Allocation of Electric Taxi Charging: Assessing the Layout of Charging Stations Based on Charging Frequency

Recent decades have witnessed the growth of the electric vehicles (EVs) industry due to technological developments. To overcome emerging environmental issues, some metropolises, i.e., Beijing, have employed electric taxi systems, which require tremendous investments in charging stations. However, the supporting charging facilities for EVs are not complete, and in terms of layout, there is also a situation where some charging stations have long charging queues, but some are unvisited. To overcome these difficulties, this paper aims to establish a set of charging stations layout assessment models for the electric taxi based on charging frequency and put forward targeted policy suggestions to make the charging frequency of each station more balanced, to avoid resource waste and undersupply. In this paper, a mathematical model based on integer programming is established in conjunction with the workflow of the electric taxi; in the case study, simulations are performed using the Anylogic platform and the results are statistically analyzed; moreover, we use real-time data to assess the layout of charging stations near and within the Fourth Ring Road in Beijing. The modeling and simulation results show that there is an imbalance in the current charging stations layout in Beijing. More specifically, there is a problem with charging frequency of some stations, which is being too low and some too high. Also, the charging frequency of stations will vary with passenger distribution factors. We classify the studied charging stations into four categories according to their actual usage characteristics and provide specific analysis and optimization suggestions for the different categories. Based on the assessment system in this paper, we also carried out some policy suggestions for further layout optimization. The optimized layout has a more balanced charging frequency, and the variance of charging frequency is reduced largely

MLEE: A method for extracting object-level medical knowledge graph entities from Chinese clinical records

As a typical knowledge-intensive industry, the medical field uses knowledge graph technology to construct causal inference calculations, such as “symptom-disease”, “laboratory examination/imaging examination-disease”, and “disease-treatment method”. The continuous expansion of large electronic clinical records provides an opportunity to learn medical knowledge by machine learning. In this process, how to extract entities with a medical logic structure and how to make entity extraction more consistent with the logic of the text content in electronic clinical records are two issues that have become key in building a high-quality, medical knowledge graph. In this work, we describe a method for extracting medical entities using real Chinese clinical electronic clinical records. We define a computational architecture named MLEE to extract object-level entities with “object-attribute” dependencies. We conducted experiments based on randomly selected electronic clinical records of 1,000 patients from Shengjing Hospital of China Medical University to verify the effectiveness of the method

X-ray Emission of Baryonic Gas in the Universe: Luminosity-Temperature Relationship and Soft-Band Background

We study the X-ray emission of baryon fluid in the universe using the WIGEON cosmological hydrodynamic simulations. It has been revealed that cosmic baryon fluid in the nonlinear regime behaves like Burgers turbulence, i.e. the fluid field consists of shocks. Like turbulence in incompressible fluid, the Burgers turbulence plays an important role in converting the kinetic energy of the fluid to thermal energy and heats the gas. We show that the simulation sample of the $\Lambda$CDM model without adding extra heating sources can fit well the observed distributions of X-ray luminosity versus temperature ($L_{\rm x}$ vs. $T$) of galaxy groups and is also consistent with the distributions of X-ray luminosity versus velocity dispersion ($L_{\rm x}$ vs. $\sigma$). Because the baryonic gas is multiphase, the $L_{\rm x}-T$ and $L_{\rm x}-\sigma$ distributions are significantly scattered. If we describe the relationships by power laws $L_{\rm x}\propto T^{\alpha_{LT}}$ and $L_{\rm x}\propto \sigma^{\alpha_{LV}}$, we find $\alpha_{LT}>2.5$ and $\alpha_{LV}>2.1$. The X-ray background in the soft $0.5-2$ keV band emitted by the baryonic gas in the temperature range $10^5<T<10^7$ K has also been calculated. We show that of the total background, (1) no more than 2% comes from the region with temperature less than $10^{6.5}$ K, and (2) no more than 7% is from the region of dark matter with mass density $\rho_{\rm dm}<50 \bar{\rho}_{\rm dm}$. The region of $\rho_{\rm dm}>50\bar{\rho}_{\rm dm}$ is generally clustered and discretely distributed. Therefore, almost all of the soft X-ray background comes from clustered sources, and the contribution from truly diffuse gas is probably negligible. This point agrees with current X-ray observations.Comment: 32 pages including 14 figures and 2 tables. Final version for publication in Ap

Disc versus wind accretion in X-ray pulsar GX 301-2

GX 301-2 provides a rare opportunity to study both disc and wind accretion in a same target. We report Insight-Hard X-ray Modulation Telescope observations of the spin-up event of GX 301-2 that happened in 2019 and compare with those of wind-fed state. The pulse profiles of the initial rapid spin-up period are dominated by one main peak, while those of the later slow spin-up period are composed of two similar peaks, as those of wind-fed state. These behaviours are confirmed by Fermi/Gamma-ray Burst Monitor data, which also show that during the rapid spin-up period, the main peak increases with luminosity up to 8 × 1037 erg s-1, but the faint peak remains almost constant. The absorption column densities during the spin-up period are ~1.5 × 1023 cm-2, much less than those of wind-fed state at similar luminosity (~9 × 1023 cm-2), supporting the scenario that most of material is condensed into a disc during the spin-up period. We discuss possible differences between disc and wind accretion that may explain the observed different trends of pulse profiles

Dietary intervention reprograms bone marrow cellular signaling in obese mice

ObjectivesThe current study aimed to investigate the pathogenesis of obesity-induced impaired bone mass accrual and the impact of dietary intervention on bone density in the mouse model of obesity.MethodsMice were fed with chow diet (CD) for 10 months, high-fat-diet (HFD) for 10 months, or HFD for 6 months then transferred to chow diet for 4 months (HFDt).ResultsWeight loss and decreased intrahepatic lipid accumulation were observed in mice following dietary intervention. Additionally, HFD feeding induced bone mass accrual, while diet intervention restrained trabecular bone density. These changes were further reflected by increased osteogenesis and decreased adipogenesis in HFDt mice compared to HFD mice. Furthermore, HFD feeding decreased the activity of the Wingless-related integration site (Wnt)-β-Catenin signaling pathway, while the Wnt signaling was augmented by diet intervention in the HFDt group.ConclusionsOur findings suggest that a HFD inhibits bone formation and that dietary intervention reverses this inhibition. Furthermore, the dietary intervention was able to compensate for the suppressed increase in bone mass to a level comparable to that in the CD group. Our study suggests that targeting the Wnt signaling pathway may be a potential approach to treat obesity-induced impaired bone mass accrual

Chemosensitivity of radioresistant cells in the multicellular spheroids of A549 lung adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>The relapse of cancer after radiotherapy is a clinical knotty problem. Previous studies have demonstrated that the elevation of several factors is likely in some way to lead to the development of treatment tolerance, so it is necessary to further explore the problem of re-proliferated radioresistant cells to chemotherapeutic agents. In the present study, we aimed to investigate the chemosensitivity of radioresistant cells originated from the multicellular spheroids of A549 lung adenocarcinoma.</p> <p>Methods</p> <p>After irradiated with 25 Gy of 6 MV X-ray to A549 multicellular spheroids, whose 10th re-proliferated generations were employed as radioresistant cells, and the control groups were A549 parental cells and MCF7/VCR resistant cells. The chemo-sensitivity test was made by six kinds of chemotherapeutic drugs which were DDP, VDS, 5-Fu, HCP, MMC and ADM respectively, while verapamil (VPL) was used as the reversal agent. Then the treatment effect was evaluated by MTT assay, and the multidrug resistant gene expressions of <it>mdr1 </it>and <it>MRP </it>were measured by RT-PCR.</p> <p>Results</p> <p>Both A549 parental cells and A549 derived radioresistant cells were resistant to DDP, but sensitive to VDS, 5-Fu, HCP, MMC and ADM. The inhibitory rates of VPL to these two types of cell were 98% and 25% respectively (P < 0.001). In addition, without drugs added, the absorbance value (A value) of A549 parental cells was 2-folds higher than that of their radioresistant cells (P < 0.001). As to the MCF7/VCR cells, they were resistant to DDP and VDS, but slight sensitive to MMC, ADM, 5-Fu, and HCP with 80% of inhibitory rate to VPL. The subsequent RT-PCR demonstrated that the <it>Mdr1</it>/β2-MG and <it>MRP</it>/β2-MG of all A549 cells were about 0 and 0.7 respectively, and those of MCF7/VCR cells were 35 and 4.36.</p> <p>Conclusion</p> <p>The chemosensitivity of A549 radioresistant cells had not changed markedly, and the decreased sensitivity to VPL could not be explained by the gene expression of <it>mdr1 </it>and <it>MRP</it>. It is possible that the changes in the cell membrane and decreased proliferate ability might be attributed to the resistance. Unlike multidrug resistance induced by chemotherapy, VPL may be not an ideal reverser to radioresistant cells. Therefore, the new biological strategy needs to be developed to treat recurring radioresistant tumor in combination with chemotherapy.</p

Gene Silencing Associated with SWI/SNF Complex Loss during NSCLC Development

The SWI/SNF chromatin-remodeling complex regulates gene expression and alters chromatin structures in an ATP-dependent manner. Recent sequencing efforts have shown mutations in BRG1 (SMARCA4), one of two mutually exclusive ATPase subunits in the complex, in a significant number of human lung tumor cell lines and primary non-small cell lung carcinoma (NSCLC) clinical specimens. To determine how BRG1 loss fuels tumor progression in NSCLC, molecular profiling was performed after restoration of BRG1 expression or treatment with an HDAC inhibitor or a DNMT inhibitor in a BRG1-deficient NSCLC cells. Importantly, validation studies from multiple cell lines revealed that BRG1 re-expression led to substantial changes in the expression of CDH1, CDH3, EHF and RRAD that commonly undergo silencing by other epigenetic mechanisms during NSCLC development. Furthermore, treatment with DNMT inhibitors did not restore expression of these transcripts indicating that this common mechanism of gene silencing did not account for their loss of expression. Collectively, BRG1 loss is an important mechanism for the epigenetic silencing of target genes during NSCLC development

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly characterized from brain diffusion MRI. In addition, to enable analysis of WM tracts in large datasets and in clinical practice it is essential to have methodology that is fast and easy to apply. This work therefore presents a new approach for WM tract segmentation: Neuro4Neuro, that is capable of direct extraction of WM tracts from diffusion tensor images using convolutional neural network (CNN). This 3D end-to-end method is trained to segment 25 WM tracts in aging individuals from a large population-based study (N=9752, 1.5T MRI). The proposed method showed good segmentation performance and high reproducibility, i.e., a high spatial agreement (Cohen's kappa, k = 0.72 ~ 0.83) and a low scan-rescan error in tract-specific diffusion measures (e.g., fractional anisotropy: error = 1% ~ 5%). The reproducibility of the proposed method was higher than that of a tractography-based segmentation algorithm, while being orders of magnitude faster (0.5s to segment one tract). In addition, we showed that the method successfully generalizes to diffusion scans from an external dementia dataset (N=58, 3T MRI). In two proof-of-principle experiments, we associated WM microstructure obtained using the proposed method with age in a normal elderly population, and with disease subtypes in a dementia cohort. In concordance with the literature, results showed a widespread reduction of microstructural organization with aging and substantial group-wise microstructure differences between dementia subtypes. In conclusion, we presented a highly reproducible and fast method for WM tract segmentation that has the potential of being used in large-scale studies and clinical practice.Comment: Preprint to be published in NeuroImag