esa-sceva/satcom-chunk-collection huggingface dataset:
# Targeting Type II Toxin-Antitoxin Systems as Antibacterial Strategies
## 3 Strategies for the Artificial Activation of Toxin-Antitoxin Systems
### Indirect Activation of TA Systems  
#### 3.2.1 Enhanced Expression of Proteases Degrading Antitoxins  
As previously mentioned, the antitoxins of type II TA systems are more susceptible to degradation by host cytoplasmic proteases than their cognate toxins. In most cases, bacterial Lon protease is involved in antitoxin degradation; however, the two-component protease ClpP, acting in cooperation with the chaperones ClpA or ClpX, is used by some TA systems [66; 67; 68].  
The depletion of antitoxin molecules results in the liberation of the toxin proteins from TA complexes and relieves transcriptional repression of TA operons, causing increased production of TA transcripts. These events alter the stoichiometry of TA molecules in a cell and ultimately have a lethal effect [69]. Therefore, increasing the level of cellular proteases or designing specific molecules that activate these proteases could be a promising strategy for the indirect activation of toxins (Figure 3a).  
Increased protease expression can be achieved by introducing a plasmid carrying a cloned protease gene. Overproduction of the Lon protease is known to be lethal for _E. coli_ cells [70]. However, by employing an inducible Lon overproduction system, [PERSON] and colleagues overcame this problem to demonstrate that the lethality is partially dependent on the _yeft-yoeB_ TA system [66]. They showed that overproduction of Lon triggered YoeB-dependent mRNA cleavage, leading to translation inhibition. This, in turn, activated the YoeB toxin by preventing the synthesis of its unstable YefM antidote, which was eventually lethal to the host cells [66].  
Proteolysis is a tightly controlled process which can be significantly influenced by specific molecules targeting proteases. For example, acyldepispeptides (ADEPs) are compounds with antibiotic properties that specifically activate the bacterial protease ClpP. Uncontrolled proteolysis induced in this way inhibits bacterial cell division and results in cell death, possibly with the participation of activated toxins [71].  
Figure 3: Proposed antibacterial strategies based on the indirect activation of toxins of TA systems: (a) activation of the Lon or ClpP proteases that degrade antitoxins; (b) triggering TA systems by quorum sensing factors; (c) triggering TAs by artificial induction of the stringent response (see text for details).
## 4 HRWS Imaging Processing
### ETF Imaging Algorithm
Based on the spectrum expression of SAR baseband signal, assume that the center of the imaging scene is set as the reference range \(R_{ref}\); then, the exact transfer function of the ETF imaging algorithm is developed as  
\[H_{eff}^{*}\Big{(}f_{\eta},f_{\tau};R_{ref}\Big{)}=\exp\left(j\pi\left(\frac{4 R_{ref}(f_{c}+f_{\tau})}{c}\sqrt{1+\frac{c^{2}f_{\eta}^{2}}{8(f_{c}+f_{\tau})^{ 2}Lr\beta_{1}\omega_{s}^{2}}}+\frac{f_{\tau}^{2}}{K_{r}}\right)\right). \tag{29}\]  
The exact transfer function multiplication has the effect of canceling the phase at the reference range, which can achieve the full focus of the targets in the range. However, since SAR echo data is dependent on the variability of the range, there exists azimuth residual phase at the non-reference range, then the azimuth image will have a different degree of defocusing. Thus, in the Doppler domain, the residual phase is further compensated to fulfill the focusing of the targets at the non-reference range. The compensation transfer function is designed as  
\[H_{\Delta\Theta}\big{(}f_{\eta},R_{s}\big{)}=\exp\left(j\pi\left(\frac{4 \Big{(}R_{s}-R_{ref}\Big{)}}{\lambda}\sqrt{1+\frac{c^{2}f_{\eta}^{2}}{8 Lr\beta _{1}\omega_{s}^{2}f_{c}^{2}}}\right)\right). \tag{30}\]  
After the processing of the compensation function multiplication and inverse Fourier transform in azimuth, the focused image of targets at the non-reference range can be finally realized. To achieve the full focus of targets near swath edge at the non-reference range, it is worth noting that the ETF imaging algorithm generally constrains the maximum non-reference range relative to the center of the SAR scene. That is, the difference of the maximum range cell migration at the non-reference range and the reference range should be less than the range resolution, meaning that  
\[\left|\sqrt{\Big{(}R_{ref}+\Delta R\Big{)}^{2}-2 Lr\beta_{1}\theta^{2}}-\sqrt {R_{ref}^{2}-2 Lr\beta_{1}\theta^{2}}-\Delta R\right|<\rho_{r}=\frac{c}{2B_{r}}, \tag{31}\]  
where \(\rho_{r}\) denotes the range resolution, and \(B_{r}\) represents the bandwidth of the transmit signal. Here, to further satisfy the requirement of SAR wide-swath imaging for hypersonic platform, the range swath can be divided into several sub-swaths based on Equation (31), and the center of each sub-swath is set as the reference range. Based on the analysis above, the major operations of the ETF algorithm for HRWS SAR imaging are shown in Figure 7, where \(H^{*}_{eff,i}(f_{\eta},f_{\tau};R_{ref,i})\) and \(H_{\Delta\Phi,i}(f_{\eta},R_{s})\) represent the exact transfer function and the compensation transfer function of the \(i\)th imaging scene, respectively.
# Comprehensive Numerical Analysis of a Porous Piezoelectric Ceramic for Axial Load Energy Harvesting
## 3 Experimental Setup  
The schematic diagram of the experimental setup is shown in Figure 2 and the experimental setup is present in Figure 3. The electric power is supplied to the electromagnetic vibrator by using signal generator through power amplifier. The piezoelectric energy harvesting device is mounted on the electromagnetic vibrator. When an electromagnetic vibrator works, it vibrates the duralumin base plate and L-shaped steel plates. The piezoelectric bimorph (\(d_{31}\)) and cylinders (\(d_{33}\)) are mounted on the duralumin base plate and the L-shaped steel plate, respectively. Due to vibration, alternating deformations tension-compression in plates (2), and compression-tension in cylinders (1) occurred due to the reaction of the fixed supports. The displacement of the duralumin base plate is measured by the optical linear displacement transducer. The output voltage of the piezoelectric bimorphs and cylinders is collected by the electric circuit. The displacement and voltage signals are transmitted to the CPU via an external ADC/DAC E14-440D module. Power graph software is used for signal processing and measuring the output signals. The technical configurations of the measuring devices are used:  
(i) the frequency range is 1-1000 Hz for force oscillations;  
(ii) a range from 0 to 5 mm is measurable for lateral displacements of the device;  
(iii) the input electric voltage is 0.1-10 V for the electromagnetic oscillations exciter;  
(iv) the sensitivity is not less than 5 um of the optical displacement sensor.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Element Name** & **Materials Used** & **Density (kg/m\({}^{3}\))** & **Young Modulus (GPa)** \\ \hline Base Plate & duralumin & 2600 & 0.7 & 0.33 \\ Proof mass & steel & 7700 & 2.1 & 0.33 \\ L-clamping bar & steel & 7700 & 2.1 & 0.33 \\ Fixing supports & duralumin & 2600 & 0.7 & 0.33 \\ Active electric load & resistor & \(10^{6}\Omega\) & \\ Damping value & & \(\xi=0.036\) & \\ \hline \end{tabular}
\end{table}
Table 2: Mechanical properties of materials.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Porosity in (\%)** & **0** & **10** & **20** & **30** & **40** & **50** & **60** & **70** & **80** \\ \hline Density(\(\rho\)), kg/m\({}^{3}\) & 7500 & 6750 & 6000 & 5250 & 4500 & 3750 & 3000 & 2250 & 1500 \\ \(C_{11}^{E},10^{10},\mathrm{N}/\mathrm{m}^{2}\) & 13.9 & 11.  
The direct piezoelectric effect acts on the cylinders (\(d_{33}\)) as well as bimorphs (\(d_{31}\)). The combined use of these elements allows increasing the output power and conversion efficiency of the converter. When these elements are combined, the converter's output power and conversion efficiency can be increased. The output voltage of the piezoelectric bimorphs and cylinders is called the total cumulative voltage output. All the piezoelectric elements are connected in series.
## 4 Discussion
### Potential for Technology Deployment
#### 4.2.2 Hardware and Software Requirements  
The resistivity method implemented may be applied using standard VES equipment (here, an ERT unit was used but only in VES mode (as no VES unit was available) and a multi-cable system was used but only to allow VES acquisition when less than three operators are available). Using a VES unit in combination with either a standard VES cable set or a \"do it yourself\" multi-cable system (as developed herein) is a low-cost alternative to using expensive ERT equipment for performing true 2-D subsurface resistivity surveys. The Ministry in Malawi possesses VES units and cables and an ERT unit but without cables. Adoption of the resistivity method implemented would allow the Ministry to undertake true 2-D subsurface resistivity surveys without having to acquire expensive ERT cables. The multi-cable system developed could be enhanced with the addition of a switchbox (with components costing under (GBP) \(\ell 100\)) connected to the resistivity unit directly or via a VES adapter [51]. This would eliminate the need to disconnect and reconnect cables between individual resistivity measurement reducing operation time.  
For non-commercial activities (e.g., not-for-profit research), resistivity inversion may be carried out using freeware R2. Otherwise, commercial 2-D inversion software would have to be used. Cross-section display may be carried out by using freeware ParaView without restrictions on commercial use.
## 2 The FSPR System and Temperature Measuring Method
### The Freezing Scheme of FSPR  
As mentioned above, for the FSPR system, the pipe roof mainly serves for load bearing, and the frozen soil wall is mainly used for water sealing. Therefore, the freezing scheme is obviously different from the general freezing method. It is necessary to consider both the requirements of water sealing between pipes and the control of surface settlement and uplift. That is to say, the minimum thickness of the frozen soil wall must meet the water sealing requirements; the maximum thickness of the frozen soil wall should satisfy the requirement of surface deformation control due to the frost heave. [PERSON] and his group proposed the three concepts of freezing philosophy of FSPR, including rapid freezing, resistance against thermal weakening, and limitation of frost heave [21].  
A new freezing scheme including three types of freezing tubes was established based on the concepts. It is impractical to embed the freezing tubes in soil because of the curvilinear tunnel axis; thus, the tubes were installed in the steel pipes. The layout of the freezing tubes in each steel pipe is shown in Figure 2. There are three types of freezing tubes: master freezing tubes, limiting freezing tubes, and enhancing freezing tubes. In each of the odd pipes, two circular master freezing tubes with a diameter of 133 mm were installed at the middle edge position as the major cold source, while one circular limiting freezing tube with a diameter of 159 mm was arranged at the middle upper position to control the frost heave by recycling brine with relatively high temperature when necessary. Furthermore, in each of the even pipes,two fan-shaped enhancing freezing tubes were welded at the inner surface for freezing reinforcement. The odd-numbered pipes would be filled with concrete as soon as the corresponding freezing tubes are installed, while the even-numbered pipes would remain hollow until excavation. The design thickness of frozen soil wall was 2 to 2.6 m.
## 3 Results and Discussion
### Liner Materials  
Each material has its unique properties that affect the quality of the copper seed layer. Parameters including surface energy, cohesive energy, interatomic potential, and lattice spacing are considered to be related. In this study, tantalum (Ta), titanium (Ti), molybdenum (Mo), tungsten (W), and cobalt (Co) were selected as the substrate material, while the other parameters were as follows: incident energy = 5 ev, deposition height = 5000 A, incident angle = 30\({}^{\circ}\), deposition rate = 10 atoms/ps, and substrate temperature = 600 K. The copper seed layer with different substrate materials is shown in Figure 34. The cohesive energy of titanium was low compared with tantalum, molybdenum, and tungsten. Moreover, its lattice spacing was larger than cobalt. Low cohesive energy means that it was easy to break the bond of titanium, while larger lattice spacing means that the incident copper was more likely to impact deeper into the substrate, transferring more energy to the substrate atoms; these mechanisms resulted in the largest alloy percentage of titanium. The best step coverage of different liner materials belonged to titanium, as illustrated in Figure 35.  
Figure 34: Copper seed layer with different substrate materials.  
Figure 33: Alloy percentage with different crystal planes.  
The potential of pure copper is lower than the alloy potential, which means the alloy leads to an increase in diffusion barrier energy of copper atoms. Thus, the titanium alloy atoms of the copper seed layer caused the diffusivity to decrease, which decreased the diffusion of the atoms on the top sidewall to the wing. Atoms would then accumulate at the top sidewall and result in decreasing necking and uniformity.  
Tungsten had the best uniformity among the liner materials discussed in this study, as shown in Figure 36. The cohesive energy of tungsten was the largest, meaning that it was difficult to break the bonding of tungsten. This led to the lowest alloy percentage of tungsten. Without the effect of dragging diffusivity by alloy potential, the diffusivity of copper on tungsten substrates was larger than on other substrate materials, making the atoms at the top side wall easier to diffuse to the wing. This caused a decrease of the number of atoms at the top sidewall and an increase of necking as well as uniformity. Figure 37 shows the corresponding bottom height and necking of different substrate materials. The alloy percentage with different substrate materials is illustrated in Figure 38. In general, a larger cohesive energy, surface energy with lower lattice spacing, interatomic potential, and diffusion barrier energy leads to a better diffusion ability, which results in a more uniform copper seed layer.  
Figure 36: Uniformity with different substrate materials.  
Figure 35: Step coverage with different substrate materials.
# On the Secrecy Sum-Rate of Internet of Things Networks: Scheduling and Power Control +
###### Abstract
Accordingly, in this paper, we tackle a PLS problem considering wireless multiuser networks which consist of \(N\) transmitters (users or IoT devices), a single desired receiver (base station), and \(M\) eavesdroppers. To be specific, we characterizes the asymptotic behavior of secrecy sum-rate scaling in multiuser networks, applicable to future 6G applications such as massive IoT scenarios and military satellite communications. Our main contributions are summarized as follows:  
* We propose an opportunistic user scheduling scheme, which achieves optimal MUD gain, combined with a power control mechanism for reducing information leakage to eavesdroppers in wireless multiuser networks;
* We prove that the achievable secrecy sum-rate scales as \(M\log(\mathrm{SNR}\log N)\) when the number of users scales as \(\mathrm{SNR}^{\frac{M(K-1)+1}{1-\theta}}\) for a constant \(\epsilon_{0}>0\) in high signal-to-noise ratio (SNR) regime when we consider \(M\) antennas at the receiver and each eavesdropper, respectively;
* We evaluate our analytic result of the proposed scheduling scheme with a power control mechanism through simulations in two eavesdropping scenarios: internal and external eavesdropping environments;
* We further discuss the extensibility of our analysis to various applications such as massive IoT scenarios and military satellite communications in future 6G networks. The rest of this paper is organized as follows. In Section 2, the overall system model is presented. Our proposed scheduling procedure and power control mechanism are described in Section 3. Secrecy sum-rate scaling of the proposed scheduling scheme is analyzed in Section 4. The performance of the proposed scheduling scheme is verified through simulations in Section 5. Finally, conclusive remarks and future work are provided in Section 7. _Notations:_ Throughout the paper, we use the following notations. \(\triangleq\) stands for \"is defined as\". \(\left|\cdot\right|\) represents a cardinality when it applies to the set or an absolute value when it applies to the scalar value. \(\mathbf{I}_{M}\) represents an \(M\) by \(M\) identity matrix. \(\left[x\right]^{+}\) denotes \(\max(x,0)\). \(\left(\cdot\right)^{T}\) is transpose operator. Similarly, \(\left(\cdot\right)^{H}\) denotes conjugate transpose. \(\det(\cdot)\) and \(\left\|\cdot\right\|\) denote determinant of a matrix and Euclidean norm, respectively. We also consider complexity analysis notations. \(f(x)=\mathcal{O}(g(x))\) indicate that there exist constants \(C\) and \(c\) such that \(f(x)\leq Cg(x)\) for all \(x>c\). \(f(x)=\Theta(g(x))\) indicate \(f(x)=\mathcal{O}(g(x))\) and \(g(x)=\mathcal{O}(f(x))\)[31].
# Anti-Recompression Video Watermarking Algorithm Based on H.264/AVC
## 1 Introduction
used an entropy encoder to encode the original video stream into intra-frame patterns and QDCT coefficients, and then constructed a two-dimensional histogram of the QDCT coefficients to embed the watermark by using the coefficient pair mapping (CPM) method. In general, among the existing video watermarking algorithms, the embedded watermark has a great impact on the video quality, and the anti-recompression ability is insufficient. In order to solve this problem, this paper proposes a video watermarking algorithm based on H.264/AVC for anti-recompression. This algorithm embeds watermarking in the QDCT (quantification discrete cosine transform) coefficient of the video I frame chroma subblock. The modulation method combines the characteristics of video and watermark, which has little impact on the video quality. The experimental results show that the algorithm takes into account the invisibility and robustness, and significantly improves the anti-re-compression ability of the video.
## 4 Experiments  
### Statistical Significance  
We conducted a correlation analysis to verify the relationship between the variables. Firstly, we analyze the correlation matrix generated through [PERSON]'s coefficients, where the measures vary between \(1\) and \(-1\). On the one hand, a value closer to \(1\) indicates a strong correlation between two variables. On the other hand, a value close to \(-1\) indicates an inverse correlation. The values are represented by means of colors. Thus, the lighter the color, the greater the correlation between the variables.  
Figure 2 shows a sample of the correlation matrix coefficients using our CKD datasets. Figure 2a presents the correlation matrix from the dataset with the 60 real-world records and 54 manually augmented data. Samples of correlation matrix coefficients from the datasets related to the application of the hold-out method are also presented, with data further resampled with SMOTE (Figure 2b), borderline-SMOTE (Figure 2c), and borderline-SMOTE SVM (Figure 2d). Figure 2e presents the correlation matrix associated with the CV method with data further resampled with SMOTE. In general, the highest correlation coefficients relate to creatinine, urea, albuminuria, and age.  
Moreover, we used linear regression to conduct a hypothesis test to verify statistical significance. We calculated the p-value to quantify statistical significance and analyze whether our hypothesis had any correlation between the features and the target. We consider a \(p\)-value \(<\) 0.05, as a strong relationship between the feature and the target. We also calculated the F-statistic to analyze the significance of the model implemented using the datasets  
Figure 2: Sample of correlation matrix coefficients. (**a**) Dataset with the 60 real-world records and 54 manually augmented data. (**b**) Dataset with the application of the hold-out method and data further resampled with SMOTE. (**c**) Dataset with the application of the hold-out method and data further resampled with borderline-SMOTE. (**d**) Dataset with the application of the hold-out method and data further resampled with borderline-SMOTE SVM. (**e**) Dataset with CV method with data further resampled with SMOTE  
(must be greater than 1). We used the R-Squared statistic to complement the analysis of the relationship between two variables, between 0 and 1 (indicates a strong correlation).  
A sample of \(p\)-value, F-statistic, and R-Squared results is presented in Table S1 of Supplementary Materials. We identified a strong correlation between variables. For example, when using the dataset that relates to the application of the CV method, with data resampled using the manual approach and SMOTE, the null hypothesis was refuted for AH, DM, creatinine, albuminuria, and age. Besides, the F-statistic resulted in 126.90 and the R-Squared in 0.828, indicating a strong relationship between the variables and the target.
# Influence of Pre-Radiation and Photo-Bleaching on the Yb-Doped Fiber Laser Radiated with Gamma-ray
## 2 Experiments
### Radiation and Photo-Bleaching Experiment  
Both the non-pre-radiated and pre-radiated fiber lasers were radiated with the gamma-ray from a \({}^{60}\)Co source of Beijing Normal University in a normal atmosphere at room temperature. The performance of both fiber lasers was researched and recorded when their radiation dose reached 1 krad(Si), 3 krad(Si), and 10 krad(Si), respectively. In the previous two radiation experiments, the dose rate was 0.1 rad(Si)/s, while the dose rate of the last experiment was increased to 0.4 rad(Si)/s to compress the radiation duration. The properties of pre-radiated and non-pre-radiated fiber lasers were contrastively investigated, such as output power, output laser spectra, laser's central wavelength, and 3 dB bandwidth, to research the improvement of pre-radiation on the radiation resistance against gamma-ray.  
To identify the crucial doping elements in the fiber core, the radial elemental concentration was researched with an electronic probe micro-analyzer (EPMA). Wavelength of the photo-bleaching laser has a tremendous influence on the bleaching effect of radiated fiber lasers. The 532 nm laser is considered an ideal photo-bleaching laser source, with the ability to convert Yb\({}^{2+}\) ions into Yb\({}^{3+}\) ions and simultaneously eliminate hole-related defects such as AIOHC and POHC [34; 38]. In this work, 532 nm light from the photo-bleaching LD fabricated by the Institute of Semiconductors (China Academy of Science, Beijing, China) with the maximum power of 6 W was injected from a pump fiber of the counter-pump combiner into the radiated fiber laser to investigate the photo-bleaching effect. Moreover, a 532 nm laser was also injected into the radiated Yb-doped commercial fiber to investigate the variation of absorption spectra.  
Figure 1: Schematic diagram of the Yb-doped fiber laser system.