gebhart/patrepeval huggingface dataset:
Short-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation (2017)

Accurate load forecasting is an important issue for the reliable and efficient operation of a power system. This study presents a hybrid algorithm that combines similar days (SD) selection, empirical mode decomposition (EMD), and long short-term memory (LSTM) neural networks to construct a prediction model (i.e., SD-EMD-LSTM) for short-term load forecasting. The extreme gradient boosting-based weighted k-means algorithm is used to evaluate the similarity between the forecasting and historical days. The EMD method is employed to decompose the SD load to several intrinsic mode functions (IMFs) and residual. Separated LSTM neural networks were also employed to forecast each IMF and residual. Lastly, the forecasting values from each LSTM model were reconstructed. Numerical testing demonstrates that the SD-EMD-LSTM method can accurately forecast the electric load.
L'influence de la grosseur des graines du Pin noir sur la germination et le développement des semis pendant la première année de végétation (1960)

International audience
In vivo optical coherence tomography in ophthalmology (1993)

If the more or less conventional interferometric techniques are applied in vivo, movements of the subject might falsify the measurement. This led us to develop the dual beam interferometry technique which compensates for these movements. First in vivo tomographic images of the human eye are presented. The implications of the application of partial coherence techniques in dispersive media are discussed. Synthesizing tomograms from interfero- metrically obtained scans is rather time-consuming and therefore difficult to apply in vivo. Hence we discuss the application of spectral interferometry to optical coherence tomography. The spectral interferometry technique does not need moving components.
Using schematically heterogeneous structures (1998)

Schematic heterogeneity arises when information that is represented as data under one schema, is represented within the schema (as metadata) in another. Schematic heterogeneity is an important class of heterogeneity that arises frequently in integrating legacy data in federated or data warehousing applications. Traditional query languages and view mechanisms are insufficient for reconciling and translating data between schematically heterogeneous schemas. Higher order query languages, that permit quantification over schema labels, have been proposed to permit querying and restructuring of data between schematically disparate schemas. We extend this work by considering how these languages can be used in practice. Specifically, we consider a restricted class of higher order views and show the power of these views in integrating legacy structures. Our results provide insights into the properties of restructuring transformations required to resolve schematic discrepancies. In addition, we show how the use of these views permits schema browsing and new forms of data independence that are important for global information systems. Furthermore, these views provide a framework for integrating semi-structured and unstructured queries, such as keyword searches, into a structured querying environment. We show how these views can be used with minimal extensions to existing query engines. We give conditions under which a higher order view is usable for answering a query and provide query translation algorithms.
Mechanisms of Protein Seeding in Neurodegenerative Diseases (2012)

Most age-associated neurodegenerative diseases involve the aggregation of specific proteins within the nervous system. In Alzheimer disease, the insidious pathogenic process begins many years before the symptoms emerge, and the lesions that characterize the disease—senile plaques and neurofibrillary tangles—ramify systematically through the brain. We review evidence that the -amyloid and tau proteins, which aggregate to form senile plaques and neurofibrillary tangles, respectively, are induced to misfold and self-assemble by a process of templated conformational change that amplifies a toxic species. Recent data also indicate that the spread of these lesions from one site to another is mediated by the cellular uptake, transport, and release of endogenous seeds formed by the cognate proteins. This simple pathogenic principle suggests that the formation, trafficking, and metabolism of pathogenic protein seeds are promising therapeutic targets for Alzheimer disease and other neurodegenerative disorders.
Mutations in the Dof Zinc Finger Genes <i>DAG2</i> and <i>DAG1</i> Influence with Opposite Effects the Germination of Arabidopsis Seeds (2002)

We describe the Arabidopsis gene DAG2 encoding a Dof zinc finger protein and show that it is involved in the control of seed germination. An Arabidopsis mutant line with a T-DNA insertion in DAG2 isolated by reverse genetics produces seeds that are substantially more dependent than the wild type on the physical stimuli-light and cold treatment-that promote germination. Mutant dag2 seeds also are less sensitive to the germination-promotive effect of gibberellins, because a 10-fold higher amount of gibberellins is needed to restore germination when endogenous gibberellin biosynthesis is blocked. The seed germination characteristics of the dag2 mutant are opposite to those of dag1, a knockout mutant of another Dof gene (DAG1) that we showed previously to be involved in the control of seed germination, and are similar to those of plants that overexpress DAG1. The promoter of the DAG2 gene is active specifically in the vascular system of the mother plant but not in the embryo, and segregation analysis indicates that the effect of the dag2 mutation is maternal. Both characteristics are in common with DAG1; additionally, the DAG1 and DAG2 proteins share high sequence homology and an identical zinc finger domain. These data suggest, and the germination phenotype of the double mutant is compatible with, a model whereby the zinc finger proteins DAG1 and DAG2 act on a maternal switch that controls seed germination, possibly by regulating the same gene(s).
Human CD3-epsilon gene contains three miniexons and is transcribed from a non-TATA promoter. (1988)

The antigen receptor of the T lymphocyte consists of two variable T-cell receptor chains (either TCR-alpha, TCR-beta or TCR-gamma, TCR-delta) noncovalently linked to four different invariant membrane proteins (CD3-gamma, CD3-delta, CD3-epsilon, and the CD3-zeta homodimer). The CD3 genes are expressed early in thymocyte development, preceding the rearrangement and expression of the T-cell receptor genes. Here we report the isolation and structural analysis of the human CD3-epsilon gene. The gene consisted of nine exons. Three exons, encoding the junction of leader peptide and mature protein, were extremely small (21, 15, and 18 base pairs, respectively). The murine gene contained only two such miniexons, the sequences of which were not homologous to those of the three human miniexons. But from comparisons of intron sequences the regions surrounding the human miniexons III and IV appeared to be closely related to those surrounding the murine miniexons III and IV. The most-3' miniexon in the human gene (IVa) had no murine counterpart and appeared not to duplicate any of the other miniexons. Sequence analysis of CD3-epsilon cDNA clones isolated from four independent libraries gave no evidence for alternative use of these miniexons. Like CD3-delta, the CD3-epsilon gene was transcribed from a weak, nontissue-specific, TATA-less promoter. Pulsed-field electrophoresis showed that the human CD3-epsilon gene was separated from the CD3-gamma, CD3-delta gene pair by at least 30 kilobases, but by no more than 300 kilobases.
Fair decentralized data-rate congestion control for V2V communications (2017)

Channel congestion is one of the most critical issues in IEEE 802.11p-based vehicular ad hoc networks because congestion may lead to unreliability of applications. As a counter measure, the European Telecommunications Standard Institute (ETSI), proposes a mandatory Decentralized Congestion Control (DCC) framework to control the channel load. DCC algorithms are proposed to tune parameters such as message-rate, data-rate, etc. to avoid congestion. An important requirement for DCC algorithms is fairness, which ensures that vehicles experiencing similar channel loads are entitled to similar transmission parameters, in particular, message-rate and data-rate. Message-rate DCC (LIMERIC) ensures a fair message-rate selection, while data-rate DCC (DR-DCC) might end up with different data-rates, creating unfairness among the vehicles: vehicles with lower data-rate have a larger communication range than those using higher data-rates. Therefore some vehicles are less visible than others, which is detrimental to the reliability of the safety applications. To avoid this, the paper defines a novel packet-count based decentralized data-rate congestion control algorithm (PDR-DCC), which enforces fairness and hence improves the application-reliability. Simulation studies are performed to demonstrate that PDR-DCC avoids congestion in a fair manner. We also show the effect of fairness on the application-reliability by comparing the performance of PDR-DCC with message-rate (LIMERIC) and data-rate (DR-DCC) congestion control algorithms for a stationary vehicle warning application in a synthetic highway scenario and for various vehicular densities. We conclude that PDR-DCC outperforms LIMERIC, and DR-DCC in terms of application-reliability.
Probing differential Ag+–nucleobase interactions with isothermal titration calorimetry (ITC): Towards patterned DNA metallization (2009)

DNA has been successfully used as a scaffold for the fabrication of metallic nanowires, primarily based on the electrostatic complexation and reduction of the metal cations on the negatively charged sugar-phosphate backbone. Here, we probe the differential binding affinities of nucleobases for silver ions using sensitive isothermal titration calorimetry (ITC) measurements of the reaction enthalpies, which go in order: C > G > A > or = T. Using the disparity between the interaction of cytosine (strong binding) and thymine (weak binding) with silver ions, we have successfully generated silver nanoparticle doublets and triplets on custom-made oligonucleotides, C(30)-T(40)-C(30) and C(20)-T(20)-C(20)-T(20)-C(20), respectively. Thus, a new and simple method of generating metallized DNA wires is presented, based entirely on the nucleotide sequence of DNA. The concept could be extended to other cations and complex DNA sequences in order to achieve intricately patterned DNA constructs.
Real-time UML-based performance engineering to aid manager's decisions in multi-project planning (2002)

We investigate the usage of software performance engineering to aid the project manager in making sound, reliable predictions in software development, and in optimizing the utilization of resources (typically the people). We assimilate the project teams to the processing elements of a performance model, and their activities to the tasks to be accomplished within established time intervals. The proposed methodology uses as the manager's interface a subset of Real-Time UML, the recently adopted OMG standard specialized profile for addressing schedulability, performance and timeliness. To illustrate the approach, we model the case of a manager that must decide a release date for a product undergoing the testing phase. We show how, by means of basic performance analyses, different workflow assumptions can be explored and their consequent outcomes automatically derived: by looking at the analysis results, the manager can thus take an informed, more responsible decision.
Social context influences recognition of bodily expressions (2010)

Previous studies have shown that recognition of facial expressions is influenced by the affective information provided by the surrounding scene. The goal of this study was to investigate whether similar effects could be obtained for bodily expressions. Images of emotional body postures were briefly presented as part of social scenes showing either neutral or emotional group actions. In Experiment 1, fearful and happy bodies were presented in fearful, happy, neutral and scrambled contexts. In Experiment 2, we compared happy with angry body expressions. In Experiment 3 and 4, we blurred the facial expressions of all people in the scene. This way, we were able to ascribe possible scene effects to the presence of body expressions visible in the scene and we were able to measure the contribution of facial expressions to the body expression recognition. In all experiments, we observed an effect of social scene context. Bodily expressions were better recognized when the actions in the scenes expressed an emotion congruent with the bodily expression of the target figure. The specific influence of facial expressions in the scene was dependent on the emotional expression but did not necessarily increase the congruency effect. Taken together, the results show that the social context influences our recognition of a person's bodily expression.
Hepatic Angiomyolipoma: A Rare Case Report and Review of the Literature (2006)

Angiomyolipoma (AML) is a rare benign tumor that occurs in the liver and other organs. Hepatic AMLs may be difficult to differentiate from other liver neoplasms by noninvasive imaging. Hepatocellular carcinoma was the most common preoperative diagnosis. Radiological findings of AML may only be suggestive of the lesion; its definitive diagnosis requires histological confirmation. Here we report a case of hepatic AML, accidentally discovered in a young woman, which was diagnosed by the pathohistological results after surgical removal of the tumor.
Time Series Data Cleaning with Regular and Irregular Time Intervals (2020)

Errors are prevalent in time series data, especially in the industrial field. Data with errors could not be stored in the database, which results in the loss of data assets. Handling the dirty data in time series is non-trivial, when given irregular time intervals. At present, to deal with these time series containing errors, besides keeping original erroneous data, discarding erroneous data and manually checking erroneous data, we can also use the cleaning algorithm widely used in the database to automatically clean the time series data. This survey provides a classification of time series data cleaning techniques and comprehensively reviews the state-of-the-art methods of each type. In particular, we have a special focus on the irregular time intervals. Besides we summarize data cleaning tools, systems and evaluation criteria from research and industry. Finally, we highlight possible directions time series data cleaning.
Rapid broth macrodilution method for determination of MICs for Mycobacterium avium isolates (1993)

A multicenter study was done to investigate the accuracy and reproducibility of a method for determining the MICs of antimicrobial agents against the Mycobacterium avium complex in 7H12 broth with the BACTEC system. In phase I, with eight drugs and 10 strains, intralaboratory reproducibility was 95.7 to 100%, allowing a 1-dilution difference upon repeat testing. The results of phase II testing with 41 additional strains were consistent with those obtained in phase I, with good interlaboratory reproducibility. The radiometric method was validated by sampling and plating of the same broth cultures and determining, by the number of CFU per milliliter, the lowest drug concentration that inhibited more than 99% of the initial bacterial population. Three test concentrations of each drug and the tentative interpretation of results are proposed. Radiometric MIC determination has the potential to become the method of choice for clinical microbiology laboratories and evaluation of new agents for the treatment of M. avium infections, both pulmonary and disseminated.
Identification of lentivirus tat functional domains through generation of equine infectious anemia virus/human immunodeficiency virus type 1 tat gene chimeras (1991)

The structural regions that comprise the functional domains of lentivirus Tat proteins were examined. Chimeric tat genes and chimeric viral promoters were constructed between the distantly related human immunodeficiency virus type 1 (HIV-1) and equine infectious anemia virus (EIAV). These exchange experiments revealed that the EIAV Tat-responsive element recognition domain is formed by two distinct structural regions. Activation domains of both HIV-1 and EIAV Tat contain a conserved core element, but at least HIV-1 Tat requires the presence of additional structural regions. The interchangeable nature of Tat activation domains suggests that these domains act through a common or ubiquitous cellular transcription factor.
Intrusion Detection Based on Rule Extraction from Dynamic Cell Structure Neural Networks (2010)

Knowledge embedded within artificial neural networks (ANNs) is distributed over the connections and weights of neurons. So, the user considers ANN as a black box system. There are many researches investigating the area of rule extraction by ANNs. In this paper, a dynamic cell structure (DCS) neural network and a modified version of LERX algorithm are used for rule extraction. On the other hand, intrusion detection system (IDS) is known as a critical technology to secure computer networks. So, the proposed algorithm is used to develop IDS and classify the patterns of intrusion. To compare the performance of the proposed system with other machine learning algorithms, multi-layer perceptron (MLP) with output weight optimization-hidden weight optimization (OWO-HWO) training algorithm is employed with selected inputs based on the results of a feature relevance analysis. Empirical results show the superior performance of the IDS based on rule extraction from DCS, in recognizing hard-detectable attack categories, e.g. userto-root (U2R) and also offering competitive false alarm rate (FAR). Although, MLP with 25 selected input features, instead of 41 standard features introduced by knowledge discovery and data mining group (KDD), performs better in terms of detection rate (DR) and cost per example (CPE) when compared with some other machine learning methods, as well.
Dissolution Inhibitory Effect of Urea Additives on a Carboxyl Polymer Through a Supramolecular Structure. (1998)

The effect of the addition of carbonyl compounds such as amide, imide, urea, and ester derivatives on the dissolution rate of carboxyl-group-containing polymers in an alkaline solution was investigated. Urea derivatives lowered the dissolution rate of the polymer film more than the other carbonyl compounds did, and 1,3-diphenylurea inhibited the dissolution of the polymer film much more efficiently than other urea derivatives. Structural studies of the dissolution inhibition led to the proposal of a supramolecular structure, in which the urea functionality hydrogen bonded to two carboxyl groups of the polymer to form a hydrophilic domain surrounded by the hydrophobic substituents of the urea derivatives. The existence of this supramolecular structure is supported by the infrared spectra of the urea additives in the polymer films.
Isolation and Screening of Enzymatic Hydrolysis of Starch by Enzyme Amylase from Soil Isolate Aspergillus Niger (2015)

Amylase has become the most promising enzyme in the industrial field due to its economical values and high catalytic rate. This class of enzyme constitutes approximately 25â€“30% of the enzyme stock around the world. It is commercially used for various purposes such as: hydrolysis of starch, resizing of textile fabrics, in pharmaceutical industries, in food industries, in paper industry, in detergent industry etc. Î±-Amylase can be produced by multitudunial sources i.e.plants, animals and microorganism but fungal amylase has become a new field of interest for the researchers.20 different soil samples were collected for the isolation of Aspergillus.niger. Selected strains from soil samples are subcultured on SDA agar and screened their ability for producing Î±- amylase by starch hydrolysis on a starch agar, clear sharp zones are observed from all the collected samples showing a clear hydrolysis of starch around the colonies. These fungal species are further processed for solid state fermentation in which wheat bran is used as a substrate from agro industrial wastes, resulted in high amount of production of enzyme amylase. Amylases hydrolyze complex molecules of starch into small oligosaccharides in step wise pattern. The determination of reducing sugar is done by Dinitrosalicylic acid method and observed by spectrophotometry at 575nm. A confirmatory starch-iodine test is also done, a drop of iodine is added in the tubes containing starch which turns the color blue but by adding raw enzyme that have been collected from the supernatant disappears the blue color which evident the production of enzyme Î±-amylase.
A Model of Sound Localisation Applied to the Evaluation of Systems for Stereophony (2008)

In this paper, a model of human sound localisation is described, and its prediction is compared to the results of listening tests. The model takes binaural signals as the input, processing them in a series of signal processing modules, which simulate the peripheral, binaural and the central stages of spatial hearing. In particular, the central processor of the model considers the excitation-inhibition (EI) cell activity patterns as the internal representation of available cues, and the source location estimates are obtained by using a simple pattern-matching procedure. In the listening tests, stereophonic images were presented to the listener's front, where the stimulus was either broadband or 1/3 octave band noise at 7 centre frequencies from 0.5 kHz to 6 kHz. The subjective responses compared well to the model prediction across frequency except for some cases where the image location was overestimated. Also, the prediction for the localisation of broadband phantom images agreed well with the test results, where the model prediction was integrated across frequency according to a tentatively suggested weighting function. Although the neuroscientific background is weak for the model, the good agreement with the subjective responses suggests that the model is worth investigating further.