Hierarchical Attention for Part-Aware Face Detection

International Journal of Computer Vision - Expressive representations for characterizing face appearances are essential for accurate face detection. Due to different poses, scales, illumination,...     

Biofortification with selenium and lithium improves nutraceutical properties of major winery grapes in the Midwestern United States

Enriching the micronutrients, selenium (Se) and lithium (Li), in grapes to improve their nutraceutical properties were implemented by foliar application of organic fertiliser rich in Se and Li onto five grape cultivars. The effects of this biofortification on vine vigour, fruit quality, overall micronutrients and phenolic compounds also were investigated. Agronomic biofortification was found greatly increased the Se and Li content in the whole grape by multiple times, meanwhile it did not significantly affect the vine vigour and fruit quality of grapes. However, the biofortification did impact the Ionome (including all the mineral nutrients and trace elements) and phenolic compounds in grapes and this varied among cultivars. This study demonstrated foliar spray of organic Se/Li fertiliser was a very effective strategy to biofortify these micronutrients in grape berries, particularly in the skin, and therefore might be a promising strategy to increase the consumption and awareness of these grapes.     

In situ Raman spectroscopic study towards the growth and excellent HER catalysis of Ni/Ni(OH)2 heterostructure

The electrochemical water splitting to produce H₂ in high efficiency with earth-abundant-metal catalysts remains a challenge. Here, we describe a simple “cyclic voltammetry + ageing” protocol at room temperature to activate Ni electrode (AC-Ni/NF) for hydrogen evolution reaction (HER), by which Ni/Ni(OH)₂ heterostructure is formed at the surface. In situ Raman spectroscopy reveals the gradual growth of Ni/Ni(OH)₂ heterostructure during the first 30 min of the aging treatment and combined with polarization measurements, it suggests a positive relation between the Ni/Ni(OH)₂ amount and HER performance of the electrode. The obtained AC-Ni/NF catalyst, with plentiful Ni–Ni(OH)₂ interfaces, exhibits remarkable performance towards HER, with the low overpotential of only 30 mV at a H₂-evolving current density of 10 mA/cm² and 153 mV at 100 mA/cm², as well as a small Tafel slope of 46.8 mV/dec in 1 M KOH electrolyte at ambient temperature. The excellent HER performance of the AC-Ni/NF could be maintained for at least 24 h without obvious decay. Ex situ experiments and in situ electrochemical-Raman spectroscopy along with density functional theory (DFT) calculations reveal that Ni/Ni(OH)₂ heterostructure, although partially reduced, can still persist during HER catalysis and it is the Ni–Ni(OH)₂ interface reducing the energy barrier of H1 adsorption thus promoting the HER performance.     

Evaluation of bismuth doped La2-xBixNiO4+δ (x = 0, 0.02 and 0.04) as cathode materials for solid oxide fuel cells

Bismuth doped La_2-xBi_xNiO_4+δ (x = 0, 0.02 and 0.04) oxides are investigated as SOFC cathodes. The effects of Bi doping on the phase structure, thermal expansion, electrical conduction behavior as well as electrochemical performance are studied. All the samples exist as a tetragonal Ruddlesden-Popper structure. Bi-doped LBNO-0.02 and LBNO-0.04 have good chemical and thermal compatibility with LSGM electrolyte. The average TEC over 20–900°С was 13.4 × 10^?6 and 14.2 × 10^?6 K^?1 for LBNO-0.02 and LBNO-0.04, respectively. The electrical conductivity was decreasing with the rise of Bi doping content. EIS measurement indicates Bi doping can decrease the ASR values. At 750 °C, the obtained ASR for LBNO-0.04 is 0.18 Ωcm², which is 56% lower than that of the sample without Bi doping, suggesting Bi doping is beneficial to the electrochemical catalytic activity of LBNO cathodes.     

P-doped CoSe2 nanoparticles embedded in 3D honeycomb-like carbon network for long cycle-life Na-ion batteries

We report for the first time a Na-ion battery anode material composed of P-doped CoSe2 nanoparticles(P-CoSe2)with the size of 5-20 nm that are uniformly embed in a 3D porous honeycomb-like carbon network.High rate capability and cycling stability are achieved simultaneously.The honeycomb-like carbon network is rationally designed to support high electrical conductivity,rapid Na-ion diffusion as well as the accommodation of the volume expansion from the active P-CoSe2 nanoparticles.In particular,heteroatom P-doping within CoSe2 introduces stronger P-Co bonds and additional P-Se bonds that signif-icantly improve the structure stability of P-CoSe2 for highly stable sodiation/desodiation over long-term cycling.P-doping also improves the electrical conductivity of the CoSe2 nanoparticles,leading to highly elevated electrochemical kinetics to deliver high specific capacities at high current densities.Benefiting from the unique nanostructure and atomic-level P-doping,the P-CoSe2(2∶1)/C anode delivers an excel-lent cycle stability with a specific capacity of 206.9 mA h g-1 achieved at 2000 mA g-1 after 1000 cycles.In addition,this material can be synthesized using a facile pyrolysis and selenization/phosphorization approach.This study provides new opportunities of heteroatom doping as an effective method to improve the cycling stability of Na-ion anode materials.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

Mesoporous Co–Mn Spinel Oxides as Efficient Catalysts for Low Temperature Propane Oxidation

Catalysis Letters - A series of mesoporous cobalt–manganese catalysts were successfully synthesized by sol–gel method as efficient catalysts for the propane oxidation. A significant...