Abstract
Virtual reality (VR) for training helps minimize risks and costs by allowing more frequent and varied use of experiential training experiences, leading to active and improved learning. However, creating VR training experiences is costly and time-consuming, requiring software development experts. Additionally, current authoring tools are desktop-oriented, which detaches the process of creating the immersive experience from experiencing it in a situated context. This paper presents the development of an immersive authoring tool designed to create immersive virtual environments that can be used to train operatives. The authoring tool can record and replay animations of each action the user performed that can later be used to instruct other users how the task should be performed. Participants were divided into two groups, and the proposed authoring tool was evaluated using usability, satisfaction, presence and cybersickness. Between groups, Independent T-tests revealed that there were no significant differences between expert and non-expert groups in any of the studied variables. Also, the results showed that the authoring tool had high usability and satisfaction, average presence, and low probability of cybersickness symptoms.

Abstract
The expansion of ethanol production in Brazil sparks several sustainability concerns, including debates on “food versus fuel”, the environmental impacts of monocultures, and indirect land-use change. Since livestock farming occupies a significantly greater area than sugarcane for ethanol production in Brazil and has a large yield gap, sugarcane-livestock integration can be a promising alternative. This integrated system considers crop production systems, biorefinery processing and meat production in both intensive and extensive livestock farming. Optimizing this system for both economic and environmental aspects can be challenging to implement and computationally expensive as this system's complexity arises from nonlinear subsystems and their intertwining input-output flows. For these reasons, this paper develops metamodels from detailed models to: (i) Optimize the extensive livestock farming, (ii) Optimize the confined animal feeding, and (iii) Optimize the integrated system. The main objective is to maximize the Net Present Value relative to investment. This study contributes to the literature by developing innovative models for ethanol-beef integrated production systems and methods for optimizing such systems to avoid negative externalities on food security and environmental impacts. © 2024 Elsevier B.V.

Abstract

Abstract
Memory safety issues in C are the origin of various vulnerabilities that can compromise a program’s correctness or safety from attacks. We propose a different approach to tackle memory safety, the replication of Rust’s Mid-level Intermediate Representation (MIR) Borrow Checker, through the usage of static analysis and successive source-to-source code transformations, to be composed upstream of the compiler, thus ensuring maximal compatibility with most build systems. This allows us to approximate a subset of C to Rust’s core concepts, applying the memory safety guarantees of the rustc compiler to C. In this work, we present a survey of Rust’s efforts towards ensuring memory safety, and describe the theoretical basis for a C borrow checker, alongside a proof-of-concept that was developed to demonstrate its potential. This prototype correctly identified violations of the ownership and aliasing rules, and accurately reported each error with a level of detail comparable to that of the rustc compiler. © 2024 Copyright held by the owner/author(s).

Abstract
The United Nations has issued a warning over the limited time for climate disaster prevention. In the last two decades, several countries have set targets to reduce fossil fuel usage and greenhouse gas emissions. These goals are tracked through the adoption of energy systems that prioritise efficiency and low-carbon alternatives, in alignment with the Sustainable Development Goals outlined by the United Nations. In the winemaking sector, the wine produced in the European Union comprised 65 % of the worldwide total from 2014 to 2018, with vineyards making up 4.7 % of its farms in 2020. Electricity is the primary source of energy used in vineries, accounting for around 90 % of the total energy consumption. The energy consumption associated with winemaking is mostly attributed to two key processes: fermentation, which accounts for 45 % to 90 % of the entire energy consumption, and bottling and storage, which contribute around 18 % of the overall energy consumption. The aim of this article is to provide an integrated review of energy efficiency in wineries through examining 144 academic publications. The selected publications cover various aspects, including sustainable energy utilisation in the wine industry, thermal performance analysis of buildings, energy efficiency assessment of systems and technologies, and the integration of renewable energy sources. A link has been established between the geographic distribution of academic publications and wine -producing countries. In relation to European publications, it is observed that research funding is associated with the energy directives of the European Union. It can also be concluded that wine customers are pushing for environmentally friendly practices. However, not everyone in the winemaking sector is moving in the same direction or at the same pace. To identify areas for improvement, winemakers must have supporting tools to manage energy use. Systems optimisation, monitoring, and accounting can be used to decrease energy consumption in winemaking processes or equipment. Progresses on sustainable energy use through greater energy efficiency and share of renewable energies in the wineries can contribute to the reduction of greenhouse gas emissions, and consequently, brings the wine industry closer to climate neutrality.

Abstract
Artificial intelligence (AI) is a strategy for global economic development due to its economic potential. However, the need for more transparency in AI applications generates mistrust because of the complexity of the algorithms. AI has transformed the service industry along with the development and challenge of human-AI interactions. This interaction can elicit negative feelings in consumers, creating communities to voice their disapproval and hatred of brands. Research in this area needs to be improved, and this study aims to understand the negative feelings that result from human-AI interaction in online communities (Reddit). Using sentiment analysis techniques and a qualitative approach, we aimed to identify the predominant negative emotions generated by this interaction. This study also hopes to understand the emotional effects of this interaction better, thus filling in a gap in the literature. The insights obtained can help develop more effective interaction strategies between humans and AI that can benefit brands and society. The results show a sizable presence of negative feelings such as hate anger and frustration. It is, therefore, essential to understand the negative interactions between consumers, brands and AI and the need to develop strategies to mitigate these feelings. Contributions from the academic and corporate fields emphasise the importance of monitoring feelings and promoting more positive interactions between brands and consumers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.