esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Photovoltaic Capacity Simulation  
PVsyst is used to evaluate the performance of various photovoltaic technologies in accordance with the IEC 61724 standard [34]. Known for its advanced weather data processing, energy yield simulation, and shading analysis, PVsyst enables the accurate comparison of PV technologies under different climatic conditions. This level of detailed analysis is essential for validating system performance [35]. In PVsyst, the modeling process involves defining the site location and setting up meteorological data. Subsequently, the PV system components, including modules, inverters, and the layout, are configured. The system is then simulated to evaluate performance and optimize the design.  
1. The first step is to select the geographical location of the PV system based on its latitude and longitude. This ensures that the system design is tailored to the specific solar irradiance and climatic conditions of the selected region. In PVsyst, selecting the predefined Guangzhou site (Guangzhou_Baiyun_MN80) from the software's database provides access to local climate data, such as solar irradiance, temperature, humidity, as well as time zone and altitude information.  
Figure 3: Computational domain: (**a**) computational domain; (**b**) body of the influence (BOI) region.  
2. We then specify the electrical parameters of the PV system, including equipment specifications such as PV modules and the inverter. A 400 W PV module from the software's predefined database is selected, as described in Table 2. The inverter is chosen based on the installed capacity using the predefined 100 kW model SUN2000-100 KTL-H1. The PVsyst software package [PVsyst! Photovoltaic Software, Design and Simulate Photovoltaic Systems. Available online: [[https://www.pvsyst.com](https://www.pvsyst.com)]([https://www.pvsyst.com](https://www.pvsyst.com)) (accessed on 20 May 2025)] includes predefined detailed technical specifications for these electrical components, so no additional input from the user is required during the simulation process.
3. Finally, based on the PV system configurations in each case (as shown in Table 3), the specific position of each row of PV panels is defined in PVsyst, thus allowing for the construction of a complete PV system model, as illustrated in Figure 4. PVsyst incorporates both the electrical equipment specifications and the 3D layout of the PV modules to account for factors affecting power generation, such as detailed electrical losses and near shading, and provides comprehensive simulation data.
## 4 Implementation Details
### Training Details  
In our experiments, we train four encoder-decoder based architectures: (1) original UNet, (2) ResUNet, (3) ResUNet++, and (4) propsoed AB-ResUNet+. All architectures were implemented using the Keras framework with TensorFlow as the backend. We performed our experiment on a single Nvidia GEForce GTX 1070 GPU. We started the training with a batch size of four, and the proposed architecture was optimized by Adam optimizer. The learning rate of the algorithm was set to \(4\times 10^{-3}\). The images of size \(256\times 256\) pixels were fed to the model. To alleviate the number of training samples, we used the following data augmentation techniques: random crop, horizontal flip, vertical flip, scale, and random rotation. The rotation angle was randomly chosen in between \(-20\) and \(20\) degrees. Fivefold cross-validation was employed to assess the performance of the proposed model. We trained all models for 200 epochs. We also used the stochastic gradient descent with restart (SGDR) to improve the model's performance. Table 2 summarizes used data augmentation methods training parameters.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline
**Dataset** & **CS** & **DA** & **IVC** & **LAA** & **LAW** & **PM** & **PML** & **PAA** & **PA** & **RVW** & **SVC** \\ \hline Number of patients & 20 & 21 & 20 & 21 & 22 & 22 & 22 & 21 & 21 & 22 & 22 \\ Number of 2D images & 153 & 2005 & 288 & 365 & 806 & 869 & 454 & 355 & 309 & 1445 & 538 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Dataset details. Number of different patients per cardiovascular structure and total number of 2D images.
## 3 Results
### Fruit Yield  
The results of this study showed that there were significant differences in the yields of tomato fruits among different salt concentration levels (S) and nutrient recipes (N). As depicted in Table 4, the highest fruit yield (27.6 kg m\({}^{-2}\)) was recorded for the low-salinity (S1, \(\sim\)2.5 dS m\({}^{-1}\)) treatment, and the fruit yield reduced to 15.6 kg m\({}^{-2}\) when the plants were treated with the high-salinity (S3, \(\sim\)9.0 dS m\({}^{-1}\)) treatment (Table 3). As illustrated in Figure 2, the tomato fruit yield (26.8 kg m\({}^{-2}\)) of the plants treated with moderate salinity stress (\(\sim\)6.0 dS m\({}^{-1}\)) was comparable to the yield of the S1 treatment, accounting for a reduction of 2.8% in yield. The plants treated with the N1 recipe produced a higher yield (24.2 kg m\({}^{-2}\)), followed by the N2 (23.8 kg m\({}^{-2}\)), N3 (23.1 kg m\({}^{-2}\)), and N4 (22.3 kg m\({}^{-2}\)) recipes. The total fruit yields of the grafted (GR) and non-grafted (NG) plants were significantly different. The GR plants recorded a mean of 25.2 kg m\({}^{-2}\) and 25.9 kg m\({}^{-2}\) for season 1 and season 2, respectively. In contrast, the mean yield of the NG plants ranged between 21.7 kg m\({}^{-2}\) (season 1) and 20.5 kg m\({}^{-2}\) (season 2), with a difference of 19.7%. Under high-salinity conditions (\(\sim\)9.0 dS m\({}^{-1}\)), the GR plants produced 18.5 kg m\({}^{-2}\) of tomatoes, accounting for a higher yield of 23% compared with the NG (12.8 kg m\({}^{-2}\)) plants (Figure 2). On the other hand, a yield difference of 37.5% between the GR and NG plants was observed under low-salinity water (S1) treatment.
## 2 Centrifuge Testing Program
### Model Preparation and Test Procedure  
The cemented material was used at a compacted density of 1.92 g/cm\({}^{3}\) when used to represent the bedrock. The mass percentage composition of the cemented material was a silica sand:fines fraction of deposit:cement:water = 0.383:0.383:0.131:0.103, and rapid strengthening agents were added to 2% mass of the cement. Then, the constructed bedrock model was cured for six days and the dynamic centrifuge tests were performed on day 7. The friction angle was 44\({}^{\circ}\) and cohesion was 201 kPa for the cemented material after a 7-day curing period, as evinced by direct shear test data. The interface between the bedrock and deposit was generalized as two inclined planes and a horizontal plane, with inclined plane angles of 45\({}^{\circ}\) and 20\({}^{\circ}\), respectively (Figure 1a,b).  
Pile bending moments were measured by seven pairs of strain gauges in a full bridge configuration mounted on the tube surface (Figure 1c); lateral pile-soil pressures were measured by four miniature transducers embedded in the pile. The pile strain gauges and miniature earth pressure transducers were calibrated before installation. After calibration and verification that all sensors were working, the model piles were embedded in the bedrock.  
When preparing the upper layer of the slope models, the deposit materials were compacted after placement in the model box using the controlled-volume method [42] to a dry density of 1.81 g/cm\({}^{3}\). After the placement of each layer, the deposit surface was smoothed with a soft brush and instruments were placed in their specific positions. Silicone oil was smeared over the sides of the rigid box to provide a lower friction coefficient at the interface with the walls.  
The dynamic input was provided by the shaking table in the centrifuge. Multiple shaking events (El Centro motion) covering a wide range of peak ground accelerations(PGA) were applied to both the 1\(\upmu\) and 2\(\upmu\) models while in flight. The shaking was applied parallel to the long sides of the model container and orthogonal to the pile row. The peak values of the horizontal input acceleration in the shaking events were adjusted to nearly 0.05 g, 0.10 g, 0.20 g, 0.40 g, and 0.20 g at the prototype scale (corresponding to 2.5 g, 5.0 g, 1.0 g, 2.0 g, and 1.0 g at the model scale), which corresponded to seismic intensities of 6\({}^{\circ}\), 7\({}^{\circ}\), 8\({}^{\circ}\), 9\({}^{\circ}\), and 8\({}^{\circ}\) based on the \"Code for Seismic Design of Buildings\" in China (GB 50011-2010) [43]. The time histories of input motions in instrument BA-0 are shown in Figure 2.
# Optical Transmitters without Driver Amplifiers--Optimal Operation Conditions
###### Abstract  
An important challenge in optical communications is the generation of highest-quality waveforms with a Mach-Zehnder modulator with a limited electrical swing (V\({}_{\text{PP}}\)). For this, we discuss, under limited V\({}_{\text{PP}}\), the influence of the waveform design on the root-mean-square amplitude, and thus, the optical signal quality. We discuss the influence of the pulse shape, clipping, and digital pre-distortion on the signal quality after the electrical-to-optical conversion. Our simulations and experiments, e.g., suggest that pre-distortion comes at the expense of electrical swing of the eye-opening and results in a lower optical signal-to-noise ratio (OSNR). Conversely, digital post-distortion provides operation with larger eye-openings, and therefore, provides an SNR increase of at least 0.5 dB. Furthermore, we find that increasing the roll-off factor increases the electrical swing of the eye-opening. However, there is negligible benefit of increasing the roll-off factor of square-root-raised-cosine pulse shaped signals beyond 0.4. The findings are of interest for single-channel intensity modulation and direct detection (IM/DD) links, as well as optical coherent communication links.  
optical communications; fiber optics communications; modulators; mitigation of optical transceiver impairments +
Footnote †: journal: Applied Physics Letters
# Influence of Milling Techniques on the Performance of Wheat Straw Ash in Cement Composites
## 1 Introduction
Moreover, the addition of WSA enhances the durability-related properties of cementitious materials. For example, replacing a portion of sand or cement with WSA results in reduced absorption and improved resistance to acid and sulfate attack [21; 22]. Similarly, in another study, it has been concluded that freeze-thaw resistance of concrete specimens containing WSA enhanced [23]. Based on the findings indicated in the existing literature, it is evident that WSA possess the filler aswell as pozzolanic properties. However, due to its lower pozzolanic activity, it has not been thoroughly studied. The pozzolanic activity of the ashes can be increased by applying grinding procedures. Grinding decreases the particle size and enhances the surface area. This adds nucleation sites which facilitates the precipitation of additional hydrates [24]. The focus of the present study is to select a suitable grinding procedure for obtaining a high pozzolanic and filler material. In this study, WSA specimens were ground separately with a ball mill and a disintegrator mill as well as with a combination of both techniques. The ash attained after each grinding procedure was examined for particle size distribution (PSD), X-ray diffraction analysis (XRD), specific surface area, and X-ray fluorescence (XRF) analysis. Each kind of WSA was added as a cement replacement (20% by weight) and paste and mortar specimens were made. Compressive, flexural, and UPV tests were conducted to assess the performance of each kind of WSA in cement composites. Additionally, isothermal calorimetric and thermogravimetric analyses (TGA), mercury intrusion porosimetry (MIP), and scanning electron microscopy (SEM) were employed.
# Analysis of the Scalability of UWB Indoor Localization Solutions for High User Densities
## 7 Conclusions  
Ultra-wideband has been showing an enormous potential to be adopted in any indoor localization scenario, it can localize a tag with cm-level accuracy, which is better than traditional RF technologies. However, its main drawback is the limited scalability in terms of tag density due to the lack of collision avoidance capabilities. We gave an overview of the regulations that have been drafted, and showed that the supported tag density can mathematically be calculated and provide the necessary formulas to calculate the impact of different UWB PHY settings, MAC protocol and localization approach. These impacts are combined in a scalability model that takes into account all the possible aspects that could impact the tag density. In three simple steps it is possible to evaluate how many users the system can ultimately support. Moreover, to validate the model, we applied it to an existing commercial solution, which allows to configure various settings. We created two configurations and then compared the outcomes for different MAC-localization scheme scenarios. We showed that with specific setting, i.e., TDoA-TDMA and short packets, UWB is capable of accommodating resources for thousands of users per second, which is a high scalable solution. However, as expected, the results vary with different inputs. The outcomes of this paper provide insights in the trade-offs for UWB full-system design, and allow UWB solution designers to determine a priori the expected number of supported users.  
Figure 8: Tag density in relation to frame length and applied to four different configurations.  
**Author Contributions:** Conceptualization, M.R. and E.D.P.; Formal analysis, M.R.; Investigation, M.R.; Methodology, M.R.; Supervision, E.D.P.; Writing--original draft, M.R.; Writing--review & editing, M.R.; S.V.d.V.; H.S. and E.D.P.  
**Acknowledgments:** This research was supported by imec.icon LUNAR project that focuses on the design of scalable UWB localization solutions for retail applications.  
**Conflicts of Interest:** The authors declare no conflict of interest.
### Contributions  
We summarize the critical contributions of this study below:  
* This work offers a security analysis of the scheme by [PERSON] et al. [15] and reveals its vulnerabilities to various attacks, including device capture, impersonation, insider, and ephemeral secret leakage attacks.
* We propose a secure and privacy-preserving authentication scheme that ensures enhanced security. A PUF is employed in the proposed scheme to ensure the security of the sensor. The proposed scheme can guarantee resistance against sensor capture attacks.
* We prove the security of the proposed scheme by using the \"Burrows-Abadi-Needham (BAN) logic\" [16], \"real-or-random (RoR) model\" [17], and \"Automated Verification of Internet Security Protocols and Applications (AVISPA) simulation tool\" [18; 19] formally to demonstrate the robustness of the proposed scheme.
* We demonstrate the efficiency of the proposed scheme through a comparative analysis of the communication cost, computational cost, and security features with related works. The proposed scheme shows superior performance over previous works.
## 6 EEG Signal Pre-Processing and Feature Extraction
### EEG Signals Classification
#### 6.3.2 Applications in Medical Diagnoses and Brain-Computer Interfaces (BCIs)  
EEG signal classification is vital in medical diagnosis, especially for identifying neurological disorders like epilepsy, Alzheimer's disease, and sleep disorders. In the realm of BCI, EEG classification plays a key role in interpreting user intentions from brain activity, facilitating the control of external devices or communication, especially in scenarios involving severe motor disabilities [109].
## 3 Materials and Methods  
This study presents a detailed analysis of six cored wells approximately 150 m in length from the Jurassic Qigu Formation in the Yongjin area. Core sketches were plotted on a 1:80 scale, documenting the single layer thickness, lithology characteristics, color, grain size, and sedimentary structures in detail. Key samples were subjected to a suite of analyses including grain size analysis, trace element analysis, thin section analysis, and porosity and permeability measurements. The core samples, logging data, and most porosity/permeability and thin section data were provided by China Sinopec Shengli Oilfield Company. The porosity and permeability measurements, trace element analysis, and grain size analysis were conducted at the Key Laboratory of Oil and Gas Resources and Exploration Technology, Ministry of Education (Yangtze University). Thin sections were identified using a Leica DM2700P microscope and Leica polarizing microscope produced in Germany following the industry standard SY/T5368-2000 [45]. Trace element analysis was conducted using an ICPMS-2030 inductively coupled plasma emission spectrometer produced Shimadzu Corporation (Japan) according to the industry standard GB/T20260-2006 [46]. Particle size distributions were determined using an LS13320 laser diffraction analyzer produced Beckman Coulter, Inc. (USA), which generated cumulative probability curves in strict accordance with the industry standard SY/T5434-2018 [47]. The porosity and permeability were measured using SCMS-E high-temperature and high-pressure core multi-parameter measurement systems produced Hachan Well Completion&Looging Science and Technology Limited Company (China) following the industry standard GB/T29172-2012 [48].  
Based on the core observations and thin-section analysis, we conducted a detailed examination of the petrological characteristics in the Qigu Formation. Through detailed observations of the cores, the lithofacies types and associations were determined by integrating lithological characteristics and logging curve morphology. The planar distribution of sedimentary microfacies for different depositional stages was constructed based on the facies analyses of single and connected wells. The sedimentary environment of the Qigu Formation was quantitatively reconstructed by combining the core color, specific minerals, and trace elements. Based on the paleoclimate, paleogeomorphology, sediment source, and the spatial distribution of sedimentary microfacies, a depositional model of shallow-water deltas in this area was proposed. Finally, porosity and permeability measurements were performed on each sedimentary microfacies to systematically evaluate variations in reservoir quality among different shallow-water delta microfacies.
## 6 Technical Challenges and Future Directions
### Technical Challenges
An OFDR-based distributed fiber optic sensor with a linewidth squeezed optical source and an optically-amplified-recirculating phase gate in its emitting side, can be superior compared with current SoTA fiber-optic sensors due to (a) the ultra-coherent source, (b) the ultra-fast modulators and PDs and (c) the 100 Gbaud electronics. These advantages can result in a resolution of less than 10 mm and a range of up to 10 km, making COFDR the ideal technology for the next generation of sensors. Central office re-architected as a datacenter (CORD) is a relatively new access architecture, designated mainly over the last five years, aiming to bring new concepts, such as NFV, SDN and cloud datacenters, closer to the end users. The main advantages of this approach are reduced latency due to the faster delivery of services, higher efficiency of network resources due to the virtualization procedure and OPEX advantages due to cloud automation and lights-out operation. However, high maintenance costs, as well as the cost of the transformation of the central office into a datacenter are the main drawbacks of this approach. This concept needs further investigation in order to quantify the relative costs and gains from this transformation; however, as emerging F5G-F6G services require very low latency, the CORD approach seems very attractive.
## 3 Proposed Solution to Predict the AoA
### Beamforming and Precoding Strategy
#### 3.4.2 Multi-User Beamforming and Interference Management  
In our DE-ACSW-R-based framework, multi-user MIMO beamforming is achieved by generating orthogonal (or near-orthogonal) beams using the predicted AoAs for each active user, as determined by the latest slot-level fusion result. When the AoAs are sufficiently separated, direct steering suffices. For closer or overlapping users, Zero-Forcing (ZF) precoding is applied to mitigate inter-user interference by ensuring the following:  
\[w_{i}^{H}w_{j}\approx 0\ \ \ \ \ \text{for}\ i\
eq j \tag{30}\]  
In practice, this is achieved by applying a Zero-Forcing precoding process on the set \(\{a\big{(}\hat{\theta}_{1}),\ldots,\ a\big{(}\hat{\theta}_{k}\big{)}\}\) to generate beamforming weights that maximise the desired signal power while suppressing interference [41; 42].  
This precoding process ensures that each user's beam remains spatially isolated, thereby suppressing cross-user interference at the transmitter. Because the AoAs are predicted one or more slots ahead, the O-RU can proactively update and apply the ZF weights without waiting for real-time CSI feedback, improving responsiveness in highly mobile environments. This lightweight ZF strategy aligns with Split 7-2x constraints, where the O-RU executes latency-sensitive beam updates based on local prediction, while broader coordination and UEID validation are handled at the O-DU.
# DDR4 BER Degradation Due to Crack in FBGA Package Solder Ball
## 4 Measurement Setup  
The defects in FBGA solder ball in running systems are difficult to analyze due to accessibility issues. The solder balls are located under the device package which makes physical inspection difficult except for corner solder balls. The removal of device for inspection may change the condition of solder balls.  
The crack in solder ball can be mimicked by loading the data line with a capacitive element [12]. The value of capacitive element corresponds to the dimensions of the crack. Figure 10 shows a DDR4 RDIMM module with a 0.2 pF capacitor loaded on the data line. The RDIMM module is used for studying the effects of crack in memory systems in running environment. FPGA based memory controller is used for running PRBS pattern on DDR4 memory channel. FPGA board is standard 16 layer board with 50 Ohm transmission line between the FPGA and DDR4 memory. Figure 11 shows the system board with the FPGA and DDR4 RDIMM module. There are discontinuities in the data channel due to FPGA to  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Data Rate** & & **No Crack** & **Crack** & **\% Loss** \\ \hline \multirow{3}{*}{2.133 Gbps} & Data eye width (UI) & 0.8598 & 0.8414 & 2.1 \\  & Top margin (V) & 0.1726 & 0.1653 & 4.22 \\  & Low margin (V) & 0.1864 & 0.1726 & 7.4 \\ \hline \multirow{3}{*}{2.666 Gbps} & Data eye width (UI) & 0.8036 & 0.7326 & 8.8 \\  & Top margin (V) & 0.1766 & 0.1545 & 12.5 \\  & Low margin (V) & 0.1857 & 0.157 & 15.45 \\ \hline \multirow{3}{*}{3.2 Gbps} & Data eye width (UI) & 0.83 & 0.712 & 14.21 \\  & Top margin (V) & 0.1797 & 0.122 & 32 \\ \cline{1-1}  & Low margin (V) & 0.1931 & 0.1498 & 22.42 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Data eye width and voltage margin loss due to crack for different data rates.  
Figure 9: Eye width loss and voltage margin loss with increasing data rate.  
board interface, vias, routing of transmission line on the layers of board and DIMM socket. These discontinuities also have an effect on the data eye.  
The data channel is probed from behind the DIMM socket as shown in Figure 11. The measurement of the data channel from this point effects the data eye measurement. For analysis two DDR4 data channels are measured. DQ3 channel has no defect in solder ball and DQ2 channel has 0.2 pF capacitor loaded on the data line to mimic the effect of crack in the solder ball. DQ3 channel is compared with DQ2 channel to show the degradation in data eye due to defect. This degradation of data eye results in bit error rate degradation as shown by bathtub plots.