gebhart/patrepeval huggingface dataset:
Spatiotemporal Partitioning of Transportation Network Using Travel Time Data (2017)

Today, the deployment of sensing technology permits the collection of massive amounts of spatiotemporal data in urban areas. These data can provide comprehensive traffic state conditions for an urban network and for a particular day. However, data are often too numerous and too detailed to be of direct use, particularly for applications such as delivery tour planning, trip advisors, and dynamic route guidance. A rough estimate of travel times and their variability may be sufficient if the information is available at the full city scale. The concept of the spatiotemporal speed cluster map is a promising avenue for these applications. However, the data preparation for creating these maps is challenging and rarely discussed. In this study, that challenge is addressed by introducing generic methodologies for mapping the data to a geographic information system network, coarsening the network to reduce the network complexity at the city scale, and estimating the speed from the travel time data, including missing data. This methodology is demonstrated on the large-scale urban network of Amsterdam, Netherlands, with real travel time data. The preprocessed data are used to build the spatiotemporal speed cluster by using three partitioning techniques: normalized cut, density-based spatial clustering of applications with noise, and growing neural gas (GNG). A new posttreatment methodology is introduced for density-based spatial clustering and GNG, which are based on data point clustering, to generate connected zones. A preliminary cross comparison of the clustering techniques shows that GNG performs best in generating zones with minimum internal variance, the normalized cut computes three-dimensional zones with the best intercluster dissimilarity, and GNG has the fastest computation time.
Stabilization of three-wave vortex beams in the waveguide (2015)

We consider two-dimensional (2D) localized vortical modes in the three-wave system with the quadratic ($\chi ^{(2)}$) nonlinearity, alias nondegenerate second-harmonic-generating system, guided by the isotropic harmonic-oscillator (HO) (alias parabolic) confining potential. In addition to the straightforward realization in optics, the system models mixed atomic-molecular Bose-Einstein condensates (BECs). The main issue is stability of the vortex modes, which is investigated through computation of instability growth rates for eigenmodes of small perturbations, and by means of direct simulations. The threshold of parametric instability for single-color beams, represented solely by the second harmonic (SH) with zero vorticity, is found in an analytical form with the help of the variational approximation (VA). Trapped states with vorticities $\left( +1,-1,0\right) $ in the two fundamental-frequency (FF) components and the SH one [the so-called \textit{hidden-vorticity} (HV) modes] are completely unstable. Also unstable are \textit{semi-vortices} (SVs), with component vorticities $% \left( 1,0,1\right) $. However, full vortices, with charges $\left( 1,1,2\right) $, have a well-defined stability region. Unstable full vortices feature regions of robust dynamical behavior, where they periodically split and recombine, keeping their vortical content.
Mapping of the dominant Me genes cluster conferring resistance to root-knot nematodes in pepper (Capsicum annuum L.) (2007)

International audience
Increased parietal amyloid burden and metabolic dysfunction in Alzheimer's disease with early onset (2012)

90 Objectives To examine the relationships between age-at-onset with both in vivo fibrillary amyloid deposition and glucose metabolism. Methods Dynamic [11C]Pittsburgh compound-B (PIB) (90 minutes) and static [18F]fluorodeoxyglucose (FDG) scans were obtained in 100 AD patients. Parametric non-displaceable binding potential (BPND) images of [11C]PIB and standardized uptake value ratio (SUVr) images of [18F]FDG were generated using cerebellar grey matter as reference tissue. Nine [11C]PIB-negative patients were excluded. The remaining AD patients were categorized into younger (n=45, mean age at diagnosis: 56±4) and older (n=46, mean age at diagnosis: 69±5) groups, based on the median age (62 years) at time of diagnosis. Results Although groups did not differ on Mini-Mental State Examination, younger patients showed more severe impairment on visuo-spatial function, attention and executive function composite scores (p Conclusions These findings suggest that clinical differences between younger and older AD patients are related not only to topographical differentiation in downstream processes, but may originate from distinctive distributions of early upstream events. As such, increased amyloid burden, together with metabolic dysfunction, in the parietal lobe of younger AD patients may explain the distinct cognitive profile in these patients
Advanced Data Collection for Inventory Management (1987)

Bar-coding, radio-frequency, and voice-operated systems selected. Report discusses study of state-of-the-art in automated collection of data for management of large inventories. Study included comprehensive search of literature on data collection and inventory management, visits to existing automated inventory systems, and tours of selected supply and transportation facilities at Kennedy Space Center. Information collected analyzed in view of needs of conceptual inventory-management systems for Kennedy Space Center and for manned space station and other future space projects.
PLGA-based microparticles for the sustained release of BMP-2 (2011)

The development of growth factor delivery strategies to circumvent the burst release phenomenon prevalent in most current systems has driven research towards encapsulating molecules in resorbable polymer matrices. For these polymer release techniques to be efficacious in a clinical setting, several key points need to be addressed. This present study has investigated the encapsulation of the growth factor, BMP-2 within PLGA/PLGA-PEG-PLGA microparticles. Morphology, size distribution, encapsulation efficiency and release kinetics were investigated and we have demonstrated a sustained release of bioactive BMP-2. Furthermore, biocompatibility of the PLGA microparticles was established and released BMP-2 was shown to promote the differentiation of MC3T3-E1 cells towards the osteogenic lineage to a greater extent than osteogenic supplements (as early as day 10 in culture), as determined using alkaline phosphatase and alizarin red assays. This study showcases a potential BMP-2 delivery system which may now be translated into more complex delivery systems, such as 3D, mechanically robust scaffolds for bone tissue regeneration applications.
The Profitability of Energy Storage in European Electricity Markets (2020)

In this work, we study the profitability of energy storage operated in the Nordic,German, and UK electricity day-ahead markets during 2006-2016. During this time period, variable renewable energy sources (vRES) have been rapidly penetrating the markets and increasing the volatility of the residual load, which is often assumed to be associated with improving financial viability of energy storages. However, storage operator profits are not publicly available, in particular not at plant level. We therefore develop a linear optimisation model which maximises profits from arbitraging hourly prices and use the model output of profits and storage operating hours in further econometric analyses. This is a novel approach merging two strands of literature (optimisation and econometrics) in a single energy storage study. Specifically, we quantify and disentangle the effects of electricity demand, solar and wind generation, the spread between gas and coal prices, carbon emission prices and tructural breaks on profits and operation of 1-13MWh/MW energy storages. Among others we find that solar generation is associated with lower profits but higher operating frequency of energy storages in Germany. Wind power generation is associated with positive effects on profits in the UK and Germany. vRES does not affect profits or operation of new Nordic energy storages.
Dynamic software updating (2001)

Many important applications must run continuously and without interruption, yet must be changed to fix bugs or upgrade functionality. No prior general-purpose methodology for dynamic updating achieves a practical balance between flexibility, robustness, low overhead, and ease of use. We present a new approach for C-like languages that provides type-safe dynamic updating of native code in an extremely flexible manner (code, data, and types may be updated, at programmer-determined times) and permits the use of automated tools to aid the programmer in the updating process. Our system is based on dynamic patches that both contain the updated code and the code needed to transition from the old version to the new. A novel aspect of our patches is that they consist of verifiable native code ( e.g. Proof-Carrying Code [17] or Typed Assembly Language [16]), which is native code accompanied by annotations that allow on-line verification of the code's safety. We discuss how patches are generated mostly automatically, how they are applied using dynamic-linking technology, and how code is compiled to make it updateable. To concretely illustrate our system, we have implemented a dynamically-updateable web server, FlashEd. We discuss our experience building and maintaining FlashEd. Performance experiments show that for FlashEd, the overhead due to updating is typically less than 1%.
Implications of neurovascular uncoupling in functional magnetic resonance imaging (fMRI) of brain tumors (2017)

Functional magnetic resonance imaging (fMRI) serves as a critical tool for presurgical mapping of eloquent cortex and changes in neurological function in patients diagnosed with brain tumors. However, the blood-oxygen-level-dependent (BOLD) contrast mechanism underlying fMRI assumes that neurovascular coupling remains intact during brain tumor progression, and that measured changes in cerebral blood flow (CBF) are correlated with neuronal function. Recent preclinical and clinical studies have demonstrated that even low-grade brain tumors can exhibit neurovascular uncoupling (NVU), which can confound interpretation of fMRI data. Therefore, to avoid neurosurgical complications, it is crucial to understand the biophysical basis of NVU and its impact on fMRI. Here we review the physiology of the neurovascular unit, how it is remodeled, and functionally altered by brain cancer cells. We first discuss the latest findings about the components of the neurovascular unit. Next, we synthesize results from preclinical and clinical studies to illustrate how brain tumor induced NVU affects fMRI data interpretation. We examine advances in functional imaging methods that permit the clinical evaluation of brain tumors with NVU. Finally, we discuss how the suppression of anomalous tumor blood vessel formation with antiangiogenic therapies can “normalize” the brain tumor vasculature, and potentially restore neurovascular coupling.
Update on Fusidic Acid (CEM-102) Tested against Neisseria gonorrhoeae and Chlamydia trachomatis (2010)

VoR
Cooling of a levitated nanoparticle to the motional quantum ground state (2020)

Quantum control of complex objects in the regime of large size and mass provides opportunities for sensing applications and tests of fundamental physics. The realization of such extreme quantum states of matter remains a major challenge. We demonstrate a quantum interface that combines optical trapping of solids with cavity-mediated light-matter interaction. Precise control over the frequency and position of the trap laser with respect to the optical cavity allowed us to laser-cool an optically trapped nanoparticle into its quantum ground state of motion from room temperature. The particle comprises 10<sup>8</sup> atoms, similar to current Bose-Einstein condensates, with the density of a solid object. Our cooling technique, in combination with optical trap manipulation, may enable otherwise unachievable superposition states involving large masses.
Typology of Plankton Communities seen by In Situ Imaging, from the Epi to the Mesopelagic Layers of the Global Ocean. (2020)

International audience
Dpb11 may function with RPA and DNA to initiate DNA replication (2017)

Dpb11 is required for the initiation of DNA replication in budding yeast. We found that Dpb11 binds tightly to single-stranded DNA (ssDNA) or branched DNA structures, while its human homolog, TopBP1, binds tightly to branched-DNA structures. We also found that Dpb11 binds stably to CDK-phosphorylated RPA, the eukaryotic ssDNA binding protein, in the presence of branched DNA. A Dpb11 mutant specifically defective for DNA binding did not exhibit tight binding to RPA in the presence of DNA, suggesting that Dpb11-interaction with DNA may promote the recruitment of RPA to melted DNA. We then characterized a mutant of Dpb11 that is specifically defective in DNA binding in budding yeast cells. Expression of dpb11-m1,2,3,5,ΔC results in a substantial decrease in RPA recruitment to origins, suggesting that Dpb11 interaction with DNA may be required for RPA recruitment to origins. Expression of dpb11-m1,2,3,5,ΔC also results in diminished GINS interaction with Mcm2-7 during S phase, while Cdc45 interaction with Mcm2-7 is like wild-type. The reduced GINS interaction with Mcm2-7 may be an indirect consequence of diminished origin melting. We propose that the tight interaction between Dpb11, CDK-phosphorylated RPA, and branched-DNA may be required for the essential function of stabilizing melted origin DNA in vivo. We also propose an alternative model, wherein Dpb11-DNA interaction is required for some other function in DNA replication initiation, such as helicase activation.
GRIP1 in GABAergic synapses (2005)

The glutamate receptor-interacting protein GRIP1 is present in glutamatergic synapses and interacts with the GluR2/3/4c subunits of the AMPA receptors. This interaction plays important roles in trafficking, synaptic targeting, and recycling of AMPA receptors as well as in the plasticity of glutamatergic synapses. Although GRIP1 has been shown to be present at GABAergic synapses in cultured neurons, the use of EM (electron microscopy) immunocytochemistry in the intact brain has failed to convincingly reveal the presence of GRIP1 in GABAergic synapses. Therefore, most studies on GRIP1 have focused on glutamatergic synapses. By using mild tissue fixation and embedding in EM, we show that in the intact brain the 7-PDZ domain GRIP1a/b is present not only in glutamatergic synapses but also in GABAergic synapses. In GABAergic synapses GRIP1a/b localizes both at the presynaptic terminals and postsynaptically, being frequently localized on the synaptic membranes or the synaptic junctional complex. Considerably higher density of GRIP1a/b is found in the presynaptic GABAergic terminals than in the glutamatergic terminals, while the density of GRIP1a/b in the postsynaptic complex is similar in both types of synapses. The results also show that the 7-PDZ and the shorter 4-PDZ domain splice forms of GRIP1 (GRIP1c 4-7) frequently colocalize with each other in individual GABAergic and glutamatergic synapses. The results suggest that GRIP1 splice forms might play important roles in brain GABAergic synapses.
Underground utility sensing network using LoRa and magnetic telemetry (Conference Presentation) (2018)

Many cities seek utilities monitoring with centrally managed Internet of Things (IoT) systems. This requires the development of many reliable low-cost wireless sensors, such as water temperature and flow meters, that can transmit information from subterranean pipes to surface-mounted receivers. Traditional radio communication systems are either unable to penetrate through multiple feet of earthen and manmade material, or have impractically large energy requirements which necessitate either frequent replacement of batteries, or a complex (and expensive) built-in energy harvesting system. Magnetic signaling systems do not suffer from this drawback: low-frequency electromagnetic waves are shown to penetrate well through several feet of earth and water. In the past, these signals were too weak for practical use; however, this has changed with the recent proliferation of high-sensitivity magnetometers and compact antennas using mechanically actuated rare-earth magnets. A permanent magnet can be either rotated or vibrated to create an oscillating magnetic field. Utilizing this phenomenon, two flow meter designs are proposed: one which uses a propeller to directly rotate a diametrically magnetized neodymium magnet; and, another which uses an oscillating tail to move a permanent magnet back-and-forth across a novel soft-magnet Y-stator, which projects a switching magnetic field. These oscillating magnetic fields are used to send water flow rate information to an above ground LoRa-capable Arduino receiver equipped with a magnetometer. Simulation software is used to model the oscillating electromagnetic fields. Complete system performance with remote datalogging is tested, with the aim of integrating many sensors and surface receivers into a single LoRa wireless IoT network.
Etude de la barriere pour un probleme de fuite optimale dans le plan (1989)

Nous etudions un probeme de commande optimale dans le plan qui modelise la poursuite d'un fugitif F par un poursuivant P qui entend le fugitif. Le bruit emis par le fugitif est une fonction croissante de sa vitesse, et le bruit entendu par le poursuivant depend du bruit emis par le fugitif et de la distance qui les separe. On s'interesse au cas simple ou le poursuivant se deplace en ligne droite et a vitesse constante. L'utilisation pour ce probleme des resultats classiques de la theorie de la commande optimale permet de definir et de calculer une "barriere" ; plusieurs proprietes qualitatives de cette barriere sont egalement demontrees. Par ailleurs, nous regroupons en annexe quelques remarques concernant des questions de commandabilite et viabilite (non lineaires) souleves par l'etude de ce probleme de fuite.
Statistical Downscaling in Climate with State-of-the-Art Scalable Machine Learning (2017)

The adaptation of infrastructure to events including hydrological and weather extremes, which may be exacerbated by climate change, largely depends on high-resolution climate projections decades and centuries into the future. The downscaling of a wide range of general circulation models (GCMs) is imperative to understanding climate change at a local scale. In parallel of developing frameworks allowing for credible validation, the statistics and machine learning communities are working on specific methods for covariate selection and prediction on various climate applications. State-of-the-art machine learning methods that are pushing the boundaries in fields such as computer vision, natural language processing, and speech recognition should be carefully considered for incorporation into statistical downscaling (SD). More specifically, the deep learning models being developed, focusing on dimensionality reduction and spatiotemporal data, have potential to improve over the current generation of SD models. Utilizing multitask learning (MTL) to take advantage of spatially dependent observations may allow for more generalizable models.
OPTICAL PHONONS IN I-III-VI2 COMPOUNDS (1975)

The optical phonons at k = 0 of CuInS2, AgInS2 and CuFeS2 were analysed by infrared reflection and absorption measurements in the region from 1 000 to 50 cm-1. To determine the transverse and longitudinal optical phonon frequencies Kramers-Kronig integrations as well as classical oscillator models were used. The results are compared with the known phonon spectra of CuAlS2, CuGaS2 and AgGaS2. It is shown by a systematic comparison of the mode frequencies that the force constants of the different I-III-S2 compounds are almost equal. The frequency difference between corresponding modes appear to be mainly due to the different cation masses.
Predicting geotechnical parameters from electric resistivity using artificial neural network (2021)

Geotechnical methods to gather information about soil parameters used in the design of infrastructure provide information at a specific point of the ground. Use of limited point data may result in greater uncertainty and less reliability in design. Electrical resistivity a non-invasive surface geophysical method which is less time consuming and provides continuous spatial information about the soil. The limitation of the electrical resistivity method is that information is not in terms of engineering parameters, but is represented in terms electrical resistivity. Correlation between geotechnical parameters and electric resistivity is needed in order to facilitate the use of electrical resistivity information into geotechnical designs. Artificial neural network (ANN) is a powerful tool to develop correlations and predict parameters. In this study, data from the literature are used to develop several ANN models to predict geotechnical parameters such as saturation, cation exchange capacity, water content, and dry density for compacted and undisturbed clay soil. Performance of the ANN models are evaluated based on the mean absolute relative error (MARE), coefficient of determination (R2) and the average squared error (ASE). Multilinear regression analysis is also performed to determine the correlation between parameters. Effectiveness of ANN models for predicting different parameters is compared to the results obtained from multilinear regression analysis.
Determination of Niacin in Infant Formula and Wheat Flour by Anion-Exchange Liquid Chromatography with Solid-Phase Extraction Cleanup (1999)

Niacin content must be included on food labels of infant formula products and bakery products containing enriched flour. Liquid chromatographic (LC) determination of niacin in complex food matrixes is complicated by the presence of endogenous compounds that absorb at the commonly used wave-length of 260 nm. Also, the presence of particulate matter in the standard sulfuric acid extraction procedure results in reduced life of LC columns and precolumns. A simple, rapid, solid-phase extraction (SPE) procedure for separation and cleanup of niacin from a complex food matrix digest has been developed. By using a vacuum manifold with the SPE column system, multiple samples can be processed quickly and efficiently for LC analysis, compared with gravimetric column cleanup. Sulfuric acid sample digest is passed over an aromatic sulfonic acid cation-exchange (ArSCX-SPE) or a sulfonated Florisil SPE column. Niacin is eluted with 0.25M sodium acetate-acetic acid, pH 5.6 buffer in vacuo. LC chromatograms of the resulting eluate are free of interference from other components absorbing at 260 nm at the retention time of niacin. Validation of the method was obtained from agreement of analytical results on available reference materials. For both SPE methods, values for niacin in SRM 1846 Infant Formula (milk-based powder) were within uncertainty ranges of the certified value. Use of several calibration procedures (the LC computer program, a peak area response graphic standard curve, or the method of standard additions) with both SPE procedures resulted in niacin values for 3 RM-Wheat Flours (not certified for niacin) in agreement (90-105%) with their respective values reported in the literature. Several commercial wheat flours showed a broad 260 nm interference, resulting in high niacin values. Niacin recoveries from spiked soy-based liquid infant formulas ranged from 95-107% with the ArSCX-SPE column. Calibration curves of niacin were linear up to 400 micrograms/mL, with a detection limit of 0.2 microgram/mL.