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Intelligent connected vehicles (ICVs) are believed to change people’s life in the near future by making the transportation safer, cleaner and more comfortable. Although many prototypes of ICVs have been developed to prove the concept of autonomous driving and the feasibility of improving traffic efficiency, there still exists a significant gap before achieving mass production of high-level ICVs. The objective of this study is to present an overview of both the state of the art and future perspectives of key technologies that are needed for future ICVs. It is a challenging task to review all related works and predict their future perspectives, especially for such a complex and interdisciplinary area of research. This article is organized to overview the ICV key technologies by answering three questions: what are the milestones in the history of ICVs; what are the electronic components needed for building an ICV platform; and what are the essential algorithms to enable intelligent driving? To answer the first question, the article has reviewed the history and the development milestones of ICVs. For the second question, the recent technology advances in electrical/electronic architecture, sensors, and actuators are presented. For the third question, the article focuses on the algorithms in decision making, as the perception and control algorithm are covered in the development of sensors and actuators. To achieve correct decision-making, there exist two different approaches: the principle-based approach and data-driven approach. The advantages and limitations of both approaches are explained and analyzed. Currently automotive engineers are concerned more with the vehicle platform technology, whereas the academic researchers prefer to focus on theoretical algorithms. However, only by incorporating elements from both worlds can we accelerate the production of high-level ICVs.

Total intracranial volume (TIV/ICV) is an important covariate for volumetric analyses of the brain and brain regions, especially in the study of neurodegenerative diseases, where it can provide a proxy of maximum pre-morbid brain volume. The gold-standard method is manual delineation of brain scans, but this requires careful work by trained operators. We evaluated Statistical Parametric Mapping 12 (SPM12) automated segmentation for TIV measurement in place of manual segmentation and also compared it with SPM8 and FreeSurfer 5.3.0. For T1-weighted MRI acquired from 288 participants in a multi-centre clinical trial in Alzheimer's disease we find a high correlation between SPM12 TIV and manual TIV (R2=0.940, 95% Confidence Interval (0.924, 0.953)), with a small mean difference (SPM12 40.4±35.4ml lower than manual, amounting to 2.8% of the overall mean TIV in the study). The correlation with manual measurements (the key aspect when using TIV as a covariate) for SPM12 was significantly higher (p<0.001) than for either SPM8 (R2=0.577 CI (0.500, 0.644)) or FreeSurfer (R2=0.801 CI (0.744, 0.843)). These results suggest that SPM12 TIV estimates are an acceptable substitute for labour-intensive manual estimates even in the challenging context of multiple centres and the presence of neurodegenerative pathology. We also briefly discuss some aspects of the statistical modelling approaches to adjust for TIV. [Display omitted] •288 T1 MRI from multiple scanners were manually segmented for intracranial volume.•We compare SPM12 with the current methods of estimating intracranial volume.•SPM12 shows a very high correlation with manual measures and little bias.•Newer automated volume measures are more accurate controls for head size variation.

RationaleIntracerebroventricular (ICV) streptozotocin (STZ) mimics sporadic Alzheimer’s disease (SAD) characterized by tau pathology and neurodegeneration arising from oxidative stress, mitochondrial dysfunction, and insulin resistance. 7,8-Dihydroxyflavone (7,8-DHF) is a flavonoid having antioxidant property interlinked with mitochondrial functioning and insulin actions.ObjectivesTo evaluate the neuroprotective and cognitive enhancement properties of 7,8-DHF in an ICV-STZ rat model of SAD.MethodsICV-STZ (3 mg/kg) was injected into male Wistar rats. Cognitive functions were evaluated by Morris water maze (MWM) and novel object recognition (NOR). 7,8-DHF (5 mg/kg, 10 mg/kg, and 20 mg/kg) and rivastigmine (2 mg/kg) were given orally for 21 days. Reduced glutathione (GSH), catalase, superoxide dismutase (SOD), glutathione peroxidase (GPX), lipid peroxidation (LPO), protein carbonylation (PCO), and nitrite assays were performed. Mitochondrial enzyme complex I, II, III, and IV, and acetylcholinesterase (AchE) activities were determined. ELISA for the insulin-degrading enzyme (IDE) and p-tau was done. Histopathology was investigated by hematoxylin and eosin staining.Results7,8-DHF treatment attenuated ICV-STZ-induced cognitive deficit in MWM and NOR. Moreover, in the cortex and hippocampus regions of the brain, GSH, catalase, SOD, GPX, LPO, PCO, and nitrite levels were reversed. Mitochondrial enzyme complex I, II, III, and IV, and acetylcholinesterase (AchE) activities were also normalized. IDE and p-tau protein were found to be significantly altered. 7,8-DHF provided protection from neuronal cell death examined in histopathology.ConclusionsConclusively, 7,8-DHF was found to be neuroprotective in the ICV-STZ rat model by ameliorating oxidative stress, mitochondrial dysfunction, and insulin resistance, thereby improving cognitive functions evident with the behavioral results.

Environment perception plays a crucial role in autonomous driving technology. However, various factors such as adverse weather conditions and limitations in sensing equipment contribute to low perception accuracy and a restricted field of view. As a result, intelligent connected vehicles (ICVs) are currently only capable of achieving autonomous driving in specific scenarios. This paper conducts an analysis of the current studies on image or point cloud processing and cooperative perception, and summarizes three key aspects: data pre-processing methods, multi-sensor data fusion methods, and vehicle–infrastructure cooperative perception methods. Data pre-processing methods summarize the processing of point cloud data and image data in snow, rain and fog. Multi-sensor data fusion methods analyze the studies on image fusion, point cloud fusion and image-point cloud fusion. Because communication channel resources are limited, the vehicle–infrastructure cooperative perception methods discuss the fusion and sharing strategies for cooperative perception information to expand the range of perception for ICVs and achieve an optimal distribution of perception information. Finally, according to the analysis of the existing studies, the paper proposes future research directions for cooperative perception in adverse weather conditions.

Whether head size and/or biological sex influence proxies of white matter (WM) microstructure such as fractional anisotropy (FA) and mean diffusivity (MD) remains controversial. Diffusion tensor imaging (DTI) indices are also associated with age, but there are large discrepancies in the spatial distribution and timeline of age‐related differences reported. The aim of this study was to evaluate the associations between intracranial volume (ICV), sex, and age and DTI indices from WM in a population‐based study of healthy individuals (n = 812) aged 50–66 in the Nord‐Trøndelag health survey. Semiautomated tractography and tract‐based spatial statistics (TBSS) analyses were performed on the entire sample and in an ICV‐matched sample of men and women. The tractography results showed a similar positive association between ICV and FA in all major WM tracts in men and women. Associations between ICV and MD, radial diffusivity and axial diffusivity were also found, but to a lesser extent than FA. The TBSS results showed that both men and women had areas of higher and lower FA when controlling for age, but after controlling for age and ICV only women had areas with higher FA. The ICV matched analysis also demonstrated that only women had areas of higher FA. Age was negatively associated with FA across the entire WM skeleton in the TBSS analysis, independent of both sex and ICV. Combined, these findings demonstrated that both ICV and sex contributed to variation in DTI indices and emphasized the importance of considering ICV as a covariate in DTI analysis. The results showed a similar positive association between intracranial volume (ICV) and fractional anisotropy (FA) in all major white matter tracts in men and women. Both men and women had areas of higher and lower FA when controlling for age, but after controlling for age and ICV, and when performing the analysis in the ICV‐matched sample, only women had areas with higher FA. Combined, these findings demonstrated that both ICV and sex contributed to variation in diffusion tensor imaging (DTI) indices and emphasized the importance of considering ICV as a covariate in DTI analysis.

Alzheimer’s disease (AD) is a predominantly heterogeneous disease with a highly complex pathobiology. The presence of amyloid-beta (Aβ) depositions and the accumulation of hyperphosphorylated tau protein remain the characteristic hallmarks of AD. These hallmarks can be detected throughout the brain and other regions, including cerebrospinal fluid (CSF) and the spinal cord. Microglia cells, the brain-resident macrophage type of the brain, are implicated in maintaining healthy brain homeostasis. The localized administration of primary healthy microglia (PHM) is suggested to play a role in mitigating AD hallmark depositions and associated cognitive dysfunction. Carbenoxolone (CBX) is the most common gap junction blocker. It cannot effectively cross the blood–brain barrier (BBB) under systemic administration. Therefore, localized administration of CBX may be a recommended intervention against AD by acting as an antioxidant and anti-inflammatory agent. This study aims to determine whether the localized intracerebroventricular (ICV) administration of PHM and CBX may act as an effective therapeutic intervention for AD neuroinflammatory type. In addition, this study also aims to reveal whether detecting AD hallmarks in the spinal cord and CSF can be considered functional and effective during AD early diagnosis. Male albino rats were divided into four groups: control (group 1), lipopolysaccharide (LPS)-induced AD neuroinflammatory type (group 2), ICV injection of LPS + isolated PHM (group 3), and ICV injection of LPS + CBX (group 4). Morris water maze (MWM) was conducted to evaluate spatial working memory. The brain and spinal cord were isolated from each rat with the collection of CSF. Our findings demonstrate that the localized administration of PHM and CBX can act as promising therapeutic approaches against AD. Additionally, Aβ and tau toxic aggregates were detected in the spinal cord and the CSF of the induced AD model concomitant with the brain tissues. Overall, it is suggested that the ICV administration of PHM and CBX can restore normal brain functions and alleviate AD hallmark depositions. Detecting these depositions in the spinal cord and CSF may be considered in AD early diagnosis. As such, conducting clinical research is recommended to reveal the benefits of related therapeutic approaches compared with preclinical findings.

[This corrects the article DOI: 10.3389/fphar.2021.662173.].

During the past 15 years, several genetically altered mouse models of human Alzheimer’s disease (AD) have been developed. These costly models have greatly facilitated the evaluation of novel therapeutic approaches. Injecting synthetic β-amyloid (Aβ) 1-42 species into different parts of the brain of non-transgenic rodents frequently provided unreliable results, owing to a lack of a genuine characterization of the administered Aβ aggregates. Previously, we have published a new rat AD-model in which protofibrillar-fibrillar Aβ1-42 was administered into rat entorhinal cortex (Sipos 2007). In order to develop a more reliable model, we have injected well-characterized toxic soluble Aβ1-42 species (oligomers, protofibrils and fibrils) intracerebroventricularly (icv) into rat brain. Studies of the distribution of fluorescent-labeled Aβ1-42 in the brain showed that soluble Aβ-species diffused into all parts of the rat brain. After seven days, the Aβ-treated animals showed a significant decrease of spatial memory in Morris water maze test and impairment of synaptic plasticity (LTP) measured in acute hippocampal slices. The results of histological studies (decreased number of viable neurons, increased tau levels and decreased number of dendritic spines) also supported that icv administration of well-characterized toxic soluble Aβ species into rat brain provides a reliable rat AD-model.

Hydraulic controlled intelligent well completion technology is a comprehensive system engineering covering petroleum engineering, mechanical and electronic engineering, automation engineering, communication engineering, computer engineering and other disciplines. The foundational innovation revolves around continuous subsurface data surveillance and advanced fluid flow management systems in downhole environments. Through the throttling regulation characteristics of intelligent water distribution valves, differential management of flow rates in various reservoir layers or branch channels can be achieved. This enables precise adjustment of fluid production dynamics, dynamic control of development processes, and optimal allocation of production capacity benefits in oil reservoirs. This paper examines the technological evolution trajectory of hydraulically-actuated intelligent completion systems within global industry benchmark projects. By employing a multi-dimensional evaluation framework, it conducts in-depth analysis of core technologies, specifically investigating the signal transmission mechanisms and pressure-resistant sealing performance metrics of downhole electro-hydraulic wet-mate connectors, as well as the dynamic response characteristics of subsurface fluid-controlled flow regulation valves, with emphasis on their synergistic operational mechanisms in key technical modules. Considering the prevailing technological constraints and operational characteristics, this approach is deeply integrated with the development realities of China’s oil and gas fields. The paper systematically elucidates the industrialization prerequisites and core technological challenges in developing hydraulically-actuated intelligent completion systems within China’s specific context. By establishing a theoretical framework tailored for complex geological environments, it formulates technical roadmap benchmarks to guide the industrial-scale implementation of intelligent completion technologies in Chinese oil and gas fields.

The combination of in-vehicle networks and smart car devices has gradually developed into Intelligent Connected Vehicles (ICVs). Through the vehicle security protocol, ICVs can quickly realize communication transmission. However, with the more frequent connections between smart in-vehicle devices and the network, the relationship between intelligent cars and external systems is becoming more and more complicated, and in-vehicle networks are gradually facing many security issues. Strengthening the security of in-vehicle protocols has become particularly important. This paper uses the model building method based on the Colored Petri Net (CPN) theory to model the Scalable service-Oriented MiddlewarE over IP (SOME/IP) protocol of the vehicle Ethernet. The security protocol is formally verified and analyzed by combining it with the Dolev–Yao adversary model detection method. After verification, the protocol is subject to three attack vulnerabilities: replay, tampering, and deception. We introduce timestamps and random numbers to strengthen the protocol security. After the final analysis and verification, the improved scheme in this paper can effectively improve the security performance of the protocol.