A simple, highly sensitive method to detect leukemia cells has been developed based on aptamer-modified fluorescent silica nanoparticles (FSNPs). In this strategy, the amine-labeled Sgc8 aptamer was conjugated to carboxyl-modified FSNPs via amide coupling between amino and carboxyl groups. Sensitivity and specificity of Sgc8-FSNPs were assessed using flow cytometry and fluorescence microscopy. These results showed that Sgc8-FSNPs detected leukemia cells with high sensitivity and specificity. Aptamer-modified FSNPs hold promise for sensitive and specific detection of leukemia cells. Changing the aptamer may allow the FSNPs to detect other types of cancer cells.

The multipath effect and non-line-of-sight (NLOS) reception of global positioning system (GPS) signals both serve to degrade performance, particularly in urban areas. Although, receiver design continues to evolve, residual multipath errors and NLOS signals remain a challenge in built-up areas. It is therefore desirable to identify the direct, multipath-affected and NLOS GPS measurements in order improve ranging based position solutions. The traditional signal strength-based methods to achieve this, however, use a single variable (e.g. C/N0) as the classifier. Because the single variable does not completely represent the multipath and NLOS characteristics of the signals, the traditional methods are not robust in the classification of signal reception. This paper uses a set of variables derived from the raw GPS measurements together with an algorithm based on an adaptive neuro fuzzy inference system (ANFIS) to classify direct, multipath-affected and NLOS measurements from GPS. Results from real data show that the proposed method could achieve rates of correct classification of 100%, 91% and 84%, respectively, for the LOS, Multipath and NLOS based on a static test with special conditions results that are superior to the other three state-of-the-art signal reception classification methods.

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The rapid growth of air travel and aviation emissions in recent years has contributed to an increase in climate impact. Contrails have been considered one of the main factors of the aviation-induced climate impact. This paper deals with the formation of persistent contrails and its relationship with fuel consumption and flight time when flight altitude and true airspeed vary. Detailed contrail formation conditions pertaining to altitude, relative humidity and temperature are formulated according to the Schmidt–Appleman criterion. Building on the contrail formation model, the proposed model would minimise total travel time, fuel consumption and contrail length associated with a given flight. Empirical data (including pressure, temperature, relative humidity, etc.) collected from seven flight information regions in Chinese observation stations were used to analyse the spatial and temporal distributions of the persistent contrail formation area. The trade-off between flight time, fuel consumption and contrail length are illustrated with a real-world case. The results provided a valuable benchmark for flight route planning with environmental, flight time, sustainable flight trajectory planning and fuel consumption considerations, and showed significant contrail length reduction through an optimal selection of altitude and true airspeed.