esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
The proposed MARL-based codebook learning design demonstrated the capability to dynamically adjust beam configurations based on user distributions and environmental topography, effectively mitigating the interference within densely populated urban environments. Leveraging uplink CSI and RSRP for reward modeling, this method reduces the need for extensive random beam searches and minimizes the number of beams required in the learned codebook, significantly reducing the beam training overhead. The proposed system outperformed traditional 32-beam beamsteering codebooks in both LOS and nLOS conditions with fewer beams by using a simple clustering scheme and a designed reward function that facilitated interference-free beam learning. MARL-based approach showcased its adaptability by efficiently managing complex propagation environments, ensuring high data rates and reliable connectivity even in challenging conditions. Comparative analysis highlighted that the proposed MARL approach achieved performance close to the optimal level, providing robust and efficient beamforming solutions for multiuser MIMO systems. This research contributes to the field by offering a practical and efficient solution for beamforming in massive MIMO systems, paving the way for enhanced multiuser communication in future wireless networks. However, the approach is not without limitations. One major limitation is the complexity of the MARL framework, which may pose scalability issues as the number of users and beams increases, potentially requiring higher computational resources. Another limitation is the user clustering method, which requires the complete reclustering and retraining of the MARL agents after significant environmental changes. Additionally, the simulations were conducted in controlled environments using ray-tracing models, and real-world deployments may present unforeseen challenges that could impact the system's performance and adaptability. Further research is needed to address these limitations and enhance the robustness of the proposed method in diverse and dynamic real-world scenarios.  
Data curation, M.B. and D.D.M.; Formal analysis, K.K.S.; Investigation, M.B. and K.G.; Methodology, M.B. and K.K.S.; Project administration, J.I.; Software, D.D.M.; Supervision, K.K.S., K.G. and J.I.; Validation, M.B. and K.K.S.; Visualization, M.B.; Writing--review and editing, D.D.M., K.G. and J.I. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study were generated dynamically using simulation models developed by the authors. The map used for the ray tracing channel simulation is sourced from [[https://www.openstreetmap.org](https://www.openstreetmap.org)]([https://www.openstreetmap.org](https://www.openstreetmap.org)), which provides crowd-sourced map data worldwide. As the data are not derived from any other publicly available dataset and were produced through the methods outlined in the manuscript, they are not available in a public repository.  
The authors declare no conflicts of interest.
## 4 Case Study  
The proposed methods have been applied to a district in Zone 9 used as case study in the city of Milan, Italy. The \"Citta Study\" neighborhood which is located around the technical university pole of the city was chosen as test bed for the implementation of the survey campaign.  
An area of approximately 2000 m\({}^{2}\) was surveyed in two nights of measurements (15 July and 23 July 2019). The area was chosen, among other reasons, because of the high average occurrence of car accidents and injured people from 2001 to 2017 as shown in Section 3.1. The surroundings of the Politecnico di Milano campus showed a concentration of degradation of the urban components and, sometimes, of social distress (Figure 15).  
Moreover, the Politecnico di Milano university campus is currently undergoing a series of refurbishments and regeneration interventions, involving the retrofit of some existing buildings, the construction of new ones and the renovation of public open spaces that will lead to a new configuration of the area. Thus, an analysis of the current light quality in the area will be useful data for the designers involved in the renovation project.  
As described in the previous section, the IoT sensor has been designed in order to optimize its compactness and portability. Each of the IoT sensors can be mounted on a mobile mechanical structure for tracking the level of luminosity on the road. During the case study, the sensor has been mounted on an odometer to allow easy monitoring. An operator performed the recognition on the neighborhood area involved in the case study using the odometer equipped with the light sensor. A single IoT sensor was used to collect all data during the two nights of the duration of the experiment. Each measurement campaign generated 2000 sampled data. It should be highlighted that the IoT sensor can be mounted on any mobile mechanical structure, such as an unmanned aerial vehicle (UAV) or unmanned ground vehicle (UGV), to create an autonomous measuring system for the mapping of an entire city. Such an approach has the great advantage that the IoT sensors are monitoring a predefined and well-known path. Notwithstanding such benefits, the integration of the light sensors on autonomous monitoring system is out of the scope of the current research work and it will be investigated in future research work.  
Figure 14: Interface between the Geographic Information System (GIS)-based informative system and the Internet of Things (IoT) light sensor.  
Figure 15: Cont.
# Femtosecond Laser Textured Surfaces for Radiative Cooling: Black Metals
## 2 Experimental: Materials and Methods
### Elemental and Chemical Binding Analysis  
Elemental analysis was conducted on energy dispersive X-ray spectroscopy (EDS) coupled with an SEM to capture surface element profiles (depth sensitivity up to \(\sim\)1 \(\upmu\)m). Chemical bonding analysis was conducted using X-ray photoelectron spectroscopy (XPS) with the Kratos Nova XPS (up to 10 nm) on both ablated and non-ablated surfaces. For XPS spectrum analysis, single-peak (singlet) fitting, which does not account for spin-orbit splitting, is generally sufficient to represent most cases. However, when single-peak fitting does not capture all spectral features, doublet fitting, which considers spin-orbit splitting, is employed to provide a more accurate representation. In this research, the copper sample used singlet fitting for the Cu 2p peak with binding energy (930-938 eV), and doublet fitting was used for tungsten and aluminum samples for W 4f (30-40 eV) and Al 2p (71-77 eV), respectively. The binding energy positions and their full-width half maximum (FWHM) were determined based on the XPS database [28], and the previous studies on aluminum [29; 30; 31; 32; 33] and copper [34; 35; 36].
## 5 Discussion
### Petrogenesis
Despite no or little basalt flux during the Early Devonian, the long-lived heat accumulation in a thick crust could induce a magmatic burst after more than 20 Ma [67; 68]. Therefore, the Haerdaban volcanic rocks were mainly derived from the partial melting of felsic crustal rocks induced by the long-lived heat accumulation with no or minimal basalt flux. The low Sr (41.2 to 120 ppm) and high Rb (56.2 to 372 ppm) concentrations of the samples imply that the fractional crystallization may be involved in the production of the A-type volcanics. The depletion of Ba, Sr, P, Ti, and Eu anomalies in the trace element patterns, as well as the high differentiation index also supported the fractional crystallization. The fractional crystallization of plagioclase and K-feldspar minerals can account for the depletion of Ba, Sr, and Eu. The P and Ti anomalies can be attributed to the fractionation of apatite and Fe-Ti oxides. It is noted that the \(\varepsilon_{\rm Nd}\)(t) values of samples range from \(-1.8\) to \(-4.0\), but \(\varepsilon_{\rm Hf}\)(t) values of zircon range from +6.13 to +14.8, showing that Nd and Hf isotopic compositions are decoupled. The Nd-Hf isotopic decoupling may be related to the elevated Lu/Hf of the rocks, which could be attributed to the removal of zircon with low Lu/Hf, or the involvement of garnet with high Lu/Hf during the re-melting of the crust [69; 70; 71]. The characteristic of positive Zr and Hf anomalies, crust-like Lu/Hf ratios (0.06 to 0.16), do not support the removal of zircon during the re-melting of the crust. The HREE of samples much higher than the upper continental crust (UCC) and lower  
Figure 8: Plot of (Na\({}_{2}\)O + K\({}_{2}\)O)/CaO versus Zr + Nb + Ce + Y, FeOT/MgO versus Zr + Nb + Ce + Y discrimination diagrams for the Early Devonian volcanic rocks from Haerdaban area in the northern margin of Yili Block (**a,b**, reference area after [58]). continental crust (LCC) (Figure 7a), combined with the high zircon saturation temperatures (T\({}_{Zr}\) = 783 \({}^{\circ}\)C to 952 \({}^{\circ}\)C), showing that the breakdown of garnet may have been involved during crustal re-melting. The breakdown of garnet would likely affect the Lu-Hf rather than the Sm-Nd isotopic systematics, so the Nd isotopic compositions may be more consistent with the source rocks [71]. The oldest inherited zircon age (1465 Ma, sample ZJ-TW1) is in agreement with the two-stage Nd model ages (1305-1476 Ma), which further emphasizes that the breakdown of garnet during crustal re-melting results in the elevated HREE and \(\epsilon_{Hf}\) (t) values of the melts. In summary, the Early Devonian volcanic rocks from Haerdaban area are considered to be generated by re-melting of lower crust induced by the long-lived heat accumulation with no or minimal basalt flux and subsequently fractional crystallization is significant.
# Internet of Things (IoT) Cybersecurity: Literature Review and IoT Cyber Risk Management
## 2 Literature Review
### Evaluation of the Literature  
The literature review of both the qualitative and quantitative approaches to cybersecurity risk management shows that the qualitative approaches focus on high-level frameworks. These qualitative frameworks recognize the relevance of other frameworks and share a similar cybersecurity risk management process. For example, much of the NIST Cybersecurity Framework includes standards of ISO 27001 geared to certify information security requirements. The CMMI Cybersecurity Platform is aligned with leading frameworks such as ISO 27001 and the NIST Cybersecurity Framework.  
However, none of the frameworks explicitly address the IoT cybersecurity ecosystem and its impacts on risk management. Furthermore, the frameworks do not provide any guide on how cybersecurity investment can be made for each cybersecurity project and how financial resources can be allocated among multiple cybersecurity projects. For example, the NIST Cybersecurity Framework provides no details of how a firm should conduct cost-benefit analysis when deciding on the organization's implementation tier [58]. Organizations are left with investing in cybersecurity projects by gut feeling.  
The quantitative approaches to cybersecurity risk management focus on the risk assessment and the quantification of cyberattacks and impacts. There are only a few studies applying the quantification approaches. They do not explain how the quantification process can be integrated into the entire risk management process. They also do not provide a detailed cost-benefit analysis nor allocation of financial resources to multiple cybersecurity projects.  
Based on the literature review, it has been determined that IoT cyber risk management did not receive proper attention. The current risk assessment approaches are inadequate in dealing with the complex array of connections among the wide range of devices and actors [3]. The review of the previous studies motivates us to develop an IoT cyber risk management framework that improves on the existing frameworks and quantitative approaches to risk assessment. This study integrates the qualitative and quantitative approaches and proposes a four-layer IoT cyber risk management framework that provides an essential guide for effective risk management.
# Design of an Underwater Acoustic Waveform and Integrated System for Communication and Detection
## 4 Simulations
### Simulations on Ambiguity Function and BER of CPM-LFM Signals in AWGN Channels
To verify the effectiveness of the proposed two-step frequency and phase offset estimation method, we compare the BER of SS-CPM-LFM under both AWGN and BELLHOP underwater acoustic channels. As shown in Figure 23, without frequency and phase offset compensation, the BERs of CPM-LFM and CPM are close to each other. In this case, the BER is around 0.5, making normal communication impossible. When the traditional preamble frame structure is employed in the CPM-LFM system, and the preamble is used for frequency and phase compensation, the system performance improves significantly, achieving a BER of \(10^{-2.8}\) at an SNR of 8 dB. However, the SS-CPM-LFM combined with the two-step frequency and phase offset estimation method reduces the system BER to \(10^{-3.6}\) at an SNR of 8 dB. This result is close to the BER of SS-CPM-LFM in an AWGN channel. It demonstrates that the SS frame structure, along with the two-step frequency and phase compensation method, can effectively mitigate the multipath and Doppler effects inherent in the underwater acoustic channel, thereby improving the system's communication performance.
## 1 Introduction
Accordingly, almost all dynamic modeling of FT slurry reactors has focused on the commercial scale of slurry bubble column reactors and there has been no detailed transient computer model at pilot scale (reactor diameter \(<\) 1 m) for SBCR so far. In fact, the modeling of laboratory scale FT slurry is a more difficult task because of the wealth of dynamic features, such as the prediction of rise velocity of small bubbles and wall effects, which make hydrodynamic parameters quite sensitive to system properties, and the presence of impurities [18]. Thus, the present work investigates, for the first time, the transient analysis of a slurry FT reactor in lab-scale under supported catalyst cobalt for all key components of Fischer-Tropsch synthesis developed by a MATLAB code. This comprehensive modeling enables us to predict the behavior of several slurry reactor parameters such as CO conversion, FT selectivity, \(\alpha\)-value and temperature profile under variable loads of synthesis gas. Furthermore, the results of the modeling are in good agreement with the experimental data. The experimental data is adopted from a Master of Science thesis which was conducted using the Fischer-Tropsch research plant. The plant is located in town of Gussing in Austria [11; 12]. Appendixs A and B reflect the experimental measurements for both base load (syngas flow rate of 5 m\({}^{3}\)/h) and change load conditions (syngas flow rate of 3.5 m\({}^{3}\)/h and 7.5 m\({}^{3}\)/h) in one specific run [12].
# Sub-Milliwatt Transceiver IC for Transcutaneous Communication of an Intracortical Visual Prosthesis
## 3 Implanted Transceiver
### IR-UWB Transmitter
The shape response is similar if they are designed to pass the same band, and does not impact non-coherent detection of the OOK IR-UWB signal at the external side in our 3-7 mm near-field scenario. In open air, far-field transmission, pulse shaping filters are relevant to make the system satisfy the FCC mask. However, in our context, with transmission through 3-7 mm of skin, already 20-25 dB loss is seen, which causes the radiated power at the surface of the head to be already far below the FCC mask. This is based on our transmitter delivering \(-27\) dBm and the aforementioned attenuation through skin. In spite of these losses, the link budget can still be met. Figure 2: Schematic of the IR-UWB transmitter. Note that the presented and measured IC does not include the filter nor the antenna.
# A Review on Millimeter-Wave Hybrid Beamforming for Wireless Intelligent Transport Systems
## 3 An In-Depth Analysis of the mmWave Hybrid Beamforming Landscape
### User
#### 3.1.1 Single-User  
To provide hybrid beamforming implementation in a single-user system, high directivity is needed to minimize the impact of fading. The number of data streams is also an important prospective in beamforming to make it more reliable. The hybrid beamforming consists of two stages; if high performance is required, both stages need design flexibility.  
* **Directional Beamforming** The mm-wave spectrum is used by 5G beamformers to transmit and receive numerous beams. Using directed beamforming with multiple beams in MIMO and reusing the spatial spectrum is the greatest technique to decrease fading in the beamspace domain. Antenna components have zero bearing on beamspace, which is defined by the total number of beams on the transmit and receive sides. Reclaiming space while in single-access mode is possible using the space division single access (SDASA) protocol, a subset of space-division multiple access (SDMA). The multi-beam notion for single-user (SU) MIMO may provide data speeds in the gigabits per second range by using mm-wave and SDSA [22].
* **Data Streams Constraint Beamforming** In particular scenarios where the number of RF chains exceeds the number of data streams, additional phase modifications are required. There is a need to either increase the number of RF chains with shorter phase shifts or decrease the number of RF chains with longer ones. The result is an improvement in spectrum efficiency [23].
* **Dual-Stage Beamforming**  
Figure 4: In-depth analysis of Mm-wave hybrid beamforming landscape.  
Mm-wave MIMO uses beamforming to send energy in the way that the user wants. There is a middle ground between the inaccuracy of entirely analog methods and the expense and energy consumption of entirely digital methods; digital subband and analog broadband components are the result. Typically, a completely digital two-stage beamforming approach is generally used, which is based on a real-world-proven zero-forcing (ZF) and singular-value decomposition of the channel response [24].
# Storytelling with Image Data: A Systematic Review and Comparative Analysis of Methods and Tools
## 3 Task 1. Building the Foundation for Organizing and Curating the Raw Image Data
### Curation: Image Preparation Using Cleaning and Preprocessing
#### 3.1.3 Image Integration  
The process of image integration might involve preprocessed imaging, segmentation of the image, and registration of image [24]. Image integration has the ability to improve the results of several image-processing applications. Active sensors are the root of volumetric range image integration technologies [25]. The integration technique should resist severe outliers in the range of pictures. The vast majority of 2D data integration solutions rely on data-level picture fusion [26]. Integration of range photos in a robust manner is a crucial step in creating high-quality 3D images [25]. Due to the fact that range pictures and specific range maps from 2D images may contain a significant number of outliers, any integration strategy attempting to produce high-quality models should be more resilient. [PERSON] et al. [27] have devised an image integration approach for data absorbed from multifocus image fusion utilizing multiscale picture decomposition and saliency identification. They were able to integrate just focused and sharpened portions into the merged picture.
# Fine-Scale Population Estimation Based on Building Classifications: A Case Study in Wuhan
## 2 Materials and Methods
### Classification of Urban Buildings
#### 2.2.1 Geometric Relationships and Classification of Space  
_POI_ data provides spatial details and the attributes of buildings, which are important for the quantitative identification of building types in cities. According to a previous study [35], over 20 types of _POI_ data are available, and they can be divided into three categories comprising commercial service, public service, and residential building (Table 1).  
Considering the geometric distribution of _POI_ and buildings, the relationships between them can be divided into three categories: (1) buildings with only a single type of _POI_, such as public service _POIs_; (2) various types of _POIs_ related to buildings, such as residential _POIs_ and commercial service _POIs_; and (3) buildings with no _POI_ types. The three geometric relationships are shown in Figure 3.  
Due to the different functions of urban buildings, buildings are divided into different types, comprising commercial services, public services, residential, and commercial- residential mixed (shops at low levels and residential buildings above). According to the relationship between the spatial distributions of buildings and _POIs_, the classification rules for buildings are defined as follows.  
1. If a building is located in an area with only residential type _POIs_, the building is a residential building.
2. If a building is located in an area with both commercial service _POIs_ and residential _POIs_, the building is a low-rise commercial building with residences above.
3. For buildings without _POIs_, the type is predicted with the _TF-IDF_ method.