The extensive amount of multimedia information available necessitates content-based video indexing and retrieval methods. Since humans tend to use high-level semantic concepts when querying and ...browsing multimedia databases, there is an increasing need for semantic video indexing and analysis. For this purpose, we present a unified framework for semantic shot classification in sports video, which has been widely studied due to tremendous commercial potentials. Unlike most existing approaches, which focus on clustering by aggregating shots or key-frames with similar low-level features, the proposed scheme employs supervised learning to perform a top-down video shot classification. Moreover, the supervised learning procedure is constructed on the basis of effective mid-level representations instead of exhaustive low-level features. This framework consists of three main steps: 1) identify video shot classes for each sport; 2) develop a common set of motion, color, shot length-related mid-level representations; and 3) supervised learning of the given sports video shots. It is observed that for each sport we can predefine a small number of semantic shot classes, about 5-10, which covers 90%-95% of broadcast sports video. We employ nonparametric feature space analysis to map low-level features to mid-level semantic video shot attributes such as dominant object (a player) motion, camera motion patterns, and court shape, etc. Based on the fusion of those mid-level shot attributes, we classify video shots into the predefined shot classes, each of which has clear semantic meanings. With this framework we have achieved good classification accuracy of 85%-95% on the game videos of five typical ball type sports (i.e., tennis, basketball, volleyball, soccer, and table tennis) with over 5500 shots of about 8 h. With correctly classified sports video shots, further structural and temporal analysis, such as event detection, highlight extraction, video skimming, and table of content, will be greatly facilitated.
Electrochemical reduction of biomass‐derived 5‐hydroxymethylfurfural (HMF) represents an elegant route toward sustainable value‐added chemicals production that circumvents the use of fossil fuel and ...hydrogen. However, the reaction efficiency is hampered by the high voltage and low activity of electrodes (Cu, Bi, Pb). Herein, we report a Ru1Cu single‐atom alloy (SAA) catalyst with isolated Ru atoms on Cu nanowires that exhibits an electrochemical reduction of HMF to 2,5‐dihydroxymethylfuran (DHMF) with promoted productivity (0.47 vs. 0.08 mmol cm−2 h−1) and faradic efficiency (FE) (85.6 vs. 71.3 %) at −0.3 V (vs. RHE) compared with Cu counterpart. More importantly, the FE (87.5 %) is largely retained at high HMF concentration (100 mM). Kinetic studies by using combined electrochemical techniques suggest disparate mechanisms over Ru1Cu and Cu, revealing that single‐atom Ru promotes the dissociation of water to produce H* species that effectively react with HMF via an electrocatalytic hydrogenation (ECH) mechanism.
Electrocatalytic hydrogenation (ECH) of 5‐hydroxymethylfurfural (HMF) to 2,5‐dihydroxymethylfuran (DHMF) was achieved over a Ru1Cu single‐atom alloy (SAA) catalyst with isolated Ru atoms on Cu nanowires. Single‐atom Ru promotes the dissociation of water to produce H* species that effectively react with HMF to afford DHMF. This work offers a catalyst design model for highly efficient ECH of biomass via single‐atom alloying.
The biomass‐derived alcohol oxidation reaction (BDAOR) holds great promise for sustainable production of chemicals. However, selective electrooxidation of alcohols to value‐added aldehyde compounds ...is still challenging. Herein, we report the electrocatalytic BDAORs to selectively produce aldehydes using single‐atom ruthenium on nickel oxide (Ru1‐NiO) as a catalyst in the neutral medium. For electrooxidation of 5‐hydroxymethylfurfural (HMF), Ru1‐NiO exhibits a low potential of 1.283 V at 10 mA cm−2, and an optimal 2,5‐diformylfuran (DFF) selectivity of 90 %. Experimental studies reveal that the neutral electrolyte plays a critical role in achieving a high aldehyde selectivity, and the single‐atom Ru boosts HMF oxidation in the neutral medium by promoting water dissociation to afford OH*. Furthermore, Ru1‐NiO can be extended to selective electrooxidation of a series of biomass‐derived alcohols to corresponding aldehydes, which are conventionally difficult to obtain in the alkaline medium.
Selective oxidation of 5‐hydroxymethylfurfural (HMF) to produce 2,5‐diformylfuran (DFF) was achieved in neutral medium over single‐atom Ru supported on NiO (Ru1‐NiO). Single‐atom Ru sites boost HMF oxidation by facilitating water dissociation, which generates electrophilic OH* as a key reactant. The substrate scope was extended to produce aldehydes from various biomass‐derived alcohols. Key: Ni (light gray), Ru (green), O (red), C (dark gray), H (white).
Abstract
Electrochemical alcohols oxidation offers a promising approach to produce valuable chemicals and facilitate coupled H
2
production. However, the corresponding current density is very low at ...moderate cell potential that substantially limits the overall productivity. Here we report the electrooxidation of benzyl alcohol coupled with H
2
production at high current density (540 mA cm
−2
at 1.5 V
vs
. RHE) over a cooperative catalyst of Au nanoparticles supported on cobalt oxyhydroxide nanosheets (Au/CoOOH). The absolute current can further reach 4.8 A at 2.0 V in a more realistic two-electrode membrane-free flow electrolyzer. Experimental combined with theoretical results indicate that the benzyl alcohol can be enriched at Au/CoOOH interface and oxidized by the electrophilic oxygen species (OH*) generated on CoOOH, leading to higher activity than pure Au. Based on the finding that the catalyst can be reversibly oxidized/reduced at anodic potential/open circuit, we design an intermittent potential (IP) strategy for long-term alcohol electrooxidation that achieves high current density (>250 mA cm
−2
) over 24 h with promoted productivity and decreased energy consumption.
Chronic Obstructive Pulmonary Disease (COPD) is a prevalent chronic pulmonary condition that affects hundreds of millions of people all over the world. Many COPD patients got readmitted to hospital ...within 30 days after discharge due to various reasons. Such readmission can usually be avoided if additional attention is paid to patients with high readmission risk and appropriate actions are taken. This makes early prediction of the hospital readmission risk an important problem. The goal of this paper is to conduct a systematic study on developing different types of machine learning models, including both deep and non-deep ones, for predicting the readmission risk of COPD patients. We evaluate those different approaches on a real world database containing the medical claims of 111,992 patients from the Geisinger Health System from January 2004 to September 2015. The patient features we build the machine learning models upon include both knowledge-driven ones, which are the features extracted according to clinical knowledge potentially related to COPD readmission, and data-driven features, which are extracted from the patient data themselves. Our analysis showed that the prediction performance in terms of Area Under the receiver operating characteristic (ROC) Curve (AUC) can be improved from around 0.60 using knowledge-driven features, to 0.653 by combining both knowledge-driven and data-driven features, based on the one-year claims history before discharge. Moreover, we also demonstrate that the complex deep learning models in this case cannot really improve the prediction performance, with the best AUC around 0.65.
Exploring highly efficient and stable oxygen evolution reaction (OER) electrocatalysts such as transition‐metal phosphides (TMPs) is critical to advancing renewable hydrogen fuel. TMP nanostructures ...typically involving binary or ternary TMPs tuned by cation or anion doping are suggested to be promising low‐cost and durable OER catalysts. Herein, the preparation of CoP/CoP2 composite nanoparticles encapsulated within N,P‐doped carbon nanotubes (CoP/CoP2@NPCNTs) is demonstrated as a synergistic electrocatalyst for OER via the calcination of a CoAl‐layered double hydroxide/melamine mixture and subsequent phosphorization. Facile visualization by scanning electron microscopy in conjunction with electron backscatter diffraction demonstrates the encapsulation of the CoP/CoP2 nanoparticles within the N,P‐codoped CNTs. Electrocatalytic evaluation shows that the composite electrode requires a low overpotential of 300 mV for the OER at 10 mA cm−2 in a 1.0 m KOH solution and, in particular, exhibits an excellent long‐term durability of ≈100 h, which is superior to that of the state‐of‐the‐art RuO2 electrocatalyst. Density functional theory calculations reveal that the synergistic effect of CoP and CoP2 can enhance the electrocatalytic performance. In addition, molecular dynamics simulations demonstrate that the generated O2 molecules can readily diffuse out of the CNTs. Both the effects give rise to the observed OER enhancement.
CoP/CoP2@N,P‐doped carbon nanotube (CNT) composite is prepared as a synergistic electrocatalyst for the oxygen evolution reaction (OER). Scanning electron microscopy/electron backscatter diffraction observation manifests the encapsulation of CoP/CoP2 nanoparticles within the N,P‐doped CNTs. The composite electrode exhibits a remarkable catalytic activity and superior long‐term stability toward the OER. Complementary density functional theory calculations and molecular dynamics simulations support the enhanced electrocatalytic performances.
Abstract
Photoelectrochemical cells are emerging as powerful tools for organic synthesis. However, they have rarely been explored for C–H halogenation to produce organic halides of industrial and ...medicinal importance. Here we report a photoelectrocatalytic strategy for C–H halogenation using an oxygen-vacancy-rich TiO
2
photoanode with NaX (X=Cl
−
, Br
−
, I
−
). Under illumination, the photogenerated holes in TiO
2
oxidize the halide ions to corresponding radicals or X
2
, which then react with the substrates to yield organic halides. The PEC C–H halogenation strategy exhibits broad substrate scope, including arenes, heteroarenes, nonpolar cycloalkanes, and aliphatic hydrocarbons. Experimental and theoretical data reveal that the oxygen vacancy on TiO
2
facilitates the photo-induced carriers separation efficiency and more importantly, promotes halide ions adsorption with intermediary strength and hence increases the activity. Moreover, we designed a self-powered PEC system and directly utilised seawater as both the electrolyte and chloride ions source, attaining chlorocyclohexane productivity of 412 µmol h
−1
coupled with H
2
productivity of 9.2 mL h
−1
, thus achieving a promising way to use solar for upcycling halogen in ocean resource into valuable organic halides.
Oxidative cleavage of C(OH)−C bonds to afford carboxylates is of significant importance for the petrochemical industry and biomass valorization. Here we report an efficient electrochemical strategy ...for the selective upgrading of lignin derivatives to carboxylates by a manganese‐doped cobalt oxyhydroxide (MnCoOOH) catalyst. A wide range of lignin‐derived substrates with C(OH)‐C or C(O)‐C units undergo efficient cleavage to corresponding carboxylates in excellent yields (80–99 %) and operational stability (200 h). Detailed investigations reveal a tandem oxidation mechanism that base from the electrolyte converts secondary alcohols and their derived ketones to reactive nucleophiles, which are oxidized by electrophilic oxygen species on MnCoOOH from water. As proof of concept, this approach was applied to upgrade lignin derivatives with C(OH)‐C or C(O)‐C motifs, achieving convergent transformation of lignin‐derived mixtures to benzoate and KA oil to adipate with 91.5 % and 64.2 % yields, respectively.
An electrochemical strategy has been developed for the oxidative cleavage of C(OH)−C bonds using a manganese‐doped cobalt oxyhydroxide catalyst under mild conditions. Preliminary studies demonstrate its application in upgrading lignin‐derived products with C(OH)‐C or C(O)‐C motifs, electrorefining them into valuable oxygenates, such as benzoate and adipate.
Percutaneous renal biopsy is essential for diagnosis of many renal diseases. Previous studies have revealed a variety of factors associated with bleeding complications of renal biopsy; however, data ...are not sufficient in the Chinese population. We aimed to investigate the risk factors for severe post-biopsy bleeding events in a large cohort of Chinese patients.
The data of patients who underwent percutaneous renal biopsy from January 2008 to December 2012 were collected. Severe bleeding complication was defined as requiring intervention, including blood transfusion or an invasive procedure (radiological or surgical) due to bleeding. Logistic regression analysis was used to assess risk factors.
Over the 5-year period, 3,577 native kidney biopsies were performed. Severe bleeding complication occurred in 14 biopsies (0.39%). The patients with complications were older, had higher blood pressure, lower hemoglobin, lower platelet count and worse renal function. Multivariable logistic regression demonstrated that platelet level and the estimated glomerular filtration rate were independently associated with the risk of complications. Each 10 × 10
/L increase of platelet count was associated with an 11% decrease of severe bleeding risk (odds ratio = 0.89; 95% CI: 0.80-0.98; P = 0.02). Each 1mL/minute/1.73m
increase of the estimated glomerular filtration rate was associated with a 4% decrease of severe bleeding risk (odds ratio = 0.96; 95% CI: 0.94-0.99; P = 0.004).
Patients with worse renal function and lower platelet counts had a higher risk of developing severe bleeding events after renal biopsy.
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