This study delves into the complex dynamics of Underwater Wireless Optical Communication (UWOC) in varied Harbor water conditions. Focusing on four distinct types of Harbor water, the research employs the Monte Carlo method to simulate photon transmission and analyze critical UWOC characteristics. Key parameters such as the transmitted full divergence angle, received aperture, and Field of View (FOV) are meticulously evaluated for their impact on communication efficacy. The study first explores the relationship between laser power variation, attenuation length, and divergence angle, revealing how different water qualities influence received power and time delay spread. Notably, the received normalized power loss and time delay spread are found to be more significantly affected by communication distance than water quality. In addition, under the condition of small received aperture and FOV, the influence on normalized power loss and time spread is more obvious in Harbor water. The findings offer novel insights into the challenges of UWOC in Harbor waters, particularly in terms of light scattering and absorption properties, and contribute to the optimization of communication systems in such complex underwater environments. Furthermore, the analysis of time pulse spread in turbid water quality is of great significance for the analysis and improvement of underwater wireless optical timing, ranging and positioning.

Radiotherapy commonly utilizes CBCT for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into HU values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow FOV systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent GAN processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm’s ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

Spectrally weighed irradiance on the corneal plane is often used to determine the visual and non-visual potency of light. Spectral irradiance or illuminance is measured with a diffuser in the so-called 2π geometry (i.e., a hemispheric measurement). Due to anatomical conditions, the human binocular field of view (FOV) does not correspond to a hemisphere but is occluded upwards and downwards. FOV-restricted measurements are scarce, however, and thus the error when using hemispheric measurements is yet to be determined. For our study, we designed and 3D printed FOV occlusions as attachments to spectral measurement devices. Measurements with and without the occlusion were taken in different lighting situations in the laboratory (light from different directions) and in real-world conditions (light typically from above). Our measurements show a reduction of visual and melanopic values due to the FOV occlusion ranging from negligible to over 60% for realistic scenarios. Further, the reduction was comparable for visual and melanopic parameters, as the distribution of light in the FOV was generally spectrally homogeneous. In the case of an exemplary and artificial laboratory situation, however, the melanopic daylight (D65) efficacy ratio changed by more than a factor of 2 only due to the FOV occlusion. Finally, head orientation showed a marked impact on all quantities. Our results reveal the potential for considerable error when just evaluating and comparing vertical, hemispheric measurements in experiments and non-visual lighting design projects. We thus encourage the (additional) use of a FOV occlusion for eye-level measurements in typical viewing directions and provide open-source 3D-print files.