gebhart/patrepeval huggingface dataset:
Using Explosions to Power a Soft Robot (2013)

Combustion causes a soft robot to jump: Rapid actuation of a soft robot (composed of silicone elastomers) was achieved using high-temperature chemical reactions. Computer-controlled electrical sparks triggered the combustion of premixed CH4 and O2 gases inside the robot, which pressurized the pneumatic channels of the robot and caused it to jump (see figure). The heat from the explosions dissipated quickly and did not damage the robot even over many jumps. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Efficacy and Safety of an Irrigated-Tip Catheter for the Ablation of Accessory Pathways Resistant to Conventional Radiofrequency Ablation (2000)

Irrigated-tip catheter ablation is safe and effective in eliminating AP conduction resistant to conventional catheters, irrespective of the location.
Electrochemistry of Platinum(II) Porphyrins: Effect of Substituents and π-Extension on Redox Potentials and Site of Electron Transfer (2012)

Fourteen platinum(II) porphyrins with different π-conjugated macrocycles and different electron-donating or electron-withdrawing substituents were investigated as to their electrochemical and spectroscopic properties in nonaqueous media. Eight compounds have the formula (Ar(4)P)Pt(II), where Ar(4)P = the dianion of a tetraarylporphyrin, while six have π-extented macrocycles with four β,β'-fused benzo or naphtho groups and are represented as (TBP)Pt(II) and (TNP)Pt(II) where TBP and TNP are the dianions of tetrabenzoporphyrin and tetranaphthoporphyrin, respectively. Each Pt(II) porphyrin undergoes two reversible one-electron reductions and one to three reversible one-electron oxidations in nonaqueous media. These reactions were characterized by cyclic voltammetry, UV-visible thin-layer spectroelectrochemistry and in some cases by ESR spectroscopy. The two reductions invariably occur at the conjugated π-ring system to yield relatively stable Pt(II) π-anion radicals and dianions. The first oxidation leads to a stable π-cation radical for each investigated porphyrin; but in the case of tetraarylporphyrins containing electron-withdrawing substituents, the product of the second oxidation may undergo an internal electron transfer to give a Pt(IV) porphyrin with an unoxidized macrocycle. The effects of macrocycle structure on UV-visible spectra, oxidation/reduction potentials, and site of electron transfer are discussed.
Observation of high-frequency ambient noise generated by capillary waves (1990)

In the absence of breaking gravity waves, capillary waves may contribute to the generation of ambient noise in the ocean. Surface profiles of capillary water waves, with surface tension as a restoring force, are picked downward in the troughs and relatively flat at the crests. At a limiting amplitude (given by H/λ≈0.73, where H and λ are the wave height and wavelength, respectively) the free surface in the trough folds onto itself, encapsulating an air bubble. By blowing air over a water-filled, Plexiglas tank, 6bubble-producing capillary waves can be generated in the laboratory. Underwater acoustic emissions from these bubbles were monitored and a visual record of their formation was established via a high-speed videotape. The initial findings of an experimental study of generation, size distribution, and acoustic emissions of bubbles produced by capillary water waves are presented. [Work supported by ONR.]
Generation of Cation Radicals from Allylic Sulfides and Their Reactions with Silyl Enol Ethers by the Use of Cerium(IV) Ammonium Nitrate (1991)

Abstract Allyl sulfides react with silyl enol ether, siloxy diene and siloxy enyne by the oxidation with cerium(IV) ammonium nitrate to give α-phenylthio γ,δ-unsaturated ketones through the nucleophilic addition of silyl enol ethers to the sulfur cation radicals and the successive [2,3]-sigmatropic rearrangement.
Effect of the abrasive hardness and the slurry pH on the micro slurry-jet erosion of SiO<sub>2</sub> film (2019)

Recently, micro slurry-jet erosion (MSE) test was proposed to the evaluation of the mechanical properties of the hard surfaces. MSE is also expected to be applied to the micro-fabrication like other abrasive technology. Chemical mechanical polishing (CMP) has been one of the key processes in semiconductor production. It uses both of the mechanical and the chemical effects of slurry in order to establish the precise and small damage surfaces. In this study, the effect of the abrasive hardness and the slurry pH on MSE rates were investigated. SiO2 film was selected as the processed material, which is widely used as the dielectric layer in semiconductor devices. As results, the erosion rates did not correspond to the abrasive hardness, and increased as the slurry pH increased. These properties showed the similarity to the polishing rates of CMP.
Conditional Generative Moment-Matching Networks (2016)

Maximum mean discrepancy (MMD) has been successfully applied to learn deep generative models for characterizing a joint distribution of variables via kernel mean embedding. In this paper, we present conditional generative moment-matching networks (CGMMN), which learn a conditional distribution given some input variables based on a conditional maximum mean discrepancy (CMMD) criterion. The learning is performed by stochastic gradient descent with the gradient calculated by back-propagation. We evaluate CGMMN on a wide range of tasks, including predictive modeling, contextual generation, and Bayesian dark knowledge, which distills knowledge from a Bayesian model by learning a relatively small CGMMN student network. Our results demonstrate competitive performance in all the tasks.
Selective disruption of MMP-2 gene exacerbates myocardial inflammation and dysfunction in mice with cytokine-induced cardiomyopathy (2005)

Tumor necrosis factor-alpha (TNF-alpha) plays a pathophysiological role in the development and progression of heart failure. Matrix metalloproteinase (MMP)-2 is involved in extracellular matrix remodeling. Recent evidence suggests a protective role for this protease against tissue inflammation. Although MMP-2 is upregulated in the failing heart, little is known about its pathophysiological role. We thus hypothesized that ablation of the MMP-2 gene could affect cardiac remodeling and failure in TNF-alpha-induced cardiomyopathy. We crossed transgenic mice with cardiac-specific overexpression of TNF-alpha (TG) with MMP-2 knockout (KO) mice. Four groups of male and female mice were studied: wild-type (WT) with wild MMP-2 (WT/MMP(+/+)), WT with MMP-2 KO (WT/MMP(-/-)), TNF-alpha TG with wild MMP-2 (TG/MMP(+/+)), and TG with MMP-2 KO (TG/MMP(-/-)). The upregulation of MMP-2 zymographic activity in TG/MMP(+/+) mice was completely abolished in TG/MMP(-/-) mice, and other MMPs and tissue inhibitors of metalloproteinase were comparable between groups. Survival was shorter for male TG/MMP(-/-) than TG/MMP(+/+) mice. Female TG/MMP(-/-) mice were more severely affected than TG/MMP(+/+) mice with diminished cardiac function. Myocardial TNF-alpha and other proinflammatory cytokines were increased in TG/MMP(+/+) mice, and this increase was similarly observed in TG/MMP(-/-) mice. The extent of myocardial infiltrating cells including macrophages was greater in TG/MMP(-/-) than in TG/MMP(+/+) mice. Selective ablation of the MMP-2 gene reduces survival and exacerbates cardiac failure in association with the increased level of myocardial inflammation. MMP-2 may play a cardioprotective role in the pathogenesis of cytokine-induced cardiomyopathy.
Neutron Multiplicity Counting Moments for Fissile Mass Estimation in Scatter-Based Neutron Detection Systems (2017)

Neutron multiplicity counting (NMC) techniques are widely used for nuclear materials accountability and international safeguards applications to quantitatively evaluate characteristic properties pertaining to fissile material. Mathematical models for NMC moments have been previously derived for systems that use capture-based detectors; however, these models are not applicable when scatter-based detectors are used because of “neutron cross talk.” Neutron cross talk occurs when a single neutron scatters and deposits energy above threshold into multiple detectors causing spurious increase in multiplicity counts; this, in turn, has caused fissile mass to be overestimated when not treated. In this paper, we propose new mathematical models derived from point kinetics to correct for neutron cross-talk effects up to any arbitrary order N, where N denotes the maximum number of counts a single neutron can cause. The new models were used to estimate the fissile mass of plutonium metal and oxide samples with effective 240Pu mass ranging from 2.5 to 250 g. The adequacy of the models was confirmed using simulations of a conceptual scatter-based neutron multiplicity counter (e.g., organic scintillators) using MCNPX v2.7e with the PoliMi fission event generating extension. The fissile mass estimates with no correction for neutron cross-talk events yielded an average relative deviation from the true 240Pueff mass of 55.94% and 84.56% for metal and oxide samples, respectively. When neutron cross-talk events of order N = 2 are included in the model, the fissile mass estimates yielded an average relative deviation of 11.89% for metal and 13.21% for oxide samples. Accounting for neutron cross-talk events of order N = 3 resulted in fissile mass estimates with an average relative deviation of 9.58% and 10.51% for metal and oxide samples, respectively. These mass estimates were compared to a reference case (i.e., no neutron cross-talk effects) that yielded an average relative deviation of 6.81% and 4.77% for metal and oxide samples, respectively. The discrepancy between the estimates from the proposed model and the reference case is attributed to the assumed value of N, which sets a finite upper bound on the order of cross-talk events the model treats (i.e., the model for N = 3 assumes that a neutron will never cause more than three counts).
Biomarker development for pancreatic ductal adenocarcinoma using integrated analysis of mRNA and miRNA expression (2014)

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, which has dismal prognosis because of its silent early symptoms, high metastatic potential, and resistance to conventional therapies. Although a PDAC patient who is diagnosed at an early stage would have a substantial increase in chance of survival, the survival rate is poor because there is no efficient non-invasive diagnostic test in the early stage. In this study, we developed an efficient prediction models to detect PDAC in its early stages. Our prediction models use both mRNA and miRNA expression data from 104 PDAC tissues and 17 normal pancreatic tissues using microarray technology. After quality control, we built prediction models based on support vector machine (SVM) from mRNA and miRNA expressions for detecting early PDAC. To prevent over-fitting effect, we conducted leave-one-out cross validation (LOOCV) and 5-fold cross validation (CV). For independent validation of prediction models, we performed evaluation on independent datasets from Gene Expression Omnibus (GEO). After the validation, we identified 28 single markers and 231 combinations of markers with powerful prediction performance. In addition, the marker candidates are annotated with cancer pathways using gene ontology analysis. Our prediction models for PDAC may have potential for early diagnosis of PDAC.
Evaluating Design of Abdominal Aortic Aneurysm Endografts in a Patient-Specific Model Using Computational Fluid Dynamics (2011)

Computer modeling of blood flow in patient-specific anatomies can be a powerful tool for evaluating the design of implantable medical devices. We assessed three different endograft designs, which are implantable devices commonly used to treat patients with abdominal aortic aneurysms (AAAs). Once implanted, the endograft may shift within the patient’s aorta allowing blood to flow into the aneurismal sac. One potential cause for this movement is the pulsatile force experienced by the endograft over the cardiac cycle. We used contrast-enhanced computed tomography angiography (CTA) data from four patients with diagnosed AAAs to build patient-specific models using 3D segmentation. For each of the four patients, we constructed a baseline model from the patient’s preoperative CTA data. In addition, geometries characterizing three distinct endograft designs were created, differing by where each device bifurcated into two limbs (proximal bifurcation, mid bifurcation, and distal bifurcation). Computational fluid dynamics (CFD) was used to simulate blood flow, utilizing patient-specific boundary conditions. Pressures, flows, and displacement forces on the endograft surface were calculated. The curvature and surface area of each device was quantified for all patients. The magnitude of the total displacement force on each device ranged from 2.43 N to 8.68 N for the four patients examined. Within each of the four patient anatomies, the total displacement force was similar (varying at least by 0.12 N and at most by 1.43 N), although there were some differences in the direction of component forces. Proximal bifurcation and distal bifurcation geometries consistently generated the smallest and largest displacement forces, respectively, with forces observed in the mid bifurcation design falling in between the two devices. The smallest curvature corresponded to the smallest total displacement force, and higher curvature values generally corresponded to higher magnitudes of displacement force. The same trend was seen for the surface area of each device, with lower surface areas resulting in lower displacement forces and vise versa. The patient with the highest blood pressure displayed the highest magnitudes of displacement force. The data indicate that curvature, device surface area, and patient blood pressure impact the magnitude of displacement force acting on the device. Endograft design may influence the displacement force experienced by an implanted endograft, with the proximal bifurcation design showing a small advantage for minimizing the displacement force on endografts.
Real-World Implementation of Artificial Intelligence/Machine Learning for Managing Surgical Spine Patients at 2 Academic Health Care Systems (2023)

Decision-making in spine surgery is complex due to patients' heterogeneity and complexity of spinal pathologies and the various surgical options applied to a given pathology. Artificial intelligence/machine learning algorithms provide an opportunity to improve patient selection, surgical planning, and outcomes. The purpose of this article is to present the experience and applications of in spine surgery at 2 large academic health care systems.
Engineering site-selective incorporation of fluorine into natural product analogs (2021)

Abstract While bioactive compounds are commonly derived both by human design as well as from living organisms, man-made and natural products typically display very different structural characteristics. As such, a longstanding goal in the discovery of new molecular function is to develop approaches to incorporate the advantageous elements of both groups of molecules, thereby expanding the molecular space accessible for this purpose. In this work, we report the engineering a fluorine-selective enzyme that can complement mutated acyltransferase (AT) domains of a modular polyketide synthase, which are the main determinants of the identity and location of substituents on polyketides, to produce different fluorinated regioisomers of the erythromycin precursor in vitro . We further show that by engineering cell uptake of fluorinated building blocks, we can control fluorine selectivity in vivo to produce selectively fluorinated polyketides using engineered E. coli . These results demonstrate that it is possible to introduce fluorine, a key synthetic design element for drug development, selectively into the scaffold of a complex natural product and produce these analogs by microbial fermentation.
In situ experiments to develop ecological relevant tools in individual and population levels (2009)

In situ bioassays are recognized as relevant tools for stressor and effect diagnosis in aquatic environments by allowing realistic exposure scenarios. However, most in situ bioassays are based on individual-level response assessment and do not enable to predict and/or assess the risk toward higher biological levels, such as population. Today, one of the challenges is to develop methods to extrapolate from effects measured in individual to population-level effects. This study aimed to enhance ecological relevance of this extrapolation step by using caging methods. The first step was to establish in situ relationships between life history traits (potentially used as markers of contaminant effects) and population dynamics of Gammarus fossarum (recognised as an ecologically relevant species). For this two methodologies were employed for a native population living in an uncontaminated stream: individual caging &amp;#38; demographic census. The second step was to assess the biological water quality of Ardières river, based on individual ecotoxicological marker measurements in transplanted organisms and then the projection of observed effects on the demography of the native population used as reference.This approach (coupling in situ bio-tests and population modeling) allows : (1) to enhance ecological relevance of diagnostic assessment, (2) to propose integrated ecotoxicological indicators.
Learning deep models of optimization landscapes (2017)

In all but the most trivial optimization problems, the structure of the solutions exhibit complex interdependences between the input parameters. Decades of research with stochastic search techniques has shown the benefit of explicitly modeling the interactions between sets of parameters and the overall quality of the solutions discovered. We demonstrate a novel method, based on learning deep networks, to model the global landscapes of optimization problems. To represent the search space concisely and accurately, the deep networks must encode information about the underlying parameter interactions and their contributions to the quality of the solution. Once the networks are trained, the networks are probed to reveal parameter combinations with high expected performance with respect to the optimization task. These estimates are used to initialize fast, randomized, local-search algorithms, which in turn expose more information about the search space that is subsequently used to refine the models. We demonstrate the technique on multiple problems that have arisen in a variety of real-world domains, including: packing, graphics, job scheduling, layout and compression. Strengths, limitations, and extensions of the approach are extensively discussed and demonstrated.
Photocoagulation Does Not Ablate Angiogenic Markers in Rabbit Retina (1988)

Panretinal photocoagulation (PRP) in rabbits produces treatment areas consisting of destroyed outer retina and intact inner retina separated by areas of normal-appearing retina. Intravenous iodoacetate produces widespread destruction of the outer retina with sparing of the inner retina, approximating total, confluent PRP. After PRP (at three weeks), intravenous injection of iodoacetate (at three weeks or four months), and in control rabbits, eyes were harvested and retinas were homogenized in a balanced salt solution. Retinal homogenates were measured for three markers of angiogenic activity: vascular endothelial cell migration, proliferation, and production of plasminogen activator. Retinas subjected to PRP or intravenous iodoacetate (at three weeks or four months) stimulated migration and proliferation above baseline levels twice as much as control retinas and stimulated plasminogen activator production by twofold to 2.5-fold. These data suggest that PRP does not eliminate the ability of the retina to produce angiogenic activity, but rather exerts its antiangiogenic effect in an indirect fashion.
390: Durable Cancer Control in High Risk Prostate Cancer Patients Treated with Radical Prostatectomy (2007)

You have accessJournal of UrologyModerated Poster 12, Sunda~May20,2007 1:00 - 3:00 pm1 Apr 2007390: Durable Cancer Control in High Risk Prostate Cancer Patients Treated with Radical Prostatectomy Markus Graefen, Jochen Walz, Andrea Gallina, Felix K.-H. Chun, Alwyn M. Reuther, James A. Eastham, Eric A. Klein, Peter T. Scardino, Francesco Montorsi, Hartwig Huland, and Pierre I. Karakiewicz Markus GraefenMarkus Graefen More articles by this author , Jochen WalzJochen Walz More articles by this author , Andrea GallinaAndrea Gallina More articles by this author , Felix K.-H. ChunFelix K.-H. Chun More articles by this author , Alwyn M. ReutherAlwyn M. Reuther More articles by this author , James A. EasthamJames A. Eastham More articles by this author , Eric A. KleinEric A. Klein More articles by this author , Peter T. ScardinoPeter T. Scardino More articles by this author , Francesco MontorsiFrancesco Montorsi More articles by this author , Hartwig HulandHartwig Huland More articles by this author , and Pierre I. KarakiewiczPierre I. Karakiewicz More articles by this author View All Author Informationhttps://doi.org/10.1016/S0022-5347(18)30643-8AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "390: Durable Cancer Control in High Risk Prostate Cancer Patients Treated with Radical Prostatectomy." The Journal of Urology, 177(4S), p. 130 © 2016 by American Urological AssociationFiguresReferencesRelatedDetails Volume 177Issue 4SApril 2007Page: 130 Advertisement Copyright & Permissions© 2016 by American Urological AssociationMetricsAuthor Information Markus Graefen More articles by this author Jochen Walz More articles by this author Andrea Gallina More articles by this author Felix K.-H. Chun More articles by this author Alwyn M. Reuther More articles by this author James A. Eastham More articles by this author Eric A. Klein More articles by this author Peter T. Scardino More articles by this author Francesco Montorsi More articles by this author Hartwig Huland More articles by this author Pierre I. Karakiewicz More articles by this author Expand All Advertisement PDF downloadLoading ...