Balanced Coarsening for Multilevel Hypergraph Partitioning via Wasserstein Discrepancy

We propose a balanced coarsening scheme for multilevel hypergraph partitioning. In addition, an initial partitioning algorithm is designed to improve the quality of k-way hypergraph partitioning. By assigning vertex weights through the LPT algorithm, we generate a prior hypergraph under a relaxed balance constraint. With the prior hypergraph, we have defined the Wasserstein discrepancy to coordinate the optimal transport of coarsening process. And the optimal transport matrix is solved by Sinkhorn algorithm. Our coarsening scheme fully takes into account the minimization of connectivity metric (objective function). For the initial partitioning stage, we define a normalized cut function induced by Fiedler vector, which is theoretically proved to be a concave function. Thereby, a three-point algorithm is designed to find the best cut under the balance constraint

Growth of high-quality CrI3 single crystals and engineering of its magnetic properties via V and Mn doping

CrI3, as a soft van der Waals layered magnetic material, has been widely concerned and explored for its magnetic complexity and tunability. In this work, high quality and large size thin CrI3, V and Mn doped single crystals were prepared by chemical vapor transfer method. A remarkable irreversible Barkhausen effect was observed in CrI3 and CrMn0.06I3, which can be attributed to the low dislocation density that facilitates movement of the domain walls. In addition, the introduction of the doping element Mn allows higher saturation magnetization intensity. Cr0.5V0.5I3 exhibits substantially increased coercivity force and larger magnetocrystalline anisotropy compared to CrI3, while kept similar Curie temperature and good environmental stability. The first principles calculations suggest direct and narrowed band gaps in Cr0.5V0.5I3 and VI3 comparing to CrI3. The smaller band gaps and good hard magnetic property make Cr0.5V0.5I3 an alternative choice to future research of spintronic devices

Effects of Simulated Nitrogen Deposition on the Bacterial Community of Urban Green Spaces

Continuing nitrogen (N) deposition has a wide-ranging impact on terrestrial ecosystems. To test the hypothesis that, under N deposition, bacterial communities could suffer a negative impact, and in a relatively short timeframe, an experiment was carried out for a year in an urban area featuring a cover of Bermuda grass (Cynodon dactylon) and simulating environmental N deposition. NH4NO3 was added as external N source, with four dosages (N0 = 0 kg N ha−2 y−1, N1 = 50 kg N ha−2 y−1, N2 = 100 kg N ha−2 y−1, N3 = 150 kg N ha−2 y−1). We analyzed the bacterial community composition after soil DNA extraction through the pyrosequencing of the 16S rRNA gene amplicons. N deposition resulted in soil bacterial community changes at a clear dosage-dependent rate. Soil bacterial diversity and evenness showed a clear trend of time-dependent decline under repeated N application. Ammonium nitrogen enrichment, either directly or in relation to pH decrease, resulted in the main environmental factor related to the shift of taxa proportions within the urban green space soil bacterial community and qualified as a putative important driver of bacterial diversity abatement. Such an impact on soil life induced by N deposition may pose a serious threat to urban soil ecosystem stability and surrounding areas

Event-triggered dynamic output quantized control for 2-D switched systems

It is well known that designing mode-dependent event-triggered control (MDETC) brings challenging difficulties to theoretical analysis, especially for two-dimensional (2-D) switched systems. Therefore, for 2-D switched Fornasini–Marchesini local state-space (FMLSS) systems, this paper designs a MDETC to investigate global exponential stabilization almost surely (GES a.s.). A MDETC based on dynamic output quantization control scheme is designed, which not only has a wide range of practicability, but also greatly saves network bandwidth resources. By constructing mode-dependent Lyapunov functions that include two time directions, some novel sufficient conditions are provided such that the switched FMLSS system achieves GES a.s. Unlike most previous results, our results do not require each mode to be stable, not even after adding control. Finally, numerical experiments are provided to verify the validity of our main theoretical results

Minimal Cut Sets-Based Reliability Evaluation of the More Electric Aircraft Power System

The More Electric Aircraft (MEA) stands for the direction of aviation development in the new era, and the reliability of power systems on the MEA has attracted widespread attention. Based on the characteristics of MEA power systems, an equivalent method of electrical topology structure is presented in this article, and evaluation method is proposed which shows the reliability of the overall system with the reliability of specific nodes. Firstly, electrical topology structure of a MEA power system is converted into a network node diagram according to the proposed equivalent method. Then, the minimal path sets of specific nodes are obtained by the adjacent matrix algorithm, and the low-order minimal cut sets of disjointed are obtained. After that, the actual failure rate of components is converted to node failure rate, and the reliability of the overall system is evaluated by operational reliability indexes of specific nodes. Finally, taking the MEA A380 as an example, this paper compares and analyzes the reliability of AC loads, DC loads, and key loads to verify the validity and feasibility of the proposed evaluation method. This evaluation system can predict the weak points existing in the MEA power system, as well as providing theoretical support for maintenance schedule

Home indoor air quality and cognitive function over one year for people working remotely during COVID

The coronavirus disease 2019 (COVID-19) pandemic triggered an increase in remote work-from-home for office workers. Given that many homes now function as offices despite not being designed to support office work, it is critical to research the impact of indoor air quality (IAQ) in homes on the cognitive performance of people working from home. In this study, we followed 206 office workers across the U.S. over one year under remote or hybrid-remote settings during 2021&ndash;2022. Participants placed two real-time, consumer-grade indoor environmental monitors in their home workstation area and bedroom. Using a custom smartphone application geofenced to their residential address, participants responded to surveys and periodic cognitive function tests, including the Stroop color&ndash;word interference test, Arithmetic two-digit addition/subtraction test, and Compound Remote Associates Task (cRAT). Exposures assessed included carbon dioxide (CO2) and thermal conditions (indoor heat index: a combination of temperature and relative humidity) averaged over 30 min prior to each cognitive test. In adjusted longitudinal mixed models (n &le; 126), we found that indoor thermal conditions at home were associated with cognitive function outcomes non-linearly (p &lt; 0.05), with poorer cognitive performance on the Stroop test and poorer creative problem-solving on the cRAT when conditions were either too warm or too cool. Most indoor CO2 levels were &lt;640 ppm, but there was still a slight association between higher CO2 and poorer cognitive performance on Stroop (p = 0.09). Our findings highlight the need to enhance home indoor environmental quality for optimal cognitive function during remote work, with benefits for both employees and employers.</p

Human-in-the-Loop Schema Induction

Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction(IE), often with limited human curation. We demonstrate a human-in-the-loop schema induction system powered by GPT-3. We first describe the different modules of our system, including prompting to generate schematic elements, manual edit of those elements, and conversion of those into a schema graph. By qualitatively comparing our system to previous ones, we show that our system not only transfers to new domains more easily than previous approaches, but also reduces efforts of human curation thanks to our interactive interface.Comment: 10 pages, ACL2023 demo trac

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure