Translation and Interpretation (TIP) Training Manual

The goal is to provide a systematic training manual for future volunteers monthly training sessions. The goal of this manual is to make sure every volunteers know how to behave appropriately in terms of campus emergency situations.https://orb.binghamton.edu/mpa_capstone/1016/thumbnail.jp

Rational design of a polyoxometalate intercalated layered double hydroxide: highly efficient catalytic epoxidation of allylic alcohols under mild and solvent-free conditions

Intercalation catalysts, owing to their modular and accessible gallery and unique interlamellar chemical environment, have shown wide application in various catalytic reactions. However, the poor mass transfer between the active components of the intercalated catalysts and organic substrates is one of the challenges that limit their further application. Herein, we have developed a novel heterogeneous catalyst by intercalating the polyoxometalate (POM) of Na9LaW10O36⋅32 H2O (LaW10) into layered double hydroxides (LDHs), which have been covalently modified with ionic liquids (ILs). The intercalation catalyst demonstrates high activity and selectivity for the epoxidation of various allylic alcohols in the presence of H2O2. For example, trans-2-hexen-1-ol undergoes up to 96 % conversion and 99 % epoxide selectivity at 25 °C in 2.5 h. To the best of our knowledge, the Mg3Al−ILs−C8−LaW10 composite material constitutes one of the most efficient heterogeneous catalysts for the epoxidation of allylic alcohols (including the hydrophobic allylic alcohols with long alkyl chains) reported so far

Integrated self-consistent macro-micro traffic flow modeling and calibration framework based on trajectory data

Calibrating microscopic car-following (CF) models is crucial in traffic flow theory as it allows for accurate reproduction and investigation of traffic behavior and phenomena. Typically, the calibration procedure is a complicated, non-convex optimization issue. When the traffic state is in equilibrium, the macroscopic flow model can be derived analytically from the corresponding CF model. In contrast to the microscopic CF model, calibrated based on trajectory data, the macroscopic representation of the fundamental diagram (FD) primarily adopts loop detector data for calibration. The different calibration approaches at the macro- and microscopic levels may lead to misaligned parameters with identical practical meanings in both macro- and micro-traffic models. This inconsistency arises from the difference between the parameter calibration processes used in macro- and microscopic traffic flow models. Hence, this study proposes an integrated multiresolution traffic flow modeling framework using the same trajectory data for parameter calibration based on the self-consistency concept. This framework incorporates multiple objective functions in the macro- and micro-dimensions. To expeditiously execute the proposed framework, an improved metaheuristic multi-objective optimization algorithm is presented that employs multiple enhancement strategies. Additionally, a deep learning technique based on attention mechanisms was used to extract stationary-state traffic data for the macroscopic calibration process, instead of directly using the entire aggregated data. We conducted experiments using real-world and synthetic trajectory data to validate our self-consistent calibration framework

SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth

Exploring robust and efficient association methods has always been an important issue in multiple-object tracking (MOT). Although existing tracking methods have achieved impressive performance, congestion and frequent occlusions still pose challenging problems in multi-object tracking. We reveal that performing sparse decomposition on dense scenes is a crucial step to enhance the performance of associating occluded targets. To this end, we propose a pseudo-depth estimation method for obtaining the relative depth of targets from 2D images. Secondly, we design a depth cascading matching (DCM) algorithm, which can use the obtained depth information to convert a dense target set into multiple sparse target subsets and perform data association on these sparse target subsets in order from near to far. By integrating the pseudo-depth method and the DCM strategy into the data association process, we propose a new tracker, called SparseTrack. SparseTrack provides a new perspective for solving the challenging crowded scene MOT problem. Only using IoU matching, SparseTrack achieves comparable performance with the state-of-the-art (SOTA) methods on the MOT17 and MOT20 benchmarks. Code and models are publicly available at \url{https://github.com/hustvl/SparseTrack}.Comment: 12 pages, 8 figure

A hazard analysis via an improved timed colored petri net with time–space coupling safety constraint

AbstractPetri nets are graphical and mathematical tools that are applicable to many systems for modeling, simulation, and analysis. With the emergence of the concept of partitioning in time and space domains proposed in avionics application standard software interface (ARINC 653), it has become difficult to analyze time–space coupling hazards resulting from resource partitioning using classical or advanced Petri nets. In this paper, we propose a time–space coupling safety constraint and an improved timed colored Petri net with imposed time–space coupling safety constraints (TCCP-NET) to fill this requirement gap. Time–space coupling hazard analysis is conducted in three steps: specification modeling, simulation execution, and results analysis. A TCCP-NET is employed to model and analyze integrated modular avionics (IMA), a real-time, safety-critical system. The analysis results are used to verify whether there exist time–space coupling hazards at runtime. The method we propose demonstrates superior modeling of safety-critical real-time systems as it can specify resource allocations in both time and space domains. TCCP-NETs can effectively detect underlying time–space coupling hazards

Culture Fever: Utopianism and Pragmatism in Chinese Intellectuals\u27 Search for Modernization

Situating the 1980s Cultural Fever in a global westernization context and as one of the three major waves of the Chinese intellectual movement in the last two centuries, this paper attempts to analyze the complexities and nuances of the cultural reckoning process in the mid-1980s by examining how such process is manifested in academia, a magazine called Reading, a TV-series documentary titled River Elegy (Heshang), and movie Red Sorghum (Honggaoliang). Although different in their schools of affiliation, areas of expertise, and intended audience, in hope of a shared utopian future, Chinese intellectuals in the 1980s carried out their self-proclaimed duty to contribute to the transformation by producing different theoretical reformulations of national identity