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Pengqi Zhang,1 Tianye Wang,1 Xiaoting Zhu,2 Lina Feng,1 Jiale Wang,1 Yunqiang Li,1 Xinyue Zhang,1 Tingting Cui,1 Mingquan Li2 1College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, Jilin Province, People’s Republic of China; 2Neurology Department, Third Affiliated Clinical Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin Province, People’s Republic of ChinaCorrespondence: Mingquan Li, Neurology Department, Third Affiliated Clinical Hospital of Changchun University of Traditional Chinese Medicine, Changchun, 130033, People’s Republic of China, Tel +86-15543120222, Email liminhquan0001@126.comObjective: The objective of this study was to explore the neuroprotective mechanism of JDYZF in treating AD from the perspective of inflammation and intestinal microflora.Methods: A total of 24 APP/PS1 mice were randomly divided into four groups: model (n = 6), JDYZF low-dose (n = 6), JDYZF high-dose (n = 6), and positive drug (n = 6), six C57 mice were used as the control group. The body weights and diets of all mice were examined daily. After 8 weeks of administration, the learning and memory of mice were evaluated by the Morris water maze test. The histopathological changes of hippocampus, liver and kidney in mice were observed by HE staining after being euthanized. The expression of p-tau in hippocampus tissue was detected by immunohistochemistry. After that, 16S rDNA sequencing was used to investigate the relationship between JDYZF and intestinal microbiota. Finally, a comparison of TLR4, p65, p-p65, iκB, p-iκB, and IL-1β protein expression in the hippocampus tissue of mice in each group was measured by Western blot.Results: Theresultsshowedthat APP/PS1 mice taking JDYZF orally were generally in good condition. Compared with the control group, JDYZF significantly improved learning and memory ability in ethology. Histology showed that JDYZF improved the hippocampal structure of mice and inhibited the deposition of p-tau. JDYZF treatment could regulate the gut microbiota of APP/PS1 mice by increasing the richness of Lachnospiraceae, Ruminococcaceae, and Actinobacteria and reducing that of Alistipes and Muribaculaceae.It also significantly inhibited the activation of the TLR4/NF-κB signaling pathway in the brain. In addition, no obvious toxic reactions were found in the liver and kidney of APP/PS1 mice after taking JDYZF for 8 weeks.Conclusion: The findings revealed that JDYZF improved cognitive ability and alleviated the TLR4/NF-κB signaling pathway in APP/PS1 mice, and the modulating the gut microbiota presented here may help illuminate its activation mechanism.Keywords: Jiedu Yizhi Formula, Alzheimer’s disease, fecal microbial diversity, NF-κB, APP/PS1 mice

The three-dimensional (3D) visualization of geological structures and the dynamic simulation of geologic evolutionary processes are helpful when studying the formation of renowned geologic features. However, most of the existing 3D modelling software is based on raster models, which is unable to generate smooth geologic boundaries. This work proposes a three-dimensional and temporally dynamic (i.e., 4D) modelling method using parametric functions and vector data structures, which can dynamically build geologic evolutionary vector models of well-known geologic features. First, we extract the typical features of different kinds of geologic formations and represent them using different parameters. Next, appropriate parametric functions are selected to simulate these geologic formations according to the characteristics of the individual structures. Then, we designed and developed a 4D vector modelling software to simulate the geologic evolution of these features. Finally, we simulated an area with complex geologic structures and selected six real-world geologic features, such as the Piqiang Fault in China and the Eye of the Sahara in the Sahara Desert, as case studies. The modelling results show that a regional geologic evolutionary model that contains smooth boundaries can be established quickly using this method. This work will support studies into the formation of these renowned geological features and make the representation of geologic processes more intuitive.

Lina Feng,1 Mingquan Li,2 Jixiang Ren,3 Yujuan Li,4 Qi Wang,5 Pengqi Zhang,1 Xinyue Zhang,1 Tianye Wang,5 Yunqiang Li1 1College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, Jilin Province, People’s Republic of China; 2Neurology Department, Third Affiliated Clinical Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin Province, People’s Republic of China; 3Preclinical Department, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin Province, People’s Republic of China; 4Ultrasonic Diagnosis Department, Third Affiliated Clinical Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin Province, People’s Republic of China; 5College of Integrated Chinese and Western Medicine, Changchun University of Chinese Medicine, Changchun, Jilin Province, People’s Republic of ChinaCorrespondence: Mingquan Li Tel +86-15543120222Email liminhquan0001@126.comObjective: The present study aimed to explore the neuroprotective mechanism of Di Dang decoction (DDD) during acute intracerebral hemorrhage (AICH) stroke in Sprague Dawley rats through proteomic analysis.Methods: A total of 135 healthy Sprague Dawley rats were randomly divided into five groups: control (n = 27), model (n = 27), DDD low-dose (n = 27), DDD medium-dose (n = 27), and DDD high-dose (n = 27). AICH stroke in rats was induced by injecting autologous blood into the caudate nucleus. The modified Neurological Severity Score (mNSS) was used to evaluate the cerebral nerve function deficit. Hematoxylin and eosin (HE) staining was performed to observe the brain tissue at the lesion site. Albumin concentration was assessed on obvious blood-brain barrier damaged and brain water content was used to evaluate the brain injury. For quantitative proteomics, proteins were extracted from the cerebral cortices. Target proteins were identified using mass spectrometer-based targeted proteomic quantification.Results: mNSS score, HE staining results, albumin concentration, and brain water content showed the most significant improvements in the neuroprotective in the high-dose group 7 days after DDD exposure. Furthermore, quantitative proteomics analysis showed that, relative to the control group, S100a8 and S100a9 were downregulated by 0.614 (p = 0.033702) and 0.506 times (p = 0.000024) in the high-dose group. Compared with the control group, Col1a1 and Col1a2 were upregulated by 1.319 (p = 0.000184) and 1.348 (p = 0.014097) times in the high-dose group. These results were confirmed using mass spectrometer-based targeted proteomic quantification.Conclusion: Application of a high-dose DDD for 7 days in AICH stroke rats showed the most significant improvements in neuroprotective. Mechanistically, this effect was mediated by S100a8 and S100a9 protein downregulation and Col1a1 and Col1a2 upregulation.Keywords: acute intracerebral hemorrhage stroke, S100a8, S100a9, Col1a1, Col1a2, Di Dang decoction

The purpose of the present study is to better understand the reaction kinetics of diesel exhaust soot during oxidation process. A thermogravimetric analyzer was used to oxidize real diesel exhaust soot generated from a Euro VI diesel engine under non-isothermal conditions. The Friedman-Reich-Levi method and the Sestak-Berggren model were used to determine the oxidation kinetics. Raman spectroscopy and high-resolution transmission electron microscopy were employed to follow the changes of the soot structure during oxidation. The activation energy gradually increased with increasing conversion level during soot oxidation. The oxidation process of diesel exhaust soot could be described as three-step kinetics, and the calculated conversions fitted the experimental results very well. The kinetic predictions of diesel soot oxidation that were obtained using the proposed kinetic models were more accurate and precise than those with the common first-order model. The structural order increased as oxidation progressed, which was responsible for the increased activation energy. The structural ordering was principally caused by the preferential oxidation of the disordered fraction in the diesel soot, especially for the amorphous carbon, which was oxidized in the initial stage of the oxidation reaction.

A radical-based asymmetric olefin difunctionalization strategy for rapidly forging all-carbon quaternary stereocenters α to diverse azaarenes is reported. Under cooperative photoredox and chiral Bronsted acid catalysis, cyclopropylamines with α-branched 2-vinylazaarenes can undergo a sequential two-step radical process, furnishing various valuable chiral azaarene-substituted cyclopentanes. The use of the rigid and confined C2-symmetric imidodiphosphoric acid catalysts achieves high enantio- and diastereo-selectivities for these asymmetric [3 + 2] cycloadditions.

Classification-based tracking strategies often face more challenges from intra-class discrimination than from inter-class separability. Even for deep convolutional neural networks that have been widely proven to be effective in various vision tasks, their intra-class discriminative capability is still limited by the weakness of softmax loss, especially for targets not seen in the training dataset. By taking intrinsic attributes of training samples into account, in this paper, we propose a position-sensitive loss coupled with softmax loss to achieve intra-class compactness and inter-class explicitness. Particularly, two additive margins are introduced to encode the position attribute for decision boundary maximization, which is also utilized with the proposed loss to supervise the fine-tuned features on the pre-trained model. With the nearest neighbor ranking measurement in the feature embedding domain, the whole scheme is able to reach an optimized balance between the feature-level inter-class semantic separability and instance-level intra-class relative distance ranking. We evaluate the proposed work on different popular benchmarks, and experimental results demonstrate that our tracking strategy performs favorably against most of the state-of-the-art trackers in the comparison of accuracy and robustness.

Unlike some other well-known challenges such as facial recognition, where Machine Learning and Inversion algorithms are widely developed, the geosciences suffer from a lack of large, labelled datasets that can be used to validate or train robust Machine Learning and inversion schemes. Publicly available 3D geological models are far too restricted in both number and the range of geological scenarios to serve these purposes. With reference to inverting geophysical data this problem is further exacerbated as in most cases real geophysical observations result from unknown 3D geology, and synthetic test datasets are often not particularly geological, nor geologically diverse. To overcome these limitations, we have used the Noddy modelling platform to generate one million models, which represent the first publicly accessible massive training set for 3D geology and resulting gravity and magnetic datasets. This model suite can be used to train Machine Learning systems, and to provide comprehensive test suites for geophysical inversion. We describe the methodology for producing the model suite, and discuss the opportunities such a model suit affords, as well as its limitations, and how we can grow and access this resource.

In the journal-bearing system, the journal inevitably moves along the bearing axis, and the axial movement of journal may affect the performance of misaligned journal bearing. In this article, a numerical model for the thermohydrodynamic lubrication of bearing considering the axial movement of journal is established, and based on which a comprehensive analysis on the performance of misaligned journal bearing is conducted by solving the generalized Reynolds equation, heat conduction equation and energy equation. The results show that axial movement of misaligned journal has more obvious influence on the bearing lubrication characteristics at the lower speed, larger inclination angle and eccentricity. The impact of axial movement on the bearing lubrication performance is greatly affected by the thermal effect and surface roughness.

An enantioconvergent substitution of 3-substituted 3-chlorooxindoles with N-aryl glycines under visible light irradiation is reported. A transition-metal-free cooperative catalysis platform with a dicyanopyrazine-derived chromophore (DPZ) as a photoredox catalyst and a chiral Brønsted acid catalyst is effective for these transformations, which involve a single-electron transfer redox step and an enantioselective radical coupling. A variety of valuable chiral 3-aminomethylene-3-substituted oxindoles can be directly synthesized with high yields and enantioselectivities.

The Lijiagou spodumene deposit in the central Songpan-Garze Fold Belt (SGFB), West Sichuan, is a spodumene pegmatite-hosted deposit within the giant Songpan-Garze polymetallic belt. Systematic zircon, cassiterite and coltan U-Pb dating, Hf isotope and whole-rock geochemical analysis were undertaken. Two-mica granite and muscovite albite granite have S-type granite affinities and chemical compositions suggesting a post-orogenic setting, and the spodumene pegmatites belong to the LCT (Li-Cs-Ta) group of pegmatites. Zircon LA-MC-ICP-MS U-Pb dating of the two-mica granite, muscovite albite granite, barren albite pegmatite and albite spodumene pegmatite give crystallization ages of 219.2 ± 2.3 Ma (MSWD = 0.55), 217 ± 2.8 Ma (MSWD = 0.47), 202.8 ± 4.9 Ma (MSWD = 3.9), 200.1 ± 4.6 Ma (MSWD = 3.1), respectively. Zircons from the same units yield εHf(t) values of −39.17 to 13.84, −22.73 to −2.83, −11.17 to 8.14, and −4.92 to −2.4, respectively, consistent with mixed crustal sources for the pegmatite and granite magmas. Cassiterite from spodumene pegmatite yields a concordia intercept age of 211.4 ± 3.3 Ma (MSWD = 2.9), while coltan yields a weighted mean age of 211.6 ± 0.5 Ma (MSWD = 0.61). The U-Pb zircon ages of the two-mica granite and muscovite albite granite are interpreted as ages of magmatic crystallization. Metamictization of zircon in both barren and spodumene pegmatites makes their U-Pb zircon ages liable to inaccuracy due to Pb loss. The coltan U-Pb age is regarded as an accurate measure of the magmatic crystallization age of the spodumene pegmatite. Given the differences in magmatic ages and εHf(t) ranges between spodumene pegmatite and both the two-mica granite and the muscovite albite granite, the spodumene pegmatite probably represents an anatectic melt and not a fractionation product of either of the granitic magmas. U-Pb coltan and U-Pb cassiterite dating are more likely to provide accurate crystallization ages of spodumene pegmatites than U-Pb zircon ages. Spodumene mineral exploration in such geological environments requires consideration both of the mineralogy and geochemistry of potential metasedimentary source rocks, and of the effects of granite intrusion in creating fertile mineral assemblages.Two key conclusions for spodumene pegmatite mineral exploration follow: 1) prior intrusion of granite may be required to generate a metasedimentary mineral assemblage that may later yield albite-spodumene pegmatite magma, and 2) a focus on the mineralogy and Li concentration of potential metasedimentary source rocks is required to identify geological environments in which albite-spodumene pegmatite magmas may have been generated.

Current weakly supervised object localization and segmentation rely on class-discriminative visualization techniques to generate pseudo-labels for pixel-level training. Such visualization methods, including class activation mapping (CAM) and Grad-CAM, use only the deepest, lowest resolution convolutional layer, missing all information in intermediate layers. We propose Zoom-CAM: going beyond the last lowest resolution layer by integrating the importance maps over all activations in intermediate layers. Zoom-CAM captures fine-grained small-scale objects for various discriminative class instances, which are commonly missed by the baseline visualization methods. We focus on generating pixel-level pseudo-labels from class labels. The quality of our pseudo-labels evaluated on the ImageNet localization task exhibits more than 2.8% improvement on top-1 error. For weakly supervised semantic segmentation our generated pseudo-labels improve a state of the art model by 1.1%., Comment: ICPR 2020

Recently the performance of dual fuel strategy on multi-cylinder engines over the whole engine map has received increasing attention. This research focuses on the potential of Homogeneous Charge Induced Ignition (HCII) combustion fueled with gasoline and diesel meeting Euro V emission standard through the whole operating range using a simple after-treatment system. This combustion mode utilizes a port injection of high-volatile fuel (gasoline) to form a homogeneous charge and a direct injection of high ignitable fuel (diesel) near the Top Dead Center (TDC) to trigger combustion. In this paper, an experimental and numerical investigation of the combustion characteristics and emission formation of HCII on a multi-cylinder heavy-duty engine is conducted. The effects of gasoline ratio (Rg), one of the most important parameters in dual-fuel mode, are explored and analyzed in detail. A Rg of 70–80% is recommended for better combustion and emission performance at the operating condition in this paper. HCII also turns out to be an effective strategy to reduce NOx and soot emissions at the same time. Furthermore, the high THC and CO emissions of HCII combustion can be eliminated using Diesel Oxidation Catalyst (DOC). Then the HCII strategy was optimized through the whole operating range showing a great potential of meeting Euro V limitations only with DOC as an after-treatment device. The fuel consumption also reduced with dual fuel strategy.

Unbalanced inertia force and moment of crankshaft generated by cylinder pressure have a significant effect on the vibration characteristics of diesel engine, but the study on the lubrication characteristics of crankshaft by balance rate needs to be studied. Based on Greenwood-Tripp asperity contact theory and average Reynolds equation, an elastohydrodynamic (EHD) lubrication model of the main bearing for a V-12 diesel engine is developed, and the influence of different balance rates on lubrication characteristics is analyzed. On this basis, a factorial experiment of ten influencing factors including the balance rate is designed, and the factors that significantly affected the lubrication characteristics of the main bearing are screened out by factor effect diagram, statistical analysis and residual probability diagram. The results show that the crankshaft with different balance rate has a great influence on the lubrication performance. With the increase of balance rate, the minimum oil film thickness first increases and then decreases, and the maximum oil film pressure first decreases and then increases. The balance rate, bearing width, bearing clearance, bush repair and oil viscosity have significant effects on the performance of main bearing, among which the balance rate of crankshaft has the greatest effect on the minimum oil film thickness, the maximum rough contact pressure and the average friction power loss.

Direct injection (DI) technology imparts natural gas (NG) engines with high thermal efficiency and reduces emissions. Furthermore, NG directly jets into the pilot flame. The interaction between the NG jet flow and pilot flame has a significant influence on the initial ignition and flame stability. This study investigates the effects of a high-pressure methane jet on the pilot ignited flame, using a constant-volume bomb (CVB) test rig. The interval between the methane injection and the ignition determines the premixed flame and jet combustion. The high-pressure methane jet flow collides with acts on the pilot premixed flame, which results in two phenomena: 1) Flame quenching: the premixed flame is blown off by the jet; and 2) Jet flame: the methane jet is ignited by the premixed flame. In the jet flame, laminar and turbulent flames co-exist. The development of the jet flame occurs in three stages: Stage I—the no-jet stage, wherein a laminar flame appears; Stage II—the interaction stage, wherein the jet interacts with the premixed flame, which results in either flame quenching or stable jet flame; and Stage III—the stable stage, wherein the flame becomes stable.