gebhart/patrepeval huggingface dataset:
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring Systems (2020)

Automatic scoring engines have been used for scoring approximately fifteen million test-takers in just the last three years. This number is increasing further due to COVID-19 and the associated automation of education and testing. Despite such wide usage, the AI-based testing literature of these "intelligent" models is highly lacking. Most of the papers proposing new models rely only on quadratic weighted kappa (QWK) based agreement with human raters for showing model efficacy. However, this effectively ignores the highly multi-feature nature of essay scoring. Essay scoring depends on features like coherence, grammar, relevance, sufficiency and, vocabulary. To date, there has been no study testing Automated Essay Scoring: AES systems holistically on all these features. With this motivation, we propose a model agnostic adversarial evaluation scheme and associated metrics for AES systems to test their natural language understanding capabilities and overall robustness. We evaluate the current state-of-the-art AES models using the proposed scheme and report the results on five recent models. These models range from feature-engineering-based approaches to the latest deep learning algorithms. We find that AES models are highly overstable. Even heavy modifications(as much as 25%) with content unrelated to the topic of the questions do not decrease the score produced by the models. On the other hand, irrelevant content, on average, increases the scores, thus showing that the model evaluation strategy and rubrics should be reconsidered. We also ask 200 human raters to score both an original and adversarial response to seeing if humans can detect differences between the two and whether they agree with the scores assigned by auto scores.
Learning Between Different Teacher and Student Models in ASR (2019)

Teacher-student learning can be applied in automatic speech recognition for model compression and domain adaptation. This trains a student model to emulate the behaviour of a teacher model, and only the student is used to perform recognition. Depending on the application, the teacher and student may differ in their model types, complexities, input contexts, and input features. In previous works, it is often shown that learning from a strong teacher allows the student to perform better than an equivalent model trained with only the reference transcriptions. However, there has not been much investigation into whether a particular form of teacher is appropriate for the student to learn from. This paper aims to study how effectively the student is able to learn from the teacher, when differences exist between their designs. The Augmented Multi-party Interaction (AMI) meeting transcription and Multi-Genre Broadcast (MGB-3) television broadcast audio tasks are used in this analysis. Experimental results suggest that a student can effectively learn from a more complex teacher, but may struggle when it lacks input information. It is therefore important to carefully consider the design of the student for each application.
Neurocognitive function in bipolar disorder (2012)

Pålsson, E; Figueras, C; Johansson, A G M; Ekman, C-J; Hultman, B; Östlind, J; Landén, M Author Information
Tests of a prototype pixel array detector for microsecond time-resolved X-ray diffraction (1999)

X-ray test results from a prototype 92 × 100 pixel array detector (PAD) for use in rapid time-resolved X-ray diffraction studies are described. This integrating detector is capable of taking up to eight full-frame images at microsecond frame times. It consists of a silicon layer, which absorbs the X-rays, bump-bonded to a layer of CMOS electronics in which each pixel has its own processing, storage and readout electronics. Tests indicate signal performance characteristics are comparable with phosphor-based CCD X-ray detectors, with greatly improved time resolution, comparable linearity and enhanced point spread. This prototype is a test module en route to a larger detector suitable for dedicated operation. Areas of needed improvement are discussed.
Optical Monitoring of Bolt Tightening Using 3D Electronic Speckle Pattern Interferometry (2006)

An optical method is presented for the real-time monitoring of the bolt tightening process that provides the necessary clamping force in bolted assemblies. The method uses the 3D electronic speckle pattern interferometry (ESPI) technique to measure and monitor the joint deformation and strain fields in the joint around the tightened fastener, and establish a reliable correlation with the clamp load provided by the fastener tightening. Because the relationship between the clamp load and joint deformation is independent of the frictional variables of the fastener, the direct monitoring of the deformation and strain fields in the clamped joint would provide a more reliable measure of the clamp load level, as compared to the conventional reliance on the tightening torque to predict the resulting clamp load level. This technique is beneficial, especially for monitoring, with high precision, the proper tightening of critical bolted connections such as those used in many pressure vessels in the nuclear power industry. The validity of the optical technique is also ascertained by comparing the results to that obtained by using finite element analysis and other classical mechanics of materials methods.
A Bayesian Model of Visual Question Answering (2016)

Visual Question Answering (VQA) is a new problem in computer vision and natural language processing, with the first three English language datasets for VQA being released in the past year: DAQUAR, The VQA Dataset, and COCO-QA. In VQA, a model is given an image and a text-based question about a scene, and the model has to answer the question. The key insight in our model for VQA is that we can predict the form of the answer from the question. We formulate our model in a Bayesian framework, which has three multiplicative terms. The first predicts the form of the answer expected based on the question, e.g., if the question is, "What color is the bear?" it would model the probability of it being a color question. The second predicts the probability of the answer given the answer-type and the question. The third term predicts the probability of the observed visual features given the answer, answer-type, and the question. Our model shares similarities with visual attention, in that it directly models that the image features that should be attended directly depend on the task (question). We used a deep convolutional neural network for visual features, and use skip-thoughts to encode the questions. Our model achieved state-of-the-art results on all three benchmark datasets for open-ended VQA on real images beating the previous best by 14.9% (in relative terms) in the best case. While our results are good, there is still substantial room for improvement compared to humans when they are given the same images and questions. Meeting abstract presented at VSS 2016
InfoNEAT: Information Theory-based NeuroEvolution of Augmenting Topologies for Side-channel Analysis (2021)

Profiled side-channel analysis (SCA) leverages leakage from cryptographic implementations to extract the secret key. When combined with advanced methods in neural networks (NNs), profiled SCA can successfully attack even those crypto-cores assumed to be protected against SCA. Despite the rise in the number of studies devoted to NN-based SCA, a range of questions has remained unanswered, namely: how to choose an NN with an adequate configuration, how to tune the NN's hyperparameters, when to stop the training, etc. Our proposed approach, ``InfoNEAT,'' tackles these issues in a natural way. InfoNEAT relies on the concept of neural structure search, enhanced by information-theoretic metrics to guide the evolution, halt it with novel stopping criteria, and improve time-complexity and memory footprint. The performance of InfoNEAT is evaluated by applying it to publicly available datasets composed of real side-channel measurements. In addition to the considerable advantages regarding the automated configuration of NNs, InfoNEAT demonstrates significant improvements over other approaches for effective key recovery in terms of the number of epochs (e.g.,x6 faster) and the number of attack traces compared to both MLPs and CNNs (e.g., up to 1000s fewer traces to break a device) as well as a reduction in the number of trainable parameters compared to MLPs (e.g., by the factor of up to 32). Furthermore, through experiments, it is demonstrated that InfoNEAT's models are robust against noise and desynchronization in traces.
Decision uncertainty as a context for motor memory (2023)

Abstract The current view of perceptual decision-making suggests that once the decision is made, a single motor program associated with the decision is carried out, irrespective of the degree of uncertainty involved in the decision-making process. As opposed to this view, we show that different levels of decision uncertainty contextualize actions differently, allowing the brain to form different motor memories based on each context. The match between decision uncertainty during learning and retrieval is critical for successful motor memory retrieval. The same movement trajectory can be associated with different motor memories if each memory is linked to a different level of decision uncertainty. Encoding motor memories based on decision contexts may enhance the robustness of control during the varying neural activities induced by different cognitive states.
Comparison of two parathyroid hormone assays for the rat: The new immunoradiometric and the older competitive binding assay (1994)

A competitive binding assay for parathyroid hormone (PTH INS) has been used since 1986 to measure PTH in rats. During the past year an immunoradiometric assay for the measurement of PTH (PTH IRMA) in the rat was developed. The purpose of the present study was to compare results obtained with the PTH INS and IRMA and to provide a framework for comparison for investigators who have used the PTH INS in previous studies. A total of 99 rats were studied; 27 rats had normal renal function, and 72 rats had surgically induced renal failure. In the azotemic rats, the magnitude of hyperparathyroidism was varied by changing the calcium and phosphorus composition of the diet. The correlation between the two PTH assays in the 99 rats was r = 0.98, p < 0.001. For the 27 rats with normal renal function, the correlation even within the narrow range of normal PTH values was significant, r = 0.71, p < 0.001. In the 72 azotemic rats, in which the highest INS PTH value was approximately 17 times normal, the correlation between the two PTH assays was r = 0.98, p < 0.001. The PTH IRMA provides distinct advantages, such as extended standard range, shortened incubation time, increased sensitivity, and technical simplicity, but our results indicate that the PTH INS provided an accurate measurement of PTH. Furthermore, our results should provide investigators who have used the PTH INS in previous studies with a framework for comparison with studies in which the PTH IRMA was used.
2,7-Disubstituted-Pyrrolotriazine Kinase Inhibitors with an Unusually High Degree of Reactive Metabolite Formation (2011)

There are numerous published studies establishing a link between reactive metabolite formation and toxicity of various drugs. Although the correlation between idiosyncratic reactions and reactive metabolite formation is not 1:1, the association between the two is such that many pharmaceutical companies now monitor for reactive metabolites as a standard part of drug candidate testing and selection. The most common method involves in vitro human microsomal incubations in the presence of a thiol trapping agent, such as glutathione (GSH), followed by LC/MS analysis. In this study, we describe several 2,7-disubstituted-pyrrolotriazine analogues that are extremely potent reactive metabolite precursors. Utilizing a UPLC/UV/MS method, unprecedented levels of GSH adducts were measured that are 5-10 times higher than previously reported for high reactive metabolite-forming compounds such as clozapine and troglitazone.
Survey for human polyomaviruses in cancer (2016)

Over the past 8 years, the discovery of 11 new human polyomaviruses (HPyVs) has revived interest in this DNA tumor virus family. Although HPyV infection is widespread and largely asymptomatic, one of these HPyVs, Merkel cell polyomavirus (MCV), is a bona fide human tumor virus. JC virus (JCV), BK virus, HPyV7, and trichodysplasia-spinulosa virus (TSV) can cause nonneoplastic diseases in the setting of immunosuppression. Few specific reagents are available to study the biology of the newly discovered HPyVs. We developed a pan-HPyV-screening method using a cocktail of 3 antibodies that, when combined, recognize T antigen proteins of all HPyVs. We validated detection characteristics of the antibody cocktail by immunoblotting and immunohistochemistry and screened 1,184 cases, including well-defined diseases and tumor tissue microarrays. This assay robustly detected MCV, TSV, JCV, and HPyV7 in etiologically related diseases. We further identified WU polyomavirus in a case of chronic lymphocytic lymphoma-associated bronchitis. Except for scattered, incidentally infected cells in 5% of lung squamous cell carcinomas and colon adenocarcinomas, a broad panel of tumor tissues was largely negative for infection by any HPyV. This method eliminates known HPyVs as suspected causes of cancers investigated in this study. Pan-HPyV survey can be applied to identify diseases associated with recently discovered polyomaviruses.
Uncertainty Quantification in Neural Differential Equations (2021)

Uncertainty quantification (UQ) helps to make trustworthy predictions based on collected observations and uncertain domain knowledge. With increased usage of deep learning in various applications, the need for efficient UQ methods that can make deep models more reliable has increased as well. Among applications that can benefit from effective handling of uncertainty are the deep learning based differential equation (DE) solvers. We adapt several state-of-the-art UQ methods to get the predictive uncertainty for DE solutions and show the results on four different DE types.
Electrochemical Depolymerization of Lignin in a Biomass-based Solvent (2022)

The successive breakdown of the lignin macromolecule into smaller units is the key to generate high value-added products from this complex plant polyphenol. Obtaining well-defined aromatic compounds is, therefore, an important step towards the production of biobased chemicals for the fuel, coating and lubricant industries. Nevertheless, processes requiring lignin dissolution are always challenging. Dissolving this macromolecule in an environment-friendly way takes this challenge to a whole new level. Levulinic acid, an organic compound formed during the hydrothermal processing of lignocellulosic biomass, has been shown to efficiently dissolve lignin. Herein, we describe a system consisting of levulinic acid as a biobased solvent for the reductive electrochemical depolymerization of lignin. Copper was used as an electrocatalyst due to the economic feasibility and low activity towards the hydrogen evolution reaction. After depolymerization, high-resolution mass spectrometry and NMR structural characterization revealed lignin-derived monomers and dimers. A predominance of aryl ether and phenolic groups was observed. The effect of the depolymerized lignin as an anti-corrosion coating was assessed, revealing enhancements on the electrochemical stability of the metal. Via a simple depolymerization process of biomass waste in a biomass-based solvent, these results demonstrate a straightforward approach to produce high value-added compounds or tailored biobased materials.
ZnO Oxygen Vacancies Formation and Filling Followed by in Situ Photoluminescence and in Situ EPR (2012)

Oxygen vacancies of zinc oxide were followed by photoluminescence (PL) and electron paramagnetic resonance (EPR) spectroscopies. The green PL emission was associated with oxygen vacancies: its intensity is enhanced upon static thermal treatment under inert or under vacuum, whereas it decreases upon oxygen treatment. A unique EPR signal at <i>g</i> = 1.96 was measured at room temperature after thermal in situ treatment under flow of inert or oxygenated atmospheres, its double integration follows the same trends than the green PL emission and its evolution was shown to probe the oxygen vacancy concentrations. The relative concentration of the related paramagnetic species would be increased/decreased upon trapping/release of the electron associated to the formation/filling of oxygen vacancy. The influence of Ti impurities on the PL and RPE signals was investigated. Finally, it is concluded that the EPR signal is related to oxygen vacancies and its position shift could be explained by the involvement of some mixing orbitals. Thanks to static (PL and EPR) and dynamic (EPR) in situ characterizations, the conditions of formation or filling of oxygen vacancies are discussed depending of the atmosphere and temperature of the pretreatment of kadox and ex-carbonate zinc oxide. High temperature treatments, inert atmospheres, and vacuum lead to the formation of new oxygen vacancies. This process is reversible upon oxygenated atmospheres. The efficiency of such filling up depends on the temperature and starts to prevail on the oxygen vacancy formation below 500 K. It is also shown that few native oxygen vacancies can also be filled up.
Performance and safety of treatment options for erectile dysfunction in patients with spinal cord injury: A review of the literature (2020)

The best treatment options for erectile dysfunction in spinal cord injury patients emerged to be phosphodiesterase 5-inhibitors and intracavernous drug injection. The choice of erectile dysfunction treatment should be based on several aspects, including residual erectile function, spinal cord injury location, and patients' comorbidities. Future studies assessing the applicability of less well-studied treatments, as well as evaluating innovative options, are needed in this specific population.
A low-cost monitoring station for detection &amp; localization of interference in GPS L1 band (2012)

GNSS sensors have become critical in some applications while the low power levels of the received signals are vulnerable to interference. This paper presents a system made of networked low-cost monitoring stations with the ability to detect and localize interference sources. The method is based on time difference of arrival (TDOA) measurements obtained by cross-correlating raw IF samples collected by unsynchronized front ends. The capabilities have been demonstrated experimentally in a controlled test executed in June 2012 with commercial jammers in both stationary and dynamic scenarios.
Surface reactions of metal clusters. II. Reactivity surveys with D2, N2, and CO (1985)

Reactions on the surface of a variety of transition metal clusters have been studied in the gas phase at near room temperature using a newly developed fast-flow reaction device. Initial examples of the use of this device are provided by survey studies of the reactivity of iron, cobalt, nickel, copper, and niobium clusters in contact with low concentrations of D2, N2 and CO. Dissociative chemisorption of D2 is found to occur with dramatic sensitivity to cluster size in the cases of iron, cobalt, and niobium clusters, the detailed pattern of reactivity differing markedly for each metal. The corresponding reaction is also observed with nickel clusters, but here the reactivity shows only a slow, steady increase with cluster size. Copper clusters are found to be completely unreactive to H2 chemisorption under these conditions. Molecular nitrogen is found to chemisorb readily to clusters of cobalt and niobium, with a reactivity pattern very similar to that observed with D2. Iron clusters are found to show slight reactivity with N2; only a small amount of chemisorption is observed on the most reactive clusters at high N2 concentration, but the pattern of this reactivity with cluster size is consistent with that observed in D2 chemisorption. In contrast to these highly structured reactivity patterns of D2 and N2, carbon monoxide is found to show only a slow, monotonic increase in reactivity with cluster size. It is suggested that these dramatic reactivity patterns for chemisorption on metal clusters provide stringent tests for future theories as to the nature of chemisorption on metal surfaces at a detailed, molecular level.
Effects of Olive (Olea europaea L.) Leaves with Antioxidant and Antimicrobial Activities on In Vitro Ruminal Fermentation and Methane Emission (2021)

We evaluated whether olive leaves (OLs) are effective as feed additives and supplements for ruminants and the potential methane reduction effects during in vitro fermentation. Two Hanwoo cows (460 ± 20 kg) equipped with cannula were fed Timothy hay and corn-based feed 3% of the body weight at a ratio of 6:4 (8:30 a.m. and 5:00 p.m.). Ruminal fluid from the cows was collected and mixed before morning feeding. In vitro batch fermentation was monitored after 12 and 24 h of incubation at 39 °C, and OLs were used as supplements to achieve the concentration of 5% in the basal diet. At 12 h of fermentation, methane production decreased in the 5% OLs group compared to that in the control group, but not at 24 h. The proportion of cellulose-degrading bacteria, <i>Fibrobacter succinogenes, Ruminococcus albus</i>, and <i>Ruminococcus flavefaciens</i>, tended to increase in the 5% OLs group at 12 h. The amount of ammonia produced was the same as the polymerase chain reaction result for <i>Prevotella ruminicola</i>. At 12 h, the proportion of <i>Prevotella ruminicola</i> was significantly higher in the 5% OLs group. OLs may be used incorporated with protein byproducts or other methane-reducing agents in animal feed.
Detachment and cytolysis of human endothelial cells by proteinase 3 (1994)

Activation and degranulation of polymorphonuclear leukocytes (PMN) with release of proteolytic enzymes, such as proteinase 3 (PR3) and elastase, in the vessels of patients with Wegener's granulomatosis (WG) is thought to play an important role in the vascular endothelial cell damage. We have investigated the detachment and cytolysis of 51Cr-labeled umbilical vein endothelial cells (HUVEC) induced by highly purified, enzymatically active, PR3 and elastase. Incubation of confluent monolayers of HUVEC with 100 mU/ml of PR3 for 3 h at 37 degrees C generally resulted in 20% detachment and 30% cytolysis. Elastase (350 mU/ml) induced approximately 40% detachment and 15% cytolysis. Both PR3-mediated and elastase-mediated detachment and cytolysis were fully inhibited by alpha-1-proteinase inhibitor (alpha 1 PI), while anti-leukoprotease (ALP) only inhibited elastase-mediated endothelial damage. By selective inhibition of an azurophilic granule extract with either alpha 1PI or ALP we calculated that PR3 is responsible for 23% of the total detachment and cytolysis induced by the extract. Elastase was responsible for 60% of the detachment and 19% of the cytolysis. Detachment induced by PR3 was inhibited by three out of five IgG preparations purified from c-ANCA-positive sera of WG patients. PR3-mediated cytolysis was inhibited by each of the c-ANCA+IgG preparations and also to a limited extent by control IgG, suggesting a partial nonspecific stabilization of the endothelial cells. These studies provide evidence that besides elastase, PR3 also plays an important role in the PMN-mediated endothelial cell damage.
A Telephony Gateway REgistration Protocol (TGREP) (2008)

A Telephony Gateway REgistration Protocol (TGREP