Search

The development of the vehicle-road cooperative intelligence can effectively resolve the current technical impediment and cost quandary associated with high-level autonomous driving. Nevertheless, the intelligent infrastructure entails initial deployment costs and ongoing energy consumption and maintenance costs, necessitating a comprehensive and quantitative analysis of the costs of intelligent infrastructure and the corresponding changes in comprehensive costs. The cost evaluation model for the cooperative intelligent system is designed in this paper, considering the corresponding intelligent infrastructure layout scheme for different road types within the technical framework. The intelligent configuration and corresponding cost transfer from roadside to vehicle side under the synergy effect is also analyzed. Using Beijing as a case study, the results indicate that the deployment of intelligent infrastructure will effectively reduce acquisition and usage costs of high-level intelligent vehicles and achieve a greater “reuse” effect by serving more intelligent connected vehicles (ICVs). Compared to the vehicle intelligence, collaborative intelligence will reduce cumulative total costs by more than ¥200 billion from 2023 to 2050, even with the inclusion of intelligent infrastructure's costs., Author(s): Guangyu Zhu [1,2]; Fuquan Zhao [1,2]; Haokun Song [1,2]; Zongwei Liu (corresponding author) [1,2] 1. Introduction Autonomous driving has become a significant factor influencing the development of the automotive [...]

Three novel sesquiterpenoid heterodimers, designated as auckcostusolides A–C (1 – 3), were isolated from Aucklandia costus leaves. The structures of compounds 1 – 3 were elucidated through comprehensive spectroscopic analysis, with their absolute configurations established using a combination of X-ray single-crystal diffraction and electronic circular dichroism (ECD) calculations. Notably, compounds 1 and 2 , despite sharing identical planar structures derived from two identical sesquiterpenoids, exhibited opposite configurations at C-11 and C-8′. This configurational difference can be attributed to distinct Diels−Alder cycloaddition processes between the sesquiterpenoid monomers. Additionally, the cytotoxic effects of compounds 1 – 3 were evaluated against colorectal cancer HCT116 cells, fibrosarcoma HT1080 cells, and hepatocellular carcinoma HepG2 cells. Compounds 1 – 3 induced cell death was characterized by endoplasmic reticulum (ER) swelling and cytoplasmic vacuolization, typical morphological changes associated with paraptosis. Mechanistic studies revealed that compounds 1 and 3 triggered paraptosis-like cell death through the accumulation of reactive oxygen species (ROS), activation of ER stress, and stimulation of the MAPK signaling pathway. [ABSTRACT FROM AUTHOR]

The article discusses the implementation of the Rapid Interactive screening Test for Autism in Toddlers (RITA‐T) model in underserved areas to improve the diagnosis of autism spectrum disorder (ASD). The study found that toddlers screened with RITA‐T came from more deprived areas, traveled farther, and were diagnosed earlier. The RITA‐T model is an easy-to-use screening measure that has successfully identified high-risk toddlers from underserved areas. The article emphasizes the importance of early identification and intervention, and highlights the barriers faced by culturally and linguistically diverse (CLD) backgrounds and underserved areas. The study found that toddlers referred through the RITA-T system had shorter wait times, traveled further, and came from different racial backgrounds, lower household incomes, and more disadvantaged neighborhoods. The RITA-T screening model improved access to diagnostic services and reduced paperwork for families. Further training and implementation of this model in other settings is necessary. [Extracted from the article]

The vehicle-road collaborative intelligence approach has become an industry consensus. It can efficiently tackle the technical hurdles and reduce the performance requirements and costs of on-board perception and computing devices. There is a need for in-depth quantitative studies to optimize the allocation of vehicle-road intelligent capabilities for collaborative intelligence. However, current research tends to focus more on qualitative analysis, and there is little research on the redistribution of vehicle and roadside intelligent capabilities. In this paper, we present a model for distributing perception and computing capabilities between vehicle-side and roadside, ensuring to meet the needs of various autonomous driving levels. Meanwhile, the collaborative intelligence approach will also introduce the costs of intelligent infrastructure deployment, energy, and maintenance. Different roads have varying scene characteristics and usage intensities. It is necessary to conduct a cost-effectiveness analysis of the intelligent deployment of different road types. A vehicle-road cost allocation model is developed based on the lifecycle traveled distance of vehicles and the lifecycle traffic flow of various roads to evaluate the function-cost effectiveness. Our study presents several vehicle-road intelligent schemes that meet the needs of various autonomous driving levels and selects Beijing for case analysis. The results indicate that primary intelligent infrastructure can reduce the lifecycle cost of the vehicle-side intelligent scheme for intermediate autonomous driving from ¥65,301 to ¥37,703, and advanced intelligent infrastructure can reduce the lifecycle cost for advanced autonomous driving from ¥126,938 to ¥42,180. Considering the distributed cost of vehicle-side and roadside, urban roads in Beijing have higher function-cost effectiveness compared to highways, especially urban expressways, which are expected to generate 43.3 times the vehicle-function-cost benefits after the advanced intelligent upgrades. The corresponding research findings can serve as a reference for city managers to make decisions on intelligent road deployment. [ABSTRACT FROM AUTHOR]

Aim: Climate is widely understood to determine elevational patterns of soil microbial communities, whereas the effects of parental material are uncertain. Changes in the composition of parental materials along elevational transects could also affect soil microbial communities by influencing soil pH and nutrient availability. Here, we aim to illustrate the combined effects of climate and parental material on the biomass and composition of soil microbial communities along an elevational transect. Location: A subtropical forest on a karst mountain (Mt. Jinfo), China. Taxon: Bacteria and Fungi. Methods: We use phospholipid fatty acid analysis (PLFA) and DNA amplicon high‐throughput sequencing to determine biomass and diversity patterns of soil microbial communities along a subtropical elevational gradient with contrasting parental materials (limestone and clasolite). Results: We observed that the microbial communities were more diverse (α‐diversity) and productive (biomass) on limestone than on clasolite. Additionally, we found that parental material played a role in shaping the composition (β‐diversity) of soil microbial communities along the elevational gradient. The impact of climate on soil microbial communities was found to be significant, albeit relatively weak. Structural equation models provided evidence for both direct and indirect effects of climate and parental material on microbial biomass and α‐diversity along the elevational gradient. Notably, the changes in soil pH, influenced by both parental material and climate, were identified as a key factor driving these effects. Main Conclusions: Our results underline the importance of both climate and parental material variations in space‐for‐time studies investigating soil microbial communities along elevational gradients. [ABSTRACT FROM AUTHOR]

Non-destructive measurements of low-intensity charged particle beams are particularly challenging for beam diagnostics. At the Heavy Ion Accelerator Facility in Lanzhou (HIRFL), beams with weak currents below 1 µA are often provided for experiments. The detection of such low beam current is below the threshold of typical standard beam current transformers. Therefore, a low-intensity monitoring system is developed by using a sensitive capacitive pick-up (PU) and low-noise electronics. This device measures beam currents by digitally analyzing the amplitude of the PU signals using a homodyne detection scheme. During lab tests, the amplitude nonlinearity is <0.5% in the operational range of 1 nA–45 µA and the amplitude resolution is 0.94 nA. At present, four measurement systems for low beam currents are installed at HIRFL for the monitoring of standard operating conditions with low beam currents below 1 µA. After an absolute calibration with a Faraday cup, it can be used for accurate beam intensity measurement with a current resolution of about 1 nA. [ABSTRACT FROM AUTHOR]

Objective: In this case report, the auxiliary role of deep learning and 3-dimensional printing technology in the perioperative period was discussed to guide transcatheter aortic valve replacement and coronary stent implantation simultaneously. Case presentation: A 68-year-old man had shortness of breath and chest tightness, accompanied by paroxysmal nocturnal dyspnea, 2 weeks before presenting at our hospital. Echocardiography results obtained in the outpatient department showed severe aortic stenosis combined with regurgitation and pleural effusion. The patient was first treated with closed thoracic drainage. After 800 mL of pleural effusion was collected, the patient's symptoms were relieved and he was admitted to the hospital. Preoperative transthoracic echocardiography showed severe bicuspid aortic valve stenosis combined with calcification and aortic regurgitation (mean pressure gradient, 42 mmHg). Preoperative computed tomography results showed a type I bicuspid aortic valve with severe eccentric calcification. The leaflet could be seen from the left coronary artery plane, which indicated an extremely high possibility of coronary obstruction. After preoperative imaging assessment, deep learning and 3-dimensional printing technology were used for evaluation and simulation. Guided transcatheter aortic valve replacement and a coronary stent implant were completed successfully. Postoperative digital subtraction angiography showed that the bioprosthesis and the chimney coronary stent were in ideal positions. Transesophageal echocardiography showed normal morphology without paravalvular regurgitation. Conclusion: The perioperative guidance of deep learning and 3-dimensional printing are of great help for surgical strategy formulation in patients with severe bicuspid aortic valve stenosis with calcification and high-risk coronary obstruction. [ABSTRACT FROM AUTHOR]