886 research outputs found

    Hilbert Based Testing of ADC Differential Non-linearity Using Wavelet Transform Algorithms

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    In testing Mixed Signal Devices such as Analog to Digital and Digital to Analog Converters, some dynamic parameters, such as Differential Non-Linearity and Integral Non-linearity, are very critical to evaluating devises performance. However, such analysis has been notorious for complexity and massive compiling process. Therefore, this research will focus on testing dynamic parameters such as Differential Non-Linearity by simulating numerous numbers of bits Analog to Digital Converters and test the output signals base on new testing algorithms of Wavelet transform based on Hilbert process. Such a new testing algorithm should enhance the testing process by using less compiling data samples and prompt testing results. In addition, new testing results will be compared with the conventional testing process of Histogram algorithms for accuracy and enactment

    On the Economics of the Transition to a Circular Economy

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    Cytotoxic chemotherapy: Still the mainstay of clinical practice for all subtypes metastatic breast cancer

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    Cytotoxic chemotherapy remains central to the treatment of all subtypes of metastatic breast cancer (MBC). We review evidence-based chemotherapy options for women with MBC after an anthracycline and a taxane including re-challenge with anthracycline or taxane, capecitabine, eribulin and ixabepilone as a single agent or combination with capecitabine (not approved in the EU); and the vinca alkaloid vinflunine as single agent or combined with either capecitabine/gemcitabine (also not approved EU or USA). Etirinotecan pegol, comprising irinotecan bound to polyethylene glycol by a biodegradable linker, is a new cytotoxic agent for patients with MBC that has achieved encouraging response rates in phase II studies; it has been further evaluated in the phase III BEACON trial. New cytotoxics should address novel targets or modes of delivery, achieve meaningful improvements in outcomes and seek to identify predictive biomarker(s)

    Ecophysiology of seedlings of three Mediterranean pine species in contrasting light regimes

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    Seasonal dynamics of net photosynthesis (Anet) in 2-year-old seedlings of Pinus brutia Ten., Pinus pinea L. and Pinus pinaster Ait. were investigated. Seedlings were grown in the field in two light regimes: sun (ambient light) and shade (25% of photosynthetically active radiation (PAR)). Repeated measures analyses over a 12-month period showed that Anet varied significantly among species and from season to season. Maximum Anet in sun-acclimated seedlings was low in winter (yet remained positive) and peaked during summer. Maximum Anet was observed in June in P. pinea (12 μmol m–2 s–1), July in P. pinaster (23 μmol m–2 s–1) and August in P. brutia (20 μmol m–2 s–1). Photosynthetic light response curves saturated at a PAR of 200–300 μmol m–2 s–1 in winter and in shade-acclimated seedlings in summer. Net photosynthesis in sun-acclimated seedlings did not saturate at PAR up to 1900 μmol m–2 s–1 in P. brutia and P. pinaster. Minimum air temperature of the preceding night was apparently one of the main factors controlling Anet during the day. In shade-acclimated seedlings, photosynthetic rates were reduced by 50% in P. brutia and P. pinaster and by 20% in P. pinea compared with those in sun-acclimated seedlings. Stomatal conductance was generally lower in shaded seedlings than in seedlings grown in the sun, except on days with a high vapor pressure deficit. Total chlorophyll concentration per unit leaf area, specific leaf area (SLA) and height significantly increased in P. pinea in response to shade, but not in P. pinaster or P. brutia. In response to shade, P. brutia showed a significant increase in total chlorophyll concentration but not SLA. Photosynthetic and growth data indicate that P. pinaster and P. brutia are more light-demanding than P. pinea

    Ecophysiology of seedlings of three Mediterranean pine species in contrasting light regimes

    Get PDF
    Seasonal dynamics of net photosynthesis (Anet) in 2-year-old seedlings of Pinus brutia Ten., Pinus pinea L. and Pinus pinaster Ait. were investigated. Seedlings were grown in the field in two light regimes: sun (ambient light) and shade (25% of photosynthetically active radiation (PAR)). Repeated measures analyses over a 12-month period showed that Anet varied significantly among species and from season to season. Maximum Anet in sun-acclimated seedlings was low in winter (yet remained positive) and peaked during summer. Maximum Anet was observed in June in P. pinea (12 μmol m–2 s–1), July in P. pinaster (23 μmol m–2 s–1) and August in P. brutia (20 μmol m–2 s–1). Photosynthetic light response curves saturated at a PAR of 200–300 μmol m–2 s–1 in winter and in shade-acclimated seedlings in summer. Net photosynthesis in sun-acclimated seedlings did not saturate at PAR up to 1900 μmol m–2 s–1 in P. brutia and P. pinaster. Minimum air temperature of the preceding night was apparently one of the main factors controlling Anet during the day. In shade-acclimated seedlings, photosynthetic rates were reduced by 50% in P. brutia and P. pinaster and by 20% in P. pinea compared with those in sun-acclimated seedlings. Stomatal conductance was generally lower in shaded seedlings than in seedlings grown in the sun, except on days with a high vapor pressure deficit. Total chlorophyll concentration per unit leaf area, specific leaf area (SLA) and height significantly increased in P. pinea in response to shade, but not in P. pinaster or P. brutia. In response to shade, P. brutia showed a significant increase in total chlorophyll concentration but not SLA. Photosynthetic and growth data indicate that P. pinaster and P. brutia are more light-demanding than P. pinea

    FlowerPhenoNet: Automated Flower Detection from Multi-View Image Sequences Using Deep Neural Networks for Temporal Plant Phenotyping Analysis

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    A phenotype is the composite of an observable expression of a genome for traits in a given environment. The trajectories of phenotypes computed from an image sequence and timing of important events in a plant’s life cycle can be viewed as temporal phenotypes and indicative of the plant’s growth pattern and vigor. In this paper, we introduce a novel method called FlowerPhenoNet, which uses deep neural networks for detecting flowers from multiview image sequences for high-throughput temporal plant phenotyping analysis. Following flower detection, a set of novel flower-based phenotypes are computed, e.g., the day of emergence of the first flower in a plant’s life cycle, the total number of flowers present in the plant at a given time, the highest number of flowers bloomed in the plant, growth trajectory of a flower, and the blooming trajectory of a plant. To develop a new algorithm and facilitate performance evaluation based on experimental analysis, a benchmark dataset is indispensable. Thus, we introduce a benchmark dataset called FlowerPheno, which comprises image sequences of three flowering plant species, e.g., sunflower, coleus, and canna, captured by a visible light camera in a high-throughput plant phenotyping platform from multiple view angles. The experimental analyses on the FlowerPheno dataset demonstrate the efficacy of the FlowerPhenoNet

    Increasing atmospheric CO2 concentrations outweighs effects of stand density in determining growth and water use efficiency in Pinus ponderosa of the semi-arid grasslands of Nebraska (U.S.A.)

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    This study investigated the impacts of environmental (e.g., climate and CO2 level) and ecological (e.g., stand density) factors on the long-term growth and physiology of ponderosa pine (Pinus ponderosa) in a semi-arid north American grassland. We hypothesized that ponderosa pine long-term growth patterns were positively influenced by an increase in atmospheric CO2 concentrations and a decrease in stand density. To test this hypothesis, comparison of long-term trends in tree-ring width and carbon and oxygen stable isotopic composition of trees growing in dense and sparse forest stands were carried out at two sites located in the Nebraska National Forest. Results indicated that tree-ring growth increased over time, more at the sparse than at the dense stands. In addition, the carbon and oxygen isotopic ratios showed long-term increases in intrinsic water use efficiency (WUEi), with little difference between dense and sparse stands. We found a clear trend over time in ponderosa pine tree growth and WUEi, mechanistically linked to long-term changes in global CO2 concentration. The study also highlighted that global factors tend to outweigh local effects of stand density in determining long-term trends in ponderosa pine growth. Finally, we discuss the implications of these results for woody encroachment into grasslands of Nebraska and we underlined how the use of long-term time series is crucial for understanding those ecosystems and to guarantee their conservation

    Challenges and Knowledge Gaps with Immune Checkpoint Inhibitors Monotherapy in the Management of Patients with Non-Small-Cell Lung Cancer: a Survey of Oncologist Perceptions

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    Background: Immune checkpoint-inhibitors (ICIs) are changing outcomes in different cancer settings, notably for patients with non-small-cell lung cancer (NSCLC). There are, however, still important gaps of evidence for clinical practice when using these novel treatments. In this study, we assessed physicians' opinion and experience on challenges for clinical practice with ICIs monotherapy in NSCLC. Methods: A survey was conducted on experienced physicians treating patients with NSCLC with ICIs. Two rounds of pilot tests were carried out for validation among a group of experts. Topics under analysis were in relation to treatment of elderly populations, performance status, brain metastases, use of steroids or antibiotics, the effects of gut microbiome, autoimmune diseases, human immunodeficiency virus infection, solid organ transplants, use of anti-programmed cell death protein 1 versus anti-programmed death-ligand 1 drugs, atypical tumour responses, predictors of response, duration of treatment and a final open question on additional relevant challenges. Results: Two hundred and twenty-one answers were collected, including 106 (48%) valid answers from experts for final analysis (physicians who have treated at least 20 patients with NSCLC with ICIs). The vast majority agreed that the selected topics in this study are important challenges ahead and more evidence is needed. Moreover, predictors of response, treating brain metastasis, shorter duration of treatment, the effects of gut microbiome and concomitant use of steroids were voted the most important topics to be further addressed in prospective clinical research. Conclusions: This survey contributed to understanding which are the main challenges for clinical practice with ICIs monotherapy in NSCLC. It can also contribute to guide further clinical research, considering the opinions and experience of those who regularly treat NSCLC patients with ICIs.info:eu-repo/semantics/publishedVersio

    Higher Order Integrability in Generalized Holonomy

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    Supersymmetric backgrounds in M-theory often involve four-form flux in addition to pure geometry. In such cases, the classification of supersymmetric vacua involves the notion of generalized holonomy taking values in SL(32,R), the Clifford group for eleven-dimensional spinors. Although previous investigations of generalized holonomy have focused on the curvature \Rm_{MN}(\Omega) of the generalized SL(32,R) connection \Omega_M, we demonstrate that this local information is incomplete, and that satisfying the higher order integrability conditions is an essential feature of generalized holonomy. We also show that, while this result differs from the case of ordinary Riemannian holonomy, it is nevertheless compatible with the Ambrose-Singer holonomy theorem.Comment: 19 pages, Late
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