The current 2019 coronavirus disease (COVID-19) pandemic is hitting citizen’s life and health like never before, with its significant loss to human life and a huge economic toll. In this case, the fever clinics (FCs) were still preserved as one of the most effective control measures in China, but this work is based on experience and lacks scientific and effective guidance. Here, we use travel time to link facilities and populations at risk of COVID-19 and identify the dynamic allocation of patients’ medical needs, and then propose the optimized allocation scheme of FCs. We selected Shenzhen, China, to collect geospatial resources of epidemic communities (ECs) and FCs to determine the ECs’ cumulative opportunities of visiting FCs, as well as evaluate the rationality of medical resources in current ECs. Also, we use the Location Set Covering Problem (LSCP) model to optimize the allocation of FCs and evaluate efficiency. Firstly, we divide the current ECs into 3 groups based on travel time and cumulative opportunities of visiting FCs within 30 min: Low-need communities (22.06%), medium-need communities (59.8%), and high-need communities (18.14%) with 0,1–2 and no less than 3 opportunities of visiting FCs. Besides, our work proposes two allocation schemes of fever clinics through the LSCP model. Among which, selecting secondary and above hospitals as an alternative in Scheme 1, will increase the coverage rate of hospitals in medium-need and high-need communities from 59.8% to 80.88%. In Scheme 2, selecting primary and above hospitals as an alternative will increase the coverage rate of hospitals in medium-need and high-need communities to 85.29%, with the average travel time reducing from 22.42 min to 17.94 min. The optimized allocation scheme can achieve two objectives: a. equal access to medical services for different types of communities has improved while reducing the overutilization of high-quality medical resources. b. the travel time for medical treatment in the community has reduced, thus improving medical accessibility. On this basis, during the early screening in prevention and control of the outbreak, the specific suggestions for implementation in developing and less developed countries are made.

Root system architecture (RSA) plays a crucial role in nutrient and water uptake in plants. RSA can be modulated to improve nitrogen use efficiency (NUE) of crops, decreasing the need for fertilization. In this study, we analyzed 12 root parameters in 48 Arabidopsis accessions grown in media with low or high nitrogen (N). Low N repressed six root traits and enhanced six others. A principal component analysis showed that six components contributed to 90.08% of N availability. The primary component contributed to 35.64% of the variation and was associated with LR characteristics. The 48 Arabidopsis accessions were divided into five response groups. Stw-0 had the highest biomass production and a high N concentration in both roots and shoots, independent of growth conditions. H55 had numerous LRs at low N. Our results provide N-responsive parameters suitable for mapping of quantitative trait loci related with root morphology.

Express delivery volume is an important indicator of intercity e-commerce trading activities, offering a new vision for glimpsing the intercity linkages. However, it has been a challenge to reveal the spatial distribution of intercity express flows due to the limitations on the use of express parcel data by most companies. The study maps the spatial pattern of intercity express connection intensity and identifies the urban centrality, supported by waybill data from China. Intercity express connections form a triangular corridor centred on the ‘Pearl River Delta–Yangtze River Delta–Beijing-Tianjin-Hebei’ urban agglomerations. Shenzhen, Guangzhou, Jinhua, Shanghai, Beijing, Quanzhou, Xingtai, etc., exhibit higher centrality for their strong consumption power or commodity production capacity. These cities also develop relatively strong connections with national central cities (Chengdu, Chongqing, Wuhan, Tianjin, etc.) and provincial capitals (Changsha, Urumqi, Hulun Buir, etc.). The cities on the western side of the Hu-line present low centrality and weak connections with the eastern cities and form sub-network with the provincial capital cities as the core.

The rapid growth of e-commerce has contributed to the booming distribution demand in rural areas but has also exposed the shortcomings of the lack of terminal facilities. The village-level pickup points (VPPs) and frequency of delivery represent among the most popular solution. In the plateau and mountainous areas where natural disasters are frequent, VPPs have been further advocated should undertake the emergency reserve and rescue function. However, optimally deploying facilities with peacetime and emergency demands remains challenging because of unique demand characteristics. This study presents a joint optimization model to determine the optimal parcel delivery periodic location-routing and prepositioned disaster response facilities location to fill the gap. The model considers the flexible choice of parcel delivery dates and the severity of natural disasters, integrates the objectives of delivery service economy (minimizing cost) and emergency response timeliness (minimizing maximum weighted travel risk). The developed model was applied to an empirical study of a rural township in Qingchuan county, Sichuan, which aimed to demonstrate its effectiveness and replicability. This study will help the plateau and mountainous public sector make informed decisions in assisting parcel delivery network design and rescue resource deployment.

Rural areas often lack convenient delivery logistics services, which has become a major obstacle to their economic development. Network design initiatives that synergize passenger and freight transport have been identified as effective solutions to address this challenge. Building upon this initiative, this study investigates a novel three-echelon location-routing problem that synergizes trucks and fixed-route buses (3E-LRP-TF). The model is designed with an innovative operational mode that enables fixed-route buses and trucks to travel in a parallel manner, representing a valuable extension to traditional integrated passenger–freight distribution network design. A mixed-integer nonlinear programming model with the objective of minimizing the total network cost is constructed to formulate the problem. Furthermore, a bottom-up three-phase adaptive large neighborhood search (ALNS) algorithm is designed to solve the problem. A final empirical study was conducted, with Qingchuan County in China serving as a case study, with the aim of validating the effectiveness of the proposed model and algorithm. The results show that, compared with using trucks alone, the synergistic network system has the potential to reduce costs by more than 5% for parcel pickup and delivery services. The proposed algorithm can address larger-scale problems and exhibits better performance with regard to solution quality and efficiency. Sensitivity analysis indicates that the parcel transport capacity of bus routes exerts a nonlinear effect on total costs, and changes in service radius result in trade-offs between cost and accessibility. These findings provide actionable insights for policymakers and logistics operators.