What are the factors that contribute to road accidents? An assessment of law enforcement views, ordinary drivers’ opinions, and road accident records

What are the main contributing factors to road accidents? Factors such as inexperience, lack of skill, and risk-taking behaviors have been associated with the collisions of young drivers. In contrast, visual, cognitive, and mobility impairment have been associated with the collisions of older drivers. We investigated the main causes of road accidents by drawing on multiple sources: expert views of police officers, lay views of the driving public, and official road accident records. In Studies 1 and 2, police officers and the public were asked about the typical causes of road traffic collisions using hypothetical accident scenarios. In Study 3, we investigated whether the views of police officers and the public about accident causation influence their recall accuracy for factors reported to contribute to hypothetical road accidents. The results show that both expert views of police officers and lay views of the driving public closely approximated the typical factors associated with the collisions of young and older drivers, as determined from official accident records. The results also reveal potential underreporting of factors in existing accident records, identifying possible inadequacies in law enforcement practices for investigating driver distraction, drug and alcohol impairment, and uncorrected or defective eyesight. Our investigation also highlights a need for accident report forms to be continuously reviewed and updated to ensure that contributing factor lists reflect the full range of factors that contribute to road accidents. Finally, the views held by police officers and the public on accident causation influenced their memory recall of factors involved in hypothetical scenarios. These findings indicate that delay in completing accident report forms should be minimised, possibly by use of mobile reporting devices at the accident scene

Predicting prostate cancer treatment choices: The role of numeracy, time discounting, and risk attitudes

Prostate cancer is the most common cancer among males in the United States and there is lack of consensus as to whether active surveillance (AS) or radical prostatectomy (RP) is the best course of treatment. In this study we examined the role of three overlooked determinants of decision making about prostate cancer treatment in a hypothetical experiment—numeracy, time discounting, and risk taking in 279 men over age 50 without a prior prostate cancer diagnosis. Results showed that AS was the most frequently chosen option. Furthermore, numeracy and time discounting significantly predicted participants’ preference for AS, whereas a propensity to take risks was associated with a preference for RP. Such insights into the factors that affects cancer treatment preferences may improve tailored decision aids and help physicians be better poised to engage in shared decision-making to improve both patient-reported and clinical outcomes

Ultrahigh-rate supercapacitors based on eletrochemically reduced graphene oxide for ac line-filtering

The recent boom in multifunction portable electronic equipments requires the development of compact and miniaturized electronic circuits with high efficiencies, low costs and long lasting time. For the operation of most line-powered electronics, alternating current (ac) line-filters are used to attenuate the leftover ac ripples on direct current (dc) voltage busses. Today, aluminum electrolytic capacitors (AECs) are widely applied for this purpose. However, they are usually the largest components in electronic circuits. Replacing AECs by more compact capacitors will have an immense impact on future electronic devices. Here, we report a double-layer capacitor based on three-dimensional (3D) interpenetrating graphene electrodes fabricated by electrochemical reduction of graphene oxide (ErGO-DLC). At 120-hertz, the ErGO-DLC exhibited a phase angle of −84 degrees, a specific capacitance of 283 microfaradays per centimeter square and a resistor-capacitor (RC) time constant of 1.35 milliseconds, making it capable of replacing AECs for the application of 120-hertz filtering

Opportunities and Challenges in Providing Health Care for International Retirement Migrants: A Qualitative Case Study of Canadians Travelling To Yuma, Arizona

Background Increasing numbers of older individuals opt to spend extended time abroad each year for lifestyle, health, and financial reasons. This practice is known as international retirement migration, and it is particularly popular among retirees in Global North countries such as Canada. Despite the popularity of international retirement migration, very little is known about how and why health care is accessed while abroad, nor the opportunities and challenges posed for destination hospitals. In this article we focus on addressing the latter knowledge gap. Methods This qualitative case study is focused on the only hospital in Yuma, Arizona – a popular destination for Canadian retirement migrants in the United States. We conducted focus groups with workers at this hospital to explore their experiences of treating this transnational patient group. Twenty-seven people participated in three, 90-min focus groups: twelve nurses, six physicians, and nine administrators. Thematic analysis of the focus group transcripts was conducted using a triangulated approach. Results Participants identified three care environments: practice, transnational, and community. Each environment presents specific opportunities and challenges pertaining to treating Canadian retirement migrants. Important opportunities include the creation of a strong and diverse seasonal workforce in the hospital, new transnational paths of communication and information sharing for physicians and health administrators, and informal care networks that support formal health care services within and beyond the hospital. These opportunities are balanced out by billing, practical, administrative, and lifestyle-related challenges which add complexity to treating this group of transnational patients. Conclusion Canadians represent a significant group of patients treated in Yuma, Arizona. This is contrary to long-standing, existing research that depicts older Canadians as being reluctant to access care while in the United States. Significant overlaps exist between the opportunities and challenges in the practice, transnational and community environments. More research is needed to better understand if these findings are similar to other destinations popular with Canadian international retirement migrants or if they are unique to Yuma, Arizona

Preparation and Application of Electrodes in Capacitive Deionization (CDI): a State-of-Art Review

As a promising desalination technology, capacitive deionization (CDI) have shown practicality and cost-effectiveness in brackish water treatment. Developing more efficient electrode materials is the key to improving salt removal performance. This work reviewed current progress on electrode fabrication in application of CDI. Fundamental principal (e.g. EDL theory and adsorption isotherms) and process factors (e.g. pore distribution, potential, salt type and concentration) of CDI performance were presented first. It was then followed by in-depth discussion and comparison on properties and fabrication technique of different electrodes, including carbon aerogel, activated carbon, carbon nanotubes, graphene and ordered mesoporous carbon. Finally, polyaniline as conductive polymer and its potential application as CDI electrode-enhancing materials were also discussed

Driver Monitoring System Based on CNN Models: An Approach for Attention Level Detection

Drivers provide a wide range of focus characteristics that can evaluate their attention level and analyze their behavioral states while driving. This information is critical for the development of new automated driving functionalities that support and assist the driver according to his/her state, ensuring safety for them and other users on the road. In this sense, this paper proposes a Driver Monitoring System (DMS) based on image processing and Convolutional Neural Networks (CNN), that analyzes two important driver distraction aspects: inattention of the road and drowsiness. Our approach makes use of CNN models for detecting the gaze and the head direction, which involves training datasets with different pre-defined labels. Additionally, the system is complemented with the drowsiness level measurement, using face features to detect the time that the eyes are closed or opened, and the blinking rate. Crossing the inference results of these models, the system can provide an accurate estimation of driver attention level. The different parts of the presented DMS have been trained in a Hardware-in-the-loop driving simulator with an eye fish camera. It has been tested as a real-time application recording driver with different characteristics