esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Therefore, in the presence of water bodies or flooded areas, values lower than the surroundings have to be expected for the combinations of spectral reflectances acquired in the VNIR (VIS and NIR) region, like the ratio R\({}_{\text{NIR}}\)/R\({}_{\text{VIS}}\)[15; 16] or the difference R\({}_{\text{NIR}}\)-R\({}_{\text{VIS}}\)[17]. In this paper, we further assess the RST-FLOOD performance in detecting flooded areas by investigating a few days of the flood event that affected the Basilicata and Puglia regions (southern Italy--Figure 1) in December 2013 [18; 19; 20; 21; 22; 23]. In order to investigate this event, we firstly implemented the MODIS-based approach using data acquired in its first two channels at 250 m of spatial resolution. In the previous work [12], the feasibility of this data providing reliable information about flooded areas was only preliminarily explored, referring to a much larger event than the one analyzed here in terms of flood extent. Then, exploiting the RST-FLOOD inherent characteristics, we exported the proposed approach on Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) imagery. The VIIRS instrument extends and improves upon a series of measurements initiated by its operational and research predecessors, the AVHRR flown on board multiple National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (Metop) satellites, and the National Aeronautics and Space Administration (NASA) MODIS, aboard the Terra and Aqua satellites, due to its better spatial and spectral resolution as well as radiometric accuracy and stability. The accuracy of the achieved results has been evaluated through a comparison analysis with a Landsat Enhanced Thematic Mapper Plus image (ETM+ on Landsat 7) acquired concurrently with MODIS and VIIRS data. The main aim of this study is to assess the potential of RST-FLOOD, when implemented on medium spatial resolution images, in effectively analyzing floods occurring within small catchments.
###### Abstract  
The adoption of wireless medical technologies in hospital environments is often limited by cellular coverage issues, especially in indoor areas with complex structures. This study presents a detailed radio spectrum measurement campaign conducted at the Cova da Beira University Hospital Center (CHUCB), using the NARDA SRM-3006 and R&S(r)SME6 equipment. The signal strength and quality of 5G NR, LTE, UMTS, and NB-IoT technologies were evaluated. Critical coverage gaps were identified, particularly at points 17, 19, and 21. Results revealed that operators MEO and NOS dominate coverage, with MEO providing better 5G NR coverage and NOS excelling in LTE signal quality. Based on the results, the localized installation of femtocells is proposed to improve coverage in these areas. The approach was designed to be scalable and replicable, with a planned application at Cumura Hospital (Guinea-Bissau), reinforcing the applicability of the solution in contexts with limited infrastructure. This work provides both technical and clinical contributions to achieving ubiquitous cellular coverage in healthcare settings.  
WABAN; wireless communications; mobile networks; ubiquitous cellular coverage; NB-IoT; radio spectrum measurements; ICT
## 3 Results and Discussion
### Pyridones: UV-Vis and Electrochemical Measurement Perspective
Pyridones with a methyl group in position 6 of the pyridone ring (**3** and **4**) did not show activity in BR buffer, while pyridones with a -OH group in position 6 were electrochemically active (**5-8**). This implies that electrooxidation is in close relationship with the presence of the -OH group in position 5 of pyridones **5-9**. The effect of substituents on **5-9** was further examined in terms of their relevance and contribution to electrooxidation activity. SWV measurements were performed since this method usually shows more apparent peak currents compared to CVs [37]. In addition, the position of Ep overlaps in CV and SWV measurements. SWVs of pyridones **5-9** containing a -OH group in position 6 of the ring in the BR electrolyte with pH 1.81 and pH 9.94 are presented in Figure 4a,b and Table S1, considering \(E_{\rm p}\) and \(j_{\rm p}\) values. The first peak appearing at 0.2 V in an acidic solution and \(-0.2\) V in an alkaline solution originated from the GC electrode in a blank solution (dotted line), as well as the currents attributed to those peaks observed in the presence of the examined pyridones. For further analysis, peaks at E > 0.5 V were considered since they corresponded to the oxidation of pyridone derivatives. By comparing the results shown in Figure 4, it can be noticed that reaction currents were higher in alkaline media and that all examined molecules exhibited a shift in peak potential towards less positive values with regard to the corresponding values obtained in an acidic medium. In addition, one well-defined voltammetric peak was established in the oxidation of pyridones **5**, **8** and **9**, while **6** and **7** exhibited two peaks. The second peak noticed in compounds **6** and **7** can be correlated with the N-substituted pyridine scaffold [38]. Figure 3: Forward scan of CVs of 5 \(\times\) 10\({}^{-4}\) M 9 in BR buffer at v = 50 mV s\({}^{-1}\), T = 295 K. Inset: Correlation between peak potential of compound 9 and pH value.
# Joint Power Charging and Routing in Wireless
## 3 Optimization Algorithms
### Joint Optimization of Routing and Charging
#### 3.2.3 Crossover and Mutation  
The crossover operation is used to mix the individuals to increase their fitness. Considering that the chromosomes are expressed by a tree data structure, a single-point crossover is designed to exchange a partial chromosome. For the two individuals selected to crossover, we first select common nodes between these two trees; then, one common node among them is randomly selected as the crossover point. After that, the subtrees rooted from this node are swapped to generate two new routing trees. We illustrate an example of single-point crossover and the individual repair operation in Figure 4, where the common node is node 11. The crossover between parent A and parent B is performed by switching the subtree rooted at node 3 with that of parent B. After the crossover, the new generated routing tree in child A has a routing loop of 2-3-5. As such, we repair this routing loop by randomly deleting link \(e_{23}\). Additionally, nodes 5 and 8 are randomly linked to child B to ensure the feasibility.  
In the mutation operation, the elements in both matrices of each individual are randomly altered to diversify the population after the crossover operation, which will pave the way towards global optima. In this paper, once a node (denoted as \(n\)) is selected as the mutation point with probability \(q_{m}\), the mutation replaces the path \(n\) to the sink node by a randomly generated new path. It is observed that the designed genetic operation still generates routing trees, indicating that routing constraints are still satisfied.  
Figure 4: Tree-based crossover operation.
###### Abstract  
The L band frequency shows high sensitivity to sea surface salinity. More stable brightness temperature (TB) measurements are required for L-band radiometers to reduce salinity retrieval errors than for high-frequency radiometers. Due to the complexity of L-band synthetic aperture radiometers, a carefully selected cold-sky target should be viewed using an L-band synthetic aperture radiometer for the purpose of absolute TB calibration since the celestial sky is relatively well characterized and stable in the L band. A novel, effective cold-sky calibration strategy is presented in this paper. The strategy of cold-sky calibration of the synthetic aperture radiometer is applied when and where the antenna main lobe points to the 'flat' celestial sky, and the impact of each type of foreign source, such as the sun or moon, on visibility values should be minimized in the meantime. Additionally, antenna thermal stability is also considered, which can cause antenna deformation, and the antenna patterns are affected. A high-precision and high-fidelity simulator is built for the cold-sky calibration optimized strategy. The orbital beta angle is introduced to characterize the variation in space environment temperatures. A planet that is considered spherical in shape requires significantly less computation than an ellipsoid one in the simulator. The trade-off study results for the planet shape assumption in the cold-sky calibration simulator are presented. Finally, the calibration uncertainty and performance are assessed.  
s 202416971. 10.3390/rs16060971  
1
# A Comprehensive Review on Music Transcription
## 4 Challenges for Music Transcription
### Subjectivity  
Music transcription involves the process of converting an audio recording of music into a symbolic representation, such as sheet music or a score [95; 96]. While transcription aims to capture the essential elements of the music, it is important to acknowledge that there is an inherent degree of subjectivity involved in the process. This subjectivity arises from the fact that different transcribers, even with expertise in music theory and transcription techniques, may interpret the same musical performance in slightly different ways [94].
## 2 Field Testing on Uplift Capacity in Composite-Anchor Cable Uplift Pile
### Static Load Test on Site  
This experiment consists of three different groups of test piles, with each group being tested multiple times and the results averaged. The relevant details of the experiment are provided in Table 1[20]. The Type-A test pile is classified as a conventional pile, while the Type-B and Type-C test piles are categorized as composite-anchor cable uplift piles. Two different hole-forming methods were employed for the three groups of test piles. The static load test for each individual pile followed the applicable technical specifications outlined in the Technical Code for the Testing of Building Foundation Piles (JGJ 106-2019) [23] and the Technical Code for Building Pile Foundations (JGJ) 94-2008) [24]. Hydraulic jacks were used to apply the load, and displacement sensors were utilized to measure the displacement of the pile top. The objective was to generate real-time load-displacement curves.  
The field test consists of three main steps: loading, terminating loading, and unloading. During the loading phase, the test pull-out force is applied gradually in stages using an equal load approach. According to the test protocol, each stage load is set at 10% of the ultimate bearing capacity calculation value, with the first stage load set at 20%. After each stage of load application, the displacement of the pile top is automatically recorded at specific time intervals, including at 5, 15, 30, 45, and 60 min, and then every 30 min thereafter. Loading continues once the displacement change rate is \(\leq\)0.1 mm/h and occurs twice in a row, indicating relative stability has been achieved. The loading should be terminated under the following conditions: (1) If the applied load or deformation value meets the design acceptance requirements. (2) If the stress in the tensioned strands of the reaction device or composite-anchor cable reaches the design value of the strand, including strand fracture. (3) If the displacement value of the pile top in the last stage of load exceeds five times that of the previous stage. (4) If the cumulative displacement value of the pile top exceeds 100 mm [24]. The unloading phase is carried out in stages, with each stage of unloading being twice the load of the corresponding loading stage. The unloading is performed evenly and equally. After each stage of unloading, the pile remains under the load for 1 h, and the displacement is measured three times at 15, 30, and 60 min. Following complete unloading, the pile remains under the load for an additional 3 h, and displacement is measured three times at 15, 30, 60, 90, 120, 150, and 180 min [25]. Upon completion of the test, the displacement acquisition system and pull-out force application system are sequentially and slowly removed.
## 2 Methods
### Providing Access to Environmental Data  
Environmental data are typically provided in a raster image file where each picture element (pixel) represents a rectangular area on the earth. The value of each pixel then represents an environmental measurement at that location. These files are then organized into \"layers\" of data which may contain multiple rasters to cover a large spatial extent. Common environmental variables include data from weather stations, field measurements, and remotely sensed data. Variables derived from weather station data include a wide variety of climatic variables such as minimum or maximum annual temperature, number of growing degree days, annual precipitation, humidity, and the amount of sunlight available at each location, typically provided as Photosynthetically Active Radiation. While these measurements are typically acquired from individual weather stations, they often are provided as raster files with continuous cover for a large geographic region such as Daymet [26].  
The GODM system was created to allow immediate access to field data and to create potential species distribution maps at different extents including local, national, and global scales and at multiple spatial resolutions. This capability required a very flexible, robust, and high-performance system for integrating field data with many environmental data layers. A relational database was used to create a hierarchical structure for the environmental data. The structure encodes all of the available files by location, resolution, date, and type of information they contain. The system then selects the correct data based on the required resolution, area being viewed, and whether the data are intended for viewing or analysis.  
We loaded a large number of default climate layers for the United States into the system from the BioClim dataset [27]. Since Maxent supports creating predicted future distributions of species based on future climate predictions, we added the option of running potential distributions in the year 2050. We used uncompressed Tagged Image File Format (TIFF) files to allow access to the original data for analysis. This design allows Web users to select a single \"layer\" with environmental information such as minimum temperature; the system can then select exactly which layers are needed for analysis. Each time a model is run, the environmental layers are cropped to the area of interest and then saved in the file format desired by the modeling algorithm.
## 4 Discussion
For example, in the case of a building that does not exist anymore but for which there are archival terrestrial photos of neighboring buildings, the total time to develop a 3D model of a non-existent building is about 4-7 h. Specifically, the first stage, i.e., the measurement of photo points on existing neighboring buildings with a tachymeter, takes (depending on the number of photo points) about 1-3 h. The Projective Transformation of archive ground photos takes about 1-2 h. Finally, the estimated time to produce a solid model and apply texture is about 2 h.  
Therefore, the challenge lies in reducing the time required for the development of 3D building models by automating the stages that can be automated. Traditional data processing techniques, including image processing, are often time-consuming; thus, future research plans involve utilizing automated, advanced processing methods such as deep learning. The use of deep learning for detecting building outlines from maps or identifying facades in photographs is an integral part of the planned approach. The last but not least advantage of the proposed method is that the participation of historians in the model development process is not necessary, although their knowledge can be very valuable and useful. Historians are the recipients of the 3D models and can use them in their own work.
# A Synergistic Elixir-EDA-MQTT Framework for Advanced Smart Transportation Systems
## 5 Details of Prototype System
### Event-Driven Design and Components
#### 5.1.1 Events  
The system operates on a foundation of defined events, representing significant occurrences within the system's lifecycle. Core event types include the following:  
* CabRequested: Initiated by a passenger application, signifying a ride request with details like passenger ID and destination.
* CabRequestAccepted: Emitted by a driver upon accepting a ride request, confirming their intent to fulfill the request.
* CabArrived: Indicates the driver's arrival at the passenger's pickup location.
* TripStarted: Marks the commencement of the passenger's journey with the chosen driver.
* TripEnded: Signifies the completion of the trip upon reaching the desired destination.  
Additional event types can be readily incorporated to cater to future needs and system enhancements. These events are structured data payloads published to the MQTT broker, facilitating efficient and decoupled communication. Upon receiving an event, the dispatch service transitions the corresponding request through its state machine, moving it from pending to assigned, and, subsequently, through other relevant states. For instance, a CabRequest event triggers the transition from pending to assigned, while a TripEnded event marks the final state. This explicit state management allows for clear observation and control of the system's evolution.
# Practical Comparison Between the CI/CD Platforms Azure DevOps and GitHub
## 6 Pricing and Cost Considerations
The cost of meeting compliance standards must also be considered for organizations operating in highly regulated industries such as finance, healthcare, and government. Azure DevOps benefits from Microsoft's extensive compliance framework, supporting certifications such as ISO 27001 [9], SOC 2 [10], GDPR [11], HIPAA [12], and FedRAMP [13]. GitHub also maintains strong compliance standards, but enterprise security and governance features are only available under GitHub Enterprise Cloud or GitHub Enterprise Server. While Azure DevOps has better built-in compliance support, it requires integration with other Microsoft security tools. GitHub requires an enterprise subscription to access advanced security features, potentially increasing costs depending on the organization's security and compliance needs [35]. Beyond the base subscription fees, organizations must also consider hidden costs, including data storage, network bandwidth, and extended support plans. Azure DevOps charges for additional storage beyond the free limit for repositories, artifacts, and pipeline logs. GitHub applies usage limits for API calls, GitHub Actions execution, and dependency security scans. An important long-term cost consideration is developer onboarding and productivity. GitHub's intuitive interface and developer-friendly workflows reduce training costs and onboarding time. Azure DevOps, due to its more complex interface and enterprise feature set, may require more training and configuration effort. For large organizations, the time required to train teams on a CI/CD platform translates into indirect costs, making GitHub a more cost-effective solution for small teams and Azure DevOps a better long-term investment for enterprises that need scalability and compliance integration. The cost-effectiveness of Azure DevOps and GitHub depends on the organization's size, the complexity of its development workflows, and its infrastructure strategy. Azure DevOps provides a more flexible pricing model, allowing organizations to select individual services and optimize costs using self-hosted agents. It is ideal for enterprises that require full DevOps integration within the Microsoft ecosystem. GitHub's tiered pricing model offers a more streamlined and predictable cost structure. Enterprise features and advanced security tools are locked behind higher-tier plans, making them potentially more expensive for large organizations that require premium security and governance controls. For individual developers, open-source projects, and small teams, GitHub is often the more cost-effective choice due to its free public repository hosting and built-in CI/CD minutes. However, Azure DevOps provides better long-term cost efficiency for large enterprises that need fine-grained DevOps control, hybrid cloud flexibility, and integration with Microsoft security solutions, particularly for organizations managing large-scale software projects and complex compliance requirements.
## 4 Experiments and Results
### Basic Settings  
#### 4.1.1 Datasets  
Two real-world large-scale OD datasets from the Beijing subway were used in the experiments, which are presented in Table 2. According to Table 2, these two OD datasets were collected in 2021 and 2022, named BJSubway2021 and BJSubway2022, respectively. For BJSubway2021, the date range is from 2021.9.14 to 2021.10.17 and from 2021.12.14 to 2021.12.29, the number of data records is 137 million, the number of stations is 369, and thus the OD matrix dimension is 369 \(\times\) 369. BJSubway2021 contains 50 days, of which 36 days, 7 days, and 7 days were used as training set, validation set, and test set, respectively. For BJSubway2022, the date range is from 2022.1.1 to 2021.1.9 and from 2022.1.18 to 2022.2.21, the number of data records is 98 million, the number of stations is 372, and thus the OD matrix dimension is 372 \(\times\) 372. BJSubway2022 contains 44 days, of which 32 days, 6 days, and 6 days were used as the training set, validation set, and test set, respectively. For both BJSubway2021 and BJSubway2022, the time range in a day was set from 6:00 to 23:00; each record contains the entry station ID, the exit station ID, the entry time, and the number of passengers entering the station; And the time interval is 5 min.
## 2 Materials and Methods
### Dataset  
We used CDW data from 3046 patients who underwent robot-assisted radical prostatectomy treatment at tertiary care institutions involved in PCa. Data were obtained for the period October 2011 to October 2021. In total, 1021 patient data related to BCR were used in the study. We used follow-up data of more than 60 months from surgery. Therefore, we predicted BCR likelihood at 5 years after surgery. A total of 283 patients with BCR and 738 patients with non-BCR for a follow-up period of more than 60 months were included. The remaining 2025 patients did not have a full follow-up period of at least 60 months and did not have a robot-assisted prostatectomy treatment, and missing critical data were excluded. Our study defines BCR as when the PSA nadir value exceeds 0.2 ng/mL in a PCa patient who had completed RP treatment [27]. We used a total of 10 input variables to predict the BCR: age at diagnosis, BMI, initial PSA value, Gleason score (sum) group, pathology T stage group, extracapsular extension (ECE), seminal vesicle (SV), perineural invasion (PNI), lymph node metastasis (LNM), and surgical margin (SM).