gebhart/patrepeval huggingface dataset:
Development of a Gray-Level Co-Occurrence Matrix-Based Texture Orientation Estimation Method and Its Application in Sea Surface Wind Direction Retrieval From SAR Imagery (2018)

A gray-level co-occurrence matrix (GLCM)-based method was developed for better texture orientation estimation in remote sensing imagery. A GLCM is essentially the joint probability distribution of gray levels at the position pairs satisfying a specific relative position within an image. We first found that when the relative position is aligned with texture orientation, larger elements of the corresponding GLCM are concentrated diagonally. Then, we developed a new texture orientation estimation method. The method uses the GLCMs of relative positions equally spaced in orientation and distance, and three schemes of these GLCMs are calculated. A GLCM-derived parameter is then defined to quantitatively measure the degree of diagonal concentration of the GLCM elements, and its integral over the variable of relative distance is selected as an indicator to find the dominant texture orientation(s). For testing, we applied the method to 44 selected images containing one or multiple aligned textures. The results show that the method is in good agreement with visual inspections from 45 randomly selected people, and is insensitive to large typical noises and illumination change. In addition, using (any) one GLCM calculation scheme over the others does not significantly affect the results. Finally, the method was applied to sea surface wind direction (SSWD) retrieval from 89 synthetic aperture radar images. In the application test, the developed method achieves better SSWD retrieval accuracy than do the commonly used Fourier transform- and gradient-based methods by 8.13° and 16.09° against the European Centre for Medium-Range Weather Forecast ERA-Interim reanalysis data and 10.21° and 17.31° against the cross-calibrated multiplatform data.
Artificial neural network application of modeling failure rate for Boeing 737 tires (2010)

Abstract This paper presents an application of artificial neural network (ANN) technique for conducting the reliability analysis of Boeing 737 tires. For this purpose, an ANN model utilizing the feed‐forward back‐propagation algorithm as a learning rule is developed. The inputs to the neural network are the flight operational time and the number of landings as independent variables and the output is the failure rate of the tires. Two years of data are used for failure rate prediction model and validation. Model validation, which reflects the suitability of the model for future predictions, is performed by comparing the predictions of the model with that of Weibull regression model. The results show that the failure rate predicted by the ANN is closer in agreement with the actual data than the failure rate predicted by the Weibull model. The present work also identifies some of the common tire failures and presents representative results based on the established model for the most frequently occurring tire failure. Copyright © 2010 John Wiley &amp; Sons, Ltd.
Optimization and Characterization of the Friction Stir Welded Sheets of AA 5754-H111: Monitoring of the Quality of Joints with Thermographic Techniques (2017)

Friction Stir Welding (FSW) is a solid-state welding process, based on frictional and stirring phenomena, that offers many advantages with respect to the traditional welding methods. However, several parameters can affect the quality of the produced joints. In this work, an experimental approach has been used for studying and optimizing the FSW process, applied on 5754-H111 aluminum plates. In particular, the thermal behavior of the material during the process has been investigated and two thermal indexes, the maximum temperature and the heating rate of the material, correlated to the frictional power input, were investigated for different process parameters (the travel and rotation tool speeds) configurations. Moreover, other techniques (micrographs, macrographs and destructive tensile tests) were carried out for supporting in a quantitative way the analysis of the quality of welded joints. The potential of thermographic technique has been demonstrated both for monitoring the FSW process and for predicting the quality of joints in terms of tensile strength.
Low-k dielectric reliability: impact of test structure choice, copper and integrated dielectric quality (2008)

As dielectric spacing between adjacent copper wires scales below 50nm, back-end-of-line dielectric reliability is becoming an increasingly important challenge both for advanced logic and memory devices. It is crucial to understand which physical mechanisms are relevant, because this has an impact on modeling and prediction. In this contribution test methods, test structures and physical mechanisms are discussed.
The benefit of planned dialysis to early survival on hemodialysis versus peritoneal dialysis: a nationwide prospective multicenter study in Korea (2023)

Optimal preparation is recommended for patients with advanced chronic kidney disease to minimize complications during dialysis initiation. This study evaluated the effects of planned dialysis initiation on survival in patients undergoing incident hemodialysis and peritoneal dialysis. Patients newly diagnosed with end-stage kidney disease who started dialysis were enrolled in a multicenter prospective cohort study in Korea. Planned dialysis was defined as dialysis therapy initiated with permanent access and maintenance of the initial dialysis modality. A total of 2892 patients were followed up for a mean duration of 71.9 ± 36.7 months and 1280 (44.3%) patients initiated planned dialysis. The planned dialysis group showed lower mortality than the unplanned dialysis group during the 1st and 2nd years after dialysis initiation (1st year: adjusted hazard ratio [aHR] 0.51; 95% confidence interval [CI] 0.37-0.72; P < 0.001; 2nd year: aHR 0.71; 95% CI 0.52-0.98, P = 0.037). However, 2 years after dialysis initiation, mortality did not differ between the groups. Planned dialysis showed a better early survival rate in hemodialysis patients, but not in peritoneal dialysis patients. Particularly, infection-related mortality was reduced only in patients undergoing hemodialysis with planned dialysis initiation. Planned dialysis has survival benefits over unplanned dialysis in the first 2 years after dialysis initiation, especially in patients undergoing hemodialysis. It improved infection-related mortality during the early dialysis period.
Cascaded Model Predictive Control of Three-Level NPC Back-to-Back Power Converter PMSG Wind Turbine Systems (2018)

Permanent magnet synchronous generator (PMSG) direct drive structure has a wide range of applications in high-power wind energy conversion systems. Considering this type of topology, model predictive control (MPC) has shown to be an promising control strategy. However, the cumbersome process of tuning weighting factors and the weak parameter robustness are the main drawbacks. In this work, a new control structure, as so called cascaded model predictive control is proposed. It avoids using weighting factors and has stronger parameter robustness. The proposed control strategies are validated and compared with the conventional MPC in Simulink simulation.
A Screening Assay for the Tetrachlorodibenzo-p-dioxin Receptor using the [125I]iodovaleramide Derivative of Trichlorodibenzo-p-dioxin as the Binding Ligand (1984)

A relatively simple assay method for the putative cytosolic 'receptor' that binds 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and related compounds is described. The assay is based on specific binding of [125I]dioxin to cytosol 'receptor' protein. Saturation is ensured by competition experiments in which unlabeled TCDD and other competitors displace the radiolabeled ligand from specific binding sites. This assay has been applied to estimation of levels of 'receptor' in cytosol.
Overview and Results: CL-SciSumm Shared Task 2019 (2019)

The CL-SciSumm Shared Task is the first medium-scale shared task on scientific document summarization in the computational linguistics~(CL) domain. In 2019, it comprised three tasks: (1A) identifying relationships between citing documents and the referred document, (1B) classifying the discourse facets, and (2) generating the abstractive summary. The dataset comprised 40 annotated sets of citing and reference papers of the CL-SciSumm 2018 corpus and 1000 more from the SciSummNet dataset. All papers are from the open access research papers in the CL domain. This overview describes the participation and the official results of the CL-SciSumm 2019 Shared Task, organized as a part of the 42nd Annual Conference of the Special Interest Group in Information Retrieval (SIGIR), held in Paris, France in July 2019. We compare the participating systems in terms of two evaluation metrics and discuss the use of ROUGE as an evaluation metric. The annotated dataset used for this shared task and the scripts used for evaluation can be accessed and used by the community at: https://github.com/WING-NUS/scisumm-corpus.
Unique Signal mathematical analysis task group FY03 status report. (2003)

The Unique Signal is a key constituent of Enhanced Nuclear Detonation Safety (ENDS). Although the Unique Signal approach is well prescribed and mathematically assured, there are numerous unsolved mathematical problems that could help assess the risk of deviations from the ideal approach. Some of the mathematics-based results shown in this report are: 1. The risk that two patterns with poor characteristics (easily generated by inadvertent processes) could be combined through exclusive-or mixing to generate an actual Unique Signal pattern has been investigated and found to be minimal (not significant when compared to the incompatibility metric of actual Unique Signal patterns used in nuclear weapons). 2. The risk of generating actual Unique Signal patterns with linear feedback shift registers is minimal, but the patterns in use are not as invulnerable to inadvertent generation by dependent processes as previously thought. 3. New methods of testing pair-wise incompatibility threats have resulted in no significant problems found for the set of Unique Signal patterns currently used. Any new patterns introduced would have to be carefully assessed for compatibility with existing patterns, since some new patterns under consideration were found to be deficient when associated with other patterns in use. 4. Markov models were shown to correspond to some of the engineered properties of Unique Signal sequences. This gives new support for the original design objectives. 5. Potential dependence among events (caused by a variety of communication protocols) has been studied. New evidence has been derived of the risk associated with combined communication of multiple events, and of the improvement in abnormal-environment safety that can be achieved through separate-event communication.
Abstract 1932: Pollock: Fishing for cell states (2022)

Abstract The use of single-cell methods is expanding at an ever-increasing rate. While multiple algorithms address the task of cell classification, they are limited in terms of cross platform compatibility, reliance on the availability of a reference dataset, and classification interpretability. Here, we introduce Pollock, a suite of algorithms for cell type identification that is compatible with popular single cell methods and analysis platforms, provides a series of pretrained human cancer reference models, and reports interpretability scores that identify the genes that drive cell type classifications. Our model combines two important approaches, one each from machine learning and deep learning: a variational autoencoder (VAE) and random forest classifier, to make cell type predictions. Pollock is highly versatile, being available as a command line tool, Python library (with scanpy integration), or R library (with Seurat integration), and can be installed as a conda package, or in containerized form via Docker. To allow for easier pan-disease and pan-tissue analyses, Pollock also ships with a library of pretrained cancer type specific and agnostic modules that were trained on expertly-curated single cell data that are ready to “plug and play” with no additional annotation or training required. Conversely, Pollock also allows for the training of custom classification modules, if an annotated reference single cell dataset is available. These pretrained models were fitted on manually curated and annotated single cell data from eight different cancer types spanning three single cell technologies (scRNA-seq, snRNA-seq, and snATAC-seq). Pollock also provides feature importance scores that allow for cell type classifications to be traced back to the genes influencing a particular cell type classification, further promoting biological interpretability. These scores could allow for new, technology-specific biomarker discovery. We also demonstrate the utility of Pollock by applying it in a pan-cancer single cell immune analysis. Citation Format: Erik Storrs, Daniel Cui Zhou, Michael C. Wendl, Matthew A. Wyczalkowski, Alla Karpova, Liang-Bo Wang, Yize Li, Austin Southard-Smith, Reyka G. Jayasinghe, Lijun Yao, Ruiyang Liu, Yige Wu, Nadezhda V. Terekhanova, Houxiang Zhu, John M. Herndon, Feng Chen, William E. Gillanders, Ryan C. Fields, Li Ding. Pollock: Fishing for cell states [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1932.
Impact of body mass index on clinicopathologic outcome and biochemical recurrence after radical prostatectomy in 1,257 Japanese patients with prostate cancer. (2013)

176 Background: To determine the impact of body mass index (BMI) on the clinicopathological characteristics and biochemical recurrence of prostate cancer (PCa) after radical prostatectomy (RP) in Japanese men. Methods: The medical records of 1,257 men with PCa treated by radical prostatectomy without neoadjuvant therapy at four medical centers between 2001 and 2009 were retrospectively reviewed. Patients were categorized into four groups using the WHO BMI classification and recommended BMI quartiles. Associations of the various BMI categories with clinicopathological characteristics and biochemical recurrences were statistically evaluated. Biochemical recurrence was defined as a prostate specific antigen (PSA) level of &gt;0.2 ng/ml. Results: Of the 1,257 patients, 230 (18.1%) experienced biochemical recurrence during the median follow-up period of 49 months. The median BMI was 23.8 kg/m 2 , and 1.4% patients were underweight, 65.4% were of normal weight, 30.9% were overweight, and 2.4% were obese (WHO classification). Preoperative PSA levels and PSA density (PSAD) were significantly higher in the underweight group than in the other groups. Pathological characteristics did not differ significantly among BMI categories. As per the WHO classification and quartile categories, biochemical recurrence rate was comparable among the BMI groups. After adjusting for other pre- and perioperative covariables, multivariate Cox proportional hazards analysis revealed that a high BMI did not have an independent impact on biochemical recurrence-free survival. Conclusions: Underweight Japanese PCa patients who underwent radical prostatectomy had higher preoperative PSA levels and PSAD. However, high BMI was not associated with increased biochemical recurrence rate.
Rapid method for detecting monoclonality in B cell lymphoma in lymph node aspirates using the polymerase chain reaction. (1992)

Detection of monoclonality in a cell population is strongly suggestive of malignant disease. The simple PCR method presented here should complement conventional cytological and immunological methods for diagnosis of malignancy by lymph node aspirates.
Different Amino Acid Replacements in CAAX-Tetrapeptide Based Peptidomimetic Farnesyltransferase Inhibitors (1999)

In a series of CAAX-tetrapeptide based farnesyltransferase inhibitors it has been shown that the central AA-dipeptide can be replaced by tranexamic acid, 4-aminobenzenesulfonic acid, and 3-amino-N-(2,3-dimethylphenyl)benzenesulfonamide, respectively, yielding inhibitors active in the low micromolar range. Lipophilic derivatives of these compounds showed moderate anti-proliferative activity against different tumor cell lines. A promising class of peptidomimetic farnesyltransferase inhibitors was discovered through the replacement of the terminal AAX motif of the CAAX-tetrapeptide by 2-acylamino-5-aminobenzophenones.
16.2 A Keccak-based wireless authentication tag with per-query key update and power-glitch attack countermeasures (2016)

Counterfeiting is a major problem plaguing global supply chains. While small low-cost tagging solutions for supply-chain management exist, security in the face of fault-injection [1] and side-channel attacks [2] remains a concern. Power glitch attacks [3] in particular attempt to leak key-bits by inducing fault conditions during cryptographic operation through the use of over-voltage and under-voltage conditions. This paper presents the design of a secure authentication tag with wireless power and data delivery optimized for compact size and near-field applications. Power-glitch attacks are mitigated through state backup on FeRAM based non-volatile flip-flops (NVDFFs) [4]. The tag uses Keccak [5] (the cryptographic core of SHA3) to update the key before each protocol invocation, limiting side-channel leakage to a single trace per key.
Study of the Surface Laplacian SNR (2005)

The surface Laplacian involves the second derivative of the potential. It will give different and perhaps more localized information concerning the sources that give rise to the surface potential distribution. In this article we study the SNR of the surface Laplacian, and figure out the measuring possibility of the surface Laplacian of some bioelectrical signals that never been mentioned by others.
Comparison of Hydraulic and Hemolytic Properties of Different Impeller Designs of an Implantable Rotary Blood Pump by Computational Fluid Dynamics (2004)

A mixed-flow blood pump for long-term applications has been developed at the Helmholtz-Institute in Aachen, Germany. Central features of this implantable pump are a centrally integrated motor, a blood-immersed mechanical bearing, magnetic coupling of the impeller, and a shrouded impeller, which allows a relatively wide clearance. The aim of the study was a numerical analysis of hydraulic and hemolytic properties of different impeller design configurations. In vitro testing and numerical simulation techniques (computational fluid dynamics [CFD]) were applied to achieve a comprehensive overview. Pressure-flow charts were experimentally measured in a mock loop in order to validate the CFD data. In vitro hemolysis tests were performed at the main operating point of each impeller design. General flow patterns, pressure-flow charts, secondary flow rates, torque, and axial forces on the impeller were calculated by means of CFD. Furthermore, based on streak line techniques, shear stress (stress loading), exposure times, and volume percentage with critical stress loading have been determined. Comparison of CFD data with pressure head measurements showed excel-lent agreement. Also, impressive trend conformity was observed between in-vitro hemolysis results and numerical data. Comparison of design variations yielded clear trends and results. Design C revealed the best hydraulic and hemolytic properties and was chosen as the final design for the mixed-flow rotary blood pump.
Regulation of Cancer Cell Growth by Inflammatory Products (2020)

The concept that cancer may be an aberrant form of the physiological process of inflammation and wound repair was put forth by T. Hunter in 1694. The importance of products of inflammatory cells in regulating tumor cell growth comes primarily in a parallel manner from studies of both tumor immunology and cancer carcinogenesis. Studies of tumor immunologists have long suggested that immune cells may paradoxically stimulate tumor cell growth. Based on these data, the concept of immunostimulation of neoplastic growth was cogently put forth by Prehn in 1977. The importance of MO in repair of injuries has long been known. In 1977, S. J. Leibovich and A. Ross demonstrated that ablation of macrophages by systemic hydrocortisone combined with topical antimacrophage serum slowed the wound healing response. The role of macrophages in stimulating or inhibiting tumor cell growth has been extensively documented in vitro and in vivo.
Cloning and promoter analysis of the cotton lipid transfer protein gene Ltp3(1). (2000)

A cotton Ltp3 gene and its 5' and 3' flanking regions have been cloned with a PCR-based genomic DNA walking method. The amplified 2.6 kb DNA fragment contains sequences corresponding to GH3 cDNA which has been shown to encode a lipid transfer protein (LTP3). The gene has an intron of 80 bp which is located in the region corresponding to the C-terminus of LTP3. The Ltp3 promoter was systematically analyzed in transgenic tobacco plants by employing the Escherichia coli beta-glucuronidase gene (GUS) as a reporter. The results of histochemical and fluorogenic GUS assays indicate that the 5' flanking region of the Ltp3 gene contains cis-elements conferring the trichome specific activity of Ltp3 promoter.
Technology Enhanced Learning Using Humanoid Robots (2021)

In this paper we present a mixture of technologies tailored for e-learning related to the Deep Learning, Sentiment Analysis, and Semantic Web domains, which we have employed to show four different use cases that we have validated in the field of Human-Robot Interaction. The approach has been designed using Zora, a humanoid robot that can be easily extended with new software behaviors. The goal is to make the robot able to engage users through natural language for different tasks. Using our software the robot can (i) talk to the user and understand their sentiments through a dedicated Semantic Sentiment Analysis engine; (ii) answer to open-dialog natural language utterances by means of a Generative Conversational Agent; (iii) perform action commands leveraging a defined Robot Action ontology and open-dialog natural language utterances; and (iv) detect which objects the user is handing by using convolutional neural networks trained on a huge collection of annotated objects. Each module can be extended with more data and information and the overall architectural design is general, flexible, and scalable and can be expanded with other components, thus enriching the interaction with the human. Different applications within the e-learning domains are foreseen: The robot can either be a trainer and autonomously perform physical actions (e.g., in rehabilitation centers) or it can interact with the users (performing simple tests or even identifying emotions) according to the program developed by the teachers.