Measuring Access to Medicines: A Survey of Prices, Availability and Affordability in Shaanxi Province of China

Objective: To measure the prices and availability of selected medicines in Shaanxi Province after the implementation of new healthcare reform in 2009. Methods: Data on the prices and availability of 47 medicines were collected from 50 public and 36 private sector medicine outlets in six regions of Shaanxi Province, Western China using a standardized methodology developed by the World Health Organization and Health Action International from September to October 2010. Medicine prices were compared with international reference prices to obtain a median price ratio. Affordability was measured as the number of days’ wages required for the lowest-paid unskilled government worker to purchase standard treatments for common conditions. Findings: The mean availabilities of originator brands and lowest-priced generics were 8.9% and 26.5% in the public sector, and 18.1% and 43.6% in the private sector, respectively. The public sector procured generics and originator brands at median price ratios of 0.75 and 8.49, respectively, while patients paid 0.97 and 10.16. Final patient prices for lowest-priced generics and originator brands in the private sector were about 1.53 and 8.36 times their international retail prices, respectively. Public sector vendors applied high markups of 30.4% to generics, and 19.6% to originator brands. In the private sector, originator brands cost 390.7% more, on average, than their generic equivalents. Generic medicines were priced 17.3% higher in the private sector than the public sector. The lowest-paid government worker would need 0.1 day’s wages to purchase captopril for lowest-priced generics from private sector, while 6.6 days’ wages for losartan. For originator brands, the costs rise to 1.2 days’ wages for salbutamol inhaler and 15.6 days’ wages for omeprazole. Conclusions: The prices, availability and affordability of medicines in China should be improved to ensure equitable access to basic medical treatments, especially for the poor. This requires multi-faceted interventions, as well as the review and refocusing of policies, regulations and educational interventions

MADiff: Offline Multi-agent Learning with Diffusion Models

Diffusion model (DM), as a powerful generative model, recently achieved huge success in various scenarios including offline reinforcement learning, where the policy learns to conduct planning by generating trajectory in the online evaluation. However, despite the effectiveness shown for single-agent learning, it remains unclear how DMs can operate in multi-agent problems, where agents can hardly complete teamwork without good coordination by independently modeling each agent's trajectories. In this paper, we propose MADiff, a novel generative multi-agent learning framework to tackle this problem. MADiff is realized with an attention-based diffusion model to model the complex coordination among behaviors of multiple diffusion agents. To the best of our knowledge, MADiff is the first diffusion-based multi-agent offline RL framework, which behaves as both a decentralized policy and a centralized controller, which includes opponent modeling and can be used for multi-agent trajectory prediction. MADiff takes advantage of the powerful generative ability of diffusion while well-suited in modeling complex multi-agent interactions. Our experiments show the superior performance of MADiff compared to baseline algorithms in a range of multi-agent learning tasks.Comment: 17 pages, 7 figures, 4 table

Adverse childhood experiences in patients with schizophrenia: related factors and clinical implications

The relationship between adverse childhood experiences (ACEs) and the development of psychotic symptoms is not well understood. Therefore, this study aimed to investigate the frequency and distribution of ACEs among patients with schizophrenia and their potential correlation with symptomatology and personality pathology. We conducted a cross-sectional study involving 571 patients with schizophrenia in Shanghai, China. Symptomatology was assessed using the Positive and Negative Symptoms Scale (PANSS) and personality pathology was assessed using the Personality Diagnostic Questionnaire Fourth Edition Plus (PDQ-4+). ACEs were assessed using the Child Trauma Questionnaire-Short Form (CTQ-SF). ACEs were highly prevalent, with 80.8% of the patients with schizophrenia reporting at least one ACE. The three most common types of ACE were physical neglect (69.8%), emotional neglect (28.2%), and emotional abuse (22.9%). For specific ACE, emotional abuse was significantly associated with PD traits, whereas emotional and physical neglect types of ACE was significantly associated with negative symptoms. A higher level of physical abuse was more commonly reported by men, younger individuals, and those with a higher level of antisocial PD traits. Higher levels of physical neglect were associated with more severe negative symptoms. ACEs are commonly observed in patients with schizophrenia. Therefore, it is strongly recommended that this clinical population be provided with a comprehensive assessment and individualized intervention for those exposed to specific ACEs

RITA: Boost Autonomous Driving Simulators with Realistic Interactive Traffic Flow

High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating traffic patterns that accurately reflect the various features of real-world data while also simulating human-like reactive responses to the tested autopilot driving strategies. Taking one step forward to addressing such a problem, we propose Realistic Interactive TrAffic flow (RITA) as an integrated component of existing driving simulators to provide high-quality traffic flow for the evaluation and optimization of the tested driving strategies. RITA is developed with consideration of three key features, i.e., fidelity, diversity, and controllability, and consists of two core modules called RITABackend and RITAKit. RITABackend is built to support vehicle-wise control and provide traffic generation models from real-world datasets, while RITAKit is developed with easy-to-use interfaces for controllable traffic generation via RITABackend. We demonstrate RITA's capacity to create diversified and high-fidelity traffic simulations in several highly interactive highway scenarios. The experimental findings demonstrate that our produced RITA traffic flows exhibit all three key features, hence enhancing the completeness of driving strategy evaluation. Moreover, we showcase the possibility for further improvement of baseline strategies through online fine-tuning with RITA traffic flows.Comment: 8 pages, 5 figures, 3 table

A guideline for economic evaluations of vaccines and immunization programs in China.

This study aimed to develop a consensus framework for economic evaluations of vaccines as a national guideline in China. Some unique and important aspects were particularly emphasized. Nineteen Chinese experts in the field of health economics and immunization decision-making were nominated to select and discuss relevant aspects of vaccine economic evaluations in China. A workshop attended by external experts was held to summarize unique and important aspects and formulate consensus recommendations. There were ten unique and/or important aspects identified for economic evaluations of vaccines in China, including study perspectives, comparator strategies, analysis types, model choices, costing approaches, utility measures, discounting, uncertainty, equity, and evaluation purposes. Background information and expert recommendations were provided for each aspect. Economic evaluations of vaccines should play an important role in China's immunization policy-making. This guideline can help improve the quality of economic evaluations as a good practice consensus

Migration from China to the EU: the challenge within Europe

At the beginning of the 21st Century, we have witnessed a rapid growth in Chinese immigration to the European Union (EU), which has had a profound impact on local Chinese communities in various ways. This chapter aims to reveal the latest developments in Chinese immigration in the EU, as well as the new dynamics, features and impacts on local Chinese communities. The above questions are addressed by a combination of secondary data analysis and our own observation in Italy and the UK in recent years. Some challenging issues facing Chinese communities are highlighted

Controlling Morphology and Aggregation in Semiconducting Polymers: The Role of Solvents on Lasing Emission in Poly[2-methoxy-5-(2′-ethyl-hexyloxy)-1,4-phenylene-vinylene]

Systematic experiments were performed to investigate solvent-dependent morphology and aggregation of the semiconducting polymer film poly[2-methoxy-5-(2′-ethyl-hexyloxy)-1,4-phenylene-vinylene] (MEH-PPV), which was span-cast from nonaromatic strong polarity solvents tetrahydrofuran (THF), trichloromethane (TCM) and aromatic weak polarity solvents chlorobenzene (CB), toluene, and p-xylene. The results indicated that the conformation of the spin-cast MEH-PPV films with weak aggregation such as THF and TCM demonstrated excellent lasing emission performances because of inhibiting the fluorescence quenching induced by bi-molecule process. The Atomic Force Microscope (AFM) images confirmed the distinct morphologies of the spin-cast MEH-PPV films. The amplified spontaneous emission (ASE) was investigated in a simple asymmetric slab planar waveguide structure by methods of variable stripe length (VSL) and shifting excitation stripe (SES). The amplified spontaneous emission (ASE) experiments confirmed the distinct polymer chain conformation. The conformation, which preserved from the spin-cast process, indicated the distinct interactions between solvents and MEH-PPV polymer chains. The pure film spectra were performed to confirm the effect of distinct conformation on the material energy level. This work provides insights into the morphology and aggregation effect of the spin-cast polymer films on the performances of lasers

Path Planning of Electric VTOL UAV Considering Minimum Energy Consumption in Urban Areas

As a new mode of transportation in the future, electric vertical take-off and landing unmanned aerial vehicles (eVTOL UAV) can undertake the task of logistics distribution and carry people in urban areas. It is challenging to carry out research designed to plan the path of eVTOL UAVs which can have a safe and sustainable operation mode in urban areas. Therefore, this work proposes a method for planning an obstacle-free path for eVTOL UAVs in urban areas with the goal of minimizing energy consumption. It aims to improve the safety and sustainability of eVTOL UAV operations. Based on variations of air density with height, a more accurate formula for calculating battery energy consumption of eVTOL UAV is derived. It is used in the vertical takeoff and landing phase and horizontal flight phase, respectively. Considering the influence of buildings on eVTOL UAV operation, a path planning method applicable to complex urban environments is proposed. The safe nodes of eVTOL UAV flight are obtained by using Voronoi diagrams based on building locations. Then, the complete shortest and obstacle-free path is obtained by using a Dubins geometric path and Floyd algorithm. After obtaining the obstacle-free paths for all flight height zones, the battery energy consumption of the eVTOL UAV in each flight height zone is calculated. Then, the flight height with the minimum energy consumption is obtained. The simulation results show that the path length obtained by the proposed path planning method is shorter than that obtained by particle swarm optimization; the total battery energy consumption changes in the same pattern in the low-altitude areas and high-altitude areas; the difference between the maximum and minimum energy consumption in the small area enables the eVTOL UAV to cover about 350 m more, and about 420 m more in the large area. Therefore, in future high-frequency UAV mission flights, choosing the altitude with the lowest energy consumption can reduce UAV operator costs. It can also significantly increase UAV transport range and make UAVs operate more sustainably