gebhart/patrepeval huggingface dataset:
Study of mechanical and rheological behaviors of linear and branched polycarbonates blends (2001)

Abstract A study of the mechanical and rheological properties of linear and branched polycarbonates blends is presented. Phase separations of the blends were checked through DSC and SEM, and, subsequently, mechanical and rheological properties were investigated. Phase separations were not observed in the blends. The mechanical properties were examined through tensile, flexural, and impact tests. All the mechanical properties of the blends were relatively independent of the compositions. For study of the rheological properties, melt viscosity, storage and loss moduli, and melt tension of the blends with various compositions were examined at various temperatures. The dependence of the viscosity on the molecular weight was also studied. As the content of branched polycarbonate increases, the dependence of the viscosity on the molecular weight and the shear thinning behavior became more marked. Melt tensions were also increased as the branched polycarbonate content increased in the blends for all tested temperatures. In this study, the blend systems which have same mechanical properties but different rheological properties can be obtained through blending of linear and branched polycarbonates. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 80: 1814–1824, 2001
Observation of a Continuum in Enhanced Raman Scattering from a Metal-Solution Interface (1979)

A background continuum in the Raman spectrum of adsorbed molecules at a silverelectrolyte interface is observed experimentally. This background continuum is potential dependent on the Stokes and anti-Strokes of the spectrum and fits a Fermi distribution function on the anti-Stokes side of the spectrum. The continuum is interpreted in terms of radiative recombination of adsorbed molecular ions produced by photoionization.
Noisy Stepped Frequency (NSF) waveform in RF tomography (2012)

Radio Frequency (RF) tomography has been proposed for imaging dielectric and conducting anomalies above-ground. Accordingly, low-cost electromagnetic transmitters are placed arbitrarily above ground, surrounding a large area of interest. In a preliminary stage, sensors identify their position, orientation, and time reference. Subsequently, a transmitter radiates a known waveform. The probing wave impinges upon a target (represented in terms of dielectric or conducting anomaly), thus producing scattered elds. Spatially distributed receivers collect samples of the total electric eld, remove noise, clutter and the direct path, and store the information concerning only the scattered eld. In the next iteration, a dierent transmitter is activated, or dierent wave- forms are used. Then, the collected data is typically relayed to a centralized location for processing and imaging. To ensure persistent sensing, fast back-propagation algorithms are implemented (either involving correlation or multiplication by a hermitian matrix). Resolution using back-propagation is aected by the sidelobe structure of the ambiguity function of the wave. Clearly, Linearly Stepped Frequency (LSF) waveform requires the lowest instantaneous bandwidth, but produces poor correlation properties. On the converse, Noise waveforms exhibit the idealized thumb-tack ambiguity function but typically require large instantaneous bandwidths. In an eort to exploit the benets of both individual waveforms, a noisy LSF waveform is developed. The NLSF performance, limitation and spectral dominance in reference to RF Tomography, along with its theoretical bounds, will be provided. Reconstructed images from simulated and experimental data will be compared.
TOR and RAS pathways regulate desiccation tolerance in<i>Saccharomyces cerevisiae</i> (2012)

Tolerance to desiccation in cultures of Saccharomyces cerevisiae is inducible; only one in a million cells from an exponential culture survive desiccation compared with one in five cells in stationary phase. Here we exploit the desiccation sensitivity of exponentially dividing cells to understand the stresses imposed by desiccation and their stress response pathways. We found that induction of desiccation tolerance is cell autonomous and that there is an inverse correlation between desiccation tolerance and growth rate in glucose-, ammonia-, or phosphate-limited continuous cultures. A transient heat shock induces a 5000-fold increase in desiccation tolerance, whereas hyper-ionic, -reductive, -oxidative, or -osmotic stress induced much less. Furthermore, we provide evidence that the Sch9p-regulated branch of the TOR and Ras-cAMP pathway inhibits desiccation tolerance by inhibiting the stress response transcription factors Gis1p, Msn2p, and Msn4p and by activating Sfp1p, a ribosome biogenesis transcription factor. Among 41 mutants defective in ribosome biogenesis, a subset defective in 60S showed a dramatic increase in desiccation tolerance independent of growth rate. We suggest that reduction of a specific intermediate in 60S biogenesis, resulting from conditions such as heat shock and nutrient deprivation, increases desiccation tolerance.
Postoperative hemodynamic instability and monitoring (2016)

When coupled with a focused physical examination and functional hemodynamic monitoring analyses, these measures become even more specific at defining volume responsiveness and vasomotor tone and can be used to drive resuscitation strategies.
Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification (2018)

This paper proposes a knowledge-guided fashion network to solve the problem of visual fashion analysis, e.g., fashion landmark localization and clothing category classification. The suggested fashion model is leveraged with high-level human knowledge in this domain. We propose two important fashion grammars: (i) dependency grammar capturing kinematics-like relation, and (ii) symmetry grammar accounting for the bilateral symmetry of clothes. We introduce Bidirectional Convolutional Recurrent Neural Networks (BCRNNs) for efficiently approaching message passing over grammar topologies, and producing regularized landmark layouts. For enhancing clothing category classification, our fashion network is encoded with two novel attention mechanisms, i.e., landmark-aware attention and category-driven attention. The former enforces our network to focus on the functional parts of clothes, and learns domain-knowledge centered representations, leading to a supervised attention mechanism. The latter is goal-driven, which directly enhances task-related features and can be learned in an implicit, top-down manner. Experimental results on large-scale fashion datasets demonstrate the superior performance of our fashion grammar network.
The expression of tousled kinases in CaP cell lines and its relation to radiation response and DSB repair (2011)

TLKs appear to be intimately linked to the pattern of resistance to DNA damage, and specifically DSBs, a finding that was not reported before for any cell lines, and certainly not systematically for human prostate cell lines.
Applications of the median filter to digital radiographic images (2005)

It is well known that Digital Subtraction Angiography (DSA) images suffer from the influence of noise. Linear filters have been applied to DSA images with some success but are known to introduce image degradation. It is particularly important that edge details be preserved in DSA images since the outline of vessels frequently contains the diagnostically useful information. The non-linear median filter possesses the property of removing spurious noise while preserving edge detail in an image. In the work presented here the difficulties of applying a median filter in two dimensions to the cartesian matrix of a typical image are investigated. The development of a suitable noise-added test image for this purpose is presented.
Evaluation of energy expenditure and cardiovascular health effects from Tai Chi and walking exercise. (2009)

1. A 12-week Tai Chi or walking exercise intervention produced significant and similar beneficial effects on body composition, aerobic fitness, muscular fitness, fasting blood glucose, resting metabolic rate, and perceived health in middle-aged Chinese. 2. While Tai Chi and walking both elicited significant cardiorespiratory responses and energy expenditure to the moderate intensity level, walking exercise elicited about 46% higher metabolic cost than Tai Chi exercise.
Oxygen addition effects in synchrotron radiation excited etching using SF6 (1991)

The effects of oxygen addition on the synchrotron radiation-excited etching of crystal Si, poly-Si, and SiO2 using SF6 reaction gas are investigated. Without oxygen, two phenomenologically classified reaction mechanisms are observed: gas phase and surface excitation mechanisms. With oxygen addition, the gas phase excitation mechanism disappears and only the surface excitation mechanism becomes dominant. Oxygen addition is extremely effective in the microfabrication of SiO2 line and space patterns using poly-Si as an etching mask. Its addition creates high selectivity between SiO2 and crystal Si. Furthermore, it is considered that the added oxygen removes some etching suppressing species generated on the poly-Si surface.
A New Possible Mechanism by Which Punicalagin Protects against Liver Injury Induced by Type 2 Diabetes Mellitus: Upregulation of Autophagy via the Akt/FoxO3a Signaling Pathway (2019)

The aim of this study was to investigate the protective effect of punicalagin (PU), which is a main component of pomegranate polyphenols, against liver injury induced by Type 2 diabetes mellitus (T2DM) and to explore the molecular mechanism based on autophagy in vivo and in vitro. In T2DM mice, we found that PU significantly improved liver histology, reversed serum biochemical abnormalities, and increased the autophagosome number in the liver. In HepG2 cells cultured in a high-glucose environment, PU upregulated the glucose uptake level. Both in vivo and in vitro, PU upregulated the expression of autophagy-related proteins, such as LC3b and p62, and reduced the phosphorylated Akt/total Akt and phosphorylated FoxO3a/total FoxO3a protein ratios, and these effects were enhanced by LY294002 (a PI3K/Akt inhibitor). In summary, our current findings suggest that PU protects against liver injury induced by T2DM by restoring autophagy through the Akt/FoxO3a signaling pathway.
Forecasting, Sensitivity and Economic Analysis of Hydrocarbon Production from Shale Plays Using Artificial Intelligence & Data Mining (2012)

Abstract Our understanding of the complexities of the flow mechanism in Shale plays has not kept up with our industry’s interest in these prolific and hydrocarbon rich formations. Furthermore, massive multi-cluster, multi-stage hydraulic fractures, that have proven to be essential for economic recovery from Shale plays, have significantly increased the complexity of the flow behavior and consequently have made the modeling efforts more challenging. In this paper, the application of a recently developed AI (Artificial Intelligence)-based reservoir modeling approach on Marcellus Shale is presented. In this approach, data mining and pattern recognition techniques were used to initiate modeling of the hydrocarbon production (dray gas and condensate) from Marcellus Shale. Instead of imposing our understanding of flow and transport in shale gas media, which is a very complex and non-linear system, we allow the production history, reservoir characteristics, and hydraulic fracturing data and operational constraint to force their will on our model and determine its behavior. In this work, the full-field history matching process was performed on a Marcellus shale asset including 135 wells with multiple pads and different landing targets. The full field AI-based Marcellus Shale model then used for forecasting the future well/reservoir performance to assist in planning field development strategies. The goodness of match quality is self-evident, thereby validating this modeling approach. Nevertheless, to examine the model validity in the forecasting mode, the field data was partially matched and then attempted forecasting. Taking validation one-step further, the production performance of a recently drilled well, which was completely blind to the model (was not involved during training and initial validation), was predicted and compared with actual field measurement. Furthermore, sensitivity and economic analysis are performed in order to identify the impact of different reservoir descriptions (e.g. different reservoir characteristics, stimulation and completion factors) and rank the impact of above-mentioned parameters on the Net Present Value (NPV) of investing on gas wells producing from Marcellus Shale.
A Technology-Assisted Design Methodology for Employee-Driven Innovation in Services (2015)

IntroductionThe increasing complexity of service processes and the increasing variety of customer needs in the service industry had highlighted the role of employees in promoting innovation. Employees in many service fields are required to respond to customers and other employees both flexibly and autonomously. Their skills and practical knowledge of services are highly
Event processing under uncertainty (2012)

Big data is recognized as one of the three technology trends at the leading edge a CEO cannot afford to overlook in 2012. Big data is characterized by volume, velocity, variety and veracity ("data in doubt"). As big data applications, many of the emerging event processing applications must process events that arrive from sources such as sensors and social media, which have inherent uncertainties associated with them. Consider, for example, the possibility of incomplete data streams and streams including inaccurate data. In this tutorial we classify the different types of uncertainty found in event processing applications and discuss the implications on event representation and reasoning. An area of research in which uncertainty has been studied is Artificial Intelligence. We discuss, therefore, the main Artificial Intelligence-based event processing systems that support probabilistic reasoning. The presented approaches are illustrated using an example concerning crime detection.
Combining MEMS-based IMU data and vision-based trajectory estimation (2014)

Abstract. This paper presents an efficient location tracking algorithm that integrates vision-based motion estimation and IMU data. Orientation and translation parameters of the mobile device are estimated from video frames or highly overlapped image sequences acquired with built-in cameras of mobile devices. IMU data are used to maintain continuity of the orientation estimation between sampling of the image homography calculation. The developed algorithm consists of six primary steps: (1) pre-processing; (2) feature points detection and matching; (3) homography calculation; (4) control points detection and registration; (5) motion estimation and filtering; (6) IMU data integration. The pre-processing of the input video frames or images is to control the sampling rate and image resolution in order to increase the computing efficiency. The overlap rate between selected frames is designed to remain above 60 % for matching. After preprocessing, feature points will be extracted and matched between adjacent frames as the conjugate points. A perspective homography is constructed and used to map one image to another if the co-planar feature points between subsequent images are fully matched. The homography matrix can provide the camera orientation and translation parameters according to the conjugate pairs. An area-based image-matching method is employed to recognize landmarks as reference nodes (RNs). In addition, a filtering mechanism is proposed to ensure the rotation angle was correctly recorded and to increase the tracking accuracy. Comparisons of the trajectory results with different combinations among vision-based motion estimation, filtering mechanism and IMU data integration are evaluated thoroughly and the accuracy is validated with on-site measurement data. Experimental results indicate that the develop algorithm can effectively estimate the trajectory of moving mobile devices and can be used as a cost-effective alternative for LBS device both in outdoor and indoor environment.
Metasurface-generated complex 3-dimensional optical fields for interference lithography (2019)

Fast, large-scale, and robust 3-dimensional (3D) fabrication techniques for patterning a variety of structures with submicrometer resolution are important in many areas of science and technology such as photonics, electronics, and mechanics with a wide range of applications from tissue engineering to nanoarchitected materials. From several promising 3D manufacturing techniques for realizing different classes of structures suitable for various applications, interference lithography with diffractive masks stands out for its potential to fabricate complex structures at fast speeds. However, the interference lithography masks demonstrated generally suffer from limitations in terms of the patterns that can be generated. To overcome some of these limitations, here we propose the metasurface-mask-assisted 3D nanofabrication which provides great freedom in patterning various periodic structures. To showcase the versatility of this platform, we design metasurface masks that generate exotic periodic lattices like gyroid, rotated cubic, and diamond structures. As a proof of concept, we experimentally demonstrate a diffractive element that can generate the diamond lattice.
MAC design for analog network coding (2011)

Most medium access control (MAC) mechanisms discard collided packets and consider interference harmful. Recent work on Analog Network Coding (ANC) suggests a different approach, in which multiple interfering transmissions are strategically scheduled. Receiving nodes collect the results of collisions and then use a decoding process, such as ZigZag decoding, to extract the packets involved in the collisions.
Molecular Pathogenesis and Targeted Therapies for Intrahepatic Cholangiocarcinoma (2015)

Intrahepatic cholangiocarcinoma (iCCA) is a molecularly heterogeneous hepatobiliary neoplasm with poor prognosis and limited therapeutic options. The incidence of this neoplasm is growing globally. One third of iCCA tumors are amenable to surgical resection, but most cases are diagnosed at advanced stages with chemotherapy as the only established standard of practice. No molecular therapies are currently available for the treatment of this neoplasm. The poor understanding of the biology of iCCA and the lack of known oncogenic addiction loops has hindered the development of effective targeted therapies. Studies with sophisticated animal models defined IDH mutation as the first gatekeeper in the carcinogenic process and led to the discovery of striking alternative cellular origins. RNA- and exome-sequencing technologies revealed the presence of recurrent novel fusion events (FGFR2 and ROS1 fusions) and somatic mutations in metabolic (IDH1/2) and chromatin-remodeling genes (ARID1A, BAP1). These latest advancements along with known mutations in KRAS/BRAF/EGFR and 11q13 high-level amplification have contributed to a better understanding of the landscape of molecular alterations in iCCA. More than 100 clinical trials testing molecular therapies alone or in combination with chemotherapy including iCCA patients have not reported conclusive clinical benefits. Recent discoveries have shown that up to 70% of iCCA patients harbor potential actionable alterations that are amenable to therapeutic targeting in early clinical trials. Thus, the first biomarker-driven trials are currently underway.
Robust Principal Component Analysis with Complex Noise (2014)

The research on robust principal component analysis (RPCA) has been attracting much atten-tion recently. The original RPCA model assumes sparse noise, and use the L1-norm to characterize the error term. In practice, however, the noise is much more complex and it is not appropriate to simply use a certainLp-norm for noise modeling. We propose a generative RPCA model under the Bayesian framework by modeling data noise as a mixture of Gaussians (MoG). The MoG is a uni-versal approximator to continuous distributions and thus our model is able to fit a wide range of noises such as Laplacian, Gaussian, sparse noises and any combinations of them. A varia-tional Bayes algorithm is presented to infer the posterior of the proposed model. All involved parameters can be recursively updated in closed form. The advantage of our method is demon-strated by extensive experiments on synthetic da-ta, face modeling and background subtraction. 1.
ANOMALY-BASED DATA MINING OF INTRUSIONS (2002)

Security of computer systems is essential to their acceptance and utility. Computer security analysts use intrusion detec-tion systems to assist them in maintaining computer system security. This paper deals with the problem of differenti-ating between masqueraders and the true user of a com-puter terminal. Prior efficient solutions are less suited to real time application, often requiring all training data to be labeled, and do not inherently provide an intuitive idea of what the data model means. Our system, called ADMIT, re-laxes these constraints, by creating user profiles using semi-incremental techniques. It is a real-time intrusion detection system with host-based ata collection and processing. Our method also suggests ideas for dealing with concept drift and affords a detection rate as high as 80.3 % and a false positive rate as low as 15.3%. 1.
A multicast transport protocol (1988)

This paper presents the design of a reliable multicast transport protocol. The aim of the protocol is to provide a service equivalent to a sequence of reliable sequential unicasts between a client and a number of servers, whilst using the broadcast nature of some networks to reduce both the number of packets transmitted and the overall time needed to collect replies.
Regulation of GLI1 by cis DNA elements and epigenetic marks (2019)

GLI1 is one of three transcription factors (GLI1, GLI2 and GLI3) that mediate the Hedgehog signal transduction pathway and play important roles in normal development. GLI1 and GLI2 form a positive-feedback loop and function as human oncogenes. The mouse and human GLI1 genes have untranslated 5' exons and large introns 5' of the translational start. Here we show that Sonic Hedgehog (SHH) stimulates occupancy in the introns by H3K27ac, H3K4me3 and the histone reader protein BRD4. H3K27ac and H3K4me3 occupancy is not significantly changed by removing BRD4 from the human intron and transcription start site (TSS) region. We identified six GLI binding sites (GBS) in the first intron of the human GLI1 gene that are in regions of high sequence conservation among mammals. GLI1 and GLI2 bind all of the GBS in vitro. Elimination of GBS1 and 4 attenuates transcriptional activation by GLI1. Elimination of GBS1, 2, and 4 attenuates transcriptional activation by GLI2. Eliminating all sites essentially eliminates reporter gene activation. Further, GLI1 binds the histone variant H2A.Z. These results suggest that GLI1 and GLI2 can regulate GLI1 expression through protein-protein interactions involving complexes of transcription factors, histone variants, and reader proteins in the regulatory intron of the GLI1 gene. GLI1 acting in trans on the GLI1 intron provides a mechanism for GLI1 positive feedback and auto-regulation. Understanding the combinatorial protein landscape in this locus will be important to interrupting the GLI positive feedback loop and providing new therapeutic approaches to cancers associated with GLI1 overexpression.