gebhart/patrepeval huggingface dataset:
Modulation of Tomato Response to Rhizoctonia solani by Trichoderma harzianum and Its Secondary Metabolite Harzianic Acid (2018)

The present study investigated the transcriptomic and metabolomic changes elicited in tomato plants (<i>Solanum lycopersicum</i> cv. Micro-Tom) following treatments with the biocontrol agent <i>Trichoderma harzianum</i> strain M10 or its purified secondary metabolite harzianic acid (HA), in the presence or the absence of the soil-borne pathogen <i>Rhizoctonia solani</i>. Transcriptomic analysis allowed the identification of differentially expressed genes (DEGs) that play a pivotal role in resistance to biotic stress. Overall, the results support the ability of <i>T. harzianum</i> M10 to activate defense responses in infected tomato plants. An induction of hormone-mediated signaling was observed, as shown by the up-regulation of genes involved in the ethylene and jasmonate (ET/JA) and salicylic acid (SA)-mediated signaling pathways. Further, the protective action of <i>T. harzianum</i> on the host was revealed by the over-expression of genes able to detoxify cells from reactive oxygen species (ROS). On the other hand, HA treatment also stimulated tomato response to the pathogen by inducing the expression of several genes involved in defense response (including protease inhibitors, resistance proteins like CC-NBS-LRR) and hormone interplay. The accumulation of steroidal glycoalkaloids in the plant after treatments with either <i>T. harzianum</i> or HA, as determined by metabolomic analysis, confirmed the complexity of the plant response to beneficial microbes, demonstrating that these microorganisms are also capable of activating the chemical defenses.
A Radio Resource Management strategy for downlink cooperation in distributed networks (2007)

This paper has been withdrawn by the author
24.7 A 673µW 1.8-to-2.5GHz dividerless fractional-N digital PLL with an inherent frequency-capture capability and a phase-dithering spur mitigation for IoT applications (2017)

The Internet-of-Things (IoT) is gaining momentum, and the ultra-low-power (ULP) RF transceiver is one of the key enablers. Generation of the local oscillator (LO) consumes a significant share of the total energy of these ULP transceivers which are typically powered by small batteries. Therefore, a fractional-N PLL needs to perform LO frequency synthesis and modulation with a very stringent power budget, i.e., below 1mW [1]. A digital PLL is favored in these applications because of the benefit of small area, which is also a critical cost consideration in IoT. On the other hand, the LO quality generated by these ULP PLLs cannot be compromised, and it needs to fulfil the RF requirements defined in the IoT standards, e.g., Bluetooth Low Energy (BLE). Although the integrated phase error is less stringent in IoT standards, the spectral purity requirements remain critical in order to fulfill the regional spectrum regulations, e.g., FCC. A high fractional spur level due to the non-linearity in PLLs (e.g., from a TDC) introduces the unwanted emission. In this work, we present a ULP dividerless digital PLL with a power-efficient spur-mitigation technique. Furthermore, one of the critical issues of the dividerless (or sub-sampling) PLLs, the lack of frequency capture capability without the assistance of an extra power-hungry frequency-locked-loop (FLL), is addressed and mitigated by the proposed digital phase unwrap technique.
Excitation‐Emission‐Matrix Fluorescence Spectroscopy of Soil Water Extracts to Predict Nitrogen Mineralization Rates (2018)

Core Ideas EEM spectroscopy was used to characterize soluble OM pools in agricultural soils. PARAFAC was used to quantify OM meaningful EEM spectral components. PARAFAC components were correlated to N mineralization rates in specific sites. NPLS modeling of EEM data can estimate N mineralization rates in diverse soils. Rapid, easy, and frequent prediction of gross or potential nitrogen mineralization rates (GNMR and PNMR, respectively) is desirable for improved understanding and quantification of soil N dynamics and for enabling advanced sustainable N management. Our goal was to extend the use of excitation–emission matrix (EEM) fluorescence spectroscopy to characterize constituents of soluble organic matter (OM) pools in agricultural soils and to couple these characterizations with advanced chemometric techniques to improve prediction of PNMR and GNMR. To achieve this, EEM‐based predictions must be valid across diverse soils, climates, and management systems. Accordingly, we analyzed soil water extracts spanning a broad range of OM contents from midwest United States (MUS) and Israeli (ISL) agroecosystems under organic‐ and mineral‐based N management strategies. Parallel factors analysis, a multiway data analysis method, was used to quantify meaningful EEM spectral components, which were used to detect changes in labile soil OM pools and to predict N mineralization rates. N‐way partial least squares regression (NPLS) was also applied to EEM data to obtain spectral factors correlated to total organic carbon concentration potential and gross N mineralization rates. This NPLS analysis led to reliable estimation of all three tested properties for ISL and MUS soils.
Token Labeling: Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (2021)

This paper provides a strong baseline for vision transformers on the ImageNet
classification task. While recent vision transformers have demonstrated
promising results in ImageNet classification, their performance still lags
behind powerful convolutional neural networks (CNNs) with approximately the
same model size. In this work, instead of describing a novel transformer
architecture, we explore the potential of vision transformers in ImageNet
classification by developing a bag of training techniques. We show that by
slightly tuning the structure of vision transformers and introducing token
labeling -- a new training objective, our models are able to achieve better
results than the CNN counterparts and other transformer-based classification
models with similar amount of training parameters and computations. Taking a
vision transformer with 26M learnable parameters as an example, we can achieve
an 84.4% Top-1 accuracy on ImageNet. When the model size is scaled up to
56M/150M, the result can be further increased to 85.4%/86.2% without extra
data. We hope this study could provide researchers with useful techniques to
train powerful vision transformers. Our code and all the training details will
be made publicly available at https://github.com/zihangJiang/TokenLabeling.
Effect of a new potent H2-blocker, 3-]]]2-[(diaminomethylene)amino]-4-thiazolyl]methyl]-thio]-N2-sulfamoylpropionamidine (YM-11170) on gastric secretion induced by histamine and food in conscious dogs. (1982)

The inhibitory effect of a new H2-receptor antagonist YM-11170 on gastric acid response to histamine and food was compared with that of cimetidine in the conscious dog with a Heidenhain pouch. When given intravenously at a steady state of gastric secretion by continuous infusion of histamine. YM-11170 was 42 times more potent and 1.3 times longer-lasting (p less than 0.05) than cimetidine in reducing the total acid output. The higher potency of YM-11170 than that of cimetidine was also demonstrated in oral antisecretory tests with histamine. The oral ED50 relative to i.v. ED50 as an indirect indication of absorption rate of the drugs was 2.9 for YM-11170 and 2.7 for cimetidine. The secretory response to food stimulation was also antagonized by oral administration of YM-11170 with 40 times greater potency than that of cimetidine. The antisecretory effects of the drugs on the histamine-induced gastric secretion were characterized by a marked decrease in the secretory volume. No behavioral change was observed in association with the H2-blockers. These results indicate that YM-11170 is a very potent inhibitor of gastric acid secretion and also suggest that the absorption rate of YM-11170 from the gastro-intestinal tract is similar to that of cimetidine.
Drug-Eluting Stents To Prevent Reblockage of Coronary Arteries (2003)

Restenosis limits the success of percutaneous transluminal coronary interventions. Coronary artery stenting decreases restenosis, improves outcomes, and is currently the most commonly used percutaneous coronary intervention in the United States. However, in-stent restenosis continues to occur at an unacceptable rate. In-stent restenosis is a neointimal hyperplastic response resulting primarily from vascular smooth muscle cell proliferation. Treatment with anti-proliferative agents presents a logical approach to eradicating restenosis, however, these drugs are highly toxic. Coating stents with anti-proliferative agents allows local delivery of high doses and avoids systemic side effects. In 2001, the results of two clinical trials, RAVEL and ELUTES, using sirolimus- and paclitaxil-coated stents demonstrated nearly complete elimination of in-stent restenosis. These dramatic results represent a tremendous advance in the treatment of coronary heart disease.
Combination Therapy with Anti-PD-1, Anti-TIM-3, and Focal Radiation Results in Regression of Murine Gliomas (2016)

This is the first preclinical investigation on the effects of dual PD-1 and TIM-3 blockade with radiation. We also demonstrate the presence of TIM-3 in human glioblastoma multiforme and provide preclinical evidence for a novel treatment combination that can potentially result in long-term glioma survival and constitutes a novel immunotherapeutic strategy for the treatment of glioblastoma multiforme. Clin Cancer Res; 23(1); 124-36. ©2016 AACR.
Dendritic Cells Derived from Acute Myelogenous Leukaemia (AML) Have a Type 2 Cytokine Bias (2003)

Conference Abstract| April 01 2003 Dendritic Cells Derived from Acute Myelogenous Leukaemia (AML) Have a Type 2 Cytokine Bias Nicki Panoskaltsis; Nicki Panoskaltsis 1Antigen Presentation Research Group, Faculty of Medicine, Imperial College London, Northwick Park Campus, Harrow Search for other works by this author on: This Site PubMed Google Scholar Stella C. Knight; Stella C. Knight 2Antigen Presentation Research Group, Faculty of Medicine, Imperial College London, Northwick Park Campus, Harrow Search for other works by this author on: This Site PubMed Google Scholar Cecil D.L. Reid Cecil D.L. Reid 3Department of Haematology, North West London Hospitals NHS Trust, Northwick Park Hospital, Harrow Search for other works by this author on: This Site PubMed Google Scholar Clin Sci (Lond) (2003) 104 (s49): 53P. https://doi.org/10.1042/cs104053Pa Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Cite Icon Cite Get Permissions Citation Nicki Panoskaltsis, Stella C. Knight, Cecil D.L. Reid; Dendritic Cells Derived from Acute Myelogenous Leukaemia (AML) Have a Type 2 Cytokine Bias. Clin Sci (Lond) 1 April 2003; 104 (s49): 53P. doi: https://doi.org/10.1042/cs104053Pa Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsClinical Science Search Advanced Search This content is only available as a PDF. © 2003 The Biochemical Society and the Medical Research Society2003 Article PDF first page preview Close Modal You do not currently have access to this content.
Learning to recognize objects in egocentric activities (2011)

This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know only the names of the objects which are present within it, and have no other knowledge regarding the appearance or location of objects. The key to our approach is a robust, unsupervised bottom up segmentation method, which exploits the structure of the egocentric domain to partition each frame into hand, object, and background categories. By using Multiple Instance Learning to match object instances across sequences, we discover and localize object occurrences. Object representations are refined through transduction and object-level classifiers are trained. We demonstrate encouraging results in detecting novel object instances using models produced by weakly-supervised learning.
Triglyceride-rich lipoproteins in chronic kidney disease patients undergoing maintenance haemodialysis treatment (2012)

Plasma RLP-C levels were high, and the TG/RLP-C ratio was low in CKD patients undergoing HD treatment. These findings indicate that total plasma TG-rich lipoprotein levels were not increased, but the distribution of plasma TG-rich lipoproteins were skewed towards remnant fractions in CKD patients undergoing HD treatment; these plasma TG-rich lipoproteins appear to be more atherogenic than those in controls.
Improving the efficiency of a standard compliant wireless battery charger (2012)

In this paper, a wireless charger for portable electronics devices is presented. A power transmitter, also known as the magnetic pad, and a power receiver are magnetically coupled. A receiver architecture which improves the power conversion efficiency is proposed. All advantages brought by the proposed architecture are discussed and standard constraints are presented as well. The receiver is fully standard-compliant. A wireless station for mobile application is designed and tested. Simulation and experimental results are compared. As shown by experimental results, thanks to the proposed architecture the power conversion efficiency of the receiver section is really close to a unit value. Power losses on the receiver side could be reasonably neglected. The wireless station efficiency now depends on the inductive coupling losses only.
Exposure to sorbitol induces resistance to cisplatin in human non-small-cell lung cancer cell lines. (1997)

Cisplatin is the most active anticancer agent for lung cancer. It has been reported that intracellular accumulation of cisplatin is important in determining resistance to cisplatin, which may be modulated by Na+, K(+)-ATPase activity. On the other hand, it is well-known that sorbitol, a metabolite of glucose mediated by aldose reductase, reduces Na+, K(+)-ATPase in diabetic neuropathy. In this study, the effect of exogenous sorbitol on Na+, K(+)-ATPase activity and sensitivity to cisplatin was evaluated using human non-small-cell lung cancer (NSCLC) cell lines. In the NSCLC cell lines, EBC-1, PC-3, and RERF-LC-MS the cytotoxicities of cisplatin were impaired by exposure to sorbitol in these cell lines. Na+, K(+)-ATPase was inactivated and intracellular accumulation of cisplatin was decreased by the exposure. These results suggest that accumulation of sorbitol may induce resistance to cisplatin in NSCLC cells, and diabetes poorly controlled may be one of the determinants of the antitumor effect of cisplatin in NSCLC.
Reactive collisions of sulfur dioxide with molten carbonates (2010)

Molecular beam scattering experiments are used to investigate reactions of SO(2) at the surface of a molten alkali carbonate eutectic at 683 K. We find that two-thirds of the SO(2) molecules that thermalize at the surface of the melt are converted to gaseous CO(2) via the reaction SO(2)(g) + CO(3)(2-) --> CO(2)(g) + SO(3)(-2). The CO(2) product is formed from SO(2) in less than 10(-6) s, implying that the reaction takes place in a shallow liquid region less than 100 A deep. The reaction probability does not vary between 683 and 883 K, further implying a compensation between decreasing SO(2) residence time in the near-interfacial region and increasing reactivity at higher temperatures. These results demonstrate the remarkable efficiency of SO(2) --> CO(2) conversion by molten carbonates, which appear to be much more reactive than dry calcium carbonate or wet slurries commonly used for flue gas desulfurization in coal-burning power plants.
Evaluation of the Potential Sensitization of Chlorogenic Acid: A Meta-Analysis (2013)

Chlorogenic acid (CGA) widely exists in many plants, which are used as medicinal substances in traditional Chinese medicine injectables (TCMIs) that have been widely applied in clinical treatments. However, it is still controversial whether CGA is responsible for TCMIs-related hypersensitivity. Several studies have been performed to evaluate its potential sensitization property, but the results were inconclusive. Therefore, the aim of this study was to evaluate its potential sensitization systematically using meta-analysis based on data extracted from literatures, searching databases of PubMed, EMBASE, ISI Web of Knowledge, CNKI, VIP, and CHINAINFO from January 1979 to October 2012, a total of 108 articles were retrieved by electronic search strategy, out of which 13 studies met the inclusion criteria. In ASA test, odds ratio of behavior changes was 4.33 (1.62, 11.60), showing significant changes after CGA treatment (P = 0.004). Serum IgG, serum histamine, PLN cellularity, and IgG1 AFCs were significantly enhanced after CGA treatment (P < 0.05). Totally, these results indicated that CGA could induce a positive reaction in potential sensitization, and intravenous administration of it might be a key factor for sensitization triggering, which could at least warrant more careful application of TCMIs containing CGA in clinical practices.
Automatic test factoring for java (2005)

Test factoring creates fast, focused unit tests from slow system-wide tests; each new unit test exercises only a subset of the functionality exercised by the system test. Augmenting a test suite with factored unit tests should catch errors earlier in a test run.One way to factor a test is to introduce mock objects. If a test exercises a component T, which interacts with another component E (the environment), the implementation of E can be replaced by a mock. The mock checks that T's calls to E are as expected, and it simulates E's behavior in response. We introduce an automatic technique for test factoring. Given a system test for T and E, and a record of T's and E's behavior when the system test is run, test factoring generates unit tests for T in which E is mocked. The factored tests can isolate bugs in T from bugs in E and, if E is slow or expensive, improve test performance or cost.Our implementation of automatic dynamic test factoring for the Java language reduces the running time of a system test suite by up to an order of magnitude.
Effect of Geometric Parameters on Simplex Atomizer Performance (2004)

A computational analysis of flow in simplex fuel atomizers using the arbitrary-Lagrangian‐Eulerian method is presented. It is well established that the geometry of an atomizer plays an important role in governing its performance. We have investigated the effect on atomizer performance of four geometric parameters, namely, inlet slot angle, spin chamber convergence angle, trumpet angle, and trumpet length. For a constant mass flow rate through the atomizer, the atomizer performance is monitored in terms of dimensionless film thickness, spray cone half-angle, and discharge coefficient. Results indicate that increase in inlet slot angle results in lower film thickness and discharge coefficient and higher spray cone angle. The spin chamber converge angle has an opposite effect on performance parameters, with film thickness and discharge coefficient increasing and the spray cone angle decreasing with increasing convergence angle. For a fixed trumpet length, the trumpet angle has very little influence on discharge coefficient. However, the film thickness decreases, and spray cone angle increases with increasing trumpet angle. For a fixed trumpet angle, the discharge coefficient is insensitive to trumpet length. Both the spray cone angle and the film thickness are found to decrease with trumpet length. Analytical solutions are developed to determine the atomizer performance considering inviscid flow through the atomizer. The qualitative trends in the variation of film thickness at the atomizer exit, spray cone angle, and discharge coefficient predicted by inviscid flow analysis are seen to agree well with computational results.
New Effect in Dynamic Polarization (1967)

A new effect in dynamic polarization is found showing characteristics similar to those of the "solid effect" but with significant difference in the spacing between enhancement peaks. A possible explanation, ascribing it to the electron spin-spin interaction, is discussed.
Abnormal Duodenal Bile Composition in Patients With Acalculous Chronic Cholecystitis (1998)

Some patients with acalculous chronic cholecystitis have duodenal bile samples characterized by a decreased bile acid concentration and a decreased proportion of biliary phospholipids. The low biliary bile acid concentration may result from impaired gallbladder contraction and/or secretion by the biliary tract epithelium. The low proportion of phospholipid may result from posthepatic hydrolysis of luminal phosphatidylcholine followed by absorption of the hydrolysis products. The latter process could be caused by and/or contribute to mucosal inflammation and would also elevate the cholesterol saturation of bile, increasing the risk for cholesterol gallstone formation.
Path Aggregation Network for Instance Segmentation (2018)

The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framework. Specifically, we enhance the entire feature hierarchy with accurate localization signals in lower layers by bottom-up path augmentation, which shortens the information path between lower layers and topmost feature. We present adaptive feature pooling, which links feature grid and all feature levels to make useful information in each level propagate directly to following proposal subnetworks. A complementary branch capturing different views for each proposal is created to further improve mask prediction. These improvements are simple to implement, with subtle extra computational overhead. Yet they are useful and make our PANet reach the 1st place in the COCO 2017 Challenge Instance Segmentation task and the 2nd place in Object Detection task without large-batch training. PANet is also state-of-the-art on MVD and Cityscapes.
Impact of care at comprehensive cancer centers on outcome: Results from a population‐based study (2015)

Among individuals aged 22 to 65 years residing in Los Angeles County with newly diagnosed adult-onset cancer, those who were treated at NCICCCs experienced superior survival compared with those treated at non-NCICCC facilities. Barriers to care at NCICCCs included race/ethnicity, insurance, socioeconomic status, and distance to an NCICCC.
A novel scheme to reduce test application time in circuits with full scan (1995)

This paper proposes a hybrid method of combining sequential testing with scan testing in circuits with full scan capability. One shortcoming of full scan testing of sequential circuits is the high test application time. The goal of our scheme is to obtain shorter test application times while achieving detection of both the classical stuck-at faults as well as nonclassical faults such as delay faults. An algorithm for test generation in this hybrid scheme is described. Experimental results demonstrating the effectiveness of our approach on ISCAS '89 sequential benchmark circuits are presented. Results for the stuck-at fault model and the transition fault model (which represents a simplified model for delay faults) are presented. Significant reduction in test application time is shown possible.
Coherent Control of Photocurrent Generation in Bulk Semiconductors (1996)

We show theoretically that interband transitions in a bulk semiconductor via coherent one- and two-photon absorption leads to the formation of an electrical current whose direction is controlled by the relative phase of the beams. The phenomenon can occur in centrosymmetric and noncentrosymmetric materials; easily measurable currents are predicted for GaAs under realistic experimental conditions.