esa-sceva/satcom-chunk-collection huggingface dataset:
# Random Access Performance of Distributed Sensors Attacked by Unknown Jammers
## 2 System Model
### Power Capture Model for Preamble Transmission  
Let us consider a typical access slot where there are \(s\) access codes available and \(k\) SNs (including SN-A) select the same code. Let \(n_{p}\) (previously \(n\)) denote the number of SNs that are in simultaneous PT, \(n_{I}\) be the total number of jammers and \(n_{m}\) be the number of SNs that are transmitting MSG in this slot. If code jamming is considered, we assume that there are one code jammer and \(n_{I}-1\)power jammers. Let \(P_{i}^{(p)}\), \(P_{j}^{(m)}\) and \(P_{l}\) be the total received power from SN-\(i\) transmitting a preamble, from SN-\(j\) transmitting MSG and from a hostile jammer, respectively. Since the preamble contains only the repetitions of a selected code, assuming a perfect RAKE receiver, HS can aggregate the power of PTs from those \(k\) code-collided SNs (including SN-A) and the jammer (if it uses code jamming) [20; 21]. Let \(\beta_{p}\) be the minimum signal-to-interference-plus-noise ratio (SINR) required to decode a preamble successfully. Then, the condition for correct reception of the preamble sent by SN-\(A\) (or SNs using the same code) when the attack is power jamming is:  
\[\frac{P_{A}^{(p)}+\sum_{i=2}^{k}P_{i}^{(p)}}{\sum_{i=k+1}^{np}P_{i}^{(p)}+\sum_ {j=1}^{n_{m}}P_{j}^{(m)}+n_{J}P_{j}+\eta}\geq\beta_{p}, \tag{4}\]  
where \(\eta\) represents interfering power from other sources (for example, from a neighbor WSN using an adjacent RF channel) plus background noise.  
If the attack includes code jamming, the above condition becomes:  
\[\frac{P_{A}^{(p)}+\sum_{i=2}^{k}P_{i}^{(p)}+P_{j}}{\sum_{i=k+1}^{np}P_{i}^{(p) }+\sum_{j=1}^{n_{m}}P_{j}^{(m)}+(n_{J}-1)P_{j}+\eta}\geq\beta_{p}, \tag{5}\]  
where \(P_{j}\) in the numerator is the received power from the code jammer transmitting a fake preamble using the same code and \((n_{J}-1)P_{j}\) is the sum of powers from power jammers and/or the other code jammers that are using different access codes.  
Let \(q\) denote the probability of successful reception of AI by an SN, which is assumed independent of all other uplink probabilistic matters since AI is received through the downlink. Additionally, let \(W\) be the number of SNs that successfully receive AI among \(K-1\) SNs except SN-A. Then:  
\[\Pr\{W=w|K=k\}=\binom{k-1}{w}q^{w}(1-q)^{k-1-w},\quad 0\leq w\leq k-1. \tag{6}\]
# Aromatic Amines in Organic Synthesis Part III; \(p\)-Aminocinnamic Acids and Their Methyl Esters
## 2 Results and Discussion
The fluorescence quantum yield of the synthesized acids and esters is low, and it does not exceed 3.5% in non-polar (1,4-Dioxane), polar aprotic (EtOAc), and protic (MeOH) solvents, which proves that the deactivation of the S\({}_{1}\) excited state occurs mainly by non-radiative processes. The only exception is compound 2o, for which the fluorescence quantum yield is 59.9% in 1,4-dioxane, 74% in ethyl acetate, 70.8% in DMF, and 61% in methanol. The results suggest that the modification of the amino group does not significantly affect the fluorescence quantum yield of the cinnamic acids. However, the slightly higher fluorescence intensity in polar solvents, both protic and aprotic (see Tables 1 and 2), may be attributed to the protic nature of the solvent and/or high polarization character (dielectric constant of 32.66 for MeOH and 36.71 for DMF). This feature contributes to the stabilization of the excited states and the charge or dipole of the molecule [41,42] and molecular symmetry, preventing non-radiative decay [43,44,45]. Compound 2e showed the lowest fluorescence intensity regardless of the solvent. Probably, the presence of a methyl group in the _ortho_ position in relation to the central double bond (_meta_ position in relation to the amino group) causes the molecule to twist and leads to a coplanar conformation, which reduces the probability of radiative transitions. On the other hand, the \(\phi_{\text{FI}}\) values for compound 2o in 1,4-dioxane, EtOAc, DMF, and MeOH with respect to 2a are over 71-, 120-, 34- and 89-fold higher, despite the same electron-donating (NMe\({}_{2}\)) and -withdrawing (COOH) groups. In fact, the electronic character of the \(N\),\(N\)-dimethylamino group in 2o is significantly altered by the elongation of the conjugated \(\pi\)-system by introducing an additional aromatic ring into the molecule, which stiffens the molecule and lowers the HOMO-LUMO energy gap [46] compared to 2a. As a consequence, the fluorescence intensity increases. The literature data for other naphthalene derivatives with a dimethylamine group: 6-(dimethylamino)-2-naphthic acid (\(\phi_{\text{fl}}\) = 0.53) [47], 6-(dimethylamino)-2-naphthaldehyde (\(\phi_{\text{fl}}\) = 0.84) [46], and 2-(dimethylamino)-naphthalene (\(\phi_{\text{fl}}\) = 0.89) [48] indicate that high fluorescence intensity is a feature of naphthalene derivatives substituted into position 2  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**No.
## 2 Working Principle of Electromagnetic-Ring Balancing Actuator
### Comparisons with Existing Electromagnetic-Ring Balancing Actuator  
The existing electromagnetic-ring (EM-ring) balancing actuator is widely used in the spindles of machine tools, such as grinding, turning and milling tools [23]. As shown in Figure 6, the balancing ring for the shaft assembly includes two balancing rotors (called counterweight discs in this paper) and these two rotors, fixed by magnetic forces, are actuated by the electromagnetic fields of the stator coils, which is the same as the new actuator proposed in this study. However, there are several obvious differences between these two balancing actuators: (1) the balancing ring and stator of the existing balancer are installed independently, which is difficult in field installation to adjust the small gap between these two parts, while the balancing ring and stator of the new balancer are integrated and the gap is pre-adjusted, which greatly reduces the difficulty of installation; (2) the gap between the ring and stator of the new actuator can be smaller than the existing one, so the transfer efficiency of the magnetic field is higher and the required current is lower; (3) the existing actuator can only be installed outside of the rotor, generally at the root of the extension section of the spindle, while the new actuator can be installed into the rotor, broadening its application; and (4) the magnetic circuit of the new actuator is redesigned to suit the new installation method, which is better for transferring magnetic field. Specific parameters of these two actuators are shown in Table 1. According to the comparison results, although the balancing speed of the new actuator is a little lower than the existing actuators, the new actuator has great advantages in the structural dimensions and balancing ability, which verifies the superiority of the new actuator.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Item** & \multicolumn{3}{c}{**Existing Actuator**} & \multicolumn{2}{c}{**New Actuator**} \\ \hline Inner diameter (mm) & 95 & 115 & 160 & — \\ Outer diameter (mm) & 192 & 203 & 250 & 66 \\ Width (mm) & 34 & 33 & 33 & 60 \\ Balancing ability (g\(\cdot\)mm) & 200 & 1000 & 1500 & 1168 \\ Balancing speed (rpm) & 5500 & 9000 & 7000 & 3600 \\ \hline \end{tabular}
\end{table}
Table 1: Parameter comparison between the existing actuator and the new actuator.  
Figure 6: Working principle of existing electromagnetic-ring balancing actuator: (**a**) Physical map of the balancing actuator; (**b**) Spindle with balancing actuator; (**c**) Sectional view of balancing actuator; (**d**) Components of balancing system.
## 3 Results  
### MSC-CM Promotes Wound Healing  
Figure 1 displays the progression of wound closure in the scratch assay of the HaCaT keratinocyte in the presence of MSC-CM from the time of scratching until 72 h after the scratch was performed under a phase-contrast microscope. Clearly, the width of the healed area of the HaCaT keratinocyte treated sample was more rapidly closed than that of the untreated sample in 48 h and 72 h of observation. A similar result was also seen from the quantitative evaluation (Figure 2) when the HaCaT keratinocyte scratch assays were performed in MSC-CM, where there was a significantly enhanced rate of cell migration compared to the control. To be more specific, when the cell migration of the HaCaT keratinocyte scratch assays was 45% in the control medium (at the 48 h time point), it was almost 60% in the presence of MSC-CM. At the 72 h time point of the experiments, when the cell migration rate of the HaCaT keratinocyte scratch assays was 70% in the presence of MSC-CM, it was only 50% in the control medium. These findings indicate that MSC-CM enhanced the rate of wound closure of the HaCaT keratinocyte by promoting cell migration during wound healing.  
To examine whether MSC-CM could stimulate cell survival and proliferation during wound closure, the HaCaT keratinocyte and HFMSC were treated with different kinds and concentrations of drugs. Given the above-mentioned reasons, these drugs have the ability to improve cell growth and proliferation, thus, in this study, we used them as positive controls compared to our MSC-CM. After the treatment, the Ki67 (proliferation marker) positive cells were found more in the HFMSC and HaCaT keratinocyte treated groups compared to control (Figure 3). The quantitative study from Figure 4 shows that among all kinds of drug treatments, in both the HFMSC and HaCaT keratinocyte, the group treated with MSC-CM showed the noticeably highest cell proliferation compared to other drugs. The results indicate that the conditioned medium of MSC at low to high concentrations can effectively promote the proliferation of the HFMSC and HaCaT keratinocyte, supporting the progression of wound healing.  
Figure 1: Optical micrographs showing the progression of wound closure in scratch assays of HaCaT in the presence of MSC-CM at different observational periods.  
Figure 2: Quantitative evaluation of the wound healing reflecting the migration rate of the cells around the wound at various time intervals (\({}^{*}p<0.05\) and \({}^{**}p<0.01\)).  
Figure 3: Ki67 staining of (**a**) HFMSC and (**b**) HaCaT after being treated with different kinds of drugs. More Ki67 positive cells were observed in both the HFMSCs and HaCaT treated samples.
## 4 Design, Development, and Implementation
### Setup and Technical Specifications of the Equipment  
The implementation of the proposed workflow for the development of the virtual reality tool considered the hardware and software setup detailed in Table 2. From a graphical perspective, special attention must be paid to the computer's graphics card to ensure proper and smooth texture processing. In this case, the application was run from the computer and was visualized and interacted with through virtual reality headsets.  
It is noted that while the Intel i5-10300H CPU used (10 th generation) is more recent than the listed minimum recommended i7-6700 (6 th generation), the latter belongs to a higher performance tier. However, for the specific demands of our VR simulation, which prioritized GPU performance for rendering the Unreal Engine environment, the i5-10300H coupled with the NVIDIA GeForce GTX 1650 Ti provided a smooth and consistent user experience without noticeable performance degradation or frame rate issues that would impede the evaluation tasks. Any potential minor performance differences were deemed not to have impacted the study's outcomes regarding accessibility evaluation.  
For the testing sessions and overall use of the experience, it is recommended to have an adequate physical space that allows for the safe use of the VR headset, free from movement restrictions or risk of collisions with surrounding objects. A stable Wi-Fi connection and a clear, unobstructed working area are particularly important. Figure 9 shows the configuration of the testing space (virtual reality lab), which includes a Meta Quest 2 headset, Oculus Link cable, 50\" TV, wheelchair, support computer, development and evaluation computer, and a smartphone tripod used for recording the testing sessions.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Components** & **Minimum** & **Minimum Recommended** & **Used** \\ \hline GPU & NVIDIA GTX 1070 & NVIDIA GeForce RTX 3080 & NVIDIA GeForce GTX 1650 Ti \\ CPU & Intel i7-6700 & Intel i7-11800 & Intel i5-10300H \\ RAM & 16 GB & 32 GB & 16 GB \\ Video Output & HDMI 1.3 & HDMI 1.3 & HDMI 1.3 \\ USB & USB 3.0 & USB 3.0 & USB 3.0 \\ Operating System & Windows 8 64 bits & Windows 11 64 bits & Windows 10 64 bits \\ VR Headset & Meta Quest 2 & Meta Quest 2/3 & Meta Quest 2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Hardware and software used.  
Figure 9: Laboratory setup for testing: **(a)** 3D model—general view of the laboratory; **(b)** testing setup.
## 1 Introduction
Using symmetrical properties, we only exploit the upper triangular part of this matrix in order to considerably reduce the computational cost of the RAD. Then, we show that for a White Gaussian Noise (WGN), the coefficients of the first top diagonal of the distance matrix become a representative sample of all other coefficients. This is not the case for a communication signal even with a small SNR. This new approach can detect a communication signal in a very low SNR. We have analytically established the probabilities of detection \(P_{d}\) and false alarm \(P_{fa}\). Through Monte Carlo simulations, we studied the Receiver Operating Characteristic (ROC) curves of the RAD. The theoretical and experimental results show the ability of the RAD to detect the presence of a communication signal as soon as the SNR is greater than \(-12\) dB with a very low probability of a false alarm. The rest of this paper is organized as follows: Section 2 presents the problem of spectrum sensing and our motivation for RQA. Section 3 deals with the concepts of RQA and the state of the art in the determination of embedding parameters in order to exhibit the hidden recurrences. Sections 4 and 5 present the Recurrence-Analysis-based detector model and its theoretical and experimental performance. The last section contains the conclusion and perspectives.
# Investigation of Steep Waste Dump Slope Stability of Iron Ore Mine--A Case Study
## 3 Results and Discussion
### Capabilities of the PFC Particle Flow in Capturing Both Mechanical Behavior and Response  
After obtaining the micro-scale parameters for the slope model through direct shear test simulation, the Waste Dump#1 slope model was imported into PFC3D. It is divided into geological base and slope morphology. A set of soil parameters of the waste dump was selected for simulation. The relationships between the average shear stress and the average shear displacement in laboratory tests and the numerical simulation results for various samples have been illustrated in Figure 9. The simulation and the experimental data represent a similarity of 94.55%. This clearly indicates that the proposed PFC-based model is an effectual numerical model for rational capturing of the soil material's mechanical strength in the presence of various vertical stress levels.  
First, both the particle size and model were determined to establish a three-dimensional direct shear model. Then, the simulation results were fitted with the experimental results to calibrate the micro-scale parameters. The effective contact modulus, stiffness ratio, friction coefficient between particles, friction coefficient between particles and walls, and tensile and shear strengths in order were determined as 0.2 GPa, 1.5, 0.5, 0.35, and 10 MPa. The boundary model for the waste dump was imported, particles were generated inside the region, and excess particles were removed. The slope model was established and a linear contact model and linear contact bonding model were assigned for simulation calculations. Figure 10 illustrates the morphology of the waste dump slope and particle displacement distributions in the \(x\) and \(y\) directions.  
Figure 9: Average shear stress in terms of the average shear displacement for various soil samples in tests and simulations.  
In the \(x\) direction, the particles have displaced up to 50% of the entire model with a maximum displacement of 0.45 m. The particles displaced in the \(y\) direction comprise 70% of the model with a maximum displacement of 0.4 m. Intercepted sections were employed to analyze the movement of particles in Waste Dump#1. Figure 11 displays the particle displacement distribution in a profile for the slope region before rectification.  
Figure 11 also provides a top view of the slope, selected location, and particle displacement distribution in the \(x\) and \(y\) directions of the profile. From the results, the maximum displacement distance of particles in the \(x\) direction reaches 0.43 m and the maximum displacement distance of particles in the \(y\) direction reaches 0.35 m. The area where sliding occurred is marked in red, which includes 40% of the particle distribution in the entire slope.
# Characterization of GNSS Signals Tracked by the iGMAS Network Considering Recent BDS-3 Satellites
## 3 Methodology and Results
### Satellite-Induced Code Bias  
Satellite-induced code bias, which is absent from other GNSS satellites, has been identified to exist in BDS-2 code observations and reported in many studies [17; 18; 19]. In our experiment, it was further confirmed using observations from the iGMAS station, as shown in Figure 6. Since such an obvious bias was consistently observed with various receivers and antennas, it can likely be attributed to the transmitting satellites [20]. In addition, this satellite-induced code bias is frequency- and elevation-dependent, and can vary more than 1 m from horizon to zenith, which would severely affect BDS-2 precise applications involved with code observations [21; 22; 23]. Therefore, the question of whether this bias continues to exist in BDS-3 code observations deserves our attention.  
Figure 7 shows the MP series for five available BDS-3 signals observed from the station HMNS equipped with GNSS_GGR receiver and RINT-8 CH CETD antenna, the station BJF1 with CETC-54-GMR-4016 receiver and LEIAR25.R4 LEIT antenna, and the station PETH with CETC-54-GMR-4011 receiver and GNSS-750 antenna, as listed in Table 3. The BDS-3 satellites used in this study can be divided into four groups (C19/C20, C21/C22, C27/C28, C29/C30) according to the launch status as shown in Table 1. We selected the results of one satellite from each group for illustration in Figure 7, and results of other BDS-3 satellites are similar. It should be noted that only the RINT-8 CH CETD antenna is capable of receiving all five of the BDS-3 signals, and others cannot receive B2b signals in the iGMAS network (Table 3). From Figure 7, we can see that the MP values become more stable and gradually approach zero as the elevation angles increase. As was also seen in Figure 4, it is clear that the BIC signal is affected more seriously by multipath and noise for all selected satellites and stations due to a lower chip rate. Most notably, the satellite-induced elevation-dependent code biases of all the available BDS-3 signals observed by different GNSS receivers and antennas were dramatically reduced and considered to be inconsequential relative to those of BDS-2 in Figure 6.  
Figure 6: Multipath (MP) series of tracked signals of BDS-2 (B1I/B3I), GPS (L1/L2/L5), and Galileo (E1/E5a/E5b) satellites as a function of satellite elevation at WUH1 station.
# A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision
## 4 Discussion
### Region of Interest Recognition Algorithm  
In field trials, the model performs well in identifying large rock sizes in trucks transporting ore, meeting the practical needs of the project in most cases. However, in engineering sites, the wide lateral field of view of the equipment can lead to misidentifications of irrelevant objects, such as tires and roadside rocks, thus reducing the scanning accuracy.  
To solve the issue of misidentifications caused by the wide lateral field of view of the equipment, this study employs a targeted ROI (Region of Interest) recognition algorithm, which limits the area of interest during the scanning process, thereby reducing the impact of misidentifications and improving the accuracy of detection and analysis. The ROI recognition algorithm is a core technology in image processing and computer vision, widely used in fields such as medical imaging, video surveillance, and autonomous driving, capable of extracting relevant parts from images or video streams for specific tasks [29; 30; 31]. The basic idea is to analyze the content of the image to identify one or more areas of interest. This includes steps such as image preprocessing, feature extraction, region segmentation, and region filtering. Through these steps, the algorithm can identify target objects or areas from the image, followed by further analysis or processing. The ROI recognition algorithm in this study involves cropping out the truck carrying ore in the image, preprocessing it, and then performing recognition, while excluding the rest of the image from inputting to the YOLOv8 instance segmentation model. After recognizing the truck part, it is then reassembled with the unrecognized portion, as shown in Figure 18. After incorporating the ROI recognition algorithm, the model's recognition performance is shown in Figure 19.
## 3 Results and Discussion  
### Fresh Behaviour  
It was noticed that the incorporation of sanitary ware waste as a filler improved the workability of the resulting mortar (SWP mortar), allowing a decrease of the w/b ratio from 1.3 to 0.9 for similar consistency, when compared with the REF mortar (Table 1). The SWP waste filled the voids between the particles of sand, thus decreasing the water needs of the mortars [6]. On the contrary, the SWF and FBA wastes were responsible for a slight reduction of the mortars' workability. These mortars presented a w/b ratio of 1.4, which corresponded to an increase of 8% in comparison with REF's [5][14]. In relation to the SWF mortar, the increment of water needs was related to their angular shape. This shape is responsible for an increase of specific surface area, in comparison with the more spherical particles of sand and, consequently, for a higher volume of water needed to lubricate the particles.  
When SWF and FBA were combined in a single mortar (SWF+FBA), the negative effects of both wastes on workability were combined, resulting in a w/b ratio of 1.5, which was higher than REF's by 15%. When SWP was combined with FBA in the SWP+FBA mortar, a reduction of w/b ratio was possible (meaning an improvement of workability), in comparison with the REF mortar. Similarly, when SWP was combined with SWF and FBA in the SWF+SWP+FBA mortar, the negative effects of SWF and FBA on workability were offset by the benefits of SWP and the SWF+SWP+FBA mortar presented a better workability than that of the REF mortar. The mortar presented a w/b ratio 8% lower than that of the REF mortar, for similar consistency.  
In conclusion, SWP+FBA and SWF+SWP+FBA mortars presented improvements in workability, which was due to the SWP waste, i.e., the filler was able to compensate for the negative effects of SWF or FBA on this fresh-state property.  
Concerning bulk density, the incorporation of sanitary ware as an aggregate (SWF) or as a filler (SWP) led to a completely different behaviour. Filler incorporation, due to a filler effect, increased the bulk density of the mortars. Aggregate incorporation, on the other hand, was responsible for a reduction of bulk density. The FBA waste also increased the bulk density of the mortars. The combination of these wastes in a single mortar (SWF+SWP+FBA) resulted in a lower bulk density, 5% lower than REF's. The value obtained was an intermediate value between the ones presented by the SWF and SWP mortars. Nevertheless, the differences between bulk densities were noticed to be slight, all the mortars presenting in fact similar values, not compromising this fresh-state characteristic.