A Macro-Micro Approach to Reconstructing Vehicle Trajectories on Multi-Lane Freeways with Lane Changing

Vehicle trajectories can offer the most precise and detailed depiction of traffic flow and serve as a critical component in traffic management and control applications. Various technologies have been applied to reconstruct vehicle trajectories from sparse fixed and mobile detection data. However, existing methods predominantly concentrate on single-lane scenarios and neglect lane-changing (LC) behaviors that occur across multiple lanes, which limit their applicability in practical traffic systems. To address this research gap, we propose a macro-micro approach for reconstructing complete vehicle trajectories on multi-lane freeways, wherein the macro traffic state information and micro driving models are integrated to overcome the restrictions imposed by lane boundary. Particularly, the macroscopic velocity contour maps are established for each lane to regulate the movement of vehicle platoons, meanwhile the velocity difference between adjacent lanes provide valuable criteria for guiding LC behaviors. Simultaneously, the car-following models are extended from micro perspective to supply lane-based candidate trajectories and define the plausible range for LC positions. Later, a two-stage trajectory fusion algorithm is proposed to jointly infer both the car-following and LC behaviors, in which the optimal LC positions is identified and candidate trajectories are adjusted according to their weights. The proposed framework was evaluated using NGSIM dataset, and the results indicated a remarkable enhancement in both the accuracy and smoothness of reconstructed trajectories, with performance indicators reduced by over 30% compared to two representative reconstruction methods. Furthermore, the reconstruction process effectively reproduced LC behaviors across contiguous lanes, adding to the framework's comprehensiveness and realism

Seen and unseen: bursty star formation and its implications for observations of high-redshift galaxies with JWST

Both observations and simulations have shown strong evidence for highly time-variable star formation in low-mass and/or high-redshift galaxies, which has important observational implications because high-redshift galaxy samples are rest-UV selected and therefore particularly sensitive to the recent star formation. Using a suite of cosmological "zoom-in" simulations at $z>5$ from the Feedback in Realistic Environments (FIRE) project, we examine the implications of bursty star formation histories for observations of high-redshift galaxies with JWST. We characterize how the galaxy observability depends on the star formation history. We also investigate selection effects due to bursty star formation on the physical properties measured, such as the gas fraction, specific star formation rate, and metallicity. We find the observability to be highly time-dependent for galaxies near the survey's limiting flux due to the SFR variability: as the star formation rate fluctuates, the same galaxy oscillates in and out of the observable sample. The observable fraction $f_\mathrm{obs} = 50\%$ at $z \sim 7$ and $M_{\star} \sim 10^{8.5}$ to $10^{9}\,M_{\odot}$ for a JWST/NIRCam survey reaching a limiting magnitude of $m^\mathrm{lim}_\mathrm{AB} \sim 29$-$30$, representative of surveys such as JADES and CEERS. JWST-detectable galaxies near the survey limit tend to have properties characteristic of galaxies in the bursty phase: on average, they show approximately 2.5 times higher cold, dense gas fractions and 20 times higher specific star formation rates at a given stellar mass than galaxies below the rest-UV detection threshold. Our study represents a first step in quantifying selection effects and the associated biases due to bursty star formation in studying high-redshift galaxy properties.Comment: 8 pages, 4 figures, resubmitted after incorporating referee's comments; analysis expanded to include more galaxies and some quantitative results correcte

Experimental demonstration of an integrated on-chip p-bit core utilizing stochastic Magnetic Tunnel Junctions and 2D-MoS2_{2} FETs

Probabilistic computing is a novel computing scheme that offers a more efficient approach than conventional CMOS-based logic in a variety of applications ranging from optimization to Bayesian inference, and invertible Boolean logic. The probabilistic-bit (or p-bit, the base unit of probabilistic computing) is a naturally fluctuating entity that requires tunable stochasticity; by coupling low-barrier stochastic Magnetic Tunnel Junctions (MTJs) with a transistor circuit, a compact implementation is achieved. In this work, through integrating stochastic MTJs with 2D-MoS$_{2}$ FETs, the first on-chip realization of a key p-bit building block displaying voltage-controllable stochasticity is demonstrated. In addition, supported by circuit simulations, this work provides a careful analysis of the three transistor-one magnetic tunnel junction (3T-1MTJ) p-bit design, evaluating how the characteristics of each component influence the overall p-bit output. This understanding of the interplay between the characteristics of the transistors and the MTJ is vital for the construction of a fully functioning p-bit, making the design rules presented in this article key for future experimental implementations of scaled on-chip p-bit networks

Bursty Star Formation Naturally Explains the Abundance of Bright Galaxies at Cosmic Dawn

Recent discoveries of a significant population of bright galaxies at cosmic dawn $\left(z \gtrsim 10\right)$ have enabled critical tests of cosmological galaxy formation models. In particular, the bright end of the galaxy UV luminosity function (UVLF) appears higher than predicted by many models. Using approximately 25,000 galaxy snapshots at $8 \leq z \leq 12$ in a suite of FIRE-2 cosmological "zoom-in'' simulations from the Feedback in Realistic Environments (FIRE) project, we show that the observed abundance of UV-bright galaxies at cosmic dawn is reproduced in these simulations with a multi-channel implementation of standard stellar feedback processes, without any fine-tuning. Notably, we find no need to invoke previously suggested modifications such as a non-standard cosmology, a top-heavy stellar initial mass function, or a strongly enhanced star formation efficiency. We contrast the UVLFs predicted by bursty star formation in these original simulations to those derived from star formation histories (SFHs) smoothed over prescribed timescales (e.g., 100 Myr). The comparison demonstrates that the strongly time-variable SFHs predicted by the FIRE simulations play a key role in correctly reproducing the observed, bright-end UVLFs at cosmic dawn: the bursty SFHs induce order-or-magnitude changes in the abundance of UV-bright ($M_\mathrm{UV} \lesssim -20$) galaxies at $z \gtrsim 10$. The predicted bright-end UVLFs are consistent with both the spectroscopically confirmed population and the photometrically selected candidates. We also find good agreement between the predicted and observationally inferred integrated UV luminosity densities, which evolve more weakly with redshift in FIRE than suggested by some other models.Comment: 12 pages, 4 figures + 1 table, submitted to ApJ

Transfer-free, lithography-free and fast growth of patterned CVD graphene directly on insulators by using sacrificial metal catalyst

Chemical vapor deposited graphene suffers from two problems: transfer from metal catalysts to insulators, and photoresist induced degradation during patterning. Both result in macroscopic and microscopic damages such as holes, tears, doping, and contamination, translated into property and yield dropping. We attempt to solve the problems simultaneously. A nickel thin film is evaporated on SiO2 as a sacrificial catalyst, on which surface graphene is grown. A polymer (PMMA) support is spin-coated on the graphene. During the Ni wet etching process, the etchant can permeate the polymer, making the etching efficient. The PMMA/graphene layer is fixed on the substrate by controlling the surface morphology of Ni film during the graphene growth. After etching, the graphene naturally adheres to the insulating substrate. By using this method, transfer-free, lithography-free and fast growth of graphene realized. The whole experiment has good repeatability and controllability. Compared with graphene transfer between substrates, here, no mechanical manipulation is required, leading to minimal damage. Due to the presence of Ni, the graphene quality is intrinsically better than catalyst-free growth. The Ni thickness and growth temperature are controlled to limit the number of layers of graphene. The technology can be extended to grow other two-dimensional materials with other catalysts

Spatiotemporal dynamic of subtropical forest carbon storage and its resistance and resilience to drought in China

Subtropical forests are rich in vegetation and have high photosynthetic capacity. China is an important area for the distribution of subtropical forests, evergreen broadleaf forests (EBFs) and evergreen needleleaf forests (ENFs) are two typical vegetation types in subtropical China. Forest carbon storage is an important indicator for measuring the basic characteristics of forest ecosystems and is of great significance for maintaining the global carbon balance. Drought can affect forest activity and may even lead to forest death and the stability characteristics of different forest ecosystems varied after drought events. Therefore, this study used meteorological data to simulate the standardized precipitation evapotranspiration index (SPEI) and the Biome-BGC model to simulate two types of forest carbon storage to quantify the resistance and resilience of EBF and ENF to drought in the subtropical region of China. The results show that: 1) from 1952 to 2019, the interannual drought in subtropical China showed an increasing trend, with five extreme droughts recorded, of which 2011 was the most severe one; 2) the simulated average carbon storage of the EBF and ENF during 1985-2019 were 130.58 t·hm-2 and 78.49 t·hm-2, respectively. The regions with higher carbon storage of EBF were mainly concentrated in central and southeastern subtropics, where those of ENF mainly distributed in the western subtropic; 3) The median of resistance of EBF was three times higher than that of ENF, indicating the EBF have stronger resistance to extreme drought than ENF. Moreover, the resilience of two typical forest to 2011 extreme drought and the continuous drought events during 2009 - 2011 were similar. The results provided a scientific basis for the response of subtropical forests to drought, and indicating that improve stand quality or expand the plantation of EBF may enhance the resistance to drought in subtropical China, which provided certain reference for forest protection and management under the increasing frequency of drought events in the future

An Intrusion Detection System Based on Genetic Algorithm for Software-Defined Networks

A SDN (Software-Defined Network) separates the control layer from the data layer to realize centralized network control and improve the scalability and the programmability. SDN also faces a series of security threats. An intrusion detection system (IDS) is an effective means of protecting communication networks against traffic attacks. In this paper, a novel IDS model for SDN is proposed to collect and analyze the traffic which is generally at the control plane. Moreover, network congestion will occur when the amount of data transferred reaches the data processing capacity of the IDS. The suggested IDS model addresses this problem with a probability-based traffic sampling method in which the genetic algorithm (GA) is used to approach the sampling probability of each sampling point. According to the simulation results, the suggested IDS model based on GA is capable of enhancing the detection efficiency in SDNs

Performance of Spiral Groove Dry Gas Seal for Natural Gas Considering Viscosity-Pressure Effect of the Gas

Centrifugal compressors used for transporting natural gas are usually equipped with dry gas seals. The working medium of the seal is usually the delivered gas, that is, natural gas. In this paper, the natural gas viscosity-pressure equation is derived from the Pederson mixed gas viscosity model and Lucas viscosity-pressure model, and the real gas property of natural gas is expressed by Redlich-Kwong equation. The gas film pressure governing equations proposed by Muijderman for narrow grooves are modified and solved for the seal faces. The influences of natural gas viscosity-pressure effect on the sealing characteristics, such as leakage rate and opening force, of spiral groove dry gas seal are analyzed. Results show that the viscosity-pressure effect has significant influence on spiral groove dry gas seal. This effect reduces the leakage rate but increases the opening force, compared to the situation without considering the viscosity-pressure effect. With the pressure up to 4 MPa, the viscosity-pressure effect of natural gas is weak and negligible. As the pressure increases, the viscosity-pressure effect increases. At 12 MPa, the relative deviations of leakage rate and opening force caused by the viscosity-pressure effect are respectively −30.6% and 1.65%. Therefore, the analyses indicate that the viscosity-pressure effect of natural gas needs to be considered when used in high pressure situation

Pregnancy in Women with Systemic Lupus Erythematosus: A Retrospective Study of 83 Pregnancies at a Single Centre

Objective: To evaluate the outcome of 80 pregnant women with systemic lupus erythematosus (SLE) and explore the risk factors for lupus flare, obstetric complications and fetal loss. Methods: 83 pregnancies in 80 women were divided into three groups. Group A: patients in remission for > 6 months before pregnancy, proteinuria < 0.5 g per day, without renal failure and discontinuation of cytotoxic drugs for > one year; Group B: patients with SLE disease activity in the six months before pregnancy; Group C: patients with new onset SLE during pregnancy. Results: In group A, 76.47% pregnancies achieved full-term deliveries and 80.39% achieved live born infants. In group B and C, the outcome was poor. Among 62 patients (64 pregnancies) diagnosed as SLE before pregnancy, SLE flares occurred in 27 (42.19%) pregnancies. SLE disease activity in the six months before pregnancy was significantly associated with lupus flare (OR 5.00, 95% CI 1.14–21.87, p = 0.03) and fetal loss. New onset lupus during pregnancy was independently associated with obstetric complications (OR 7.22, 95% CI 2.14–24.38, p = 0.001). Conclusions: The current study confirmed the previous report that SLE should be considered a high risk of pregnancy. If pregnancy is planned after remission for > 6 months, the favorable outcome can be achieved