gebhart/patrepeval huggingface dataset:
Imagerie et spectroscopie Terahertz: applications aux problématiques de défense et de sécurité (2015)

National audience
Design of New Imaging Agents Using Positron-Emitting Radionuclides as the Reporter (2008)

There are a number of imaging techniques that can be used for external detection of either anatomical or physiological changes in animals and humans. The anatomical techniques are important for determining the size, shape, and position of abnormalities with high resolution and the measurement of the longest dimension of the tumor by X-ray is the gold standard for tumor regression (RECIST). Positron emission tomography (PET) was developed using the short-lived radionuclides of oxygen, nitrogen, carbon, and fluorine. Their advantage in radiolabeling small molecules was readily recognized because these radionuclides represent the smallest perturbation of the chemical structure, whereas single-photon computed tomography (SPECT) radiotracers, magnetic resonance imaging (MRI) contrast agents, and fluorescent reporter probes create larger perturbations, in general. PET has been to measure blood volume (BV) using -labeled red blood cells, blood flow (BF) using -labeled water, and permeability (P) of tumors in oncology.
Thermal conductivity enhancement of nanofluids containing graphene nanosheets (2011)

This paper envisages a mechanism of heat conduction behind the thermal conductivity enhancement observed in graphene nanofluids. Graphene nanofluids have been prepared, characterized, and their thermal conductivity was measured using the transient hot wire method. The enhancements in thermal conductivity are substantial even at lower concentrations and are not predicted by the classical Maxwell model. The enhancement also shows strong temperature dependence which is unlike its carbon predecessors, carbon nanotube (CNT) and graphene oxide nanofluids. It is also seen that the magnitude of enhancement is in-between CNT and metallic/metal oxide nanofluids. This could be an indication that the mechanism of heat conduction is a combination of percolation in CNT and Brownian motion and micro convection effects in metallic/metal oxide nanofluids, leading to a strong proposition of a hybrid model.
Einsatz von Membrantrennverfahren in der chemischen Industrie (1998)

Abstract Membran Processes in the Chemical Industry In the chemical industry (less so in the pharmaceutical industry), membrane technology is still at an early stage of acceptance. However, in this field too, it is gaining increasing importance as an innovative, reliable and, first and foremost, cost‐effective alternative to conventional processes. This trend is evidenced by a variety of new plants which have been installed in recent years, and also by the rapidly growing interest in this technology shown by production and design departments. This article gives an overview of the industrial importance of membrane processes in chemical and pharmaceutical production and also presents some typical examples of applications in this field by describing plants which have already been installed and are now in production.
K[sub s]K[sub s] system at 800 GeV/c (1998)

Results are presented from a partial wave analysis of a sample of centrally produced mesons in the reaction pp→pslow(KsKs)pfast, with 800 GeV/c protons incident on a liquid hydrogen target. The meson system is found to be predominantly S-wave in the mass range between KsKs threshold and 1.58 GeV/c2. The f0(1500) is clearly observed in this region. Above 1.58 GeV/c2 two solutions are possible, one with mainly S-wave and another with mainly D-wave. This ambiguity prevents a unique determination of the spin of the fJ(1710) meson.
Prediction of Partially Observed Dynamical Processes Over Networks via Dictionary Learning (2014)

Prediction of dynamical processes evolving over network graphs is a basic task encountered in various areas of science and engineering. The prediction challenge is exacerbated when only partial network observations are available, that is when only measurements from a subset of nodes are available. To tackle this challenge, the present work introduces a joint topology- and data-driven approach for network-wide prediction able to handle partially observed network data. First, the known network structure and historical data are leveraged to design a dictionary for representing the network process. The novel approach draws from semi-supervised learning to enable learning the dictionary with only partial network observations. Once the dictionary is learned, network-wide prediction becomes possible via a regularized least-squares estimate which exploits the parsimony encapsulated in the design of the dictionary. Second, an online network-wide prediction algorithm is developed to jointly extrapolate the process over the network and update the dictionary accordingly. This algorithm is able to handle large training datasets at a fixed computational cost. More important, the online algorithm takes into account the temporal correlation of the underlying process, and thereby improves prediction accuracy. The performance of the novel algorithms is illustrated for prediction of real Internet traffic. There, the proposed approaches are shown to outperform competitive alternatives.
On Learning the $c\mu$ Rule: Single and Multiserver Settings (2018)

We consider learning-based variants of the $c \mu$ rule -- a classic and well-studied scheduling policy -- in single and multi-server settings for multi-class queueing systems. In the single server setting, the $c \mu$ rule is known to minimize the expected holding-cost (weighted queue-lengths summed both over classes and time). We focus on the setting where the service rates $\mu$ are unknown, and are interested in the holding-cost regret -- the difference in the expected holding-costs between that induced by a learning-based rule (that learns $\mu$) and that from the $c \mu$ rule (which has knowledge of the service rates) over any fixed time horizon. We first show that empirically learning the service rates and then scheduling using these learned values results in a regret of holding-cost that does not depend on the time horizon. The key insight that allows such a constant regret bound is that a work-conserving scheduling policy in this setting allows explore-free learning, where no penalty is incurred for exploring and learning server rates. 
We next consider the multi-server setting. We show that in general, the $c \mu$ rule is not stabilizing (i.e. there are stabilizable arrival and service rate parameters for which the multi-server $c \mu$ rule results in unstable queues). We then characterize sufficient conditions for stability (and also concentrations on busy periods). Using these results, we show that learning-based variants of the $c\mu$ rule again result in a constant regret (i.e. does not depend on the time horizon). This result hinges on (i) the busy period concentrations of the multi-server $c \mu$ rule, and that (ii) our learning-based rule is designed to dynamically explore server rates, but in such a manner that it eventually satisfies an explore-free condition.
(Invited) Scalable GaN-on-Silicon Using Rare Earth Oxide Buffer Layers (2013)

Growth of GaN epilayers on silicon (111) is achieved by using a rare earth oxide buffer layer technology. The use of the REO material system allows strain engineering of the silicon wafers prior to GaN growth in order to mitigate stresses formed during the growth and subsequent cooling process. Alloying of oxides with more than one rare earth element allows compositional and lattice parameter control of the REO material and thereby imparting different strains into the silicon wafer. The wafer bow of the REO/Si heterostructures is also a found to be dependent on the thickness of the oxide layers grown. Growth of GaN on REO/Si templates result in lower bow compared to growth on silicon wafers alone.
Clutter locus equation for more general linear array orientation. (2016)

Abstract not provided.
Chemically Functionalized Reduced Graphene Oxide as Additives in Polyethylene Composites for Space Applications (2019)

The discovery of radiation‐shielding materials remains a critical technology to enable long‐term space travel and extraterrestrial colonization. Hydrocarbon polymers, such as high‐density polyethylene (HDPE), are among the best radiation attenuators due to their rich H content and lightweight. Due to their simple chemical structure that lacks larger heteroatoms, HDPE is also resistant to numerous radiation‐induced degradation pathways that often limit the applicability of more sophisticated polymers. One drawback of hydrocarbon polymers is their inferior mechanical properties, such as tensile strength and impact toughness, relative to metals and other high‐performance polymer systems. In this report, we develop an alkylated reduced graphene oxide that is used as an additive to enhance the storage and tensile moduli of HDPE by 10–15% across the lunar temperature range. These additives outperform unmodified reduced graphene oxide by 30% due to better dispersion through the polymer matrix as observed by cross‐sectional scanning electron microscopy. POLYM. ENG. SCI., 60:86–94, 2020. © 2019 Society of Plastics Engineers
Toughening of poly(L‐lactide) by melt blending with rubbers (2009)

Abstract Poly( L ‐lactide) (PLA) was melt‐blended with four rubber components—ethylene–propylene copolymer, ethylene–acrylic rubber, acrylonitrile–butadiene rubber (NBR), and isoprene rubber (IR)—in an effort to toughen PLA. All the blend samples exhibited distinct phase separation. Amorphous PLA constituted a topologically continuous matrix in which the rubber particles were dispersed. According to Izod impact testing, toughening was achieved only when PLA was blended with NBR, which showed the smallest particle size in its blend samples. In agreement with the morphological analysis, the value of the interfacial tension between the PLA phase and the NBR phase was the lowest, and this suggested that rubber with a high polarity was more suitable for toughening PLA. Under the tensile stress conditions for NBR and IR blend samples, these rubbers displayed no crosslinking and showed a high ability to induce plastic deformation before the break as well as high elongation properties; this suggested that the intrinsic mobility of the rubber was important for the dissipation of the breaking energy. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
Graph Convolutional Networks with EigenPooling (2019)

Graph neural networks, which generalize deep neural network models to graph structured data, have attracted increasing attention in recent years. They usually learn node representations by transforming, propagating and aggregating node features and have been proven to improve the performance of many graph related tasks such as node classification and link prediction. To apply graph neural networks for the graph classification task, approaches to generate thegraph representation from node representations are demanded. A common way is to globally combine the node representations. However, rich structural information is overlooked. Thus a hierarchical pooling procedure is desired to preserve the graph structure during the graph representation learning. There are some recent works on hierarchically learning graph representation analogous to the pooling step in conventional convolutional neural (CNN) networks. However, the local structural information is still largely neglected during the pooling process. In this paper, we introduce a pooling operator $\pooling$ based on graph Fourier transform, which can utilize the node features and local structures during the pooling process. We then design pooling layers based on the pooling operator, which are further combined with traditional GCN convolutional layers to form a graph neural network framework $\m$ for graph classification. Theoretical analysis is provided to understand $\pooling$ from both local and global perspectives. Experimental results of the graph classification task on $6$ commonly used benchmarks demonstrate the effectiveness of the proposed framework.
Use of Proteomic and Hematology Biomarkers for Prediction of Hematopoietic Acute Radiation Syndrome Severity in Baboon Radiation Models (2018)

Use of plasma proteomic and hematological biomarkers represents a promising approach to provide useful diagnostic information for assessment of the severity of hematopoietic acute radiation syndrome. Eighteen baboons were evaluated in a radiation model that underwent total-body and partial-body irradiations at doses of Co gamma rays from 2.5 to 15 Gy at dose rates of 6.25 cGy min and 32 cGy min. Hematopoietic acute radiation syndrome severity levels determined by an analysis of blood count changes measured up to 60 d after irradiation were used to gauge overall hematopoietic acute radiation syndrome severity classifications. A panel of protein biomarkers was measured on plasma samples collected at 0 to 28 d after exposure using electrochemiluminescence-detection technology. The database was split into two distinct groups (i.e., "calibration," n = 11; "validation," n = 7). The calibration database was used in an initial stepwise regression multivariate model-fitting approach followed by down selection of biomarkers for identification of subpanels of hematopoietic acute radiation syndrome-responsive biomarkers for three time windows (i.e., 0-2 d, 2-7 d, 7-28 d). Model 1 (0-2 d) includes log C-reactive protein (p < 0.0001), log interleukin-13 (p < 0.0054), and procalcitonin (p < 0.0316) biomarkers; model 2 (2-7 d) includes log CD27 (p < 0.0001), log FMS-related tyrosine kinase 3 ligand (p < 0.0001), log serum amyloid A (p < 0.0007), and log interleukin-6 (p < 0.0002); and model 3 (7-28 d) includes log CD27 (p < 0.0012), log serum amyloid A (p < 0.0002), log erythropoietin (p < 0.0001), and log CD177 (p < 0.0001). The predicted risk of radiation injury categorization values, representing the hematopoietic acute radiation syndrome severity outcome for the three models, produced least squares multiple regression fit confidences of R = 0.73, 0.82, and 0.75, respectively. The resultant algorithms support the proof of concept that plasma proteomic biomarkers can supplement clinical signs and symptoms to assess hematopoietic acute radiation syndrome risk severity.
Advanced metallization scheme for 3×50µm via middle TSV and beyond (2015)

An advanced Via-Middle TSV metallization scheme is presented, featuring a high conformal ALD oxide liner, a thermal ALD WN barrier, an electroless NiB platable seed and a high throughput copper ECD filling process. Because of the high conformality of the WN barrier and NiB seed, these layers can be deposited very thinly, reducing the cost significantly, while still guaranteeing continuous barrier/seed layers all along the TSV sidewall till the bottom of the TSV. This metallization scheme has been successfully processed on 3 m diameter and 50 m deep Via-Middle TSVs, showing void-free copper fill in FIB cross-sections. Good adhesion between liner, barrier and seed was maintained during the processing, including the post plate anneal which is present to reduce the copper pumping. The polishing of the NiB seed and WN barrier has been optimized in order to limit the recess of these layers at the top of the TSV. Electrical results are shown, proving the maturity of this new TSV middle process scheme. Low leakage current in both accumulation and depletion mode is measured. The flat band voltage is low as well, indicating little ionic contamination in the liner oxide. The intrinsic integrity of the liner and the ability of the barrier to prevent Cu diffusion from TSV to silicon has been verified, using the established controlled I-V method. High field acceleration factors are extracted, ensuring good reliability of this advanced and scalable 3×50 TSV middle module.
Impact of Isradipine on Contractile Performance, Metabolism, and Coronary Resistance Studied in Isolated Rat Hearts (1994)

Summary: In anesthetized dogs, isradipine has been reported to induce peripheral vasodilation and increase cardiac output (CO) and myocardial contractility, whereas myocardial oxygen consumption (MVO2) decreases, suggesting that isradipine may increase overall metabolic efficiency of the ventricle of intact animals. Whether isradipine has any direct myocardial effects that could cause intrinsic increase in metabolic efficiency or whether the observation relates to favorable isradipine-induced changes in hemodynamic loading conditions is not known. Therefore, we determined the direct myocardial effects of isradipine on contractile strength and metabolic efficiency in isolated rat heart. Isolated crystalloid perfused rat hearts were instrumented for measurement of ventricular pressure, volume, and MVO2. Isradipine decreased developed pressure (DP) and MVO2 in a concentration-dependent manner; at 32 nM irradipine, both quantities were ˜70% of their control values. Isradipine caused a downward shift of the end-systolic pressurevolume relation (ESPVR) and in the relation between ventricular work (indexed by pressure-volume area, PVA) and MVO2, indicating that for any given amount of total mechanical work performed, the rat heart consumed less O2 during administration of isradipine than under control conditions. However, the magnitude of the downward shift of this relation was nearly identical to that observed in a separate group of hearts in which we decreased contractility by decreasing the perfusate calcium concentration. Thus, isradipine does not appear to have a contractility-independent effect on myocardial efficiency.
Composition control of high Ga Cu(In, Ga)(S, Se)2 using RTP reaction (2020)

CIGS absorbers are developed using Se-capped precursor films with increased Ga composition. Films are reacted using a rapid thermal process, which uses reaction times on the order of minutes. It is observed that Ga profiles can be controlled by adjusting the Se availability in the reaction. Additionally, it is shown that CIGS grain size increases with Ga content; however, morphology variability may be increased. Two different processes for introducing S to the reaction are investigated.
User Body Effect on Phased Array in User Equipment for the 5G mmWave Communication System (2016)

The millimeter-wave phased array in the user equipment (UE) for 5G communication is studied in this letter. In particular, the body effect on the phased array in the UE at 15 GHz is investigated with the 3-D measurement data, and its impact on some key parameters for phased array in the UE, such as the total scan pattern, the coverage efficiency, and the probability of detection, are analyzed.
Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels (2011)

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We then present new "void filling" methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed form equations for the symbol error probability with and without void-filling are also developed.
The Effect of Isoelectronic In-Doping on the Structural and Optical Properties of (Al)GaN Grown by Metalorganic Vapor Phase Epitaxy (2000)

We have studied the effect of isoelectronic In-doping on the structural and optical properties of GaN and Al 0.05 Ga 0.95 N. The films were grown by atmospheric metalorganic vapor phase epitaxy at 950°C in H 2 or N 2 carrier gas (hereafter referred to as H 2 -(Al)GaN and N 2 -(Al)GaN, respectively) with a low-temperature deposited AlN buffer layer. With the technique, we were able to control the strain in the films. Indeed, with increasing trimethylindium flow, the strain in GaN decreased, and accordingly, the tilting and twisting components of the crystalline mosaicity were also decreased. The photoluminescence (PL) emission peak energy shifted in accordance with the strain in GaN. Strong enhancement of the excitonic PL intensity of In-doped GaN and AlGaN was observed. In all the samples, room temperature PL mapping for linewidth and peak wavelength showed that with the addition of In, the uniformity of the PL improved significantly.
Tables S7-S8 from Genomic Evolutionary Patterns of Leiomyosarcoma and Liposarcoma (2023)

&lt;p&gt;Supplementary Tables 7 and 8&lt;/p&gt;
Self-made phage libraries with heterologous inserts in the Mtd of Bordetella bronchiseptica (2012)

Phage display libraries are widely used as tools for identifying, dissecting and optimizing ligands. Development of a simple method to access greater library diversities could expedite and expand the technique. This paper reports progress toward harnessing the naturally occurring diversity generating retroelement used by Bordetella bronchiseptica bacteriophage to alter its tail-fiber protein. Mutagenesis and testing identified four sites amenable to the insertion of <19-residue heterologous peptides within the variable region. Such sites allow auto-generation of peptide libraries surrounded by a scaffold with additional variations. The resultant self-made phage libraries were used successfully for selections targeting anti-FLAG antibody, immobilized metal affinity chromatography microtiter plates and HIV-1 gp41. The reported experiments demonstrate the utility of the major tropism determinant protein of B.bronchiseptica as a natural scaffold for diverse, phage-constructed libraries with heterologous self-made phage libraries.
Filter-Bank-Based Narrowband Interference Detection and Suppression in Spread Spectrum Systems (2004)

A filter-bank-based narrowband interference detection and suppression method is developed and its performance is studied in a spread spectrum system. The use of an efficient, complex, critically decimated perfect reconstruction filter bank with a highly selective subband filter prototype, in combination with a newly developed excision algorithm, offers a solution with efficient implementation and performance close to the theoretical limit derived as a function of the filter bank stopband attenuation. Also methods to cope with the transient effects in case of frequency hopping interference are developed and the resulting performance shows only minor degradation in comparison to the stationary case.