gebhart/patrepeval huggingface dataset:
Matriptase-3 is a novel phylogenetically preserved membrane-anchored serine protease with broad serpin reactivity (2005)

We report in the present study the bioinformatic identification, molecular cloning and biological characterization of matriptase-3, a novel membrane-anchored serine protease that is phylogenetically preserved in fish, birds, rodents, canines and primates. The gene encoding matriptase-3 is located on syntenic regions of human chromosome 3q13.2, mouse chromosome 16B5, rat chromosome 11q21 and chicken chromosome 1. Bioinformatic analysis combined with cDNA cloning predicts a functional TTSP (type II transmembrane serine protease) with 31% amino acid identity with both matriptase/MT-SP1 and matriptase-2. This novel protease is composed of a short N-terminal cytoplasmic region followed by a transmembrane domain, a stem region with one SEA, two CUB and three LDLRa (low-density lipoprotein receptor domain class A) domains and a C-terminal catalytic serine protease domain. Transcript analysis revealed restricted, species-conserved expression of matriptase-3, with the highest mRNA levels in brain, skin, reproductive and oropharyngeal tissues. The full-length matriptase-3 cDNA directed the expression of a 90 kDa N-glycosylated protein that localized to the cell surface, as assessed by cell-surface biotin labelling. The purified activated matriptase-3 serine protease domain expressed in insect cells hydrolysed synthetic peptide substrates, with a strong preference for Arg at position P(1), and showed proteolytic activity towards several macromolecular substrates, including gelatin, casein and albumin. Interestingly, activated matriptase-3 formed stable inhibitor complexes with an array of serpins, including plasminogen activator inhibitor-1, protein C inhibitor, alpha1-proteinase inhibitor, alpha2-antiplasmin and antithrombin III. Our study identifies matriptase-3 as a novel biologically active TTSP of the matriptase subfamily having a unique expression pattern and post-translational regulation.
Testes-specific protease 50 (TSP50) promotes invasion and metastasis by inducing EMT in gastric cancer (2018)

TSP50 promotes the proliferation, migration and invasion of gastric cancer cells involving NF-κB dependent EMT activation. Targeting TSP50 may provide a novel therapeutic strategy for the management of gastric cancer.
Synthesis, characterization, and properties of polychelates of poly(styrene sulfonic acid‐<i>co</i>‐maleic acid) with Co(II), Cu(II), Ni(II), and Zn(II) (2002)

Abstract Polymer metal complexes of poly(styrene sulfonic acid‐ co ‐maleic acid) and Cu(II), Ni(II), Co(II), and Zn(II) were synthesized. The magnetic, spectral, and thermal properties, as well as the electrical conductivities, of the chelates were investigated, and possible structures were assigned to the polychelates. Semiempirical calculations at the AM1 level were carried out on the geometrical arrangement of the polychelates. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2546–2551, 2002
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge (2017)

In many machine learning applications, labeled data is scarce and obtaining more labels is expensive. We introduce a new approach to supervising neural networks by specifying constraints that should hold over the output space, rather than direct examples of input-output pairs. These constraints are derived from prior domain knowledge, e.g., from known laws of physics. We demonstrate the effectiveness of this approach on real world and simulated computer vision tasks. We are able to train a convolutional neural network to detect and track objects without any labeled examples. Our approach can significantly reduce the need for labeled training data, but introduces new challenges for encoding prior knowledge into appropriate loss functions.
A visual analytics approach to high-dimensional logistic regression modeling and its application to an environmental health study (2016)

In the domain of epidemiology, logistic regression modeling is widely used to explain the relationships among explanatory variables and dichotomous outcome variables. However, logistic regression modeling faces challenges such as overfitting, confounding, and multicollinearity when there is a large number of explanatory variables. For example, in the birth defect study presented in this paper, variable selection for building high quality models to identify risk factors from hundreds of pollutant variables is difficult. To address this problem, we propose a novel visual analytics approach to logistic regression modeling for high-dimensional datasets. It leverages the traditional modeling pipeline by providing (1) intuitive visualizations for inspecting statistical indicators and the relationships among the variables and (2) a seamless, effective dimension reduction pipeline for selecting variables for inclusion in high quality logistic regression models. A fully working prototype of this approach has been developed and successfully applied to the birth defect study, which illustrates its effectiveness and efficiency. Its application in an insurance policy study and feedback from domain experts further demonstrate its usefulness.
The "gated-diode" configuration in MOSFET's, a sensitive tool for characterizing hot-carrier degradation (1995)

This paper describes a new measurement technique, the forward gated-diode current characterized at low drain voltages to be applied in MOSFET's for investigating hot-carrier stress-induced defects at high spatial resolution. The generation/recombination current in the drain-to-substrate diode as a function of gate voltage, combined with two-dimensional numerical simulation, provides a sensitive tool for detecting the spatial distribution and density of interface defects. In the case of strong accumulation, additional information is obtained from interband tunneling processes occurring via interface defects. The various mechanisms for generating interface defects and fixed charges at variable stress conditions are discussed, showing that information complementary to that available from other methods is obtained.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
New plasma processes for antireflective structures on plastics (2008)

A new technology based on plasma etching has been developed to produce antireflective surface structures. By choosing thin initial layers and variable plasma conditions, a broad range of nanostructures can be obtained on various polymers. A broadband antireflective effect can be achieved that is less sensitive to the incident angle of light compared to multilayer interference coatings. Thin layers of silica help in mechanical protection, especially if the structured surface is nearly enclosed by the protection layer. In addition, surfaces that show both antireflective properties and an antifogging effect have been prepared. Combinations of SiO<sub>2</sub> and fluorine-containing layers were found to be useful in obtaining super-hydrophobic behavior. This advanced plasma etching is not limited to a special plasma source and the suitability of different plasma sources is discussed.
DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis (2017)

In this paper we present two deep-learning systems that competed at SemEval-2017 Task 4 "Sentiment Analysis in Twitter". We participated in all subtasks for English tweets, involving message-level and topic-based sentiment polarity classification and quantification. We use Long Short-Term Memory (LSTM) networks augmented with two kinds of attention mechanisms, on top of word embeddings pre-trained on a big collection of Twitter messages. Also, we present a text processing tool suitable for social network messages, which performs tokenization, word normalization, segmentation and spell correction. Moreover, our approach uses no hand-crafted features or sentiment lexicons. We ranked 1 st (tie) in Subtask A, and achieved very competitive results in the rest of the Subtasks. Both the word embeddings and our text processing tool 1 are available to the research community.
Isolation of a Highly Strained Bicyclic Alkyne (1981)

Being a cyctoalkyne and a bicyclo[n.1.0]-derivative at the same time is a unique feature of the compounds (1a) and (1b). Both were generated from the corresponding tricyclic selenadiazoles. (1) is isolable, (1b) can be trapped.
<I>Secretion of Transforming Growth Factor-β1 and -β2 by Malignant Glioma Cells</I> (1995)

The secretion of transforming growth factor-beta (TGF-beta), a growth inhibitory factor with immunosuppressive properties, was investigated in one glioblastoma cell line and seven surgically resected malignant glioma cells. Cultured cells from surgically resected tumors were examined immunohistochemically for glial fibrillary acidic protein (GFAP) and S-100 protein. The levels of TGF-beta 1 and TGF-beta 2 in culture supernatants from malignant glioma cells were determined by a specific bioassay using anti-TGF-beta 1 and anti-TGF-beta 2 antibodies. Two glioblastoma cell lines were cultured in the presence of TGF-beta 1 or TGF-beta 2 to assess the effect of TGF-beta on the growth of glioblastoma cells. Cultured cells from surgically resected tumors were positive for both GFAP and S-100 protein. Both active and latent forms of TGF-beta 1 and TGF-beta 2 were detected in the culture supernatants from malignant gliomas, except in one patient with anaplastic astrocytoma which secreted only latent forms of TGF-beta 1 and TGF-beta 2. There was no statistical difference in the levels of TGF-beta 1 and TGF-beta 2 in glioblastomas and anaplastic astrocytomas. Neither TGF-beta 1 nor TGF-beta 2 affected the growth of glioblastoma cells. These findings suggest that most malignant glioma cells secrete both TGF-beta 1 and TGF-beta 2, can convert TGF-beta from a latent to active form, and may suppress cytokine secretion by activated lymphocytes in vivo as well as in vitro.
Enhanced bistability by guest inclusion in Fe(ii) spin crossover porous coordination polymers (2012)

Inclusion of thiourea guest molecules in the tridimensional spin crossover porous coordination polymers {[Fe(pyrazine)[M(CN)(4)]} (M = Pd, Pt) leads to novel clathrates exhibiting unprecedented large thermal hysteresis loops of ca. 60 K wide centered near room temperature.
Novel state-of-health diagnostic method for Li-ion battery in service (2016)

The development of improved State-of-Health (SoH) diagnostic methods is a current research topic for battery-powered applications. For instance, the current rapid development of Electric Vehicles (EV) creates a strong demand for an accurate and reliable on-board SoH indicator during operation. Such an indicator is a key parameter required to optimize battery energy management and to track the degradation of the system performance. The electrochemical impedance spectrum (EIS) of an electrochemical system is a powerful lab-based diagnostic technique, usually measured using a frequency response analyzer. In this paper, we present an innovative diagnostic technique based on analysis of free voltage and current signals to give a so called “quasi-electrochemical impedance spectrum” (QEIS) and demonstrate its application on a Li-ion battery during a real EV duty cycle. It is worth noting that in our technique no additional signal is applied to the cell, since the current flowing into cells during use on-board is directly processed in the data treatment step. Commercial batteries (1.4 Ah cylindrical LiFePO4/graphite cell) were selected in this study to validate the diagnostic method in the framework of an applied case study related to an electric school bus demonstrator. In order to study the capability of QEIS measurements as a diagnostic tool for SoH of Li-ion cells, a test procedure including ageing phases has been defined to characterise Li-ion cells before and during ageing. Voltage and current signals were treated by Fast Fourier Transform (FFT) in order to determine the QEIS spectra of Li-ion cells under study. Then, SoH prediction algorithms have been obtained from a mathematical analysis of the impedance parameters sensitive to SoH.
Runlength limited binary error control codes (1992)

A systematic procedure is presented for modifying standard binary error control codes (ECCs) to form runlength-limited ECCs without reducing rates or affecting minimum distances. This procedure is then optimised to find the tightest runlength bound given an ECC defined by its generator matrix. A simple example based on the BCH (15, 5) ECC is presented to illustrate the procedure, which is nonetheless more generally applicable. The effects of the modification on spectral characteristics are also considered.
Antimicrobial effect of pressurised carbon dioxide onEnterococcus faecalis in physiological saline and foods (2000)

Inactivation of Enterococcus faecalis by high-pressure CO2 was investigated in a batch system. Two phases were observed in the survival curves. The earlier stage was characterised by a slow rate of decrease in the number of E faecalis. This rate increased sharply at the later stage. Enterococcus faecalis suspended in physiological saline was completely inactivated under 6.05 and 3.02 MPa CO2 treatment in 18 and 80 min respectively at 35 ° C. The high pressure of CO2 at 45 ° C was effective at sterilising orange, peach and carrot juices but ineffective for whole and skimmed milk. A minimum D-value was obtained under 6.05 MPa CO2 pressure at 45 ° C. Reduction rates of E faecalis were sensitive to pressure, temperature, exposure time, the initial number of cells and the suspending medium. © 2000 Society of Chemical Industry
SLA-Aware Multi-Criteria Data Placement in Cloud Storage Systems (2021)

This paper proposes a multi-criteria data placement mechanism for typical cloud storage systems. The primary goal of this study is to place the clients' files in the storage cluster by taking into account the principles of service level agreements and the levels of user support services. For this purpose, a multi-criteria scoring model is defined based on a trade-off between three criteria that can be crucial from the clients' viewpoint: data access latency, data privacy, and computational performance. The second goal of the proposed mechanism is to improve the fairness of the storage allocation mechanism for various kinds of files compared to the conventional mechanisms. In this case, the cloud service provider gives each data storage node a chance to become the host of an already received file using a probabilistic ranking model. The experimental results demonstrate that the proposed data placement mechanism increases the robustness of cloud storage architecture under different file, network, and storage configurations compared to the existing data placement mechanisms.
The Limit-Switched Loop: A Phase-Locked Loop for Burst Mode Operation (1982)

In a time-division or burst mode communications systems, synchronization must be achieved within a short preamble time at the beginning of each burst. When used in such a system, a conventional phase-locked loop (PLL) occasionally exhibits a prolonged phase acquisition transient. This effect, known as hangup, occurs at a large value of phase error and may cause loss of a data burst. The present paper investigates a modification of a PLL known as a limit-switched loop (LSL). The LSL offers faster phase acquisition and better hangup immunity than a PLL. The LSL estimates its position in the phase plane at the beginning of acquisition and, if hangup is about to occur, makes a phase correction so as to forestall its occurrence. The structure and properties of the LSL are investigated in this paper.
Eradication of a Large Outbreak of a Single Strain of vanB Vancomycin-Resistant <i>Enterococcus faecium</i> at a Major Australian Teaching Hospital (2004)

Despite widespread dissemination of VRE in a large acute care facility, eradication was achievable by a well-resourced, coordinated, multifaceted approach and was in accordance with good clinical governance.
Non-contiguous processor allocation algorithms for distributed memory multicomputers (1994)

Current processor allocation techniques for highly parallel systems have thus far been restricted to contiguous allocation strategies for which performance suffers significantly due to the inherent problem of fragmentation. We are investigating processor allocation algorithms which lift the restriction on contiguity of processors in order to address the problem of fragmentation. Three non-contiguous processor allocation strategies: Naive, Random and the Multiple Buddy Strategy (MBS) are proposed and studied in this paper. Simulations compare the performance of the non-contiguous strategies with that of several well-known contiguous algorithms. We show that non-contiguous allocation algorithms perform better overall than the contiguous ones, even when message-passing contention is considered. We also present the results of experiments on an Intel Paragon XP/S-15 with 208 nodes that show non-contiguous allocation is feasible with current technologies.
Development of a chronic toxicity structure-activity relationship for alkyl sulfates (1997)

Much of the historical data regarding the toxicity of alkyl sulfate (AS) surfactants to aquatic organisms have been compromised due to excessive loss of the parent material via biodegradation and precipitation—processes especially important during chronic tests. To minimize these issues, a novel flow-through system for Ceriodaphnia dubia was developed and acute and chronic toxicity data were obtained for several AS structures. Acute toxicity increased linearly with increased alkyl chain length (CL) from C12AS to C16AS. However, a parabolic response was observed for reproduction where toxicity increased with alkyl chainlength from C12AS to C14AS, but decreased with increased chain length from C14AS to C18AS. Soluble vs precipitated forms of AS contribute to the parabolic relationship. A quadratic approach using the chronic end points no observed effect concentration, lowest observed effect concentration, maximum acceptable toxicant concentration, EC50, and EC20 yielded the best fit for EC20 (R2=0.99). Quantitative structure–activity relationships for AS, based on acute toxicity alone, overpredict chronic toxicity at chainlengths greater than C14AS. Use of the quadratic model [EC20(M)=5.12×10−7(CL)2−1.49×10−5(CL)+11.1×10−5] is advocated for use in environmental risk assessment. © 1997 John Wiley & Sons, Inc. Environ Toxicol Water Qual 12: 295–303, 1997
Signal strength prediction in built-up areas. Part 2: Signal variability (1983)

Analysis of mobile radio propagation results in London at 168, 455 and 900 MHz has shown that over small areas the signal envelope is well described by Rayleigh statistics, the local mean over larger similar areas being lognormally distributed. A comparison of different statistical distributions has been undertaken to provide a bridge between the local and global statistics and it shows that the experimental data are best fitted by a Suzuki (Rayleigh plus log-normal) distribution, the lognormal part having a standard deviation of approximately 4 dB. Values near the tails of the distribution can thereby be described with good accuracy, and hence the propagation prediction model is useful for area coverage estimation and frequency reuse planning.
Seizure prediction based on classification of EEG synchronization patterns with on-line retraining and post-processing scheme (2011)

Epilepsy is one of the most common brain disorders in the world. The spontaneous seizure onset influences the daily life of epilepsy patients. The studies on feature extraction and feature classification from Electroencephalography(EEG) signal in seizure prediction methods have shown great improvement these years. However, the variation issue of EEG signal (being awake, being asleep, severity of epilepsy, etc.) poses a fundamental difficulty in seizure prediction problem. The traditional off-line training method trains the model using a fixed training set, and expects the performance of the model to remain stable even after a long period of time, and thus suffers from variation issue. In this paper, we propose an on-line retraining method to leverage the recent input data by gradually enlarging the training set and retraining the model. Also, a simple post-processing scheme is incorporated to reduce false alarms. We develop our method based on the state of the art machine learning based classification of bivariate patterns method. The performance of the method is evaluated on Electrocorticogram(ECoG) recording from Freiburg database as well as long-term scalp EEG recording from CHB-MIT EEG Database and National Taiwan University Hospital. The proposed method achieves 74.2% sensitivity on ECoG database and 52.2% sensitivity on scalp EEG database, while improving the sensitivity of off-line training method by 29.0% and 17.4% in ECoG database and EEG database respectively. The experimental result suggests that on-line retraining can greatly improve the reliability and is promising for future seizure prediction method development.
Study the most favorable shapes of electrostatic quadrupole doublet lenses (2017)

The optical properties of an electrostatic quadrupole doublet lens with two different electrode shapes were studied with the aid of computer simulation. The optimal electrode voltages of the electrostatic quadrupole lenses which give the stigmatic image in both planes simultaneously were found for both concave cylindrical electrode shape and plan electrode shape of the operation mode: parallel to point focusing. The effect of electrode shape on the image properties was investigated, and the aberration figures were studied. The results showed that under the same operation condition and the geometrical dimensions, the changing of the electrode shape of the electrostatic quadrupole doublet lenses lead to important differences in the optical properties of the lenses and the characteristics of the systems.
Fast Appearance Modeling for Automatic Primary Video Object Segmentation (2015)

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.