Jet charge identification in ee-Z-qq process at Z pole operation

Accurate jet charge identification is essential for precise electroweak and flavor measurements at the high-energy frontier. We propose a novel method called the Leading Particle Jet Charge method (LPJC) to determine the jet charge based on information about the leading charged particle. Tested on Z - bb and Z - cc samples at a center-of-mass energy of 91.2GeV, the LPJC achieves an effective tagging power of 20%/9% for the c/b jet, respectively. Combined with the Weighted Jet Charge method (WJC), we develop a Heavy Flavor Jet Charge method (HFJC), which achieves an effective tagging power of 39%/20% for c/b jet, respectively. This paper also discusses the dependencies between jet charge identification performance and the fragmentation process of heavy flavor jets, and critical detector performances

Precision Higgs physics at the CEPC

The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS and CMS Collaborations marked the beginning of a new era in high energy physics. The Higgs boson will be the subject of extensive studies of the ongoing LHC program. At the same time, lepton collider based Higgs factories have been proposed as a possible next step beyond the LHC, with its main goal to precisely measure the properties of the Higgs boson and probe potential new physics associated with the Higgs boson. The Circular Electron Positron Collider~(CEPC) is one of such proposed Higgs factories. The CEPC is an $e^+e^-$ circular collider proposed by and to be hosted in China. Located in a tunnel of approximately 100~km in circumference, it will operate at a center-of-mass energy of 240~GeV as the Higgs factory. In this paper, we present the first estimates on the precision of the Higgs boson property measurements achievable at the CEPC and discuss implications of these measurements.Comment: 46 pages, 37 figure

Artificial Intelligence‐Based Medical Sensors for Healthcare System

Abstract The aging population and the prevalence of infectious diseases have impacted the traditional medical order, significantly increasing the burden on healthcare and adversely affecting the socio‐economic system. Medical sensors based on artificial intelligence (AI) provide new ideas for modern medical data collection to monitor the health status of individuals and environmental changes. Meanwhile, with the aid of AI algorithms, the big data processing capabilities of sensor systems have been greatly improved, further realizing early predictions and timely diagnoses. In this paper, a brief overview is offered on the development status of AI‐enabled medical sensors for off‐body detection, near‐body monitoring, disease prediction, and clinical decision support system, and the ongoing challenges and future prospects to move from concept to implementation are discussed. In the foreseeable future, breakthroughs in the combination of medical sensors and AI algorithms are expected to pave the way for early detection and clinical decision support and improve the accuracy and efficiency for disease diagnosis

Acute Gaseous Air Pollution Exposure and Hospitalizations for Acute Ischemic Stroke: A Time-Series Analysis in Tianjin, China

Background: Stroke has always been an important problem troubling human health. Short-term exposure to air pollutants is associated with increased hospital admissions. The rise of pollutants such as O3 has caused a huge social and economic burden. This study aims to explore the relationship between short-term exposure to ambient gaseous pollutants and daily hospitalizations for ischemic stroke, utilizing a four-year time-series study in Tianjin. Methods: Collecting the data of gaseous pollutants (NO2, SO2, CO, O3), meteorological data (including daily average temperature and relative humidity) and the number of hospitalizations due to ischemic stroke in Tianjin Medical University General Hospital from 2013 to 2016. Poisson regression generalized additive model with single-day and multi-day moving average lag structure was used to estimate adverse effects of gaseous pollutants on daily hospitalizations. Subgroup analysis was performed to detect modification effect by gender and age. Results: In total, there were 9081 ischemic stroke hospitalizations. After controlling for the meteorological factors in the same period, no significant findings were found with the increase of NO2, SO2, CO and O3 concentrations at most of the time in the single-pollutant model. Similarly, in the stratified analysis, no associations between gaseous pollutants and ischemic stroke were observed in this study. Conclusions: Short-term exposure to NO2, SO2, CO and O3 was not distinctly associated with daily hospitalizations for ischemic stroke in Tianjin. Multicenter studies in the future are warranted to explore the associations between gaseous pollution exposure and ischemic stroke

The Influence of Climate Change on Droughts and Floods in the Yangtze River Basin from 2003 to 2020

In recent decades, extreme floods and droughts have occurred frequently around the world, which seriously threatens the social and economic development and the safety of people’s lives and properties. Therefore, it is of great scientific significance to discuss the causes and characteristic quantization of extreme floods and droughts. Here, the terrestrial water storage change (TWSC) derived from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) data was used to characterize the floods and droughts in the Yangtze River basin (YRB) during 2003 and 2020. To reduce the uncertainty of TWSC results, the generalized three-cornered hat and least square methods were used to fuse TWSC results from six GRACE solutions. Then combining precipitation (PPT), evapotranspiration, soil moisture (SM), runoff, and extreme climate index data, the influence of climate change on floods and droughts in the YRB was discussed and analyzed. The results show that the fused method can effectively improve the uncertainty of TWSC results. And seven droughts and seven floods occurred in the upper of YRB (UY) and nine droughts and six floods appeared in the middle and lower of YRB (MLY) during the study period. The correlation between TWSC and PPT (0.33) is the strongest in the UY, and the response time between the two is 1 month, while TWSC and SM (0.67) are strongly correlated with no delay in the MLY. The reason for this difference is mainly due to the large-scale hydropower development in the UY. Floods and droughts in the UY and MLY are more influenced by the El Niño-Southern Oscillation (ENSO) (correlation coefficients are 0.39 and 0.50, respectively) than the Indian Ocean Dipole (IOD) (correlation coefficients are 0.19 and 0.09, respectively). The IOD event is usually accompanied by the ENSO event (the probability is 80%), and the hydrological hazards caused by independent ENSO events are less severe than those caused by these two extreme climate events in the YRB. Our results provide a reference for the study on the formation, development, and recovery mechanism of regional floods and droughts on a global scale

Mechanical Force Modulates Alveolar Bone Marrow Mesenchymal Cells Characteristics for Bone Remodeling during Orthodontic Tooth Movement through Lactate Production

Orthodontic tooth movement (OTM) relies on mechanical force-induced bone remodeling. As a metabolic intermediate of glycolysis, lactate has recently been discovered to participate in bone remodeling by serving as a signaling molecule. However, whether lactate could respond to mechanical stimulus during OTM, as well as whether lactate has an impact on the alveolar bone remodeling during orthodontics, remain to be further elucidated. In the current study, we observed physiologically elevated production of lactate along with increased osteogenic differentiation, proliferation, and migration of alveolar bone marrow mesenchymal cells (ABMMCs) under mechanical force. Inhibition of lactate, induced by cyclic mechanical stretch by GNE-140, remarkably suppressed the osteogenic differentiation, proliferation, and migration, yet enhanced apoptosis of ABMMCs. Mechanistically, these regulatory effects of lactate were mediated by histone lactylation. Taken together, our results suggest that force-induced lactate is involved in controlling bone remodeling-related cellular activities in ABMMCs and plays a vital role in the alveolar bone remodeling during OTM. Our findings indicate that lactate might be a critical modulator for alveolar bone remodeling during OTM, providing a novel therapeutic target for the purpose of more effectively controlling tooth movement and improving the stability of orthodontic results

Comparison of the characteristics of three kinds of HVDC systems with ABB, SIMENS, and Cigre Benchmark

This study presents the comparison among three control systems: Cigre Benchmark model, ABB model, and SIMENS model based on PSCAD. Firstly, the control systems which refer to Cigre Benchmark control model, ABB control model, and SIMENS control model are introduced, respectively. Analysis and comparison are done on these control systems about their design theories, control logic, and functional models, and the advantages and disadvantages of each control system are concluded. Secondly, simulations in both normal and fault conditions are done in order to verify the conclusions. On the one hand, the steady-state response characteristics of these three high-voltage direct current (HVDC) models are obtained and compared by setting different voltage of the receiving terminal AC bus. On the other hand, the transient response characteristics of these three HVDC models under different operating conditions are obtained, such as symmetrical and asymmetrical short-circuit fault, line switching on or off etc. The research results will provide experiences and references for the future optimisation of the HVDC control system