Supply chains create global benefits from improved vaccine accessibility

Ensuring a more equitable distribution of vaccines worldwide is an effective strategy to control global pandemics and support economic recovery. We analyze the socioeconomic effects - defined as health gains, lockdown-easing effect, and supply-chain rebuilding benefit - of a set of idealized COVID-19 vaccine distribution scenarios. We find that an equitable vaccine distribution across the world would increase global economic benefits by 11.7% ($950 billion per year), compared to a scenario focusing on vaccinating the entire population within vaccine-producing countries first and then distributing vaccines to non-vaccine-producing countries. With limited doses among low-income countries, prioritizing the elderly who are at high risk of dying, together with the key front-line workforce who are at high risk of exposure is projected to be economically beneficial (e.g., 0.9%~3.4% annual GDP in India). Our results reveal how equitable distributions would cascade more protection of vaccines to people and ways to improve vaccine equity and accessibility globally through international collaboration

Genetic algorithm optimization for storing arbitrary multimode transverse images in thermal atomic vapor

Storing multimode transverse images in atomic media is crucial in constructing large-scale quantum networks. A major obstacle of storing transverse images in the thermal atomic vapor is the distortion of the retrieved images caused by atomic diffusion. Here, we demonstrate the combination of genetic algorithm with the phase-shift lithography method to construct the optimal phase for an arbitrary transverse image that can diminish the effect of diffusion. Theoretical simulations and experimental results manifest that the retrieved images' resolution can be substantially improved when carrying the optimal phases. Our scheme is efficient and straightforward and can be extensively applied in storing complex transverse multimodes in diffusion media

Vehicle Driving Data Collection and Analysis Based on GPRS

Abstract: In order to build China's typical urban vehicle driving cycle, this paper based on the GPRS wireless data acquisition system, through the on-board PDA collect data, the kinematics fragments after initial treatment can be got, and then use the principal component analysis and dynamic clustering method to partition the fragments, so as to build a vehicle driving cycle. The new driving cycle compares about driving characteristics with the foreign typical driving cycle, the results show that the time ratio of driving characteristics of acceleration and deceleration based on China's urban driving cycle above the time ratio of driving characteristics of acceleration and deceleration in EU, the time ratio of constant speed based on China's urban driving cycle under the time ratio in EU. Copyright © 2014 IFSA Publishing, S. L

Towards High-Safety Lithium-Ion Battery Diagnosis Methods

With the great development of new energy vehicles and power batteries, lithium-ion batteries have become predominant due to their advantages. For the battery to run safely, stably, and with high efficiency, the precise and reliable prognosis and diagnosis of possible or already occurred faults is a key factor. Based on lithium-ion batteries’ aging mechanism and fault causes, this paper summarizes the general methods of fault diagnosis at a macro level. Moreover, lithium-ion battery fault diagnosis methods are classified according to the existing research. Therefore, various fault diagnosis methods based on statistical analysis, models, signal processing, knowledge and data-driven are discussed in depth. Finally, the main challenges faced by fault diagnosis technology and future directions for possible research and development are put forward