Facile preparation and strong adhesive strength of honeycomb polyurethane films with small pore diameter

With the continuous development of bionics, such as, geckos and virginia creeper with both superhydrophobic and super-adhesive, the surface wetting and super-adhesive properties of various porous materials have attracted extensive attention of the scientific and medical communities. Here, the honeycomb polyurethane (PU) porous films with strong adhesion were successfully prepared by microphase separation method and the effects of growth parameters on their microstructure and adhesive strength to ice were investigated. It was found that a high relative humidity (e.g., 100%) and a low solution concentration (e.g., 2%) facilitated the formation of ordered honeycomb PU porous films, and as-prepared PU pores with average pore diameter as small as 5 μm are better ordered and more uniform than these in related documents. Although the contact angle of water droplets on the surface of PU porous films increased from the premodification value of 85–130° to more than 160° after surface modification with polydopamine (PDA), the corresponding rolling angle remained approximately constant (180°), indicating that the surface of PU porous films has strong adhesion similar to geckos and virginia creeper. Furthermore, at lower temperature, the PU porous films exhibited the high adhesive strength of 142.13 kPa on ice, which was strongly dependent on the porous microstructures and surface compositions. The improved adhesive behavior to ice of honeycomb PU porous films modified with PDA provides new strategies for surface modification of materials and potential applications in medical domain.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

A Case Report of Germline Compound Heterozygous Mutations in the BRCA1 Gene of an Ovarian and Breast Cancer Patient

The germline carrier of the BRCA1 pathogenic mutation has been well proven to confer an increased risk of breast and ovarian cancer. Despite BRCA1 biallelic pathogenic mutations being extremely rare, they have been reported to be embryonically lethal or to cause Fanconi anemia (FA). Here we describe a patient who was a 48-year-old female identified with biallelic pathogenic mutations of the BRCA1 gene, with no or very subtle FA-features. She was diagnosed with ovarian cancer and breast cancer at the ages of 43 and 44 and had a strong family history of breast and gynecological cancers.     

Multimodal sensing and active continuous closed‐loop feedback for achieving reliable manipulation in the outdoor physical world

The use of field robots can greatly decrease the amount of time, effort, and associated risk compared to if human workers were to carryout certain tasks such as disaster response. However, transportability and reliability remain two main issues for most current robot systems. To address the issue of transportability, we have developed a lightweight modularizable platform named AeroArm. To address the issue of reliability, we utilize a multimodal sensing approach, combining the use of multiple sensors and sensor types, and the use of different detection algorithms, as well as active continuous closed‐loop feedback to accurately estimate the state of the robot with respect to the environment. We used Challenge 2 of the 2017 Mohammed Bin Zayed International Robotics Competition as an example outdoor manipulation task, demonstrating the capabilities of our robot system and approach in achieving reliable performance in the fields, and ranked fifth place internationally in the competition.     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Estimates of pollutant temporal and spatial variability in commercial buildings from the joint urban 2003 field experiments

In this paper, we report on the indoor concentrations from a suite of full-scale outdoor tracer-gas point releases conducted in the downtown area of Oklahoma City in 2003. A point release experiment consisted of releases of sulfur hexafluoride (SF₆) in multiple buildings and from different outdoor locations. From the measurements, we are able to estimate the concentration variations indoors for a building operating under “typical” operating conditions. The mean indoor spatial coefficients of variation are 30% to 45% from a daytime outdoor release are around 80% during an outdoor evening release. Having estimates of the spatial coefficient of variation provides stakeholders, including first responders, with the likely range of concentrations in the building when little is known about the building characteristics and operating behavior, such as developing urban-scale hazard and consequence analyses. We show differences in indoor measurements at different distances to the release points, floors of the building, and heating, ventilation, and air conditioning system (HVAC) operation. We also show estimates at different time resolutions. The statistics show that in the studied medium to large commercial buildings, spatial differences would result in peak indoor concentrations in certain parts of the buildings that may be substantially higher than the building average. To our knowledge, very few tracer gas measurements have been conducted in buildings of this scope, particularly with measurements on multiple floors and within a floor. The resulting estimates of spatial variability provide a unique opportunity for hazard assessment, and comparison to multi-zone models.