Abstract
This preprint has been withdrawn at the request of the corresponding author due to internal coordination requirements and project data privacy considerations.

Abstract
Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. This paper introduces a two-party quantum SMC protocol designed for evaluating binary Boolean functions using single qubits. Complexity analyses demonstrate a reduction of 66.7% in required quantum resources, achieved by utilizing single qubits instead of multi-particle entangled states. However, the quantum communication cost has increased by 40% due to the amplified exchange of qubits among participants. Furthermore, we bolster security by performing additional quantum operations along the y-axis of the Bloch sphere, effectively hiding the output from potential adversaries. We design the corresponding quantum circuit and implement the proposed protocol on the IBM Qiskit platform, yielding reliable outcomes.

Abstract

Abstract
Lung cancer stands as the most prevalent and deadliest type of cancer, with adenocarcinoma being the most common subtype. Computed Tomography (CT) is widely used for detecting tumours and their phenotype characteristics, for an early and accurate diagnosis that impacts patient outcomes. Machine learning algorithms have already shown the potential to recognize patterns in CT scans to classify the cancer subtype. In this work, two distinct pipelines were employed to perform binary classification between adenocarcinoma and non-adenocarcinoma. Firstly, radiomic features were classified by Random Forest and eXtreme Gradient Boosting classifiers. Next, a deep learning approach, based on a Residual Neural Network and a Transformer-based architecture, was utilised. Both 2D and 3D CT data were initially explored, with the Lung-PET-CT-Dx dataset being employed for training and the NSCLC-Radiomics and NSCLC-Radiogenomics datasets used for external evaluation. Overall, the 3D models outperformed the 2D ones, with the best result being achieved by the Hybrid Vision Transformer, with an AUC of 0.869 and a balanced accuracy of 0.816 on the internal test set. However, a lack of generalization capability was observed across all models, with the performances decreasing on the external test sets, a limitation that should be studied and addressed in future work.

Abstract
The efficient operation of Autonomous Underwater Vehicles (AUVs) is crucial for various applications, including weather forecasting, marine life sustainability, underwater mining, renewable energy harvesting, and defense operations. Given the limited energy storage available on AUVs, improving propulsion efficiency is a key challenge. Variable Buoyancy Systems (VBSs) offer a promising alternative to traditional propeller-based propulsion by consuming energy only during buoyancy adjustments, thereby reducing overall power consumption. This study builds on prior simulation-based research by experimentally evaluating the energy consumption and performance of different PID-based controllers for a prototype driven by an electromechanical VBS. The experimental results show that by adequately choosing a closed loop control algorithm, significant energy savings can be obtained without compromising the control performance.

Abstract
Virtual Reality (VR) offers immersive experiences through advanced interaction mechanisms and rich sensory stimuli but is often inaccessible to blind people due to its over-reliance on visual feedback. While prior work has investigated specific aspects of VR accessibility, there is little knowledge on how to design full, feature-rich VR experiences accessible to blind people. This paper presents the design and evaluation of a VR Boxing experience, developed through participatory design with an ex-professional boxer who is now blind. A user study with 15 blind participants explored their perceptions of the three-mode experience developed - Heavy Bag Training, Coach Training, and Combat - to inform the design of accessible VR experiences. Our findings highlight the importance of combining natural movement, rich auditory feedback, and well-timed guidance that also fosters user independence. Furthermore, they demonstrate the value of structured progression in complexity, while also opening opportunities for engaging spatial awareness and coordination training.