esa-sceva/satcom-chunk-collection huggingface dataset:
# Quality of Experience in 6G Networks: Outlook and Challenges
## 3 Enabling Technologies of Sixth Generation Networks
### Infrastructure and Topology  
Support for drone-based (unmanned aerial systems/vehicles) has already been introduced in 5G networks and its evolutions, i.e., Releases 15 through 17 ([https://www.3 gpp.org/uas-uav](https://www.3 gpp.org/uas-uav)). This support allows for added flexibility in infrastructure and a possible means of enhanced spectral efficiency. In 6G networks, it appears viable that drones will further contribute to the computing and softwarization infrastructure [47].  
As established earlier (in Release 14), satellite communications requirements have been set in response to the increasingly visible potential regarding expanded coverage, especially in mission-critical applications and specific industrial deployments. These requirements span outer space vehicles, i.e., LEO, MEO, and GEO satellites, and nonterrestrial networks. These last networks are typical cellular networks that use either spaceborne or airborne elements such as high-altitude platforms (HAPs) and unmanned aerial systems (UAS). The support for nonterrestrial elements is studied in Release 15 [48], while the study of satellite use is part of Release 16 [49].  
A direct advantage of these additions is that they can expand network coverage to maritime networks reliably and sustainably. This expansion is particularly advantageous for the shipping and oil industries, where the cost of constant monitoring can be substantially reduced. Meanwhile, the notion of controlled variable-topology in the network dramatically benefits network operators. For example, the network structure can efficiently and effectively adapt to varying demands, be it planned (as in rallies, sports events, etc.) or emerging (accidents, natural phenomena, etc.). More critically, these connectivity options will enable providers to address the digital divide, allowing for more effective Internet access to areas that were either previously neglected or unreachable [50].  
The adaptive infrastructure of 6G promises adaptive computing capabilities. Specifically, in addition to managing logical computing power in the network, the network can now redirect physical resources to areas where computing is geographically needed. In establishing this \"edge-to-cloud continuum\", the network's computing resources can be realigned (both logically and physically) depending on the existing demand [51]. This includes engaging computing resources in the user's context, e.g., in the VR visor, as part of the end-to-end resource alignment for applications.
# Biochar Amended Soils and Water Systems: Investigation of Physical and Structural Properties
## 4 Conclusions  
The selected biochar (BC), obtained in Italy from forest biomass waste material, improved the quality of soil classified as loamy sand, by considering water retention increase, plant available water (PAW), aggregate stability (SI), and specific surface area (BET-SSA). Macropores, mesopores and micropores were increased by BC in the loamy sand. Instead, BC partially improved the soil physical properties of the loam, increasing the amount of macropores as well as the aggregate stability condition, but decreasing the amount of micropores, and did not determine any significant increase in the amount of PAW. With reference to the clay, BC did not determine any improvement in the soil water retention, expressed in terms of volumetric water contents, determining a reduction in the amount of macropores, mesopores and micropores probably from the hash deposited by the BC that reduced the pore space and volume. BC did not improve the aggregate stability condition, but increased the amount of PAW, expressed in terms of volumetric field capacity and wilting point. The measured surface area, BET-SSA, was increased by BC application, with more evident effects in the loamy sand and in the loam than in the clay [57]. A tendency of the measured BET-SSA values to increase at increasing PAW was found. This investigation confirmed that BC modified the pores configuration, affecting water retention, aggregate and surface properties of soil, but with different effects, related to the different soil textures. The results also demonstrate as the BC application and interaction with soil have significant effects of hydraulic parameters due to the structural change of the mixture. Nevertheless, the effects of biochar amendment require additional research by considering other variations of soil parameters and BC nature, also in view of environmental holistic considerations of world circular economy implementation.  
Conceptualization, G.B., G.C., C.D.P., methodology, G.B., G.C., C.D.P. and F.P; data analysis, G.B. and C.D.P.; writing--original draft preparation, G.B., G.C., C.D.P.; writing--review and editing, G.B., G.C., C.D.P. and F.P.; supervision, G.B., G.C., C.D.P. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Figure 2: Relationship between the plant available water (PAW) and the specific surface area (BET-SSA). The figure also reports the fitted equation.
## 5 Comparative Analysis of Hydrocarbon Source Rock Indicators
### Thermal Evolution Characteristics  
In North Africa, the Middle East, and South China, basins within different tectonic plates are influenced by tectonic movements and the evolutionary processes of sedimentary filling, leading to significant regional variations in the thermal maturation characteristics of organic matter in hydrocarbon source rocks [77]. These variations are evident not only between basins across different plates but also within different basins of the same plate. This phenomenon reflects the direct impact of tectonic activities and sedimentary evolution on the thermal maturity of organic matter, subsequently affecting the quality of hydrocarbon source rocks and their potential for hydrocarbon generation [79].  
In the Silurian of the Wederburn Basin in North Africa, Ro ranges from 0.5% to 1.3%, and the thermal evolution of hydrocarbon source rocks is mainly oil-generating. The Illizi and Ghadames Basins exhibit Ro values of 0.9% to 2.0% and 1.1% to 2.0%, respectively, indicating the co-generation of oil and gas. In contrast, the Timimoun Basin exhibits a Ro of 1.0% to 4.0%, with the thermal evolution mainly generating gas, especially dry gas.  
The thermal maturation of Silurian thermal shales in the Middle East also varies, with Ro ranging from 0.7% to 2.5%. On average, it is greater than 2%, generally falling within the mature to over-mature stages. Moving westward, closer to the Arabian Shield, the thermal maturation gradually decreases, being in the oil-generating phase. Overall, the North African Craton Basin is characterized by a high degree of thermal evolution of homogeneous organic matter.  
In the Longmaxi shale of the middle and upper Yangtze regions, the thermal maturity of Ro ranges between 2.5% and 4.0%. In the southern Sichuan area, the thermal maturity of the Longmaxi shale is generally between 1.8% and 3.8%. In the Chongqing East-Hubei West area, the maturity ranges from 2.0% to 4.5%. The maturity shows a trend of increasing from northwest to southeast, reaching an overall over-mature stage. Comparatively, the degree of organic matter thermal evolution in the Sichuan Basin of the Yangtze region is higher than the former.
# Designing a C-ITS Communication Infrastructure for Traffic Signal Priority of Public Transport
### Motivation
As this development is based on a continued exchange of messages between vehicles and the metropolitan infrastructure instead of merely triggering at pre-defined locations, the radio coverage of C-ITS must be precisely planned, measured, and verified. Hence, the purpose of this paper is, on the one hand, to demonstrate a method to carry out planning and measurement. The system wascalibrated with praxis data, the results were then compared with factual measurements, and ultimately, these results and algorithms were validated. On the other hand, C-ITS services demonstrate how they can be combined in order to benefit from the maximum traffic potential in terms of efficiency, safety, and effectiveness.
# An Energy-Efficient Routing Algorithm
## 4 Packet Format and Energy Consumption Model  
### Packet Format  
The independent and identically distributed (i.i.d.) Bernoulli vectors provide a universal observation matrix, which is in coherence with FFT basis [8]. Hence, we select Bernoulli coefficients to encode the data gathered into one packet. The selection of random projection coefficient \(\phi_{i,j}\) is given by  
\[\phi_{i,j}=\left\{\begin{array}{c}+1,probability\frac{1}{2}\\ -1,probability\frac{1}{2}\end{array}\right. \tag{3}\]  
Figure 1: System model of 3-D underwater sensor networks.  
Figure 2: Original temperature data and its fast Fourier transform (FFT) transformation. (**a**) The original signal; (**b**) The FFT transformation of original signal.  
The packet design is illustrated in Figure 3; the header field has two sections, a 1-bit slot for projection coefficient \(\phi_{i,j}\), and \(\log_{2}N\)-bit slots for node ID. The data field is constructed by 64-bit slots, which stores the random projection values. There, two packets can be merged into one packet if they do not share any node ID and the length of header does not exceed its maximum length.
## 4 Imaging Experiments  
### Experimental Process  
According to the system structure described in Section 2.1, we constructed an experimental system platform, as shown in Figure 8. The experimental device was installed on a vibration isolation platform, and the position and relative distance of the lens and other experimental devices were manually adjusted.  
In the experiment, four different sampling rates (0.2, 0.4, 0.6, and 0.8) were selected, and compressed sensing 3D imaging was performed at these sampling rates. The test target is shown in Figure 9.  
Figure 8: Experimental system platform.  
Figure 7: Reconstructed three-dimensional image of a complex target when the sampling rates are 0.8, 0.6, 0.4, and 0.2.  
The target to be measured was a square target with a set distance of 2 m and a modulation frequency of \(5\times 10^{6}\) Hz. The measurement matrix was a Hadamard matrix, the sparse transform was FFT, and the reconstruction algorithms were BP, OMP, and TV.
# Neuroimaging of Pediatric Cerebellum in Inherited Neurodegenerative Diseases
## 1 Introduction
### Infantile Neuroaxonal dystrophy  
Infantile neuroaxonal dystrophy (PLAN, PLA2G6-Associated Neurodegeneration) belongs to the neurodegeneration with brain iron accumulation (NBIA) with onset in the first or second year of life. It is a rare neurodegenerative disorder due to mutations in the gene PLA2G6. It is characterized by psychomotor regression, profound hypotonia, gait disturbance, cerebellar ataxia, pyramidal signs, and early optic atrophy with loss of visual acuity and ultimate blindness. A progressive peripheral neuropathy leads to hyporeflexia and dementia [12; 13].  
MRI shows global atrophy of the cerebellum, mainly involving the inferior part of the vermis. Associated features are hyperintensity of the cerebellar cortex and dentati nuclei, thinning of the optic chiasm, clava hypertrophy, and, inconstantly, iron deposition in the globus pallidus and the substantia nigra [14; 15] (Figure 3).
## 2 Materials and Methods
### Analysis Methods  
ATLAS.ti is a qualitative analysis software designed to assist researchers in managing and drawing conclusions from large datasets through features such as code building and data visualization [39]. While the software has the potential for AI-assisted coding and sentiment analysis, the data in this study was opted out of this service to preserve confidentiality. As an additional confidentiality measure, all identifying data of users were removed before the transcripts were uploaded into the software. Each transcript was only identifiable by a secure user ID number.  
Coding was created by the researchers and organized through the qualitative analysis software in order to determine a general sentiment analysis. Compared to machine learning or dictionary-based coding systems, manual coding was found to have superior accuracy [40]. Qualitative coding of textual data involves examining individual quotations within a dataset and sorting them into predetermined categories referred to as codes [41]. These codes act as tags for specific comments made in the transcripts. For this study's purpose, each user comment was coded as positive, neutral, or negative. Each transcript was individually coded, and three major themes emerged from the data. These themes were then split into further categories according to the codes. The final coded categories were positive, neutral, or negative within each of the three themes: environment, usability, and user interface (UI). Coding was a collaborative effort between a pair of researchers in an attempt to reduce potential bias. Consensus coding is a team-based approach to analyzing qualitative data sets and has been shown to yield reliable results [42].  
The categories had rigid outlines that contained pre-set elements of the game. The environment included the user's gameplay experience, graphics, audio, in-game features, and level theming. Usability referred to the users' ability to navigate the game controls, as well as the perceived difficulty of the flexion-based controller. UI categorization was reserved for interactions with on-screen commands, game setup, and the eye-tracking interface.
## 3 Results and Discussion
### Biosorption Characteristics of 1 M NaOH-Treated \(H\). fusiformis
#### 3.4.2 Effect of Initial Heavy Metal Concentration
Pb\({}^{2+}\), which had a larger ionic radius and lower charge density, was taken up by _H. fusiformis_, indicating that electrostatic attraction was not a critical factor for the uptake of heavy metals by _H. fusiformis_. The removal of heavy metals by biosorption using algae has many advantages: high removal efficiency, low-cost material, reduction of chemical and hazardous sludge, regeneration of biosorbent, and metal recovery [59]. The Langmuir maximum biosorption capacities of 1 M NaOH-treated _H. fusiformis_ was compared to that of various algae such as red, green, and brown algae (Table 5), which was comparable to that of other biomass. Figure 6: Equilibrium sorption of Cd\({}^{2+}\), Cu\({}^{2+}\), Ni\({}^{2+}\), and Pb\({}^{2+}\) by 1 M NaOH-treated _H. fusiformis_.
## 2 Operation Principle
### Triangular Waveform  
In principle, the Fourier expansion of triangular waveform can be expressed as:  
\[f_{\text{tr}}(t)=DC_{\text{tr}}+A_{\text{tr}}\sum_{n=1,3,5...}^{\infty}\frac{1 }{n^{2}}\cos(n\omega t)\approx DC_{\text{tr}}+A_{\text{tr}}\Big{(}\cos(\omega t )+\frac{1}{9}\cos(3\omega t)+\cdots\Big{)} \tag{7}\]  
Comparing Equation (6) with Equation (7), Equation (6) contains all the required odd order harmonics, when we set \(\theta\
eq 0\), \(\Delta\phi=\pi/2\) and neglect the higher order harmonics, which means the DDMZM working at the quadrature point and the input signal of its two arms have a phase difference of \(\theta\). The triangular waveform can be obtained under the condition that the ratio of the fundamental and third harmonic signals \(r_{1/3}\) is approximately 9:1. According to Figure 2, the optimized operation for \(r_{1/3}=9\) will be easily realized when \(\beta\) is set to be 1.5, 1.06, and 0.75 by properly setting the input RF power at the \(\theta\) of \(\pi\)/3 rad, \(\pi\)/2 rad, and \(\pi\) rad, respectively. Besides, a \(90^{\circ}\) hybrid coupler is attached after the PD to compensate for the phase mismatch. The ultimate output electric current Equation (6) can then be further expressed as:  
\[I(t)\approx\frac{\Re|E_{\text{in}}|^{2}}{2}\bigg{[}2-4J_{1}(2\beta\sin\frac{ \theta}{2})\cos(\omega_{RF}t+\frac{\theta}{2}+\frac{\pi}{2})-\frac{4J_{1}(2 \beta\sin\frac{\theta}{2})}{9}\cos(3\omega_{RF}t+\frac{3\theta}{2}+\frac{3\pi }{2})\bigg{]} \tag{8}\]  
As can be seen from Equation (8), a theoretical full-duty triangular pulse train is successfully obtained.  
The proposed scheme is quite simple in structure and easy to implement. Since no further filtering or dispersing elements were needed in the scheme, the frequency of the generated pulse train could be tuned by simply tuning the input RF signal frequency.
## 1 Introduction
Jamming optimization tests are conducted, targeting the LEO constellation of the China Satellite Network in the southwest outskirts of Xi'an, China, in order to verify the effectiveness of the proposed method for jamming the downlink of LEO satellites compared to existing methods. The rest of the article is organized as follows: Section 2 introduces related works in the field of satellite countermeasures. Section 3 describes the distributed jamming system model for LEO satellite downlinks. Section 4 introduces the distributed jamming method for LEO satellites using the third-generation non-dominated sorting genetic algorithm. Section 5 details the experimental verification and analysis. Finally, Section 6 presents the conclusions.
# Clinical Applications of In Vivo and Ex Vivo Confocal Microscopy
###### Abstract  
Confocal laser scanning microscopy (CLSM) has been introduced in clinical settings as a tool enabling a quasi-histologic view of a given tissue, without performing a biopsy. It has been applied to many fields of medicine mainly to the skin and to the analysis of skin cancers for both in vivo and ex vivo CLSM. In vivo CLSM involves reflectance mode, which is based on refractive index of cell structures serving as endogenous chromophores, reaching a depth of exploration of 200 \(\upmu\)m. It has been proven to increase the diagnostic accuracy of skin cancers, both melanoma and non-melanoma. While histopathologic examination is the gold standard for diagnosis, in vivo CLSM alone and in addition to dermoscopy, contributes to the reduction of the number of excised lesions to exclude a melanoma, and to improve margin recognition in lentigo maligna, enabling tissue sparing for excisions. Ex vivo CLSM can be performed in reflectance and fluorescent mode. Fluorescence confocal microscopy is applied for \"real-time\" pathological examination of freshly excised specimens for diagnostic purposes and for the evaluation of margin clearance after excision in Mohs surgery. Further prospective interventional studies using CLSM might contribute to increase the knowledge about its application, reproducing real-life settings.  
skin cancer; in vivo confocal microscopy; ex vivo confocal microscopy; melanoma; basal cell carcinoma +
Footnote †: journal:  
first conceived reflectance confocal microscopy (RCM) as a device in skin imaging, thanks to progressive advances in instrument development [4; 5].  
Confocal microscopes can be used with two different modalities: in vivo and ex vivo.  
The first one is applied for in vivo exploration of tissues that can be reached directly such as the eyes, skin and mucosae or indirectly, through endomicroscopy, such as gastrointestinal and genitourinary tract, for lung and in intraoperative brain tumor imaging with the aim of a diagnosis with a quasi-histological resolution without any biopsy [6; 7].  
In vivo CLSM involves reflectance mode (reflectance confocal microscopy, RCM), exploiting backscattered light from cell structures, which is based on refractive index of cell structures and organelles, with keratin, melanin and collagen showing higher refractive indices compared to water, therefore serving as \"endogenous chromophores\" [5].  
Ex vivo CLSM can be performed in reflectance and fluorescent mode. Fluorescence confocal microscopy (FCM) is usually employed, enabling the visualization of cellular details through fluorescent agents to produce image contrast. FCM is applied for \"real-time\" pathological examination of freshly excised specimens for diagnostic purposes and for the evaluation of margin clearance after excision [7; 8; 9; 10].  
The aim of this review is to present current clinical applications of CLSM, both in vivo and ex vivo, focusing mainly on skin applications.
# Application and Assessment of Cooperative Localization in Three-Dimensional Vehicle Networks
## 8 Simulation Results
### A Test Case  
We initially simulate a test case to demonstrate the effectiveness of CL using the first four vehicles listed in Table 2. In the test case, there are no relative measurements for the first 40 s, and therefore, each state is estimated using propagation only. Then, some vehicles fall within the line of sight of other vehicles such that vehicle 1 measures the relative pose of vehicle 2, vehicle 2 measures vehicle 3, and vehicle 3 measures vehicle 4 from \(t=40\) s until \(t=160\) s. These measurements all happen simultaneously. For the final 40 s, all vehicles lose sight of each other, such that there are no relative measurements. However, vehicles 1 and 4 take absolute measurements of their own pose until \(t=200\) s possibly due to the availability of GPS or SLAM for those vehicles.  
The actual paths of the four vehicles along with those estimated with and without CL are shown in Figure 4 where significant improvement in the estimation of the path is observed after 40 s when CL is applied. We denote the norm of error in position vector \(r_{0}^{v}\) as \(\Delta\tau\) and the norm of error in orientation vector \(q^{v}\) as \(\Delta q\). Figures 5 and 6 compares the time history of \(\Delta\tau\) and \(\Delta q\) for the four vehicles with and without CL, along with their \(2\sigma\) plots. It is clear that there is a significant improvement in the estimation of the pose of all vehicles during CL (from 40 s to 160 s), including vehicle 1, whose relative pose is never measured. In addition, the absolute measurements of vehicles 1 and 4 not only greatly reduce localization errors for those vehicles but also for vehicles 2 and 3 due to their cross-covariance matrices with vehicles 1 and 4. Another observation is that there are discontinuities in state estimations when measurement scenarios are changed, caused by abrupt changes in the covariance matrix, as observed in the \(2\sigma\) plots in Figures 5 and 6. These discontinuities, however, are not of any concern as long as the algorithm remains numerically stable.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & \([\mathbf{v_{x}},\mathbf{v_{y}},\mathbf{v_{z}}]\) & \([\mathbf{\omega_{x}},\mathbf{\omega_{y}},\mathbf{\omega_{z}}]\) \\  & **Linear** & **Angular** \\ \hline \(V^{1}\) & \(-0.30\), \(0.00\), \(0.00\) & \(0.28\), \(0.55\), \(0.55\) \\ \(V^{2}\) & \(-0.35\), \(0.00\), \(0.00\) & \(0.35\), \(0.70\), \(0.70\) \\ \(V^{3}\) & \(0.40\), \(0.00\), \(0.00\) & \(0.43\), \(0.85\), \(0.85\) \\ \(V^{4}\) & \(0.35\), \(0.00\), \(0.00\) & \(0.50\), \(1.00\), \(1.00\) \\ \(V^{5}\) & \(-0.30\), \(0.00\), \(0.00\) & \(0.58\), \(1.15\), \(1.15\) \\ \(V^{6}\) & \(-0.35\), \(0.00\), \(0.00\) & \(0.65\), \(1.30\), \(1.30\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Input linear (m/s) and angular (\(\lx@math@degree\)/s) velocities of vehicles for all simulations.  
Figure 4: Vehicle actual path versus paths estimated with and without CL in the test case.  
Figure 5: Time history of vehicle position error norm in the test case.