gebhart/patrepeval huggingface dataset:
Remaining Useful Life Prediction of Aircraft Auxiliary Power Unit with On-wing Sensing Data (2018)

As one key subsystem of the aircraft, Auxiliary Power Unit (APU) is mainly utilized to provide compressed air for starting the main engines. Besides, APU also supplies air conditioning and electrical power in the cabin when the aircraft is at the gate. Its reliability determines the flight quality at a large degree. In the future all-electric aircraft, APU will also be adopted to provide some additional thrust. The safety of the more/all-electric aircraft will also depend on the APU condition. Therefore, how to predict the Remaining Useful Life (RUL) of the on-wing APU has become an important research interest. In this study, one kind of data-driven RUL prediction approach for APU is proposed, which is based on the combination of mutual information and Gaussian Process Regression. By predicting the RUL of APU, the condition-based maintenance can be scheduled more reasonably and precisely. The effectiveness of the proposed approach is evaluated by utilizing the on-wing sensing data of APU APS3200 from the Shenyang Maintenance Base of China Southern Airlines Company Limited.
Tree-Independent Dual-Tree Algorithms (2013)

Dual-tree algorithms are a widely used class of branch-and-bound algorithms. Unfortunately, developing dual-tree algorithms for use with different trees and problems is often complex and burdensome. We introduce a four-part logical split: the tree, the traversal, the point-to-point base case, and the pruning rule. We provide a meta-algorithm which allows development of dual-tree algorithms in a tree-independent manner and easy extension to entirely new types of trees. Representations are provided for five common algorithms; for k-nearest neighbor search, this leads to a novel, tighter pruning bound. The meta-algorithm also allows straightforward extensions to massively parallel settings.
Advances in engineering hydrogels (2017)

Hydrogels are formed from hydrophilic polymer chains surrounded by a water-rich environment. They have widespread applications in various fields such as biomedicine, soft electronics, sensors, and actuators. Conventional hydrogels usually possess limited mechanical strength and are prone to permanent breakage. Further, the lack of dynamic cues and structural complexity within the hydrogels has limited their functions. Recent developments include engineering hydrogels that possess improved physicochemical properties, ranging from designs of innovative chemistries and compositions to integration of dynamic modulation and sophisticated architectures. We review major advances in designing and engineering hydrogels and strategies targeting precise manipulation of their properties across multiple scales.
Application of metagenomics in the human gut microbiome (2015)

There are more than 1000 microbial species living in the complex human intestine.The gut microbial community plays an important role in protecting the host against pathogenic microbes,modulating immunity,regulating metabolic processes,and is even regarded as an endocrine organ.However,traditional culture methods are very limited for identifying microbes.With the application of molecular biologic technology in the field of the intestinal microbiome,especially metagenomic sequencing of the next-generation sequencing technology,progress has been made in the study of the human intestinal microbiome.Metagenomics can be used to study intestinal microbiome diversity and dysbiosis,as well as its relationship to health and disease.Moreover,functional metagenomics can identify novel functional genes,microbial pathways,antibiotic resistance genes,functional dysbiosis of the intestinal microbiome,and determine interactions and co-evolution between microbiota and host,though there are still some limitations.Metatranscriptomics,metaproteomics and metabolomics represent enormous complements to the understanding of the human gut microbiome.This review aims to demonstrate that metagenomics can be a powerful tool in studying the human gut microbiome with encouraging prospects.The limitations of metagenomics to be overcome are also discussed.Metatranscriptomics,metaproteomics and metabolomics in relation to the study of the human gut microbiome are also briefly discussed.
Transdermal Drug Delivery: Innovative Pharmaceutical Developments Based on Disruption of the Barrier Properties of the Stratum Corneum (2015)

The skin offers an accessible and convenient site for the administration of medications. To this end, the field of transdermal drug delivery, aimed at developing safe and efficacious means of delivering medications across the skin, has in the past and continues to garner much time and investment with the continuous advancement of new and innovative approaches. This review details the progress and current status of the transdermal drug delivery field and describes numerous pharmaceutical developments which have been employed to overcome limitations associated with skin delivery systems. Advantages and disadvantages of the various approaches are detailed, commercially marketed products are highlighted and particular attention is paid to the emerging field of microneedle technologies.
High Frequency Trading: Overview of Recent Developments (2016)

This report provides background on various High-frequency trading (HFT) strategies and some associated policy issues, recent regulatory developments and selected enforcement actions by the SEC and Commodity Futures Trading Commission (CFTC), on HFT, and congressional action such as proposed legislation and hearings related to HFT.
Effect of Flaws on the Fracture Behavior of Structural Ceramics: A Review (1988)

Ceramic materials have been recognized as potential candidates for use in structural applications by virtue of their potentially excellent mechanical integrity and chemical stability at high temperatures. These structural applications include advanced heat engines, heat exchangers, and components subjected to friction and wear. Important structural ceramics include Si{sub 3}N{sub 4}, SiC, and toughened ZrO{sub 2}. It has been observed that the mechanical properties of these ceramics, especially the strength, are often degraded by the presence of flaws. The effective service strength can be increased by eliminating the flaws or eliminating parts that contain flaws. This type of quality assurance requires nondestructive evaluation (NDE) techniques to detect flaws and an understanding of the effect of flaws on fracture behavior; the latter area has been the subject of considerable experimental and theoretical work. This paper presents a critical review of the literature in terms of the ability to predict fracture behavior from flaws detected by NDE.
Billions and billions of constraints: Whitebox fuzz testing in production (2013)

We report experiences with constraint-based whitebox fuzz testing in production across hundreds of large Windows applications and over 500 machine years of computation from 2007 to 2013. Whitebox fuzzing leverages symbolic execution on binary traces and constraint solving to construct new inputs to a program. These inputs execute previously uncovered paths or trigger security vulnerabilities. Whitebox fuzzing has found one-third of all file fuzzing bugs during the development of Windows 7, saving millions of dollars in potential security vulnerabilities. The technique is in use today across multiple products at Microsoft. We describe key challenges with running whitebox fuzzing in production. We give principles for addressing these challenges and describe two new systems built from these principles: SAGAN, which collects data from every fuzzing run for further analysis, and JobCenter, which controls deployment of our whitebox fuzzing infrastructure across commodity virtual machines. Since June 2010, SAGAN has logged over 3.4 billion constraints solved, millions of symbolic executions, and tens of millions of test cases generated. Our work represents the largest scale deployment of whitebox fuzzing to date, including the largest usage ever for a Satisfiability Modulo Theories (SMT) solver. We present specific data analyses that improved our production use of whitebox fuzzing. Finally we report data on the performance of constraint solving and dynamic test generation that points toward future research problems.
Adducts of Polymeric Organolithiums with 1,1‐Diphenylethylene. Rates of Formation and Crossover to Styrene and Diene Monomers (2003)

Abstract The addition reactions of 1,1‐diphenylethylene (DPE) to polymeric organolithium (PLi) compounds and the crossover reactions of the resulting polymeric 1,1‐diphenylalkyllithiums with styrene, isoprene and butadiene monomers have been investigated and optimized. The addition of poly(styryl)lithium (PSLi) to one unit of DPE at 25 °C is complete in 6 and 8 h in benzene and cyclohexane, respectively. After 3 d at 25 °C, the extent of end‐capping with DPE was only 9% for poly(butadienyl)lithium and 15% for poly(isoprenyl)lithium. Addition of THF ([THF]/[PLi] = 15–40) promotes quantitative addition of poly(dienyl)lithiums to DPE within 1–4 hours at 25 °C. Crossover reactions of polymeric 1,1‐diphenylalkyllithiums (growth out) to styrene monomers are slow relative to crossover reactions to diene monomers. Crossover to diene monomers is complete within approximately 2 min at 25 °C and leads to well‐defined, narrow molecular weight distribution block copolymers ( $\overline M _{\rm w} /\overline M _{\rm n}$ = 1.01 with $\overline M _{\rm n}$ (out, calc) > 2 900 g · mol −1 ). Crossover to styrene monomers requires 12 h and leads to broad molecular weight distributions ( $\overline M _{\rm w} /\overline M _{\rm n}$ > 1.1) and inefficient crossover if $\overline M _{\rm n}$ (out; calc) < 7 000 g · mol −1 and the chain end concentration is ≤ 10 −3 M . Crossover to the styrene monomer is favored by low temperatures (5 °C), high chain end concentrations, and higher molecular weights of the growing block. magnified image
Biochemical characterization of the sixth component (C6) of human complement (1982)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTBiochemical characterization of the sixth component (C6) of human complementWilliam P. Kolb, Linda M. Kolb, and Jay R. SavaryCite this: Biochemistry 1982, 21, 2, 294–301Publication Date (Print):January 19, 1982Publication History Published online1 May 2002Published inissue 19 January 1982https://pubs.acs.org/doi/10.1021/bi00531a015https://doi.org/10.1021/bi00531a015research-articleACS PublicationsRequest reuse permissionsArticle Views41Altmetric-Citations25LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models (2021)

While counterfactual examples are useful for analysis and training of NLP models, current generation methods either rely on manual labor to create very few counterfactuals, or only instantiate limited types of perturbations such as paraphrases or word substitutions. We present Polyjuice, a general-purpose counterfactual generator that allows for control over perturbation types and locations, trained by finetuning GPT-2 on multiple datasets of paired sentences. We show that Polyjuice produces diverse sets of realistic counterfactuals, which in turn are useful in various distinct applications: improving training and evaluation on three different tasks (with around 70% less annotation effort than manual generation), augmenting state-of-the-art explanation techniques, and supporting systematic counterfactual error analysis by revealing behaviors easily missed by human experts.
Utilization of a Cloud-Based Diabetes Management Program for Insulin Initiation and Titration Enables Collaborative Decision Making Between Healthcare Providers and Patients (2015)

Mobile health technology could be an effective tool in sharing data, enhancing communication, and improving glycemic control while enabling collaborative decision making in diabetes care.
Src, a molecular switch governing gain control of synaptic transmission mediated by <i>N-</i> methyl- <scp>d</scp> -aspartate receptors (1999)

The N-methyl-D-aspartate (NMDA) receptor is a principal subtype of glutamate receptor mediating fast excitatory transmission at synapses in the dorsal horn of the spinal cord and other regions of the central nervous system. NMDA receptors are crucial for the lasting enhancement of synaptic transmission that occurs both physiologically and in pathological conditions such as chronic pain. Over the past several years, evidence has accumulated indicating that the activity of NMDA receptors is regulated by the protein tyrosine kinase, Src. Recently it has been discovered that, by means of up-regulating NMDA receptor function, activation of Src mediates the induction of the lasting enhancement of excitatory transmission known as long-term potentiation in the CA1 region of the hippocampus. Also, Src has been found to amplify the up-regulation of NMDA receptor function that is produced by raising the intracellular concentration of sodium. Sodium concentration increases in neuronal dendrites during high levels of firing activity, which is precisely when Src becomes activated. Therefore, we propose that the boost in NMDA receptor function produced by the coincidence of activating Src and raising intracellular sodium may be important in physiological and pathophysiological enhancement of excitatory transmission in the dorsal horn of the spinal cord and elsewhere in the central nervous system.
A Handheld Gun Detection using Faster R-CNN Deep Learning (2017)

Today's, most of the criminal activities are taken place using handheld arms particularly gun, pistol and revolver. Several surveys revealed that hand held gun is the foremost weapon used for diverse crimes like burglary, rape, etc. Therefore, automatic gun detection is a prime requirement in current scenario and this paper presents automatic gun detection from cluttered scene using Convolutional Neural Networks (CNN). We have used Deep Convolutional Network (DCN), a state-of-the-art Faster Region-based CNN model, through transfer learning, for automatic gun detection from cluttered scenes. We have evaluated our gun detection over Internet Movie Firearms Database (IMFDB), a benchmark gun database. For detecting the visual handheld gun, we got propitious performance of our system. Moreover, we demonstrate that, against the number of several training images, CNN model magnifies the classification accuracy, which is most advantageous in those practices where generous liberal is often not available.
Revisiting the PnP Problem: A Fast, General and Optimal Solution (2013)

In this paper, we revisit the classical perspective-n-point (PnP) problem, and propose the first non-iterative O(n) solution that is fast, generally applicable and globally optimal. Our basic idea is to formulate the PnP problem into a functional minimization problem and retrieve all its stationary points by using the Gr¨obner basis technique. The novelty lies in a non-unit quaternion representation to parameterize the rotation and a simple but elegant formulation of the PnP problem into an unconstrained optimization problem. Interestingly, the polynomial system arising from its first-order optimality condition assumes two-fold symmetry, a nice property that can be utilized to improve speed and numerical stability of a Gr¨obner basis solver. Experiment results have demonstrated that, in terms of accuracy, our proposed solution is definitely better than the state-ofthe- art O(n) methods, and even comparable with the reprojection error minimization method.
Investigations into the arc and spatter behaviour of pulsed MAG welding (1990)

Abstract The arc behaviour and losses due to weld spatter during pulsed MAG welding were investigated for each of three different types of pulsed current source. A discussion of the advantages and disadvantages of the pulsed arc technique when used with automatic welding systems is presented.
A Domain-Driven, Generative Data Model for Big Pet Store (2014)

Generating large amounts of semantically-rich data for testing big data workflows is paramount for scalable performance benchmarking and quality assurance in modern machine-learning and analytics workloads. The most obvious use case for such a generative algorithm is in conjunction with a big data application blueprint, which can be used by developers (to test their emerging big data solutions) as well as end users (as a starting point for validating infrastructure installations, building novel applications, and learning analytics methods). We present a new domain-driven, generative data model for Big Pet Store, a big data application blueprint for the Hadoop ecosystem included in the Apache Big Top distribution. We describe the model and demonstrate its ability to generate semantically-rich data at variable scale ranging from a single machine to a large cluster. We validate the model by using the generated data to answer questions about customer locations and purchasing habits for a fictional targeted advertising campaign, a common business use case.
<i>Candidatus Magnetobacterium</i> (2015)

Abstract Mag.ne'to.bac.te'ri.um. Gr. n. magnes magnet, comb. form magneto‐; Gr. n. bakterion a small rod; M.L. neut. n. Magnetobacterium a magnetic rod. Rod‐shaped, large, magnetic cells occurring in freshwater sediments. The original description is based on bacteria enriched from the littoral sediment of a freshwater lake in Southern Germany (Chiemsee); similar types of bacteria were also observed in sediments of other freshwater lakes and ponds in Southern Germany and Brazil. Counts of active bacteria in different vertical layers of Chiemsee sediment indicated that “ Candidatus M. bavaricum” is a typical gradient organism, particularly adapted to zones characterized by low levels of oxygen, where it reaches the highest abundance (Spring et al., 1993). A minor fraction of these bacteria was also found in the anoxic zone, whereas high concentrations of oxygen can apparently not be tolerated by this bacterium over longer periods of time. Type species : “ Candidatus Magnetobacterium bavaricum ” Spring, Amann, Ludwig, Schleifer, van Gemerden and Petersen 1993, 2398. Taxonomic and Nomenclature Notes According to the List of Prokaryotic names with Standing in Nomenclature (LPSN), the taxonomic status of the genus Candidatus Magnetobacterium is: synonym (and no standing) (last update, February 2025) * . LPSN classification: Bacteria / Pseudomonadati / Nitrospirota / Nitrospiria / Nitrospirales / Nitrospiraceae / Candidatus Magnetobacterium The genus Candidatus Magnetobacterium can also be recovered in the Genome Taxonomy Database (GTDB) as g__Magnetobacterium (version v220) ** . GTDB classification: d__Bacteria / p__Nitrospirota / c__Thermodesulfovibrionia / o__Thermodesulfovibrionales / f__Magnetobacteriaceae / g__Magnetobacterium * Meier‐Kolthoff et al. ( 2022 ). Nucleic Acids Res , 50 , D801 – D807 ; DOI: 10.1093/nar/gkab902 ** Parks et al. ( 2022 ). Nucleic Acids Res , 50 , D785 – D794 ; DOI: 10.1093/nar/gkab776
Preparation and properties of nickel borate acylate (2001)

The synthetic method for nickel borate acylate(NBA), a kind of rubber steel cord adhesion promoter, through nickelous carbonate borate and mixed carboxylic acids was studied, and many factors influencing the synthesis of NBA were investigated systematically. By detection and comparison with product 680?C from Manobond Company of England, the NBA synthesized through isooctanoic acid and tributyl borate is very similar with product 680?C in IR data, 300% fixed extension strength, tensile strength, hardness and cure curve, and is a little lower than product 680?C in tensile failure extensibility and hot air aging. The experimental results show that the prepared NBA can be used as rubber steel cord adhesion promoter. [
Unsupervised Bayesian Inference to Fuse Biosignal Sensory Estimates for Personalizing Care (2018)

The role of sensing technologies, such as wearables, in delivering precision care is becoming widely acceptable. Given the very large quantities of sensor data that rapidly accumulate, there is a need to employ automated algorithms to label biosignal sensor data. In many real-life clinical applications, no such expert labels are available, and algorithms for processing sensor data must be relied upon, without access to the "ground truth." It is therefore extremely difficult to choose which algorithms to trust or discard at any point in time, where different algorithms may be optimal for different patients, or even for different points in time for the same patient. We propose two fully Bayesian approaches for fusing labels from independent and potentially correlated annotators (i.e., algorithms or, where available, experts). These are generative models to aggregate labels (i.e., the outputs of the algorithms, such as identified ECG morphology) in an unsupervised manner, to estimate jointly the assumed bias and precision of each algorithm without access to the ground truth. The latter fused estimate may then be used to infer the underlying ground truth. For the first time in the biomedical context, we show that modeling correlations between annotators, and fusing information concerning task difficulty (such as the estimated quality of the sensor data), improve these estimates with respect to commonly employed strategies in the literature. Also, we adopt a strongly Bayesian approach to inference using Gibbs sampling to improve estimates over the existing state of the art. We present results from applying the proposed pair of models to simulated and two publicly available biomedical datasets, to demonstrate proof-of-principle. We show that our proposed models outperform all existing approaches recreated from the literature. We also show that the proposed methods are robust when dealing with missing values (as often occurs in real-life biomedical applications), and that they are suitably efficient for use in real-time applications, thereby providing the basis for the reliable use of sensors for personalizing the care of the individual.