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Aims: This study aims to provide representative information on heart failure (HF) patients in China, especially older adults aged ≥75 years. We aim to clarify the age‐related discrepancies in performance measures and the modifying effect of age on the impact of HF patients' characteristics on clinical outcomes. Methods and results: All HF patients admitted into five tertiary and four secondary hospitals of the Capital Medical University were divided into two groups according to age: 1419 (53.3%) were <75 years, and 1244 (46.7%) were ≥75 years. Older HF patients were more likely to be women, with higher left ventricular ejection fraction, with co‐morbidities including chronic obstructive pulmonary disease/asthma, anaemia, chronic kidney disease, stroke/transient ischemic attack (TIA), atrial fibrillation/atrial flutter, hypertension, and coronary artery disease, while obesity, diabetes mellitus, hypercholesterolaemia and valvular heart disease were more prevalent among younger HF patients. Left ventricular ejection fraction assessment was performed in a similar proportion of patients in the younger and older groups (81.7% vs. 80.5%, P = 0.426), while B‐type natriuretic peptide/N terminal pro brain natriuretic peptide was tested in a lower proportion in the younger group (84.8% vs. 89%, P = 0.001). At discharge, HF with reduced ejection fraction patients were less likely to receive beta‐blockers, angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers, or combined beta‐blockers and angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers therapy in the older group (49.74% vs. 63.2%, P = 0.002; 52.9% vs. 64.7%, P = 0.006; and 28.57% vs. 45.5%, P < 0.001, respectively) but were equally likely to receive mineralocorticoid receptor antagonists in the two age groups (80.8% vs. 84.1%, P = 0.322). Older patients with HF had higher risk of in‐hospital and 1 year mortality (2.7% vs. 1.3%, P = 0.011; 21.7% vs. 12.5%; P < 0.001, respectively). Higher body mass index was associated with better outcomes in both age groups. New York Heart Association functional class IV and estimated glomerular filtration rate < 60 mL/min/1.73 m2 were independent predictors of 1 year mortality. The associations between patients' characteristics and risk of mortality were not modified by age. Conclusions: HF patients aged ≥75 years had distinct clinical profiles, received worse in‐hospital therapies and experienced higher in‐hospital and 1 year mortality. [ABSTRACT FROM AUTHOR]

Background: Langerhans cell histiocytosis (LCH) is a myeloid dendritic cell disorder frequently affecting children more than adults. The presentation of LCH varies with age, however, the clinical characteristics and genetic profiles of adolescent LCH remain elusive. To address the knowledge gap, we performed a single-centre retrospective study of 36 adolescent LCH patients aged between 14 and 17 years at Peking Union Medical College Hospital.Results: At the time of diagnosis, 10 patients were classified as unifocal single system LCH (27.8%), 2 patients had pulmonary single system LCH (5.6%), 5 patients had multifocal single system LCH with bone involvement (13.9%), and 19 patients had multisystem LCH (52.8%). The most prevalent involvement in multisystem patients was the pituitary gland (78.9%), followed by the bone (42.1%), lung (42.1%), and lymph nodes (42.1%). Eight (42.1%) patients had risk organ involvement. BRAFN486_P490 was detected in 50% of patients who underwent next generation sequencing, and BRAFV600E was detected in one patient. Chemotherapies were the first line treatment in 24 patients. One patient died and thirteen patients relapsed during the follow-up. The estimated 5-year OS rate and EFS rate were 94.7% and 59.0%, respectively.Conclusions: In this study, we report a large series of adolescent LCH patients. The clinical characteristics of adolescent LCH patients may be close to adult LCH. Compared with pediatric cases, adolescent LCH tends to have more pituitary lesions and pulmonary involvement, fewer skin and hematopoietic involvement, a higher frequency of BRAF deletion mutation, and a lower frequency of BRAFV600E mutation. [ABSTRACT FROM AUTHOR]

The production of Chinese chives is reduced throughout China due to a root-feeding dipteran pest Bradysia odoriphaga Yang et Zhang (Diptera: Sciaridae), therefore deciphering the conditions influencing its growth and development are important in developing ecological control strategies. A study was conducted from 2014 to 2017 to determine the relationship between the abundance of B. odoriphaga and temperature (atmospheric and soil), soil water content, and atmospheric humidity in a Chinese chive field in Beijing City, China. Numbers of adults peaked in March and October to November and were lowest in July to August and December to next February; numbers of larvae were highest in December to next February and lowest in July to August. From 2014 to 2017, the numbers of adults and larvae were significantly correlated with monthly mean atmospheric temperatures and soil temperatures, but were not significantly correlated with monthly mean atmospheric relative humidity and soil water content. However, for both adults and larvae, numbers were significantly greater with high soil water contents compared with drought treatment. The results of this study suggest that the very low soil water contents, high atmospheric temperatures, and high soil temperatures were critical for regulating field populations of B. odoriphaga. [ABSTRACT FROM AUTHOR]

Although ride sharing as a way to improve transportation efficiency is not new, the scale of ride sharing has historically been limited due to safety concerns and logistics challenges. Recent developments in information and communications technology (ICT) enable real-time sharing of individual geographical information, allow for easier participation in the "sharing economy", and present opportunities for implementing ride sharing at a large-scale. This research aims to quantify the environmental benefits of ride sharing using shared taxis in Beijing as a case study. Trip information extracted from vehicle trajectory data of 12,083 taxis in Beijing are used to evaluate the benefits of ride sharing. Our results show that: 1) only limited opportunity cost to the rider (i.e. tolerance of early departure or delayed arrival) can enable large-scale ride sharing; 2) at a tolerance level of 10 min, ride sharing can reduce fleet vehicle-miles-traveled (VMT) by 33%; and 3) if implemented for the entire taxi fleet, shared taxis can save 28.3 million gallons of gasoline and reduce 186 tons VOC, 199 tons NOx, 53 tons PM 10 , 25 tons PM 2.5 , and 2392 tons CO emissions annually. • Wide adoption of smart phones and apps enable large-scale dynamic ride sharing. • This study quantifies the environmental benefits of taxi ride sharing in Beijing. • If riders can tolerate a travel time change of 10 min, 33% of the VMT can be saved. • Shared taxis can also reduce energy consumption and vehicular air pollution. [ABSTRACT FROM AUTHOR]

We propose an optimization model based on vehicle travel patterns to capture public charging demand and select the locations of public charging stations to maximize the amount of vehicle-miles-traveled (VMT) being electrified. The formulated model is applied to Beijing, China as a case study using vehicle trajectory data of 11,880 taxis over a period of three weeks. The mathematical problem is formulated in GAMS modeling environment and Cplex optimizer is used to find the optimal solutions. Formulating mathematical model properly, input data transformation, and Cplex option adjustment are considered for accommodating large-scale data. We show that, compared to the 40 existing public charging stations, the 40 optimal ones selected by the model can increase electrified fleet VMT by 59% and 88% for slow and fast charging, respectively. Charging demand for the taxi fleet concentrates in the inner city. When the total number of charging stations increase, the locations of the optimal stations expand outward from the inner city. While more charging stations increase the electrified fleet VMT, the marginal gain diminishes quickly regardless of charging speed. [ABSTRACT FROM AUTHOR]

Charging infrastructure is critical to the development of electric vehicle (EV) system. While many countries have implemented great policy efforts to promote EVs, how to build charging infrastructure to maximize overall travel electrification given how people travel has not been well studied. Mismatch of demand and infrastructure can lead to under-utilized charging stations, wasting public resources. Estimating charging demand has been challenging due to lack of realistic vehicle travel data. Public charging is different from refueling from two aspects: required time and home-charging possibility. As a result, traditional approaches for refueling demand estimation (e.g. traffic flow and vehicle ownership density) do not necessarily represent public charging demand. This research uses large-scale trajectory data of 11,880 taxis in Beijing as a case study to evaluate how travel patterns mined from big-data can inform public charging infrastructure development. Although this study assumes charging stations to be dedicated to a fleet of PHEV taxis which may not fully represent the real-world situation, the methodological framework can be used to analyze private vehicle trajectory data as well to improve our understanding of charging demand for electrified private fleet. Our results show that (1) collective vehicle parking “hotspots” are good indicators for charging demand; (2) charging stations sited using travel patterns can improve electrification rate and reduce gasoline consumption; (3) with current grid mix, emissions of CO 2 , PM, SO 2 , and NO x will increase with taxi electrification; and (4) power demand for public taxi charging has peak load around noon, overlapping with Beijing’s summer peak power. [ABSTRACT FROM AUTHOR]

To enhance the energy saving, emission reduction, and economic feasibility of battery swapping stations (BSSs), this paper develops a BSS configuration and operation model with three charging strategies for Beijing. The model dynamically and holistically analyzes the configuration of chargers, swappers, and reserve batteries, as well as the different annual battery rental fees of BSSs to satisfy the battery swapping demand of users and enhance the profitability of BSSs. The simulation results show that the valley charging strategy can achieve the lowest peak-valley grid load difference (reducing the peak-valley load difference by 156.02 MW) and the greatest emission reductions (2,683,078.49 tons). However, higher investments in reserve batteries and chargers are required to enable service of all demands through valley charging. Based on the current technology, policy, and BSS plan, the BSSs cannot be profitable regardless of their charging strategies. The battery costs and the battery swapping price are the key factors that influence the life-cycle net income of BSSs. Business model innovation, such as charging taxi companies an annual battery rental fee (in the range of 10,300 to 12,160 yuan per battery), can help improve the financial feasibility of the BSSs. • Propose a system dynamics model to improve BSSs' environmental and economic effects. • The model includes five modules and evaluates three charging strategies. • Valley charging can reduce the peak-valley load difference by 156.02 MW. • Charging an annual battery rental fee of at least 12,160 yuan per battery can make BSS profitable. • Policy suggestions are made for battery swapping station development in Beijing. [ABSTRACT FROM AUTHOR]

The choice of battery range (all-electric driving range) for battery electric vehicles (BEVs) is an important issue for both BEV adopters and BEV makers. This paper proposes a model to identify the minimum BEV battery range that can satisfy given travel demands, considering the opportunities to charge at existing public charging stations and the uncertainties in charging decision making. We conducted a stated preference survey to study the charging decision making and analyzed the data using the Latent Class model to generate the model coefficients for charging decisions making. The proposed approach can better identify the needed battery range than the often-used simplified charging rules. We applied the model to a case study of Beijing to evaluate the needed battery range for taxis and private vehicles. For taxis, BEVs with 220-mile battery range are able to satisfy the travel demands for about 90% of the drivers. For private vehicles, a 300-mile range is needed to cover the travel demands of 90% of the drivers, while a 100-mile range battery is able to satisfy the need for 80% of the private drivers. Simplified charging rules tend to underestimate the range needs for taxis but overestimate the range needs for private vehicles. Image 1 • Proposed a Battery Range Optimization Model (BROM). • Integrated heterogeneous charging behaviors into battery range optimization. • Evaluated the battery range needs for taxis and private vehicles in Beijing as case studies. • Simple charging rules may lead to overestimated battery needs for taxis. • Simple charging rules may lead to underestimated battery range needs for private vehicles. [ABSTRACT FROM AUTHOR]