53 research outputs found
Convergence behaviour for the arginine catabolism model.
No full text<p>Plots show the average best fitness values of the Nelder-Mead, PSO, FA and the proposed methods at each iteration.</p
Rosyjski personalizm Mikołaja Bierdiajewa
No full textIm Artikel werden die Anschauungen von Nikolai Bierdjajew in personalistischer Perspektive dargelegt. Der russische Denker wird meistens, besonders aus westeuropäischer Sicht, als religiöser Existentialist (neben Leo Szestow) bezeichnet. Es wird versucht aufzuzeigen, dass es eine nicht völlig berechtigte Einstufung des philosophischen Schaffens von Bierdjajew ist. Im Existentialismus ist nämlich der Ausgangspunkt die Existenz des Individuums, im Personalismus ist es dagegen die Existenz der gemeinschaftlichen relationalen Person. Im Schluss stellt die Verfasserin fest, dass das Denken von Bierdjajew dem personalistischen Dialogismus näher ist als dem Existentialismus.W artykule zostały przedstawione poglądy Mikołaja Bierdiajewa w perspektywie personalistycznej. Zazwyczaj rosyjskiego myśliciela nazywa się, zwłaszcza w recepcji zachodniej, religijnym egzystencjalistą (obok Lwa Szestowa). W artykule wykazuję, że nie jest to w pełni uzasadnione. W egzystencjalizmie punktem wyjścia jest jednostka, w personalizmie jest nim natomiast wspólnotowa, relacyjna osoba. W konkluzji stwierdzam, że myśleniu Bierdiajewa bliżej jest do dialogizmu (personalistycznego), niż do egzystencjalizmu.The article presents Nicholas Berdyaev’s personalistic view. The Russian thinker is usually – especially in the western tradition – called a religious existentialist and as such is situated alongside Lev Shestov. This is not a fully legitimate and sound interpretation of Berdyaev’s philosophical work, which will be proven in the article. In existentialism the starting point is the existence of an individual, while personalism is concerned with the relational and communitarian person. Ultimately, Bierdyaev’s thinking is closer to dialogism (personalistic) than to existentialism
Work-efficient parallel non-maximum suppression for embedded GPU architectures
No full textWith the emergence of GPU computing, deep neural networks have become a widely used technique for advancing research in the field of image and speech processing. In the context of object and event detection, slidingwindow classifiers require to choose the best among all positively discriminated candidate windows. In this paper, we
introduce the first GPU-based non-maximum suppression (NMS) algorithm for embedded GPU architectures. The obtained results show that the proposed parallel algorithm reduces the NMS latency by a wide margin when compared to CPUs, even clocking the GPU at 50% of its maximum frequency on an NVIDIA Tegra K1. In this paper, we show
results for object detection in images. The proposed technique is directly applicable to speech segmentation tasks such as speaker diarization.Peer ReviewedPostprint (published version
Work-efficient parallel non-maximum suppression kernels
No full textIn the context of object detection, sliding-window classifiers and single-shot convolutional neural network (CNN) meta-architectures typically yield multiple overlapping candidate windows with similar high scores around the true location of a particular object. Non-maximum suppression (NMS) is the process of selecting a single representative candidate within this cluster of detections, so as to obtain a unique detection per object appearing on a given picture. In this paper, we present a highly scalable NMS algorithm for embedded graphics processing unit (GPU) architectures that is designed from scratch to handle workloads featuring thousands of simultaneous detections on a given picture. Our kernels are directly applicable to other sequential NMS algorithms such as FeatureNMS, Soft-NMS or AdaptiveNMS that share the inner workings of the classic greedy NMS method. The obtained performance results show that our parallel NMS algorithm is capable of clustering 1024 simultaneous detected objects per frame in roughly 1 ms on both Tegra X1 and Tegra X2 on-die GPUs, while taking 2 ms on Tegra K1. Furthermore, our proposed parallel greedy NMS algorithm yields a 14–40x speed up when compared to state-of-the-art NMS methods that require learning a CNN from annotated data.This work has been partially supported by the Ministerio de Economía y Competitividad under contracts (TIN2015-65316-P, TEC2012-38939-C03-02), the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya under project MPEXPAR: Models de Programació i Entorns d’Execució Paral·lels (2014-SGR-1051), and the European Commission under the Horizon 2020 program (H2020-ICT-644312).Peer ReviewedPostprint (author's final draft
STAT1 signaling pathway is activated by GD-1 treatment.
No full text<p><b>A</b>. The phosphorylation of STAT1 was induced within 1 hr after GD-1 treatment. <b>B</b>. The increase of phosphorylated STAT1 was detected at high concentration of GD-1 (>1 µg/ml). <b>C</b>. The addition of STAT1 inhibitor blocked IFN-γ production induced by GD-1 treatment on a concentration-dependent manner. All ELISA data are representative of at least three independent experiments. Triplicate samples in each time were tested and averaged. Error bars indicate standard deviation. *<i>P</i><0.05. <b>D</b>. The induction of IFN-γ production in GD-1-treated NK-92 cells was inhibited by the addition of STAT1 and NF-κB inhibitors but by STAT3 inhibitor.</p
Activation of PKC isoforms in the GD-1 treated NK-92 cells.
No full text<p><b>A</b>. 200 ng of GD-1 was treated onto NK-92 cells for 20 min. The cell lysates were analyzed by Western blotting with various antibodies against PKC isoforms, including PKD1. <b>B</b>. Phosphorylation of PKD1 was observed at serially diluted GD-1 concentrations with specific antibody to phosphorylated PKD1. <b>C</b>. Phosphorylation of PKD1 was observed to increase in a time-dependent manner within 15 min of GD-1 treatment. <b>D</b>. The addition of Rottlerin, a PKC inhibitor, and CID755673, a PKD inhibitor, has showed inhibitory effect on GD-1-mediated IFN-γ production, which support the increase of IFN-γ production by GD-1 is dependent of PKC signaling pathway. All ELISA data are representative of at least three independent experiments. Triplicate samples in each time were tested and averaged. Error bars indicate standard deviation. *<i>P</i><0.05.</p
IFN-γ production induced by GD-1 is dependent on NF-κB activity.
No full text<p><b>A</b>. GD-1 was treated onto NK-92 cells at 1 to 100 ng/ml concentrations, and several down-stream targets for PKC signaling were analyzed by Western blotting. The phosphorylation of IKK was detected with the concomitant degradation of IκB. ERK and MEK were also phosphorylated by GD-1 treatment. The bands were quantified using Quantity One 1-D Analysis Software (Bio-Rad Laboratories) and p-IKK and IκB expression normalized to control their protein expression. And p-ERK and p-MEK expressions normalized to total their protein expression. The values are given above the blots. <b>B</b>. Inhibitors of NF-κB, Bay11-7082, was treated with a serial dilution from 100 µM with 10 0 ng/ml GD-1, and IFN-γ production was analyzed by ELISA. The addition of Bay11-7082 has showed an inhibitory effect on GD-1 activity to increase IFN-γ production. All ELISA data are representative of at least three independent experiments. Triplicate samples in each time were tested and averaged. Error bars indicate standard deviation. *<i>P</i><0.05. <b>C</b>. The nuclear translocation of p65 (an NF-κB subunit) was observed in GD-1-stimulated NK-92 cells. The modulation of cytoskeleton was observed through Phase contrast images and DAPI was used to visualize nuclei. GD-1 treatment onto NK-92 cells induced nuclear localization of cytosolic p65 transcription factor, which was inhibited by the co-addition of Rottlerin or Bay11-7082.</p
GD-1 regulates the transcription of IFN-γ.
No full text<p><b>A</b>. The effect of GD-1 on IFN-γ production was analyzed by Western blotting of the culture medium after GD-1 treatment at various concentrations (0∼200 ng/ml). The production of IFN-γ increased with the increase of GD-1 concentration. <b>B</b>. The time-dependent increase of IFN-γ secretion was analyzed by ELISA, which showed the production of IFN-γ reached plateau around 3-hr treatment of GD-1. Triplicate samples in each time were tested and averaged. Error bars indicate standard deviation. All ELISA data are representative of at least three independent experiments. *<i>P</i><0.05. <b>C</b>. The production of IFN-γ was increased in a time-dependent manner. 100 ng/ml of GD-1 was treated onto NK-92 cells, and the culture supernatant was taken at various time points for Western blot analysis. IFN-γ production was seemed to begin within 1 hr. Golgistop treatment has showed that GD-1 does not affect the secretory pathway for IFN-γ production. <b>D</b>. Time dependent transcriptional activity for IFN-γ in NK-92 cell after GD-1 treatment was evaluated by RT-PCR. The transcription of IFN-γ was increased within 1 hr after GD-1 treatment.</p
The effects of the flower bud extracts on IFN-γ production and morphological changes. A
No full text<p>. The structure of GD-1 and yuanhuacine isolated from the extract of <i>Daphne genkwa</i> plant. <b>B</b>. ELISA-based assay for IFN-γ production. Total extract (TE) and twenty fractions (1 to 20) were treated on NK-92 and IFN-γ secretion was analyzed by ELISA. Fraction number 10 (#10) and 11 (#11) indicate GD-1 and yuanhuacine, respectively. All ELISA data are representative of at least three independent experiments. <b>C</b>. NK-92 cell morphologies were analyzed microscopically after the treatment of flower extracts. The addition of GD-1 (#10), yuanhuacine (#11) and TE have induced the morphological changes of NK-92 cells, which matches with the pattern of IFN-γ production.</p
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