Street Smart in 5G : Vehicular Applications, Communication, and Computing

Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Specifically, vehicles, roadside units, and other road users can collaborate to deliver novel services and applications that leverage, for example, big vehicular data and machine learning. Relatedly, fifth-generation cellular networks (5G) are being developed and deployed for low-latency, high-reliability, and high bandwidth communications. While 5G adjacent technologies such as edge computing allow for data offloading and computation at the edge of the network thus ensuring even lower latency and context-awareness. Overall, these developments provide a rich ecosystem for the evolution of vehicular applications, communications, and computing. Therefore in this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data. In particular, this paper highlights several vehicular applications, investigates their requirements, details the enabling communication technologies and computing paradigms, and studies data analytics pipelines and the integration of these enabling technologies in response to application requirements.Peer reviewe

Application mapping on multiprocessor hardware platforms using genetic algorithms

Synchronous Dataflow (SDF) is a widely-used model-of-computation for signal processing and multimedia applications. As Moore’s law comes to an end, multiprocessor systems are becoming ubiquitous in today’s embedded systems design. In this thesis, I address the problem of mapping a Homogeneous Synchronous Dataflow (HSDF) graph onto a multiprocessor platform with the objective of maximizing system throughput. The hardware platform consists of multiple processors connected with a communication substrate with guaranteed inter-processor communication latency, e.g. a hard real-time Network-on-Chip. Since the problem is a NP-hard combinatorial optimization problem, it is generally infeasible to use exhaustive search to obtain optimal solutions for realistic-sized applications. In this thesis, I adopt Genetic Algorithms, to search the design space of all possible actor-to-processor mappings and actor orderings on each processor to find the optimal solution, and compare the performance and scalability of GA with the exact solution technique based on SAT solving

Highly Proliferative Immortalized Human Dental Pulp Cells Retain the Odontogenic Phenotype when Combined with a Beta-Tricalcium Phosphate Scaffold and BMP2

Human dental pulp cells (HDPCs) play a vital role in dentin formation and reparative dentinogenesis, which indicated their potential application in regenerative medicine. However, HDPCs, which can only be obtained from scarce human pulp tissues, also have a limited lifespan in vitro, and stem cells usually lose their original characteristics over a large number of passages. To overcome these challenges, we successfully immortalized human dental pulp cells using the piggyBac system which was employed to efficiently overexpress the SV40 T-Ag, and we then comprehensively described the cell biological behavior. The immortalized human dental pulp cells (iHDPCs) acquired long-term proliferative activity and expressed most HDPC markers. The iHDPCs maintained multiple differentiation potential and could be induced to differentiate into chondrogenic, osteogenic, and adipogenic cells in vitro. We also proved that the iHDPCs gained a stronger ability to migrate than the primary cells, while apoptosis was inhibited. Furthermore, highly proliferative iHDPCs displayed no oncogenicity when subcutaneously implanted into athymic nude mice. Finally, iHDPCs exhibited odontogenic differentiation ability and secreted dentin sialophosphoprotein (DSPP) when combined with a beta-tricalcium phosphate scaffold and bone morphogenetic protein-2 (BMP2) in vivo. Conclusively, the established iHDPCs are a valuable resource for mechanistic study of dental pulp cell differentiation and dental pulp injury repair, as well as for applications in tooth regeneration

Primary Cilia as a Biomarker in Mesenchymal Stem Cells Senescence: Influencing Osteoblastic Differentiation Potency Associated with Hedgehog Signaling Regulation

Bone tissue engineering-based therapy for bone lesions requires the expansion of seeding cells, such as autologous mesenchymal stem cells (MSCs). A major obstacle to this process is the loss of the phenotype and differentiation capacity of MSCs subjected to passage. Recent studies have suggested that primary cilia, primordial organelles that transduce multiple signals, particularly hedgehog signals, play a role in senescence. Therefore, we explored the relationships among senescence, primary cilia, and hedgehog signaling in MSCs. Ageing of MSCs by expansion in vitro was accompanied by increased cell doubling time. The osteogenic capacity of aged MSCs at passage 4 was compromised compared to that of primary cells. P4 MSCs exhibited reductions in the frequency and length of primary cilia associated with decreased intensity of Arl13b staining on cilia. Senescence also resulted in downregulation of the expression of hedgehog components and CDKN2A. Suppression of ciliogenesis reduced the gene expression of both Gli1, a key molecule in the hedgehog signaling pathway and ALP, a marker of osteoblastic differentiation. This study demonstrated that the senescence of MSCs induced the loss of osteoblastic differentiation potency and inactivated hedgehog signaling associated with attenuated ciliogenesis, indicating that primary cilia play a mediating role in and are biomarkers of MSC senescence; thus, future antisenescence strategies involving manipulation of primary cilia could be developed

An experimental study on the CO2/sand dry-frac process

The CO2/sand dry-frac process is a waterless fracturing technology in which CO2 instead of water is used as fracturing fluid. The application of the technology abroad (in the USA and Canada) shows that it works well in stimulating low-pressure, low-permeability, strong water-locking/water sensitive reservoirs. Thus, a series of experimental studies were carried out on its production increase mechanism, fracturing fluid system, pressurized air-tight sand blender, and fracturing process. Some conclusions were made. First, the CO2 viscosity enhancement technology can raise the critical CO2 viscosity by 240–490 times, significantly improving the sand-carrying and fracture-making capacities of CO2 fracturing fluid, so it is a key technique in CO2/sand dry-frac process. Second, with the development of CO2 pressurized air-tight sand blender, a complete set of key devices for the CO2/sand dry-frac process can be made in China, meeting the requirements of the fracturing operation. Third, fully automatic flowback is also realized. Fourth, CO2 instead of water is used in this fracturing operation, saving a large amount of water consumed in fracturing, and lowering cost. Fifth, the CO2/sand dry-frac process is feasible and suitable for the stimulation of low-pressure, low-permeability and strong water-locking reservoirs, with substantial production increase

Pressure-induced superconductivity and topological phase transitions in the topological nodal-line semimetal SrAs3

Topological nodal-line semimetals (TNLSMs) are materials whose conduction and valence bands cross each other, meeting a topologically protected closed loop rather than discrete points in the Brillouin zone (BZ). The anticipated properties for TNLSMs, include drumhead-like nearly flat surface states, unique Landau energy levels, special collective modes, long-range Coulomb interactions, or the possibility of realizing high-temperature superconductivity. Recently, SrAs(3)has been theoretically proposed and then experimentally confirmed to be a TNLSM. Here, we report high-pressure experiments on SrAs3, identifying a Lifshitz transition below 1 GPa and a superconducting transition accompanied by a structural phase transition above 20 GPa. A topological crystalline insulator (TCI) state is revealed by means of density functional theory (DFT) calculations on the emergent high-pressure phase. As the counterpart of topological insulators, TCIs possess metallic boundary states protected by crystal symmetry, rather than time reversal. In consideration of topological surface states (TSSs) and helical spin texture observed in the high-pressure state of SrAs3, the superconducting state may be induced in the surface states, and is most likely topologically nontrivial, making pressurized SrAs(3)a strong candidate for topological superconductor