esa-sceva/satcom-chunk-collection huggingface dataset:
# 5G New Radio Open Radio Access Network Implementation in Brazil: Review and Cost Assessment
## 4 Challenges and Opportunities in Implementing 5G NR Open RAN in Brazil
### Opportunities  
The 5G technology is transforming the Brazilian national economy as its implementation expands, opening opportunities for its improvement. The anticipated effects are estimated to reach around USD 60 billion by 2030, equivalent to approximately 0.9% of the GDP. These effects will be felt in various sectors, including improved access to healthcare and education, advances in the manufacturing industry, enhanced public security responses, improved traffic conditions and driving safety, and reduced pollution [42].  
The primary sectors directly affected by implementing Open RAN in Brazil include agribusiness, smart cities, technology, media and telecommunications, gas and energy, utilities, transportation and logistics, and manufacturing. Substantial economic benefits are expected to facilitate the adoption of Industry 4.0 practices and the implementation of private networks.  
The distributed topography of rural areas certainly improves the Open RAN deployment network economy. Removing vendor lock-in and enabling network sharing allows deployment in regions with low population density, reducing CAPEX and saving on OPEX. Virtualization and the built-in ability to update equipment remotely make it even more sense in a geographically dispersed network [44].  
The topology utilized by Open RAN allows for the distribution of the processing solution at the network's edge, enabling applications with strict requirements to meet their goals and become achievable. Some ultra-reliable low-latency communication (uRLLC) requirements include transmitting data end-to-end within 1 ms with \(10^{5}\) reliability. The RAN must be meticulously configured and ready to support the UEs attached to the gNodeB to achieve this level of performance. Edge cloud computing technology can facilitate the relocation of the virtualized solution closer to the UEs, thus reducing latency and errors across the 5G network infrastructure.  
One of the significant advantages of Open RAN is the sharing of base stations, transport links, and data centers. The factors that sustain this model are economic benefits, long-term relationships, and a focus on management and operation. Due to infra-sharing, we have CAPEX and OPEX optimization, no duplication of equipment, reduced service costs, scalability, and implementation savings [27].
## 2 Methods  
### GNSS Tracking Networks  
#### 2.1.1 iGMAS Tracking Network  
To analyze the signals of multi-GNSS constellations, and to investigate the PNT performance of the multi-GNSS, the iGMAS has been established by China. A continuous tracking network for BDS and other GNSS satellites has been deployed by iGMAS. Up to July 2022, iGMAS comprises 21 operational stations, 8 in China and 13 abroad. All of these data collected by iGMAS tracking stations could be downloaded from the iGMAS data archive centers, e.g., Wuhan University and National Time Service Center (NTSC, CAS).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Center** & **Description** & **Mountpoint** \\ \hline \multirow{4}{*}{IGS01} & GPS-only orbit and clock corrections based on & \\  & IGS ultrarapid orbits; Single-Epoch GPS clock & SSRA01 IGS0 \\  & combination, RETINA solution & \\  & GPS-only orbit and clock corrections based on & \\  & IGS02 & IGS ultrarapid orbits; Kalman Filter GPS clock & SSRA02 IGS0 \\  & combination, BNC solution & \\  & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits; Kalman Filter & \\  & GPS+GLONASS clock combination, BNC & \\  & solution & \\  & BKG & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits & \\  & CNES & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits & \\  & CAS & GPS+GLONASS orbit and clock corrections & \\  & based on internal ultrarapid orbits & \\  & DLR/GSOC & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits & \\  & GPS-only orbit and clock corrections based on & \\  & IGS ultrarapid orbits & \\  & GPS-only orbit and clock corrections based on & \\  & GPS-only orbit and clock corrections based on & \\  & internal ultrarapid orbits & \\  & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits & \\  & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits & \\  & GPS+GLONASS orbit and clock corrections & \\  & based on IGS ultrarapid orbits & \\  & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Status of IGS RTS combinations and individual analysis center products.
# Deep Learning-Based Hip X-ray Image Analysis for Predicting Osteoporosis
## 4 Experimental Results
### Image Classification Results
#### 4.2.3 Categorization Results Using Image Segmentation  
We used the best performance of each of the two previous classification metrics as the test for the image segmentation experiment and tested whether the addition of segmentation improved accuracy. Table 10 shows the results of the classification experiments of the pre-trained model using DenseNet121 on the total hip as a T-score indicator and the pre-trained model using VGG16 on the total hip as a BMD indicator. In the classification results after adding image segmentation, no matter whether using T-score or BMD as the index for osteoporosis classification, overall, the accuracy and F1-score did not improve, and the accuracy decreased from 74% to about 60%.
## 5 Mission Technical Implementation
### Payload Design: IPDALLS System and nadir LiDAR
Dielectric beam splitters will be used to separate the 1,064 nm first- and the 532 nm second-harmonic channels, for which the depolarization ratio will be analyzed using a polarizing assembly. Low dark current analogue avalanche photodiodes (APDs) are needed for the near-IR channels, whilst photo-multiplier tubes (PMTs) or appropriate (vacuum) APDs will be used for the 532 nm wavelength. Gated diaphragms are used to avoid telescope cross-talk and direct sun exposure. The outgoing pulse is sampled for pulse diagnostic and calibration and transient recorder triggering. Hardware averaging over multiple range-bins or pulses onboard the spacecraft was deemed inappropriate in [4], which will be an important factor to consider when sizing the data downlink.
# Flying Real-Time Network to Coordinate Disaster Relief Activities in Urban Areas +
## 3 Proposed Network System
### Initial Network Deployment
The simulation results show that 16 TWUs were required to fully cover the work area without any loss in terms of connectivity; however, 8 units were enough to address at least the 80% of the communication requests. Considering these results and the fact that several communication instances can be happening simultaneously between a TWU and a set of first responders, we can evidently expect that the use of these networks actually provide the stable and real-time digital communication support required in the study scenario. Figure 3: Simulation results considering various numbers of TWUs (2, 4, 8, 16) and particular allocations for them to provide stable and real-time digital communication support. Algorithm 1, used in these simulations to perform the initial placement of TWUs, represents a first approximation to help generate variations in the TWUs' locations for more complex deployment scenarios. In that direction, the next section presents two meta-heuristics to search for sub-optimal deployments of the network nodes, in order to reach maximum communication coverage in the current work area, using the minimum active number of nodes and energy consumption.
# Image Analysis of Dynamic Brain Activity Based on Gray Distance Compensation
## 2 Automated Detection of Cellular Activity  
The fiber optic brain imaging system prototype, as previously described [5], consists of a 473-nm laser, a fiber bundle, a charge-coupled device (CCD) camera (GS2-FW-14S5M, Point Gray, San Diego, CA, USA), and custom-designed micro-objective lenses. The expanded 473-nm laser beam is coupled into the fiber bundle, then the light out of the fiber distal tip projects onto the brain tissue and the fluorescent light emitted from cells in the brain is collected by the same fiber, reflected off a dichroic mirror, and detected by the CCD camera. Transgenic mice that express the calcium indicator GCaMP3 in astrocytes (GLAST-CreER;R26-lsl-GCaMP3) [3] were used for this study. All experiments were performed in strict accordance with protocols approved by the Animal Care and Use Committee at Johns Hopkins University.  
The automated activity region detection method consists of two main steps, as shown in Figure 1. In step 1, serial brain images are enhanced to extract cellular activity areas based on gray transformation and distance compensation. Cellular activity centers are located and matched within frames in step 2.
## 5 Experimental Validation  
It is difficult to test the pressure distribution, velocity magnitude, turbulent intensity, streamlines, and vortices of the hydrostatic thrust bearing with various OLDRs. To decrease the experimental difficulty and cost, the proposed hydrostatic thrust bearing with the OMDR of 2 is manufactured and assembled based on Figure 1 to validate the employed CFD simulation method of this paper.  
The load capacity and stiffness of the hydrostatic thrust bearing under the aforementioned operating conditions are tested based on the constructed experimental rig, as shown in Figure 14. If the experimental results are in good agreement with the simulation data, the proposed CFD simulation method of this paper will be verified and then other simulation results of this paper will be indirectly validated.  
The dial indicator is employed to measure the displacements of the thrust part, and the weights combined with the gravity of the thrust part are used to balance the load capacity of the thrust bearing. Oil is not supplied to the thrust bearing at the beginning and there is no gap between the thrust bearing and the thrust part. When the thrust bearing is supplied oil with gauge total pressure of 2.5 MPa, the weights are adjusted so that the displacement of the thrust part is 20 \(\upmu\)m and 19 \(\upmu\)m, respectively. Then the load capacities of the thrust bearing are obtained with oil film thicknesses of 20 \(\upmu\)m and 19 \(\upmu\)m, respectively.  
The stiffness is calculated by the difference method with the tested load variation and the displacement variation. The tested load capacities and stiffness are shown in Table 2.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Performance** & **Displacement** & \
\begin{tabular}{c} **Computational Fluid Dynamics** \\ **(CFD) Simulation Results** \\ \end{tabular} & **Experimental Data** & **Error** \\ \hline \multirow{2}{*}{Load capacity (N)} & 20 \(\upmu\)m & 6811 & 6800 & 0.16\% \\ \cline{2-5}  & 19 \(\upmu\)m & 7331 & 7315 & 0.22\% \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Oil film stiffness \\ (N/\(\upmu\)m) \\ \end{tabular} } & \multirow{2}{*}{520} & \multirow{2}{*}{515} & \multirow{2}{*}{0.96\%} \\ \cline{2-5}  & & & & \\ \end{tabular}
\end{table}
Table 2: Comparisons of performance specifications of the hydrostatic thrust bearing with OMDR of 2 between CFD simulation results and experimental data.  
Figure 14: Experimental bench of the hydrostatic thrust bearing with OMDR of 2. (**a**) Schematic diagram of the test rig; (**b**) experimental setup.  
It can be found from Table 2 that the errors between the CFD simulation results and the experimental data are very small, validating that the CFD simulation results of this paper are acceptable.
## 7 Maintenance and Evolution
### Configuring Product Variants  
The application engineering process begins with selecting and configuring core assets to develop ML product variants tailored to specific requirements. Using variability models as a guide, datasets, model architectures, pipelines, and hyperparameters are customized to align with the product's domain, operational environment, and performance objectives. For example, in a space system, telemetry data analysis pipelines might be adapted to handle different satellite subsystems or orbital configurations.
## 3 Materials and Methods
### HPLC-DAD Analysis of the Phenolic Compounds before and after Acidic Hydrolysis  
Phenolic compounds from olive oils were extracted and analyzed according to the IOC official method [19]. Phenolic compounds were extracted with a MeOH:H\({}_{2}\)O 80:20 _v/v_ solution and immediately analyzed by an HP1100 system equipped with an autosampler, a column heater module, and a quaternary pump, and coupled to a diode array detector (DAD) (all from Agilent Technologies). A SphereClone ODS(2), 5 um, 250 \(\times\) 4.6 mm id column was used; elution was performed by using the H\({}_{2}\)O (pH 3.2 by formic acid)/acetonitrile/methanol eluents and using the gradient reported in the IOC method. The injection volume was 20 \(\upmu\)L. Identification was carried out at 280 nm. Syringic acid was used as the internal standard and the content of phenolic compounds was expressed in mg/kg of tyros.  
The acidic hydrolysis was then applied on the hydroalcoholic extracts to evaluate the total content of free and bound tyrosol and hydroxytyrosol [23]: 300 \(\upmu\)L of the extract was added with 300 \(\upmu\)L of H\({}_{2}\)SO\({}_{4}\) 1.0 M, the mixture was maintained in an oven for 2 h at 80 \({}^{\circ}\)C, diluted using 400 \(\upmu\)L of water, and analyzed by HPLC-DAD. Analysis was performed using an HP1200 liquid chromatograph equipped with HP DAD (Agilent Technologies). An RP18 column, 150 \(\times\) 3 mm (5 \(\upmu\)m) Gemini (Phenomenex, Torrance, CA, USA) was used; flow rate was 0.4 mL/min. The eluents were H\({}_{2}\)O acidified to pH 3.2 with formic acid (A) and acetonitrile (B); the following linear solvent gradient was applied: from 95% to 70% A in 5 min, to 50% A in 5 min, to 98% B in 5 min, then a plateau of 5 min and finally to 95% in 2 min. The total time of analysis was 22 min.
# Leakage Detection Method of Coal Mine Power Supply System Based on 3 AC
## 2 Leakage Protection Method Based on 3 AC Detection Circuit
### Mathematical Model Based on 3 AC Detection Method
According to the equivalent model diagram, the following derivation can be made:  
\[\dot{I}_{C0}=\dot{U}_{A}\mathrm{j}\omega C_{1}+(\dot{U}_{B}+\dot{U}_{C}) \mathrm{j}\omega C_{2}+\dot{U}_{0}\mathrm{j}\omega(C_{1}+2C_{2}) \tag{3}\]  
where \(C_{1}=2C_{2}=2C_{3}\), \(\dot{U}_{B}+\dot{U}_{C}=-\dot{U}_{A}\), Substitute it into Equation (3), we can get:  
\[\dot{I}_{C0}=\dot{U}_{A}\mathrm{j}\omega C_{2}+\dot{U}_{0}\mathrm{j}\omega 4C _{2} \tag{4}\]  
That is:  
\[\dot{I}_{C0}=\mathrm{j}\omega C_{2}(\dot{U}_{A}+4\dot{U}_{0}) \tag{5}\]
## 1 Introduction
Chordae tendineae length measurements are required for mitral valve procedures involving the implantation of artificial chordae [10]. It is nevertheless challenging to determine their optimal length because direct observation is limited to physical measurements made inside the flacied heart during surgery, along with 2D transgastric long-axis images which require that the image plane be aligned with the entire chord to achieve accurate results [11]. While 3D transgastric TEE ultrasound is safe and easily acquired during routine TEE imaging (adding approximately 3-5 min to the procedure), it is rarely employed due to the limited visibility of the leaflets and field-of-view limitations preventing the entire length of the chordae from being captured. Without the ability to see the entire subvalvular apparatus in the same image data as the standard en-face view of the leaflets, transgastric image information is of very limited clinical value. In our prior work on volume compounding using TEE volumes, we explored a workflow using only the semi-simultaneous registration strategy and a distance-based weighted average blending [12]. Our prior approach was able to successfully produce compounded volumes; however, the registration component of the workflow was not robust, could fail depending on the order in which the volumes were processed, and the blending approach induced imaging artefacts. In this study, we propose an improved method to register and compound transgastric and en-face volumes utilizing a combination of semi and fully simultaneous registration with a novel weighting function for blending overlapping re gions to reduce compounding artefacts. This provides an avenue for combining common cardiac ultrasound views into a single volume with reduced noise and fewer dropout artefacts. Many image compounding techniques involve the use of a tracked probe and were targeted at combining multiple transthoracic views [6]. Our method differs from these previous methods as it does not require any external tracking of the ultrasound probe, and it has been tailored for use with TEE probes to combine 3D mid-esophageal and transgastric volumes that can be acquired as part of a standard diagnostic imaging session. In the en-face volumes, the mitral valve is clearly visible, and in the transgastric views, the chordae are very clear, as these views are nearly perpendicular to each other. By combining both the en-face and transgastric views, we can maintain optimal imaging for both structures in a single compounded volume. Integrated leaflet and chordae geometry in a single volume will greatly improve the cardiac surgeons' ability to accurately measure the length of individual chordae (a crucial factor in neochordae repair techniques [9]) and plan their repair strategy.
# A New Method for Calculating Prediction Parameters of Surface Deformation in the Mining Area
## 3 Methodology
### Analysis of Influencing Factors of PIM in Huainan Mining Area
#### 3.2.2 Horizontal Movement Coefficient  
The horizontal movement coefficient refers to the ratio between the maximum horizontal surface movement value and the maximum surface subsidence value under the critical mining of horizontal or nearly horizontal coal seams. It mainly depends on the dip angle of the coal seam and the thickness of the loose layer. Based on the collected data,  
Figure 2: Random model of particle medium movement.  
mining depth and the thickness of the loose layer of some typical working faces in the Huainan mining area, the regression formula between horizontal movement coefficient \(b\) and loose layer and mining depth ratio \(h_{\text{s}}/H_{0}\) could be expressed as Equation (2):  
\[b=-0.2521h_{\text{s}}/H_{0}+0.4785 \tag{2}\]  
The fitting results are shown in Figure 4, The goodness of fit \(R^{2}\) = 0.7318. The fitting results show that the horizontal movement coefficient is closely related to thickness of unconsolidated layer and mining depth, and decreases with increase of the proportion of unconsolidated layer in the mining depth.
# Circularly Polarized High-Gain Fabry-Perot Cavity Antenna with High Sidelobe Suppression
## 2 Proposed FPCA Design and Operation
### Design of the PRS and AMC Unit Cells and Feeder  
Figure 2 illustrates the geometry of the PRS. The PRS unit cell is composed of three copper layers placed on two identical (\(t=1.52\) mm) Taconic RF-35 substrates. The top and bottom metal layers are connected by a metallic 0.018 mm thick through-hole (\(d_{3}=1\) mm) [see Figure 1], which passes through an etched circular hole (\(d_{2}=1.9\) mm) at the center of the middle ground layer [see Figure 2b]. These two identical substrates of the PRS are firmly bonded by a 0.04 mm epoxy FR4 layer with relative permittivity \(\varepsilon_{r}=4.3\) and loss tangent tan \(\delta=0.025\).  
The AMC unit cell consists of a square copper patch on a Taconic RF-35 substrate, which is shown in Figure 3. Its bottom side is fully covered with copper.  
The geometry of the \(x\)-polarized U-slot MPA, which is used as a source feeder, is shown in Figure 4. For better impedance matching, the U-slot is introduced with the probe feeding offset \(m_{x}\). The reflection coefficient and the 3D radiation power pattern of the MPA are shown in the Supplementary Materials [see Figures S1 and S2].
# Biosynthetic Pathways of Hormones in Plants
## 12 Jasmonates
The stereochemistry of the pentenyl side chain and the carboxylic acid side chain at positions 3 and 7, respectively, of the pentanone ring in the JA structure is fixed in the step catalyzed via AOC and conserved in later reactions. In the cytosol, \(\alpha\)-LeA can be oxygenated by enzyme 9-LOX and, subsequently, by enzyme 9-AOS to create two products: \(\alpha\)-ketols and/or \(\gamma\)-ketols. On the other hand, \(\alpha\)-LeA can also be oxygenated by \(\alpha\)-dioxygenase (\(\alpha\)-DOX) [211]. OPDA is known as a biosynthetic precursor of the phytohormone JA. It is also involved in various biological processes, which range from plant defence and stress responses to the regulation of growth and development [212]. OPDA is produced in the chloroplast through the 13-LOX/AOS pathway and then transported to peroxisomes. Recently, a plastid inner envelope-localized protein, known as OPDATI, has been found in _Populus trichocarpa_. This observation suggested that this protein may participate in the export of OPDA from the chloroplast to other organelles [213]. OPDA can enter the peroxisome via diffusion of the protonated form of OPDA along its gradient. The cyclopentenone ring of OPDA after transportation into the peroxisome is reduced in the reaction catalyzed by the flavin-dependent oxidoreductaseupDA reductase 3 (OPR3). 3-oxo-2-(20-[\(Z\)]-pentenyl)-cyclopentane-1-octanoic acid (OPC-8) is produced during this step [214]. In the next reaction, OPC-8 is activated via esterification to CoA in the biochemical reaction catalyzed by OPC-8 coenzyme A ligase1, which is a member of the acyl-activating family of enzymes [215]. OPC-8 is then transformed into JA through three rounds of sequentially catalyzed peroxisomal \(\beta\)-oxidation reactions by acyl-CoA oxidase, which is a multifunctional protein, and L-3-ketoacyl-CoA thiolase [202]. During these reactions, six carbons are eliminated from the carboxy-terminal carbon chain. Therefore, the pentenyl side chain of JA is shortened in reactions that involve the \(\beta\)-oxidation mechanism of the fatty acid [206]. Recently, an alternative pathway for JA synthesis has been proposed. Studies of the _opr3_-3 mutant in which OPR3 activity is completely depleted showed that OPDA and hexadecatrienoic acid-derived dn-OPDA are metabolized to create tetranor-ODA and 4,5-didehydro-JA. Next, this compound may be reduced to JA by OPR2 after being transported into the cytosol. This process suggests that the OPR2-dependent and OPR3-independent JA biosynthetic pathways may be very ancient in vascular plants and activated under different processes or the influence of certain environmental conditions [200,216,217].