Predicting the effects of environmental parameters on the spatio-temporal distribution of the droplets carrying coronavirus in public transport - A machine learning approach

Urea-Self Powered Biosensors: A Predictive Evolutionary Model for Human Energy Harvesting

The objective of this study is to create a reliable predictive model for the electrochemical performance of self-powered biosensors that rely on urea-based biological energy sources. Specifically, this model focuses on the development of a human energy harvesting model based on the utilization of urea found in sweat, which will enable the development of self-powered biosensors. In the process, the potential of urea hydrolysis in the presence of a urease enzyme is employed as a bioreaction for self-powered biosensors. The enzymatic reaction yields a positive potential difference that can be harnessed to power biofuel cells (BFCs) and act as an energy source for biosensors. This process provides the energy required for self-powered biosensors as biofuel cells (BFCs). To this end, initially, the platinum electrodes are modified by multi-walled carbon nanotubes to increase their conductivity. After stabilizing the urease enzyme on the surface of the platinum electrode, the amount of electrical current produced in the process is measured. The optimal design of the experiments is performed based on the Taguchi method to investigate the effect of urea concentration, buffer concentration, and pH on the generated electrical current. A general equation is employed as a prediction model and its coefficients calculated using an evolutionary strategy. Also, the evaluation of effective parameters is performed based on error rates. The obtained results show that the established model predicts the electrical current in terms of urea concentration, buffer concentration, and pH with high accuracy.

Efficient and Moisture-Stable Inverted Perovskite Solar Cells via n-Type Small-Molecule-Assisted Surface Treatment

Defect states at the surface and grain boundaries of perovskite films have been known to be major determinants impairing the optoelectrical properties of perovskite films and the stability of perovskite solar cells (PeSCs). Herein, an n-type conjugated small-molecule additive based on fused-unit dithienothiophen[3,2-b]-pyrrolobenzothiadiazole-core (JY16) is developed for efficient and stable PeSCs, where JY16 possesses the same backbone as the widely used Y6 but with long-linear n-hexadecyl side chains rather than branched side chains. Upon introducing JY16 into the perovskite films, the electron-donating functional groups of JY16 passivate defect states in perovskite films and increase the grain size of perovskite films through Lewis acid-base interactions. Compared to Y6, JY16 exhibits superior charge mobility owing to its molecular packing ability and prevents decomposition of perovskite films under moisture conditions owing to their hydrophobic characteristics, improving the charge extraction ability and moisture stability of PeSCs. Consequently, the PeSC with JY16 shows a high power conversion efficiency of 21.35%, which is higher than those of the PeSC with Y6 (20.12%) and without any additive (18.12%), and outstanding moisture stability under 25% relative humidity, without encapsulation. The proposed organic semiconducting additive will prove to be crucial for achieving highly efficient and moisture stable PeSCs.

All-Polymer Solar Cells with 17% Efficiency Enabled by the "End-Capped" Ternary Strategy

Recently, all-polymer solar cells (all-PSCs) have received increasing attention and made tremendous progress. However, the power conversion efficiency (PCE) of all-PSCs still lags behind the polymer-donor-small-molecule-acceptor based organic solar cells, owing to the excessive phase separation with poor miscibility between polymer donor and acceptor. In this research, an "end-capped" ternary strategy is proposed by introducing PM6TPO as a third component to fabricate highly efficient all-PSCs. The PM6:PM6TPO:PY-IT based ternary devices exhibit impressive PCE of 17.0% with enhanced light absorption and optimal morphology, and the introduction of PM6TPO significantly reduces the phase separation. The ternary devices also exhibit improved stability, outstanding tolerance of active layer thickness, and high performance of 1 cm2 unit cells. More importantly, the "end-capped" ternary strategy enables efficient and facile improvement of all-PSCs performance without additional selection and complicated synthesis for the third component.

A systematic review of COVID-19 transport policies and mitigation strategies around the globe

This paper reports a Scopus-based systematic literature review of a wide variety of transportation policies and mitigation strategies that have been conducted around the world to minimize COVID-19 contagion risk in transportation systems. The review offers a representative coverage of countries across all continents of the planet, as well as among representative climate regions - as weather is an important factor to consider. The readership interested in policies and mitigation strategies is expected to involve a wide range of actors, each involving a particular application context; hence, the literature is also characterized by key attributes such as: transportation mode; actor (users, operators, government, industry); jurisdiction (national, provincial, city, neighborhood); and area of application (planning, regulation, operations, research, incentives). An in-depth analysis of the surveyed literature is then reported, focusing first on condensing the literature into 151 distinct policies and strategies, which are subsequently categorized into 25 broad categories that are discussed at length. The compendium and discussion of strategies and policies reported not only provide comprehensive guidelines to inform various courses of action for decision-makers, planners, and social communicators, but also emphasize on future work and the potential of some of these strategies to be the precursors of meaningful, more sustainable behavioral changes in future mobility patterns.

Assessing Spatial Variations of Traffic Congestion Using Traffic Index Data in a Developing City: Lessons from Johannesburg, South Africa

The COVID-19 pandemic has created unforeseen effects in public transport and the mobility of people in cities globally. Johannesburg, being a developing city in one of the most affected countries in Africa during the pandemic, has experienced severe changes in traffic management and travel patterns as a result of the restrictions imposed on movement. Hence, this study examined the spatial variations in traffic during the pandemic. The study utilized data obtained from the TomTom Traffic Index for the city of Johannesburg from 2019 to 2021, with 2019 representing the period pre-COVID-19 with no lockdown restrictions, 2020 representing the period with restricted movement to limit spread of COVID-19, and 2021 representing a period of relaxed and minimized restrictions on movement. Our findings revealed that there was a variation in congestion levels between 2019–2021 with year 2020 having the least congestion from the beginning of the COVID-19 restrictions due to regulations enforced in movement and reduced travel. Our findings further revealed that traffic congestion was higher during weekdays than weekends during the three periods, with mini-bus taxis as the major contributors to congestion. Consequently, there is a need to discourage the use of single occupancy vehicles and invest in more sustainable means of transportation to ease the mobility of people and reduce traffic on major roads.

Public Transport COVID-19-Safe: New Barriers and Policies to Implement Effective Countermeasures under User’s Safety Perspective

The COVID-19 emergency forced cities worldwide to adopt measures to restrict travel and implement new urban public transport solutions. The discontinuity and reduction of services made users recognize public transport systems as contamination vectors, and the decrease in the number of passengers can already be seen in several places. Thus, this study assessed the impact of the COVID-19 pandemic on urban public transport. We used hybrid choice models (HCMs) to identify the new barriers and potential solutions to increase users’ perception of safety, considering preexistent perceptions of public transportation quality. We used data from an online survey with users of public transportation in a metropolitan area in southern Brazil. We identified that the main barriers to using public transport during virus transmission are related to the system characteristics that force constant interaction with other passengers. Crowded vehicles and crowded stops/stations were considered the most detrimental factor in feeling safe while riding in the COVID-19 outbreak. Countermeasures that reduce the contact with other passengers—directly (limit the number of passengers in vehicles) or indirectly (operate with large vehicles)—and increase offers are possible solutions to make users feel safe while riding. The results of this research might help reduce passenger evasion and migration to more unsustainable transport modes.