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Traffic energy consumption estimation is significant for the sustainable transportation. However, it is difficult to directly employ macro traffic flow data to accurately estimate the traffic energy consumption due to many traffic energy consumption models need second-by-second vehicle trajectory. To solve this problem, this paper proposes a traffic energy consumption model based on the macro-micro data, which the macro data derived from the fixed-location sensors and sparse micro data derived from the Connected and Automated Vehicles (CAVs). The completed vehicle trajectories are constructed by the nonparametric kernel smoothing algorithm and variational theory. To test the performance of the proposed method, the Next Generation Simulation micro (NGSIM) dataset and Caltrans Performance Measurement System macro dataset obtained from the same road and time are used. The results indicate that the proposed method not only can reflect the characteristics of traffic kinematic waves caused by traffic congestion, but also minimize the errors generated by the macro-micro transformation. In addition, it can significantly improve the accuracy of energy consumption estimation. 

Car-following (CF) behavior is a fundamental of traffic flow modeling; it can be used for the virtual testing of connected and automated vehicles and the simulation of various types of traffic flow, such as free flow and traffic oscillation. Although existing CF models can replicate the free flow well, they are incapable of simulating complicated traffic oscillation, and it is difficult to strike a balance between accuracy and efficiency. This article investigates the error variation when the traffic oscillation is simulated by the intelligent driver model (IDM). Then, it divides the traffic oscillation into four phases (coasting, deceleration, acceleration, and stationary) by using the space headway of multiple steps. To simulate traffic oscillation between multiple human-driven vehicles, a dynamic transformation CF model is proposed, which includes the long-time prediction submodel [modified sequence-to-sequence (Seq2seq)] model, short-time prediction submodel (Transformer), and their dynamic transformation strategy]. The first submodel is utilized to simulate the coasting and stationary phases, while the second submodel is utilized to simulate the acceleration and deceleration phases. The results of experiments indicated that compared to K -nearest neighbors, IDM, and Seq2seq CF models, the dynamic transformation CF model reduces the trajectory error by 60.79–66.69% in microscopic traffic flow simulations, 7.71–29.91% in mesoscopic traffic flow simulations, and 1.59–18.26% in macroscopic traffic flow simulations. Moreover, the runtime of the dynamic transformation CF model (Inference) decreased by 14.43–66.17% when simulating the large-scale traffic flow. 

Abstract The Arabidopsis (Arabidopsis thaliana) TRANSPARENT TESTA GLABRA2 (TTG2) gene encodes a WRKY transcription factor that regulates a range of development events like trichome, seed coat, and atrichoblast formation. Loss-of-function of TTG2 was previously shown to reduce or eliminate trichome specification and branching. Here, we report the identification of an allele of TTG2, ttg2-6. In contrast to the ttg2 mutants described before, ttg2-6 displayed unique trichome phenotypes. Some ttg2-6 mutant trichomes were hyper-branched, whereas others were hypo-branched, distorted, or clustered. Further, we found that in addition to specifically activating R3 MYB transcription factor TRIPTYCHON (TRY) to modulate trichome specification, TTG2 also integrated cytoskeletal signaling to regulate trichome morphogenesis. The ttg2-6 trichomes displayed aberrant cortical microtubules (cMTs) and actin filaments (F-actin) configurations. Moreover, genetic and biochemical analyses showed that TTG2 could directly bind to the promoter and regulate the expression of BRICK1 (BRK1), which encodes a subunit of the actin nucleation promoting complex suppressor of cyclic AMP repressor (SCAR)/Wiskott–Aldrich syndrome protein family verprolin homologous protein (WAVE). Collectively, taking advantage of ttg2-6, we uncovered a function for TTG2 in facilitating cMTs and F-actin cytoskeleton-dependent trichome development, providing insight into cellular signaling events downstream of the core transcriptional regulation during trichome development in Arabidopsis. 

Abstract Topological insulators (TIs) have attracted significant attention in photonics and acoustics due to their unique physical properties and promising applications. Electronics has recently emerged as an exciting arena to study various topological phenomena because of its advantages in building complex topological structures. Here, we explore TIs on an integrated circuit (IC) platform with a standard complementary metal-oxide-semiconductor technology. Based on the Su–Schrieffer–Heeger model, we design a fully integrated topological circuit chain using multiple capacitively-coupled inductor–capacitor resonators. We perform comprehensive post-layout simulations on its physical layout to observe and evaluate the salient topological features. Our results demonstrate the existence of the topological edge state and the remarkable robustness of the edge state against various defects. Our work shows the feasibility and promise of studying TIs with IC technology, paving the way for future explorations of large-scale topological electronics on the scalable IC platform. 

Abstract Harnessing parity–time symmetry with balanced gain and loss profiles has created a variety of opportunities in electronics from wireless energy transfer to telemetry sensing and topological defect engineering. However, existing implementations often employ ad hoc approaches at low operating frequencies and are unable to accommodate large-scale integration. Here we report a fully integrated realization of parity–time symmetry in a standard complementary metal–oxide–semiconductor process technology. Our work demonstrates salient parity–time symmetry features such as phase transition as well as the ability to manipulate broadband microwave generation and propagation beyond the limitations encountered by existing schemes. The system shows 2.1 times the bandwidth and 30% noise reduction compared to conventional microwave generation in the oscillatory mode, and displays large non-reciprocal microwave transport from 2.75 to 3.10 GHz in the non-oscillatory mode due to enhanced nonlinearities. This approach could enrich integrated circuit design methodology beyond well-established performance limits and enable the use of scalable integrated circuit technology to study topological effects in high-dimensional non-Hermitian systems. 

Recently, exceptional points, a degeneracy of open wave systems, have been observed in photonics, acoustics, and electronics. They have mainly been realized as a degeneracy of resonances; however, a degeneracy associated with the absorption of waves can exhibit distinct and interesting physical features. Here, we demonstrate such an absorbing exceptional point by engineering degeneracies in the absorption spectrum of dissipative optical microcavities. We experimentally distinguished the conditions to realize an absorbing exceptional point versus a resonant exceptional point. Furthermore, when the optical loss was tuned to achieve perfect absorption at an absorbing exceptional point, we observed its signature, an anomalously broadened line shape in the absorption spectrum. The distinct scattering properties of the absorbing exceptional point create opportunities for both fundamental study and applications of non-Hermitian degeneracies. 

We report a microfluidic droplet generator which can produce single and compound droplets using a 3D axisymmetric co-flow structure. The design considered for the fabrication of the device integrated a user-friendly and cost-effective 3D printing process. To verify the performance of the device, single and compound emulsions of deionized water and mineral oil were generated and their features such as size, generation frequency, and emulsion structures were successfully characterized. In addition, the generation of bio emulsions such as alginate and collagen aqueous droplets in mineral oil was demonstrated in this study. Overall, the monolithic 3D printed axisymmetric droplet generator could offer any user an accessible and easy-to-utilize device for the generation of single and compound emulsions. 

Abstract There is a long history of using angle sensors to measure wavefront. The best example is the Shack-Hartmann sensor. Compared to other methods of wavefront sensing, angle-based approach is more broadly used in industrial applications and scientific research. Its wide adoption is attributed to its fully integrated setup, robustness, and fast speed. However, there is a long-standing issue in its low spatial resolution, which is limited by the size of the angle sensor. Here we report a angle-based wavefront sensor to overcome this challenge. It uses ultra-compact angle sensor built from flat optics. It is directly integrated on focal plane array. This wavefront sensor inherits all the benefits of the angle-based method. Moreover, it improves the spatial sampling density by over two orders of magnitude. The drastically improved resolution allows angle-based sensors to be used for quantitative phase imaging, enabling capabilities such as video-frame recording of high-resolution surface topography.