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Given the imperative for advanced wireless networks in the next generation and the rise of real-time applications within wireless communication, there is a notable focus on investigating data rate performance across various fading scenarios. This research delved into analyzing the effective throughput of the shadowed Beaulieu-Xie (SBX) composite fading channel using the PDF-based approach. To get the simplified relationship between the performance parameter and channel parameters, the low-SNR and the high-SNR approximation of the effective rate are also provided. The proposed formulations are evaluated for different values of system parameters to study their impact on the effective throughput. Also, the impact of the delay parameter on the EC is investigated. Monte-Carlo simulations are used to verify the facticity of the deduced equations., Comment: 18 pages

Resection and whole brain radiotherapy (WBRT) are the standards of care for the treatment of patients with brain metastases (BM) but are often associated with cognitive side effects. Stereotactic radiosurgery (SRS) involves a more targeted treatment approach and has been shown to avoid the side effects associated with WBRT. However, SRS requires precise identification and delineation of BM. While many AI algorithms have been developed for this purpose, their clinical adoption has been limited due to poor model performance in the clinical setting. Major reasons for non-generalizable algorithms are the limitations in the datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models to improve generalizability. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and whole tumor (including peritumoral edema) 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging feature information. We used a streamlined approach to database-building leveraging a PACS-integrated segmentation workflow., Comment: 12 pages, 2 figures, 1 table

Entanglement is a valuable resource in quantum information technologies. The practical implementation of entangled photon sources faces obstacles from imperfections and defects inherent in physical systems, resulting in a loss or degradation of entanglement. The topological photonic insulators, however, have emerged as promising candidates, demonstrating an exceptional capability to resist defect-induced scattering, thus enabling the development of robust entangled sources. Despite their inherent advantages, building programmable topologically protected entangled sources remains challenging due to complex device designs and weak material nonlinearity. Here we present a development in entangled photon pair generation achieved through a non-magnetic and tunable anomalous Floquet insulator, utilizing an optical spontaneous four-wave mixing process. We verify the non-classicality and time-energy entanglement of the photons generated by our topological system. Our experiment demonstrates a substantial enhancement in nonclassical photon pair generation compared to devices reliant only on topological edge states. Our result could lead to the development of resilient quantum sources with potential applications in quantum technology., Comment: 24 pages, 14 figures

Visual servoing for the development of autonomous robotic systems capable of administering UltraSound (US) guided regional anesthesia requires real-time segmentation of nerves, needle tip localization and needle trajectory extrapolation. First, we recruited 227 patients to build a large dataset of 41,000 anesthesiologist annotated images from US videos of brachial plexus nerves and developed models to localize nerves in the US images. Generalizability of the best suited model was tested on the datasets constructed from separate US scanners. Using these nerve segmentation predictions, we define automated anesthesia needle targets by fitting an ellipse to the nerve contours. Next, we developed an image analysis tool to guide the needle toward their targets. For the segmentation of the needle, a natural RGB pre-trained neural network was first fine-tuned on a large US dataset for domain transfer and then adapted for the needle using a small dataset. The segmented needle trajectory angle is calculated using Radon transformation and the trajectory is extrapolated from the needle tip. The intersection of the extrapolated trajectory with the needle target guides the needle navigation for drug delivery. The needle trajectory average error was within acceptable range of 5 mm as per experienced anesthesiologists. The entire dataset has been released publicly for further study by the research community at https://github.com/Regional-US/, Comment: Accepted at IROS 2024, 1 supplementary video

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space.The BraTS-METS 2023 challenge successfully curated well-annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied clinical environments and providing personalized volumetric reports to patients undergoing BM treatment.

Efficient artificial photosynthesis systems are currently realized as catalyst- and surfacefunctionalized photovoltaic tandem- and triple-junction devices, enabling photoelectrochemical (PEC) water oxidation while simultaneously recycling CO2 and generating hydrogen as a solar fuel for storable renewable energy. Although PEC systems also bear advantages for the activation of dinitrogen - such as a high system tunability with respect to the electrocatalyst integration and a directly controllable electron flux to the anchoring catalyst through the adjustability of incoming irradiation - only a few PEC devices have been developed and investigated for this purpose. We have developed a series of photoelectrodeposition procedures to deposit mixed-metal electrocatalyst nanostructures directly on the semiconductor surface for light-assisted dinitrogen activation. These electrocatalyst compositions containing Co, Mo and Ru in different atomic ratios follow previously made recommendations of metal compositions for dinitrogen reduction and exhibit different physical properties. XPS studies of the photoelectrode surfaces reveal that our electrocatalyst films are to a large degree nitrogen-free after their fabrication, which is generally difficult to achieve with traditional magnetron sputtering or e-beam evaporation techniques. Initial chronoamperometric measurements of the p-InP photoelectrode coated with the Co-Mo alloy electrocatalyst show higher photocurrent densities in the presence of N2(g) than in the presence of Ar at -0.09 V vs RHE. Indications of successful dinitrogen activation have also been found in consecutive XPS studies, where both, N 1s and Mo 3d spectra, reveal evidence of nitrogen-metal interactions.