gebhart/patrepeval huggingface dataset:
Predicting Infectious Disease Using Deep Learning and Big Data (2018)

Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It is a problem that causes harm at both individual and macro scales. The Korea Center for Disease Control (KCDC) operates a surveillance system to minimize infectious disease contagions. However, in this system, it is difficult to immediately act against infectious disease because of missing and delayed reports. Moreover, infectious disease trends are not known, which means prediction is not easy. This study predicts infectious diseases by optimizing the parameters of deep learning algorithms while considering big data including social media data. The performance of the deep neural network (DNN) and long-short term memory (LSTM) learning models were compared with the autoregressive integrated moving average (ARIMA) when predicting three infectious diseases one week into the future. The results show that the DNN and LSTM models perform better than ARIMA. When predicting chickenpox, the top-10 DNN and LSTM models improved average performance by 24% and 19%, respectively. The DNN model performed stably and the LSTM model was more accurate when infectious disease was spreading. We believe that this study's models can help eliminate reporting delays in existing surveillance systems and, therefore, minimize costs to society.
3-D broad-band estimates of reflector dip and amplitude (2000)

Abstract Estimates of seismic coherence of 3-D data sets have provided a radically new way of delineating detailed structural and stratigraphic features. Covariance matrices provide the natural formalism to extend the original three-trace crosscorrelation algorithm to larger analysis windows containing multiple traces, thus providing greater fidelity in low signal-to-noise environments. By use of 3-D phase compensation using Radon transforms, we exploit advances made in the high-resolution multiple signal classification (MUSIC) algorithms, originally developed for the defense industry. All three families of multitrace attributes (coherence, amplitude, and phase) are coupled through the underlying geology, such that we obtain three families of complimentary images of geologic features that result in lateral changes in wave form. The phase attributes of dip/azimuth and curvature allow us to image areas that have undergone folding or draping that can not be seen on coherence or amplitude images. The amplitude attributes allow us to image oil/water contacts or other areas of amplitude variation that may not be seen on coherence or dip/azimuth images. Coupled with coherence and the conventional seismic data, these new multitrace dip and amplitude data cubes can greatly accelerate the interpretation of the major features of large 3-D data volumes. At the reservoir scale, they will be of significant help in delineation of subtle internal variations of lithology, porosity, and diagenesis. In computer-assisted interpretation, we strongly feel these new attributes will become the building blocks for the application of modern texture analysis and segmentation algorithms to the delineation of geologic features.
Characteristics of Wallet Contracts on Ethereum (2020)

For the management of cryptocurrencies or cryptographic tokens, many users employ a software wallet that facilitates the interaction with a blockchain in general or with on-chain programs (smart contracts) in particular. While many blockchain wallets execute their core program code off-chain, some wallets implement core functionality on-chain as smart contracts with the intent to increase trust and security by using transparent and verifiable execution.In this work, we investigate smart contracts for wallets with regard to the functionality that makes use of cryptographically secured blockchain technology. We focus on wallet contracts deployed on Ethereum, as it is the most prominent platform for tokens and smart contracts with readily available data. We aim at a better understanding of this frequently deployed group of smart contracts by analyzing characteristics of wallet contracts and grouping them into six types. To this end, we present approaches to identify wallet contracts by analyzing source code, bytecode, and execution traces extracted from transaction data. Moreover, we investigate usage scenarios and patterns. From the derived data, we extract blueprints for wallets and compile a ground truth. We provide numbers and temporal perspectives regarding the creation and use of wallets.
Impacts of Shale Gas Wastewater Disposal on Water Quality in Western Pennsylvania (2013)

The safe disposal of liquid wastes associated with oil and gas production in the United States is a major challenge given their large volumes and typically high levels of contaminants. In Pennsylvania, oil and gas wastewater is sometimes treated at brine treatment facilities and discharged to local streams. This study examined the water quality and isotopic compositions of discharged effluents, surface waters, and stream sediments associated with a treatment facility site in western Pennsylvania. The elevated levels of chloride and bromide, combined with the strontium, radium, oxygen, and hydrogen isotopic compositions of the effluents reflect the composition of Marcellus Shale produced waters. The discharge of the effluent from the treatment facility increased downstream concentrations of chloride and bromide above background levels. Barium and radium were substantially (>90%) reduced in the treated effluents compared to concentrations in Marcellus Shale produced waters. Nonetheless, (226)Ra levels in stream sediments (544-8759 Bq/kg) at the point of discharge were ~200 times greater than upstream and background sediments (22-44 Bq/kg) and above radioactive waste disposal threshold regulations, posing potential environmental risks of radium bioaccumulation in localized areas of shale gas wastewater disposal.
Technical Guide for Nervous System Sampling of the Cynomolgus Monkey for General Toxicity Studies (2012)

For general toxicity studies, a technique was designed to consistently sample the most important neuroanatomic regions of the brain, spinal cord, and peripheral nerve of cynomolgus monkeys using a limited number of blocks and slides. Using the most rostral portion of the pons as a landmark, the entire fixed brain was cut dorsoventrally into cross-sectional slabs 4 mm in thickness. For microscopic evaluation, six blocks of the brain at the levels of the frontal pole, anterior commissure, rostral thalamus, caudal thalamus, middle cerebellum with brainstem, and occipital lobe were trimmed to fit in standard tissue cassettes. Cross- and oblique sections of the spinal cord including the dorsal root ganglion and dorsal and ventral nerve roots were obtained at the levels of C1-C4, T10-T12, and L1-L4. Cross- and longitudinal sections of the sciatic nerve were also obtained. This technique offers a consistent and reliable method to routinely sample most of the important regions of the central and peripheral nervous system of monkeys using ten blocks. This method is readily adaptable to other species of nonhuman primates, dogs, and minipigs and can be quickly learned by the technicians performing the trimming procedures.
Urea Glycoside Synthesis in Water (2004)

A novel approach to the synthesis of urea glycosides in aqueous media has been developed. Reaction of Steyermark’s ­glucosyl carbamate 1 with amines was carried out in water to afford urea glucosides in good yields. This method was successfully ­applied to develop a new route to the synthesis of urea-tethered neoglycoconjugates and pseudooligosaccharides.
Named Entity Sequence Classification (2017)

Named Entity Recognition (NER) aims at locating and classifying named entities in text. In some use cases of NER, including cases where detected named entities are used in creating content recommendations, it is crucial to have a reliable confidence level for the detected named entities. In this work we study the problem of finding confidence levels for detected named entities. We refer to this problem as Named Entity Sequence Classification (NESC). We frame NESC as a binary classification problem and we use NER as well as recurrent neural networks to find the probability of candidate named entity is a real named entity. We apply this approach to Tweet texts and we show how we could find named entities with high confidence levels from Tweets.
Treatment failure of pharyngeal gonorrhoea with internationally recommended first-line ceftriaxone verified in Slovenia, September 2011 (2012)

We describe the second case in Europe of verified treatment failure of pharyngeal gonorrhoea, caused by an internationally occurring multidrug-resistant gonococcal clone, with recommended first-line ceftriaxone 250 mg in Slovenia. This is of grave concern since ceftriaxone is last remaining option for empirical treatment. Increased awareness of ceftriaxone failures, more frequent test-of-cure, strict adherence to regularly updated treatment guidelines, and thorough verification/falsification of suspected treatment failures are essential globally. New effective treatment options are imperative.
Sustainability Calculator: A Tool to Assess Sustainability in Cosmetic Products (2020)

Assessing sustainability is extremely necessary and appears as an industrial need and requirement in order to facilitate decision making and to evaluate the impacts of existing strategies, products and technologies. Thus, the main goal of this research was to develop a sustainability calculator based on the opinion of experts that work in the different branches of the cosmetic industry, in order to cover the entire life cycle of a cosmetic product. A detailed survey in which all the steps of a cosmetic product life cycle were addressed, was designed and applied to cosmetic professionals. The data obtained with the survey was statistically analysed for the positive and negative impacts of each parameter on sustainability. The analysed data allowed the creation of a Microsoft Excel tool that mirrors the experts’ opinion. A proof of concept was also designed in order to prove the usefulness of the tool. The results show that there are no raw materials and/or packaging materials and practices, that can be considered 100% sustainable. However, with the appropriate strategies, it is possible to drastically decrease the impacts of any type of cosmetic product on sustainability. This is a promising tool that includes the three dimensions of sustainability in a simple, fast, objective and interactive way for the user. Its application will facilitate the work of the formulators and reduce the time of analysis and decision.
Inorganic Synthesis for the Stabilization of Nanoparticles:  Application to Cu/Al<sub>2</sub>O<sub>3</sub> Nanocomposite Materials (2007)

A series of copper/aluminum nanocomposites with different mixing homogeneities and different texture features were prepared via various inorganic synthesis methods including coprecipitation, gelation, and stepwise thermal modification. Nitrogen sorption measurements and X-ray diffraction were used for textural and structural analysis, respectively. Solid−solid reaction analysis and differential scanning calorimetry (DSC) analysis were developed for the determination of the mixing homogeneities of copper-based nanocomposite materials. A sintering experiment at 250−600 °C for 350 h under methanol-steam reforming conditions was carried out to compare the stability of supported Cu0 nanoparticles. Although a large initial size of supported nanoparticles is not favorable, those supported nanoparticles with a small initial size cannot ensure good thermal stability. The mixing homogeneities of CuO/Al2O3 mixed metal oxide (MMO) nanocomposites significantly affected the thermal stability of their reduced Cu0 crystallites. Besides homogeneity control, creation of narrow distributions of pore sizes with small major pore diameters (e.g., around 3.5 nm) can also be used for the stabilization of supported Cu0 nanoparticles. We found that mixing homogeneity of a nanocomposite is likely the major factor in the stabilization of nanoparticles, whereas a narrow distribution of pore sizes might confine the growth of nanoparticles, possibly via space limitations. Field-emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), and convergent beam electron diffraction (CBED) were used for the observation or structure determination of the copper/aluminum nanocomposites. This paper also provides information on the deactivation of copper catalysts via thermal sintering under methanol-steam reforming conditions.
High-power, efficient, low-noise, continuous-wave all-solid-state Ti:sapphire laser (1996)

A cw 1.4-W TEM(00) single-frequency output, to our knowledge the highest ever reported, was obtained in a Ti:sapphire ring laser pumped by a diode-pumped, intracavity-doubled Nd:YAG laser, which provides 6.3 W of cw maximum TEM(00) green output. The electrical-optical conversion efficiency of the all-solid-state Ti:sapphire laser is 1.1%. A range of wavelength tuning of 150 nm with a narrow linewidth of <5 MHz is successfully demonstrated. The Ti:sapphire laser shows excellent low-noise characteristics, <-130 dB/Hz.
Tagging, Folksonomy & Co - Renaissance of Manual Indexing? (2007)

This paper gives an overview of current trends in manual indexing on the Web. Along with a general rise of user generated content there are more and more tagging systems that allow users to annotate digital resources with tags (keywords) and share their annotations with other users. Tagging is frequently seen in contrast to traditional knowledge organization systems or as something completely new. This paper shows that tagging should better be seen as a popular form of manual indexing on the Web. Difference between controlled and free indexing blurs with sufficient feedback mechanisms. A revised typology of tagging systems is presented that includes different user roles and knowledge organization systems with hierarchical relationships and vocabulary control. A detailed bibliography of current research in collaborative tagging is included.
Intermediate cubic-panorama synthesis based on triangular re-projection (2010)

Image-based rendering (IBR) techniques provide a powerful tool for implementing free navigation in image-based virtual environments. Panoramas can produce an immersive and omnidirectional display of the virtual environment. This paper addresses the synthesis of virtual intermediate cubic panoramas given several reference panoramas. A 2D/3D complex triangular meshing representation of the scene is used to render the desired view, which involves solving a variety of visibility issues due to occlusion and disocclusion. The generalized disparity-based homography transformation can project these 2D/3D triangles onto the desired view in the sense of perspective accuracy. In addition, special measures are taken to handle the difficulties caused by the edge discontinuity of cubic panoramas. The experimental results show that we can obtain photo-realistic virtual images with high fidelity, indicating this is an effective approach for virtual cubic-panorama synthesis.
In vivo porcine model of reperfused myocardial infarction: In situ double staining to measure precise infarct area/area at risk (2007)

This model and methodology could provide a reproducible and consistent infarct size. The current study demonstrated that 60-min mid LAD occlusion can be the most feasible to serve as a porcine reperfused myocardial infarction model.
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore (2016)

In this study, with Singapore as an example, we demonstrate how we can use mobile phone call detail record (CDR) data, which contains millions of anonymous users, to extract individual mobility networks comparable to the activity-based approach. Such an approach is widely used in the transportation planning practice to develop urban micro simulations of individual daily activities and travel; yet it depends highly on detailed travel survey data to capture individual activity-based behavior. We provide an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes. With growing ubiquitous mobile sensing, and shrinking labor and fiscal resources in the public sector globally, the method presented in this research can be used as a low-cost alternative for transportation and planning agencies to understand the human activity patterns in cities, and provide targeted plans for future sustainable development.
Synthesis of highly dispersed metal sulfide catalysts via low temperature sulfidation in dielectric barrier discharge plasma (2014)

Highly dispersed metal sulfide catalysts were synthesized by low temperature sulfidation in a non-thermal plasma directly from the metal salts.
Are milk polyamines preventive agents against food allergy? (2000)

Insufficient polyamine intake could play a role in the induction of sensitization to dietary allergens. This proposal is based essentially on investigations made in sucking rats and in children. In sucking rats it has been established that oral administration of spermine can induce all the modifications occurring in the digestive tract at weaning. In the intestine events occur in two phases. The early event consists of desquamation of the epithelium resulting from an activation of apoptosis. The late event appears to involve an hormonal cascade in which adrenocorticotropic hormone, cytokines, bombesin and corticosterone are included. Observations in human subjects show that: (1) the spermine and spermidine concentrations are generally lower in infant formulas than in human breast milk. Mothers seem consistently to have relatively high or relatively low concentrations of spermine and spermidine in their milk. These individual variations may be due to diet, lifestyle or genetic background; (2) the probability of developing allergy can reach 80 % if the mean spermine concentration in the milk is lower than 2 nmol/ml milk. It is approximately 0 % if the mean spermine concentration is higher than 13 nmol/ml milk; (3) preliminary results show that the intestinal permeability to macromolecules differs in premature babies when they are fed on breast milk compared with infant formulas (J Senterre, J Rigo, G Forget, G Dandrifosse and N Romain, unpublished results). This difference does not seem to be present when powdered milk is supplemented with polyamines at the concentration found in breast milk; (4) spermine increases proliferation and differentiation of lymphocytes isolated from the tonsils of children.
Multiple imputation for threshold‐crossing data with interval censoring (1993)

Medical statistics often involve measurements of the time when a variable crosses a threshold value. The time to threshold crossing may be the outcome variable in a survival analysis, or a time-dependent covariate in the analysis of a subsequent event. This paper presents new methods for analysing threshold-crossing data that are interval censored in that the time of threshold crossing is known only within a specified interval. Such data typically arise in event-history studies when the threshold is crossed at some time between data-collection points, such as visits to a clinic. We propose methods based on multiple imputation of the threshold-crossing time with use of models that take into account values recorded at the times of visits. We apply the methods to two real data sets, one involving hip replacements and the other on the prostate specific antigen (PSA) assay for prostate cancer. In addition, we compare our methods with the common practice of imputing the threshold-crossing time as the right endpoint of the interval. The two examples require different imputation models, but both lead to simple analyses of the multiply imputed data that automatically take into account variability due to imputation.
Text/Conference Paper (2019)

Integrating Internet of Things (IoT) devices into an existing network is a nightmare. Minimalistic, unfriendly user interfaces, if any; badly chosen security methods, most notably the defaults; lack of long term security; and bugs or misconfigurations are plentiful. As a result, an increasing number of owners operate unsecure devices. Our investigations into the root causes of the problems resulted in the development of Home Certificate Authority (HomeCA). HomeCAincludes a comprehensive set of secure, vendor-independent interoperable practices based on existing protocols and open standards. HomeCA avoids most of the current pitfalls in network integration by design. Long-term protocol security, permission management, and secure usage combined with simplified device integration and secure key updates on ownership acquisition pave the way toward scalable, federated IoT security.
Built-In Self-Test for Multi-Port RAMs. (1991)

In this paper we present a new approach to the test of multi-port RAMS. A new fault model that takes into account complex couplings resulting from simultaneous access of memory cells is used in order to ensure a very high fault coverage. A new algorithm for the test of dual-port memories is here detailed. This algorithm achieves qn) complexity thanks to the use of some topological restrictions. We also present a new BlST scheme, based on programmable schematic generators, that allows great flexibility for ASIC design. I - INTRODUCTION Multi-port RAMS are widely used as embedded memories in telecommunication ASlCs and also in multi-processor systems. These special RAM chips are provided by IC vendors as well as multi-port RAM generators that are already available in some ASIC vendors libraries. The testing of these memories is getting more important since they are often embedded in VLSl and ULSl circuits (RAT 901. Efficient algorithms for the test of multi-port RAMS can thus be used in two ways : ASIC libraries providing test algorithms and ASIC libraries providing BIST circuit generators as an option for the multi-port RAM generator. Multi-port RAMS differ from single port RAMS by the possibility of accessing more than one cell at a time. Various authors have studied the fault modeling of single port RAMS as well as test algorithms for the detection of such faults. Coupling faults are a widely used model for the testing of single port RAMS (SUK 811 (THA 781. Recent work on multi-port RAM testing use the same coupling fault models (RAP 88) (NAD 90) or Induction Fault Analysis extracted faults (SAS 901 (which do not take couplings into account). In (CASSl), we have shown that the above fault model is not sufficient in order to test multi-port RAMS. Thus, we have introduced the complex coupling faults. In section II we briefly review the concept of complex coupling. In this paper, we detail an algorithm based on a topdogical approach that results in an O(n) complexity test algorithm with a very high fault coverage. Conceming the implementation of the algorithm and in order to be compatible with the high flexibility provided by ASIC libraries RAM generators, we have developed a totally parameterizable BlST circuit. The development is done using GDP tools and the THOMSON Composants Militaires et Spatiaux (TMS) CSAM ASIC compiled function library.