gebhart/patrepeval huggingface dataset:
Few-Shot Bearing Anomaly Detection via Model-Agnostic Meta-Learning (2020)

As an essential component of many mission-critical equipment, mechanical bearings need to be monitored to identify any traces of abnormal conditions. Most of the latest data-driven methods applied to bearing anomaly detection are trained using a large amount of fault data collected a priori. However, in many practical applications, it may be unsafe and time-consuming to collect enough data samples for each fault category, which brings challenges to training a robust classifier. This paper proposes a few-shot learning framework for bearing anomaly detection based on model-agnostic meta-learning (MAML), which aims to train an effective fault classifier using very limited data. In addition, it can use training data and learn to more effectively identify new fault conditions. A case study on the generalization of new artificial faults shows that this method can achieve up to 25% overall accuracy when compared to a benchmark study based on the Siamese network. Finally, the generalization ability of MAML is also competitive when compared with some state-of-the-art few-shot learning methods in terms of identifying realistic bearing damages using a sufficient amount of training data from artificial damages.
What Can Be Done by Individuals, Associations, and Governments (2014)

Abstract The tale of the Pied Piper of Hamelin is well known for its final imagery of a town losing its children as they are led away by a musician clad in multicolored clothes. What is less often recalled is that the cause was the council’s attempts to save money. Children were sacrificed for financial gain. This final chapter argues that actions by individuals in their daily lives, but also within associations and as electors, can be significant and worthwhile. Individual action and lifestyle choices can, to some extent, limit exposure to certain chemical categories. Clearly, pregnant women and nursing mothers need to be informed of potential risks so they can take precautionary action, and the medical profession needs to be trained to help. Ensuring that women do not enter pregnancy in a state of even mild iodine lack is a first inexpensive requirement with immense cost benefit.
Targeting norepinephrine in mild cognitive impairment and Alzheimer's disease (2013)

The Alzheimer's disease (AD) epidemic is a looming crisis, with an urgent need for new therapies to delay or prevent symptom onset and progression. There is growing awareness that clinical trials must target stage-appropriate pathophysiological mechanisms to effectively develop disease-modifying treatments. Advances in AD biomarker research have demonstrated changes in amyloid-beta (Aβ), brain metabolism and other pathophysiologies prior to the onset of memory loss, with some markers possibly changing one or two decades earlier. These findings suggest that amyloid-based therapies would optimally be targeted at the earliest clinically detectable stage (such as mild cognitive impairment (MCI)) or before. Postmortem data indicate that tau lesions in the locus coeruleus (LC), the primary source of subcortical norepinephrine (NE), may be the first identifiable pathology of AD, and recent data from basic research in animal models of AD indicate that loss of NE incites a neurotoxic proinflammatory condition, reduces Aβ clearance and negatively impacts cognition - recapitulating key aspects of AD. In addition, evidence linking NE deficiency to neuroinflammation in AD also exists. By promoting proinflammatory responses, suppressing anti-inflammatory responses and impairing Aβ degradation and clearance, LC degeneration and NE loss can be considered a triple threat to AD pathogenesis. Remarkably, restoration of NE reverses these effects and slows neurodegeneration in animal models, raising the possibility that treatments which increase NE transmission may have the potential to delay or reverse AD-related pathology. This review describes the evidence supporting a key role for noradrenergic-based therapies to slow or prevent progressive neurodegeneration in AD. Specifically, since MCI coincides with the onset of clinical symptoms and brain atrophy, and LC pathology is already present at this early stage of AD pathogenesis, MCI may offer a critical window of time to initiate novel noradrenergic-based therapies aimed at the secondary wave of events that lead to progressive neurodegeneration. Because of the widespread clinical use of drugs with a NE-based mechanism of action, there are immediate opportunities to repurpose existing medications. For example, NE transport inhibitors and NE-precursor therapies that are used for treatment of neurologic and psychiatric disorders have shown promise in animal models of AD, and are now prime candidates for early-phase clinical trials in humans.
Virulence factor expression by Gram-positive cocci exposed to subinhibitory concentrations of linezolid (2002)

Linezolid is a new oxazolidinone with potent antibacterial activity against Gram-positive cocci; it uniquely inhibits bacterial translation through inhibition of 70S initiation complex formation. The effects of sub-growth-inhibitory concentrations of linezolid on the expression of various structural and soluble virulence factors of Staphylococcus aureus and Streptococcus pyogenes were examined. For S. aureus, strains Wood 46 and Cowan 1 (NCTC 8532) were used to measure protein A, coagulase, alpha-haemolysin (hla) and delta-haemolysin (hld). For S. pyogenes, strain NCTC 9994 was used to measure M protein, streptolysin O (SLO) and DNase. Coagulase was assayed by clotting of citrated rabbit plasma, and hla, hld and SLO by lysis of rabbit, human and horse erythrocytes, respectively. Protein A and M protein were measured indirectly using bacterial susceptibility to phagocytic ingestion of radiolabelled bacteria by human neutrophils. When S. aureus was grown in 1/2, 1/4 and 1/8 MIC, linezolid, coagulase, hla and hld production were impaired. Susceptibility to phagocytosis was changed by growth in the presence of 1/2 MIC linezolid compared with that in its absence (50.8 +/- 4.1% versus 38.9 +/- 2.9%; P <or= 0.05). When S. pyogenes was grown in 1/2, 1/4 and 1/8 MIC linezolid, SLO and DNase production were impaired compared with that of bacteria grown in the absence of the drug; its susceptibility to phagocytosis was also increased (52.8% bacteria ingested versus 37.5%; P <or= 0.05). A reduction in virulence factor expression at sub-MIC linezolid concentrations may be of benefit in the treatment of Gram-positive infections.
Low cost inverter suitable for medium-power fuel cell sources (2003)

A low-cost high performance fuel cell inverter for 48 V to 120 V/sub ac/ conversion is described. The design addresses total system cost including battery and battery management while providing a current sourced interface for the fuel cell and galvanic isolation at the output. The inverter topology eliminates the need for a DC intermediate voltage by using an AC-link output inverter. This circuit is based on a square-wave cycloconverter combined with a simple new control approach to produce a "PWM cycloconverter" that supports the use of either IGBTs or SCRs to further reduce the system cost.
A Public Web Services Security Framework Based on Current and Future Usage Scenarios. (2002)

The thermodynamic association of RNA polymerase (RNAP) with DNA is sensitive to salt concentration in vitro. Paradoxically, previous studies of changes in osmolarity during steady-state cell growth found no dependence between the association of RNAP to DNA and K(+) concentration in Escherichia coli. We reevaluated this issue by following the interaction of RNAP and genomic DNA in time-course experiments during the hyper-osmotic response. Our results show that the interaction is temporally controlled by the same physical chemistry principle in the cell as in vitro. RNAP rapidly dissociates from the genome during the initial response when the cytoplasmic K(+) accumulates transiently, and concurrently the nucleoid becomes hyper-condensed. The freed RNAP re-associates with the genome during a subsequent osmoadaptation phase when organic osmoprotectants accumulate as K(+) levels decrease. RNAP first surrounds the hyper-condensed nucleoid forming a sphere of RNAP before it progressively moves in to the center of the nucleoid. Our findings reinterpret the dynamic protein-DNA interactions during osmotic stress response. We discuss the implications of the dissociation/association of RNAP for osmotic protection and nucleoid structure.
Mixed ligand cobalt(ii) picolinate complexes: synthesis, characterization, DNA binding and photocleavage (2010)

Complexes of the type [Co(pic)(2)(NN)], where pic = picolinate, NN = dipyrido[3,2-d:2',3'-f]quinoxaline (dpq) (4) and 4b,5,7,7a-tetrahydro-4b,7a-epiminomethanoimino-6H-imidazo[4,5-f][1,10]-phenanthroline-6,13-dione (bipyridyl-glycoluril) (bpg) (6) have been synthesized and characterized by elemental analysis, IR, UV-vis, NMR and ESI-MS spectroscopy and thermogravimetic analysis (TGA). Their physicochemical properties are compared with previously synthesized complexes, where NN = (H(2)O)(2) (1), 2,2'-bipyridine (bpy) (2), 1,10-phenanthroline (phen) (3) and dipyrido[3,2-a:2',3'-c]phenazine (dppz) (5). The crystal structures of the complexes 4-6 were solved by single-crystal X-ray diffraction. The complexes 4 and 5 crystallize from a mixture of chloroform and methanol in monoclinic and orthorhombic crystal systems, respectively, whereas complex 6 crystallizes from dimethyl sulfoxide (DMSO) in a tetragonal crystal system. The coordination sphere consists of two oxygen atoms and two nitrogen atoms from the two picolinates and two nitrogen atoms from the dpq, dppz or bpg ligand, respectively. Co(ii)/Co(iii) oxidation potentials have been determined by cyclic voltammetry. The DNA binding of complexes 1-5 has been investigated using thermal melting, fluorescence quenching and viscosity measurements, which indicate the partial intercalation of complex 5 with an apparent binding constant (k(app)) of 8.3 × 10(5) M(-1). DNA cleavage studies of complexes 1-5 have been investigated using gel electrophoresis in the presence of H(2)O(2) as an oxidizing agent and also by photoirradiation at 365 nm. The mechanistic investigations suggest that singlet oxygen ((1)O(2)) is the major species involved in the DNA cleavage by these complexes. The structures of complexes 2-6 were optimized with density functional theory (DFT) method (B3LYP/6-31G(d,p)). The low vertical ionization potential values indicate photoredox pathways for the DNA cleavage activity by complexes 4 and 5, which is corroborated by DNA cleavage experiments.
Human Action Recognition Using Global Point Feature Histograms and Action Shapes (2009)

This paper investigates the recognition of human actions from three-dimensional (3-D) point clouds that encode the motions of people acting in sensor-distributed indoor environments. Data streams are time sequences of silhouettes extracted from cameras in the environment. From the 2-D silhouette contours we generate space–time streams by continuously aligning and stacking the contours along the time axis as third spatial dimension. The space–time stream of an observation sequence is segmented into parts corresponding to subactions using a pattern matching technique based on suffix trees and interval scheduling. Then, the segmented space–time shapes are processed by treating the shapes as 3-D point clouds and estimating global point feature histograms for them. The resultant models are clustered using statistical analysis and our experimental results indicate that the presented methods robustly derive different action classes. This holds despite large intra-class variance in the recorded datasets due to performances from different persons at different time intervals.
Inventor Name Disambiguation for a Patent Database Using a Random Forest and DBSCAN (2016)

Inventor name disambiguation is the task that distinguishes each unique inventor from all other inventor records in a patent database. This task is essential for processing person name queries in order to get information related to a specific inventor, e.g. a list of all that inventor's patents. Using earlier work on author name disambiguation, we apply it to inventor name disambiguation. A random forest classifier is trained to classify whether each pair of inventor records is the same person. The DBSCAN algorithm is use for inventor record clustering, and its distance function is derived using the random forest classifier. For scalability, blocking functions are used to reduce the complexity of record matching and enable parallelization since each block can be run simultaneously. Tested on the USPTO patent database, 12 million inventor records were disambiguated in 6.5 hours. Evaluation on the labeled datasets from USPTO PatentsView competition shows our algorithm outperforms all algorithms submitted to the competition.
Environmental test program for superconducting materials and devices (1991)

This report is divided into two parts. The first dealing with work involved with Clemson University and the second with the results from Westinghouse/Savannah River. Both areas of work involved low noise, low thermal conductivity superconducting grounding links used in the NASA-sponsored Spectroscopy of the Atmosphere using Far Infrared Emission (SAFIRE) Project. Clemson prepared the links from YBa2Cu3O(7-x) superconductor tape that was mounted on a printed circuit board and encapsulated with epoxy resin. The Clemson program includes temperature vs. resistance, liquid nitrogen immersion, water immersion, thermal cycling, humidity, and radiation testing. The evaluation of the links under a long term environmental test program is described. The Savannah River program includes gamma irradiation, vibration, and long-term evaluation. The progress made in these evaluations is discussed.
Application of the bilateral Dual-Grid FDTD method to the calculation of Specific Absorption Rate in fetal brain (2010)

International audience
Membership Inference Attacks are Easier on Difficult Problems (2021)

Membership inference attacks (MIA) try to detect if data samples were used to train a neural network model, e.g. to detect copyright abuses. We show that models with higher dimensional input and output are more vulnerable to MIA, and address in more detail models for image translation and semantic segmentation, including medical image segmentation. We show that reconstruction-errors can lead to very effective MIA attacks as they are indicative of memorization. Unfortunately, reconstruction error alone is less effective at discriminating between non-predictable images used in training and easy to predict images that were never seen before. To overcome this, we propose using a novel predictability error that can be computed for each sample, and its computation does not require a training set. Our membership error, obtained by subtracting the predictability error from the reconstruction error, is shown to achieve high MIA accuracy on an extensive number of benchmarks.
Mine First to See Better: Constraint-based Data Mining for Computer Vision Applications: Habilitation à Diriger des Recherches (2015)

This "Habilitation à Diriger des Recherches" aims at assessing the work I did for the last ten years after defending my PhD thesis. It shows not only the coherence but the evolution and the multidisciplinary aspects of my work. It is organized as follows. In Chapter 2, I will present the constraint-based exhaustive data mining tools I have developed in the context of inductive databases. In particular, I will focus on the definition of a general framework of inductive database and then on the constraints and their properties to restrict the search space and make this exhaustive search possible in the case of decision trees, clustering, closed sets and graph mining. Chapters 3 and 4 will develop my computer vision applications and will give some results obtained by applying the previously introduced algorithms as well as new algorithms dedicated to this particular context. I will, in particular, cover applications in image classification and object tracking in videos. The last chapter concludes this report and draws some possible prospects for this work.
Optical limiting properties of metallodielectric photonic bandgap structures (2003)

In this work we investigated the nonlinear optical properits of a one-dimensional, tranparent metallo-dielectric photonic band gap structure. Specifically, we consider multilayer samples having a nonlinear material as a component. We chose ZnO due to its transparency in the visible region and to its well known optical nonlinearity. By means of dual ion beam sputtering technique we realized a four period sample where the single period consists of ZnO and Ag layers. Sample structure was opportunely designed in order to achieve high nonlinear optical response. A Q-switched frequency doubled Nd:YAG laser has been used in order to investigate the transmissive properties of the sample under high light intensities. A transmission decrease of approximately 50% was found for a maximum incident light intensity of 2 GW/cm<sup>2</sup>.
Brain Endothelial Cells Bridge Neural and Immune Networks (2007)

The brain has the highest metabolic rate of any organ structure in the human body. Although the human brain contributes only 2% to the total body weight, it uses approximately 16% of the body's cardiac output and accounts for nearly 25% of the body's oxygen consumption (1). Brain-associated endothelium includes all endothelial cells (ECs) found within the brain, including ECs of the blood–brain barrier (BBB) and circumventricular organs (CVOs) (Figure 124.1). One of the major functions of the endothelium within the brain is to direct the flow of oxygenated blood. It is estimated that approximately 600 to 700 mL of blood flows through the carotid arteries and their branches every minute to distribute oxygenated blood to the anterior portion of the brain. The capillaries, the principal vasculature within the brain, are very important components of the brain's supply system. Because of their small diameter and large number per volume of brain tissue, these capillaries provide a large surface area for delivering adequate supplies of glucose and oxygen.
Nucleotide Sequence of Oat (<i>Avena sativa</i>L.) cDNA Encoding an Auxin-binding Protein (ABP1) (1998)

We isolated and determined a nucleotide sequence of a cDNA clone encoding a protein homologous to maize major auxin-binding protein (ABP1) from a cDNA library of oat coleoptiles. The deduced amino acid sequence of this clone contained an N-linked glycosylation signal and an ER-retention signal. Furthermore, two domains that were important to interact with auxins, were conserved in this clone at amino acid level.
High Throughput Multi-Threaded Software Defined Convolutional Interleaver (2021)

A convolutional interleaver is a data reordering operation used to distribute bursts of errors and improve the performance of forward error correction algorithms in the presence of dropout events. This type of interleaver is used in several commercial and military standards as it offers the same performance as a traditional rectangular interleaver but with half the memory requirement. This paper presents a very novel algorithm and architecture for convolutional interleaving implemented on modern general-purpose processors (CPUs). The naïve implementation of a convolutional interleaver does not map well to modern multi-processor CPUs due to its non-sequential memory access pattern and inherently serial processing sequence. Non-sequential memory access is very inefficient in general-purpose processors as the high-speed, low-latency cache memory in modern CPU architectures assume some level of data locality. The sparse memory access pattern of a naïve convolutional interleaver implementation has almost no data locality, causing the CPU to frequently stall as it waits on data from the high-latency external memory. In addition, these memory bottlenecks make attempts to multithread the software implementation pointless, as modern general-purpose processor cores share memory resources. The key breakthroughs described in the paper address both these challenges - the algorithm is modified to interleave buffers of bits in a `cache friendly' order rather than the input order, leading to significantly higher single-core performance. Resolving the memory access bottleneck also enables an efficient parallelization approach that can take advantage of multiple cores with shared memory, pushing performance even higher. Whereas previous convolutional interleaver software implementations ran into memory bottlenecks around 0.5GSps, the multithreaded version of the presented algorithm can be consistently benchmarked at above 8 GSps on a mid-range server CPU.
Exogenous expression of caspase-14 induces tumor suppression in human salivary cancer cells by inhibiting tumor vascularization. (2009)

Salivary gland cancer cells underwent growth inhibition, cell death, and reduced tumorigenicity in vivo when exogenous caspase-14 was expressed, which could be due, in part, to an inhibitory effect of caspase-14 on tumor vascularization.
Multi-Exposure Image Fusion Based on Exposure Compensation (2018)

This paper proposes a novel multi-exposure image fusion method based on exposure compensation. Multi-exposure image fusion is a method to produce images without color saturation regions, by using photos with different exposures. However, in conventional works, it is unclear how to determine appropriate exposure values, and moreover, it is difficult to set appropriate exposure values at the time of photographing due to time constraints. In the proposed method, the luminance of the input multi-exposure images is adjusted on the basis of the relationship between exposure values and pixel values, where the relationship is obtained by assuming that a digital camera has a linear response function. The use of a local contrast enhancement method is also considered to improve input multi-exposure images. The compensated images are finally combined by one of existing multi-exposure image fusion methods. In some experiments, the effectiveness of the proposed method are evaluated in terms of the tone mapped image quality index, statistical naturalness, and discrete entropy, by comparing the proposed one with conventional ones.
Development and Feasibility of a Non-Invasive, Wireless Parachute Load Distribution Measuring System (2014)

In order to improve the accuracy of low-cost circular parachute systems, it is necessary to understand the physical effects present during descent. Historically, parachute loading has been assumed to be relatively symmetric regardless of the canopy mode (inflating or steady state), therefore, typical testing of the parachute loads consists of only a single load cell placed at the suspension line confluence point. Recent investigations have shown significant asymmetric suspension line loads during parachute drop testing; however, only four load cells were used in the investigation. Asymmetric loading impacts both the stresses imposed on suspension lines, as well as the repeatability of parachute performance between tests. This paper discusses the development and preliminary flight testing of a wireless, noninvasive load-cell instrumentation suite capable of capturing loading information on each individual suspension line. The system incorporates low-cost, custom designed strain gauge load cells that clamp onto existing suspension lines. All information is telemetered wirelessly to a single microcontroller unit in the cargo payload. Static and dynamic calibration experiments were conducted to quantify the accuracy of the load cells prior to drop testing. Drop testing was conducted in a controlled, indoor environment with a small-scale 0.91 m (36 inch) circular parachute and a payload weight of 10.2 N (2.29 lbs.). Testing results demonstrate the feasibility of a wireless system; however, additional testing and verification is required prior to conducting a rigorous parachute testing regime.