Modelling the relationship between match outcome and match performances during the 2019 FIBA basketball world cup: A quantile regression analysis

The FIBA Basketball World Cup is one of the most prominent sporting competitions for men’s basketball, with coaches interested in key performance indicators (KPIs) that give a better understanding of basketball competitions. The aims of the study were to (1) examine the relationship between match KPIs and outcome in elite men’s basketball; and (2) identify the most suitable analysis (multiple linear regression (MLR) vs. quantile regression (QR)) to model this relationship during the men’s basketball tournament. A total of 184 performance records from 92 games were selected and analyzed via MLR and QR, using 10th, 25th, 50th, 75th and 90th quantiles. Several offensive (Paint Score, Mid-Range Score, Three-Point Score, Offensive Rebounds and Turnovers) and defensive (Defensive Rebounds, Steals and Personal Fouls) KPIs were associated with match outcome. The QR model identified additional KPIs that influenced match outcome than the MLR model, with these being Mid-Range Score at the 10th quantile and Offensive Rebounds at the 90th quantile. In terms of contextual variables, the quality of opponent had no impact on match outcome across the entire range of quantiles. Our results highlight QR modelling as a potentially superior tool for performance analysts and coaches to design and monitor technical–tactical plans during match-play. Our study has identified the KPIs contributing to match success at the 2019 FIBA Basketball World Cup with QR modelling assisting with a more detailed performance analysis, to support coaches with the optimization of training and match-play styles

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation

Personalized text generation has broad industrial applications, such as explanation generation for recommendations, conversational systems, etc. Personalized text generators are usually trained on user written text, e.g., reviews collected on e-commerce platforms. However, due to historical, social, or behavioral reasons, there may exist bias that associates certain linguistic quality of user written text with the users' protected attributes such as gender, race, etc. The generators can identify and inherit these correlations and generate texts discriminately w.r.t. the users' protected attributes. Without proper intervention, such bias can adversarially influence the users' trust and reliance on the system. From a broader perspective, bias in auto-generated contents can reinforce the social stereotypes about how online users write through interactions with the users. In this work, we investigate the fairness of personalized text generation in the setting of explainable recommendation. We develop a general framework for achieving measure-specific counterfactual fairness on the linguistic quality of personalized explanations. We propose learning disentangled representations for counterfactual inference and develop a novel policy learning algorithm with carefully designed rewards for fairness optimization. The framework can be applied for achieving fairness on any given specifications of linguistic quality measures, and can be adapted to most of existing models and real-world settings. Extensive experiments demonstrate the superior ability of our method in achieving fairness while maintaining high generation performance

Exploring the Influence Factors of Early Hydration of Ultrafine Cement

This work intends to contribute to the understanding of the influence factors of early hydration of ultrafine cement by focusing on the different fineness, different kinds of hardening accelerators, and different curing temperatures. Isothermal calorimetry, thermogravimetry, and X-ray diffraction (XRD) were performed to compare the hydration and chemical evolution of pastes containing accelerators with different fineness and curing temperatures; meanwhile, mechanical properties and water absorption were tested. The results showed that the cement fineness had a significant effect on the early hydration process; the smaller the cement particle size, the higher the early compressive strength. The 24 h compressive strength of ultrafine cement with a particle diameter of 6.8μm could reach 55.94 MPa, which was 118% higher than the reference cement. Water absorption test results indicated that adding 1% Ca(HCOO)2 to ultrafine cement can effectively reduce the water absorption, and it was only 1.93% at 28 d, which was 46% lower than the reference cement. An increase in curing temperature accelerated the activation of ultrafine cement in terms of the strength development rate, and the content of Ca(OH)2 in the ultrafine cement paste could reach 13.09% after being mixed with water for 24 h, which was 22% higher than that of the reference cement

Biomass and nitrogen responses to grazing intensity in an alpine meadow on the eastern Tibetan Plateau

This study was conducted to examine the seasonal dynamics of biomass and plant nitrogen (N) content under three grazing intensities (light grazing - LG: 1.2, moderate grazing - MG: 2.0, and heavy grazing - HG: 2.9 yaks ha(-1)) in representative alpine meadow on the eastern Tibetan Plateau. Differentiation in grazing intensity in the study area started since 1997 and has continued to the present time. Plant samples were collected in the middle of June, August and September. The highest aboveground biomass occurred at the MG site for both August and September. Over the growing season, below-ground biomass (0-30 cm) increased as grazing intensity increased. The total below-ground biomass averaged over all sampling dates was 1226, 1908 and 2244 g m(-2) for LG site, MG site and HG site, which accounted for 75, 81 and 88% of total biomass, respectively. The results suggested that grazing intensity changed biomass allocation pattern between aboveground and belowground parts of plants. Higher grazing intensity resulted in higher N concentration in both live and dead aboveground biomass over the study period. Increased grazing intensity tended to increase plant N content averaged over all sampling dates, which were 17.9 g m(-2), 23.8 g m(-2) and 27.6 g m(-2) in LG site, MG site and HG site. The results indicated that higher grazing intensity had a potential to increase the ecosystem pool of plant N

Dietary Inflammatory Index and Its Association with the Prevalence of Coronary Heart Disease among 45,306 US Adults

Inflammation plays a pivotal in the occurrence and development of coronary heart disease (CHD). We aim to investigate the association between the Dietary Inflammatory Index (DII) and CHD in the present study. In this cross-sectional study, adult participants from the National Health and Nutrition Examination Survey (NHANES) (1999–2018) were enrolled. The social demographic information, lifestyle factors, blood biochemical measurements, dietary information, and CHD status of all the participants were systematically collected. Multivariable logistic regression was adopted to investigate the association between the risk of CHD and the DII. Besides, restricted cubic spline (RCS) analysis was used to explore whether there was a nonlinear association of the DII and CHD. Subgroup analysis stratified by sex, age, race/ethnicity, and BMI was conducted to evaluate the association of the DII and CHD among different populations. A total of 45,306 adults from NHANES (1999–2018) were included. Compared with individuals without CHD, the DIIs of the participants with CHD were significantly elevated. A positive association was observed between the DII and CHD in multivariable logistic analysis after adjusting for age, sex, race/ethnicity, education levels, smoking, drinking, diabetes, hypertension, and body mass index (BMI). Results of RCS analysis suggested a nonlinear relationship between the DII and CHD. In addition, the increment of the DII had a greater impact on female individuals compared with male individuals. The DII is closely associated with the risk of CHD. For better prevention and treatment of CHD, more attention should be paid to controlling dietary inflammation

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

In order to increase the reliability and service life of piston in a heavy-duty diesel engine, the geometric structure of piston was optimized based on its maximum temperature and maximum coupling stress. To begin with, the boundary conditions of thermal and stress fields are calculated, which include the heat produced by the combustion in cylinder, the friction-induced heat, and the heat transferred to cooling system. Then, the finite element model was established to calculate and analyse the temperature and thermal-mechanical coupling stress fields of the piston. By combining this simulation model with orthogonal experimental design methods, computations and analyses were performed to determine how the five geometric parameters (depth of intake and exhaust valve grooves, radius of valve grooves transition, radius of top of valve grooves, height of first piston ring groove, and depth of piston ring groove) influence the two evaluation indicators (maximum temperature and maximum stress of piston). Subsequently, using the proposed ABC-OED- FE (artificial bee colony, orthogonal experiment design, and fitting equations) method, the fitting equations between the geometric parameters and evaluation indicators were determined. Taking the minimum values of two evaluation indicators of piston as optimization objectives, artificial bee colony method was run to determine the values of parameters. At last, the two evaluation indicators of the optimized piston were computed. The results indicate that, after optimization, the maximum temperature of piston decreases to be 16.05 K and the maximum stress decreases to be 13.54 MPa. Both temperature and stress conditions of the optimized piston had been improved, which demonstrates the effectiveness of the optimization and the validity of the algorithm

Clinical Research of Status Epilepticus: a report of 224 cases

Objective: To study the clinical efficacy of midazolam in the treatment of 224 patients with status epilepticus (SE). Methods: A total of 224 patients with status epilepticus (SE) admitted in our hospital from October, 2010 to October, 2013 were selected and randomly divided into midazolam group (n ＝ 144) and combination group (tranquillizer ＋ phenobarbital) (n ＝ 80). 0.1 - 0.2 mg/ kg of midazolam were slowly given to midazolam group for 5 - 10 min while 0.3 - 0.5 mg/ kg of diazepam and 5 - 10 mg/kg of phenobarbital were intramuscularly injected to patients in combination group. Results: SE’s time was significantly controlled in midazolam group than in combination group, while it was suggested that SE children’s age, etiology, incentives, seizure type, EEG, imaging changes were independent with the short-term efficacy of SE patients (P > 0.05), and the duration of attack, treatment programs and short-term efficacy of SE were correlated (P < 0.05), according to the analysis of age, etiology, incentives, seizure type, duration of attack, laboratory examinations, the relationship between treatment and curative effect. Conclusion: Midazolam is a new BZDs drug containing some special advantages when compared with traditional ones, which is also a favorable anti-epileptic drug with high safety and reliability, rapid onset, simple application and mild toxic responses