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 an approach to tackle memory safety by replicating Rust’s Mid-level Intermediate Representation (MIR) Borrow Checker. Our solution uses static analysis and successive source-to-source code transformations to be composed upstream of the compiler, ensuring maximal compatibility with existing build systems. This allows us to apply the memory safety guarantees of the rustc compiler to C code with fewer changes than a rewrite in Rust. In this work, we present a comprehensive study 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. We have evaluated the prototype on the CHStone and bzip2 benchmarks. This prototype correctly identified violations of the ownership and aliasing rules, and exposed incompatibilities between such rules and common C patterns, which can be addressed in future work.

Abstract
Cybersickness refers to the negative symptoms caused by exposure to a Virtual Reality (VR) experience. The literature is consensual that cybersickness is a key factor in an experience, as the non-existence of cybersickness provides an optimal virtual experience. Thus, it is of utmost importance to evaluate cybersickness when assessing VR applications to understand the impact of this factor on the user experience and, ultimately, on the VR application viability. However, there is a lack of Portuguese instruments to evaluate this variable. To tackle this, this aimed to translate and validate the Simulator Sickness Questionnaire (SSQ) to Portuguese so it can be used with the Portuguese population and maintain its psychometric properties. The new instrument was validated using a sample of 603 Portuguese subjects aged between 16 and 79. Based on the observed results, the obtained theoretical model shows that the Portuguese version of the SSQ is valid for properly evaluating cybersickness in VR experiences with Portuguese samples.

Abstract
The progressive and complex nature of Parkinson's disease (PD) may largely benefit from regular and personalised monitoring, which is beyond the current clinical practice and routinely available systems. This paper proposes a simple and effective system to address this issue by using a wearable device to quantify a key PD's motor symptom - gait impairment as a proof-of-concept for a future broader approach. In this study, 60 inertial signals were collected from the ankle in 41 PD patients during a clinical standard gait assessment exercise. Each exercise iteration was classified by a specialised neurologist based on the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). A signal processing and feature extraction pipeline was employed to characterise gait, followed by a statistical analysis of their ability to differentiate between the 5 levels of impairment. The results revealed that 4 of the 8 studied features exhibited high discriminatory power between different severity levels of gait impairment, with statistical significance. The distinguishing capability of these 4 extracted features - gait consistency, rotation angle, mean height and length of steps - holds great promise for the development of a gait severity quantification remote monitoring for PD patients at home or on the move, proving the concept of the usefulness of wearable devices for regular and personalised PD symptom monitoring.

Abstract
This paper presents an optically transparent 2-bit unit-cell for reflective intelligent surface applications in Wi-Fi 6E. The unit-cell is based on a metalmesh and can be reconfigured electronically by adjusting the voltage applied to a varactor diode. The performance of the RIS is demonstrated through simulation, which shows that the results are in good agreement with the theoretical predictions.

Abstract
Power-to-Hydrogen (P2H) clean systems have been increasingly adopted for Virtual Power Plant (VPP) to drive system decarbonization. However, current models for the joint operation of VPP and P2H often disregard the full impact on grid operation or hydrogen supply to multiple consumers. This paper contributes with a VPP operating model considering a full Alternating Current Optimal Power Flow (AC OPF) while integrating different paths for the use of green hydrogen, such as supplying hydrogen to a Combined Heat and Power (CHP), industry and local hydrogen consumers. The proposed framework is tested using a 37-bus distribution grid and the results illustrate the benefits that a P2H plant can bring to the VPP in economic, grid operation and environmental terms. An important conclusion is that depending on the prices of the different hydrogen services, the P2H plant can increase the levels of self-sufficiency and security of supply of the VPP, decrease the operating costs, and integrate more renewables.

Abstract
Capturing high-resolution imagery of the Earth's surface often calls for a telescope of considerable size, even from low Earth orbits (LEOs). A large aperture often requires large and expensive platforms. For instance, achieving a resolution of 1 m at visible wavelengths from LEO typically requires an aperture diameter of at least 30 cm. Additionally, ensuring high revisit times often prompts the use of multiple satellites. In light of these challenges, a small, segmented, deployable CubeSat telescope was recently proposed creating the additional need of phasing the telescope's mirrors. Phasing methods on compact platforms are constrained by the limited volume and power available, excluding solutions that rely on dedicated hardware or demand substantial computational resources. Neural networks (NNs) are known for their computationally efficient inference and reduced onboard requirements. Therefore, we developed a NN-based method to measure co-phasing errors inherent to a deployable telescope. The proposed technique demonstrates its ability to detect phasing errors at the targeted performance level [typically a wavefront error (WFE) below 15 nm RMS for a visible imager operating at the diffraction limit] using a point source. The robustness of the NN method is verified in presence of high-order aberrations or noise and the results are compared against existing state-of-the-art techniques. The developed NN model ensures its feasibility and provides arealistic pathway towards achieving diffraction-limited images. (c) 2024 Optica Publishing Group