The rapid growth of e-commerce in South Africa has increased the demand for efficient last-mile delivery. Motorcycle delivery drivers play a crucial role in the last-mile delivery process to bridge the gap between retailers and consumers. However, these drivers face significant challenges that impact both logistical efficiency and their socio-economic well-being. This study critically analyzes media narratives on the safety and working conditions of motorcycle delivery drivers in the e-commerce sector in South Africa. The thematic analysis of newspaper articles identified recurring themes. This study reveals critical safety and labor vulnerabilities affecting motorcycle delivery drivers in South Africa’s e-commerce sector. Key findings include heightened risks of violence, hijackings, and road accidents, exacerbated by inadequate infrastructure and safety gear. Coupled with low wages, job insecurity, and limited benefits, these conditions expose drivers to significant precarity. Policy interventions are urgently needed for driver safety and sustainable logistics. By integrating insights from multiple disciplines, this study offers a comprehensive understanding of the complex challenges within this rapidly growing sector.

This research implements sustainable environmental practices by repurposing post-industrial plastic waste as an alternative material for non-conventional construction systems. Focusing on the development of a recycled polymer matrix, the study produces panels suitable for masonry applications based on tensile and compressive stress performance. The project, conducted in Portoviejo and Medellín, comprises three phases combining bibliographic and experimental research. Low-density polyethylene (LDPE), high-density polyethylene (HDPE), and polypropylene (PP) were processed under controlled temperatures to form a composite matrix. This material demonstrates versatile applications upon cooling—including planks, blocks, caps, signage, and furniture (e.g., chairs). Key findings indicate optimal performance of the recycled thermoplastic polymer matrix at a 1:1:1 ratio of LDPE, HDPE, and PP, exhibiting 15% deformation. The proposed implementation features 50 × 10 × 7 cm panels designed with tongue-and-groove joints. When assembled into larger plates, these panels function effectively as masonry for housing construction, wall cladding, or lightweight fill material for slab relieving.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.

Increasing levels of everyday cycling has many benefits for both individuals and for cities. Reduced traffic congestion, improved air quality and safer spaces for all vulnerable road users are among the significant benefits for urban developments. Despite this, public opposition to cycling infrastructure is common, particularly when it involves reprioritising road space for cycles instead of vehicles. The purpose of the research was to examine various stakeholders’ perspectives on proposed cycle infrastructure projects. This study utilised an innovative data collection approach through detailed content analysis of 322 public consultation submissions on a proposed active travel scheme in Limerick City, Ireland. By categorising submissions into support, opposition, and proposals, the study reveals the nuanced public perceptions that influence behavioural adaptation and acceptance of sustainable transport infrastructure. Supportive submissions, which outnumbered opposition-related submissions by approximately 2:1, emphasised the need for dedicated cycling infrastructure, enhanced cyclist safety, and potential improvements in environmental conditions. In contrast, opposition submissions focused on concerns over car parking removal, decreased accessibility for residents, and safety issues for vulnerable populations, particularly the elderly. Proposal submissions suggested design modifications, including enhanced safety features, provisions for convenient car parking, and alternative cycle routes. This paper highlights the value of structured public consultation data in uncovering behavioural determinants and barriers to cycling infrastructure adoption, offering policymakers essential insights into managing public opposition and fostering support. The methodology demonstrates how qualitative data from consultations can be effectively used to inform policy by capturing community-specific needs and enhancing the design of sustainable urban mobility systems. These findings underscore the need for innovative, inclusive data collection methods that reveal public sentiment, facilitating evidence-based transport policies that support climate-neutral mobility.

Segregating the scavenging processes from the lubrication methodology is a very effective way of improving two-stroke cycle engine durability. The application of stepped or twin diameter pistons is one such method that has repeatedly shown significantly greater durability over comparable crankcase scavenged engines together with an ability to operate on neat fuel without any added oil. This research study presents the initial results observed from a gasoline/indolene fuelled stepped piston engine ultimately intended for Hybrid Electric Vehicle and/or Range Extender Electric Vehicle application using hydrogen fuelling. Hydrogen fuelling offers the potential to significantly reduce emissions, with near zero emission operation possible, and overcoming the serious issues of range anxiety in modern transport solutions. The low environmental impact is discussed along with results from 1-d Computational Fluid Dynamic modelling. The engine type is a low-cost solution countering the financial challenges of powertrain duplication evident with Hybrid Electric and Range Extender Electric Vehicles.