Optimal subsampling for large scale Elastic-net regression

Datasets with sheer volume have been generated from fields including computer vision, medical imageology, and astronomy whose large-scale and high-dimensional properties hamper the implementation of classical statistical models. To tackle the computational challenges, one of the efficient approaches is subsampling which draws subsamples from the original large datasets according to a carefully-design task-specific probability distribution to form an informative sketch. The computation cost is reduced by applying the original algorithm to the substantially smaller sketch. Previous studies associated with subsampling focused on non-regularized regression from the computational efficiency and theoretical guarantee perspectives, such as ordinary least square regression and logistic regression. In this article, we introduce a randomized algorithm under the subsampling scheme for the Elastic-net regression which gives novel insights into L1-norm regularized regression problem. To effectively conduct consistency analysis, a smooth approximation technique based on alpha absolute function is firstly employed and theoretically verified. The concentration bounds and asymptotic normality for the proposed randomized algorithm are then established under mild conditions. Moreover, an optimal subsampling probability is constructed according to A-optimality. The effectiveness of the proposed algorithm is demonstrated upon synthetic and real data datasets.Comment: 28 pages, 7 figure

Effects of the novel catalyst Ni–S2O82−–K2O/TiO2 on efficient lignin depolymerization

To improve the utilization of lignin, much effort has been devoted to lignin depolymerization with the aim to decrease waste and enhance profitability. Here, a dual property (acid and base) catalyst, namely S2O8 2−–K2O/TiO2, was carefully researched. Upon loading S2O8 2− and K2O onto TiO2, acid and base sites emerged, and S2O8 2− and K2O mutually enhanced the acid and base strengths of the catalyst enormously; this indeed facilitated lignin depolymerization. Under appropriate conditions, the yields of liquid product, petroleum ether soluble (PEsoluble) product and total monomer products were 83.76%, 50.4% and 28.96%, respectively. The constituents of the PE-soluble fraction, which are mainly monomers and dimers, can be used as liquid fuels or additives. In addition, after the catalyst was modified by Ni, better results were obtained. Surprisingly, it was found that the Ni enhanced not only the hydrogenation capacity but also the acidity. The highest high heating value (HHV) of the liquid product (33.6 MJ kg−1) was obtained, and the yield of PE-soluble product increased from 50.4 to 56.4%. The product can be utilized as a fuel additive or be converted to bio-fuel. This catalysis system has significant potential in the conversion of lignin to bio-fuel

Estimates of daily ground-level NO2 concentrations in China based on big data and machine learning approaches

Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants. However, current ground-level NO2 concentration data are lack of either high-resolution coverage or full coverage national wide, due to the poor quality of source data and the computing power of the models. To our knowledge, this study is the first to estimate the ground-level NO2 concentration in China with national coverage as well as relatively high spatiotemporal resolution (0.25 degree; daily intervals) over the newest past 6 years (2013-2018). We advanced a Random Forest model integrated K-means (RF-K) for the estimates with multi-source parameters. Besides meteorological parameters, satellite retrievals parameters, we also, for the first time, introduce socio-economic parameters to assess the impact by human activities. The results show that: (1) the RF-K model we developed shows better prediction performance than other models, with cross-validation R2 = 0.64 (MAPE = 34.78%). (2) The annual average concentration of NO2 in China showed a weak increasing trend . While in the economic zones such as Beijing-Tianjin-Hebei region, Yangtze River Delta, and Pearl River Delta, the NO2 concentration there even decreased or remained unchanged, especially in spring. Our dataset has verified that pollutant controlling targets have been achieved in these areas. With mapping daily nationwide ground-level NO2 concentrations, this study provides timely data with high quality for air quality management for China. We provide a universal model framework to quickly generate a timely national atmospheric pollutants concentration map with a high spatial-temporal resolution, based on improved machine learning methods

The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and International Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. Twenty four valid state-of-the-art liver and liver tumor segmentation algorithms were applied to a set of 131 computed tomography (CT) volumes with different types of tumor contrast levels (hyper-/hypo-intense), abnormalities in tissues (metastasectomie) size and varying amount of lesions. The submitted algorithms have been tested on 70 undisclosed volumes. The dataset is created in collaboration with seven hospitals and research institutions and manually reviewed by independent three radiologists. We found that not a single algorithm performed best for liver and tumors. The best liver segmentation algorithm achieved a Dice score of 0.96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0.67(ISBI) and 0.70(MICCAI). The LITS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.Comment: conferenc

Efficient Synthesis of Liquid Fuel Intermediates from Furfural and Levulinic Acid via Aldol Condensation over Hierarchical MFI Zeolite Catalyst

A water-tolerant, basic, and hierarchical MFI zeolite catalyst was synthesized and applied in the aldol condensation reaction between biomass-derived furfural and levulinic acid. The results showed that the addition of poly(diallyl dimethylammonium chloride) significantly affected the textural and acid-base properties of hierarchical zeolite, which subsequently influenced the catalytic performance of hierarchical zeolite. In the aqueous phase, potassium-modified, hierarchical MFI zeolite (K/H-MFI-n) was more active for aldol condensation between furfural and levulinic acid than the potassium-modified, conventional MFI zeolite (K/MFI). This was ascribed to higher basic sites density and improved diffusion limitation of K/H-MFI-n. A 70.6% yield of aldol condensation product was achieved with a complete conversion of furfural at 100 degrees C for 9 h by K/H-MFI-0.6. However, only 27.4% yield of aldol condensation product with 55.1% furfural conversion was obtained by K/MFI at the same condition. Two major isomeric aldol products, beta-furfurylidenelevulinic acid and delta-furfurylidenelevulinic acid (beta-FDLA and delta-FDLA), were obtained after acidification. K/H-MFI-n displayed an enhanced selectivity (54.9%) to delta-FDLA, owing to the stronger basicity of K/H-MFI-n. However, K/MFI showed a preferred selectivity to beta-FDLA (42.7%), owing to the dominant Lewis acidity. Recyclability research showed that the catalytic performance of potassium-modified, hierarchical MFI zeolite was acceptable after five runs

Numerical analysis on combustion characteristics of diffusion jet flame under different gravity environments

To study the combustion characteristics of turbulent jet flames under different gravity environments, the centerline temperature distribution curve and air entrainment rate of turbulent jet flame from microgravity to hyper gravity was carried out by CFD simulation. Five different gravity values have been considered. The simulation results show that the flame temperature decreases with the increase of gravity in the intermittent flame region and plume region. The maximum temperature decreases with the increase of gravity, while their position decreases accordingly. The evolution of air entrainment has been analyzed under different gravity environments. Based on the hydroxyl concentration distribution, a correlation of flame height has been obtained through dimensionless analysis. The evolution of air entrainment has been described under different heat release rate and gravity environments

Catalytic depolymerization of Kraft lignin to produce liquid fuels via Ni-Sn metal oxide catalysts

In this study, Ni-Sn metal oxide catalysts, with strong Lewis acidity, were prepared and applied in lignin depolymerization to produce liquefied fuels. The Ni-Sn metal oxide catalysts could cleave the lignin linkages and stabilize the reaction intermediates due to the high Lewis acidity and the hydrogenation of nickel sites. When the molar ratio of nickel to tin was 1 : 3, a liquid product yield of 90% and a petroleum ether soluble product (mainly monomers and dimer degradation products) yield of 60% were obtained at 310 degrees C for 24 h. Under these reaction conditions, the petroleum ether soluble product had a higher heating value (HHV) (36.45 MJ kg(-1)) than Kraft lignin (25.83 MJ kg(-1)). A meticulous study on Ni-Sn metal oxide catalysts revealed that Lewis acidity and the synergistic effect between Ni and Sn played an important role in lignin depolymerization

Production of liquefied fuel from depolymerization of kraft lignin over a novel modified nickel/H-beta catalyst

In this study, a novel modified nickel/H-beta (Ni/DeAl-beta) catalyst, which has active acidic sites and hydrogen binding sites, was prepared and used to produce liquefied fuel from lignin. The bifunctional Ni/DeAl-beta catalyst efficiently converted kraft lignin into liquefied fuel due to the synergistic effect of aluminum Lewis acid sites and nickel hydrogen binding sites. At a nickel content of 0.6 mmol/g(zeolite), the Ni/DeAl-beta catalyst gave a high liquid product yield of 88.6% at 300 degrees C for 36 h. Most of the liquid product was dissolved in petroleum ether (73% of 88.6%), which was mainly composed of monomeric and dimeric degradation products. Under these conditions, the higher heating values (HHV) increased from 24.9 MJ/kg for kraft lignin to 32.0 MJ/kg for the liquid product. These results demonstrated the bifunctional Ni/DeAl-beta catalyst could be an efficient catalyst for lignin to liquefied fuel conversion

Apolipoprotein A-V Is a Novel Diagnostic and Prognostic Predictor in Pediatric Patients with Sepsis: A Prospective Pilot Study in PICU

Background. Sepsis induces the release of lipid mediators, which control both lipid metabolism and inflammation. However, the role of serum apolipoprotein A-V (ApoA5) in sepsis is poorly understood in pediatric patients. Methods. ApoA5 was screened from serum proteomics profile in lipopolysaccharide- (LPS-) treated mice for 2 h, 24 h, and controls. Then, we conducted a prospective pilot study, and patients with sepsis admitted to a pediatric intensive care unit (PICU) were enrolled from January 2018 to December 2018. Serum ApoA5 levels on PICU admission were determined using enzyme-linked immunosorbent assays (ELISA). Blood samples from 30 healthy children were used as control. The correlation of ApoA5 with the clinical and laboratory parameters was analyzed. Logistic regression analyses and receiver operating characteristic curve (ROC) analysis were used to investigate the potential role of serum ApoA5 as a prognostic predictor for PICU mortality in pediatric patients with sepsis. Results. A total of 101 patients with sepsis were enrolled in this study. The PICU mortality rate was 10.9% (11/101). Serum ApoA5 levels on PICU admission were significantly lower in nonsurvivors with sepsis compared with survivors (P=0.009). In subgroup analysis, serum levels of ApoA5 were significantly correlated with sepsis-associated multiple organ dysfunction syndrome (MODS) (P0.05). Correlation analyses revealed significant correlations of serum ApoA5 with Ca2+ concentration. Remarkably, the area under ROC curve (AUC) for serum ApoA5 levels on PICU admission was 0.789 for prediction of PICU mortality with a sensitivity of 75% and a specificity of 84.5% at a threshold value of 822 ng/mL. Conclusions. Serum ApoA5 level is associated with sepsis-associated shock, AKI, ALI, GI dysfunction, or MODS in children. Moreover, the findings of the present study suggest a prognostic value of ApoA5 in children with sepsis, and lower serum ApoA5 than 822 ng/mL predicts worse outcome in pediatric sepsis

Efficient depolymerization of Kraft lignin to liquid fuels over an amorphous titanium-zirconium mixed oxide supported partially reduced nickel-cobalt catalyst

A series of non-precious metal/metal oxide nickel-cobalt catalysts was prepared for a highly efficient depolymerization of Kraft lignin (KL) into liquid fuels using amorphous TiZr-oxide (Ti1-yZryO2) as a carrier. The effects of Ni-NiOx, Co-CoOx, NiCo-NiCoOx, NiCoOx, and NiCo catalysts supported on amorphous TiZr-oxide carrier on KL depolymerization were investigated. It was found that the NiCo-NiCoOx/Ti1-yZryO2 catalyst is optimal for converting KL to petroleum ether (PE)-soluble product (mainly composed of monomers and dimers) in an 80.2% high yield at 320 degrees C for 24 h, with excellent reusability and a low formation of char. Under these conditions, the higher heating value (HHV) increased from 25.11 to 33.89 MJ/kg. A meticulous study on NiCo-NiCoOx/Ti1-yZryO2 catalysts revealed that the synergistic effect among Lewis acid sites, basic sites and metal active sites played an important role in obtaining high yields of monomers and low rates of char formation during lignin conversion