esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### Algorithms for Optical Particle Sensors
#### 1.2.3 Algorithms Offered by Plantower
Its two algorithms are said to be \"proprietary\", which seems contrary to the practice of earlier manufacturers, whose algorithms were openly described. A problem with \"proprietary\" algorithms is the ever-present possibility that the manufacturer could change the algorithm at will. If the manufacturer does not announce that the algorithm has changed, consumers would not know a change had occurred, unless a careful examination of their historical data might reveal a change in some parameter (e.g., the relation of particle numbers in adjacent size categories). This is not only a theoretical possibility but actually occurred for the Plantower PMS 5003 sensor (and possibly other sensors) in about March of 2022. At that time, the PurpleAir technical staff noticed for some new instruments a clear change in the relative number of particles in the 0.3-0.5 \(\upmu\)m and 0.5-1 \(\upmu\)m size categories. Whereas previously the smallest size category (0.3-0.5 \(\upmu\)m) had about three times as many particles as the next larger one (0.5-1 \(\upmu\)m), now both categories seemed to have about the same number of particles. Plantower had made no notice about the change, but when contacted by PurpleAir they did admit that a change had occurred. PurpleAir made the decision not to accept the \"new\" instruments, which could be distinguished from the \"old\" instruments by the tests that PurpleAir runs on all monitors before releasing them for sale. After some time, no further \"new\" instruments were received by PurpleAir. However, it is unclear whether some of these \"new\" instruments may still be available to the 10 or so companies that use Plantower sensors.
## 3 Results
### Effect of CLI Content and Curing Time on Sodium Sulfate Content in the Soil  
CLI addition exhibited a satisfactory performance in improving shearing strength. It also showed great potential to enhance soil water-holding capacity. Figure 7a shows the effect of CLI content and curing time on the moisture content of soil samples. For samples after the same curing time, the reduction in moisture content showed the tendency of a V-shaped decrease and increase as the content of CLI increased, with the turning point at the content of 8%. This indicated that the CLI addition could increase water storage capacity, which was the most effective when the CLI content reached 8%. In comparison to the non-modified soils, the moisture content of the samples of 8% CLI was higher by 0.25%, 0.93%, 2.27%, and 2.75% after different curing times, respectively. Moreover, the results reveal that the curing time significantly influences the water-holding capacity of CLI-treated soil. For samples after a day of curing, the moisture content was approximately 12%. As the curing time increased, the difference between the moisture content of samples with different CLI contents became larger. As the curing time increased from 7 days to 14 days, the effect of curing time on the modified soil became negligible.  
Figure 6: Shear strength parameters of samples: (**a**) Relationship between cohesion and curing time; (**b**) Relationship between internal friction angle and curing time.  
To describe the variation of salt content in the sulfate saline soil, the mass of barium sulfate was calculated. The content of CLI added and the curing time had significant effects on the concentration of sulfate ions in the sulfate saline soil (Figure 7b). CLI treatments caused a notable decrease in the concentration of sulfate ions in the soils (by 1.49-2.31 g after the curing time from 1 day to 14 days), with the greatest decrease found in the samples of 12% CLI With the increase in the curing time, the largest decrease was found between 1 and 3 days. When the curing time increased from 7 days to 14 days, the reduction in the mass of barium sulfate was slight, indicating that CLI-induced decreases in the content of sulfate ions were more significant during the first 7 days than those of the following 7 days. In addition, Figure 8 shows that the amount of precipitation sodium sulfate crystals gradually decreased as the CLI content increased. Further evidence is that CLI is effective in reducing soluble salt content in sulfate saline soil.
# Stability Analysis of the Longitudinal Slope Linear Shield Tunnel Excavation Face
## 1 Introduction
Although previous studies have extensively examined excavation face stability in horizontal shield tunnels, the effects of longitudinal slope variations remain insufficiently explored. This study aims to bridge this gap by employing transparent soil modeling and FLAC3D numerical simulations to quantify the destabilization process under varying slope conditions. Specifically, a series of longitudinal slope gradients were introduced to simulate realistic tunnel inclinations encountered in engineering practice. In the transparent soil tests, three slope configurations were adopted: \(i=-15\%\), \(0\%\), and \(15\%\). The numerical simulations further expanded the range by including \(i=-7.5\%\) and \(7.5\%\), resulting in a total of five slope scenarios. Through transparent soil tests, the displacement characteristics of the soil in front of the excavation face were captured using the PIV method. Numerical simulations were further employed to analyze the ultimate support force of the excavation face, ground surface displacement, and stress variations in the soil ahead of the excavation. This research aims to elucidate the influence mechanism of slope variations on excavation face stability, providing experimental insights and data support for the design and construction of longitudinal slope shield tunnels.
## 1 Introduction
A novel serial code acquisition method based on segment correlation is proposed, which effectively solves the informational misjudgment caused by the unreasonable data acquisition time. (2). An overall communication DSSS transceiver system solution based on the proposed novel code acquisition is introduced. (3). The function of the different modules of the DSSS transceiver based on the proposed code synchronization algorithm was verified through MATLAB simulations. The tested modules include M-sequence, BPSK modulation, BPSK demodulation, Numerically Controlled Oscillator (NCO), low pass filter, carrier synchronization and code synchronization. (4). The verified modules were then simulated using Verilog language in order to load each module codes to a FPGA system and then verify the overall system's functionality. The general implementation of the DSSS transceiver can be summarized as below: the DSSS transmitter and receiver are both linked with a computer through a serial port line. The computer transmits signals through the digital transmitter using Com Wizard. Signals are transmitted to the digital receiver after SPSP and modulation. Then the received signals are restored through demodulation, carrier and code synchronization. The restored signals are conveyed to the computer, which is linked with the digital receiver. Hence, we can verify whether the original signal is restored by the computer. In this manner, the feasibility of our proposed code synchronization algorithm was confirmed through the implementation of the DSSS transceiver on FPGA. (5). For the purposes of this paper, a PCB layout was also designed and physically constructed. (6). The digital DSSS transceiver's behavior was also analyzed through the use of Signaltap II. The rest of this paper is organized as follows: the overall communication solution is proposed in Section 2. In Section 3, we describe the code synchronization algorithm based on segment correlation. Modules simulation via MATLAB is presented in Section 4. In Section 5, we describe the implementation of the DSSS transceiver based on the proposed code synchronization algorithm on FPGA. In Section 5, we conclude this paper.
###### Abstract  
This study proposes a novel approach to improving the crashworthiness of lithium-ion cylindrical cell packs by strategically placing spacers between the cells. The spacers transform the initial line contacts into broader surface contacts, enhancing the overall stiffness of the pack and reducing radial deformation during compression. The concept was evaluated using finite element analysis (FEA), leveraging established material models to efficiently assess the concept's potential prior to physical testing. To validate the robustness of the homogenized cell material and its application in a full pack, a compression experiment was performed on a pack of nine cells. The experimental results aligned closely with the simulation data, underlining the reliability of the material model and simulation methodology. Across all configurations and load cases--quasi-static compression using a plate or cylinder, and dynamic impact tests simulating crash indentation with a ball--the inclusion of spacers resulted in significant reductions in cell deformation and pack intrusion. The study also examined three spacer materials: aluminum, printed PLA, and printed PLA conditioned at 60 \({}^{\circ}\)C. The results showed that stiffer spacers, such as those made of aluminum, were the most effective in improving crash performance. However, even the conditioned PLA spacer, despite its lower stiffness, delivered meaningful benefits by enhancing structural integrity and reducing deformation. This demonstrates the versatility of the spacer concept, which can accommodate a range of materials based on specific performance and manufacturing requirements. These findings establish a solid foundation for the practical implementation of spacers in electric vehicle battery packs. Future research should include experimental validation under real-world crash conditions and explore spacer design and material optimization to maximize crashworthiness without compromising energy density or thermal performance.  
Li-ion battery; experimental compression test; material models; quasi-static simulation; dynamic simulation; crashworthiness; pack design; spacers +
Footnote †: journal: Applied Sciences
# Risk Management for the Reliability of Robotic Assisted Treatment of Non-resectable Liver Tumors
## 3 Results
### HeRo Design Concept  
Based on the medical protocol and the design constraints (the main purpose of which was to minimize the risk while increasing the therapeutic efficiency and reliability), a set of QFD analyses was conducted and the design of the HeRo parallel robotic system [17] emerged. Figure 11a illustrates the HeRo concept augmented into the relevant medical environment (in the operating room), whereas Figure 11b illustrates the CAD (computer aided design) of one guiding module. The following components with their technical characteristics are highlighted:  
* The parallel robotic system is composed of two modules, Module 1 and Module 2, which are attachable by the operating bed (via modular attaching mechanisms) with each module being capable of guiding the needle instrument or the I-US instrument;
* The main components of each module have a total of 5 DOFs and are composed of two main mechanisms: one **gantry mechanism** with 3 Cartesian DOFs for the insertion point/RCM positioning (having three linear drives) and one **spherical mechanism** with 2 orientation DOFs for the needle trajectory or I-US probe manipulation (having two circular drives);
* The characteristics of the main components are defined by reliable motion with low friction due to the **3 linear guides** and **2 circular guides** (with rails based on bearing balls and carriages) and **5 servo motors** with high rotation motion resolution. Each module allows a quick plug/unplug of the medical tools (needles, I-US probe) to facilitate fast intervention times, for the clinicians, in the case of unexpected patient trauma.
# A Deep Learning Approach for Automatic Hate Speech Detection in the Saudi Twittersphere
## 4 Experiment Setup
### Neural Network Models
#### 4.2.3 GRU Architecture  
Currently, GRU is the state-of-the-art model for Arabic hate speech detection. In this experiment, we employed a GRU-based network similar to the one applied in [12]. Our network architecture, as illustrated in Figure 2, contains 4 layers: an input layer (embedding layer), a GRU layer, a hidden dense layer, and finally the output layer. Similar to CNN architecture, the inputs (tweets) are fed into the embedding layer, which maps tweets' tokens into a 300-dimensional real valued vector. Letting \(m\) be the length of the longest tweet, the embedding layer produces an output matrix with a shape of (m \(\times\) 300) passed into a dropout layer with a rate of 0.2 to reduce the problem of overfitting. Then, the output of the dropout layer is passed into a GRU layer with 250 units to model long-range contextual information, producing an output with a shape of (1 \(\times\) 250). This output is then passed to a dense layer with 50 neurons and rectified linear unit function for activation. After that, a dropout layer with a rate of 0.2 is used for regularization. The final layer is a sigmoid layer that produces the final predictions.  
Figure 1: Convolutional neural network (CNN) architecture.  
Figure 2: Gated recurrent unit (GRU) architecture.
## 3 Numerical Study of Developed Algorithms
### The Griewank Problem  
\[f(x)=1+\sum_{i=1}^{n}\left(\frac{x_{i}^{2}}{4000}\right)-\prod_{i=1}^{n}\cos \left(\frac{x_{i}}{\sqrt{i}}\right),\ X=[-600.0,\ 600.0]^{n},\ n=100. \tag{2}\]  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm**} & \multicolumn{2}{c}{**[PERSON]**} & \multicolumn{2}{c}{**[PERSON]**} & \multicolumn{2}{c}{**[PERSON]**} & \multicolumn{2}{c}{**[PERSON]**} \\ \cline{2-9}  & **Mean** & **SD** & **Mean** & **SD** & **Mean** & **SD** & **Mean** & **SD** \\ \hline FP (v.1) & 343.92 & 28.532 & 550.21 & 28.974 & 11,892.6 & 648.79 & 15.532 & 0.2518 \\ FP (v.2) & 0.0496 & 0.0306 & 2.9473 & 1.5561 & 1933.58 & 106.95 & 4.3835 & 0.8977 \\ TL (v.1) & 25.834 & 12.927 & 280.16 & 27.019 & 23,524.7 & 6213.6 & 7.1138 & 1.1376 \\ TL (v.2) & 0.0446 & 0.0255 & 0.0433 & 0.0292 & 7808.61 & 2069.5 & 0.7892 & 0.2384 \\ FA (v.1) & 205.35 & 17.120 & 818.99 & 69.126 & 21,146.8 & 942.92 & 15.872 & 0.9408 \\ FA (v.2) & 11.713 & 2.4140 & 265.91 & 73.013 & 3519.01 & 157.43 & 6.2518 & 1.8042 \\ GA (v.1) & 38.675 & 6.5504 & 191.98 & 18.622 & 5126.49 & 544.45 & 8.1085 & 0.5020 \\ GA (v.2) & 0.0536 & 0.0262 & 0.0089 & 0.0055 & 808.215 & 91.187 & 0.4323 & 0.1315 \\ BBO (v.1) & 36.248 & 5.1454 & 937.15 & 76.528 & 20,091.3 & 1201.3 & 10.998 & 0.5813 \\ BBO (v.2) & 0.5953 & 0.5083 & 215.03 & 8.9858 & 3341.13 & 200.06 & 1.9491 & 0.5387 \\ PSO (v.1) & 339.37 & 49.630 & 937.38 & 53.785 & 35,812.4 & 1218.7 & 15.201 & 0.5299 \\ PSO (v.2) & 10.801 & 4.4535 & 269.85 & 6.2304 & 8948.39 & 304.70 & 4.1005 & 0.5175 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Statistics on algorithm launches: mean and standard deviation (SD).  
Figure 3: Box and whisker diagrams of algorithms comparison (Schwefel problem).  
Absolute minimum point and value: \(x_{i}^{*}=0.0,\ f^{*}=0.0\).  
Figure 1 and Table 2 show that the developed modifications (v.2) demonstrated essentially better results in comparison to basic variants of algorithms (v.1). On this problem, the TL algorithm turned out to be the most effective among the proposed algorithms.
# Multilevel Bipolar Electroforming-Free Resistive Switching Memory Based on Silicon Oxynitride
## 2 Materials and Methods  
SiO\({}_{x}\)N\({}_{y}\) thin films with thicknesses of 7, 10, and 15 nm were deposited by plasma-enhanced chemical vapor deposition (PECVD)(Oxford plasmalab system 100 PECVD, Oxford Instruments Plasma Technology, UK, Plasma Technology, 66.7 mi \(\cdot\) Yatton, Bristol, UK, BS49 4 AP) on a p\({}^{+}\)-Si substrate (boron-doped, 3.0 m\(\Omega\)-cm) at 300 \({}^{\circ}\)C. The gas mixture, N\({}_{2}\)O/SiH\({}_{4}\)/NH\({}_{3}\)/N\({}_{2}\) (60/400/20/600 SCCM), was supplied under a working pressure of 650 mTorr and an RF power of 15 W (30.6 W/mm\({}^{2}\)). The heavily doped p\({}^{+}\)-Si substrate served as the bottom electrode, and a circular-shaped Au/Ni (150/40 nm) top electrode with a radius of 50 \(\upmu\)m was then deposited by e-beam evaporation through a shadow mask. To observe the area dependency, four different sizes of the 10-nm-thick SiO\({}_{x}\)N\({}_{y}\)-based devices were also fabricated with a radius of 35, 50, 150, and 225 um, respectively. Separately, 10-nm-thick SiO\({}_{x}\)N\({}_{y}\) films with the same composition were grown on a glass substrate for Fourier transform infrared (FTIR) absorbance spectroscopy measurement. The electrical characteristicsof the memory devices were measured using a semiconductor parameter analyzer (HP-4155A). (Hewlett-Packard Company, 3000 Hanover Street Palo Alto, CA 94304-1185 USA) Voltage was applied directly to the top electrode while the bottom electrode was grounded.
## 5 Discussion
### Detectable and Sensitivity of XCO\({}_{2}\) in Response to Local CO\({}_{2}\) Flux Change  
In order to identify local CO\({}_{2}\) flux changes using the XCO\({}_{2}\) extreme detection method, we need to understand their relationship [77]. A significant positive correlation between increased XCO\({}_{2}\) and local CO\({}_{2}\) flux change can be found in Figure 7, however the magnitude of that relationship varies across the six regions examined. These differences are likely due to different patterns of atmospheric transport [78]. For example, atmospheric inversions have historically been constrained by surface CO\({}_{2}\) concentrations to infer surface fluxes. Inversion model inter-comparisons, like the Atmospheric Tracer Transport Model Intercomparison Project (TRANSCOM) found that it was difficult to constrain surface fluxes in the tropics because high rates of vertical transport of air masses results in low sensitivity of the surface CO\({}_{2}\) monitoring fluxes to changes in local surface fluxes [79; 80]. However, satellite column observations, such as from ACOS-GOSAT, are sensitive to CO\({}_{2}\) variations throughout the boundary layer and free troposphere [81]. Therefore, XCO\({}_{2}\) anomalies are more sensitive to fluxes in the tropics than in the mid-latitudes, the opposite of the sensitivity biases in atmospheric inversions using surface observations. Our results also show that regions with large CO\({}_{2}\) flux magnitudes, like the topics, are more likely to produce a detectable change in XCO\({}_{2}\).
## 3 _HoloSec_: Proposed Conceptual Holochain Security Framework for IoT Distributed Networks
### Secure Communication and Authentication  
Communication between agents is secured using asymmetric cryptography, such as RSA or ECC. Data is encrypted with the recipient's public key and signed with thesender's private key, ensuring confidentiality, authenticity, and non-repudiation, with the following examples.
* The sender encrypts the data using the recipient's public key (e.g., RSA or ECC).
* The sender signs the encrypted data using its private key.
* The recipient decrypts the data using its private key and verifies the sender's signature using the sender's public key.  
Mutual authentication is performed to ensure that both parties are legitimate. This involves the exchange of public keys between the sender and recipient, followed by verification of each party's identity by validating the received public key against the Holochain global DHT.  
To further enhance security, encryption keys can be periodically rotated using a key rotation protocol. Key rotation involves re-encrypting data using a newly generated key to replace the old one [61]. For instance, a new key pair can be generated every X hours. The new public key is then broadcast to all trusted peers and stored on the DHT, while the old private key is securely deleted to prevent unauthorized access.
## 2 Materials and Processing Methods
### Wear Testing  
Wear testing was conducted using a pin-on-disc machine for all the samples after sintering, depending on the ASTM-G99 standard. Wear testing was conducted on the samples at (2 cm in length and 1 cm in diameter). The wear testing was performed by applying loading at (3, 6, 9, 12 and 15 N) and a constant time of 10 min. The wear rate of the samples was measured by the weighing method. This method depends on measuring the losses in weight for all samples with a sensitive electronic balance of about (0.01 mg) accuracy. Figure 1 shows the schematic diagram of the wear-testing machine. Afterward, the wear rate was calculated using the formula [37]:  
\[\text{\emph{wear rate}}=\frac{\Delta\text{w}}{2\pi rnt} \tag{5}\]  
\[\Delta\text{w}=\text{w}_{1}-\text{w}_{2} \tag{6}\]  
\[\text{S.D.}=2\pi\cdot r\cdot n\cdot t\]  
where:  
\(\Delta\text{w}\): Change in weight (g).  
\(\text{w}_{1}\) and \(\text{w}_{2}\): Weight of the specimen prior and after testing (gm).  
\(r\): Radius of the rotating disc (mm).  
\(n\): Number of the disc rotating's (rpm).  
\(t\): Testing time (min).
# Bio-Sourced and Biodegradable Membranes
## 4 Green Membrane Technology Applications
### Fuel Cell
\begin{table}
\begin{tabular}{c c c c c} \hline
**Polymer** & **Application** & **Advantage** & **Disadvantage** & **Ref** \\ \hline PLA & Oil/water separation & Superoleophilic and superhydrophobic property, excellent reusability & Low oil adsorption capacity & [189] \\ \hline PLA/TiO\({}_{2}\) & Oil/water separation & Superoleophobicity, long-term behavior, excellent separation efficiency (>99\%), high permeate flux, antifouling property & Low BSA adsorption capacity & [190] \\ \hline PLA & Oil/water separation & Robust recyclability, excellent adsorption capacity & & [191] \\ \hline CA/PVP & Oil, dye, metal removal & Excellent removal efficiency for oil, dye and metal ions (>99\%), long-term reusability, super hydrophilicity and underwater superoleophobicity & & [192] \\ \hline CA & Oil/water separation & Robust recyclability, antifouling property, high infuse flux, enhanced adsorption capacity & lower infused flux for solutions, containing crude oil & [193] \\ \hline CA/MOFDPC & Dye removal & Excellent reusability, High MB removal, long term behaviour, high water flux & Lower tensile strength and flexibility compared to CA membrane & [176] \\ \hline CA/Cotton & Dye removal & MB rejection of 98\% over 8 filtration cycle, high durability, low fouling, high mechanical stability & Tested for low volume wastewater (5-10 mL, dead end filtration setup) & [186] \\ \hline CS/PVA & Dye removal & Strong interaction between CS and PVA, higher tensile strength, stability in DI, acidic and alkaline medium & Lower thermal stability compared to pristine membranes & [8] \\ \hline CS/GO & Dye removal & At least 95\% of cationic MB removal & GO size affected the anionic MB removal such that the maximum removal efficiency was 64\% for nanoscale GO & [187] \\ \hline PLA/CS & Dye removal & Large porous framework though a nanofibrous structure, High removal capacity of 86.43 and 82.37 mg/g for rhodamine B and MB & Adsorption capacity reduction after fourth cycle & [255] \\ \hline PCL/MXene & Dye removal & High hydrophilicity and water permeability by adding only 4 wt\% of MXene, more than 99\% or crystal violet removal & Lower CV rejection after adding MXene nanoparticles & [78] \\ \hline CS/PVA/MMT & Heavy metal removal & High hydrophilicity and water flux, antibofouling property, 84–88.34\% of Chromium removal efficiency & Low removal efficacy after 1 h and at high pH (pH of 9) & [138] \\ \hline PLA/PBS & Heavy metal removal & Heat resistance improvement, enhanced hydrophilicity and mechanical stability, about 83\% of ion removal efficiency & & [182] \\ \hline CS/PVA & Heavy metal removal & Improved chemical stability in acidic medium, enhanced hydrophilicity and anti-swelling, good adsorption recovery & Adsorption capacity decay by increasing the Cd (II) concentration (about 95\% at 50 mg/L) & [195] \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._