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In this article, an anti-jamming high-temperature sensor up to 1000 °C based on optical fiber in-line Mach–Zehnder interferometer (MZI) structure fabricated by cutting and splicing single-mode fiber (SMF), multimode fiber (MMF), and suspended core fiber (SCF) consisting of pure silica material to a sandwich-like compact structure under optimized discharge parameters is proposed. The MMFs function as a light coupler and the silica core modes and the air cladding modes are excited to interference. A temperature response of 45.75 pm/°C is achieved, due to the significant thermo-optic coefficient exhibited by these two modes, while maintaining a high linearity of 0.99867. In addition, an investigation reveals a maximum temperature fluctuation of 2.56 °C at 1000 °C and a maximum hysteresis error within 0.225 nm. Furthermore, the proposed structure demonstrates exceptional resistance to interference from bending, strain, fluctuations in external refractive index (RI), and vibration. This proposed sensor showcases outstanding anti-jamming capabilities, along with high repeatability and stability, positioning it as an excellent alternative for measuring high temperatures in harsh environments.

Channel spatial characterization for tunnel entrance scenarios is an essential issue to ensure the sustained and stable mobile broadband communications of railway communication system. In this letter, a geometry-based channel model for multiple-input multiple-output channels in tunnel entrance scenarios is proposed. The closed-form expressions of channel spatial correlation and capacity are derived. The impacts of different scenarios and transceiver element spacings on channel spatial characteristics are thoroughly analyzed. Moreover, the measurement results are utilized to validate the proposed model and numerical results.

This article presents a novel composite vector bending sensing system capable of switching freely between wavelength and intensity modulation. The fundamental sensing unit of the system depends on an offset rotation twisted Mach–Zehnder interferometer (TW-MZI) with unique refractive index (RI) distribution characteristics proven through experiments. The sensing unit delivers remarkable performance in intensity modulation, reaching a maximum of 18.74 ± 0.01 dB/ $\text{m}^{-1}$ . The sensing unit features a nonuniform geometric distribution and utilizes polarization-maintaining optical fibers as its structural material, enabling it to detect the correlation of polarized light and recognize the bending direction. With these advantages, a quasi-parallel distributed curvature sensing system is constructed, integrating a Sagnac interferometer (SI) as the sensing reference arm combined with the TW-MZI sensing unit. Adjusting the interference length and optical power can obtain a first-order harmonic vernier spectrum. Additionally, the envelope differencing technique enhances the interference fringe contrast, reducing the reliance on the monitoring wavelength domain. This combination highlights the composite system’s wavelength modulation-based vector curvature sensing capability, achieving a maximum value of 15.59 ± 0.01 nm/ $\text{m}^{-1}$ . Moreover, this system exhibits characteristics such as low-temperature crosstalk, high stability, and rapid responsiveness, making it well suited for applications in medical device diagnostics, oil and gas pipeline inspection, and structural safety monitoring within the construction industry.

Railway communications are required to have the ability of constant connection to ensure railway operation efficiency and safety. However, most travelers have encountered instances of Internet disconnection or call dropping when the train enters and exits tunnels, significantly impacting the quality of train-ground communication. To achieve constant connection capability, it is crucial to characterize the channels in tunnel entrance scenarios for railway communication systems. This article provides a 3-D geometry-based stochastic model (GBSM) for tunnel entrance scenarios, which considers both the leaky coaxial cable (LCX) signals in tunnels and antenna signals out of tunnels. The channel statistical characteristics are derived based on the presented model, including time-frequency correlation function and delay power spectrum density. The validation using actual measurement data demonstrates that the proposed model may achieve an acceptable degree of accuracy. The boundary of the tunnel entrance scenarios is analyzed based on the numerical results. Furthermore, numerical results have shown that nonisotropic scattering degree and antenna position have substantial effects on channel correlation. These can be applied for forthcoming antenna deployment, network design, and performance evaluations of railway communications.

Objective: We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect. Methods: We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation. Results and Conclusion: The calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics.

A high-temperature measurement fiber sensor based on the Vernier effect is proposed and demonstrated. The sensor comprises two parallel Fabry–Perot interferometers (FPIs) constructed by the splicing of the single-mode fiber (SMF) and a micrometer-scale dimensions suspended-core fiber (SCF). These two parallel interferometers possess a high degree of symmetry and both packaged with a hollow core fiber (HCF) to provide resistance against external pollution. The HCF is charged to collapse on the other side, but the length of SCF differs between them. High-temperature tests were conducted on both a single sensing FPI and parallel structures. The impact of the reference units with different free spectrum ranges (FSRs) on the sensitivity of parallel structures was investigated through simulation and experimentation. Leveraging on the Vernier effect and the parallel structures, the sensor exhibited highest temperature sensitivities of −86.11, −99.01, and −112.66 pm/°C across a temperature range from 25 °C to 1000 °C. Furthermore, the parallel structures were subjected to three rounds of heating with a 24-h interval to verify their repeatability and stability. Additionally, a high-temperature stability error test was conducted on these tip-packaged parallel sensors, which exhibit simple fabrication, excellent repeatability, and stability across a wide temperature range. As such, they are expected to be highly practical for use in harsh environments and mass production.

ABSTRACTThis paper establishes a rolling shared parking allocation model to optimize the matching of supply and demand in parking-dense districts by maximizing platform revenue and minimizing parking users’ travel costs. An adjustment mechanism that dynamically adjusts the allocated parking slots is developed to be embedded in the model. Considering multi-candidate adjacent parking lots, combined sharing and individual sharing patterns are compared to verify the benefits of resource combination. Numerical experiments indicate that the proposed model works well for changing parking demands and achieves more successful matches than the first-book-first-serve model. The combination of adjacent parking resources improves the platform revenue, the parking slot utilization, and the acceptance rate of parking requests, as well as reduces the average walking distance. The direct parking revenue of the parking lot with fewer slots is remarkably increased under combined sharing. The findings provide managerial insights for local collaborative shared parking.

A string of niobium–based transition metal composite oxides (named as Nb2O5-MOx, M = Cr, V, Ti, Cu, Co, Fe, Mn and Ni, respectively) were synthesized, and their catalytic performances for the elimination of monochlorobenzene/toluene as typical VOCs were studied. Research result of structure–property relationship showed that nanocrystalline/amorphous state and mesoporous structure were formed, and transition metal elements were highly dispersed into Nb2O5, which were conducive to adjusting the physico-chemical properties of Nb2O5-MOxand enhancing the synergistic catalysis effect. The mesoporous and surface acidity of material promoted the adsorption, sensitization and breakage of chemical bonds in the organic reactants, and then reaction intermediates were oxidized and transformed into CO2and H2O by the redox sites of material. Oxidation properties and electron density of catalysts were the most important factors affecting the catalytic combustion reaction. The order of apparent catalytic activity for monochlorobenzene elimination was: Nb2O5–Cr2O3 > Nb2O5–CuO > Nb2O5–Co3O4 > Nb2O5–Fe2O3 > Nb2O5–V2O5 > Nb2O5–Mn3O4 > Nb2O5 > Nb2O5–NiO, and the order for toluene degradation was: Nb2O5–CuO > Nb2O5–Mn3O4 > Nb2O5–V2O5 > Nb2O5–Fe2O3 > Nb2O5–Cr2O3 > Nb2O5–Co3O4 > Nb2O5 > Nb2O5–NiO. Considering the toxicity of Cr and V, the by-products produced by Cu and the high price of Co, Nb2O5–Fe2O3was selected as the most suitable catalyst. Its catalytic activity could reach 69% conversion for monochlorobenzene (320 °C), 80% for toluene (320 °C) and 81% for 1,2-dichloroethane elimination (270 °C), and also maintain 120 h without significant deactivation, indicating that the applicability of Nb2O5–Fe2O3was worthy of more attention and further study.

Emerging intelligent transportation services are latency-sensitive with heavy demand for computing resources, which can be supported by a multi-tier computing system composed of vehicular edge computing (VEC) servers along the roads and micro servers on vehicles. In this work, we investigate the dual Uu/PC5 interface offloading and resource allocation strategy in Cellular Vehicle-to-Everything (C-V2X) enabled multi-tier VEC system. The successful transmission probability is characterized to obtain the normalized transmission rate of PC5 interface. We aim to minimize the system latency of task processing while satisfying the resource requirements of Uu and PC5 interfaces. Due to the non-convex and variables coupling, we decompose the original problem into two subproblems, i.e., resource allocation and offloading strategy subproblems. Specifically, we derive the closed-form expressions of packet transmit frequency of PC5 interface, transmission power of Uu interface, and CPU computation frequency in the resource allocation subproblem. Moreover, for the offloading strategy subproblem, the offloading ratio matrix is obtained by proposing the PC5 interface based greedy offloading (PC5-GO) algorithm, which concludes offloading decision and ratio. Simulation results are provided that the proposed PC5-GO algorithm can significantly improve the system performance compared with other baseline schemes by 13.7% at least.

A novel scheme for improving the resolution of temperature sensor using fast and slow light in a fiber resonator is proposed and demonstrated experimentally. In the measurement system, the shift of resonance wavelength produced by the temperature change can be converted into strong variations of delay time. By measuring the delay time, this sensor we proposed has high-temperature sensitivity. Different from the traditional method of tracing spectrum, the temperature detection is carried out using an oscilloscope, which results in the sensor with fast response and high resolution. Moreover, the sensitivity, resolution, and measurement range of the sensor can be easily tuned by changing the ${Q}$ -factor of the resonator. Using this approach, we demonstrate temperature measurements at fiber resonators with low- ${Q}$ and high- ${Q}$ , respectively, as well as a $3.76\times 10^{-{4}}\,\,^{\circ }\text{C}$ resolution and a 2706 ns/°C sensitivity of temperature sensing are obtained. The scheme is simple in structure and easy to implement, which is particularly suitable for detecting very small temperature changes.

Road accidents can be effectively reduced by broadcasting basic safety messages (BSMs) of vehicles in Cellular V2X (C-V2X). However, with the increase of the number of C-V2X devices, the collision probability of BSMs at a fixed transmission frequency increases due to limited spectrum resources. In this letter, the transmission frequency adjustment mechanism (TFAM) based on channel busy ratio (CBR) is proposed to maintain the timeliness of BSMs. First, the CBR is estimated based on BSM transmission frequency and sensing occupancy probability considering channel fading. To quantify the performance of C-V2X communication, the performance metric freshness of information (FOI) is defined, which comprehensively trades off the reliability and latency of BSMs. Furthermore, an optimization problem is formulated to minimize FOI. We solve the optimization problem to derive the optimal transmission frequency. Simulation results show that the proposed TFAM enables vehicles to exchange BSMs with minimum FOI.

The automotive industry is increasingly deploying software solutions to provide value-added features for vehicles, especially in the era of vehicle electrification and automation. However, the ever-increasing cyber components of vehicles (i.e., computation, communication, and control) incur new risks of anomalies, as evident by the millions of vehicle recalls by different automakers. To mitigate these risks, we design the B-Diag, a battery-based diagnostic system detects engine anomalies with a cyber-physical approach. The core idea of B-Diag is to diagnose engines using the physically-induced correlations between battery voltage and engine variables, which is captured as a customized 3-layer correlation graph and a set of data-driven norm models describing the edges thereof. The design of B-Diag is steered by a dataset collected with a prototype system when driving a 2018 Subaru Crosstrek in real-life for over three months. Our evaluation shows B-Diag to detect anomalies of 17 engine variables with a $>$>$86\%$86% (up to $100\%$100%) accuracy.

COVID-19 casualties vary among different ancestral groups due to a variety of factors. Here, we present a protocol for analyzing publicly available genome-wide association studies (GWASs) to search for ancestry-specific genetic factors related to severe COVID-19. We describe steps for downloading and comparing two COVID-19 GWASs, calculating expression quantitative trait loci, and single-cell gene expression analysis. We demonstrate this approach using GWASs from Host Genetics Initiative; however, it is applicable to other databases such as the UK Biobank.

Designing an accurate vehicular channel simulator which generates samples at the high speed is a key issue to the vehicular communications transmission scheme and protocol design. Although the finite-state Markov channel (FSMC) models have been extensively investigated to describe fading channels, FSMC models cannot show the combined effect of shadowing and small-scale fading on the temporal statistical characteristic of the vehicular channel. In this letter, a vehicular channel simulator based on the FSMC is designed, which incorporates the impacts of shadowing with small-scale fading and movement speed on the temporal statistical characteristic. The steady-state probabilities and the closed-form expressions of state transition probabilities between channel states are derived based on the approximation of Lognormal-Nakagami distribution. To validate the accuracy of the proposed FSMC channel simulator, the derived model parameters and second-order statistical parameters of the simulated channel are compared with the real field measurements of high-speed vehicular channels.

Pd/Ce0.67Zr0.33O2catalyst was pretreated in different atmosphere respectively, and characterized by CO chemical adsorption, XPS, HR-TEM, H2-TPR, Raman, OSC and in situDRIFTs to investigate the effect of the structure properties of PdOxspecies on the catalytic performance for CO, HC and NOxelimination. The results show that Pd/CZ catalyst pretreated in air atmosphere has higher oxidation activity of HC due to having high Pd dispersion and strong interaction between PdOxand CZ support. Pd/CZ-H catalyst pretreated in reducing atmosphere exhibits better catalytic performance of NOxelimination because of having relatively big Pd particle size, more Pd species in metallic state and higher concentration of oxygen vacancies. While for the Pd/CZ-RG catalyst pretreated in reactant atmosphere, strong adsorption of HC species on the surface of catalysts would lead to a part of active sites being covered, which inhibits HC and NO conversions.

A novel hydrogel (HA-az-F127 hydrogel) formed by reacting hydrazide modified hyaluronic acid (HAAD) and benzaldehyde terminated F127 triblock copolymers (BAF127) was developed in this work. The hydrogel with dynamic covalent chemically and micellar physically double-cross-linked networks exhibited rapid gelation and shear thinning properties. Besides, the hydrogel possessed functions, such as adaptable mechanical strength, self-healability, liquid-absorption, or drainage and tissue adhesion, which are important for wound treatment. Studies on cytocompatibility and histopathology by 3-(4,5-dimethyl-thiazol-2-yl)-2,5-diphenyl tetrazolium bromide tests, live/death staining, and cell counting kit 8 assay demonstrated excellent biocompatibility of the hydrogels. After it was applied in the deep partial-thickness burn model, the hydrogel contributed effectively in promoting burn wound repair. Therefore, the HA-az-F127 hydrogel combined multiple functions in one system, demonstrating potential application in promoting burn wound healing.

Full-duplex wireless communication becomes a promising technique for doubling the system spectral efficiency (SE). In this letter, we propose a variable-rate variable-power (VRVP) modulation scheme for the first time to increase the average system SE. The average SE maximization problem is formulated subject to average power and bit error rate constraints. Due to the unknown self-interference of the other side receiver, this problem is difficult to solve directly. Then, we study the problem for maximizing the lower bound of the average SE, which can be solved in a feasible way. Next, the analytical solutions of power and rate adaptation are obtained. Finally, numerical results show that, compared with the variable-rate constant-power ${M}$ -ary quadrature amplitude modulation, the proposed VRVP scheme increases the SE by 25% in the low average signal noise ratio region.

Conventional approaches for screening anticancer drugs rely on chemical reactions, which are time consuming, labor intensive, and costly. Here, we present a protocol for label-free and high-throughput assessment of drug efficacy using a vision transformer and a Conv2D. We describe the steps for cell culture, drug treatment, data collection, and preprocessing. We then detail the building of deep learning models and their use to predict drug potency. This protocol can be adapted for screening chemicals that affect the density or morphological features of cells.

5G wireless communications aim at providing higher data rates, spectral efficiency, and energy efficiency than 4G. To achieve this target, the spectrum resource with low utilization is emptied out for 5G refarming. The refarmed spectrum is of effective propagation nature; however, it leads to extensive competition between PTOs and DTOs. To mitigate such competition, dynamic spectrum sharing should be realized. For this purpose, a spectrum sharing framework of a 5G system is designed in this article, in which the public users and dedicated users can access the sharing spectrum dynamically. In the framework, to ensure the QoE of the secondary users in a spectrum sharing system, the DTO in this case, an advanced dynamic channel access strategy is proposed. The spectrum sharing system states are modeled as a finite state Markov chain, and are used to analyze the system state transition model. Based on the analysis results, the optimal dynamic channel access strategy with minimum queuing time for DTO is derived by a Markov decision process. Extensive simulations show that the proposed dynamic channel access strategy can achieve the optimal queuing time.

A Pd/CZ(NO) catalyst prepared with Pd(NO3)2as the metal precursor exhibited the best catalytic performance for HC and CO elimination because of a higher oxygen storage capacity, abundant small Pdnclusters and a strong Pd-support interaction that facilitated electron transfer from PdOxparticles to the CZ support. A Pd/CZ(NH) catalyst prepared with Pd(NH3)4(NO3)2as the metal precursor exhibited good performance for NO and NO2elimination due to a higher Pd dispersion, abundant bigger Pdnclusters and oxidized/metallic Pd coexistence. A Pd/CZ(Cl) catalyst prepared with H2PdCl4as the metal precursor exhibited low catalytic activity due to a low Pd dispersion, weak Pd-support interaction, and the trace amount of CeOCl which inhibited oxygen vacancy creation. However, it showed good thermal stability, and benefited when an aging treatment removed the residual chlorine species and also promoted the interaction between PdOxand the support.

To reveal the role of alkaline earths modification in promoting the catalytic activity of HC and NOxconversion, catalytic activity tests and DRIFT experiments under different reaction conditions were performed. The introduction of alkaline earths promotes the catalytic activities of both HC and NOxelimination under stoichiometric NOx–CO–HC–O2conditions, especially for Pd/CZBa, whereas it inhibits CO oxidation. In addition, the operation window of NOxconversion is also obviously widened as a result of enhanced NOxstorage ability. DRIFTS results demonstrate that modification with alkaline earths improves the formation rate of nitrites and nitrates due to enhanced electron transfer and oxygen mobility, as well as the dissociation of NO species on the active metal, which increases the storage ability and reduction performance of NOx. On the other hand, the doping of alkaline earths could weaken the inhibiting effect arising from strongly bonded HC species on NO adsorption and dissociation due to the promoted catalytic activity of HC deep oxidation, which promotes the reaction of CO and NOxat low temperature.

A series of La-Al2O3supported Pd-Ce close-coupled catalysts were synthesized by a co-adsorption impregnation method and subsequently investigated. In the case of fresh catalysts, the presence of an optimal concentration of ceria obviously promoted the catalytic activity during HC and NOxeliminations, owing to the interaction between the palladium oxide species (PdOx) and CeO2that improves the oxidation of Pd0to PdO and enhances the adsorption of nitrite/nitrates and isocyanate intermediate species on the support under reaction conditions. Pd-Ce(2.0)/La-Al2O3catalyst (where 2.0 is the wt% of CeO2) exhibited the highest catalytic activity for HC and NO eliminations. Following aging at 1100 °C, the operational window for HC and NOxconversions was broadened and the thermal stability of the catalysts was also improved as a result of the presence of an appropriate quantity of ceria (2.0–4.0 wt%). The enhanced interactions between PdOxand CeO2evidently led to the formation of a Pd-O-Ce system, stabilizing PdOxspecies with smaller particle sizes at high temperatures. This result is significant since it suggests a means of improving the catalytic performance of Pd-only close-coupled catalysts during automobile exhaust elimination.

In this paper, we investigate the asymptotic behavior of solutions of the three‐dimensional Brinkman–Forchheimer equation. We first prove the existence and uniqueness of solutions of the equation in L2, and then show that the equation has a global attractor in H2when the external forcing term belongs to L2. Copyright © 2008 John Wiley & Sons, Ltd.