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A highly robust, durable, and flexible ion sensor was prepared by coating polymer membranes on porous carbon electrodes. The ion sensor realized the real-time analysis of human sweat.

Fluorescent carbon quantum dots are emerging as a new class of fluorescent probes due to their unique optical properties. Herein, we presented a simple, one-pot and effective preparation strategy for copper-functionalized carbon quantum dots (Cu-CDs). The Cu-CDs demonstrated excitation-independent emissions, high fluorescent quantum yield (~ 24.4%) and excellent fluorescent stability. The fluorescence of Cu-CDs could be quenched efficiently in the presence of histidine (His) due to the coordination occurring between surface Cu and imidazole side chains of His. Thus, the Cu-CDs could be used as an efficient fluorescent probe for His detection. Under optimal conditions, the fluorescent signals of Cu-CDs decreased linearly with the concentrations of His over a range of 0.1–15 µM. The detection limit was 30 nM. The proposed method provided obvious advantages of rapid response, convenience, simplicity, high selectivity and sensitivity. Moreover, good results also have been obtained for His detection in real biological fluid samples.

In view of the simplified superposition problem during the opinion leader identification process and it is difficult to form a system between identification and evaluation, this paper researches the opinion leader identification and reliability tracking method based on optimal synthesis. We propose an improved index construction model, to measure overall node characteristics in the social network during two periods of event. Then we propose an optimal synthesis method to identify the opinion leader, and based on it, we construct opinion leader Reliability Index as an evaluation basis to realize the opinion leader reliability tracking. This method could effectively identify and evaluate opinion leaders. The experiment result shows that 77% of the opinion leaders satisfy the reliability tracking evaluation criteria, which effectively validates the beneficial effect of optimal synthesis and the feasibility of the identification-tracking system.

The high-definition (HD) map is critical for the localization and motion planning of connected and automated vehicles (CAVs). With all the road and lane information pre-scanned in a certain area, the vehicles can know its position with respect to the lane marks and roadside, and hence make better decisions on planning future trajectories. A common issue, however, is the accuracy of the scanned outputs from different data sources. Because of the limitations of online maps (e.g., zooming and stretching in their image layers), visualizing the data in the bird's eye view on maps cannot satisfy the accuracy requirement of being the ground-truth system. To this end, a feasible method that can combine sensing data from different sources and obtain reliable ground-truth information is necessary. In this paper, we develop a novel method to transform the data points from the bird's eye view to the view angle of a web camera installed on the windshield of the ego vehicle. In such a case, the position of landmarks from the captured frames of the camera can be used as the ground-truth. In particular, we take the lane marking detection outputs from the Mobileye system as the reference for a better accuracy. We evaluate the proposed method using the field data on highway I-75 in Michigan, USA. The results show that this method has achieved a very good accuracy of over 90% for location determination of lane information. The main contribution of this paper is that the proposed method can be more intuitive and reliable than using the traditional maps in bird's eye view.

Fluorescent N,S-CDs with a quantum yield of 37.8% were synthesized via a one-pot solvothermal method. Detailed characterizations on physical, chemical and optical properties have been investigated. N,S-CDs demonstrated remarkably quenched and enhanced fluorescence in acidic and basic media. Direct qualitative analysis in pH sensor and cell imaging were preliminarily studied.

As the largest social media platform in China, Sina-microblog is characterized by instant interaction, which makes thousands of pieces of data and information spread at each time. Based on this, this paper makes an in-depth analysis of the mechanism of single information transmission on Weibo, constructs a derived information transmission dynamics model with considering the linear retention rate based on the classical infectious disease model, and introduces the least square function LS to perform curve fitting for real data, to obtain the optimal parameter vector of the model. The early prediction of microblog information diffusion is realized.

As the largest flat social platform in China, mi-croblog is the main position of public opinion dissemination. In the propagation network composed of hot event, not only the static propagation structure is worth studying, but also the dynamic evolution rule. In this paper, we propose evolution analysis methods based on staged propagation network in the light of three propagation structure studies: core group mining, opinion leader identification and participant classification. Then the evolution types are further classified to achieve the measurement of evolution stability. Experiments on four real event datasets show that the research methods of evolution rule in this paper can reflect the evolution characteristics, which are of both feasibility and practicability.

The outbreak of a novel coronavirus (COVID-19) aroused great public opinion in the Chinese Sina-microblog. To help in designing effective communication strategies during a major public health emergency, we analyze the real data of COVID-19 information and propose a comprehensive susceptible–reading–forwarding–immune (SRFI) model to understand the patterns of key information propagation considering both public contact and participation. We develop the SRFI model, based on the public reading quantity and forwarding quantity that denote contact and participation respectively, and take into account the behavior that users may re-enter another related topic during the attention phase or the participation phase freely. Data fitting using the real data of both reading quantity and forwarding quantity obtained from Chinese Sina-microblog can parameterize the model to make an accurate prediction of the COVID-19 public opinion trend until the next major news item occurs, and the sensitivity analysis provides the basic strategies for communication.