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Current adaptive cruise control (ACC) systems adopt a fixed desired time headway, which often leads to abrupt speed changes in response to a close new leader after a cut-in or a lane change. These are disruptive maneuvers. In contrast, human drivers are willing to accept spacings much smaller than equilibrium values at the onset of these maneuvers and then gradually increase the spacing until they again reach equilibrium. This process, which typically lasts around 20 s or 30 s, is known as driver relaxation, which improves comfort and capacity. Therefore, this paper aims to incorporate relaxation into ACC systems. Based on the open-source factory-level ACC platform Openpilot by Comma.ai, the paper proposes a feasible relaxation model compatible with recent market ACC systems. The model is tested using simulation and road tests using a 2019 Honda Civic with its stock ACC hardware. The study further investigates the potential benefits of relaxation ACC on traffic operations. Comparative simulations suggest that incorporating relaxation into ACC can help: (i) reduce the magnitude of speed perturbations in both cut-in vehicles and followers; (ii) stabilize the lane-changing (LC) traffic by reducing the speed variance and preventing the lateral propagation of congestion; and (iii) increase the average flow speed and capacity after a bottleneck occurs.

This paper investigates a new class of non-autonomous second-order measure evolution systems involving state-dependent delay and non-instantaneous impulses. We introduce a stronger concept of exact controllability called total controllability. The existence of mild solutions and controllability for the considered system are obtained by applying strongly continuous cosine family and the Mönch fixed point theorem. Finally, an example is used to verify the practical application of the conclusion.

This paper is mainly concerned with a class of fractionalp,q-difference equations underp,q-integral boundary conditions. Multiple positive solutions are established by using the topological degree theory and Krein–Rutman theorem. Finally, two examples are worked out to illustrate the main results.

Early monitoring of gastrointestinal diseases via orally delivered NIR-II ratiometric fluorescent probes represents a promising noninvasive diagnostic modality, but is challenging due to the limitation of harsh digestive environment. Here, we report a single-component NIR-II ratiometric molecular nanoprobe (LC-1250 NP) to monitor gastrointestinal disease with high specificity to its biomarker H

This paper is concerned with the existence of mild solutions and approximate controllability for a class of noninstantaneous impulsive fractional neutral measure evolution systems with state-dependent delay. First, the existence of mild solutions for the considered system is obtained by using Kuratowski’s measure of noncompactness and the set contraction fixed point theorem. Next, under the assumption that the correlated linear system is approximately controllable, the approximate controllability of the system is studied. Finally, we present two applications to support the practical usefulness of the study

Connected and autonomous vehicles (CAVs) can be leveraged to enable cooperative platooning control to alleviate traffic oscillations. However, in the near future, CAVs and human-driven vehicles (HDVs) will coexist on roads, creating a mixed-flow traffic environment. In mixed-flow traffic, CAV platoons would inevitably encounter lane changes by HDVs in adjacent lanes. These lane changes can generate disturbances and oscillations upstream, jeopardizing the performance of platooning control. Hence, it is necessary to explore the interactions between CAVs and HDVs in the lane-change process, to analyze how CAVs can be used to manage disruptive lane changes of HDVs in mixed-flow traffic. This study proposes deep reinforcement learning-based proactive longitudinal control for CAVs to counteract disruptive HDV lane-change behaviors that can induce disturbances, such that the smoothness of traffic flow can be preserved in the platooning control process. Results from numerical experiments suggest that CAVs controlled by the proposed control strategy can effectively reduce the occurrence of disruptive lane-change maneuvers of HDVs to improve string stability performance in mixed-flow traffic. Further, the reliability of the proposed control strategy for different HDV driver types is illustrated.

The abundance of organic matter in shales, which has a direct effect on the hydrocarbon generation potential of shales, is an important organic geochemical parameter for evaluating shale gas reservoirs. The total organic carbon content (TOC content) in shale is controlled by the abundance of original sedimentary organic matter. Therefore, it is very important to study the mechanism of organic matter enrichment in shale. In this paper, the Lower Cambrian marine shales from the Lower Yangtze region are selected as the research subject, most of which originate from a typical area well called Well JXY1. The degree of pyritization (DOP) is used to characterize the redox environment of the water body, while the P/Al ratio is used to analyze the biological productivity of paleoseawater. The paleosalinity of seawater is calculated via carbon and oxygen isotope analysis. In addition, the early Cambrian hydrothermal activities were studied by using core description; Si, Al, Fe, and Mn elemental analysis; and oxygen isotope calculations. The results show that during the early Cambrian Wangyinpu sedimentary period, the seawater was an anaerobic water body with H2S, and the oxygen concentration was approximately 0 mL/L. In the middle stages of the Wangyinpu sedimentary period, the water body had the strongest reducibility and the highest biological productivity. Moreover, the paleoocean in this period between the Yangtze plate and the Cathaysian plate was greatly affected by hydrothermal activities, with temperatures ranging from 90°C to 120°C. Active hydrothermal activities promoted high biological productivity and an anaerobic environment, both of which were conducive to the preservation and enrichment of organic matter, resulting in extremely high TOC content in the Wangyinpu shales (from 6.5% to approximately 16%).

In this article, we propose an efficient quantum $k$ -collision search algorithm with low quantum memory $O(n)$ . The previous quantum $k$ -collision algorithms can not be converted into a low quantum memory $k$ -collision algorithm directly, because the time complexity of the converted algorithm is larger than the basic $k$ -collision algorithm. To solve this problem, we shall not only divide our low memory quantum $k$ -collision algorithm into several subroutines, but also need to achieve some balances between these subroutines. The time complexity of our $k$ -collision search algorithm is $\widetilde {O}\left({2^{\frac {(2^{k}-2)n}{2^{k+1}-3}}}\right)$ , and the classical memory and quantum memory complexities are $\widetilde {O}\left({2^{\frac {(2^{k-1}-1)n}{2^{k+1}-3}}}\right)$ and $O(n)$ respectively. In addition, we propose an efficient $k$ -claw search algorithm, which can output a $k$ -claw with $O(n)$ qubits. Given $2^{s}$ quantum processors, we can construct our quantum $k$ -collision and $k$ -claw parallel algorithm with the time of $\widetilde {O}\left({2^{\frac {(2^{k}-2)n-(2^{k+1}-2^{k-1}-3)s}{2^{k+1}-3}}}\right)$ , while the classical memory and quantum memory complexities are $\widetilde {O}\left({2^{\frac {(2^{k-1}-1)n+s\cdot 2^{k-2}}{2^{k+1}-3}}}\right)$ and $O(n)$ , respectively.

Vehicle automation and connectivity enable the cooperative platooning control of connected and autonomous vehicles (CAVs), which can enhance traffic safety and alleviate traffic oscillations. However, CAVs and human-driven vehicles (HDVs) will coexist on roads prior to the pure CAV environment, creating a mixed-flow traffic environment. Mixed-flow traffic introduces challenges for CAV operations in terms of lane-change maneuvers of HDVs in adjacent lanes, which can generate oscillations, jeopardizing the performance of platooning control. Hence, there is a need to explore the interactions between the CAV and the HDV in the lane-change process, and analyze how CAVs can proactively respond to HDV lane change to dampen the generated disturbances. This study proposes a deep reinforcement learning-based proactive longitudinal control strategy for the CAV to assist the HDV lane change, and minimize the adverse impact on the smooth operation of the mixed platoon. Results from numerical experiments illustrate the effectiveness of the proposed control strategy. Further, the generalizability of the proposed control strategy for different HDV driver types is demonstrated.

Controllable regulation of stem cell differentiation is a critical concern in stem cell-based regenerative medicine. In particular, there are still great challenges in controlling the directional differentiation of neural stem cells (NSCs) into neurons. Herein, we developed a novel linear-branched poly(

Axonal transport plays a significant role in the establishment of neuronal polarity, axon growth, and synapse formation during neuronal development. The axon of a naturally growing neuron is a highly complex and multifurcated structure with a large number of bends and branches. Nowadays, the study of dynamic axonal transport in morphologically complex neurons is greatly limited by the technological barrier. Here, a sparse gene transfection strategy was developed to locate fluorescent mCherry in the lysosome of primary neurons, thus enabling us to track the lysosome-based axonal transport with a single-particle resolution. Thereby, several axonal transport models were observed, including forward or backward transport model, stop-and-go model, repeated back-and-forth transport model, and cross-branch transport model. Then, the accurate single-particle velocity quantification by TrackMate revealed a highly heterogeneous and discontinuous transportation process of lysosome-based axonal transport in freely orientated axons. And, multiple physical factors, such as the axonal structure and the size of particles, were disclosed to affect the velocity of particle transporting in freely orientated axons. The combined single-particle fluorescence tracking and TrackMate assay can be served as a facile tool for evaluating axonal transport in neuronal development and axonal transport-related diseases.

The R&D platform is an important part of the scientific and technological innovation system, and the construction of the evaluation index of the research and development platform plays a vital role in improving the scientific research level of the platform and promoting the transformation of research and development results. Based on the research of various evaluation indicators of domestic and foreign laboratories (centers), innovation platforms and other R&D platforms, this paper uses the literature content analysis method of qualitative research as the research method to sort out the evaluation and evaluation indicators of various R&D platforms, hoping to be R&D platform management provides practical reference.

Traffic flow effects of cooperative adaptive cruise control (CACC) have not been fully understood, though such understanding is essential for the forthcoming research and applications concerning connected and automated vehicles as well as the implication for future traffic management and control. This paper aims to explore the impacts of CACC on traffic flow efficiency based on in-depth microscopic simulation studies using an enhanced version of AIMSUN. First, the Gipps car-following and lane-changing models used by default in AIMSUN were replaced or enhanced with more advanced car-following and lane-changing models to improve the capability of the simulation system in realistically reproducing capacity drop phenomena and capturing traffic merging processes. Second, a simulation platform was established using the enhanced AIMSUN with respect to a 10-km Dutch freeway stretch that includes multiple bottlenecks involving recurrent congestion. Third, we explored on this simulation platform the impacts of CACC on traffic flow mixed with manually driven vehicles and CACC equipped vehicles, in consideration of a variety of CACC market penetration rates. The study results suggest that the CACC impacts are quite positive.

Controllable regulation of stem cell differentiation is a critical concern in stem cell-based regenerative medicine. In particular, there are still great challenges in controlling the directional differentiation of neural stem cells (NSCs) into neurons. Herein, we developed a novel linear-branched poly(β-amino esters) (S4-TMPTA-BDA-DT, STBD) through a two-step reaction. The synthesized linear-branched polymers possess multiple positively charged amine terminus and degradable intermolecular ester bonds, thus endowing them with excellent properties such as high gene load, efficient gene delivery, and effective gene release and transcription in cells. In the mCherry transfection test, a high transfection efficiency of approximately 70% was achieved in primary NSCs after a single transfection. Moreover, STBD also showed high biocompatibility to NSCs without disturbing their viability and neural differentiation. With the high gene delivery property, STBD is capable of delivering siRNA (shSOX9) expression plasmid into NSCs to significantly interfere with the expression of SOX9, thus enhancing the neuronal differentiation and maturation of NSCs. The STBD/DNA nano-polyplex represents a powerful non-viral approach of gene delivery for manipulating the differentiation of stem cells, showing broad application prospects in NSC-based regenerative therapy for treating neurodegenerative diseases.

Light‐based technique, including optical imaging and photoregulation, has become one of the most important tools for both fundamental research and clinical practice, such as cell signal sensing, cancer diagnosis, tissue engineering, drug delivery, visual regulation, neuromodulation, and disease treatment. In particular, low energy near‐infrared (NIR, 700–1700 nm) light possesses lower phototoxicity and higher tissue penetration depth in living systems as compared with ultraviolet/visible light, making it a promising tool for in vivo applications. Currently, the NIR light‐based imaging and photoregulation strategies have offered a possibility to real‐time sense and/or modulate specific cellular events in deep tissues with subcellular accuracy. Herein, the recent progress with respect to NIR light for monitoring and modulating the spatiotemporal dynamics of cell functions in living systems are summarized. In particular, the applications of NIR light‐based techniques in cancer theranostics, regenerative medicine, and neuroscience research are systematically introduced and discussed. In addition, the challenges and prospects for NIR light‐based cell sensing and regulating techniques are comprehensively discussed., NIR light‐based technique, including optical imaging and photoreglation, has become one of the most important tools for both fundamental research and clinical practice. Herein, the recent progress of NIR light‐based cell function sensing and modulation in cancer theranostics, regenerative medicine, and neuroscience research is summarized.

The neural membrane potential of nerve cells is the basis of neural activity production, which controls advanced brain activities such as memory, emotion, and learning. In the past decades, optical voltage indicator has emerged as a promising tool to decode neural activities with high-fidelity and excellent spatiotemporal resolution. In particular, the hybrid optical probes can combine the advantageous photophysical properties of different components such as voltage-sensitive molecules, highly fluorescent fluorophores, membrane-targeting tags and optogenetic materials, thus showing numerous advantages in improving the photoluminescence intensity, voltage sensitivity, photostability and cell specificity of probes. In this review, we first highlight the current state-of-the-art hybrid probes that designed by using fluorescent proteins, organic dyes and fluorescent nanoprobes as the fluorophores, respectively. Then, the design strategies, voltage-sensing mechanisms and the in vitro and in vivo neural activity imaging applications of the hybrid probes are summarized. Finally, based on the current achievements of voltage imaging studies, we present the challenges and prospects for design and application of hybrid optical probes in the future. This article is protected by copyright. All rights reserved.

TiB2-SiC-Si ceramic composites were fabricated based on molten silicon infiltration method. The influence of particle size distribution of TiB2 on the microstructure and mechanical properties of TiB2-SiC-Si ceramic composites was studied by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electron universal testing machines, etc. The results showed that the composite consisted of TiB2, SiC and Si phases. The microstructure analysis showed that: the content of residual Si could be controlled less than 16 vol.% in the composite by particle size distribution. When the particle size distribution of TiB2 was 42:32:26, the TiB2-SiC-Si composite showed the optimum properties. The open porosity, volume density, Vickers-hardness, flexural strength and fracture toughness were 0.51%, 3.63 g/cm3, 17 GPa, 275 MPa and 5.7 MPa·m1/2, respectively.

Connectivity is a fundamental requirement for Vehicular Ad hoc NETworks (VANETs) to secure reliable information dissemination. Connectivity is not guaranteed in the case of traffic sparsity and low market penetration of networked vehicles. Therefore, it is essential to examine the connectivity condition before deploying VANETs. The probabilistic distribution of inter-vehicle spacing plays a crucial role in the study of connectivity. It is quite often in previous studies to assume a priori distribution. This paper has studied this issue analytically and proved a general result as follows: Poisson vehicle flow of volume λ enters a road stretch over the period [0, ∞), with the speed of each vehicle sampled from a common distribution of PDF f v (v), then in the steady state the number of vehicles within any road section [x 1 , x 2 ] at any time instant t > 0 is Poisson distributed with the parameter λ(x 2 − x 1 ) ∫∞ 0 1/v f v (v) dv. This theoretical result is also confirmed with our simulation studies.