GI/Geom/1/N/MWV queue with changeover time and searching for the optimum service rate in working vacation period

AbstractIn this paper, we consider a finite buffer size discrete-time multiple working vacation queue with changeover time. Employing the supplementary variable and embedded Markov chain techniques, we derive the steady state system length distributions at different time epochs. Based on the various system length distributions, the blocking probability, probability mass function of sojourn time and other performance measures along with some numerical examples have been discussed. Then, we use the parabolic method to search the optimum value of the service rate in working vacation period under a given cost structure

Application of bronchoscopic argon plasma coagulation in the treatment of tumorous endobronchial tuberculosis: Historical controlled trial

ObjectiveThe purpose of this study was to evaluate the efficacy and safety of bronchoscopic argon plasma coagulation for tumorous endobronchial tuberculosis.MethodsWe analyzed the records of 115 patients with tumorous endobronchial tuberculosis who did not show luminal narrowing of the bronchus at diagnosis. Of these 115 patients, 41 patients received bronchoscopic argon plasma coagulation plus routine antituberculosis chemotherapy (argon plasma coagulation group) and the other 74 patients received only routine antituberculosis chemotherapy (chemotherapy group). The treatment effects between these 2 groups were compared based on changes in lesions, rate of lesion disappearance, and complications associated with bronchoscopic argon plasma coagulation.ResultsThe complete removal rate was 100% in patients in argon plasma coagulation group. About 84.6% lesions disappeared completely in patients in the chemotherapy group. The rate of disappearance of lesions in the argon plasma coagulation group was faster than that of the chemotherapy group. There were no severe complications in the argon plasma coagulation group.ConclusionsBronchoscopic argon plasma coagulation can accelerate the healing of tumorous endobronchial tuberculosis and can help prevent progressive bronchial stenosis resulting from tumorous endobronchial tuberculosis, and it is a very safe method

Ultrafast Video Attention Prediction with Coupled Knowledge Distillation

Large convolutional neural network models have recently demonstrated impressive performance on video attention prediction. Conventionally, these models are with intensive computation and large memory. To address these issues, we design an extremely light-weight network with ultrafast speed, named UVA-Net. The network is constructed based on depth-wise convolutions and takes low-resolution images as input. However, this straight-forward acceleration method will decrease performance dramatically. To this end, we propose a coupled knowledge distillation strategy to augment and train the network effectively. With this strategy, the model can further automatically discover and emphasize implicit useful cues contained in the data. Both spatial and temporal knowledge learned by the high-resolution complex teacher networks also can be distilled and transferred into the proposed low-resolution light-weight spatiotemporal network. Experimental results show that the performance of our model is comparable to ten state-of-the-art models in video attention prediction, while it costs only 0.68 MB memory footprint, runs about 10,106 FPS on GPU and 404 FPS on CPU, which is 206 times faster than previous models

Novel strains with superior degrading efficiency for lincomycin manufacturing biowaste

As the antibiotic pollution source in the environment, a large amount of biowastes generated from antibiotic fermentation manufacture needs proper disposal. Recycling the biowaste as resources and nutrients is of great interest. Besides, degradation or removal of antibiotics is indispensable for the reclamation of antibiotic manufacturing biowaste. To establish environmentally friendly disposal strategies for lincomycin manufacturing biowaste (LMB), we screened the microbial strains that could efficiently degrade lincomycin from the antibiotic wastewater treatment plant. Among them, three novel strains were identified as Bacillus subtilis (strain LMB-A), Rhodotorula mucilaginosa (strain LMB-D) and Penicillium oxalicum (strain LMB-E), respectively. LMB-A and LMB-D could degrade 92.69% and 74.05% of lincomycin with an initial concentration of 1117.55 mg/L in 144 h, respectively. The lincomycin degradation products were formed by the breakage of amide bond or losing N-demethyl/thiomethyl group from the pyrrolidine/pyranose ringcata cata catalyzed by the strains. Moreover, LMB-A could decontaminate LMB, and the decontaminated LMB could be used as a nitrogen source to culture salt-resistant bacteria and other useful microorganisms. LMB-A and LMB-D have the potential to be used for the bioremediation of water and soil polluted by lincomycin and its analogs. LMB-E could degrade 88.20% LMB after 144-h cultivation. In summary, this study gives an insight into the green disposal of LMB, and the established strategy has potential application for biotreatment of other antibiotic fermentation manufacturing biowastes

Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography

Hydraulic tomography (HT) has emerged as a potentially viable method for mapping fractures in geologic media as demonstrated by recent studies. However, most of the studies adopted equivalent porous media (EPM) models to generate and invert hydraulic interference test data for HT. While these models assign significant different hydraulic properties to fractures and matrix, they may not fully capture the discrete nature of the fractures in the rocks. As a result, HT performance may have been overrated. To explore this issue, this study employed a discrete fracture network (DFN) model to simulate hydraulic interference tests. HT with the EPM model was then applied to estimate the distributions of hydraulic conductivity (K) and specific storage (S-s) of the DFN. Afterward, the estimated fields were used to predict the observed heads from DFN models, not used in the HT analysis (i.e., validation). Additionally, this study defined the spatial representative elementary volume (REV) of the fracture connectivity probability for the entire DFN dominant. The study showed that if this spatial REV exists, the DFN is deemed equivalent to EPM and vice versa. The hydraulic properties estimated by HT with an EPM model can then predict head fields satisfactorily over the entire DFN domain with limited monitoring wells. For a sparse DFN without this spatial REV, a dense observation network is needed. Nevertheless, HT is able to capture the dominant fractures.National Science and Technology Major Project of China [2017ZX05008-003-021]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB10030601]; Youth Innovation Promotion Association of the Chinese Academy of Sciences [2016063]; US Civilain Research and Development Foundation (CRDF) under the award: Hydraulic tomography in shallow alluvial sediments: Nile River Valley, Egypt [DAA2-15-61224-1]; Global Expert award through Tianjin Normal University from the Thousand Talents Plan of Tianjin City6 month embargo; published online: 23 April 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Effect of Water Saturation on Gas-Accessible Effective Pore Space in Gas Shales

AbstractThe existence and content of water will certainly affect the effective pore space of shales and therefore is a key point for the evaluation of in-situ gas content and gas flow capacity of shale reservoirs. In order to reasonably evaluate the gas storage and flow capacities of water-bearing shale reservoirs, the effect of water on the effective pore space of shales needs to be understood. In this study, the Upper Permian Longtan shale in the southeastern Sichuan Basin, China, was selected as an example to conduct nuclear magnetic resonance cryoporometry (NMRC) measurements under different water saturation levels. The gas-accessible effective pore spaces in shales under different water saturation levels were quantified, and the effect of water saturation on gas-accessible effective pore space in shales was investigated. The results show that water plays an important role in the gas-accessible effective pore space of shales. When the Longtan shale increases from a dry state to a water saturation of 65%, 75%, and 90%, the gas-accessible effective pore volume decreases by 35%-60% (average 46.3%), 50%-70% (average 58.8%), and 65%-82% (average 75.8%), respectively. Water has an effect on the gas-accessible effective pore space regardless of pore size, and the effect is the strongest in the 4-100 nm range, which may be mainly due to the high content of clay minerals in the Longtan shale. Our studies are of important theoretical significance and application prospects for accurately evaluating the gas-accessible effective pore space of gas shales under actual geological conditions

Size-resolved particle number emissions in Beijing determined from measured particle size distributions

The climate and air quality effects of aerosol particles depend on the number and size of the particles. In urban environments, a large fraction of aerosol particles originates from anthropogenic emissions. To evaluate the effects of different pollution sources on air quality, knowledge of size distributions of particle number emissions is needed. Here we introduce a novel method for determining size-resolved particle number emissions, based on measured particle size distributions. We apply our method to data measured in Beijing, China, to determine the number size distribution of emitted particles in a diameter range from 2 to 1000 nm. The observed particle number emissions are dominated by emissions of particles smaller than 30 nm. Our results suggest that traffic is the major source of particle number emissions with the highest emissions observed for particles around 10 nm during rush hours. At sizes below 6 nm, clustering of atmospheric vapors contributes to calculated emissions. The comparison between our calculated emissions and those estimated with an integrated assessment model GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) shows that our method yields clearly higher particle emissions at sizes below 60 nm, but at sizes above that the two methods agree well. Overall, our method is proven to be a useful tool for gaining new knowledge of the size distributions of particle number emissions in urban environments and for validating emission inventories and models. In the future, the method will be developed by modeling the transport of particles from different sources to obtain more accurate estimates of particle number emissions.Peer reviewe