Microbial biofilms for self-powered noncontact sensing.

Noncontact sensing technology plays a vital role in the intelligent human-machine interface, as the essential medium for exchanging information between human and electronic devices. To date, several inorganic materials-based noncontact sensing techniques have been used to accurately detect touch, electrical property, and physical motion. However, limited available materials, dependence on additional power supplies, and poor power production performance, have seriously obstructed the practical applications of noncontact sensing technology. Here, we developed simple self-powered noncontact sensors (SNSs) assembled using a typical G. sulfurreducens biofilm as the core component. In noncontact mode, the sensor demonstrated excellent self-powered sensing performance with maximum voltage output of 10 V and a current of 60 nA, a maximum sensing range of 40 cm which is the farthest reported to date. Depending on its excellent sensing characteristic, the SNSs was used to monitor human breathing in this work. Furthermore, an array of united SNSs was able to localize external electric fields and effectively extend the sensing area by increasing the number of devices. Compared to traditional inorganic materials, microbial biofilms have the advantages of wide existence, self-proliferation, low cost, environmental friendliness, and ultra-fast self-healing property (seconds level). The proposed biofilm SNSs in our work provides new insights for noncontact power generation of biomaterials and self-driven sensing.

Review of Research on Road Traffic Operation Risk Prevention and Control.

Road traffic safety can be ensured by preventing and controlling the potential risks in road traffic operations. The relevant literature was systematically reviewed to identify the research context and status quo in the road traffic operation risk prevention and control field and identify the key study contents needing further research. As research material, the related English and Chinese literature published between 1996 and 2021 (as of 31st December 2021) was obtained through the Web of Science Core Collection and Chinese Science Citation Database. These research materials include 22,403 English and 7876 Chinese papers. Based on the bibliometrics, this study used CiteSpace software to conduct keyword co-occurrence analysis in the field. The results show that the relevant research topics mainly covered the risks of drivers, vehicles, roads, and the traffic environment. In the aspect of driver risks, the studies focused on driving behavior characteristics. In terms of vehicle risks, the related studies were mainly about the vehicle control system, driving assistance system, hazardous material transportation, automated driving technology, safe driving speed, and vehicle collision prediction. For the road risks, the safe driving guarantee of high-risk road sections, driving risks at intersections, and safe road alignment design were the three study hotspots. In terms of traffic environment risks, identifying traffic risk locations and driving safety guarantees under adverse weather conditions were the two main research highlights. Moreover, mathematical modeling was the main method for studying road traffic operation risk. Furthermore, the impact of environmental factors on drivers, the emergency rescue system for road traffic accidents, the connection between automated driving technology and safe driving theory, and the man-machine hybrid traffic flow characteristics are the subjects needing further research.

Multivariate analysis of roadway multi-fatality crashes using association rules mining and rules graph structures: A case study in China.

Roadway multi-fatality crashes have always been a vital issue for traffic safety. This study aims to explore the contributory factors and interdependent characteristics of multi-fatality crashes using a novel framework combining association rules mining and rules graph structures. A case study is conducted using data from 1068 severe fatal crashes in China from 2015 to 2020, and 1452 interesting rules are generated using an association rule mining approach. Several modular rules graph structures are constructed based on graph theory to reflect the interactions and patterns between different variables. The results indicate that multi-fatality crashes are highly associated with improper operations, passenger overload, fewer lanes, mountainous terrain, and run-off-the-road crashes, representing the key variables of factors concerning driver, vehicle, road, environment, and accident, respectively. Furthermore, crashes involving different severity levels, road categories, and terrain are verified to possess unique association rules and independent crash patterns. Moreover, the proportion of severe crashes caused by a combination of human-vehicle-road-environment factors (43%) is much higher than that of normal crashes (3%). This study reveals that the hidden associations between various factors contribute to the overrepresentation and severity of multi-fatality crashes. It also demonstrates that the crash mechanisms involving multi-fatality crashes and their interactions are more complex at the system level than those for normal crashes. The proposed framework can effectively map the intrinsic link between multiple crash factors and potential risks, providing transportation agencies with helpful insights for targeted safety measures and preventive strategies.

The influence of the pavement friction coefficient evolution caused by traffic flow on the risk of motorway horizontal curves.

The friction coefficient between the tire and the road is one of the key parameters affecting road traffic safety. The purpose of this paper is to quantify the risk of skidding for the vehicles due to the friction evolution caused by the traffic polishing in the horizontal curve. Based on the reliability theory, an innovative dynamic risk assessment model is developed in the present study for passenger cars and trucks. The influence of two traffic characteristics for pavement friction is quantified: cumulative traffic volume (CTV) and annual average daily traffic of trucks (AADTT). The speed distribution on the horizontal curve of the motorway is obtained through field experiments as the basic parameter of the model. The Hasofer-Lind Method is adopted to solve the reliability and the risk probability of vehicle skidding. The results show that in the traffic characteristics, the AADTT has a significant impact on the pavement friction; When the AADTT on the road exceeds 2000 veh/d, the increasing CTV leads to friction decrease rapidly and therefore has a significant impact on the risk of horizontal curve. Especially for roads with more than 50 million vehicles of the CTV, the risk of the horizontal curve shows a sharp increase with CTV rising. The research results can provide reference for the road maintenance department to determine the timing of road maintenance.

Impacts of COVID-19 Travel Restriction Policies on the Traffic Quality of the National and Provincial Trunk Highway Network: A Case Study of Shaanxi Province.

According to recent research, the COVID-19 pandemic has impacted road traffic quality. This study aims to analyze the impacts of COVID-19 travel restriction policies on the traffic quality of the national and provincial trunk highway network (NPTHN) in Shaanxi Province. We collected the traffic data of the NPTHN for three consecutive years (from 2019 to 2021), before and after the COVID-19 outbreak, including weekly average daily traffic, weekly traffic interruption times, weekly traffic control time, weekly traffic accidents, weekly traffic injuries, and weekly traffic deaths. Using descriptive statistics and dynamic analysis methods, we studied the safety and service levels of the NPTHN. We set up an assessment model of the NPTHN operational orderliness through dissipative structure theory and entropy theory to study the operational orderliness of the NPTHN. Results show that in 2020, the service level, safety level, and operational orderliness of the NPTHN dropped to the lowest levels. The pandemic was gradually brought under control, and the travel restriction policies were gradually reduced and lifted. The adverse impacts on the operational orderliness of the NPTHN decreased, but the operational orderliness did not yet recover to the pre-pandemic level. Meanwhile, the service and safety levels of the NPTHN did not recover. Taken together, the COVID-19 travel restriction policies had adverse impacts on the traffic quality of the NPTHN in Shaanxi Province.

Water evaporation-induced electricity with Geobacter sulfurreducens biofilms.

Water evaporation-induced electricity generators (WEGs) have recently attracted extensive research attention as an emerging renewable energy-harvesting technology that harvests electricity directly from water evaporation. However, the low power output, limited available material, complicated fabrication process, and extremely high cost have restricted wide applications of this technology. Here, a facile and efficient WEG prototype based on Geobacter sulfurreducens biofilm was demonstrated. The device can generate continuous electric power with a maximum output power density of ~685.12 µW/cm2, which is two orders of magnitude higher than that of previously reported analogous devices. The superior performance of the device is attributed to the intrinsic properties of the G. sulfurreducens biofilm, including its hydrophilicity, porous structure, conductivity, etc. This study not only presents the unprecedented evaporating potential effect of G. sulfurreducens biofilms but also paves the way for developing hydrovoltaic technology with biomaterials.

The chemical structure characteristics of dissolved black carbon and their binding with phenanthrene.

The elucidation of interactions between the dissolved black carbon (DBC) in biochar and hydrophobic organic contaminants (HOCs) is crucial for controlling the environmental behavior of HOCs. The complicated chemical structures of DBCs result in diverse interaction mechanisms between DBCs and HOCs, which were driven by different chemical structures in DBCs. In the present study, ten DBCs were extracted from rice straw and corncob biochars and their chemical structures were characterized and analyzed. The binding of phenanthrene (Phen) with DBC were studied through fluorescence quenching experiments. DBCs with low concentration (1 mg C/L) were found to complex with high amounts of Phen per unit mass. No significant difference was found in the amount of the bound Phen per unit amount of DBC when the concentration of DBC increased beyond >5 mg C/L. The dominant mechanisms involved in the binding of Phen by DBCs are speculated to be hydrophobic interactions, π-π electron donor-acceptor (EDA), and chemical partition, which was driven by the fatty carbon chain, aromatic rings, and quinone groups or ester groups, respectively. This study elucidates the interactions between DBC and Phen, which is of great significance for understanding the environmental behavior of HOCs.

[Determination of common antibiotics and metronidazole in cosmetics by ultra performance liquid chromatography-tandem mass spectrometry].

A method for the analysis of common antibiotics and metronidazole in cosmetics was developed by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/ MS). One gram of each cosmetic sample was extracted by methanol-water containing 0.1 mol/L formic acid (1:1, v/v). The extracted sample was filtered before being analyzed with UPLC/MS/MS. The effects of formic acid concentration in the mobile phase on the sensitivity and retention time were studied, and the results showed that 1% was the optimum concentration. Seven analytes, minocycline, oxytetracycline, tetracycline, chlortetracycline, doxycycline, chloramphenicol, metronidazole, can be separated and detected in 5 min, which is much faster than that by the conventional liquid chromatography. The detection limits were 3 - 20 ng/g, and the recoveries were 87% -101%. The calibration curves showed good linearity in the range of 2 - 1 000 microg/L with correlation coefficients larger than 0.995. The method was also applied to determine common antibiotics and metronidazole in 11 real samples from the market. Chloramphenicol was detected in 2 samples and the concentrations were 0.37% and 0.19%; metronidazole was detected in 1 sample and the concentration was 1.02%; others were not detected.