using the two noise reduction techniques of autozeroing and chopper stabilization. The proposed amplifier utilizes a feedback with virtual grounded input-switches and a multiple-output switched op-amp. The low-noise amplifier fabricated in a 0.18-/spl mu/m CMOS technology achieved 50-nV/VHz input noise at 1-MHz chopping and 0.5-mW power consumption at 1-V supply voltage.
The Extended Family of Neutral Sphingomyelinases (2006)

The neutral sphingomyelinases (N-SMases) are considered major candidates for mediating the stress-induced production of ceramide, and N-SMase activity has been identified, characterized, and cloned from bacteria, yeast, and mammalian cells. Although the level of identity between these enzymes is low, a number of key residues thought to be involved in metal binding and catalysis are conserved. This has led to the suggestion of a common catalytic mechanism, and thus, these enzymes are considered to form an extended family of N-SMases. Despite considerable research into N-SMase activity in cell culture and various tissues, the lack, until recently, of molecular identification of specific N-SMase enzymes had precluded specific insights into the regulation, physiological, and pathological roles of these proteins. In this review, we summarize, for the first time, current knowledge of the N-SMase family, focusing on cloned members from bacteria, yeast, and mammalian cells. We also briefly consider the major future directions for N-SMase research which promises highly significant and specific insight into sphingolipid-mediated functions.
Structure of the Cytoplasmic β Subunit--T1 Assembly of Voltage-Dependent K <sup>+</sup> Channels (2000)

The structure of the cytoplasmic assembly of voltage-dependent K+ channels was solved by x-ray crystallography at 2.1 angstrom resolution. The assembly includes the cytoplasmic (T1) domain of the integral membrane alpha subunit together with the oxidoreductase beta subunit in a fourfold symmetric T1(4)beta4 complex. An electrophysiological assay showed that this complex is oriented with four T1 domains facing the transmembrane pore and four beta subunits facing the cytoplasm. The transmembrane pore communicates with the cytoplasm through lateral, negatively charged openings above the T1(4)beta4 complex. The inactivation peptides of voltage-dependent K(+) channels reach their site of action by entering these openings.
Coarsening and aging of lattice polymers: Influence of bond fluctuations (2017)

We present results for the nonequilibrium dynamics of collapse for a model flexible homopolymer on simple cubic lattices with fixed and fluctuating bonds between the monomers. Results from our Monte Carlo simulations show that, phenomenologically, the sequence of events observed during the collapse are independent of the bond criterion. While the growth of the clusters (of monomers) at different temperatures exhibits a non-universal power-law behavior when the bonds are fixed, the introduction of fluctuations in the bonds by considering the existence of diagonal bonds produces a temperature independent growth, which can be described by a universal nonequilibrium finite-size scaling function with a non-universal metric factor. We also examine the related aging phenomenon, probed by a suitable two-time density-density autocorrelation function showing a simple power-law scaling with respect to the growing cluster size. Unlike the cluster-growth exponent α<sub>c</sub>, the nonequilibrium autocorrelation exponent λ<sub>C</sub> governing the aging during the collapse, however, is independent of the bond type and strictly follows the bounds proposed by Majumder and Janke [Phys. Rev. E 93, 032506 (2016)] at all temperatures.
Constant Modulus Algorithm With Reduced Probability of Singularity Enabled by PDL Mitigation (2017)

In this paper, a constant modulus algorithm (CMA) with reduced probability of singularity is proposed. Before implementing the conventional CMA, the correlation matrix of the signals on different polarizations is evaluated. Through singular value decomposition (SVD), it is possible to find the polarization-dependent loss (PDL) and conduct the channel inversion operation by multiplying two matrices on the received signals, i.e., the unitary matrix obtained from SVD and the inverse of the PDL matrix. The proposed algorithm has been implemented in an optical link which is divided into multiple sections. Each section has a 60-km fiber and the PDL of 0.6 dB. It is found that the proposed method greatly improves the singularity avoidance performance in comparison with the standard CMA. The proposed method can be combined with the existing singularity avoidance techniques to further improve the performance. In the combined algorithm, the data are pre-processed by multiplying the PDL mitigation matrix and is then de-multiplexed by the tap-coefficient constrained CMA or the two-stage CMA. Promising performance is obtained with the combined algorithms so that the singularity problem is completely eliminated with the optical signal-to-noise ratio of 18 dB and the PDL of 15 dB. The proposed algorithm, in combination with the existing algorithms, is expected to significantly improve the performance of the polarization-division multiplexing systems.
Magic size InP and InAs clusters: synthesis, characterization and shell growth (2017)

Magic size III-V semiconductor nanoclusters were synthesized. Non-continuous transition of the absorption spectra upon mild heating of the reaction solution is observed, indicating transformation between differently sized clusters. Further manipulation of the clusters is demonstrated for an InP MSC by growing a ZnS and ZnSe shell aiming at blue fluorescence. The quantum yield is limited due to formation of interfacial defects for thick ZnS shells.
Evaluation of pixel- and motion vector-based global motion estimation for camera motion characterization (2009)

Pixel-based and motion vector-based global motion estimation (GME) techniques are evaluated in this paper with an automatic system for camera motion characterization. First, the GME techniques are compared with a frame-by-frame PNSR measurement using five video sequences. The best motion vector-based GME method is then evaluated together with a common and a simplified pixel-based GME technique for camera motion characterization. For this, selected unedited videos from the TRECVid 2005 BBC rushes corpus are used. We evaluate how the estimation accuracy of global motion parameters affects the results for camera motion characterization in terms of retrieval measures. The results for this characterization show that the simplified pixel-based GME technique obtains results that are comparable with the common pixel-based GME method, and outperforms significantly the results of an earlier proposed motion vector-based GME approach.
Single molecule analysis by biological nanopore sensors (2014)

Nanopore sensors provide a highly innovative technique for a rapid and label-free single molecule analysis, which holds a great potential in routing applications. Biological nanopores have been used as ultra-sensitive sensors over a wide range of single molecule analysis including DNA sequencing, disease diagnosis, drug screening, environment monitoring and the construction of molecule machines. This mini review will focus on the current strategies for the identification and characterization of an individual analyte, especially based on our recent achievements in biological nanopore biosensors.
Dipoles localized at helix termini of proteins stabilize charges. (1991)

The charge-stabilization effect associated with alpha-helices in proteins has been reexamined by microscopic calculations without any a priori assumptions about the dielectric constant of the protein. The calculations reproduce the observed charge stabilization effect of a helix in two well-defined test cases: a histidine residue situated at the C-terminal end of a helix in barnase and the sulfate ligand located near the N-terminal end of a helix of the sulfate-binding protein. They also show that the effective dielectric constant for helix-charge interactions is much larger than previously assumed and that the stabilizing effect of the helix is not associated with the helix macrodipole but rather with a few localized dipoles confined mostly to the first turn of the helix. It is predicted that mutations at one end of the helix should have very small effects on the stabilization of charges at the opposite terminus. It is pointed out that the relatively short-ranged effect of the helix is essentially similar to other cases in which localized dipoles play key roles in electrostatic stabilization.
Structural Deficiencies in Granuloma Formation in TNF Gene-Targeted Mice Underlie the Heightened Susceptibility to Aerosol <i>Mycobacterium tuberculosis</i> Infection, Which Is Not Compensated for by Lymphotoxin (1999)

TNF and lymphotoxin-alpha (LT alpha) may act at various stages of the host response to Mycobacterium tuberculosis. To dissect the effects of TNF independent of LT alpha, we have used C57BL/6 mice with a disruption of the TNF gene alone (TNF-/-). Twenty-one days following aerosol M. tuberculosis infection there was a marked increase in the number of organisms in the lungs of TNF-/- mice, and by 28-35 days all animals had succumbed, with widespread dissemination of M. tuberculosis. In comparison with the localized granulomas containing activated macrophages and T cells in lungs and livers of C57BL/6 wild-type (wt) mice, cellular infiltrates in TNF-/- mice were poorly formed, with extensive regions of necrosis and neutrophilic infiltration of the alveoli. Phenotypic analysis of lung homogenates demonstrated similar numbers of CD4+ and CD8+ T cells in TNF-/- and wt mice, but in TNF-deficient mice the lymphocytes were restricted to perivascular and peribronchial areas rather than colocated with macrophages in granulomas. T cells from TNF-/- mice retained proliferative and cytokine responses to purified protein derivative, and delayed-type hypersensitivity to purified protein derivative was demonstrable. Macrophages within the lungs of TNF-/- and wt mice showed similar levels of MHC class II and inducible nitric oxide synthase expression, and levels of serum nitrite were comparable. Thus, the enhanced susceptibility of TNF-/- is not compensated for by the presence of LT alpha, and the critical role of TNF is not in the activation of T cells and macrophages but in the local organization of granulomas.
Synthesis of large low-redundancy linear arrays (2001)

Aperture synthesis interferometric radiometers can overcome mass, weight and mechanical scan limitations of present-day radiometers. A full antenna array is "thinned" by eliminating selected antennas, while keeping all possible antenna separations. This paper describes a new technique for the direct synthesis of low-redundancy large arrays, consisting in growing small arrays by inserting a seed repeatedly. This technique has achieved the largest thinned arrays with the least redundancy reported in the literature.
Skeletal muscle blood flow abnormalities in rats with a chronic myocardial infarction: rest and exercise (1992)

The purpose of this study was to determine the regional distribution of blood flow deficit in the skeletal muscle vascular bed of rats with a chronic myocardial infarction (MI) and heart failure (HF). Accordingly, blood flow was determined (via radioactive microspheres) in rats with a small infarction (MI less than 30%) and in rats with a large (MI greater than 30%) infarction, induced by surgically ligating the left main coronary artery, and compared with rats that had received a sham operation. Results demonstrate that blood flow to the hindlimb musculature was significantly (P less than 0.05) less during a given level of treadmill exercise (20% grade and speed of 28 m/min) in the MI groups of rats compared with their sham counterparts. These differences in hindlimb blood flow were the result of blood flow deficits found in the individual muscles of the thigh and leg. Moreover, the blood flow deficits were more pronounced in the MI greater than 30% group of rats compared with the MI less than 30% group. The blood flow deficits found for the MI greater than 30% group of rats were positively correlated with the percentage of fast-twitch oxidative-glycolytic fibers and negatively correlated with the percentage of fast-twitch glycolytic fibers found in the individual muscles. Our study supports the contention that MI rats demonstrate skeletal muscle blood flow abnormalities during exercise. It appears that the degree of blood flow abnormalities produced in rats is dependent on the size of the MI and the amount of left ventricular dysfunction produced in the HF state.
Analysis of resveratrol‐induced apoptosis in human B‐cell chronic leukaemia (2002)

Trans-resveratrol was analysed for its apoptotic and growth inhibitory activity in human B-cell lines derived from chronic B-cell malignancies (WSU-CLL and ESKOL), and in leukaemic lymphocytes from patients with B-cell chronic lymphocytic leukaemia (B-CLL). Resveratrol displayed antiproliferative activity on both B-cell lines, as estimated by the decrease in cell recovery and inhibition of thymidine uptake. Furthermore, resveratrol induced apoptosis in the two cell lines as well as in B-CLL patients' cells, as evidenced by the increase in annexin V binding, caspase activation, DNA fragmentation and decrease of the mitochondrial transmembrane potential DeltaPsim. We previously reported that nitric oxide (NO), endogenously released by an iNO synthase (iNOS) spontaneously expressed in these leukaemic cells, contributed to their resistance towards apoptosis. We show here that resveratrol inhibited both iNOS protein expression and in situ NO release in WSU-CLL, ESKOL and B-CLL patients'cells. In addition, Bcl-2 expression was also inhibited by resveratrol. Thus, downregulation of the two anti-apoptotic proteins iNOS and Bcl-2 can contribute to the apoptotic effects of resveratrol in leukaemic B cells from chronic leukaemia. Our data suggest that this drug is of potential interest for the therapy of B-CLL.
A Large-scale Multimodal Study for Predicting Mortality Risk Using Minimal and Low Parameter Models and Separable Risk Assessment (2019)

The majority of biomedical studies use limited datasets that may not generalize over large heterogeneous datasets that have been collected over several decades. The current paper develops and validates several multimodal models that can predict 1-year mortality based on a massive clinical dataset. Our focus on predicting 1-year mortality can provide a sense of urgency to the patients. Using the largest dataset of its kind, the paper considers the development and validation of multimodal models based on 25,137,015 videos associated with 699,822 echocardiography studies from 316,125 patients, and 2,922,990 8-lead electrocardiogram (ECG) traces from 631,353 patients. Our models allow us to assess the contribution of individual factors and modalities to the overall risk. Our approach allows us to develop extremely low-parameter models that use optimized feature selection based on feature importance. Based on available clinical information, we construct a family of models that are made available in the DISIML package. Overall, performance ranges from an AUC of 0.72 with just ten parameters to an AUC of 0.89 with under 105k for the full multimodal model. The proposed approach represents a modular neural network framework that can provide insights into global risk trends and guide therapies for reducing mortality risk.