Optimal charging plan for electric bus considering time-of-day electricity tariff

Purpose: The purpose of this study is to develop an optimization method for charging plans with the implementation of time-of-day (TOD) electricity tariff, to reduce electricity bill. Design/methodology/approach: Two optimization models for charging plans respectively with fixed and stochastic trip travel times are developed, to minimize the electricity costs of daily operation of an electric bus. The charging time is taken as the optimization variable. The TOD electricity tariff is considered, and the energy consumption model is developed based on real operation data. An optimal charging plan provides charging times at bus idle times in operation hours during the whole day (charging time is 0 if the bus is not get charged at idle time) which ensure the regular operation of every trip served by this bus. Findings: The electricity costs of the bus route can be reduced by applying the optimal charging plans. Originality/value: This paper produces a viable option for transit agencies to reduce their operation costs

AMD-DBSCAN: An Adaptive Multi-density DBSCAN for datasets of extremely variable density

DBSCAN has been widely used in density-based clustering algorithms. However, with the increasing demand for Multi-density clustering, previous traditional DSBCAN can not have good clustering results on Multi-density datasets. In order to address this problem, an adaptive Multi-density DBSCAN algorithm (AMD-DBSCAN) is proposed in this paper. An improved parameter adaptation method is proposed in AMD-DBSCAN to search for multiple parameter pairs (i.e., Eps and MinPts), which are the key parameters to determine the clustering results and performance, therefore allowing the model to be applied to Multi-density datasets. Moreover, only one hyperparameter is required for AMD-DBSCAN to avoid the complicated repetitive initialization operations. Furthermore, the variance of the number of neighbors (VNN) is proposed to measure the difference in density between each cluster. The experimental results show that our AMD-DBSCAN reduces execution time by an average of 75% due to lower algorithm complexity compared with the traditional adaptive algorithm. In addition, AMD-DBSCAN improves accuracy by 24.7% on average over the state-of-the-art design on Multi-density datasets of extremely variable density, while having no performance loss in Single-density scenarios. Our code and datasets are available at https://github.com/AlexandreWANG915/AMD-DBSCAN.Comment: Accepted at DSAA202

A Heterogeneous Parallel Non-von Neumann Architecture System for Accurate and Efficient Machine Learning Molecular Dynamics

This paper proposes a special-purpose system to achieve high-accuracy and high-efficiency machine learning (ML) molecular dynamics (MD) calculations. The system consists of field programmable gate array (FPGA) and application specific integrated circuit (ASIC) working in heterogeneous parallelization. To be specific, a multiplication-less neural network (NN) is deployed on the non-von Neumann (NvN)-based ASIC (SilTerra 180 nm process) to evaluate atomic forces, which is the most computationally expensive part of MD. All other calculations of MD are done using FPGA (Xilinx XC7Z100). It is shown that, to achieve similar-level accuracy, the proposed NvN-based system based on low-end fabrication technologies (180 nm) is 1.6x faster and 10^2-10^3x more energy efficiency than state-of-the-art vN based MLMD using graphics processing units (GPUs) based on much more advanced technologies (12 nm), indicating superiority of the proposed NvN-based heterogeneous parallel architecture

Insights into the metabolic profiling of Polygonati Rhizoma fermented by Lactiplantibacillus plantarum under aerobic and anaerobic conditions using a UHPLC-QE-MS/MS system

IntroductionPolygonati Rhizoma is a multi-purpose food with medicinal uses. Fermentation of Polygonati Rhizoma by lactic acid bacteria could provide new insights into the development of Polygonati Rhizoma products.MethodsIn this study, Lactiplantibacillus plantarum was fermented with Polygonati Rhizoma extracts in a bioreactor under aerobic and anaerobic conditions with pH and DO real-time detection. Metabolic profiling was determined by UHPLC-QE-MS/MS system. Principal component analysis and orthogonal partial least-squares discriminant analysis were used to perform multivariate analysis.ResultsA total of 98 differential metabolites were identified in broth after fermentation, and 36 were identified between fermentation under aerobic and anaerobic conditions. The main metabolic pathways in the fermentation process are ABC transport and amino acid biosynthesis. Most of the compounds such as L-arginine, L-aspartic acid, leucine, L-lysine, citrate, inosine, carnitine, betaine, and thiamine were significantly increased during fermentation, playing a role in enhancing food flavor. Compared with anaerobic fermentation, aerobic conditions led to a significant rise in the levels of some compounds such as valine, isoleucine, and glutamate; this increase was mainly related to branched-chain amino acid transaminase, isocitrate dehydrogenase, and glutamate dehydrogenase.DiscussionAerobic fermentation is more beneficial for the fermentation of Polygonati Rhizoma by L. plantarum to produce flavor and functional substances. This study is the first report on the fermentation of Polygonati Rhizoma by L. plantarum and provides insights that would be applicable in the development of Polygonati Rhizoma fermented products

Measurement of the relationship between maxillary premolar roots and the maxillary sinus floor using cone beam CT and analysis of the impact on immediate implantation

Objective To analyze the spatial relationship between the roots of maxillary anterior premolars and the maxillary sinus, thus providing an anatomical basis for timing, planning, surgical approaches, and implant selection at this site. Methods Cone beam CT (CBCT) images were collected from 264 patients (aged 20-65 years) who visited the Ruihua Dental Clinic between January 2017 and March 2023. The minimum distance from the apex of the maxillary anterior premolar roots to the lower wall of the maxillary sinus was measured on the coronal plane. The classification of the vertical relationship between the tooth root and the lower wall of the maxillary sinus was performed, and comparisons were made bilaterally, between genders, and among different age groups. Results The minimum distance (Q50) from the apex of the first maxillary premolar root to the lower wall of the maxillary sinus was 7.34 mm for the single-root type, 7.80 mm for the buccal root of the double-root type, and 7.36 mm for the palatal root. For the second maxillary premolar, the median distance was 2.56 mm for the single root type, 1.73 mm for the buccal root type, and 1.23 mm for the palatal root type. There was a significant difference in the shortest distance from the apex of the right second maxillary premolar single root to the lower wall of the maxillary sinus among the different age groups (P<0.05), with the 20-29-year-old group having the smallest median distance (1.52 mm) and the ≥ 40-year-old group having the largest (4.44 mm). There was no significant difference in the effect of sex or laterality on distance (P>0.05). The most common vertical relationship between the apex of the maxillary anterior premolar roots and the lower wall of the maxillary sinus was noncontact. There was no significant difference in the vertical relationship classification between the single-root and double-root types (P>0.05). Conclusion Most maxillary first premolar roots can provide sufficient bone height, which makes it easy to achieve immediate implantation. The maxillary second premolar root frequently involves insufficient bone, which is necessary to make full use of the bone wall of the extraction socket or the sinus floor cortical bone to achieve initial stability. The vertical relationship between the premolar root and maxillary sinus was influenced by age and dental position. Younger age groups often exhibit inadequate bone height, and the indication for immediate implantation should be carefully considered. The number of roots does not significantly affect the relationship between the sinus and root; however, double-rooted premolars offer more support for immediate implantation and socket healing due to the small root diameter and bony separation between the roots

Increased KIF15 Expression Predicts a Poor Prognosis in Patients with Lung Adenocarcinoma

Background/Aims: Lung cancer is the leading cause of cancer-related deaths worldwide. The outcome of patients with non-small cell lung cancer remains poor; the 5-year survival rate for stage IV non-small cell lung cancer is only 1.0%. KIF15 is a tetrameric kinesin spindle motor that has been investigated for its regulation of mitosis. While the roles of kinesin motor proteins in the regulation of mitosis and their potentials as therapeutic targets in pancreatic cancer have been described previously, the role of KIF15 in lung cancer development remains unknown. Methods: Paired lung carcinoma specimens and matched adjacent normal tissues were used for protein analysis. Clinical data were obtained from medical records. We first examined KIF15 messenger RNA expression in The Cancer Genome Atlas database, and then determined KIF15 protein levels using immunohistochemistry and western blotting. Differences between the groups were analyzed using repeated measures analysis of variance. Overall survival was analyzed using the Kaplan–Meier method. Cell-cycle and proliferation assays were conducted using A549, NCI-H1299, and NCI-H226 cells. Results: KIF15 was significantly upregulated at both the messenger RNA and protein levels in human lung tumor tissues. In patients with lung adenocarcinoma, KIF15 expression was positively associated with disease stages; high KIF15 expression predicted a poor prognosis. KIF15 knockdown using short hairpin RNA in two human lung adenocarcinoma cell lines induced G1/S phase cell cycle arrest and inhibited cell growth, but there was no effect in human lung squamous cell carcinoma. Conclusion: Our findings show that KIF15 is involved in lung cancer carcinogenesis. KIF15 could therefore serve as a specific prognostic marker for patients with lung adenocarcinoma