gebhart/patrepeval huggingface dataset:
Highly Sensitive Active-Matrix Driven Self-Capacitive Fingerprint Sensor based on Oxide Thin Film Transistor (2019)

The fingerprint recognition has been widely used for biometrics in mobile devices. Existing fingerprint sensors have already been commercialized in the field of mobile devices using primarily Si-based technologies. Recently, mutual-capacitive fingerprint sensors have been developed to lower production costs and expand the range of application using thin-film technologies. However, since the mutual-capacitive method detects the change of mutual capacitance, it has high ratio of parasitic capacitance to ridge-to-valley capacitance, resulting in low sensitivity, compared to the self-capacitive method. In order to demonstrate the self-capacitive fingerprint sensor, a switching device such as a transistor should be integrated in each pixel, which reduces a complexity of electrode configuration and sensing circuits. The oxide thin-film transistor (TFT) can be a good candidate as a switching device for the self-capacitive fingerprint sensor. In this work, we report a systematic approach for self-capacitive fingerprint sensor integrating Al-InSnZnO TFTs with field-effect mobility higher than 30 cm<sup>2</sup>/Vs, which enable isolation between pixels, by employing industry-friendly process methods. The fingerprint sensors are designed to reduce parasitic resistance and capacitance in terms of the entire system. The excellent uniformity and low leakage current (<10<sup>-12</sup>) of the oxide TFTs allow successful capture of a fingerprint image.
Entangling atoms and ions in dissipative environments (2000)

Abstract Quantum information processing rests on our ability to manipulate quantum superpositions through coherent unitary transformations, and to establish entanglement between constituent quantum components of the processor. The quantum information processor (a linear ion trap, or a cavity confining the radiation field for example) exists in a dissipative environment. We discuss ways in which entanglement can be established within such dissipative environments. We can even make use of a strong interaction of the system with its environment to produce entanglement in a controlled way.
Epigenetic differences in monozygotic twins discordant for major depressive disorder (2016)

Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD.
The relationship between plasma beta-endorphin and the dimensions of the Chinese Cancer Pain Assessment Tool (CCPAT) (2002)

Purpose. The purpose of the study was to identify the relationship between plasma β-endorphin (objective variable) and the dimensions of the Chinese Cancer Pain Assessment Tool (CCPAT) (subjective variables). The dimensions included functional, pharmacological, psychosocial, pain beliefs and meanings, emotional and pain intensity. Methods. In this correlational study, 48 Chinese patients who had experienced cancer pain in the 24 hours before the investigation were recruited from an oncology unit by convenience. CCPAT scores and venous blood for β-endorphin were taken from each subject concurrently on two occasions, 8 a.m. and 8 p.m. Plasma β-endorphin was measured by radioimmunoassay. Results. Thirty-eight men and nine women were recruited. With the exception of 14 subjects who did not have the blood-taking procedure in the evening, all subjects completed the CCPAT and their blood was taken. Nineteen subjects suffered from gastrointestinal cancers, 17 from nasopharyngeal carcinoma, 9 from lung cancer and 2 from other types. Twenty-four of them did not have known metastasis. The mean age was 48.8 (SD 11.5). The mean β-endorphin levels for 8 a.m. and 8 p.m. were 42.55 pg/ml (SEM = 5.47) and 42.15 pg/ml (SEM = 5.80) respectively. There was no significant difference between the morning and the evening β-endorphin levels. The mean weighted scores for the functional, psychosocial, pharmacological, emotional, pain belief and meaning and intensity dimensions were 40.02, 13.85, 21.72, 25.37, 25.77, 62.17 and 2.35, respectively. A stepwise regression was done to examine the relationships among the β-endorphin levels and the scores of the six dimensions. The regression model was significant (p = 0.02). A cluster analysis was performed and the results supported the contention that a link may exit between the six dimensions and plasma β-endorphin levels. Conclusions. The importance of psychosocial, emotional and intensity factors in assessment of pain is re-affirmed by this study using β-endorphin as a biological benchmarker.
Mesoionic Carbenes in Low- to High-Valent Vanadium Chemistry (2021)

We report the synthesis of vanadium(V) oxo complex 1 with a pincer-type dianionic mesoionic carbene (MIC) ligand L1 and the general formula [VOCl(L1)]. A comparison of the structural (SC-XRD), electronic (UV–vis), and electrochemical (cyclic voltammetry) properties of 1 with the benzimidazolinylidene congener 2 (general formula [VOCl(L2)]) shows that the MIC is a stronger donor also for early transition metals with low d-electron population. Since electrochemical studies revealed both complexes to be reversibly reduced, the stronger donor character of MICs was not only demonstrated for the vanadium(V) but also for the vanadium(IV) oxidation state by isolating the reduced vanadium(IV) complexes [Co(Cp*)2][1] and [Co(Cp*)2][2] ([Co(Cp*)2] = decamethylcobaltocenium). The electronic structures of the compounds were investigated by computational methods. Complex 1 was found to be a moderate precursor for salt metathesis reactions, showing selective reactivity toward phenolates or secondary amides, but not toward primary amides and phosphides, thiophenols, or aryls/alkyls donors. Deoxygenation with electron-rich phosphines failed to give the desired vanadium(III) complex. However, treatment of the deprotonated ligand precursor with vanadium(III) trichloride resulted in the clean formation of the corresponding MIC vanadium(III) complex 6, which undergoes a clean two-electron oxidation with organic azides yielding the corresponding imido complexes. The reaction with TMS-N3 did not afford a nitrido complex, but instead the imido complex 10. This study reveals that, contrary to popular belief, MICs are capable of supporting early transition-metal complexes in a variety of oxidation states, thus making them promising candidates for the activation of small molecules and redox catalysis.
Ziele und Methoden (1981)

Soziale Normen bestimmen schlechthin das soziale Verhalten. Diese genuin “soziologische” These wird seit jeher mit beträchtlichem theoretischen und empirischen Forschungsaufwand gerechtfertigt. Dem Folgeproblem, der Erklärung des Entstehens sozialer Normen, wurde weitaus weniger Aufmerksamkeit gewidmet. Einen Lösungsansatz zu diesem Problem vorzulegen, ist Ziel dieser Untersuchung.
Nondestructive photon counting in waveguide QED (2020)

The authors propose to use arrays of multilevel atoms coupled to waveguides as photon detectors capable of resolving the number of photons. Both destructive and nondestructive detectors can be constructed in this way
ON THE STRUCTURE AND SOME PROPERTIES OF NYLON 66 COPOLYMERS (1976)

Nylon 66 copolymers were prepared by substitutions up to 50 mol%, of diacid comonomers: terephthalic acid (T), isophthalic acid (I) and 1, 2-diphenoxyethane-p, p′-dicarboxylic acid (B), and diamine comonomers: p-xylylenediamine (PXD), m-xylylenediamine (MXD), p-phenylenediamine (P), m-phenylenediamine (M), 4, 4′-diaminodiphenylmethane (C), 4, 4′-diaminodiphenylether (0), 4, 4′-diaminodiphenylsulfone (S) and piperazine (Pip). The amorphous samples of these copolymers were subjected to the following measurements: glass transition temperature (Tg) and cold crystallization temperature (Tcc) by DTA method, and density.Tg's of N66-6I and N66-MXD6 conform to Gibbs-Dimarzio's equation and Wood's equation, whereas Tg's and densities of p-phenylene type copolymers (N66-6T, N66-PXD6 and N66-P6) are higher than those of corresponding m-phenylene type copolymers (N66-6I, N66-MXD6 and N66-M6). Tg's and densities of pdiphenylenediamine type copolymers increase in the following order: N66-C6<N66-06<N66-S6. Tg's of N66-6B are lower than those of above p-diphenylenediamine type copolymers. Tg's of N66-Pip6 are lowest among the copolymers studied. (Tg-Tcc) of N66-6T and N66-PXD6 are lower than those of N66-6I, N66-MXD6, N610-6T and N610-6I, which suggests that N66-PXD6 is isomorphous. The isomorphism of N66-PXD6 is supported by the fact that the results of dynamic viscoelastic measurement are similar to those of isomorphous N66-6T.
Courts and justice in the era of HIV/AIDS (2000)

Click to increase image sizeClick to decrease image size Notes Justice of the High Court of Australia. Lately President of the International Commission of Jurists. One‐time Member of the World Health Organisation Global Commission on AIDS.
Impact of assessor disagreement on ranking performance (2012)

We consider the impact of inter-assessor disagreement on the maximum performance that a ranker can hope to achieve. We demonstrate that even if a ranker were to achieve perfect performance with respect to a given assessor, when evaluated with respect to a different assessor, the measured performance of the ranker decreases significantly. This decrease in performance may largely account for observed limits on the performance of learning-to-rank algorithms.
Incentive based spectrum pricing: practicalities (2007)

Non-discrimination – the spectrum charge should be calculated fairly, i.e. if two users are using the same amount of spectrum in the same way, both should pay the same charge.
Online extraction of lumen region and boundary from endoscopic images using a quad structure (1999)

A new approach for the automatic extraction of the lumen region and its boundary for the gastrointestinal (GI) endoscopic images is presented. At first, a quasi region of interest representing the darker regions of the image is segmented by using a region splitting scheme named progressive thresholding. Then the lumen region is obtained by using a region growing technique called integrated neighbourhood search (INS). A new quadstructure based technique is introduced to enhance the speed of INS significantly. A back projection algorithm is suggested to optimise the search for the pixels belonging to the lumen region and boundary. A boundary-thinning algorithm is also proposed to remove the redundant pixels from the lumen boundary and to generate a connected single pixel width boundary. The proposed approach does not need a priori knowledge about the image characteristics. The efficiency of this method in terms of speed and accuracy is validated by various GI images and the results of the experiments are presented. The main advantage of the proposed technique is its high-speed response that facilitates real time analysis of the endoscopic images.
Towards mold-free composites. A novel control method to cure carbon fiber through punctual force (2019)

Composites are vital to the aircraft industry for their reduced weight and excellent mechanical properties. Autoclave curing is used for primary structures, with void content below 1%, to obtain optimal mechanical properties. The drawbacks of this method are the need for a mold for each component, the limited size of the autoclave, and the long curing time. Therefore, a novel process to cure prepregs with a hot tool applying a localized force (punctual) is introduced. The aim is a process without molds, but initial research focuses on using a mold to support carbon fiber/epoxy resin prepregs (CFER) while the hot tool is driven with a Cartesian machine. However, variability in the mold surface and prepreg layup make it difficult to achieve a uniform force when the tool presses and slides over the CFER sample. Therefore, a model of the mold surface is obtained and a control method to simulate a caterpillar is implemented to compensate the surface variability. The control method is tested with CFER prepegs at a force range of 3N-12N and temperature range of 175°C-225°C. The cured samples undergo t-peeling test to obtain a degree of bonding between the prepreg layers. The t-peeling results tests showed a reduction of 12.5% in the required curing temperature due to uniform pressure when using the caterpillar method. Additionally, there is a lack of fiber dislocation with the caterpillar method.
A framework for enhancing industrial soft sensor learning models (2023)

Refinery industrial processes are very complex with nonlinear dynamics resulting from varying feedstock characteristics and also from changes in product prioritization. Along these processes, there are key properties of intermediate compounds that must be monitored and controlled since they directly affect the quality of the end products commercialized by these manufacturers. However, most of these properties can only be measured through time-consuming and expensive laboratory analysis, which is impossible to obtain in high frequencies, as required to properly monitor them. In this sense, developing soft sensors is the most common way to obtain high-frequency estimations for these measurements, helping advanced control systems to establish the correct setpoints for temperatures, pressures, and other sensors along the refining process, controlling the quality of end products. Since the amount of labeled data is scarce, most academic research has focused on employing semi- supervised learning strategies to develop machine learning (ML) models as soft sensors. Our research, on the other hand, goes in another direction. We aim to elaborate a framework that leverages the knowledge of domain experts and employs data augmentation techniques to build an enhanced fully labeled dataset that could be fed to any supervised ML algorithm to generate a quality soft sensor. We applied our framework together with Automated ML to train a model capable of predicting a specific key property associated with the produc- tion of Naphtha compounds in a refinery: the ASTM 95% distillation temperature of the Heavy Naphtha. Although our framework is model agnostic, we opted by using Automated ML for the optimization strategy, since it applies a diverse set of models to the dataset, reducing the bias of utilizing a single optimization algorithm. We evaluated the proposed framework on a case study carried out in an industrial refinery in Brazil, where the previous model in production for estimating the ASTM 95% distillation temperature of the Heavy Naphtha was based entirely on the physicochemical knowledge of the process. By adopting our framework with Automated ML, we were capable of improving the R2 score by 120%. The resulting ML model is currently operating in real-time inside the refinery, leading to significant economic gains.
Effect of Temperature on the Layered Structure of Hydrotalcite-like Mg and Al Layered Double Hydroxides by Means of in situ High Temperature Powder X-ray Diffraction. (1998)

Mg/Al-layered double hydroxide with interlayer carbonate (Mg/Al/CO3-LDH) is synthesized with atomic ratio Mg/Al=2, 3 or 4. In situ high temperature powder X-ray diffraction (in situ HTXRD) patterns of Mg/Al/CO3-LDH reveal that the solid phase having hydrotalcite-like layered structure (Phase I) is unstable when the temperature of the solid sample is elevated. Immediately after Phase I disappears, another solid phase (Phase II) grows and becomes predominant. In the direction of c-axis, Phase II has the basal spacing d=0.659 nm which is smaller than that of Phase I. Mixed solids of MgO and a spinel (MgAl2O4) are observed after Phase II degrades. Two endothermic peaks both of which are associated with weight loss appear below 400° in the result of differential thermal analysis/thermal gravimetry (DTA/TG). Phase II is formed at the endotherm of lower temperature and degrades at that of higher temperature. Phase II is unstable at room temperature and transits to an amorphous phase slowly after days of storage in a dry condition. It is observed that a very small part of this amorphous phase transits to Phase I in the same dry condition. Solid state chemistry of the synthetic Mg/Al/CO3-LDH is investigated by means of in situ HTXRD, DTA/TG and X-ray photoelectron spectroscopy (XPS).
Three-dimensional Imaging in Confocal Fluorescent Microscopy with Annular Lenses (1991)

Abstract Three-dimensional imaging properties in confocal fluorescent microscope systems with annular lenses are investigated in terms of the three-dimensional optical transfer function (OTF). Starting from the OTF, we also consider the optical sectioning property. The dependence of the OTF and the optical sectioning strength on the radius of the central obstruction of the lens is revealed. For the case of a finite-sized circular pinhole in front of the detector, both the OTF and the optical sectioning strength, together with the signal level, are calculated as a function of the radius of the pinhole. Investigations show that for a given finite size of the pinhole, the optical sectioning strength can be increased by altering the radius of the central obstruction of the lens to an optimum value, and that a higher signal level may be maintained by using an annular objective only.
A Sparse Coding Multi-Scale Precise-Timing Machine Learning Algorithm\n for Neuromorphic Event-Based Sensors (2018)

This paper introduces an unsupervised compact architecture that can extract\nfeatures and classify the contents of dynamic scenes from the temporal output\nof a neuromorphic asynchronous event-based camera. Event-based cameras are\nclock-less sensors where each pixel asynchronously reports intensity changes\nencoded in time at the microsecond precision. While this technology is gaining\nmore attention, there is still a lack of methodology and understanding of their\ntemporal properties. This paper introduces an unsupervised time-oriented\nevent-based machine learning algorithm building on the concept of hierarchy of\ntemporal descriptors called time surfaces. In this work we show that the use of\nsparse coding allows for a very compact yet efficient time-based machine\nlearning that lowers both the computational cost and memory need. We show that\nwe can represent visual scene temporal dynamics with a finite set of elementary\ntime surfaces while providing similar recognition rates as an uncompressed\nversion by storing the most representative time surfaces using clustering\ntechniques. Experiments will illustrate the main optimizations and trade-offs\nto consider when implementing the method for online continuous vs. offline\nlearning. We report results on the same previously published 36 class character\nrecognition task and a 4 class canonical dynamic card pip task, achieving 100%\naccuracy on each.\n
Effect of network connectivity on behavior of synthetic Broborg hillfort glasses (2022)

Abstract There is wide industrial interest in developing robust models of long‐term (&gt;100 years) glass durability. Archeological glass analogs, glasses of similar composition, and alteration conditions to those being tested for durability can be used to evaluate and inform such models. Two such analog glasses from a 1500‐year‐old vitrified hillfort near Uppsala, Sweden have previously been identified as potential analogs for low concentration Fe‐bearing aluminosilicate nuclear waste glasses. However, open questions remain regarding the melting environment from which these historic glasses were formed and the effect of these conditions on their chemical durability. A key factor to answering the previous melting and durability questions is the redox state of Fe in the starting and final materials. Past work has shown that the melting conditions of a glass‐forming melt may influence the redox ratio value (Fe +3 /∑Fe), a measure of a glass's redox state, and both melting conditions and the redox ratio may influence the glass alteration behavior. Synthetic analogs of the hillfort glasses have been produced using either fully oxidized or reduced Fe precursors to address this question. In this study, the melting behavior, glass transition temperature, oxidation state, network structure, and chemical durability of these synthesized glass analogs is presented. Resulting data suggests that the degree of network connectivity as impacted by the oxidation state of iron impacted the behavior of the glass‐forming melt but in this case does not affect the chemical durability of the final glass. Glasses with a lower degree of melt connectivity were found to have a lower viscosity, resulting in a lower glass transition temperature and softening temperature, as well as in a lower temperature of foam onset and temperature of foam maximum. This lower degree of network connectivity most likely played a more significant role in accelerating the conversion of batch chemicals into glass than the presence of water vapor in the furnace's atmosphere. Future work will focus on using the results from this work with outcomes from other aspects of this project to evaluate long‐term glass alteration models.