INITIAL RESULTS ON A NEW LIGHT-DUTY 2.7L OPPOSED-PISTON GASOLINE COMPRESSION IGNITION MULTI-CYLINDER ENGINE

Gasoline compression ignition (GCI) is a cost-effective approach to achieving diesel-like efficiencies with low emissions. The fundamental architecture of the two-stroke Achates Power Opposed-Piston Engine (OP Engine) enables GCI by decoupling piston motion from cylinder scavenging, allowing for flexible and independent control of cylinder residual fraction and temperature leading to improved low load combustion. In addition, the high peak cylinder pressure and noise challenges at high-load operation are mitigated by the lower BMEP operation and faster heat release for the same pressure rise rate of the OP Engine. These advantages further solidify the performance benefits of the OP Engine and emonstrate the near-term feasibility of advanced combustion technologies, enabled by the opposed-piston architecture. This paper presents initial results from a steady state testing on a brand new 2.7L OP GCI multi-cylinder engine designed for light-duty truck applications. Successful GCI operation calls for high compression ratio, leading to higher combustion stability at low-loads, higher efficiencies, and lower cycle HC+NOX emissions. Initial results show a cycle average brake thermal efficiency of 31.7%, which is already greater than 11% conventional engines, after only ten weeks of testing. Emissions results suggest that Tier 3 Bin 160 levels can be achieved using a traditional diesel after-treatment system. Combustion noise was well controlled at or below the USCAR limits. In addition, initial results on catalyst light-off mode with GCI are also presented.

Ethical Considerations of Using VR in Mental Health Training

Mental health students, who are still undergoing training, might find it challenging to visualise and fully understand what their patients experience. For this reason, the authors created a virtual reality simulator which mimics the symptoms of a person suffering from schizophrenia at a virtual workplace. The simulation is managed by an artificial intelligence system which asks the user to attempt simple tasks, while simultaneously facing both visual and auditory hallucinations. The AI also adapts the storyline and character behaviour dynamically to increase the immersiveness of the experience. A pilot study was carried out, and the initial results were very encouraging. In fact, the absolute majority of the users stated that the simulation has helped increase their understanding of schizophrenia. In this chapter, the authors evaluate this experiment but from a different perspective. They focus mainly on the use of emerging technologies such as AI and VR and discuss the ethical considerations of their use within the field of mental health.

Decision Support for Plan Adaptation in Unforeseen Situations

Handling irregular phenomena might bring great complexity for involved teams. Variables considered for undertaking recommended procedures may yield many decision alternatives, challenging to deal with at planning time. Additionally, expectations regarding the phenomena handling may not match those observed. This means that the existing plan’s application may become inappropriate, and teams must be creative in performing actions and decision-making. An approach for on-the-fly adaptation of plans aims to assist teams in identifying and diagnosing unforeseen situations, besides adjusting previously developed plans at runtime. This approach was evaluated through experiments in the emergency management domain, and the initial results indicate its feasibility in dealing with unforeseen situations while handling irregular phenomena in complex environments.

Using Epistemic Game Development to Teach Software Development Skills

This paper presents a pilot study on the evaluation of instruments for data gathering for an epistemic game development competition for high school students. The initial results show that a significant percentage of the students who participated in the competition appear to exhibit a skillset of professional attitude, software-related knowledge, and employability traits, and this skillset may be attributed to the intervention. The data was validated through a two-method triangulation technique that utilized expert evaluation and participant interviews. The data analysis shows early indicators of the desired learning outcomes, although a more thorough methodology is needed to verify this. Furthermore, the competition acts as an awareness campaign that promotes computer science studies through a gamification process. It is proposed that competitions of this type are held and evaluated on an annual basis to maximize the benefits and to further prepare students to acquire early in their studies a skillset that will make them the innovators of the future society.

A different approach to b(an,bn)-hypermetric spaces

Introduction/purpose: The aim of this paper is to present the concept of b(an,bn)-hypermetric spaces. Methods: Conventional theoretical methods of functional analysis. Results: This study presents the initial results on the topic of b(an,bn)-hypermetric spaces. In the first part, we generalize an n-dimensional (n ≥ 2) hypermetric distance over an arbitrary non-empty set X. The b(an,bn)-hyperdistance function is defined in any way we like, the only constraint being the simultaneous satisfaction of the three properties, viz, non-negativity and positive-definiteness, symmetry and (an, bn)-triangle inequality. In the second part, we discuss the concept of (an, bn)-completeness, with respect to this b(an,bn)-hypermetric, and the fixed point theorem which plays an important role in applied mathematics in a variety of fields. Conclusion: With proper generalisations, it is possible to formulate well-known results of classical metric spaces to the case of b(an,bn)-hypermetric spaces.