gebhart/patrepeval huggingface dataset:
Clustering Scatter Plots Using Data Depth Measures (2013)

Clustering is rapidly becoming a powerful data mining technique, and has been broadly applied to many domains such as bioinformatics and text mining. However, the existing methods can only deal with a data matrix of scalars. In this paper, we introduce a hierarchical clustering procedure that can handle a data matrix of scatter plots. To more accurately reflect the nature of data, we introduce a dissimilarity statistic based on "data depth" to measure the discrepancy between two bivariate distributions without oversimplifying the nature of the underlying pattern. We then combine hypothesis testing with hierarchical clustering to simultaneously cluster the rows and columns of the data matrix of scatter plots. We also propose novel painting metrics and construct heat maps to allow visualization of the clusters. We demonstrate the utility and power of our new clustering method through simulation studies and application to a microbe-host-interaction study.
Quantum treatment of the Bose-Einstein condensation in nonequilibrium systems (2015)

We develop a fully quantum-mechanical approach, based on stochastic trajectories, for an incoherently pumped system of interacting bosons in contact with a thermal reservoir. It enables a complete characterization of coherence in such a multimode system. We apply our model to microcavity exciton polaritons interacting with acoustic phonons and observe the formation of a macroscopic occupation in the lowest-energy mode accompanied by the simultaneous establishment of temporal and spatial coherence. We describe the transition from thermal to coherent statistics together with the expected emergence of an off-diagonal long-range order.
Supplementary Figure 2 from Discovery and Characterization of Novel Mutant FLT3 Kinase Inhibitors (2023)

Supplementary Figure 2 from Discovery and Characterization of Novel Mutant FLT3 Kinase Inhibitors
Adaptive IIR filtering using cascade structures (2002)

This paper studies the use of cascade form filter structures for implementing adaptive IIR filters. An efficient scheme for the computation of the gradient is developed. This greatly simplifies the complexity of the adaptive algorithms for cascade implementation of adaptive IIR filters. Issues related to the convergence of the adaptive cascade filter, and computational complexity reduction via alternate mixed form implementations are explored. The application of the cascade IIR adaptive filter for enhancing narrowband/sinusoidal signals in noise is also considered. Simulation results are presented to support the observations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Novel Drug OMS103HP Reduces Pain and Improves Joint Motion and Function for 90 Days After Arthroscopic Meniscectomy (2011)

Level I, prospective, randomized, controlled trial.
Pomegranate Peel Extract Prevents Bone Loss in a Preclinical Model of Osteoporosis and Stimulates Osteoblastic Differentiation in Vitro (2015)

The nutritional benefits of pomegranate have attracted great scientific interest. The pomegranate, including the pomegranate peel, has been used worldwide for many years as a fruit with medicinal activity, mostly antioxidant properties. Among chronic diseases, osteoporosis, which is associated with bone remodelling impairment leading to progressive bone loss, could eventually benefit from antioxidant compounds because of the involvement of oxidative stress in the pathogenesis of osteopenia. In this study, with in vivo and ex vivo experiments, we investigated whether the consumption of pomegranate peel extract (PGPE) could limit the process of osteopenia. We demonstrated that in ovariectomized (OVX) C57BL/6J mice, PGPE consumption was able to significantly prevent the decrease in bone mineral density (-31.9%; p < 0.001 vs. OVX mice) and bone microarchitecture impairment. Moreover, the exposure of RAW264.7 cells to serum harvested from mice that had been given a PGPE-enriched diet elicited reduced osteoclast differentiation and bone resorption, as shown by the inhibition of the major osteoclast markers. In addition, PGPE appeared to substantially stimulate osteoblastic MC3T3-E1 alkaline phosphatase (ALP) activity at day 7, mineralization at day 21 and the transcription level of osteogenic markers. PGPE may be effective in preventing the bone loss associated with ovariectomy in mice, and offers a promising alternative for the nutritional management of this disease.
Polymer–Nanocrystal Nanocomposites: Device Concepts in Capacitors and Multiferroics (2019)

Nanotechnology offers a variety of pathways to novel and low cost device fabrication for a future that will undoubtedly contain literally billions of ubiquitous electronic devices. Nanocomposite metal-insulator-metal (MIM) capacitors are of interest due to the possibility of reducing the number of discrete components in printed circuit boards, and alternatively using embedded or directly printed capacitors for nanopackaging in conjunction with integrated circuits. Flexible substrates also become candidates when employing low processing temperatures. In addition to compatibility with nanomanufacturing, the prospect of designing a nanocomposite dielectric, by combining colloidal nanoparticle fillers and polymer hosts, lends itself very well to the idea of tunability of the mechanical and electrical properties. In exploring combinations of complex oxide materials and polymers, the field goes beyond simple capacitors, towards multiferroic devices in which the potential overlap of magnetic permeability with permittivity can produce enactable devices for magnetodielectrics and magnetoelectrics. Our work in solution processing of inorganic oxide dielectrics and multiferroics, using a modified sol-gel approach allows for the preparation of a variety of formulations that can be treated as inks for deposition as layers and/or for the design of novel nanocomposite films. Starting with high dielectric materials, we discuss nanocomposite capacitance based energy storage, and progress to materials development for multiferroic nanocomposites.
M$^3$Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging (2020)

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic. Considering the limited training cases and resources (e.g, time and budget), we propose a Multi-task Multi-slice Deep Learning System (M <sup>3</sup>Lung-Sys) for multi-class lung pneumonia screening from CT imaging, which only consists of two 2D CNN networks, i.e., slice- and patient-level classification networks. The former aims to seek the feature representations from abundant CT slices instead of limited CT volumes, and for the overall pneumonia screening, the latter one could recover the temporal information by feature refinement and aggregation between different slices. In addition to distinguish COVID-19 from Healthy, H1N1, and CAP cases, our M <sup>3</sup>Lung-Sys also be able to locate the areas of relevant lesions, without any pixel-level annotation. To further demonstrate the effectiveness of our model, we conduct extensive experiments on a chest CT imaging dataset with a total of 734 patients (251 healthy people, 245 COVID-19 patients, 105 H1N1 patients, and 133 CAP patients). The quantitative results with plenty of metrics indicate the superiority of our proposed model on both slice- and patient-level classification tasks. More importantly, the generated lesion location maps make our system interpretable and more valuable to clinicians.
Consolidation anti-CD22 fractionated radioimmunotherapy (RIT) with 90Y-epratuzumab tetraxetan following R-CHOP in elderly diffuse large B-cell lymphoma (DLBCL) patients (2011)

179 Objectives A French phase II trial sponsored by the LYSA group assessed fractionated 90Y-epratuzumab tetraxetan as consolidation after front-line R-CHOP in untreated elderly (age >60 yrs) patients (pts) with stage I/II bulky or III/IV DLBCL. Methods Treatment included 6 cycles of R-CHOP14 followed 8 wks later by 2 infusions of 90Y-epratuzumab tetraxetan (15 mCi/m2 [555 MBq/m2]), 7 days apart. Results 75 pts have been accrued prospectively and 61 (81.2%) received RIT. RIT toxicity consisted of grade 3-4 neutropenia in 46/61 pts (75.4%), anemia in 15 (24.6%), and thrombocytopenia in 47 (77.0%). Two pts developed myelodysplastic syndrome. Based on the 1999 International Workshop for Response Criteria, overall response rate (ORR) after 6 R-CHOP14 was 94.6% (71/75), with complete/unconfirmed complete responses (CR/CRu) in 52 pts (69.3%) and partial responses (PR) in 19 pts (25.3%). In an intention-to-treat analysis, CR/CRu rate after RIT was 72.0% (N=54), 7 pts (9.3%) remained in PR, and 8 (10.7%) progressed. At a median follow-up of 27.5 mos (1 to 46), the estimated 2-year progression-free-survival (PFS) was 75.4% (63.4-83.9%) and overall survival (OS) 83.8% (72.6-90.7%). For the 61 pts treated by RIT, ORR was 91.8% (56/61), with 81.9% (50/61) CR/CRu; 8/16 pts (50.0%) converting to CR/CRu after RIT; the estimated 2-year PFS was 79.9% (67.3-88.1%), and OS 90.8% (79.2-96.1%). Conclusions Fractionated 90Y-epratuzumab tetraxetan as consolidation after R-CHOP is tolerable in elderly untreated pts. PFS compares favorably to R-CHOP alone. Research Support French InCa institute, Immunomedics, AMGEN
A practical optimization method for designing large PV plants (2011)

Nowadays Photovoltaic (PV) plants have multi MW sizes, the biggest plants reaching tens of MW of capacity. Such large-scale PV plants are made up of several thousands of PV panels, each panel being in the range of 150-350W. This means that the design of a Large PV power plant is a big challenge and configuring such a plant should be implemented taking into consideration not only the cost of the installation, but also the Annual Energy Production, the Performance Ratio and the Levelized Cost Of Energy. In this paper, an algorithm is presented including the most important models of the PV system, that optimizes the structure of the plant based on predefined targets, such as the minimum Levelized Cost Of Energy.
Correction: Atomic layer deposition of Cu(i) oxide films using Cu(ii) bis(dimethylamino-2-propoxide) and water (2017)

Correction for 'Atomic layer deposition of Cu(i) oxide films using Cu(ii) bis(dimethylamino-2-propoxide) and water' by J. R. Avila, et al., Dalton Trans., 2017, DOI: .
Direct detection of circulating microRNA-122 using dynamic chemical labelling with single molecule detection overcomes stability and isomiR challenges for biomarker qualification (2019)

Abstract Circulating microRNAs are biomarkers reported to be stable and translational across species. miR-122 (miR-122-5p) is a hepatocyte-specific microRNA biomarker for drug-induced liver injury (DILI). Our objective was to develop an extraction-free and amplification-free detection method for measuring miR-122 that has translational utility in context of DILI. We developed a single molecule dynamic chemical labelling (DCL) assay based on miR-122 hybridization to an abasic peptide nucleic acid probe that contained a reactive amine instead of a nucleotide at a specific position in the sequence. The single molecule DCL assay specifically measured miR-122 directly from 10 µL of serum or plasma without any extraction steps, with a fit-for-purpose limit of detection of 1.32 pM. In 192 human serum samples, DCL accurately identified patients at risk of DILI (area under ROC curve 0.98 (95%CI 0.96-1), P&lt;0.0001). The miR-122 assay also quantified liver injury in rats and dogs. When DCL beads were added to serum, the miR-122 signal was stabilised (no loss of signal after 14 days at room temperature). By contrast, there was substantial degradation of miR-122 in the absence of beads (≈60% lost in 1 day). RNA sequencing demonstrated the presence of multiple miR-122 isomiRs with DILI that were at low concentration or not present in healthy patient serum. Sample degradation over time produced more isomiRs, particularly rapidly with DILI. PCR was inaccurate when analysing miR-122 isomiRs, whereas the DCL assay demonstrated accurate quantification. In summary, the DCL assay can accurately measure miR-122 directly from serum and plasma to diagnose liver injury in humans and other species, and can overcome important microRNA biomarker analytical and biological challenges.
N-best T5: Robust ASR Error Correction using Multiple Input Hypotheses and Constrained Decoding Space (2023)

Error correction models form an important part of Automatic Speech Recognition (ASR) post-processing to improve the readability and quality of transcriptions.Most prior works use the 1-best ASR hypothesis as input and therefore can only perform correction by leveraging the context within one sentence.In this work, we propose a novel N-best T5 model for this task, which is fine-tuned from a T5 model and utilizes ASR N-best lists as model input.By transferring knowledge from the pretrained language model and obtaining richer information from the ASR decoding space, the proposed approach outperforms a strong Conformer-Transducer baseline.Another issue with standard error correction is that the generation process is not well-guided.To address this a constrained decoding process, either based on the N-best list or an ASR lattice, is used which allows additional information to be propagated.
PCAT-1 , a Long Noncoding RNA, Regulates BRCA2 and Controls Homologous Recombination in Cancer (2014)

Impairment of double-stranded DNA break (DSB) repair is essential to many cancers. However, although mutations in DSB repair proteins are common in hereditary cancers, mechanisms of impaired DSB repair in sporadic cancers remain incompletely understood. Here, we describe the first role for a long noncoding RNA (lncRNA) in DSB repair in prostate cancer. We identify PCAT-1, a prostate cancer outlier lncRNA, which regulates cell response to genotoxic stress. PCAT-1 expression produces a functional deficiency in homologous recombination through its repression of the BRCA2 tumor suppressor, which, in turn, imparts a high sensitivity to small-molecule inhibitors of PARP1. These effects reflected a posttranscriptional repression of the BRCA2 3'UTR by PCAT-1. Our observations thus offer a novel mechanism of "BRCAness" in sporadic cancers.
Example-based image compression (2010)

The current standard image-compression approaches rely on fairly simple predictions, using either block- or wavelet-based methods. While many more sophisticated texture-modeling approaches have been proposed, most do not provide a significant improvement in compression rate over the current standards at a workable encoding complexity level. We re-examine this area, using example-based texture prediction. We find that we can provide consistent and significant improvements over JPEG, reducing the bit rate by more than 20% for many PSNR levels. These improvements require consideration of the differences between residual energy and prediction/residual compressibility when selecting a texture prediction, as well as careful control of the computational complexity in encoding.
The Effect of Calcium Co-Doping on Praseodymium Doped LSO (2009)

Cerium-doped lutetium oxyorthosilicate (LSO:Ce) is a well-known scintillator whose high density (7.4 g/cc), high light yield ( ~ 6 times that of BGO), and fast decay time ( ~ 43 ns) make it especially well suited for use in Positron Emission Tomography. Recent work suggests that divalent calcium co-doping eliminates many of the shallow electron traps, thus facilitating fast energy transfer to the Ce <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3+</sup> luminescence centers and shortening the scintillation decay time to ~ 30 ns. Here we report preliminary observations of the effect of Ca <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> co-doping on the crystal growth, photoluminescence, and scintillation properties of LSO:Pr. Single crystals with Pr concentrations ranging from 0.05% to 0.2% and Ca <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> concentrations up to 0.2% were grown via the Czochralski technique. Absorption, emission, and excitation spectra revealed the numerous 5d-4f and 4f-4f transitions characteristic of trivalent Pr. The main optical absorption due to Ca <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> occurs in the far UV, similar to previous observations of LSO:Ce, but with a more intense tail extending through the visible region. Consequently, 4f to 5d optical excitation ( ~ 260 nm) is greatly reduced in Ca co-doped samples, and the related 5d to 4f emission ( ~ 400 nm) is largely absent. Optical excitation ( ~ 450-500 nm) of the red ( ~ 610 nm) emission appears to be unaffected, for the most part, by the presence of Ca <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> . The scintillation decay of LSO:Pr is the sum of two exponential components with time constants of 7-8 and 26-29 ns, similar to previous reports. The addition of Ca <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> appears to relatively enhance the shorter component while reducing the longer one, although one or more additional slow components appear.
Supplementary Figure and Table Legends 1-5 from Acquired Resistance of Non–Small Cell Lung Cancer Cells to MET Kinase Inhibition Is Mediated by a Switch to Epidermal Growth Factor Receptor Dependency (2023)

Supplementary Figure and Table Legends 1-5 from Acquired Resistance of Non–Small Cell Lung Cancer Cells to MET Kinase Inhibition Is Mediated by a Switch to Epidermal Growth Factor Receptor Dependency
Machine Learning on High-Dimensional Data to Predict Bleeding Post Percutaneous Coronary Intervention (2020)

The AI-BR model accurately predicts bleeding post PCI and outperforms the ACC-BR model in predicting the risk of bleeding in patients undergoing PCI.
Dark-field X-ray imaging of unsaturated water transport in porous materials (2014)

We introduce in this Letter an approach to X-ray imaging of unsaturated water transport in porous materials based upon the intrinsic X-ray scattering produced by the material microstructural heterogeneity at a length scale below the imaging system spatial resolution. The basic principle for image contrast creation consists in a reduction of such scattering by permeation of the porosity by water. The implementation of the approach is based upon X-ray dark-field imaging via Talbot-Lau interferometry. The proof-of-concept is provided by performing laboratory-scale dark-field X-ray radiography of mortar samples during a water capillary uptake experiment. The results suggest that the proposed approach to visualizing unsaturated water transport in porous materials is complementary to neutron and magnetic resonance imaging and alternative to standard X-ray imaging, the latter requiring the use of contrast agents because based upon X-ray attenuation only.
Synthesis, Characterization, and Application of Cross-Linked Poly(ethylene glycol) Networks Used for the Gelation of Ionic Liquids (2005)

Cross-linking polymerization of functionalized poly(ethylene glycol) (PEG) monomers has been found to effectively gel hydrophobic ionic liquids (ILs). By coupling a tetra-arm PEG amine with a bifunctional succinimidyl PEG monomer, stable, free-standing gels can be formed. Gelation showed a strong IL anion dependence, whereas changing the IL cations gave little change. The gels showed a shrink-swell response to their solvent environment, while the IL entrained within the gels retains bulk properties of the neat IL. Applications include potential separations media and as IL-polymer electrolytes.
Designing Micro-SOFC Devices through the Sol-gel Process? (2012)

This presentation reports on a facile, cost effective and versatile method to fabricate nanostructured, mesoporous NiO-Gd-CeO2 (GDC) Gd-CeO2, La1-xSrxFe1-yCoyO3+delta and GDC/LSCF films. These films were synthesized through the "sol-gel method" combined with the dip-coating approach. Compared to spray-pyrolysis, APCVD or ALD methods, the proposed method avoids the use of expensive equipment and metal-organic precursors. In addition, we focussed on relatively low temperature processes that allow retaining a well-organized nanostructure within the material. Different techniques were used to characterize the films: FE-SEM, XRD, XPS, HR-TEM. Additionally, thermal or porosimetry Ellipsometry were also performed to define the heat treatment that allows synthesizing films with controlled porosity and particle size and to characterize the porous network, respectively. Using X-ray diffraction techniques coupled with a modelling approach, we have studied the formation of particle into these mesoporous films and we have shown that particle growth is governed by the surface curvature within the films. Based on these results, a discussion on the stability of the film has been proposed. Electrochemical characterization has been performed to characterize our films under various conditions of temperature and atmosphere (air and 5%H2/N2). For NiO/GDC mesoporous films, we have developed an "in-situ" technique based on impedance spectroscopy to understand the mechanism of reduction of NiO to Ni into the mesoporous Gd-CeO2 films. These studies allow us designing the films with the adequate microstructure and composition. In parallel, we have extended this impedance based approach to the characterization of the cathode, GDC/LSCF. This study permits to propose a heat-treatment that conduces to the formation of highly conductive GDC/LSCF. Finally, these films were used to synthesize a micro-SOFC and performances will be discussed as function of the architecture of the micro-SOFC device.
Data Augmentation of Room Classifiers using Generative Adversarial Networks (2019)

The classification of acoustic environments allows for machines to better understand the auditory world around them. The use of deep learning in order to teach machines to discriminate between different rooms is a new area of research. Similarly to other learning tasks, this task suffers from the high-dimensionality and the limited availability of training data. Data augmentation methods have proven useful in addressing this issue in the tasks of sound event detection and scene classification. This paper proposes a method for data augmentation for the task of room classification from reverberant speech. Generative Adversarial Networks (GANs) are trained that generate artificial data as if they were measured in real rooms. This provides additional training examples to the classifiers without the need for any additional data collection, which is time-consuming and often impractical. A representation of acoustic environments is proposed, which is used to train the GANs. The representation is based on a sparse model for the early reflections, a stochastic model for the reverberant tail and a mixing mechanism between the two. In the experiments shown, the proposed data augmentation method increases the test accuracy of a CNN-RNN room classifier from 89.4% to 95.5%.