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The presence of T2-Al2MgC2 compound has significant influence on the mechanical properties of magnesium alloys. The mechanical, electronic and dynamical properties of T2-Al2MgC2 under high pressure are investigated by plane wave pseudopotential method based on the first-principles calculation. The results show that T2-Al2MgC2 is mechanically stable under high pressure, the elastic constants except C 1 4 increase with the increase of pressure. This compound presents brittleness and the brittleness decreases with increasing pressure when P < 4 0 GPa, but it displays ductility when P > 4 0 GPa. T2-Al2MgC2 has strong anisotropy, and the anisotropy decreases with increasing pressure. T2-Al2MgC2 is an indirect bandgap semiconductor material. Our calculated bandgap is 1.893 eV at ambient pressure, the bandgap first increases and then decreases with increasing pressure. The phonon band structure as well as the total and partial phonon density of the state under different pressures had been analyzed. The constant volume heat capacity C V and entropy S of T2-Al2MgC2 increase with increasing pressure. [ABSTRACT FROM AUTHOR]

Background: Chronic obstructive pulmonary disease (COPD) management in China is far from adequate; underdiagnosis and undertreatment are major barriers to optimal care and improved patient outcomes. Objective: To generate reliable information on COPD management, outcomes, treatment patterns and adherence, and disease knowledge in China in a real-world setting. Design: A 52-week multicentre, prospective, observational study. Methods: Outpatients (⩾40 years old) diagnosed with COPD were enrolled from 50 secondary and tertiary hospitals across six geographical regions. Data were collected in routine clinical practice. Results: Between June 2017 and January 2019, 5013 patients were enrolled and 4978 included in the analysis. Mean [standard deviation (SD)] age was 66.2 (8.9) years, 79.5% were male and 90% had moderate-to-very-severe airflow limitation. Annual rates of overall and severe exacerbation were 0.56 and 0.31, respectively. During 1 year, 1536 (30.8%) patients experienced ⩾1 exacerbation and 960 (19.3%) patients had ⩾1 exacerbation requiring hospitalization/emergency visit. Mean (SD) COPD assessment test score was 14.6 (7.6) at baseline and 10.6 (6.8) at follow-up; however, 42–55% of patients had persistent dyspnoea, chest tightness and wheezing at 1 year. The most prescribed treatments were inhaled corticosteroid (ICS)/long-acting β2-agonist (LABA) (36.0%), ICS/LABA + long-acting muscarinic antagonist (LAMA) (17.7%) and LAMA monotherapy (15.3%). Among patients with high exacerbation risk (GOLD Groups C and D), 10.1% and 13.1%, respectively, did not receive any long-acting inhalers; only 53.8% and 63.6% of Group C and D patients with ⩾1 exacerbation during follow-up were prescribed ICS-containing therapy, respectively. Mean (SD) adherence for long-acting inhalers was 59.0% (34.3%). Mean (SD) score for the COPD questionnaire was 6.7 (2.4). Conclusion: These results indicate a high burden of severe exacerbations and symptoms in Chinese outpatients with COPD, and low adherence with treatment guidelines, highlighting the need for more effective management nationwide. Registration: The trial was registered on 20 March 2017 (ClinicalTrials.gov identifier: NCT03131362). Plain language summary: The current state of chronic obstructive pulmonary disease management in China Background: Chronic obstructive pulmonary disease is a chronic inflammatory lung disease characterized by progressive and irreversible airflow limitation. The disease is poorly managed in China, and many patients do not receive a diagnosis or appropriate treatment. Inadequate treatment can cause a 'flare up' of symptoms, known as exacerbation, which reduces a patient's quality of life and increases the risk of hospitalization and death. Objective: This study aimed to generate reliable, nationally representative information on the current status of chronic obstructive pulmonary disease management in China to help inform future management strategies. Study Design and Methods: Patients aged ⩾40 years with a diagnosis of chronic obstructive pulmonary disease were eligible for this study. Patients were enrolled from 50 hospitals across 6 regions of China, and their physicians collected study data during routine outpatient visits over the course of 1 year. Results: Of the 4978 patients included in this study, 90% had moderate-to-very-severe airflow limitation. A substantial proportion of patients had exacerbations (31%), with a large number being admitted to the hospital for treatment or visiting the emergency department (19%). About half of the patients had persistent symptoms related to the disease, including shortness of breath, chest tightness and wheezing. Some patients were prescribed long-acting inhaled treatments that are recommended to help prevent exacerbations. However, there were patients who were not prescribed any long-acting inhalers despite having a high risk of exacerbation. Moreover, patients prescribed long-acting inhalers only used their inhalers 59% of the time. Overall, patients' knowledge of the disease was poor. Conclusion: Chinese patients with chronic obstructive pulmonary disease are substantially impacted by exacerbations and chronic symptoms, and do not always receive appropriate treatment. The results from this study emphasize the need for more effective management across the country. [ABSTRACT FROM AUTHOR]

This paper considers how an online food delivery platform can improve last-mile delivery services' performance using multi-source data. The delivery time is one critical but uncertain factor for online platforms that also regarded as the main challenges in order assignment and routing service. To tackle this challenge, we propose a data-driven optimization approach that combines machine learning techniques with capacitated vehicle routing optimization. Machine learning methods can provide more accurate predictions and have received increasing attention in the operations research field. However, different from the traditional predict-then-optimize paradigm, we use a new smart predict-then-optimize framework, whose prediction objective is constructed by decision error instead of prediction error when implementing machine learning. Using this type of prediction, we can obtain a more accurate decision in the following optimization step. Efficient mini-batching gradient and heuristic algorithms are designed to solve the joint order assignment and routing problem of last-mile delivery service. Besides, this paper considers the mutual effect between routing decision and delivery time, and provides the corresponding solution algorithm. In addition, this paper conducts a computational study and finds that the proposed method's performance has an approximate 5% improvement compared with other methods. [ABSTRACT FROM AUTHOR]