Sales Model Selection for Second-hand vehicle E-commerce

The online second-hand vehicle sales models now include: auction model, consignment sales model, purchase and sales model, third party evaluation platform model and information consultant platform model. So choose a right sales model is important for sellers. We use AHP method to confirm key factors and built a score model base for different sales models. Though analysis, we can the conclusion that the best order of choice for online second-hand vehicle business model is: auction model, consignment sales model, purchase and sale model, information consultant platform and third party evaluation platform

A Supervised STDP-based Training Algorithm for Living Neural Networks

Neural networks have shown great potential in many applications like speech recognition, drug discovery, image classification, and object detection. Neural network models are inspired by biological neural networks, but they are optimized to perform machine learning tasks on digital computers. The proposed work explores the possibilities of using living neural networks in vitro as basic computational elements for machine learning applications. A new supervised STDP-based learning algorithm is proposed in this work, which considers neuron engineering constrains. A 74.7% accuracy is achieved on the MNIST benchmark for handwritten digit recognition.Comment: 5 pages, 3 figures, Accepted by ICASSP 201

Endocytic sorting and recycling require membrane phosphatidylserine asymmetry maintained by TAT-1/CHAT-1. PLoS Genet

Endocytic sorting is achieved through the formation of morphologically and functionally distinct sub-domains within early endosomes. Cargoes destined for recycling are sorted to and transported through newly-formed tubular membranes, but the processes that regulate membrane tubulation are poorly understood. Here, we identified a novel Caenorhabditis elegans Cdc50 family protein, CHAT-1, which acts as the chaperone of the TAT-1 P4-ATPase to regulate membrane phosphatidylserine (PS) asymmetry and endocytic transport. In chat-1 and tat-1 mutants, the endocytic sorting process is disrupted, leading to defects in both cargo recycling and degradation. TAT-1 and CHAT-1 colocalize to the tubular domain of the early endosome, the tubular endocytic recycling compartment (ERC), and the recycling endosome where PS is enriched on the cytosolic surface. Loss of tat-1 and chat-1 function disrupts membrane PS asymmetry and abrogates the tubular membrane structure. Our data suggest that CHAT-1 and TAT-1 maintain membrane phosphatidylserine asymmetry, thus promoting membrane tubulation and regulating endocytic sorting and recycling

Lipoic Acid Metabolism as a Potential Chemotherapeutic Target Against Plasmodium falciparum and Staphylococcus aureus

Lipoic acid (LA) is an organic compound that plays a key role in cellular metabolism. It participates in a posttranslational modification (PTM) named lipoylation, an event that is highly conserved and that occurs in multimeric metabolic enzymes of very distinct microorganisms such as Plasmodium sp. and Staphylococcus aureus, including pyruvate dehydrogenase (PDH) and α-ketoglutarate dehydrogenase (KDH). In this mini review, we revisit the recent literature regarding LA metabolism in Plasmodium sp. and Staphylococcus aureus, by covering the lipoate ligase proteins in both microorganisms, the role of lipoate ligase proteins and insights for possible inhibitors of lipoate ligases

Examination and evaluation of multi-source monthly scale fusion precipitation product in China based on machine learning algorithm

Grid format precipitation products have better spatial monitoring capabilities compared to ground meteorological station observations, but there are significant differences in performance among different products. This article evaluates the accuracy of nine monthly scale precipitation products TRMM, GPM, CMORPH, CHIRPS, ERA5, ERA5 Land, PERSIANN, PERSIANN-CDR, PERSIANN-CCS in China, and selects five better precipitation products from them. XGBoost is used to select the best precipitation products Three machine learning algorithms, random forest and multiple linear regression, were used for data fusion. Research has found that TRMM, GPM, CMORPH, CHIRPS, and PERSIANN-CDR products have relatively good accuracy. In high altitude and arid regions, the error of precipitation products significantly increases. After machine learning algorithm fusion, the optimal XGBoost algorithm model significantly improves product correlation coefficient, and significantly reduces root mean square error and bias. The three algorithms have shown good accuracy in each month, with XGBoost algorithm model products performing better in summer and random forest algorithm model products performing better in winter. Moreover, the three algorithm model products have shown high accuracy in different regions. Compared with the five original products before the fusion, the accuracy of the three algorithm model products has improved. The product fused with XGBoost algorithm has more variation and local precipitation details compared to the optimal original GPM product and meteorological station interpolation product in space

Automatic interval management for aircraft based on dynamic fuzzy speed control considering uncertainty

A novel real-time autonomous Interval Management System (IMS) is proposed to automate interval management, which considers the effect of wind uncertainty using the Dynamic Fuzzy Velocity Decision (DFVD) algorithm. The membership function can be generated dynamically based on the True Air Speed (TAS) limitation changes in real time and the interval criterion of the adjacent aircraft, and combined with human cognition to formulate fuzzy rules for speed adjusting decision-making. Three groups of experiments were conducted during the en-route descent stage to validate the proposed IMS and DFVD performances, and to analyze the impact factors of the algorithm. The verification experimental results show that compared with actual flight status data under controllers’ command, the IMS reduces the descent time by approaching 30% with favorable wind uncertainty suppression performance. Sensitivity analysis shows that the ability improvement of DFVD is mainly affected by the boundary value of the membership function. Additionally, the dynamic generation of the velocity membership function has greater advantages than the static method in terms of safety and stability. Through the analysis of influencing factors, we found that the interval criterion and aircraft category have no significant effect on the capability of IMS. In a higher initial altitude scenario, the initial interval should be appropriately increased to enhance safety and efficiency during the descent process. This prototype system could evolve into a real-time Flight-deck Interval Management (FIM) tool in the future

Gradual Disturbances of the Amplitude of Low-Frequency Fluctuations (ALFF) and Fractional ALFF in Alzheimer Spectrum

Background: Alzheimer’s disease (AD) is a common neurodegenerative disease in which the brain undergoes alterations for decades before symptoms become obvious. Subjective cognitive decline (SCD) have self-complain of persistent decline in cognitive function especially in memory but perform normally on standard neuropsychological tests. SCD with the presence of AD pathology is the transitional stage 2 of Alzheimer’s continuum, earlier than the prodromal stage, mild cognitive impairment (MCI), which seems to be the best target to research AD. In this study, we aimed to detect the transformational patterns of the intrinsic brain activity as the disease burden got heavy.Method: In this study, we enrolled 44 SCD, 55 amnestic MCI (aMCI), 47 AD dementia (d-AD) patients and 57 normal controls (NC) in total. A machine learning classification was utilized to detect identification accuracies between groups by using ALFF, fALFF, and fusing ALFF with fALFF features. Then, we measured the amplitude of the low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) levels in three frequency bands (classic: 0.01–0.1 Hz; slow-5: 0.01–0.027 Hz; and slow-4: 0.027–0.073 Hz) and compared alterations in patients with NC.Results: In the machine learning verification, the identification accuracy of SCD, aMCI, d-AD from NC was higher when fused ALFF and fALFF features (76.44, 81.94, and 91.83%, respectively) than only using ALFF or fALFF features. Several brain regions showed significant differences in ALFF/fALFF within these bands among four groups: brain regions presented decreasing trend of values, including the Cingulum_Mid_R (aal), bilateral inferior cerebellum lobe, bilateral precuneus, and the Cingulum_Ant_R (aal); increasing trend of values were detected in the Hippocampus_L (aal), Frontal_Mid_Orb_R (aal), Frontal_Sup_R (aal) and Paracentral_Lobule_R (aal) as disease progressed. The normalized ALFF/fALFF values of these features were significantly correlated with the neuropsychological test scores.Conclusion: This study revealed gradual disturbances in intrinsic brain activity as the disease progressed: the normal objective performance in SCD may be dependent on compensation; as disease advanced, the cognitive function gradually impaired and decompensated in aMCI, severer in d-AD. Our results indicated that the ALFF and fALFF may help detect the underlying pathological mechanism in AD continuum.Clinical Trial Registration:ClinicalTrials.gov, identifier NCT02353884 and NCT02225964

Thermoelectric Properties of Novel Semimetals: A Case Study of YbMnSb2

The emerging class of topological materials provides a platform to engineer exotic electronic structures for a variety of applications. As complex band structures and Fermi surfaces can directly benefit thermoelectric performance it is important to identify the role of featured topological bands in thermoelectrics particularly when there are coexisting classic regular bands. In this work, the contribution of Dirac bands to thermoelectric performance and their ability to concurrently achieve large thermopower and low resistivity in novel semimetals is investigated. By examining the YbMnSb2 nodal line semimetal as an example, the Dirac bands appear to provide a low resistivity along the direction in which they are highly dispersive. Moreover, because of the regular-band-provided density of states, a large Seebeck coefficient over 160 µV K−1 at 300 K is achieved in both directions, which is very high for a semimetal with high carrier concentration. The combined highly dispersive Dirac and regular bands lead to ten times increase in power factor, reaching a value of 2.1 mW m−1 K−2 at 300 K. The present work highlights the potential of such novel semimetals for unusual electronic transport properties and guides strategies towards high thermoelectric performance. © 2020 The Authors. Advanced Materials published by Wiley-VCH Gmb

Research on the Effect of Heat Pipe Inclination Angle on Temperature Distribution in Electrical Machines

Due to high equivalent thermal conductivity with lightweight and small size, heat pipes (HPs) are being extensively applied in the motor cooling system to improve its thermal performance. However, when practically installed in electrical machines, the inclination angle of the HP will affect its thermal conductivity and motor temperature distribution as well, which is still unclear. This article intends to figure out the effects of HP inclination angle on motor temperature distribution via both theoretical and experimental investigation. Based on the theoretical analysis of the HP inclination effect, the equivalent thermal conductivity of the HP with different inclination angles from 0° to 180° is experimentally investigated on a dedicated platform. Then, temperature distribution across a full-size stator-winding assembly with HPs is quantitatively studied using an established thermal model. Finally, the thermal simulation results are experimentally verified by testing on a processed specimen. The results indicate that the HP thermal performance degrades by over 80% with the inclination angle from 0° to 180°, which results in a significant temperature nonuniformity across the motor under liquid cooling conditions