Distribution Route Optimization for Electric Vehicles in Urban Cold Chain Logistics for Fresh Products under Time-Varying Traffic Conditions

Electric vehicles (EVs) have been widely used in urban cold chain logistic distribution and transportation of fresh products. In this paper, an electric vehicle routing problem (EVRP) model under time-varying traffic conditions is designed for planning the itinerary for fresh products in the urban cold chain. The object of the EVRP model is to minimize the total cost of logistic distribution that includes economic cost and fresh value loss cost. To reflect the real situation, the EVRP model considers several influencing factors, including time-varying road network traffic, road type, client’s time-window requirement, freshness of fresh products, and en route queuing for charging. Furthermore, to address the EVRP, an improved adaptive ant colony algorithm is designed. Simulation test results show that the proposed method can allow EVs to effectively avoid traffic congestion during the distribution process, reduce the total distribution cost, and improve the performance of the cold chain logistic distribution process for fresh products. Document type: Articl

Research Progress and Trend Analysis of "Artificial Intelligence +" Education -- Visual Analysis Based on CiteSpace Knowledge Graph

With the rapid development of artificial intelligence (AI) technology, its application in the field of education has gradually gained popularity. Based on the CiteSpace visual knowledge graph analysis method, this paper makes a systematic visual analysis of the core literatures on artificial intelligence collected by CNKI from 2018 to 2023 in terms of the number of publications, authors, institutions, keyword co-occurrence, clustering and emergence. The analysis results show that in the past six years, the research in the field of "artificial intelligence + education" is in a prosperous period, and the current research hotspots are mainly focused on the application scope of artificial intelligence in the field of education, the impact of artificial intelligence on education and the development direction of artificial intelligence in the field of education in the future. The practical focus of "artificial intelligence + education" mainly focuses on labor education and the cultivation of students' labor literacy

A Route Analysis Study of Artificial Intelligence Enabling Education—Visualization Analysis Based on Citespace Literature Keywords

With the advent of the intelligent era, artificial intelligence technology promotes the innovation and development of the education field. Based on the data in Web of Science database and CNKI database, the article uses Citespace software to construct keyword co-occurrence network mapping, keyword clustering mapping, keyword emergence map, etc. to visualize and analyze the data, and sort out the domestic and international research hotspots, themes, and trends of educational artificial intelligence. It is found that the current research on AI in education in China can be categorized into three major themes: research on empowering education based on technological support, AI for educational change, and research on the application and impact of AI in education; while the research results on AI in education abroad mainly focus on two major themes: case studies on the application of machine learning, and research on the way of focusing on people's teaching/learning based on technological support. The article presents and analyzes the hotspots, themes and trends of domestic and foreign educational artificial intelligence research visually, with a view to understanding the current status of domestic and foreign educational artificial intelligence research, grasping the current research hotspots, themes and trends, finding the differences and connections between domestic and foreign research, and thus putting forward useful references to the development of educational artificial intelligence in China

A method for considering a distributed spring constant for studying the flexural vibration of an Euler-beam with lightweight multistage local resonators

For the traditional locally resonant beams there always attached the one-stage local resonator and result that the lower band gap the heavier the scattering ring. In order to resolve this problem, the flexural vibration band gap in an Euler beam with periodically arranged lightweight multistage local resonators was theoretically investigated using the transfer matrix method based on discretization of lumped mass. The present method considered a distributed spring constant, which showed fast convergence with less computational requirements. A finite element method was then employed to calculate the frequency response function of a finite sample simultaneously, which demonstrated that the results calculated using the proposed method were closer to the simulation results than those obtained using the traditional transfer matrix method. The study found that, under the same additional mass, the lightweight multistage structure had much lower beginning frequency than one-stage structure, and the total width of the gaps was basically the same. In addition, a simplified model of the beginning frequency of gaps was proposed, and the effect of scattering density on the model precision was further explored numerically. The results show that the lower scattering density, the more important the role of the rubber mass and the higher precision of the simplified model

The History and Outlook of Animal Drugs Treating Asthma, Chronic Bronchitis, and Haze Episode-induced Respiratory Diseases

Animal drugs have been historically applied in Chinese remedies for more than two thousands. It was reported that Chinese medical animals consisting of 1,590 species took up 12.5% of the total number of all TCM resources. Those animal drugs such as, earthworm, gecko, periostracum cicadae, and scorpios, of commonly used in China, are very remarkable and traditional for the treatment of asthma or chronic bronchitis. This review presents research advance of animal drugs possessing significant implications for the development of novel anti-asthma or chronic bronchitis drugs. The experimental studies and clinical efficacies against asthma and chronic bronchitis of animal drugs were summarized herein. Moreover, the potential utilization of animal drugs on inhibiting haze/fog induced respiratory diseases was also discusse

Alteration of Brain Structure With Long-Term Abstinence of Methamphetamine by Voxel-Based Morphometry

Background: A large portion of previous studies that have demonstrated brain gray matter reduction in individuals who use methamphetamine (MA) have focused on short-term abstinence, but few studies have focused on the effects of long-term abstinence of methamphetamine on brain structures.Materials and Methods: Our study includes 40 healthy controls and 44 abstinent methamphetamine-dependent (AMD) subjects who have abstained for at least 14 months. For every AMD subject, the age when they first used MA, the total time of MA use, the frequency of MA use in the last month before abstinence, the duration of abstinence and the craving score were recorded. Here we used magnetic resonance imaging (MRI) to measure the gray matter volume (GMV) of each subject with voxel-based morphometry method. Two-sample t-test (AlphaSim corrected) was performed to obtain brain regions with different gray matter volume (GMV) between groups. In addition, partial correlation coefficients adjusted for age, years of education, smoking, and drinking were calculated in the AMD group to assess associations between the mean GMV values in significant clusters and variables of MA use and abstinence.Results: Compared with the healthy control group, AMD group showed increased gray matter volumes in the bilateral cerebellum and decreased volumes in the right calcarine and right cuneus. Moreover, GMV of left cerebellum are positively correlated with the duration of abstinence in the AMD group (p = 0.040, r = 0.626).Conclusions: The present study showed that the gray matter volume in some brain regions is abnormal in the AMD subjects with long-term abstinence. Changes in gray matter volume of visual and cognitive function regions suggested that these areas play important roles in the progress of MA addiction and abstinence. In addition, positive correlation between GMV of the left cerebellum crus and duration of abstinence suggested that prolonged abstinence is beneficial to cognitive function recovery

Multi-dimensional vibration sensing and simultaneous self-homodyne optical transmission of single wavelength net 5.36 Tb/s signal using telecom 7-core fiber

We present a high-capacity self-homodyne optical transmission system that enables simultaneously multidimensional vibration sensing based on a weakly-coupled 7-core fiber. To our knowledge, we demonstrate for the first-time detection of fiber vibration direction along with strength, frequency, and location of the vibration source, while transmitting in the meantime single-carrier 16 QAM signal reaching a net date rate of 5.36 Tb/s over 41.4 km of telecom 7-core fiber.Comment: 5 pages, 4 figure

An essential role for sulfur in sulfide-silicate melt partitioning of gold and magmatic gold transport at subduction settings

Sulfide-silicate melt partitioning controls the behavior of gold in magmas, which is critical for understanding the Earth's deep gold cycle and formation of gold deposits. However, the mechanisms that control the sulfide-silicate melt partitioning of gold remain largely unknown. Here we present constraints from laboratory experiments on the partition coefficient of gold between monosulfide-solid-solution (MSS) and silicate melt (DAuMSS/SM) under conditions relevant for magmatism at subduction settings. Thirty-five experiments were performed in Au capsules to determine DAuMSS/SM at 950-1050°C, 0.5-3 GPa, oxygen fugacity (fO2) of ∼FMQ-1.7 to FMQ+2.7 (FMQ refers to the fayalite-magnetite-quartz buffer), and sulfur fugacity (fS2) of −2.2 to 2.1, using a piston cylinder apparatus. The silicate melt composition changes from dry to hydrous andesite to rhyolite. The results obtained from electron microprobe and laser-ablation ICP-MS analyses show that the gold solubility in silicate melts ranges from 0.01 to 55.3 ppm and is strongly correlated with the melt sulfur content [S]melt at fO2 of ∼FMQ-1.7 to FMQ+1.6, which can be explained by the formation of complex Au-S species in the silicate melts. The gold solubility in MSS ranges from 130 to 2800 ppm, which is mainly controlled by fS2. DAuMSS/SM ranges from 10 to 14000 at fO2 of ∼FMQ-1.7 to FMQ+1.6, the large variation of which can be fully explained by combined [S]melt and fS2. Therefore, all of the parameters that can directly affect [S]melt and fS2, such as alkali metals, water, FeO, and fO2, can indirectly affect DAuMSS/SM. The mechanisms that control the sulfide-silicate melt partitioning of gold and the other chalcophile elements, such as Ni, Re, and Mo, differ significantly. This is because gold is dissolved mainly as Au-S species in the silicate melts, while the other chalcophile elements are dissolved mainly as metal oxides in the silicate melts. Applying the correlation between DAuMSS/SM and [S]melt to slab melting and arc magmatic differentiation under different redox conditions, we find that ancient to modern slab melts carry negligible to less than 25% of the slab gold to the subarc mantle; however, gold-enrichment can occur in MSS-saturated arc magmas that have differentiated under moderately oxidized conditions with fO2 between FMQ and FMQ+1.6, in particular if the magmatic crystallization follows a fractional crystallization model. We conclude that moderately oxidized magmas with high contents of alkali metals, sulfur, and water, owing to their low DAuMSS/SM and efficient magma-to-fluid transfer of gold and sulfur, have a high potential to form gold deposits

Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions

BackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.MethodsFifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.ResultsThe ADCmean, ADCmedian, Dmean and Dmedian values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kappmean, Kappmedian, KappSD, Kappkurtosis and Dappskewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and Dmedian (p = 0.031) were identified as independent predictors of lung cancer. Dmedian showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a Dmedian of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.ConclusionsWhole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and Dmedian shows the best performance in the differential diagnosis of solitary pulmonary lesions

A case-crossover study on association between ambient temperature and injury incidence in Shenzhen City

BackgroundUnder the background of global warming, research on association between ambient temperature and risk of injury is needed. ObjectiveTo examine the effect of temperature on injury in Bao'an district, Shenzhen and identify the sensitive population, thereby providing a scientific basis for formulating prevention and control strategies and measures of injury. MethodsThe injury reports from the Injury Surveillance System and the meteorological data of Bao'an District between 2018 to 2022 were collected. The meteorological data were sourced from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) land reanalysis data. Based on time-stratified case-crossover design, conditional logistic regression combined with distributed lag nonlinear model was used to evaluate the exposure-response association between ambient temperature and injury. The stratified analyses were further conducted by gender, age, and causes of injury. ResultsA total of 156205 injury cases were collected from the injury surveillance sentinel hospitals in Bao'an District of Shenzhen from 2018 to 2022, and the median of daily average temperature during the same period was 20.0 ℃. The exposure-response curve showed that the risk of injury was positively correlated with temperature. The linearized analysis revealed that each 1°C increase in temperature was associated with a 1.05% (95%CI: 0.68%, 1.42%) rise in injury risk (ER). Notably, the effect was greater in females (ER=1.31%, 95%CI: 0.67%, 1.94%) than males (ER=0.92%, 95%CI: 0.47%, 1.37%). Among age groups, adults ＞60 years faced the highest risk (ER=1.91%, 95%CI: −0.36%, 4.24%). The top three temperature-associated injury risks were sharp instrument injuries (ER=2.19%, 95%CI: 1.16%, 3.22%), animal injuries (ER=1.71%, 95%CI: 0.86%, 2.56%), and blunt injuries (ER=071%, 95%CI: −0.08%, 1.51%). The impact of temperature on unintentional injuries (ER=1.11%, 95%CI: 0.72%, 1.49%) was higher than that on intentional injuries (ER=0.43%, 95%CI: −0.85%, 1.72%). Severe injuries (ER=2.20%, 95%CI: −3.09%, 7.77%) were more affected by temperature than mild injuries (ER=1.00%, 95%CI: 0.58%, 1.43%) and moderate injuries (ER=1.15%, 95%CI: 0.42%, 1.89%). ConclusionThe increase in ambient temperature associates with injury occurrence, and the impact of temperature exhibits obvious heterogeneity among different populations, indicating that targeted intervention measures should be taken for different populations and types of injuries