Novel manufacturing process of pneumococcal capsular polysaccharides using advanced sterilization methods

Pneumococcal disease is caused by Streptococcus pneumoniae, including pneumonia, meningitis and sepsis. Capsular polysaccharides (CPSs) have been shown as effective antigens to stimulate protective immunity against pneumococcal disease. A major step in the production of pneumococcal vaccines is to prepare CPSs that meet strict quality standards in immunogenicity and safety. The major impurities come from bacterial proteins, nucleic acids and cell wall polysaccharides. Traditionally, the impurity level of refined CPSs is reduced by optimization of purification process. In this study, we investigated new aeration strategy and advanced sterilization methods by formaldehyde or β-propiolactone (BPL) to increase the amount of soluble polysaccharide in fermentation supernatant and to prevent bacterial lysis during inactivation. Furthermore, we developed a simplified process for the CPS purification, which involves ultrafiltration and diafiltration, followed by acid and alcohol precipitation, and finally diafiltration and lyophilization to obtain pure polysaccharide. The CPSs prepared from formaldehyde and BPL sterilization contained significantly lower level of residual impurities compared to the refined CPSs obtained from traditional deoxycholate sterilization. Finally, we showed that this novel approach of CPS preparation can be scaled up for polysaccharide vaccine production

Station-Free Bike Rebalancing Analysis: Scale, Modeling, and Computational Challenges

In the past few years, station-free bike sharing systems (SFBSSs) have been adopted in many cities worldwide. Different from conventional station-based bike sharing systems (SBBSSs) that rely upon fixed bike stations, SFBSSs allow users the flexibility to locate a bike nearby and park it at any appropriate site after use. With no fixed bike stations, the spatial extent/scale used to evaluate bike shortage/surplus in an SFBSS has been rather arbitrary in existing studies. On the one hand, a balanced status using large areas may contain multiple local bike shortage/surplus sites, leading to a less effective rebalancing design. On the other hand, an imbalance evaluation conducted in small areas may not be meaningful or necessary, while significantly increasing the computational complexity. In this study, we examine the impacts of analysis scale on the SFBSS imbalance evaluation and the associated rebalancing design. In particular, we develop a spatial optimization model to strategically optimize bike rebalancing in an SFBSS. We also propose a region decomposition method to solve large-sized bike rebalancing problems that are constructed based on fine analysis scales. We apply the approach to study the SFBSS in downtown Beijing. The empirical study shows that imbalance evaluation results and optimal rebalancing design can vary substantially with analysis scale. According to the optimal rebalancing results, bike repositioning tends to take place among neighboring areas. Based on the empirical study, we would recommend 800 m and 100/200 m as the suitable scale for designing operator-based and user-based rebalancing plans, respectively. Computational results show that the region decomposition method can be used to solve problems that cannot be handled by existing commercial optimization software. This study provides important insights into effective bike-share rebalancing strategies and urban bike transportation planning

Supplemental Material - Impacts of COVID-19 on Food Access: An Examination of People’s Food Shopping Methods Change

Supplemental Material for Impacts of COVID-19 on Food Access: An Examination of People’s Food Shopping Methods Change by Xueting Jin and Daoqin Tong in International Regional Science Review</p

Beijing Opera Synthesis Based on Straight Algorithm and Deep Learning

Speech synthesis is an important research content in the field of human-computer interaction and has a wide range of applications. As one of its branches, singing synthesis plays an important role. Beijing Opera is a famous traditional Chinese opera, and it is called Chinese quintessence. The singing of Beijing Opera carries some features of speech but it has its own unique pronunciation rules and rhythms which differ from ordinary speech and singing. In this paper, we propose three models for the synthesis of Beijing Opera. Firstly, the speech signals of the source speaker and the target speaker are extracted by using the straight algorithm. And then through the training of GMM, we complete the voice control model to input the voice to be converted and output the voice after the voice conversion. Finally, by modeling the fundamental frequency, duration, and frequency separately, a melodic control model is constructed using GAN to realize the synthesis of the Beijing Opera fragment. We connect the fragments and superimpose the background music to achieve the synthesis of Beijing Opera. The experimental results show that the synthesized Beijing Opera has some audibility and can basically complete the composition of Beijing Opera. We also extend our models to human-AI cooperative music generation: given a target voice of human, we can generate a Beijing Opera which is sung by a new target voice

A Real-Time Energy Consumption Simulation and Comparison of Buildings in Different Construction Years in the Olympic Central Area in Beijing

Energy consumed the in urban sector accounts for a large proportion of total world delivered energy consumption. Residential building energy consumption is an important part of urban energy consumption. However, there are few studies focused on this issue and that have simulated the energy consumption of residential buildings using questionnaire data. In this research, an eQUEST study was conducted for different residential buildings in the Olympic Central Area in Beijing. Real-time meteorological observation data and an actual energy consumption schedule generated by questionnaire data were used to improve the eQUEST model in the absence of actual energy consumption data. The simulated total energy consumption of residential buildings in the case area in 2015 is 21,262.28 tce, and the average annual energy consumption per unit area is 20.09 kgce/(m2·a). Space heating accounted for 45% of the total energy consumption as the highest proportion, and the second highest was household appliances, which accounted for 20%. The results showed that old residential buildings, multi-storey buildings and large-sized apartment buildings consume more energy. The internal units, building height, per capita construction area, the number of occupants and length of power use had significant impact on residential energy consumption. The result of this study will provide practical reference for energy saving reconstruction of residential buildings in Beijing

Factors Controlling Urban and Rural Indirect Carbon Dioxide Emissions in Household Consumption: A Case Study in Beijing

Residential carbon dioxide emissions can be divided into a direct component caused by consumers via direct energy usage and an indirect component caused by consumers buying and using products to meet their needs, with a higher proportion caused by the latter. Based on Beijing panel data for 1993&ndash;2012, an economic boom period in China, indirect carbon dioxide emissions were separately calculated for urban and rural households using the consumer lifestyle approach (CLA) model. Then, an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model was used to analyze the influence from two aspects, social economy, and land use, with high precision. Results indicate that indirect CO2 emissions in Beijing households display a rising trend in urban areas but a slight decrease in rural areas. Technology influences and forest land are, respectively, the most important aspects of the social economy and land use. Higher population and urbanization resulted in enhanced emissions in both urban and rural areas. The Engel coefficient presented a negative correlation with indirect CO2 emissions for both rural and urban areas. Compared with urban areas, the per capita net income of rural areas restrained consumption. The consumption structure of urban residents was more biased toward the tertiary industry than that of rural residents. Although technical progress has proceeded, it cannot offset urban residents&rsquo; indirect CO2 emissions caused by the large amount and rapid growth of consumption. Regarding land use, urban construction land net primary productivity (NPP) was high and not an important factor contributing to indirect CO2 emissions. Forest and lawn primarily served a recreational function and exhibited a positive impact. Water and cultivated land offered insufficient production and thus had a negative influence. For rural residents, lawn and cultivated land production is self-sufficient. Forests offer a carbon sequence effect, and construction land expansion increased the proportion of developed area, offering a scale effect that resulted in reduced carbon emissions. Based on the results, alternative carbon emission reduction policies have been proposed for each tested influence aspect to reduce emissions, including policies for optimizing industrialization quality, constructing a medium-density city, increasing space efficiency, encouraging sustainable consumption behavior, and increasing the efficiency of energy utilization

Assessment of municipal infrastructure development and its critical influencing factors in urban China: A FA and STIRPAT approach.

Municipal infrastructure is a fundamental facility for the normal operation and development of an urban city and is of significance for the stable progress of sustainable urbanization around the world, especially in developing countries. Based on the municipal infrastructure data of the prefecture-level cities in China, municipal infrastructure development is assessed comprehensively using a FA (factor analysis) model, and then the stochastic model STIRPAT (stochastic impacts by regression on population, affluence and technology) is examined to investigate key factors that influence municipal infrastructure of cities in various stages of urbanization and economy. This study indicates that the municipal infrastructure development in urban China demonstrates typical characteristics of regional differentiation, in line with the economic development pattern. Municipal infrastructure development in cities is primarily influenced by income, industrialization and investment. For China and similar developing countries under transformation, national public investment remains the primary driving force of economy as well as the key influencing factor of municipal infrastructure. Contribution from urbanization and the relative consumption level, and the tertiary industry is still scanty, which is a crux issue for many developing countries under transformation. With economic growth and the transformation requirements, the influence of the conventional factors such as public investment and industrialization on municipal infrastructure development would be expected to decline, meanwhile, other factors like the consumption and tertiary industry driven model and the innovation society can become key contributors to municipal infrastructure sustainability

Correction: Assessment of municipal infrastructure development and its critical influencing factors in urban China: A FA and STIRPAT approach.

[This corrects the article DOI: 10.1371/journal.pone.0181917.]