Age Spreads and Systematics in λ Orionis with Gaia DR2 and the SPOTS Tracks

In this paper we investigate the robustness of age measurements, age spreads, and stellar models in young pre-main-sequence stars. For this effort, we study a young cluster, λ Orionis, within the Orion star-forming complex. We use Gaia data to derive a sample of 357 targets with spectroscopic temperatures from spectral types or from the automated spectroscopic pipeline in APOGEE Net. After accounting for systematic offsets between the spectral type and APOGEE temperature systems, the derived properties of stars on both systems are consistent. The complex interstellar medium, with variable local extinction, motivates a star-by-star dereddening approach. We use a spectral energy distribution fitting method calibrated on open clusters for the Class III stars. For the Class II population, we use a Gaia G-RP dereddening method, minimizing systematics from disks, accretion, and other physics associated with youth. The cluster age is systematically different in models incorporating the structural impact of starspots or magnetic fields than in nonmagnetic models. Our mean ages range from 2–3 Myr (nonmagnetic models) to 3.9 ± 0.2 Myr in the SPOTS model (f = 0.34). We find that star-by-star dereddening methods distinguishing between pre-main-sequence classes provide a smaller age spread than techniques using a uniform extinction, and we infer a minimum age spread of 0.19 dex and a typical age spread of 0.35 dex after modeling age distributions convolved with observed errors. This suggests that the λ Ori cluster may have a long star formation timescale and that spotted stellar models significantly change age estimates for young clusters.

Direct Measurements of Giant Star Effective Temperatures and Linear Radii: Calibration against Spectral Types and V − K Color

We calculate directly determined values for effective temperature (T eff) and radius (R) for 191 giant stars based upon high-resolution angular size measurements from optical interferometry at the Palomar Testbed Interferometer. Narrow- to wideband photometry data for the giants are used to establish bolometric fluxes and luminosities through spectral energy distribution fitting, which allows for homogeneously establishing an assessment of spectral type and dereddened V 0 − K 0 color; these two parameters are used as calibration indices for establishing trends in T eff and R. Spectral types range from G0III to M7.75III, V 0 − K 0 from 1.9 to 8.5. For the V 0 − K 0 = {1.9, 6.5} range, median T eff uncertainties in the fit of effective temperature versus color are found to be less than 50 K; over this range, T eff drops from 5050 to 3225 K. Linear sizes are found to be largely constant at 11 R ⊙ from G0III to K0III, increasing linearly with subtype to 50 R ⊙ at K5III, and then further increasing linearly to 150 R ⊙ by M8III. Three examples of the utility of this data set are presented: first, a fully empirical Hertzsprung–Russell diagram is constructed and examined against stellar evolution models; second, values for stellar mass are inferred based on measures of R and literature values for log g ; finally, an improved calibration of an angular size prediction tool, based upon V and K values for a star, is presented.

Usage and Temporal Patterns of Public Bicycle Systems: Comparison among Points of Interest

The public bicycle system is an important component of “mobility as a service” and has become increasingly popular in recent years. To provide a better understanding of the station activity and driving mechanisms of public bicycle systems, the study mainly compares the usage and temporal characteristics of public bicycles in the vicinity of the most common commuting-related points of interest and land use. It applies the peak hour factor, distribution fitting, and K-means clustering analysis on station-based data and performs the public bicycles usage and operation comparison among different points of interest and land use. The following results are acquired: (1) the demand type for universities and hospitals in peaks is return-oriented when that of middle schools is hire-oriented; (2) bike hire and return at metro stations and hospitals are frequent, while only the rental at malls is; (3) compared to middle schools and subway stations with the shortest bike usage duration, malls have the longest duration, valued at 18.08 min; and (4) medical and transportation land, with the most obvious morning return peak and the most concentrated usage in a whole day, respectively, both present a lag relation between bike rental and return. In rental-return similarity, the commercial and office lands present the highest level.

Decreasing methane emissions from China's coal mining with rebounded coal production

China is the world’s largest anthropogenic methane (CH4) emitter, with coal mine methane (CMM) as one of the main contributors. However, previous studies have not reach consensus on the magnitude and trend of China’s CMM emissions since 2010. Through distribution fitting and Monte Carlo methods, dynamic emission factors (EFs) of CMM at the province-level were derived with high confidence; along with the updated data on surface mining, abandoned coal mines, and methane utilization, we revealed that China’s annual CMM emissions were estimated at 20.11 Tg between 2010 and 2019 with a decline of 0.93 Tg yr-1. Although coal production was revived in 2017, we found that the growing trend of China’s CMM emissions since 2012 were curbed by the previously-overlooked factors including the growth of CMM utilization and coal production from surface mining, and decrease of emission factors driven by the closure of high CH4-content coal mines and a regional production shift to lower-emission areas.

Determining the effectiveness of pollution control policies implemented by the Chinese government: Distribution fitting and testing of daily PM2.5 data

Air pollution has become an urgent issue affecting sustainable urban development. The Chinese government has implemented a series of air pollution control policies since 2012. Exploring the effectiveness of pollution control policies is important for future policy-making and improvements in air quality. Mean and variance tests were used for evaluation on the effectiveness of pollution control policies implemented in major cities and estimates of the heterogeneity among cities based on the distribution fitting and testing of daily PM2.5 data from January 2015 to January 2020. The nonparametric kernel density estimation adopted in this paper can effectively describe the data characteristics, and this is very important for air quality monitoring and control. Our findings demonstrate that air pollution prevention and control policies have significantly improved the levels and distribution of urban air quality in China.

Remaining Useful Life Prediction of the Concrete Piston Based on Probability Statistics and Data Driven

This paper proposes a method on predicting the remaining useful life (RUL) of a concrete piston of a concrete pump truck based on probability statistics and data-driven approaches. Firstly, the average useful life of the concrete piston is determined by probability distribution fitting using actual life data. Secondly, according to condition monitoring data of the concrete pump truck, a concept of life coefficient of the concrete piston is proposed to represent the influence of the loading condition on the actual useful life of individual concrete pistons, and different regression models are established to predict the RUL of the concrete pistons. Finally, according to the prediction result of the concrete piston at different life stages, a replacement warning point is established to provide support for the inventory management and replacement plan of the concrete piston.

Expected Shortfall Reliability—Added Value of Traditional Statistics and Advanced Artificial Intelligence for Market Risk Measurement Purposes

The Fundamental Review of the Trading Book is a market risk measurement and management regulation recently issued by the Basel Committee. This reform, often referred to as “Basel IV”, intends to strengthen the financial system. The newest capital standard relies on the use of the Expected Shortfall. This risk measure requires to get sufficient information in the tails to ensure its reliability, as this one has to be alimented by a sufficient quantity of relevant data (above the 97.5 percentile in the case of the regulation or interest). In this paper, after discussing the relevant features of Expected Shortfall for risk measurement purposes, we present and compare several methods allowing to ensure the reliability of the risk measure by generating information in the tails. We discuss these approaches with respect to their relevance considering the underlying situation when it comes to available data, allowing practitioners to select the most appropriate approach. We apply traditional statistical methodologies, for instance distribution fitting, kernel density estimation, Gaussian mixtures and conditional fitting by Expectation-Maximisation as well as AI related strategies, for instance a Synthetic Minority Over-sampling Technique implemented in a regression environment and Generative Adversarial Nets.

Local Gaussian Distribution Fitting Boundary Image Segmentation Algorithm for Ultrasound Images in Avoiding Recurrent Laryngeal Nerve Injury during Thyroid Nodules Treatment

This work aimed to analyze the effect of the boundary segmentation algorithm in thyroid nodules image segmentation and the influence of its adoption in avoiding recurrent laryngeal nerve (RLN) injury during treatment of thyroid nodules. The nodule boundary was extracted aided by the local Gaussian distribution fitting energy (LGDF) segmentation algorithm, which was compared with the normalized cut (Ncut) algorithm and the Canny algorithm. Then, 51 patients treated with microwave ablation for thyroid nodules were taken as a test group, and 51 patients treated with surgical resection were taken as a control group. The incidence of RLN injury and the levels of free triiodothyronine (FT3), free thyroid hormone (FT4), and thyroid-stimulating hormone (TSH) were compared between the two groups before and after treatment. The results showed that the true positive fraction (TPF) of the LGDF segmentation algorithm was 69.45%, the TPF of the Ncut algorithm and the Canny algorithm were 58.65% and 52.37%, respectively. The TPF of LGDF algorithm was higher than that of the Ncut algorithm and Canny algorithm, with notable differences ( P < 0.05 ). In the control group, there were 10 cases of temporary and permanent damage to the RLN after operation, and the total incidence was 19.61%. In the test group, there were 3 cases of temporary and permanent damage to the RLN after operation, and the total incidence was 5.88%, which was lower than that of the control group ( P < 0.05 ). No evident differences were shown in the levels of FT3, FT4, and TSH between the two groups before treatment ( P > 0.05 ). However, after treatment, the TSH level of the test group (4.58 ± 0.79) was higher than that of the control group (3.19 ± 0.17), and the levels of FT3 and FT4 in the test group were lower than those in the control group, and the differences were remarkable ( P < 0.05 ). In short, the LGDF algorithm had more ideal segmentation effect. In addition, ultrasound-guided microwave ablation was effective in treating benign thyroid nodules, which could reduce damage to the RLN and maintain normal thyroid function.