Model and Data Agreement for Learning with Noisy Labels

Learning with noisy labels is a vital topic for practical deep learning as models should be robust to noisy open-world datasets in the wild. The state-of-the-art noisy label learning approach JoCoR fails when faced with a large ratio of noisy labels. Moreover, selecting small-loss samples can also cause error accumulation as once the noisy samples are mistakenly selected as small-loss samples, they are more likely to be selected again. In this paper, we try to deal with error accumulation in noisy label learning from both model and data perspectives. We introduce mean point ensemble to utilize a more robust loss function and more information from unselected samples to reduce error accumulation from the model perspective. Furthermore, as the flip images have the same semantic meaning as the original images, we select small-loss samples according to the loss values of flip images instead of the original ones to reduce error accumulation from the data perspective. Extensive experiments on CIFAR-10, CIFAR-100, and large-scale Clothing1M show that our method outperforms state-of-the-art noisy label learning methods with different levels of label noise. Our method can also be seamlessly combined with other noisy label learning methods to further improve their performance and generalize well to other tasks. The code is available in https://github.com/zyh-uaiaaaa/MDA-noisy-label-learning.Comment: Accepted by AAAI2023 Worksho

Synthesis and Catalytic Performance of Ni/SiO 2

A series of Ni/SiO2 catalysts with different Ni content were prepared by sol-gel method for application in the synthesis of 2-methyltetrahydrofuran (2-MTHF) by hydrogenation of 2-methylfuran (2-MF). The catalyst structure was investigated by X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and temperature programmed reduction (TPR). It is found that structures and catalytic performance of the catalysts were highly affected by the Ni content. The catalyst with a 25% Ni content had an appropriate size of the Ni species and larger BET surface area and produced a higher 2-MF conversion with enhanced selectivity in 2-MTHF

Application of Ambient Ionization Mass Spectrometry in Forensic Toxicological Analysis

Ambient ionization mass spectrometry(AIMS)is a mass spectrometry technology which could be used to analyze target analytes in samples under atmospheric pressure without or with simple sample pretreatment. With the advantages of simplicity, rapidness, non-destructiveness and wide application range, it is widely used in forensic toxicological analysis. This article gives a brief over- view on the ambient ionization(AI)technique, and the samples are divided into two types: in vivo test materials and in vitro test materials. The application of AIMS in the poison analysis of different types of test materials is summarized, and its application direction in forensic toxicological analysis is prospected

Flutter reliability analysis of Xiangshan Harbor Highway Cable-Stayed Bridges in Service

With the development of bridge structures towards being light weight and having a large span , the overall flexibility, and, hence, wind sensitivity, of the bridge increases. Flutter is one of the pivotal factors considered in the design and operation stage for long-span cable-stayed bridges due to its devastating impact, often intrigued by relatively low instability caused by wind speed. This paper presents a reliability theory-based numerical analysis on bridge flutter stability and its influence law of key parameters using a real bridge, the Xiangshan Harbor highway cable-stayed bridge in China. The analysis starts with creating a full scale of finite element model for the bridge in service to calculate the flutter derivative and time-dominated combining rational function in order to obtain the critical-flutter wind speed, and then the aerodynamic self-excited forces on the bridge and flutter time-history response are calculated to identify the flutter critical wind speed. Further, the influence of key parameters for flutter reliability, including the stiffness of the main girder, wire breaking rate, damping ratio and cable breakage location are analyzed comprehensively to achieve the change law of critical flutter wind speed with these parameters. Considering the uncertainty of the actual parameters, these parameters are taken as random variables, and the reliability index and failure probability of bridge flutter are calculated according to their probability distribution and the Latin hypercube sampling method. On this basis, a few suggestions are put forward for flutter risk-control during the service of this cable-stayed bridge, which can further enhance the design theory for long-span flexible bridges

Boosting CO2 electrolysis performance : via calcium-oxide-looping combined with in situ exsolved Ni-Fe nanoparticles in a symmetrical solid oxide electrolysis cell

Financial support from National Key Research & Development Project (2016YFE0126900), National Natural Science Foundation of China (51672095), Hubei Province (2018AAA057) and the EPSRC Capital for Great Technologies Grant EP/L017008/1. We are grateful to the China Scholarship Council for funding (201806160178).The electrocatalysis of CO2 to valuable chemical products is an important strategy to combat global warming. Symmetrical solid oxide electrolysis cells have been extensively recognized for their CO2 electrolysis abilities due to their high efficiency, low cost, and reliability. Here, we produced a novel electrode containing calcium oxide-looping and in situ exsolved Ni–Fe nanoparticles by performing a one-step reduction of La0.6Ca0.4Fe0.8Ni0.2O3−δ (LCaFN). The CO2 captured by CaO was electrolyzed in situ by the Ni–Fe nanocatalysts. The cell with this special cathode showed a higher current density (0.632 A cm−2vs. 0.32 A cm−2) and lower polarization resistance (0.399 Ω cm2vs. 0.662 Ω cm2) than the unreduced LCaFN cathode at 800 °C with an applied voltage of 1.3 V. Use of the developed novel electrode offers a promising strategy for CO2 electrolysis.PostprintPeer reviewe

Driving forces and impacts of food system nitrogen flows in China, 1990 to 2012

Food nitrogen (N), which includes animal-food (AN) and plant-food N (PN), has been driven by population growth (PG), dietary changes associated with incomegrowth (DC) andrural-urban migration (M) over the past three decades, andthese changes combined with theirNcost, have caused some effect onNuse in China's food system. Although there is an increasing literature on food N and its environmental impacts in China, the relative magnitude of these driving forces are notwell understood. Here we first quantify the differences in per capita AN and PNconsumption in urban and rural areas and their impacts on N input to the food system during 1990–2012, and then quantify the relative contributions of DC, PG andMin the overall N change during this period. Our results show that a resident registered as living in city required 0.5 kg more AN yr−1 and 0.5 kg less PN yr−1 than one living in a rural area, in 2012. DC, PG and M accounted for 52%, 31% and 17% of the total AN increase, respectively. These three factors caused 46% of the increased N use for food production over the past two decades. Another 54% was mainly caused by the declining in N use efficiencies of the food system. Foodsourced N loss intensity in urban and rural areas were 502 and 162 kg N hm−2 in 2012, a three-fold difference due to the increasing amount and a linear rural-urbanflowofNinput, and inadequateNrecovery via solid waste and wastewater treatment in cities. Our study highlights China is facing higher risks of environmental N pollution with urbanization, because of the high demand for AN and higher food-sourced N loss intensity in urban than in rural areasThis manuscript is based on the several projects, sponsored by the National Basic Research Program of China (2014CB953801), the Young Talents Projects of the Institute of Urban Environment, the Chinese Academy of Sciences (IUEMS201402) and the National Natural Science Foundation of China (31500391)

Identification of microRNAs Involved in the Host Response to Enterovirus 71 Infection by a Deep Sequencing Approach

Role of microRNA (miRNA) has been highlighted in pathogen-host interactions recently. To identify cellular miRNAs involved in the host response to enterovirus 71 (EV71) infection, we performed a comprehensive miRNA profiling in EV71-infected Hep2 cells through deep sequencing. 64 miRNAs were found whose expression levels changed for more than 2-fold in response to EV71 infection. Gene ontology analysis revealed that many of these mRNAs play roles in neurological process, immune response, and cell death pathways, which are known to be associated with the extreme virulence of EV71. To our knowledge, this is the first study on host miRNAs expression alteration response to EV71 infection. Our findings supported the hypothesis that certain miRNAs might be essential in the host-pathogen interactions

High-Throughput Sequencing of MicroRNAs in Adenovirus Type 3 Infected Human Laryngeal Epithelial Cells

Adenovirus infection can cause various illnesses depending on the infecting serotype, such as gastroenteritis, conjunctivitis, cystitis, and rash illness, but the infection mechanism is still unknown. MicroRNAs (miRNA) have been reported to play essential roles in cell proliferation, cell differentiation, and pathogenesis of human diseases including viral infections. We analyzed the miRNA expression profiles from adenovirus type 3 (AD3) infected Human laryngeal epithelial (Hep2) cells using a SOLiD deep sequencing. 492 precursor miRNAs were identified in the AD3 infected Hep2 cells, and 540 precursor miRNAs were identified in the control. A total of 44 miRNAs demonstrated high expression and 36 miRNAs showed lower expression in the AD3 infected cells than control. The biogenesis of miRNAs has been analyzed, and some of the SOLiD results were confirmed by Quantitative PCR analysis. The present studies may provide a useful clue for the biological function research into AD3 infection

Feeding a low-protein maternal diet affects qinghai bamei piglet jejunal structure and microbial function response

This experiment investigated the impacts of feeding a maternal low-CP concentration diet having iso-essential amino acids on newborn suckling piglet"s intestinal microbial composition and function. Forty randomly selected purebred Bamei sows were divided into two groups and fed a low dietary CP (12%, LP) or a normal CP (14%, CON) diet, respectively, but formulated to contain similar (iso-) essential amino acid concentrations per current recommendations. At 21 days, 12 piglets were randomly selected from each treatment and euthanized with jejunum content samples collected. The 16S rRNA gene sequencing was combined as an integrated approach for evaluating the functional impact of maternal CP concentrations on piglet intestinal microbiome. Even though piglets demonstrated similar 0 to 21 d ADG among treatments, the jejunum relative weight, villus width, crypt depth and muscular thickness were increased (P<0.05), while villus height, and villus height/crypt depth were reduced (P<0.05) for the material LP compared to the maternal fed CON diet. Maternal CP concentrations can modify the intestinal microbial composition of Bamei suckling piglets. The relative abundances of the bacterial species Escherichia-Shigella, Actinobacillus, Clostridium_sensu_stricto_1, Veillonella, and Turicibacter were increased (P<0.05) in the maternal LP fed diet compared with the maternal fed CON diet microbiota metabolites. Overall, LP diet contributed to improve piglet intestinal histomorphology, microbial composition and function