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Carbon Monoxide Oxidation Promoted by Surface Polarization Charges in a CuO/Ag Hybrid Catalyst.
Composite structures have been widely utilized to improve material performance. Here we report a semiconductor-metal hybrid structure (CuO/Ag) for CO oxidation that possesses very promising activity. Our first-principles calculations demonstrate that the significant improvement in this system's catalytic performance mainly comes from the polarized charge injection that results from the Schottky barrier formed at the CuO/Ag interface due to the work function differential there. Moreover, we propose a synergistic mechanism underlying the recovery process of this catalyst, which could significantly promote the recovery of oxygen vacancy created via the M-vK mechanism. These findings provide a new strategy for designing high performance heterogeneous catalysts
Comparative morphology of the larval mouthparts among six species of Notodontidae (Insecta, Lepidoptera), with discussions on their feeding habits and pupation sites
Larval mouthparts are significant organs for the individual development, morphologically related with feeding habits, and providing valuable characters for taxonomy and phylogenetic analysis. In previous studies, larval mouthparts revealed two identifying characters of Notodontidae. However, the evolutionary driving force and exact definition of these structures remain unsatisfactory. In this study, the larval mouthparts of Euhampsonia cristata (Butler, 1877), Fentonia ocypete (Bremer, 1861), Phalera assimilis (Bremer & Grey, 1853), Nerice davidi Oberthür, 1881, Cerura erminea (Esper, 1783) and Furcula furcula (Clerck, 1759) are morphologically observed and compared using scanning electron microscopy (SEM). The larval mouthparts of the six species are commonly equipped with paired maxillary sacs, congruent with the previous descriptions. However, the larval mouthparts of N. davidi are peculiar for bearing toothed mandibles, providing an exception of Notodontidae. Otherwise, the mouthparts exhibit morphological differences on mandibles, spinnerets, labral notches, and setal arrangements among the six species. The morphological diversity and the related feeding and pupation habits are briefly discussed
Białko CTRP3 zwiększa wrażliwość na insulinę adipocytów 3T3-L1 przez hamowanie procesu zapalnego i poprawę przekazywania sygnału insulinowego
Introduction: C1q/TNF-related Protein-3 (CTRP3) is a novel adipokine with multiple effects such as lowering glucose levels, inhibiting glyconeogenesis in the liver, and increasing angiogenesis and anti-inflammation. But little is known about the effects of CTRP3 on insulin resistance in adipose tissue. This study aims to investigate the effects and mechanisms of CTRP3 on the insulin sensitivity of 3T3-L1 adipocytes.Material and methods: Insulin resistant 3T3-L1 adipocytes were induced by palmic acid cultivation. Such adipocytes were treated with recombinant CTRP3 protein at different concentrations (0, 10, 50, 1,250 ng/mL)for 12 hours, and at a concentration of 250 ng/mL for differing times (2, 6, 12, and 24h). Another group was pre-treated with wortmannin, the special inhibitor of phosphatidylinositol-4,5- bisphosphate 3-kinase (PI3K), for 20 minutes before the treatment with 250 ng/mL CTRP3. The glucose consumption, the glucose uptake, the expression and release of tumour necrosis factor α (TNF-α) and interleukin-6(IL-6) in supernatant, and the protein relative expression of PI3K and protein kinase B (PKB)(ser437) were detected.Results: Compared to the control group, glucose consumption in the CTRP3 intervention group at concentrations of 10, 50, 250, and 1,250 ng/mL was increased by 22.1%, 42.9%, 76.6% and 80.5% respectively (all P < 0.01); the glucose uptake was increased by 39.0%, 68.0%, 108.0% and 111.0% respectively (all P < 0.01); the content of TNF-α in the culture media of CTRP3 (10, 50, 250 ng/mL) intervention group was decreased by 7.6% (P > 0.05), 13.0% (P < 0.05) and 17.4% (P < 0.01) respectively; the content of IL-6 was decreased by 7.1%, 12.4% and 17.1% respectively (all P < 0.01); the protein relative expression of PI3K was increased by 0.63-, 1.00- and 1.36-fold respectively (all P < 0.01), and PKB(ser437) increased by 0.65-, 1.61- and 1.93-fold respectively (all P < 0.01); the mRNA relative expression of GLUT-4 was increased by 23.0%, 47.0% and 62.0% respectively (all P < 0.01). After the treatment with wortmannin, glucose consumption, glucose uptake, PI3K and PKB(ser437) protein relative expression, as well as GLUT-4 mRNA relative expression, was decreased by 53.2%, 44.7%, 43.4%, 56.1 and 30.9% respectively (all P < 0.01).Conclusions: CTRP3 could improve insulin sensitivity of insulin resistant 3T3-L1 adipocytes by decreasing inflammation and ameliorating insulin signalling transduction, indicating that CTRP3 may be a new target for the prevention and cure of insulin resistance and type 2 diabetes. (Endokrynol Pol 2014; 65 (4): 252–258) Wstęp: Białko związane z C1q/TNF typu 3 (CTRP3, C1q/TNF-related Protein-3) jest nowo odkrytą adipokiną o wielorakim działaniu obejmującym obniżenie stężenia glukozy we krwi, hamowanie glukoneogenezy w wątrobie, pobudzanie angiogenezy i działanie przeciwzapalne, Niewiele jednak wiadomo na temat wpływu CTRP3 na insulinooporność komórek tłuszczowych. Badanie to przeprowadzono w celu oceny mechanizmów działania tej adipokiny i jej wpływu na wrażliwość na insulinę adipocytów 3T3-L1.Materiał i metody: Insulinooporne adipocyty 3T3-L1 uzyskano poprzez dodanie do hodowli tych komórek kwasu palmitynowego. Następnie adipocyty te poddano działaniu rekombinowanego białka CTRP3 w różnych stężeniach (0, 10, 50, 1250 ng/ml przez 12 godzin oraz w stężeniu 250 ng/ml przez różny czas (2, 6, 12, 24 godz.). Inną grupę hodowli komórkowych przed dodaniem CTRP3 w stężeniu 250 ng/ml inkubowano wstępnie z wortmaniną, inhibitorem kinazy fosfatydyloinozytolu-4,5 (PI3K, phosphatidylinositol-4,5- bisphosphate 3-kinase) przez 20 minut. Określono zużycie glukozy, wychwyt glukozy, ekspresję i uwalnianie czynnika martwicy nowotworów typu alfa (TNF-α, tumor necrosis factor α) i interleukiny 6 (IL-6, interleukin-6,) w supernatancie oraz ekspresję PI3K i kinazy białkowej B (PKB, protein kinase B) (ser437).Wyniki: Zużycie glukozy w hodowlach poddanych działaniu CTRP3 w stężeniach 10, 50, 250, 1250 ng/ml było większe niż w hodowli kontrolnej odpowiednio o 22,1%, 42,9%, 76,6% i 80,5% (dla wszystkich porównań p < 0,01). Wychwyt glukozy był większy o 39,0%, 68,0%, 108,0% i 111,0% (dla wszystkich porównań p < 0,01) Zawartości TNF-α w medium hodowli komórkowej z dodatkiem CTRP3 (10, 50, 250 ng/ml) były mniejsze odpowiednio o 7,6% (p > 0,05), 13,0% (p < 0,05) i 17,4% (p < 0,01), a zawartości IL-6 były mniejsze o odpowiednio 7,1%, 12,4% i 17,1% (dla wszystkich porównań p < 0,01). Związana z białkami ekspresja PI3K stanowiła odpowiednio 0,63-, 1,00- i 1,36-krotność wartości uzyskanej w hodowli kontrolnej (dla wszystkich porównań p < 0,01), a ekspresja PKB(ser437) stanowiła odpowiednio 0,65-, 1,61- i 1,93-krotność (dla wszystkich porównań p < 0,01); Względna ekspresja mRNA GLUT-4 była większa odpowiednio o 23,0%, 47,0% i 62,0% (dla wszystkich porównań p < 0,01). W hodowlach poddanych wstępnie działaniu wortmaniny zużycie glukozy, signifiwychwyt glukozy, ekspresja PI3K i PKB(ser437) oraz ekspresja mRNA GLUT-4 były mniejsze odpowiednio o 53,2%, 44,7%, 43,4%, 56,1% i 30,9% (dla wszystkich porównań p < 0,01).Wnioski: Białko CTRP3 może powodować zwiększenie wrażliwości na insulinę insulinoopornych adipocytów 3T3-L1 przez hamowanie procesu zapalnego i poprawę przewodzenia sygnałów insulinowych, co wskazuje, że białko to może być nowym celem w zapobieganiu i leczeniu insulinooporności i cukrzycy typu 2. (Endokrynol Pol 2014; 65 (4): 253–258)
Adaptive Control of Resource Flow to Optimize Construction Work and Cash Flow via Online Deep Reinforcement Learning
Due to complexity and dynamics of construction work, resource, and cash
flows, poor management of them usually leads to time and cost overruns,
bankruptcy, even project failure. Existing approaches in construction failed to
achieve optimal control of resource flow in a dynamic environment with
uncertainty. Therefore, this paper introducess a model and method to adaptive
control the resource flows to optimize the work and cash flows of construction
projects. First, a mathematical model based on a partially observable Markov
decision process is established to formulate the complex interactions of
construction work, resource, and cash flows as well as uncertainty and
variability of diverse influence factors. Meanwhile, to efficiently find the
optimal solutions, a deep reinforcement learning (DRL) based method is
introduced to realize the continuous adaptive optimal control of labor and
material flows, thereby optimizing the work and cash flows. To assist the
training process of DRL, a simulator based on discrete event simulation is also
developed to mimic the dynamic features and external environments of a project.
Experiments in simulated scenarios illustrate that our method outperforms the
vanilla empirical method and genetic algorithm, possesses remarkable capability
in diverse projects and external environments, and a hybrid agent of DRL and
empirical method leads to the best result. This paper contributes to adaptive
control and optimization of coupled work, resource, and cash flows, and may
serve as a step stone for adopting DRL technology in construction project
management
Label Mask AutoEncoder(L-MAE): A Pure Transformer Method to Augment Semantic Segmentation Datasets
Semantic segmentation models based on the conventional neural network can
achieve remarkable performance in such tasks, while the dataset is crucial to
the training model process. Significant progress in expanding datasets has been
made in semi-supervised semantic segmentation recently. However, completing the
pixel-level information remains challenging due to possible missing in a label.
Inspired by Mask AutoEncoder, we present a simple yet effective Pixel-Level
completion method, Label Mask AutoEncoder(L-MAE), that fully uses the existing
information in the label to predict results. The proposed model adopts the
fusion strategy that stacks the label and the corresponding image, namely Fuse
Map. Moreover, since some of the image information is lost when masking the
Fuse Map, direct reconstruction may lead to poor performance. Our proposed
Image Patch Supplement algorithm can supplement the missing information, as the
experiment shows, an average of 4.1% mIoU can be improved. The Pascal VOC2012
dataset (224 crop size, 20 classes) and the Cityscape dataset (448 crop size,
19 classes) are used in the comparative experiments. With the Mask Ratio
setting to 50%, in terms of the prediction region, the proposed model achieves
91.0% and 86.4% of mIoU on Pascal VOC 2012 and Cityscape, respectively,
outperforming other current supervised semantic segmentation models. Our code
and models are available at https://github.com/jjrccop/Label-Mask-Auto-Encoder
Generalized Few-shot Semantic Segmentation
Training semantic segmentation models requires a large amount of finely
annotated data, making it hard to quickly adapt to novel classes not satisfying
this condition. Few-Shot Segmentation (FS-Seg) tackles this problem with many
constraints. In this paper, we introduce a new benchmark, called Generalized
Few-Shot Semantic Segmentation (GFS-Seg), to analyze the generalization ability
of simultaneously segmenting the novel categories with very few examples and
the base categories with sufficient examples. It is the first study showing
that previous representative state-of-the-art FS-Seg methods fall short in
GFS-Seg and the performance discrepancy mainly comes from the constrained
setting of FS-Seg. To make GFS-Seg tractable, we set up a GFS-Seg baseline that
achieves decent performance without structural change on the original model.
Then, since context is essential for semantic segmentation, we propose the
Context-Aware Prototype Learning (CAPL) that significantly improves performance
by 1) leveraging the co-occurrence prior knowledge from support samples, and 2)
dynamically enriching contextual information to the classifier, conditioned on
the content of each query image. Both two contributions are experimentally
shown to have substantial practical merit. Extensive experiments on Pascal-VOC
and COCO manifest the effectiveness of CAPL, and CAPL generalizes well to
FS-Seg by achieving competitive performance. Code will be made publicly
available
A new method of fast distance transform 3D image based on “neighborhood between voxels in space” theory
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