gebhart/patrepeval huggingface dataset:
Qualitative Test for Carbohydrate Material (1946)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTQualitative Test for Carbohydrate MaterialRoman DreywoodCite this: Ind. Eng. Chem. Anal. Ed. 1946, 18, 8, 499Publication Date (Print):August 1, 1946Publication History Published online1 May 2002Published inissue 1 August 1946https://pubs.acs.org/doi/10.1021/i560156a015https://doi.org/10.1021/i560156a015research-articleACS PublicationsRequest reuse permissionsArticle Views2958Altmetric-Citations541LEARN 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 options Get e-Alerts
InGaN/GaN Quantum Well Microcavities Formed by Laser Lift-Off and Plasma Etching (2001)

Photoluminescence measurements have been used to investigate InGaN/GaN quantum well microcavities formed between two dielectric Bragg reflectors. Both single and ten-period quantum wells emitting near 420 nm were studied. The structures were formed using a combination of MOCVD growth for the nitride layers, laser lift-off to remove the sapphire substrates and electron-beam evaporation to deposit the mirrors. Room temperature photoluminescence measurements have been used to investigate the cavity modes observed from both plasma etched and unetched microcavities, and half widths as low as 0.6 meV were observed. The cavity modes were visible as dips in measured reflectance spectra and as peaks in the PL. Comparison of the mode wavelengths with simulated reflectivity spectra has allowed the determination of the cavity thickness before and after etching; this has shown the etch-back step to have a degree of control (±5%) necessary for the later fabrication of resonant periodic gain structures.
Real-time Hand Tracking based on Skin-colored Model (2014)

Currently, hand tracking technologies are getting more attentions because it might become a better paradigm of human-machine interaction. In this report, we would firstly show some applications based on these technologies. Then, potential challenges in face of hand tracking would be discussed. Next, specific research aim and objects in this project would be listed. After that, how this report organized would be described. Additionally, we would review other researcher’s work in terms of skin-colored based hand tracking models. Specifically, corresponding research topics would include color space, skin-colored region classifiers, shape models and related tracking algorithms. Moreover, proposed method would encompasses a set of technologies mentioned in the background research, and these employed methods and technologies would be described in detail in corresponding chapter. Meanwhile, a prototype hand tracking system based on the proposed methods has been implemented, and acceptable detecting and tracking results have been obtained. On top of that, we would explain the pipeline of evaluation, which includes testing data collection and ROC (Receiver operating characteristics) analysis for detector and tracker respectively. Lastly, current progress and following work would be presented, and a Ganttchart was drawn to monitor the status of the project. Chapter
Convolutional neural networks: an illustration in TensorFlow (2016)

column Share on Convolutional neural networks: an illustration in TensorFlow Author: Abhineet Saxena Guru Gobind Singh Indraprastha University, New Delhi, India Guru Gobind Singh Indraprastha University, New Delhi, IndiaView Profile Authors Info & Claims XRDS: Crossroads, The ACM Magazine for StudentsVolume 22Issue 4Summer 2016 pp 56–58https://doi.org/10.1145/2951024Published:13 June 2016Publication History 17citation1,577DownloadsMetricsTotal Citations17Total Downloads1,577Last 12 Months97Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Spatio-Temporal Tensor Decomposition of a Polyaffine Motion Model for a Better Analysis of Pathological Left Ventricular Dynamics (2015)

Given that heart disease can cause abnormal motion dynamics over the cardiac cycle, understanding and quantifying cardiac motion can provide insight for clinicians to aid with diagnosis, therapy planning, and determining prognosis. The goal of this paper is to extract population-specific motion patterns from 3D displacements in order to identify the mean motion in a population, and to describe pathology-specific motion patterns in terms of the spatial and temporal components. Since there are common motion patterns observed in patients with the same condition, extracting these can lead towards a better understanding of the disease. Quantifying cardiac motion at a population level is not a simple task since images can vary widely in terms of image quality, size, resolution, and pose. To overcome this, we analyze the parameters obtained from a cardiac-specific Polyaffine motion-tracking algorithm, which are aligned both spatially and temporally to a common reference space. Once all parameters are aligned, different subjects can be compared and analyzed in the space of Polyaffine transformations by projecting the transformations to a reduced order subspace in which dominant motion patterns in each population can be extracted. Using tensor decomposition, the spatial and temporal aspects can be decoupled in order to study the components individually. The proposed method was validated on healthy volunteers and Tetralogy of Fallot patients according to known spatial and temporal behavior for each population. A key advantage of this method is the ability to regenerate motion sequences from the models, which can be visualized in terms of the full motion.
Right Ventricular Dysfunction is an Independent Predictor for Mortality in ST-Elevation Myocardial Infarction Patients Presenting with Cardiogenic Shock on Admission (2010)

In STEMI patients presenting with CS on admission and treated with primary PCI, RV dysfunction as assessed by echocardiography is an independent predictor for long-term mortality.
α2-3 Sialic acid binding and uptake by human monocyte-derived dendritic cells alters metabolism and cytokine release and initiates tolerizing T cell programming (2021)

Summary Dendritic cells (DCs) are key in the initiation of the adaptive T cell responses to tailor adequate immunity that corresponds to the type of pathogen encountered. Oppositely, DCs control the resolution phase of inflammation and are able to induce tolerance after receiving anti-inflammatory cytokines or upon encounter of self-associated molecular patterns, such as α2-3 linked sialic acid (α2-3sia). Objective: We here investigated whether α2-3sia, that bind immune inhibitory Siglec receptors, would alter signaling and reprogramming of LPS-stimulated human monocyte-derived DCs (moDCs). Methods and Results: Transcriptomic analysis of moDCs stimulated with α2-3sia-conjugated dendrimers revealed differentially expressed genes related to metabolic pathways, cytokines, and T cell differentiation. An increase in genes involved in ATPase regulator activity, oxidoreductase activity, and glycogen metabolic processes was detected. Metabolic extracellular flux analysis confirmed a more energetic moDC phenotype upon α2-3sia binding as evidenced by an increase in both glycolysis and mitochondrial oxidative phosphorylation. TH1 differentiation promoting genes IFNL and IL27, were significantly downregulated in the presence of α2-3sia. Functional assays confirmed that α2-3sia binding to moDCs induced phosphorylation of Siglec-9, reduced production of inflammatory cytokines IL-12 and IL-6, and increased IL-10. Surprisingly, α2-3sia-differentiated moDCs promoted FoxP3+CD25+/-CD127- regulatory T cell differentiation and decreased FoxP3-CD25-CD127- effector T cell proliferation. Conclusions: In conclusion, we demonstrate that α2-3sia binding to moDCs, phosphorylates Siglec-9, alters metabolic pathways, cytokine signaling, and T cell differentiation processes in moDCs and promotes regulatory T cells. The sialic acid-Siglec axis on DCs is therefore, a novel target to induce tolerance and to explore for immunotherapeutic interventions aimed to restore inflammatory processes.
Learning Individual Moving Preference and Social Interaction for Location Prediction (2018)

Location prediction has attracted increasing attention in diverse fields due to its wide applications, such as traffic planning and control, weather forecasting, homeland security, and travel recommendation. Many existing algorithms forecast a user's next location by learning that user's past moving patterns. However, the individual moving patterns in many practical applications (e.g., the moving trajectory of a taxi driver) tend to be random, which poses a big challenge for location prediction. In this paper, we propose a new robust location prediction model that considers both individual preferences and social interactions (PSI) at a group level to alleviate the effect of randomness and improve the location prediction performance. Specifically, we first extract hot places of interesting (POIs) and normal POIs, respectively, via a two-stage clustering approach. To characterize exterior social interactions, an associated group is identified, and an outline of group moving patterns is then extracted based on association rule mining. Finally, the next location is predicted by learning the individual's regular patterns and group moving patterns via a pair-wise ridge regression. In contrast to the traditional approaches, our proposed algorithm has several desirable characteristics: 1) PSI provides an intuitive and quantitative way to model human movement from two aspects: the individual's internal moving preferences and group-level exterior social interactions; 2) Building upon group-level pattern mining, PSI provides a more robust prediction model by learning both individual and group trend information simultaneously, alleviating the randomness of location prediction from individual historical trajectory data only; and 3) The experimental results demonstrate that PSI achieves a better prediction performance compared to the state-of-the-art methods.
Effect of Passive Horizontal Rotations and Vertical Oscillations on Dynamic Visual Acuity (2010)

Astronauts experience sensorimotor disturbances after long duration space flight. These crewmembers may need to egress the vehicle within a few minutes for safety and operational reasons in various sea state conditions following a water landing. Exposure to even low frequency motions induced by sea conditions surrounding a vessel can cause significant fine and gross motor control problems affecting critical functions. The objective of this study was to document human motor and visual performance during simulated wave motion in the 0.1 to 2.0 Hz range. We examined in 12 healthy subjects the changes in accuracy when performing a seated visual target acquisition task in which the location of target was offset vertically during horizontal full body rotation at an oscillating frequency of 0.8 Hz (peak velocity of 160 deg/s). The main finding was that the accuracy of performance degraded in 7 of 12 subjects when acquiring vertical targets at perturbing frequencies of 0.8 Hz in the horizontal plane by one step size. We also examined in a separate study on 12 healthy subjects seated dynamic visual acuity (DVA) task performance during vertical full body oscillations at perturbing frequencies of 2 Hz (peak to peak motion of 5 cm). The main finding was that DVA was significantly reduced when acquiring targets at perturbing oscillations at frequencies of 2 Hz in the vertical plane by approximately 1 chart line. Thus low frequencies of perturbations in the horizontal and vertical planes can cause decrement in visual performance.
Electron spin control in dilute nitride semiconductors (2009)

We report on a study of spin-dependent recombination processes (SDR) for conduction band electrons on deep paramagnetic centers in a series of GaAs(1-y)N(y) epilayers by time-resolved optical orientation experiments. We demonstrate that this dilute nitride compound can be used as an effective electron spin filter under a polarized optical excitation of appropriate intensity. This optimum intensity can moreover be controlled by adjusting the nitrogen composition in the layer.
Chemically Improved Filter Cakes for Drilling Wells (2002)

Blast furnace slag (BFS) is a latent hydraulic material similar in composition to Portland cement. BFS was originally studied for mud to cement (MTC) purposes. This application called for large quantities of BFS (40–500 ppb (lb/bbl)) and ultimately proved to be ineffective. Subsequently, BFS has been investigated as an additive in drilling fluids. In a recent study, muds containing additive-level concentrations (5–30 lb/bbl) of BFS were shown to be effective in reducing formation damage. The present work extends the investigation of BFS as a drilling fluid additive. Specifically, we have explored the use of chemical reagents to activate the BFS in filter cakes to achieve cakes that are thin, impervious and firm. Filter cakes were formed from slag-laden drilling fluids in a high-pressure, high-temperature reverse filtration apparatus (permeability plugging apparatus). Studies were conducted with partially hydrolyzed polyacrlyamide (PHPA) muds and CaCO3-based fluids containing different loadings of BFS. Filter cakes of these fluids were treated with several different activators and the results were compared to cakes containing no BFS. Different activation techniques were investigated and a novel device was designed to measure the strength of the filter cakes. An environmental scanning electron microscope examined the relationship between the structural features of the activated cakes and their strengths. This study demonstrates that filter cakes containing BFS can be chemically activated to produce thin, firm cakes with improved filtration properties. These cakes should be able to form better bonds with cement subsequently used for completion.
Structure of Aristolone, a Constituent of <i>Aristolochia debilis</i>. II (1961)

Permanganate oxidation of aristolone and deoxoaristolone, obtained by its Wolff-Kishner reduction, gave aristoic acid, C15H20O5. Treatment of aristoic acid with mineral acid afforded a kind of phenolic carboxylic acid, C11H14O3, which was assumed to be a m-hydroxybenzoic acid derivative possessing methyl and isopropyl groups, by the determination of C-methyl group and absorption spectra. Based on this assumption, 3-isopropyl-5-hydroxy-o-toluic. acid was synthesized from 2-isopropyl-4-nitrotoluene and identity of the foregoing phenolic carboxylic acid was established.
Using GPU for face detection (2009)

Many modern image analysis systems such as digital face image based authentication, 3D reconstruction, entertainment systems and many others, require fast and accurate face detection system. More advanced techniques, achieving better results, usually require high amount of computations and therefore use to much of the system resources. Using parallel GPU architecture in the crucial parts of the algorithms can significantly reduce the time needed for the detection. This paper prooves, that it is possible to use advantages of the GPU over CPU in the face detection on the example of the Discrete Gabor Jets face and facial features detection algorithm.
Essentials of clinical psychiatry : based on the American Psychiatric Press textbook of psychiatry, Third edition (1999)

Part 1 Theoretical Foundations and Assessment: The Neuroscientific Foundations of Psychiatry Normal Child and Adolescent Development Theories of the Mind and Psychopathology The Psychiatric Interview, Psychiatric History and Mental Status Examination Laboratory and Other Diagnostic Tests in Psychiatry. Part 2 Psychiatric Disorders: Delirium, Dementia and Amnestic Disorders Alcohol and Other Psychoactive Substance Use Disorders Schizophrenia, Schizophreniform Disorder and Delusional (Paranoid) Disorder Mood Disorders Anxiety Disorders Somatoform Disorders Factitious Disorders and Malingering Dissociative Disorders Sexual and Gender Identity Disorders Adjustment Disorder Impulse Control Disorders Not Elsewhere Classified Personality Disorders Disorders Usually First Diagnozed in Infancy, Childhood or Adolescence Sleep Disorders Eating Disorders - Anorexia Nervosa, Bulimia Nervosa and Obesity Pain Disorders. Part 3 Psychiatric Treatments: Psychopharmacology and Electroconvulsive Therapy Brief Dynamic Individual Psychotherapy Psychoanalysis, Psychoanalytic Psychotherapy and Supportive Psychotherapy Treatment of Children and Adolescents.
Dielectric Breakdown Process of Polymers (1980)

Much experimental work has been done on the dielectric breakdown of solid dielectrics, and a number of breakdown theories have been proposed. Many problems, however, still remain on the breakdown process of polymers. Here, the breakdown process of polymers are discussed from the standpoint of the inherent properties of polymers such as chemical structure, structural irregularities, the presence of additives, molecular motion, and so on. Further, as for the long-time breakdown processes of polymer insulation systems, electrical degradations caused by (PD) and treeing breakdown have been mentioned as important factors. Using experimental results obtained in our laboratory together with those presented by others, our considerations for fundamental processes of electrical degradation are reported. Also, the behavior of dc trees caused by space charge accumulation are discussed with the nature of carrier injection and trapping in polymers, which are estimated by TSC and TL measurements.
Genetic Diversity of Field Pennycress (Thlaspi arvense) Reveals Untapped Variability and Paths Toward Selection for Domestication (2019)

Evaluation of genetic diversity within wild populations is an essential process for improvement and domestication of new crop species. This process involves evaluation of population structure and individual accessions based on genetic markers, growth habits, and geographic collection area. In this study, accessions of field pennycress were analyzed to identify population structure and variation in germplasm available for breeding. A total of 9157 genome-wide single nucleotide polymorphisms (SNPs) were identified among the 121 accessions analyzed, and linkage disequilibrium based pruning resulted in 3497 SNPs. Bayesian cluster analysis was implemented in STRUCTURE v2.3.4 to identify four population groups. These groups were confirmed based on principal components analysis and geographic origins. Pairwise diversity among accessions was evaluated and revealed considerable genetic variation. Notably, a subset of accessions from Armenia with exceptional genetic variation was identified. This survey is the first to report significant genetic diversity among pennycress accessions and explain some of the phenotypic differences previously observed in the germplasm. Understanding variation in pennycress accessions will be a crucial step for selection, breeding, and domestication of a new cash cover crop for cold climates.
CHAPTER 13: Blast Diseases: Evolution and Challenges of a Staple Food Crop Fungal Pathogen (2020)

Blast diseases of rice and millet continue to affect small-holder famers in Asia, Africa, and Latin America. Wheat blast is an emerging disease that has reached epidemic status in a limited number of regions so far, but its impact on wheat production is already enormous and long lasting. The changing climate, along with the high evolutionary potential of blast diseases, underscores the continuing danger of new diseases emerging and calls for an understanding of the genetic and environmental factors that cause them.
A COMPARISON OF CURRENT WORK-HARDENING MODELS USED IN THE ANALYSIS OF PLASTIC DEFORMATIONS (1973)

The report presents an evaluation of four hardening rules of the incremental theory of plasticity to determine which of the rules are better suited for use in finite element or finite difference structural analysis computer programs. The hardening rules considered are isotropic hardening, the Prager-Ziegler kinematic hardening rule, the Mroz model, and the mechanical sublayer model. Comparisons of experimental data with hardening rule predictions (from a total incremental plasticity formulation using the von Mises yield condition and associated flow rule) for simple loading paths are first considered. Next the computer storage requirements associated with each hardening rule are investigated. Finally, the two most promising hardening rules are incorporated into an existing dynamic, shell of revolution finite element computer code and the cases of an impulsively loaded circular ring and circular plate are examined. Conclusions regarding the areas of applicability of each hardening rule are then presented. (Author)
Design of Unmanned Air Vehicles Using Transformer Surrogate Models (2022)

Computer-aided design (CAD) is a promising new area for the application of artificial intelligence (AI) and machine learning (ML). The current practice of design of cyber-physical systems uses the digital twin methodology, wherein the actual physical design is preceded by building detailed models that can be evaluated by physics simulation models. These physics models are often slow and the manual design process often relies on exploring near-by variations of existing designs. AI holds the promise of breaking these design silos and increasing the diversity and performance of designs by accelerating the exploration of the design space. In this paper, we focus on the design of electrical unmanned aerial vehicles (UAVs). The high-density batteries and purely electrical propulsion systems have disrupted the space of UAV design, making this domain an ideal target for AI-based design. In this paper, we develop an AI Designer that synthesizes novel UAV designs. Our approach uses a deep transformer model with a novel domain-specific encoding such that we can evaluate the performance of new proposed designs without running expensive flight dynamics models and CAD tools. We demonstrate that our approach significantly reduces the overall compute requirements for the design process and accelerates the design space exploration. Finally, we identify future research directions to achieve full-scale deployment of AI-assisted CAD for UAVs.