gebhart/patrepeval huggingface dataset:
Improvement of Input Current Waveforms for a Matrix Converter Using a Novel Hybrid Commutation Method (2007)

This paper proposes a novel hybrid commutation method and a compensation method for the output voltage error and input current error of a matrix converter in order to improve the input current. The proposed commutation method combines input voltage commutation and load current commutation. There are two conventional commutation methods; one that depends on the polarity of the input line voltage and is called voltage commutation, and one that depends on the polarity of the output current and is called current commutation. However, a problem with voltage commutation is that commutation failure occurs at around an input line voltage of zero. It is difficult to detect the voltage polarity due to dependence on the offset and delay of the sensor. Similarly, current commutation failure occurs at around a load current of zero. The cause of these detection errors are detection delay and the offset of the sensor. However, the proposed commutation method can decrease the commutation failure without the need for a high accuracy sensor, because the current commutation is compensated by the voltage commutation. In addition, a new commutation error compensation method is proposed for the proposed commutation. The output voltage and input current error are compensated at the same time, because the duty ratio of each switch is directly compensated. The proposed method is validated based on the experimental results with a 750 W induction motor and a R-L load. The total harmonic distortion (THD) of the input current and the output current with the proposed hybrid commutation are 3.9% and 2.1%, respectively, and are obtained for an induction motor load with vector control.
Correction: Probing viscoelastic response of soft material surfaces at the nanoscale (2015)

Correction for ‘Probing viscoelastic response of soft material surfaces at the nanoscale’ by David B. Haviland et al., Soft Matter, 2015, DOI: 10.1039/c5sm02154e.
Underwater video mosaicing for seabed mapping (2002)

This paper presents improved techniques and applications in mosaicing of underwater video images. The applications are of use to many marine scientists. High resolution seabed maps are created. The improvements in the processing relate to the removal of interframe variability and lighting, speed up of the mosaicing process and improved accuracy in the estimation of the transformation parameters. Results are presented for real data acquired under a variety of circumstances and scenes.
Di-iodotetrakis(triphenylarsine oxide)uranium(IV) hexaiodouranate(IV). A new type of actinoid co-ordination compound (1987)

A new type of co-ordination compound having UX4L2 stoicheiometry consisting of both cationic and anionic six co-ordinated metal species has been isolated (M = uranium, X = iodide, and L = neutral donor ligand).
Palliation of bone pain with Sn-117m(4+)DTPA (1994)

Sn-117m(4+)DTPA prepared at Brookhaven National Laboratory has favorable physical and biological characteristics for use as a palliative agent to relieve pain from osseous metastases. The short range of the emitted conversion electrons permits large bone radiation doses without excessive radiation to the bone marrow. An accompanying 158.6 keV gamma is useful for monitoring the distribution. The T1/2 of 13.6 days provides an adequate shelf life. A previous study in humans has demonstrated favorable dosimetry with a bone surface dose of approximately 57.9 mGy/MBq and a bone surface to marrow ratio of 10:1. This study was instituted to find a dose level which was effective and to monitor effects on bone marrow. Sn-117m was administered to 14 patients. Administered activity ranged between 66 and 573 MBq or 1.2-5.8 MBq/kg body weight. At the lower dose levels (<3.1 MBq/kg, n=7), 1 obtained good relief of pain, 1 partial relief, and 1 no relief. The remaining 4 were not evaluated because of the need for further treatment of soft tissue disease or because of intervening death. The 7 patients treated at the higher dose level (4.8-5.8 MBq/kg) included patients with prostate (3), breast (3) and unknown (1) primary cancers. All patients experienced reliefmore » of pain, 5 excellent and 2 partial. No marrow suppression was observed as a result of Sn-117m therapy. Initial observations indicate that Sn-117m DTPA is effective in palliation of pain from osseous metastases without producing bone marrow suppression. Further studies at a higher dose level are planned.« less
Abstract 2712: Identification of tumor initiating genes RPL39 and MLF2 that mediate lung metastasis through nitric oxide signaling and mesenchymal to epithelial transition. (2013)

Abstract Triple negative breast cancer (TNBC) is the most aggressive and lethal form of cancer characterized by lack of estrogen, progesterone and Her2 receptors. It is prevalent in women of African American descent, often present in younger and premenopausal women. It shows high risk of recurrence and frequently metastasizes to lungs and brain, resulting in poor overall prognosis. There is no targeted therapy for TNBC as it does not respond to hormonal therapy and is intrinsically resistance to conventional chemotherapy. It is therefore imperative to understand the mechanism of survival of these cancers and unravel its biological pathways and modes of progression. We have previously described breast cancer stem cells (BCSC) to be intrinsically resistant to treatment which is further confirmed by recent publications by other groups that describe direct functional evidence for the same. Using genomic assays, we traced a BCSC gene signature comprising of 477 genes derived from patient biopsies. On selective shRNA knockdown of these genes we identified RPL39 and MLF2 as the top two candidates that affect BCSC self-renewal. Selective siRNA knockdown of RPL39 and MLF2 in human cancer xenografts, showed reduced tumor volume and lung metastases with a concomitant decrease in BCSC markers. Thus, targeting BCSCs in combination with chemotherapy should eliminate the heterogeneous populations within a tumor. Additionally, next generation RNA-seq confirmed mutations in RPL39 and MLF2 in 50% of lung metastases from breast cancer patients. In vitro and in vivo siRNA knockdown of RPL39 and MLF2 showed decrease in nitric oxide synthase, suggesting that these genes are driven by nitric oxide signaling. In conclusion this study reveals novel tumor initiating genes, RPL39 and MLF2 that target the breast cancer stem cells and also show impact on lung metastasis. Our findings enhance the understanding of treatment resistant breast cancer stem cells, the mutations that cause metastases and also lay foundation for developing new therapies for such cancers with poor prognosis. Citation Format: Bhuvanesh Dave, Sergio Granados, Junhua Mai, Dong Soon Choi, Ding Cheng Gao, Sucharita Mitra, Haifa Shen, Senthil Muthuswamy, Vivek Mittal, Mauro Ferrari, Jenny Chang. Identification of tumor initiating genes RPL39 and MLF2 that mediate lung metastasis through nitric oxide signaling and mesenchymal to epithelial transition. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2712. doi:10.1158/1538-7445.AM2013-2712
Profiling early infection responses: Pseudomonas aeruginosa eludes host defenses by suppressing antimicrobial peptide gene expression (2005)

Insights into the host factors and mechanisms mediating the primary host responses after pathogen presentation remain limited, due in part to the complexity and genetic intractability of host systems. Here, we employ the model Drosophila melanogaster to dissect and identify early host responses that function in the initiation and progression of Pseudomonas aeruginosa pathogenesis. First, we use immune potentiation and genetic studies to demonstrate that flies mount a heightened defense against the highly virulent P. aeruginosa strain PA14 when first inoculated with strain CF5, which is avirulent in flies; this effect is mediated via the Imd and Toll signaling pathways. Second, we use whole-genome expression profiling to assess and compare the Drosophila early defense responses triggered by the PA14 vs. CF5 strains to identify genes whose expression patterns are different in susceptible vs. resistant host-pathogen interactions, respectively. Our results identify pathogenesis- and defense-specific genes and uncover a previously undescribed mechanism used by P. aeruginosa in the initial stages of its host interaction: suppression of Drosophila defense responses by limiting antimicrobial peptide gene expression. These results provide insights into the genetic factors that mediate or restrict pathogenesis during the early stages of the bacterial-host interaction to advance our understanding of P. aeruginosa-human infections.
Recyclable Polymer-Supported Pd Catalysts for Aryl Amination Reactions (2005)

The authors have prepared polymer-supported palladium catalysts from three commercially available phosphine-functionalized polystyrenes, Pd2(dba)3, and P(t-Bu)3. The stability of the catalysts is dependent on the method of preparation and the nature of the polymer-bound phosphine. Thus, substantial catalyst leaching (determined by VT 31P NMR spectroscopy) and/or decomposition (indicated by the deposition of palladium black) were observed for all the catalysts prepared by method A. The catalyst (PS-PCy2)Pd[P(t-Bu)3], prepared by method B, was stable even at 100 ºC, though leaching was observed in the case of catalysts prepared from PS-PPh2 and PS-CH2PPh2. (PS-PCy2)Pd[P(t-Bu)3] prepared by method B can be reused in the amination of chlorotoluene without loss in yield (first run: >95%, second run: >95%).
Bridge damage detection using machine learning algorithms (2021)

The application of accelerated bridge construction (ABC) methods is becoming more widespread owing to their many advantages. In this construction method, prefabricated bridge elements are assembled on-site by establishing in-situ joints to minimize on-site construction time. Despite the improved life-cycle performance and cost benefits of ABC bridges, some concerns exist about the degrading environmental effects on the joints and invisible internal damages. In this study, the long-term performance of an ABC bridge that had been in service for more than 50 years was investigated utilizing machine-learning processes. Observation of reflective cracking on the deck surface and leakage through the joints in this bridge indicated some damage to the bridge longitudinal joints. Damages to the joints are not always visible, nor their extent is known. Therefore, a new damage detection approach is proposed that uses the results of a series of load tests as input in machine-learning techniques with the ultimate aim of detecting the location and severity of joint damages with a high level of certainty. The proposed approach uses the bridge responses obtained from a detailed finite element (FE) model under the assumption of various damage scenarios and predicts the potential damages using the training process of machine-learning algorithms and the actual bridge responses. The results show that the supervised learning algorithm successfully estimated the location and amount of damage in the bridge joints.
Motion Guided Attention Fusion to Recognize Interactions from Videos (2021)

We present a dual-pathway approach for recognizing fine-grained interactions from videos. We build on the success of prior dual-stream approaches, but make a distinction between the static and dynamic representations of objects and their interactions explicit by introducing separate motion and object detection pathways. Then, using our new Motion-Guided Attention Fusion module, we fuse the bottom-up features in the motion pathway with features captured from object detections to learn the temporal aspects of an action. We show that our approach can generalize across appearance effectively and recognize actions where an actor interacts with previously unseen objects. We validate our approach using the compositional action recognition task from the Something-Something-v2 dataset where we outperform existing state-of-the-art methods. We also show that our method can generalize well to real world tasks by showing state-of-the-art performance on recognizing humans assembling various IKEA furniture on the IKEA-ASM dataset.
Cannabinoids modulate hippocampal memory and plasticity (2009)

Considerable evidence demonstrates that cannabinoid agonists impair whereas cannabinoid antagonists improve memory and plasticity. However, recent studies suggest that the effects of cannabinoids on learning do not necessarily follow these simple patterns, particularly when emotional memory processes are involved. We investigated the involvement of the cannabinoid system in hippocampal learning and plasticity using the fear-related inhibitory avoidance (IA) and the non-fear-related spatial learning paradigms, and cellular models of learning and memory, i.e., long-term potentiation (LTP) and long-term depression (LTD). We found that microinjection into the CA1 of the CB1/CB2 receptor agonist WIN55,212-2 (5 μg/side) and an inhibitor of endocannabinoid reuptake and breakdown AM404 (200 ng/side) facilitated the extinction of IA, while the CB1 receptor antagonist AM251 (6 ng/side) impaired it. WIN55,212-2 and AM251 did not affect IA conditioning, while AM404 enhanced it, probably due to a drug-induced increase in pain sensitivity. However, in the water maze, systemic or local CA1 injections of AM251, WIN55,212-2, and AM404 all impaired spatial learning. We also found that i.p. administration of WIN55,212-2 (0.5 mg/kg), AM404 (10 mg/kg), and AM251 (2 mg/kg) impaired LTP in the Schaffer collateral-CA1 projection, whereas AM404 facilitated LTD. Our findings suggest diverse effects of the cannabinoid system on CA1 memory and plasticity that cannot be categorized simply into an impairing or an enhancing effect of cannabinoid activation and deactivation, respectively. Moreover, they provide preclinical support for the suggestion that targeting the endocannabinoid system may aid in the treatment of disorders associated with impaired extinction-like processes, such as post-traumatic stress disorder.
Supplementary Figure S2 from Metformin Synergizes with BCL-XL/BCL-2 Inhibitor ABT-263 to Induce Apoptosis Specifically in p53-Defective Cancer Cells (2023)

&lt;p&gt;Combination of metformin with ABT-263 had no significant growth inhibition effect on HEK-293 cells.&lt;/p&gt;
Homogenization and age hardening behavior in AZ91D magnesium alloy solidified in water-cooled copper mold. (1991)

Microsegregation, homogenization behavior and aging characteristics were investigated in AZ91D magnesium alloy solidified in water-cooled copper mold. Specimens were extracted from a location 1mm away from chill plate because the microstructures with dendrite cell size from 10m to 15m were typical microstructure of diecastings. Minimum
The toronto mindfulness scale: Development and validation (2006)

In this study, the authors both developed and validated a self-report mindfulness measure, the Toronto Mindfulness Scale (TMS). In Study 1, participants were individuals with and without meditation experience. Results showed good internal consistency and two factors, Curiosity and Decentering. Most of the expected relationships with other constructs were as expected. The TMS scores increased with increasing mindfulness meditation experience. In Study 2, criterion and incremental validity of the TMS were investigated on a group of individuals participating in 8-week mindfulness-based stress reduction programs. Results showed that TMS scores increased following treatment, and Decentering scores predicted improvements in clinical outcome. Thus, the TMS is a promising measure of the mindfulness state with good psychometric properties and predictive of treatment outcome.
Caractérisation d'un dépôt multicouches diélectriques par pulvérisation cathodique - application à la réalisation de lasers monomodes à nanostructures quantiques (2010)

National audience
Field Test Results of a New Neutron-Induced Gamma-Ray Spectroscopy Geochemical Logging Tool (2009)

Abstract A new geochemical logging tool has been developed to provide measurements of elements important to the mineralogical analysis of rock formations and geochemical stratigraphy. The measurement system uses a chemical americium-beryllium neutron source to introduce moderate energy neutrons into the surrounding environment. These neutrons lose energy through scattering reactions and are eventually absorbed by materials in the borehole, the formation and the tool itself. The scattering and absorption reactions cause various elements among the atoms in the surrounding materials to emit gamma rays which have characteristic energies. Emitted gamma ray spectra are detected and recorded using a large bismuth germanate scintillation detector coupled to a high-efficiency photomultiplier and pulse-height analyzer. The recorded 256-channel spectra are analyzed to derive individual contributions, or elemental yields, arising from neutron capture reactions involving hydrogen, silicon, calcium, iron, sulfur, potassium, titanium, gadolinium, magnesium, aluminum and chlorine. The spectral analysis is performed with a constrained, weighted least-squares solver to ensure physically meaningful solutions are obtained for the elemental yields. Additional signals from inelastic neutron reactions with oxygen, carbon, silicon, calcium, and iron are treated separately in the spectral fitting process. The paper discusses several subjects including basic operation of the tool, derivation of characteristic elemental spectral responses, processing of the recorded spectra to obtain elemental yields and the conversion to elemental weight fractions for downstream formation mineralogy evaluations. Example logs from initial field tests are presented to demonstrate tool performance under various borehole conditions and lithologic environments including sandstone and carbonate reservoirs as well as organic shales.
Accurate computer‐aided quantification of left ventricular parameters: Experience in 1555 cardiac magnetic resonance studies from the Framingham Heart Study (2011)

Quantitative analysis of short-axis functional cardiac magnetic resonance images can be performed using automatic contour detection methods. The resulting myocardial contours must be reviewed and possibly corrected, which can be time-consuming, particularly when performed across all cardiac phases. We quantified the impact of manual contour corrections on both analysis time and quantitative measurements obtained from left ventricular short-axis cine images acquired from 1555 participants of the Framingham Heart Study Offspring cohort using computer-aided contour detection methods. The total analysis time for a single case was 7.6 ± 1.7 min for an average of 221 ± 36 myocardial contours per participant. This included 4.8 ± 1.6 min for manual contour correction of 2% of all automatically detected endocardial contours and 8% of all automatically detected epicardial contours. However, the impact of these corrections on global left ventricular parameters was limited, introducing differences of 0.4 ± 4.1 mL for end-diastolic volume, -0.3 ± 2.9 mL for end-systolic volume, 0.7 ± 3.1 mL for stroke volume, and 0.3 ± 1.8% for ejection fraction. We conclude that left ventricular functional parameters can be obtained under 5 min from short-axis functional cardiac magnetic resonance images using automatic contour detection methods. Manual correction more than doubles analysis time, with minimal impact on left ventricular volumes and ejection fraction.
Size and Shape Control of Co Nanoparticles With a Cluster Gun (2006)

Nanoscale magnetic and nonmagnetic clusters exhibit unique structures and properties, which are strongly depending on their size and distribution. In this study, we have demonstrated the ability of our cluster gun system to fabricate magnetic nanoparticles (Co) with different size and shape, and studied their magnetic and structural and microstructural properties.
Treatment of PBMC with killed Helicobacter pylori subverts the environment of inflammatory cytokines. (2003)

It is well known that inflammation induced by Helicobacter pylori is characterized by the local production of cytokines and chemokines. In the present study, we analyse the kinetics of MCP-1, IL-12 and IL-4 induction during the interaction of peripheral blood mononuclear cells with killed and/or live H. pylori. Our results demonstrate that live H. pylori does not induce IL-4 release whereas it stimulates MCP-1 and IL-12 production. In addition, the neutralization of IL-12 with monoclonal antibodies determines a lower MCP-1 release. These data demonstrate that MCP-1 production is in part supported by IL-12 induced by live H. pylori. On the contrary, killed H. pylori stimulates the IL-4 but not MCP-1 and IL-12 production. The combined treatment with killed and live H. pylori upregulates the IL-4 production and at the same time downregulates IL-12 and MCP-1 production.
Improved training of cellular SRN using Unscented Kalman Filtering for ADP (2014)

Cellular Simultaneous Recurrent Network (CSRN) is a unique type of recurrent networks that is designed to solve complex optimization problems. This network has already shown to successfully solve many challenging problems such as 2D maze navigation, image registration and affine transformation, game of go, and power system voltage profile prediction. One of the main challenges of using a complex network structure as CSRN is to efficiently train the network. Many representative training algorithms such as Back-propagation Through Time (BPTT), Extended Kalman Filtering (EKF) and Particle Swarm Optimization (PSO) have been used to train CSRN. Our prior works with CSRN suggest that for large number of network inputs, which is very common for large scale maze and image data, computational complexity of computing Jacobian in EKF training becomes prohibitive. In this paper, we propose Unscented Kalman Filter (UKF) for the training of CSRN to avoid computing Jacobian. We show that CSRN trained with UKF can solve the 2D maze traversal problem with better convergence rate than that of EKF. We also report preliminary results on binary image affine transformation wherein CSRN trained with UKF offers comparable performance to that of EKF. A comparison has been obtained between CSRN with GMLP core versus an Elman core trained with UKF for Affine transform results. Finally, we show that for more complex applications such as large scale image processing, UKF is much faster than EKF in training CSRN.
Exact solutions for the propagation of electric and acoustic waves in distributed coupling transducers (1975)

A distributed coupling transducer consists of an acoustic transmission line continuously and reversibly coupled to an electrical transmission line. In such a device it is possible to transfer almost all of the energy from one of the transmission lines to the other transmission line. In particular if the transmission lines are finite in length it is possible to achieve a high efficiency, nonresonant, broad-band electroacoustic transducer. Some of the salient features of the exact solution are as follows: (1) the distance required to achieve complete energy transfer is significantly less than that predicted by approximate theory when the coupling coefficient is large; (2) the amount of energy transferred depends strongly on the termination impedance at the input end of the nondriven line; and (3) the input impedance of the driven line depends on the coupling coefficient and the termination impedance at the input end of the nondriven line. Some of the differences between a continuously coupled and a discretely coupled transducer are presented. [Work supported by NAVSEA 06H1.]