esa-sceva/satcom-chunk-collection huggingface dataset:
# Compact MIMO System Performances in Metallic Enclosures
## 4 Experimental Results and Discussions
### EVM Measurements in the Presence of Interference  
The 2 \(\times\) 2 MIMO EVM measurements are presented in the presence of the MIMO interference as functions of interference gain values. The QPSK receiver was tested in the presence of the MIMO interference generated by B210 USRP. The measurement setup is shown in Figure 6, which shows the MIMO antenna configuration and MIMO antenna interference antennas attached to the enclosure lid. B210 USRP, which generated MIMO interference, can also be seen on the enclosure lid. We used GNU radio-based signals, transmitted via B210 USRP as a source of interference. B210 USRP is a full-duplex fully  
Figure 5: Channel 1 and channel 2 instantaneous EVM measurements at 5.6 GHz in a mode-stirred metal enclosure. AGC gain = 60 dB, Rx gain = 0 dB, and Tx gain varied from 2 dB to 8 dB with the step of 2 dB.  
coherent 2 \(\times\) 2 MIMO transceiver with an integrated RF agile direct conversion transceiver AD9361 chip. B210 USRP has RF coverage from 70 MHz to 6 GHz and it supports the instantaneous bandwidth of 56 MHz in the 1 \(\times\) 1 configuration and 30.72 MHz instantaneous bandwidth in the 2 \(\times\) 2 configuration. The Tx and Rx antennas were placed at a distance of 50 mm and the inter-element distance between the transmit and receiving elements was 45 mm. The MIMO interference signal, which is white Gaussian noise, was generated using B210 USRP. USRP channel 1 and USRP channel 2 constellation diagrams degraded as the interference increased. However, the QPSK constellation diagram can be improved by increasing the Tx gain of the communication link USRP with the direct implication of increasing the signal-to-interference-plus-noise power ratio (SINR). Figure 7 shows the measured EVMs of channels 1 and 2. It is clear that the EVM degrades as the interference signal level increases from 60 to 75 dB. The channel 1 EVM degraded from 34% to 43%, which is 26.4% increase in the RMS EVM. Similarly, the channel 2 RMS EVM degraded from 17% to 66%, which is a 288.23% increase in the RMS EVM. Additionally, the channel 1 RMS EVM had a higher standard deviation than the channel 2 RMS EVM standard deviation.  
Figure 8 shows the two-channel BER in the metal enclosure in the presence of MIMO interference. We can see the two-channel BER degrades as we increase the interference level using B210 USRP. The measured BERs are presented for the two Tx gain values ( 8 dB and 10 dB) of the main communication link. The typical BER values increase from 10\({}^{-8}\) to 10\({}^{-1}\) as we increase the interfering USRP gain.  
Figure 6: The 2 \(\times\) 2 MIMO BER and EVM measurement setup in the presence of the MIMO interference.
# VAE-Based Real-Time Anomaly Detection Approach for Enhanced V2X Communication Security
## 5 Discussion
### Future Research Direction  
Building upon the current findings and addressing these limitations, future research will explore several key areas. A primary focus will be to extend the methodology to detect a broader spectrum of anomalies and more sophisticated attack scenarios, such as 'ghost vehicle' creation or advanced DoS attacks, which will involve incorporating additional BSM parameters and potentially fusing data from other V2X message types (CAMs, DENMs) [40] or even V2N messages relevant to applications like teleoperated driving. Crucially, the adaptive retraining mechanism requires rigorous experimental validation using datasets that feature evolving data distributions to quantify its benefits and determine optimal strategies. In conjunction, we plan to investigate advanced continual learning techniques to mitigate catastrophic forgetting during these retraining cycles more effectively. Validation on larger-scale, diverse real-world V2X datasets, collected from different geographical locations and under various data aggregation scenarios, such as distributed detection by multiple agents, is also a priority. Furthermore, we intend to explore the model's scalability and performance when deployed on actual OBU/RSU hardware to assess its practical efficiency and resource utilization. Finally, the attack model will be further refined to include more sophisticated adversarial strategies, and the model's robustness against such advanced threats will be evaluated, potentially incorporating adversarial retraining techniques. Addressing these directions will further enhance the reliability and applicability of VAE-based anomaly detection for securing V2X communications.
## 5 Connected Vehicles
### Prospects
#### 5.4.1 Empowering Technology Development
In addition, vehicle IDs can be readily bound to the owner's credit account and payment information, strengthening the coupling between the physical and the network world to enhance the overall information security and reliability;
* New in-vehicle and mobile-side intelligent terminal software and hardware industries will be spawned, prompting the CV to become an irreplaceable large mobile device integrated into mobile Internet life. Intelligent terminals should have specific human-machine interfaces and be adapted with in-vehicle display hardware to synthesize mobile payment terminals. In addition, they should also have intelligent cloud services based on Telematics, such as intelligent traffic, real-time localization, remote diagnostics, and GID.
## 1 Introduction  
An accurate implant impression and an adequate working cast are important steps in avoiding mechanical and biological complications of dental-implant-supported prostheses [1, 2, 3, 4]. However, a conventional workflow is susceptible to errors that can result in the displacement of implant components and subsequent inaccuracy in the reproduction of the three-dimensional (3D) implant position [5]. By using computer aided design/computer aided manufacturing (CAD/CAM) technology, clinical and laboratory procedures are reduced. Thus, potential inaccuracies related to a conventional workflow are avoided [6, 7].  
The first step in a digital workflow is the acquisition of virtual data by means of intraarol or laboratory scanning [8]. For this purpose, different optical technologies are used, such as photogrammetry, triangulation, confocal imaging, or active wavefront sampling [9]. In general, the principle of image acquisition is the overlapping of multiple acquired images, creating a three-dimensional representation of the scanned object.  
Final surface reconstruction accuracy depends on several steps related to the image acquisition and processing procedures [10]. Whereas scanner devices differ in their capture mode and image reconstruction, the operator experience and scanning protocol also affect the accuracy of digital data [11, 12]. Clinical conditions, such as the presence of saliva and blood, may make it difficult to acquire data, when intraarol scanners are used [13].  
Previous studies have recommended the use of ultrasound to scan dental implants and surrounding tissues [14, 15, 16, 17, 18, 19]. Recently, a high-frequency ultrasound-based scanner was introduced for scanning teeth [19, 20, 21, 22]. According to [PERSON] et al. (2019), the mean deviation value of ultrasound images ranged from 12.34 to 46.38 \(\upmu\)m, and its accuracy was comparable with that obtained by commercially available optical scanners.  
Clinically, it is frequently necessary to scan prepared teeth and dental implants at the same time. However, to date, no study has been conducted on the possibility of using ultrasound for scanning the dental implant. Therefore, this preliminary pilot study showed the digitalization of dental implants scanned with a new ultrasound-based intraoral scanner prototype. Trueness of the ultrasound scanner in comparison with commercially available optical scanners was assessed.
# Comprehensive Analysis of Maritime Cybersecurity Landscape Based on the NIST CSF v2.0
## 5 NIST CSF-Based Analysis of Maritime Cybersecurity
### Protect
#### 5.3.1 Identity Management, Authentication, and Access Control  
The NIST CSF emphasizes the need for Identity Management, Authentication, and Access Control in maritime cybersecurity. Research shows that secure management systems and multi-factor authentication improve security without sacrificing usability. It's crucial to balance these aspects in the digital maritime industry, with ongoing advancements needed to keep systems resilient in a interconnected world.  
The literature highlights the vital importance of education and training in enhancing maritime cybersecurity. It stresses the need for widespread cybersecurity knowledge throughout the industry, including ports, supply chains, and interfaces. The consensus is clear on the need for specialized and practical training solutions to improve maritime cyber defenses. These initiatives aim to increase awareness and establish a robust cyber-secure culture within the maritime sector.  
The reviewed literature highlights the crucial role of robust data security measures in the increasingly digital and interconnected maritime domain. Key findings include the importance of applying technologies like AI and blockchain, using secure protocols, and maintaining ethical standards in cybersecurity research to protect shipboard data, secure communication systems, and ensure the integrity of navigation data. This underscores the urgent need to safeguard maritime systems and data from cyber threats, focusing on comprehensive and proactive approaches to bolster the resilience and security of maritime operations.  
The Platform Security category focuses on aligning the management of an organization's hardware, software, and services with its risk strategy. It highlights the importance of proper configuration management and secure software development to protect the integrity, availability, and confidentiality of platforms. This is crucial for enhancing maritime cybersecurity, including the protection of AS systems and maritime operations. By adopting advanced algorithms and preventive measures for better decision-making and collision avoidance, organizations can boost their cybersecurity resilience and create a safer digital space.
## 3 Results
### Pesticide Use
Specifically, based on the CanESM2 model, pesticide type A as well as pesticide types I, RC, and Ro in projected periods PP1 and PP3 exhibit more considerable pesticide use compared to the CanESM5 model. For pesticide type A, the relative difference between the projected AAIR values by CanESM2 and CanESM5 across all projected periods (PP1, PP2, and PP3) exceeds 90%. In the case of pesticide types I, RC, and Ro, this relative difference falls within the range of [28%, 35.3%] for PP1 and PP3 and [1.5%, 14.4%] for PP2. Conversely, for pesticide types F and H, where the CanESM5 model projects higher pesticide use than CanESM2, the relative differences span [65.6%, 222.9%%] and [114%, 247%], respectively. Figure 7: Comparison of the observed (historical) and projected average pesticide use (in kilograms) for different pesticide types across various projected periods (PP1, PP2, and PP3) based on CanESM2 and CanESM5 climate models (F: fungicides, H: herbicides, I: insecticides, RC: growth regulators, Ro: rodenticides, and A: others). Table 4 shows the ANOVA results (F-statistics and corresponding \(p\)-values) for six pesticide types (A, F, H, I, RC, and Ro) across all years and specific periods. The ANOVA results indicate highly significant differences between the historical data and the CanESM2 model across most pesticides and periods, particularly for pesticide F and pesticide A. For instance, pesticide A shows a large variance in PP2, with an F-statistic of 1.43 \(\times\) 10\({}^{2}\) and a very low \(p\)-value of 4.31 \(\times\) 10\({}^{-30}\), indicating substantial deviation in the projected usage compared to historical values. Similarly, pesticide F shows extremely significant differences across all periods, with an exceptionally high F-statistic (1.84 \(\times\) 10\({}^{3}\)) for all years, confirming strong discrepancies between historical and CanESM2 projections. These results suggest that CanESM2 predicts substantial increases in pesticide usage for certain types, especially during the later periods, likely due to changing climate conditions under this model. In addition to pesticides A and F, other pesticide types, such as RC and Ro, show notable differences under the CanESM2 model.
## 4 Fatigue Wear Test
### Analysis of Fatigue Test Results
#### 4.3.2 Analysis of Bearing Lubrication Parameters  
Figure 13 presents a comparison of the bearing lubrication parameters for the different bearings with varying wear test durations. As the wear time increases, the torque and the bearing temperature signals show an upward trend. Combined with the measurements of wear amount, it can be seen that the wear amount of the aluminium alloy bearing increased in the third and fourth hours of the five-hours wear test. This is because the poor lubrication state increased friction power consumption, and the corresponding bearing temperature and torque increased significantly. However, the torque and bearing temperature of the copper alloy bearing increased slightly, indicating its good abrasion resistance.  
Figure 14 shows a comparison of the oil film thickness of the different bearings. With the extension of the fatigue wear test time, the oil film thickness of the aluminium alloy bearing varied greatly, in the range of 5-160 \(\upmu\)m. The copper alloy had the better wear resistance, and its oil film thickness was relatively stable, with small fluctuations in the range of 5-98 \(\upmu\)m.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Time (h)**} & **Bearing Clearance** & **Lower Bearing** & **Lower Bearing** \\  & **(mm)** & **Thickness (mm)** & **Roughness (\(\upmu\)m)** \\ \hline
0 & 0.140 & 1.820 & 0.787 \\ \hline
5 & 0.145 & 1.816 & 0.812 \\ \hline
10 & 0.149 & 1.813 & 0.982 \\ \hline
15 & 0.151 & 1.812 & 1.232 \\ \hline
20 & 0.152 & 1.810 & 2.332 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Measurement results of the surface state of the copper alloy bearing at different times.  
Figure 13: Comparison of bearing lubrication parameters of different bearing shells with different wear test durations.  
Figure 15 presents a comparison of the minimum oil film thickness of the different wear test durations. As the fatigue wear test progressed, the minimum oil film thickness of the two bearings decreased. When the bearing was severely worn, the minimum oil film thickness was below 5 \(\upmu\)m.
# A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station
## 4 Performance Comparison
### Simulation Setting and Examples
#### 4.1.2 Example SRS and Positioning Result  
In this section, the example SRS used in the simulation in Section 4.2 for the positioning of three different UEs is shown in Figure 3(a),b.
# Adaptive Path Planning for UAV-Based Pollution Sampling
## 4 Experiments and Results
### Results of Pollution Sampling with Adaptive Path Planning
#### 4.6.3 Final Modifications and Results
Additionally, the map includes obstacles (red semi-transparent polygons). Red markers with numbers indicate measurement maneuvers. The type and parameters of each maneuver are defined via point metadata. For example, point 18 indicates ascending vertical helix profiling, while points 15, 16, and 17 are the next measurement waypoints that comprise a point-to-point horizontal measurement path. Figure 11: Initial mission settings as presented in Mission Planner—final integration experiments. Figure 10: Real path visualized in Mission Planner. The final optimized flight path provided by the GPP is shown in Figure 12. Due to Mission Planner's inability to display a relatively complex 3D path, only the MATLAB results are presented. Thin yellow dots comprise the path planned by GPP. Red and green tetrahedrons mark the start and end waypoints.
## 4 Anti-Cancer Activities of Tanshinones
### Anti-Proliferation and Pro-Apoptosis
#### 4.1.2 Tanshinone IIA (TIIA)
Moreover, combination of TIIA with a PI3K inhibitor (LY294002) enhanced TIIA-induced apoptosis in LNCaP and PC-3 prostate cancer cells which contained high AKT, but did not in MDA-MB-231 breast cancer cells which contained undetectable AKT, suggesting a possible involvement of PI3K/AKT survival pathway [133]. [PERSON] _et al._[163] found that TIIA treatment activated pro-apoptosis p38 MAPK pathway and then suppressed the expression of pro-survival gene survivin, as well as drug-resistance genes excision repair cross-complementing gene 1 (ERCC1) and lung resistance protein (LRP) in a time- and concentration-dependent manner. Blockade of p38 MAPK pathway by its inhibitor SB203580 attenuated TIIA-induced inhibition of these pro-survival genes and apoptosis, suggesting a mediator role of p38 MAPK. In addition, TIIA was used as an AP-1 inhibitor to suppress AP-1-mediated transcription of aldo-keto reductase 1B10 (AKR1B10), an oncoprotein over-expressed in human liver and lung tumors [177].
## 4 Experimental Evaluation and Performance Analysis
### Experiment Scenario
\right],Q_{p}=\left[ \begin{array}{cccccc}0.5138&0.5701&1.0000&0. 1291\\ 0.1562&0.2368&0.1837&0.1931\\ 0.0393&0.2015&0&1.0000\\ 0.0076&0.0215&0.2857&0.7566\\ 1.0000&0.1838&0.0476&0.3294\\ 0.1353&0.6197&0.2857&0.1291\\ 0.0118&0.1411&0.0476&0\\ 0.2368&0.0476&0.2286\\ 0.0620&0.2563&0.1071&0.1931\\ 0.1644&0.1411&0.0476&0.1000\\ 0.0392&0&0.0476&0\\ 0.1353&0.6197&0.2857&0.5395\\ 0.0776&0.4444&0.629&0.6400\\ 0.2314&0.3804&0.4286&0\\ 0.3754&1.0000&0.4286&0.4000\\ \end{array} \right]\]  
The development environment included an Intel(r) CoreTM i7-8550U CPU (Intel, Santa Clara, CA, USA), 1.80 GHz notebook with an 8.00 GB memory. The operating system of the notebook was Windows 10 (64 bit), and the MATLAB version was R2022a. Based on the above discussion, the value range for \(\sigma_{t}\) and \(\sigma_{p}\) was set as [0, 10]. The cloud manufacturing platform and the user set parameters were as follows: \(a_{\#}=2\), \(b_{\#}=7\), \(a_{fc}=2\), \(b_{fc}=7\), \(a_{t}=2\), \(b_{t}=7\), \(a_{p}=2\), and \(b_{p}=7\), from which the decision satisfaction membership function could be determined. Before using the genetic algorithm in a real-time simulation environment, different genetic algorithm parameters within the implementation were studied, as the parameter settings might impact the solution quality and speed. The influencing factors of genetic algorithms include the population size (POP), maximum number of iterations (MAX), crossover rate (CR), and mutation rate (MR). We compared the influence of each parameter on the experiment and set the final parameters of the genetic algorithm, as shown in Table 1.
## 3 Results
### _TLC-UV Fractionation and FTIR Measurements of Crude S. triloba Acetone Extract_  
TLC-UV fractionation of the acetone crude extract yielded four fractions (RF1, RF2, RF3, and RF4) with respective retention factors of 0.22, 0.39, 0.57, and 0.81. These varying retention factors indicated that the isolated fractions possessed a range of polarities, with RF1 displaying the least polarity, followed by RF2, RF3, and RF4 (Figure 10 and Table 8).  
Figure 10: TLC-UV fractionation of crude S. _triloba_ acetone extract. Four fractions were generated from the acetone extract by thin layer chromatography (TLC); the calculated retention factors (Rf) ranging from 0.2 to 0.8 suggested a mixture of compounds with varying polarities whose bioactivities require further investigation.  
Figure 9: _S. triloba_ acetone extract does not induce hemolysis in human erythrocytes. Hemolytic activity of _S. triloba_ acetone extract at concentrations approximate to either IC\({}_{50}\) (54.51 ug/mL) or IC\({}_{75}\) (190 ug/mL) was about 1.282% and 3.157% respectively. When compared to untreated samples, the hemolytic activity of _S. triloba_ acetone extract was negligible and the differences were not statistically significant. Deionized water served as a positive control that induced 100% hemolysis. Results are a representation of three independent experiments (\({}^{***}p\leq 0.001\), \({}^{**}p\leq 0.01\), \({}^{*}p\leq 0.05\)).  
Furthermore, FTIR measurements were performed on _the S. triliba_ leaves and their crude acetone extract, and the obtained spectra are shown in Figure 11. Similar peaks appear in both spectra which indicate that acetone extracted most of the major constituents of the leaves. Peaks at 3420 and 1383 cm\({}^{-1}\) pertain to the respective stretching and bending of the OH phenolic groups [50; 51]. The peaks at 2920 cm\({}^{-1}\) can be attributed to the stretching vibration of the CH aliphatic groups that probably belong to terpen [50]. In addition, the peaks corresponding to the carbonyl stretch of the carboxylic acid and ester groups appeared at 1728 and 1262 cm\({}^{-1}\)[52], while the peaks appearing at 1650 and 1450 cm\({}^{-1}\) can be ascribed to the vibrations of the uronic acid groups [53; 54]. As for the 1109 cm\({}^{-1}\) peak, it belongs to the acidic polysaccharides [51; 55].
## 3 System Outbound Process Modelling
### Average Service Time Model for a Four-Way Shuttle System Server  
To describe the four-way shuttle system based on the operation time model in detail, the parameters used in the model and their meanings are expressed as shown in Table 2.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Meaning** & **Parameters** & **Meaning** \\ \hline \(T\) & Storage levels of shelves & \(W_{A}\) & Roadway width (m) \\ C & storage columns for shelves & \(H\) & Single storage rack height (m) \\ N & Number of tunnels served by a single hoist & \(Vs\) & The average speed of shuttle (m/s) \\ \(A\) & Number of longitudinal aisles of single-level shelves & \(\epsilon_{s}\) & Average loading/unloading time for shuttles (t) \\ \(S\) & Total storage system capacity & \(\gamma_{s}\) & Time delay caused by shuttle \\ \(L\) & Length of individual cargo space (m) & \(V1\) & The average speed of hoist (m/s) \\ \(W\) & Width of individual cargo space (m) & \(\epsilon_{l}\) & Average loading/unloading time of hoist (t) \\ \(M\) & Number of shuttles served by a single hoist & \(\gamma_{l}\) & Time delay due to hoist acceleration/deceleration (t) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Meaning of unknown parameters in the model.  
Set the pickup task at the t tier as a customer of class t. From assumption 3, the probability of serving a customer of class t is:  
\[P(t)=\frac{1}{T} \tag{1}\]  
Set the goods to be picked up in column \(M_{ac}\) of aisle t, where \(a=1,2,\dots,\ N\), \(c=1,2,\dots,\ C\); then, the probability of picking up the goods is:  
\[P(M_{ac})=\frac{1}{2\cdot N\cdot\mathbb{C}} \tag{2}\]  
The calculation of the equipment service time can be divided into two cases, depending on the availability of the idle four-way shuttles in the layer of goods to be picked up. These are the parallel operation strategy, where there are free four-way shuttles in the pickup layer, and the serial operation strategy, where there are no free four-way shuttles in the pickup layer.