Observed hydrological changes associated with active tectonic blocks before three consecutive earthquakes in Qinghai, China.

In the past 2 years, three earthquakes of magnitude 6.0 and above occurred consecutively in Qinghai province, China, i.e., the 22 May 2021 Ms7.4 Maduo, 8 January 2022 Ms6.9 Menyuan, and 26 March 2022 Ms6.0 Delingha earthquakes. The hydrological observation instruments set up by the China Earthquake Administration allow us to study the dynamic processes in the well-aquifer systems during the establishment of criticality. Particularly, the observations played an important role in the prediction of the 8 January 2022 Ms6.9 Menyuan earthquake that was approved by the People's Government of Qinghai province. This work presents the hydrological data recorded by 7 stations to show the short-term anomalies before these earthquakes. To explore the performance of the hydrological observations in detecting earthquakes that occurred on different active tectonic blocks, we calculate the relative amplitudes of the pre-seismic changes. Results indicate that markedly pre-seismic change is found if the observation station and the detection earthquake are on the same block, and moderate change is found if they are on the adjacent blocks, while the precursor is hard to be identified if they are on the separated blocks. The variations in the hydrological responses may be caused by the strength weakening (or dilatancy) of source media. And the increased volumes in the crust can be evidenced by the changes in the geodetic time series in the same neighborhoods and during the same period, augmenting stress loading between the blocks.

YOLO-LWNet: A Lightweight Road Damage Object Detection Network for Mobile Terminal Devices.

To solve the demand for road damage object detection under the resource-constrained conditions of mobile terminal devices, in this paper, we propose the YOLO-LWNet, an efficient lightweight road damage detection algorithm for mobile terminal devices. First, a novel lightweight module, the LWC, is designed and the attention mechanism and activation function are optimized. Then, a lightweight backbone network and an efficient feature fusion network are further proposed with the LWC as the basic building units. Finally, the backbone and feature fusion network in the YOLOv5 is replaced. In this paper, two versions of the YOLO-LWNet, small and tiny, are introduced. The YOLO-LWNet was compared with the YOLOv6 and the YOLOv5 on the RDD-2020 public dataset in various performance aspects. The experimental results show that the YOLO-LWNet outperforms state-of-the-art real-time detectors in terms of balancing detection accuracy, model scale, and computational complexity in the road damage object detection task. It can better achieve the lightweight and accuracy requirements for object detection for mobile terminal devices.

Americans do not select their doctors based on race.

To what extent do Americans racially discriminate against doctors? While a large literature shows that racial biases pervade the American healthcare system, there has been no systematic examination of these biases in terms of who patients select for medical treatment. We examine this question in the context of the ongoing global COVID-19 pandemic, where a wealth of qualitative evidence suggests that discrimination against some historically marginalized communities, particularly Asians, has increased throughout the United States. Conducting a well-powered conjoint experiment with a national sample of 1,498 Americans, we find that respondents do not, on average, discriminate against Asian or doctors from other systematically minoritized groups. We also find no consistent evidence of treatment effect heterogeneity; Americans of all types appear not to care about the racial identity of their doctor, at least in our study. This finding has important implications for the potential limits of American prejudice.

An N-heterocyclic carbene-catalyzed switchable reaction of 9-(trimethylsilyl)fluorene and aldehydes: chemoselective synthesis of dibenzofulvenes and fluorenyl alcohols.

An N-heterocyclic carbene-catalyzed synthesis of dibenzofulvenes and fluorenyl alcohols was developed. In the presence of 10 mol% NHC (1,3-bis(2,6-diisopropylphenyl)imidazol-2-ylidene) and 4 Å molecular sieves, 9-(trimethylsilyl)fluorene undergoes an olefination reaction with aldehydes to produce dibenzofulvenes in 43-99% yields. However, on reducing the NHC loading to 1 mol% and with the addition of water, 9-(trimethylsilyl)fluorene selectively undergoes nucleophilic addition with aldehydes to afford fluorenyl alcohols in 40-95% yields.