gebhart/patrepeval huggingface dataset:
Performance analysis of CNN frameworks for GPUs (2017)

Thanks to modern deep learning frameworks that exploit GPUs, convolutional neural networks (CNNs) have been greatly successful in visual recognition tasks. In this paper, we analyze the GPU performance characteristics of five popular deep learning frameworks: Caffe, CNTK, TensorFlow, Theano, and Torch in the perspective of a representative CNN model, AlexNet. Based on the characteristics obtained, we suggest possible optimization methods to increase the efficiency of CNN models built by the frameworks. We also show the GPU performance characteristics of different convolution algorithms each of which uses one of GEMM, direct convolution, FFT, and the Winograd method. We also suggest criteria to choose convolution algorithms for GPUs and methods to build efficient CNN models on GPUs. Since scaling DNNs in a multi-GPU context becomes increasingly important, we also analyze the scalability of the CNN models built by the deep learning frameworks in the multi-GPU context and their overhead. The result indicates that we can increase the speed of training the AlexNet model up to 2X by just changing options provided by the frameworks.
Aero-ZnS architectures with dual hydrophilic–hydrophobic properties for microfluidic applications (2020)

Here, we report on a new aero-material, called aero-ZnS, representing self-organized architectures made of ZnS hollow micro-tetrapod structures with nanoscale thin walls. The fabrication process is based on the hydride vapor phase epitaxy of CdS on sacrificial micro-tetrapods of ZnO with simultaneous or subsequent transformation of CdS into ZnS and removal of the sacrificial ZnO crystals. The nanostructure of the obtained ZnS hollow micro-tetrapods exhibits the polytypic intergrowth of wurtzite- and sphalerite-type phases perpendicular to their close packed planes. The inner surface of the micro-tetrapod walls preserves oxygen sites, as demonstrated by imaging based on electron energy-loss filtering. The self-organized aero-ZnS architecture proves to be hydrophilic under tension and hydrophobic when compressed against water. Self-propelled liquid marbles assembled using ZnS hollow micro-tetrapod structures are demonstrated.
Susceptibility mapping in the human brain using threshold‐based k‐space division (2010)

A method for calculating quantitative three-dimensional susceptibility maps from field measurements acquired using gradient echo imaging at high field is presented. This method is based on division of the three-dimensional Fourier transforms of high-pass-filtered field maps by a simple function that is the Fourier transform of the convolution kernel linking field and susceptibility, and uses k-space masking to avoid noise enhancement in regions where this function is small. Simulations were used to show that the method can be applied to data acquired from objects that are oriented at one angle or multiple angles with respect to the applied field and that the use of multiple orientations improves the quality of the calculated susceptibility maps. As part of this work, we developed an improved approach for high-pass filtering of field maps, based on using an arrangement of dipoles to model the fields generated by external structures. This approach was tested on simulated field maps from the substantia nigra and red nuclei. Susceptibility mapping was successfully applied to experimental measurements on a structured phantom and then used to make measurements of the susceptibility of the red nuclei and substantia nigra in healthy subjects at 3 and 7 T.
Dust Mites and Asthma (2008)

This chapter contains sections titled: Introduction and history Mite allergens and mite fecal particles Discussion Conclusions References
Evolution of Microstructure during the Thermal Processing of Manganese-Promoted Tin(IV) Oxide Catalysts (2003)

The chemical transformations occurring during the thermal activation of manganese-promoted tin(IV) oxide catalysts have been investigated by FT-IR, powder X-ray diffraction, and nitrogen adsorption. Two methods of catalyst preparation have been employed: (i) coprecipitation from aqueous solutions containing both tin(IV) and manganese(II) ions and (ii) impregnation of SnO2 using aqueous manganese(II) nitrate or acetate solutions. The initial product obtained by coprecipitation comprises small (2-nm) particles of SnO2 together with much larger (57-nm) crystallites of MnSn(OH)6. Thermal processing at 573 K causes decomposition of MnSn(OH)6. No Mn-containing phase can be identified in the temperature range 573−873 K, but crystalline α-Mn2O3 is present after treatment at 1073 K and Mn3O4 after treatment at 1273 K. The impregnation route leaves adsorbed nitrate or acetate on the surface of the SnO2 particulate, but both adsorbates are decomposed by 573 K. For the nitrate-derived material, no Mn-containing phase can be identified in the temperature range 573−873 K, although crystalline γ-Mn2O3 is present after treatment at 573 K, which is transformed to α-Mn2O3 by 873 K in the acetate-derived material. Both α-Mn2O3 and Mn3O4 are present after treatment at temperatures >1073 K in both materials but in different amounts. Pore texture, surface area, and particle size evolution with temperature are similar in the three materials.
<title>Diffractive optics for head-mounted displays</title> (1995)

Diffractive optics have the potential to play a key role in several areas of head mounted displays. They can reduce size and weight while providing some unique optical functions that would be difficult to implement with conventional refractives. There are four areas in which diffractive optics may contribute: Magnifier optics, combiner optics, head and hand tracking, and optical data interface. This paper is primarily concerned with the introduction of a new image combiner element based on Babinet's principle.
Radar Guided Dynamic Visual Attention for Resource-Efficient RGB Object Detection (2022)

An autonomous system's perception engine must provide an accurate understanding of the environment for it to make decisions. Deep learning based object detection networks experience degradation in the performance and robustness for small and far away objects due to a reduction in object's feature map as we move to higher layers of the network. In this work, we propose a novel radar-guided spatial attention for RGB images to improve the perception quality of autonomous vehicles operating in a dynamic environment. In particular, our method improves the perception of small and long range objects, which are often not detected by the object detectors in RGB mode. The proposed method consists of two RGB object detectors, namely the Primary detector and a lightweight Secondary detector. The primary detector takes a full RGB image and generates primary detections. Next, the radar proposal framework creates regions of interest (ROIs) for object proposals by projecting the radar point cloud onto the 2D RGB image. These ROIs are cropped and fed to the secondary detector to generate secondary detections which are then fused with the primary detections via non-maximum suppression. This method helps in recovering the small objects by preserving the object's spatial features through an increase in their receptive field. We evaluate our fusion method on the challenging nuScenes dataset and show that our fusion method with SSD-lite as primary and secondary detector improves the baseline primary yolov3 detector's recall by 14 % while requiring three times fewer computational resources.
A Novel Control Strategy for Wind Farm Active Power Regulation Considering Wake Interaction (2019)

Given the ever-increased penetration of wind power generation in today's power systems, wind farms tend to operate in a dispatchable way to a certain extent by actively fulfilling dispatch orders from system operators. This paper is focused on the challenging issue of coordinating the interactive wind turbines in a wind farm, which are influenced by non-negligible wake effect, to efficiently respond to external dispatch orderx. To achieve this, a novel control strategy is proposed by: 1) effectively allocating power regulation task to individual wind turbines; and 2) utilizing the existing resources (i.e., rotational kinetic energy and pitching capability) of wind turbine to satisfy the dispatch order efficiently and reliably. Extensive case studies on both constant and variable wind speed conditions are carried out to demonstrate the effectiveness of the proposed control strategy. As a comparison, simulations results based on uniform load sharing strategy are also presented. It is exhibited that our proposed strategy has better control performance in terms of total energy harvesting and pitching activation frequency.
Electrochemical synthesis and properties of -fluoroacyl and G-perfluoroalkyl transition metal complexes (2000)

The electrochemical synlhesis of ~-Ouoroacyl complexes (MI--cr-COP h. (M = C5tts(CO}?W or (CO)5Mn. R r = CF 3 or C4F ~) was pertbrmed according to two procedures: (l) the preliminary.' electrochemical synthesis of [MIfrom [M] 2 followed by reaction with a fluorine-containing compound and t2) the electrochemical synthesis of[M tin the presence of a fluorine-containing compound Trifluoroacetic anhydride was dcmonstrated to be the best acylating agent in these reactions. The electrochemical properties of the resulting complexes were studied.
Type 2 Diabetes and Intravenous Thrombolysis Outcome in the Setting of ST Elevation Myocardial Infarction (2004)

The present study suggests that type 2 diabetes is a strong predictor of acute intravenous thrombolysis failure during STEMI. This finding may significantly contribute to the worse prognosis for type 2 diabetic subjects compared with nondiabetic ones in this setting.
Anti‐Methamphetamine Antibody Gene Therapy Protects Against Some METH‐Induced Inflammation (2018)

Methamphetamine (METH) is a highly abused, addictive drug that can adversely affect the peripheral immune response, causing immune dysregulation in the user. This can lead to an overproduction of cytokines, chemokines, and cellular adhesion molecules causing potential physiologic damage. Thus novel, sustained treatments that focus on mitigating these effects should be evaluated. Our laboratory is combining an anti‐METH single chain variable antibody‐fusion fragment (7F9‐Fc) with adeno‐associated virus (AAV) particles as a potential gene therapy. AAV‐7F9‐Fc works as a pharmacokinetic antagonist to slow and reduce entry of METH into the brain and can achieve lasting serum concentrations in mice (&gt;7 months) from a single treatment. Thus, this therapy has the clinical potential to attenuate the effects of periodic METH relapse during rehabilitation and possibly decrease associated physiological complications such as inflammation. We hypothesized that an AAV‐delivered anti‐METH antibody fragment (AAV‐7F9‐Fc) will provide protection from METH‐induced inflammation. To test this hypothesis, we established a mouse model of METH‐induced early withdrawal inflammation in our laboratory. Male BALB/c mice were divided into six groups (n=5/group); 1) Saline + Saline, 2) Saline + METH, 3) LPS, 4) AAV‐7F9‐Fc + Saline, 5) AAV‐7F9‐Fc + METH, 6) AAV‐empty vector + saline. METH administration followed a dosing regimen of 1 mg/kg i.p. for seven consecutive days with sacrifice after 72 hrs. We performed a MSD Proinflammatory Panel multiplex analysis to measure important serum cytokine and chemokine levels (e.g., IL‐10, IL‐6, IL‐1®). In brain tissues, we measured markers of glial cell activation, glial fibrillary acidic protein (GFAP), ionized calcium binding adaptor molecule (Iba1) and proinflammatory cytokines via qPCR. Our results indicate that this dosing regimen lead to a significant (p &lt; 0.05) increase in proinflammatory mediators (e.g., IL‐1® and IL‐6) in the striatum of Saline + METH mice, but not AAV‐7F9‐Fc + METH mice. In the hippocampus and frontal cortex, the Saline + METH mice showed a significant increase in the mRNA transcripts of IL‐6 &amp; IL‐1® vs those mice treated with AAV‐7F9‐Fc + METH. Noticeably, GFAP was also increased in all observed brain regions of Saline + METH vs those treated with AAV‐7F9‐Fc + METH. Our results also indicate that this dosing regimen lead to a significant increase in serum proinflammatory cytokines (e.g., IL‐1® and IL‐6) vs the AAV‐7F9‐Fc + METH mice. Taken together, these data indicate that a chronic, low dose METH regimen can induce proinflammatory cytokine elevations in serum and brain, increase activation of glial cell markers in brain tissue, and that AAV‐7F9‐Fc treatment has the potential to mitigate some of these proinflammatory effects. Support or Funding Information Funded by NIH R01‐DA036600, R01 DA036600‐03S1, T32‐GM106999, and R25GM083297 This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Mud loss estimation using machine learning approach (2018)

Lost circulation costs are a significant expense in drilling oil and gas wells. Drilling anywhere in the Rumaila field, one the world’s largest oilfields, requires penetrating the Dammam formation, which is notorious for lost circulation issues and thus a great source of information on lost circulation events. This paper presents a new, more precise model to predict lost circulation volumes, equivalent circulation density (ECD), and rate of penetration (ROP) in the Dammam formation. A larger data set, more systematic statistical approach, and a machine-learning algorithm have produced statistical models that give a better prediction of the lost circulation volumes, ECD, and ROP than the previous models for events. This paper presents the new model, validates the key elements impacting lost circulation in the Dammam formation, and compares the predicted outcomes to those from the older model. The work previously presented by Al-Hameedi et al. ( http://www.onepetro.org , 2017a; http://www.AADE.org , 2017b) provided a platform for predicting the severity of lost circulation incidents in the Dammam formation. Using the new models, the predictions closely track actual field incidents of lost circulation. When new lost circulation events were compared with predictions from the old and new models, the new model presented a much tighter prediction of events. Three equations for optimizing operations were developed from these models focusing on the elements that have the highest degree of impact. The total flow area of the nozzles was determined to be a significant factor in the ROP model indicating that nozzle size should be chosen carefully to achieve optimal ROP. Good modeling of projected lost circulation events can assist in evaluating the effectiveness of new treatments for lost circulation. The Dammam formation is a significant source of lost circulation in a major oilfield and warrants evaluation of the effectiveness of lost circulation treatments. These techniques can be applied to other fields and formations to better understand the economic impact of lost circulation and evaluate the effectiveness of various lost circulation mitigation efforts.
Smooth muscle tumors of the small bowel: A case report and review of the literature (1985)

We report a rare case of peritonitis caused by perforation of smooth muscle tumor of the jejunum. In spite of having all the reported presenting symptoms of these tumors, the diagnosis was not made preoperatively. Although histopathologically diagnosis was that of a benign tumor, the subsequent course was rapid and malignant. A complete review of the literature is presented.
Learning and Recognizing Archeological Features from LiDAR Data (2019)

We present a remote sensing pipeline that processes LiDAR (Light Detection And Ranging) data through machine & deep learning for the application of archeological feature detection on big geo-spatial data platforms such as e.g. IBM PAIRS Geoscope [1], [2].Today, archeologists get overwhelmed by the task of visually surveying huge amounts of (raw) LiDAR data in order to identify areas of interest for inspection on the ground. We showcase a software system pipeline that results in significant savings in terms of expert productivity while missing only a small fraction of the artifacts.Our work employs artificial neural networks in conjunction with an efficient spatial segmentation procedure based on domain knowledge. Data processing is constraint by a limited amount of training labels and noisy LiDAR signals due to vegetation cover and decay of ancient structures. We aim at identifying geo-spatial areas with archeological artifacts in a supervised fashion allowing the domain expert to flexibly tune parameters based on her needs.
The Preparation of Titania Nano Crystals and Silica-Titania Core-Shell Particles through Peptization Process (2013)

Monodispersed silica-titania core-shell particles with a controllable thickness and crystallinity were prepared by a simple peptization process in an aqueous acidic solution without the use of any external additives such as polyelectrolytes, polymers, and surfactants. The crystallinity of the titania nanocrystals coated on core-shell particles was controlled by adjusting the pH of the reaction medium. The shell thickness was found to increase as the reaction temperature, time, and the amount of Ti source material were increased. As-prepared core-shell particles with a smooth surface roughness were transformed into coreshell particles covered with largely grown titania crystals with different phases depending on the heat treatment temperature. The morphology and phase development of the particles were characterized via SEM, TEM, and XRD.
Efficacy and Safety of Tadalafil in Men With Erectile Dysfunction Following Spinal Cord Injury (2007)

Tadalafil (10 mg and 20 mg) improved erectile function and was well tolerated by men with ED secondary to traumatic SCI.
Pathophysiological basis of low contrast visual acuity loss in multiple sclerosis (2018)

While retinal ganglion cell axonal loss is a superior predictor of LCVA, the degree of demyelination contributes significantly to worsening of LCVA, particularly when patients with severe axonal loss are excluded. These results support the feasibility of using LCVA as a functional biomarker in remyelination therapy trials, providing appropriate patient's selection criteria are implemented.
Model-Based Three-Dimensional Interpretations of Two-Dimensional Images (1983)

ACRONYM is a comprehensive domain independent model-based system for vision and manipulation related tasks. Many of its submodules and representations have been described elsewhere. Here the derivation and use of invariants for image feature prediction is described. Predictions of image features and their relations are made from three-dimensional geometric models. Instructions are generated which teli the interpretation algorithms how to make use of image feature measurements to derive three-dimensional size, structural, and spatial constraints on the original three-dimensional models. Some preliminary examples of ACRONYM's interpretations of aerial images are shown.
Sperm-egg fusion: events at the plasma membrane (2004)

Sperm-egg fusion is a cell-cell membrane fusion event essential for the propagation of sexually reproducing organisms. In gamete fusion, as in other fusion events, such as virus-cell and intracellular vesicle fusion, membrane fusion is a two-step process. Attachment of two membranes through cell-surface molecules is followed by the physical merger of the plasma membrane lipids. Recent progress has demonstrated an essential role for an oocyte tetraspanin, CD9, in mouse sperm-egg fusion, and a specific molecular site crucial for CD9 function has been identified. Absence of glycosylphosphatidylinositol-anchored proteins on the oocyte surface also results in loss of oocyte fusion competence in this gamete. These discoveries provide a strong starting point for the identification of additional proteins that have roles in sperm-egg fusion.
Targeted thrombolysis by using c-RGD-modified N,N,N-Trimethyl Chitosan nanoparticles loaded with lumbrokinase (2018)

Lumbrokinase (LK) has strong fibrinolytic and thrombolytic activities, but it has a short half-life, can be easily inactivated, and may cause hemorrhage as a side effect. This study develops a potential thrombolytic therapy by fabricating N,N,N-Trimethyl Chitosan (TMC) nanoparticles modified with the cyclic Arg-Gly-Asp-Phe-Lys peptide (c-RGD) and loaded with LK (i.e. c-RGD-LK-NPs). The binding of c-RGD to platelet membrane GPIIb/IIIa receptors is expected to enable targeted delivery of the c-RGD-conjugated TMC to the thrombus. The synthesized c-RGD-LK-NPs had a mean particle size of 232.0 nm, zeta potential of 19.8 mV, entrapment efficiency of 52.7% ± 2.5%, and loading efficiency of 17.4% ± 0.65%. Transmission electron microscopy showed that they were generally spherical. The c-RGD-LK-NPs gave a cumulative in vitro LK release of 80.6% over 8 h, and the activity of LK was close to 80%, indicating that the nanoparticles protected the activity of LK. In vitro blood clot lysis assays were carried out and in vivo thrombolysis effect was tested in Sprague-Dawley rats carotid artery thrombus model. In all cases, the c-RGD-LK-NPs showed superior performance compared with the free LK and the unmodified TMC nanoparticles loaded with LK. The c-RGD-LK-NPs reagent is expected to be potentially useful in treating thromboembolic diseases.
Synthesis and Characterization of Novel Biodegradable Polyamides Containingα-amino Acid (2009)

The polyamides were obtained from 1,6-hexanediamine and diacylchloride which incorporated α -amino acid residues through interfacial polycondensation. High molecular weight (ηinh = 1.05–1.18 dL/g) polymers were produced with high yields. The structure of polyamides was verified by FT-IR and 1H NMR spectra. They showed a remarkable ability to develop high crystallinity with melting temperatures in the range 117–191°C and was stable up to 350°C under nitrogen. Two methods such as alkali hydrolysis (10% NaOH w/v, 80°C) and enzymatic hydrolysis were employed for assessing the susceptibility of these polyamides to degradation. A preliminary investigation of the 5-fluorouracil (5-FU) release characteristics of these polyamides showed that the release rate increased with increasing water absorption of the polymers.
Konzervativní léčba glaukomu (2009)

Glaukom je chronicka progresivni irreverzibilni neuropatie zrakoveho nervu. Lecbu glaukomu dělime na konzervativni, laserovou a chirurgickou.
Zakladem konzervativni lecby je pravidelna každodenni instilace ocnich kapek s obsahem antiglaukomatik. V konzervativni
lecbě glaukomu se uplatňuji prostaglandinova analoga a prostamid, β-blokatory, inhibitory karboanhydrazy, α2-sympatomimetika,
parasympatomimetika, jejich fixni kombinace a hyperosmoticke latky. Hlavnim cilem lecby glaukomu je zachovani adekvatnich zrakových
funkci při minimalnim ovlivněni kvality života nasich pacientů.