Abstract
Lung cancer represents a significant health concern necessitating diligent monitoring of individuals at risk. While the detection of pulmonary nodules warrants clinical attention, not all cases require immediate surgical intervention, often calling for a strategic approach to follow-up decisions. The Lung-RADS guideline serves as a cornerstone in clinical practice, furnishing structured recommendations based on various nodule characteristics, including size, calcification, and texture, outlined within established reference tables. However, the reliance on labor-intensive manual measurements underscores the potential advantages of integrating decision support systems into this process. Herein, we propose a feature-based methodology aimed at enhancing clinical decision-making by automating the assessment of nodules in computed tomography scans. Leveraging algorithms tailored for nodule calcification, texture analysis, and segmentation, our approach facilitates the automated classification of follow-up recommendations aligned with Lung-RADS criteria. Comparison with a previously reported end-to-end image-based classification method revealed competitive performance, with the feature-based approach achieving an accuracy of 0.701 +/- 0.026, while the end-to-end method attained 0.727 +/- 0.020. The inherent explainability of the feature-based approach offers distinct advantages, allowing clinicians to scrutinize and modify individual features to address disagreements or rectify inaccuracies, thereby tailoring follow-up recommendations to patient profiles.

Abstract
Since the 1970s, extensive halite extraction in Macei & oacute;, Brazil, has resulted in significant geological risks, including ground collapses, sinkholes, and infrastructure damage. These risks became particularly evident in 2018, following an earthquake, which prompted the cessation of mining activities in 2019. This study investigates subsidence deformation resulting from these mining operations, focusing on the collapse of Mine 18 on 10 December 2023. We utilized the Quasi-Persistent Scatterer Interferometric Synthetic Aperture Radar (QPS-InSAR) technique to analyze a dataset of 145 Sentinel-1A images acquired between June 2019 and April 2024. Our approach enabled the analysis of cumulative displacement, the loss of amplitude stability, the evolution of amplitude time series, and the amplitude change matrix of targets near Mine 18. The study introduces an innovative QPS-InSAR approach that integrates phase and amplitude information using amplitude time series to assess the lifecycle of radar scattering targets throughout the monitoring period. This method allows for effective change detection following sudden events, enabling the identification of affected areas. Our findings indicate a maximum cumulative displacement of -1750 mm, with significant amplitude changes detected between late November and early December 2023, coinciding with the mine collapse. This research provides a comprehensive assessment of deformation trends and ground stability in the affected mining areas, providing valuable insights for future monitoring and risk mitigation efforts.

Abstract
The application of optical fibers in optogenetics is rapidly expanding due to their compactness, cost-effectiveness, sensitivity, and accuracy. This paper introduces a twin-core optical fiber (TCF) sensor employing a Mach-Zehnder interferometer (MZI) to monitor the optogenetic response of opsin-expressing human dental pulp stem cells (hDPSCs) based on refractive index (RI) measuring. In order to improve the RI sensitivity of the sensor, an in fiber Mach-Zeander modulator formed using TCF optics segments can detect changes in the RI in the surrounding medium, and in order to improve the RI sensitivity of the sensor, it is proposed to etch one side of the TCF cladding. The RI sensitivity of the sensor was obtained 233.62 nm/RIU in the range of 1.33-1.4 RIU and 870.01 nm/RIU in the range of 1.4-1.43 RIU, R2 = 0.99. simulation results show that in terms of sensor sensitivity and spectral response, there is a good agreement between the theoretical and experimental results, indicating that the TCF-MZI sensor can perform optical neural recording. In vitro experiments monitored wavelength changes in opsin-expressing and non-opsin-expressing in human dental pulp stem cells (hDPSCs) during optogenetic stimulation with 473 nm pulsed illumination. The results revealed that optical stimulation of ChR2 opsin-expressing hDPSCs leads to active the light sensitive ion channel and changing the effective RI of the surrounding medium. The neural activity is driven by changes in intracellular and extracellular ion concentrations, which lead to alterations in the RI of the cell medium RI variations detectable by the sensor. The novel sensor structure demonstrated its ability to detect RI changes in the cell medium during optogenetic stimulation and fiber optic sensors can be a good candidate for optical recording of the neural activity. Beyond these in vivo applications, label free fiber optic biosensors-based IR measurement can be used for all optical multifunctional probe in stimulation, recording, and sensing of neuroscience applications.

Abstract

Abstract
Following the widespread interest of both the scientific community and companies in using autonomous vehicles to perform deliveries, we propose the 'Drone-Assisted Vehicle Routing Problem with Robot Stations' (VRPD-RS), a problem that combines two concepts studied in the autonomous vehicles literature: truck-drone tandems and robot stations. We model the VRPD-RS as a mixed-integer linear program (MILP) for two different objectives, the makespan and operational costs, and analyze the impact of adding trucks, drones, and robots to the delivery fleet. Given the computational complexity of the problem, we propose a General Variable Neighborhood Search (GVNS) metaheuristic to solve more realistic instances within reasonable computational times. Results show that, for small instances of 10 customers, where the solver obtains optimal solutions for almost all cases, the GVNS presents solutions with gaps of 0.7% to the solver for the makespan objective and gaps of 0.0% for the operational costs variant. For instances of up to 50 customers, the GVNS presents improvements of 21.5% for the makespan objective and 8.0% for the operational costs variant. Furthermore, we compare the GVNS with a Simulated Annealing (SA) metaheuristic, showing that the GVNS outperforms the SA for the whole set of instances and in more efficient computational times. Accordingly, the results highlight that including an additional drone in a truck-drone tandem increases delivery speed alongside a reduction in operational costs. Moreover, robot stations proved to be a useful delivery element as they were activated in almost every studied scenario.

Abstract
This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency of the Distribution Network (DN). A Demand Response Program (DRP) integrated with Home Energy Storage Systems (HESSs) is presented to optimize the energy consumption of household consumers. Each consumer implements a Smart Home Energy Management System (SHEMS) to optimize their energy consumption according to their desired comfort and preferences. To modify the consumption pattern of household consumers, a Real-Time Pricing (RTP) algorithm is proposed to reflect the energy price of the wholesale market to the retail market and consumers. In addition, a Self-Healing System Reconfiguration (SHSR) program integrated with Distributed Energy Resources (DER), reactive power compensation equipment, and Energy Storage Systems (ESSs) is presented to manage the DN energy and restore the network loads in disruptive events. The reconfiguration operation is performed by converting the isolated part of the DN from the upstream network to several self-sufficient networked virtual microgrids without executing any switching process. Real data of California households are considered to model the home appliances and HESSs. The proposed comprehensive program is validated on the modified IEEE 123-bus feeder in normal and emergency operating conditions.