esa-sceva/satcom-chunk-collection huggingface dataset:
# Ensuring the Quality of the Analytical Process in a Research Laboratory
## 2 Materials and Methods
### Chalcogenide Glasses
#### 2.4.2 Determination of Density  
The density of chalcogenide glasses was determined following pycnometric and hydrostatic methods based on \"Archimedes' principle\". Both methods are widely used because they allow for the density to be measured directly without altering or damaging the sample, which preserves the integrity of sensitive or valuable substances when sample preservation is important. The procedure with a pycnometer is based on a relatively simple principle, making it accessible to a wide range of users. It can provide accurate and reliable results and also offer good repeatability and reproducibility of density measurements.  
The measurement procedure consisted of weighing the sample by Ainsworth DE-310 balance. The sample's density was calculated as follows [22]:  
\[\rho=\frac{m}{m_{0}}\times\rho_{0} \tag{3}\]where \(m\) was the mass of the solid of the determined volume; \(m_{0}\)--the mass of water having the same volume; \(\rho\) the density of the solid; \(\rho_{o}\)--the density of the water at the temperature of the experiment.  
The hydrostatic balance method or Mohr balance was used to determine the density of glass in the solid state and in the molten state at high temperature. The chalcogenide glass sample was weighed successively on hydrostatic balance Mettler Toledo ME104 (Mettler Toledo Inc, Greifensee, Switzerland) in air and liquid. Then, the density was calculated as follows [22]:  
\[\rho=\frac{m_{1}}{m_{1}-m_{2}}(\rho_{1}-\rho_{2})+\rho_{2} \tag{4}\]  
where \(m_{1}\)--the mass of the studied sample in air, g; \(m_{2}\)--the mass of the sample studied in the calibration liquid, g; \(\rho_{1}\)--the density of the liquid at the temperature of the experiment, kg/m\({}^{3}\); \(\rho_{2}\)--air density at the experiment temperature, kg/m\({}^{3}\).  
Both methods used distilled water as the immersion fluid when determining the density of samples from the Ge-Te-In system.
## 3 Results and Discussions
### The Effects of Two Uncertainties  
When uncertainties exist in both the physical property of nanofluid and the geometric parameter, the situation becomes more serious than that when a single uncertainty happens. Deviations in solid volume fraction and the depth of the grooves are selected as 10% and 20%, respectively. Comparisons between the results of IM and those of SM are summarized in Table 6, and a good agreement is shown between the bounds predicted by the two methods, which proves the accuracy of IM. There are 10,000 samples used in the prediction procedure by employing SM while only 25 samples are used by using IM, which proves the effectiveness of IM. The results of the uncertain temperature, velocity, and local Nusselt number are shown in Figures 7 and 8, and results of a deviation of 10% in the solid volume fraction are shown for comparison. Wherein, the two cases are referred to as Case 2 and Case 1, respectively. The deviation in both the solid volume fraction and the depth of the grooves slightly widen the bounds of temperature of Case 1 in Figure 7. And the difference between the bounds of temperature of Case 1 and Case 2 increase as the \(x\) coordinate increases. The two uncertainties in Case 2 lead to a wider bound of velocity than that of Case 1, only at which the groove occurs, and the bounds of velocity is hardly changed in other places. Conclusions can be drawn that the uncertain temperature and velocity is dominated by the deviation in the solid volume fraction. For the local Nusselt number in Figure 8, the two uncertainties in Case 2 remarkably influence the local Nusselt number of groove position on the upper wall. On the upper wall, the uncertain local Nusselt number at the grooves is dominated by the deviation in the depth of the grooves while the local Nusselt number in other places is dominated by the deviation in solid volume fraction. However, on the lower wall, bounds of the local Nusselt number caused by the two uncertainties are just slightly wider than that of Case 1, which means the uncertain local Nusselt number is dominated by the deviation in the solid volume fraction. This is because the grooves on the upper wall are far away from the lower wall.  
Figure 6: Bounds of the local Nusselt number along the \(x\)-axis with a 20% deviation in \(\delta\) at \(\varphi=0.05\) and \(\mathrm{Re}=25\): (**a**) The upper wall; (**b**) the lower wall.
# A Novel Piezoelectric Ceramic Actuator with Scissoring Composite Vibration for Medical Applications
## 4 Experimental Analysis and Discussion
### Results and Discussion  
Two mode shapes (Supplementary Materials), i.e., mode 1 (3558.9 Hz) and mode 2 (4507.8 Hz), around the scissoring mode have been measured and illustrated in Figure 10. Figure 10a shows that the opposite transverse deformation is concentrated on two side beams of the beam tip, whereas the other part of the beam remained at the horizontal position without significant deflection along the actuator. However, the beam part in Figure 10a has a small deflection compared with the FEM simulation results in Figure 3. That is because the boundary conditions in FEM simulation are prefect, however, the boundary conditions in the real test system is non-ideal. On the other hand, Figure 10b shows that the big deflection is generated along the whole beam. The imaging vibration mode shape demonstrates that the designed actuator exhibited superior performance in terms of scissoring mode excitation under real conditions.  
It has been observed that the measured resonant frequency of the actuator at scissoring mode was 3558.9 Hz, which is close to the simulated resonant frequency (3518.8 Hz). Hence, despite the difference in real boundary conditions due to machining errors and assembly error, the experimental results are consistent with FEM results including the mode shape and resonance frequency, indicating the structural stability of the actuator and the generation of scissoring vibrations.  
Figure 9: The experiment setup for vibration mode detection.  
Furthermore, the vibration amplitude at the front (point A) and back (point B) sides of the beam tip are recorded to further verify the generation of scissoring vibration. As shown in Figure 11, the unsmooth curves of the measured amplitude originated from the complicated and non-ideal boundary condition due to machining and assembly errors compared with the FEM simulations. The amplitude at the front tip and end tip, under mode 1 (scissoring mode), was found to be \(8.65\times 10^{-2}\) and \(3.45\times 10^{-3}\)\(\upmu\)m, respectively, whereas the corresponding amplitude values under mode 2 were \(2.79\times 10^{-2}\) and \(1.45\times 10^{-2}\)\(\upmu\)m. It can be readily observed that the actuator can generate relatively larger bending vibration at the front tip under both modes, whereas the deflection of point B under mode 1 is negligible compared with point A. These results further confirm that the longitudinal driving vibration has been effectively converted into scissoring transverse vibration at the beam tip. Therefore, both theoretical and experimental analysis verified the effectiveness of proposed scissoring actuator.  
Figure 10: Scanning mode shapes around the resonant frequency: (**a**) scissoring mode and (**b**) normal bending mode.
# Multi-Constraint and Multi-Policy Path Hopping Active Defense Method Based on SDN
## 4 Design of Multi-Constraint Multi-Strategy Hopping Algorithm
### Related Constraints and Weight Calculation  
This paper aims to expand the space of path jumps and enhance the diversity of path jumps by using DFS to compute all communication paths between two points without constraining the similarity of paths or key nodes. Consequently, in the space of jumps, it is inevitable that multiple similar paths or paths containing the same nodes will be repeated across multiple jump cycles. These nodes often relay a large amount of data, and when attackers monitor these nodes for extended periods, despite path jumping during the process, there remains a risk of significant data theft, reducing the unpredictability and defensive efficacy of path jumping. Furthermore, in the process of path jumping, the availability of paths should also be considered. While the previous sections focused on path generation, during jumping, it is essential to ensure that the remaining bandwidth of the path meets the data transmission requirements to avoid issues like link congestion and packet loss. To further enhance the diversity, unpredictability, and availability of path jumping, this study imposes constraints on the selected jumping paths in terms of similarity, selection cycles, remaining path bandwidth, and key nodes. This allows the network to adaptively select jumping strategies and paths based on the current network state. Most existing research on path jumping is based on fixed jump cycles, which reduces the diversity and unpredictability of jumps. This study achieves adaptive path jumping strategies while dynamically varying the jump cycles to enhance the diversity and unpredictability of path jumps. The related constraints and weight calculation equations are as follows.  
Remaining Path Bandwidth Constraint  
When path hopping is performed, in order to ensure the availability of the path and avoid congestion and packet loss, it is necessary to constrain the remaining bandwidth of the path. The equation is as follows:  
\[B_{ik}\geq B \tag{3}\]  
\[B_{ik}=MIN(b_{k}(set(link_{i}^{S\to D}))) \tag{4}\]  
The \(B_{ik}\) in Equation (3) represents the remaining bandwidth of path \(i\) at the \(k\)-th hopping cycle, and \(B\) represents the bandwidth required for data forwarding. Equation (4) is the calculation method of \(B_{ik}\), where \(set(link_{i}^{S\to D})\) represents all link sets in path \(i\) except those directly connected to the source and destination nodes, and \(b_{k}\) represents the remaining bandwidth of each link at the \(k\)-th hopping cycle. It can be seen from the equation that the constraint rule of the remaining path bandwidth is to select the minimum value of all link bandwidths on the path at the \(k\)-th hopping cycle.
# AV-Teller: Browser Fingerprinting for Client-Side Security Software Identification
## 7 Discussion
### Portability, Threat Model, and Disclosure  
This study specifically examines Windows-based environments due to their ubiquity and the robust testing interfaces provided by leading antivirus solutions. However, antivirus behavior exhibits considerable variability across other platforms, including macOS, Linux, and mobile operating systems. Extending the capabilities of AV-Teller to these platforms represent a significant avenue for future research. Each platform introduces distinct technical challenges, including variations in browser architecture, JavaScript API compatibility, and antivirus integration mechanisms.  
For instance, in Android environments, integration with WebView could enable the monitoring of DOM-level changes analogous to traditional browsers, contingent on the support of WebView for JavaScript-based instrumentation. On cloud-based platforms such as AWS WorkSpaces or Azure Virtual Desktop, AV-Teller could function similarly to conventional desktop browser, provided that browser access and network stack behavior remain consistent. However, cloud-specific constraints, including shared kernel execution, session isolation, and endpoint security policies, may impact observability and detection mechanisms.  
Responsible disclosure remains a critical consideration when publishing research that could reveal unintended behaviors in security products. Although no direct disclosure to antivirus vendors occurred during the preparation of this manuscript, we aim to disseminate our findings in follow-up work to foster transparency and improve browser-antivirus interactions.
## 3 Results and Discussion
### Chemical Characterization of XBM and XBM-Ca by ATR-FTIR  
To better understand the chemical interactions between the polymeric matrix and the 5-ASA, the ATR-IR was performed. Figure 6A shows the ATR-IR spectra of xylan (I), XBM (II), and PEG (III), while Figure 6B depicted the ATR-IR spectra of XBM-Ca-F9 without 5-ASA (I), XBM-Ca-F9-loaded with 5-ASA (II), and pure 5-ASA (III).  
The xylan infrared spectrum was like other spectra observed elsewhere (Figure 6A (I)) [26; 27]. Furthermore, it was observed that the spectrum of XBM and PEG (Figure 6A (II and III, respectively)) had similar peaks, likely due to the shielding effect presented by the PEG in the formulation. In fact, after the drying process, it could be possible that the PEG shielding effect form a film and prevent ATR-IR from analyzing XBM. On the other hand, in formulations containing CaCl\({}_{2}\) (Figure 6B (I and II)), this phenomenon was not observed. It could be speculated that, likely, the CaCl\({}_{2}\) play an important role at the interface of the microparticles, which hinders the shielding effect of PEG.  
The ATR-IR results also revealed that the bond P=O formed during the crosslinking process between the STMP and the polysaccharides was not observed. This phenomenon was equally observed for the empty and loaded XBM-Ca-F9 and might reveal a low degree of crosslinking, which was suggested by [PERSON] and co-workers (2012) [15]. The presence of a sharp peak at the 848 cm\({}^{-1}\) region was observed for the XBM-Ca-F9 loaded with 5-ASA (Figure 6B (II)), while it was not seen on the empty XBM-Ca-F9 (Figure 6B (I)). This peak is commonly attributed to the C-H bonds of aromatic groups, such as the aromatic ring presented at the 5-ASA structure and was also observed on its spectrum  
Figure 6: ATR-IR spectra (**A**) of xylan (I), XBM (II), and PEG (III) and (**B**) formulation XBM-Ca-F9 without drug (I), XBM-Ca-F9 loaded with 5-ASA (II), and 5-ASA alone (III).  
in Figure 6B (III) [22]. In addition, the increase on the intensity of the peak near 1500 cm\({}^{-1}\) may be associated with the enhancement of drug 5-ASA loading, once these peaks are associated to the C-C and C=C stretching mode, and also to the N-H bond [22].
## 3 Ultrasonic Measurement of Air Void Distribution in Early-Age Concrete
### The Correlation between Compressive Strength and Ultrasonic Parameter  
Besides the analysis of air void volume shrinkage, the compressive strength gain during early age can also be possibly investigated with ultrasonic parameters. The cement hydration process can lead to the increase in concrete stiffness and the decline of viscosity [39]. The rising concrete stiffness means higher transmission speed. The decreasing viscosity can also generate a drop in cement attenuation, as demonstrated in Figure 3. In addition, the shrinkage of the air void volume fraction, as depicted in Figures 6-8, can also lead to higher transmission speed and lower attenuation. Hence, the ultrasonic transmission speed and attenuation are in positive and negative correlations with the compressive strength during the concrete early-age. The ultrasonic transmission speed is determined with the arrival time of Signal \(S_{1}(t)\) and the sample thickness. The calculated ultrasonic transmission speeds are shown in Table 2. Similar to the study [21], this study also applied the peak value ratios for the strength gain prediction. As shown in Figure 2, the peak value of both the first and second transmission  
Figure 8: Air voids evolution for Sample Type 3. (**a**) Comparison of the air void content measurement with ultrasonic scattering (at early stages Day 1–28) and the ASTM C138 (Day 0); (**b**) Air void size distribution evolution with curing time.  
Figure 7: Air voids evolution for Sample Type 2. (**a**) The change of air void content with curing age measured with ultrasonic scattering (at early stages Day 1–28) and the ASTM C138 (Day 0); (**b**) Air void size distribution evolution with curing time.  
waves are located around 500 kHz. Hence, the ultrasonic attenuation value at 500 kHz was chosen to represent the change of attenuation with time, as depicted in Table 2.  
The compressive strength analysis, applied to the measured results of all three sample types, was applied for the correlation analysis to better demonstrate the relationship between ultrasonic parameters and the strength gain during early stages. The relationship between compressive strength with ultrasonic speed and attenuation is demonstrated in Figure 9a,b respectively. Both of these correlations were evaluated with the linear fitting, and the fitted results are demonstrated as Equations (15) and (16), respectively. The corresponding correlation coefficient between the fitted and measured results are 93.23% and 98.20%, respectively, which demonstrate that the change of ultrasonic attenuation is in stronger linear correlation with the strength gain during early stages.  
\[f_{c}=0.0291\times v_{p}-88.96 \tag{15}\]  
where \(f_{c}\) is the compressive strength (MPa) and \(v_{p}\) is the ultrasonic transmission speed (m/s).  
\[f_{c}=-0.61\times\alpha_{u,f}+112.59 \tag{16}\]  
where \(\alpha_{u,f}\) is the ultrasonic attenuation (Np/m).
# Vulnerability Analysis of LTE-R Train-to-Ground Communication Time Synchronization
## 7 Conclusions  
LTE-R is the next generation of high-speed railway wireless communication systems. However, due to the all-IP architecture of LTE-R and the use of a multicast address in the PTP, the time synchronization process of LTE-R communication is very vulnerable to attack. In this paper, an LTE-R train-to-ground communication vulnerability analysis method based on the combination of stochastic Petri nets and a continuous-time Markov chain is proposed, an analysis model of LTE-R time synchronization vulnerability based on stochastic Petri nets is established, and the Markov chain is obtained using the method of model isomorphism. The relationship between the average firing rate in the attack state and the steady-state probability of the end state of the clock node is quantitatively obtained, and the following conclusions are drawn:  
1. The master-slave clock is a vulnerable node in the whole process when it is waiting to receive the key PTP message. If it is attacked to varying degrees at this critical time, the whole synchronization process will be greatly impacted.
2. Whenthe master clock of the synchronization process, eNodeB, is attacked to varying degrees, the end states of the whole synchronization process are affected. However, when the slave clock, the OBC, whose timing structure is lower than that of eNodeB, is attacked to varying degrees, only the OBC is affected. This conclusion is consistent with the conclusion drawn in a previous study that conducted a physical experiment, further verifying the effectiveness of the SPN analysis model in this paper.  
Conceptualization, Y.C. and Z.Z.; methodology, Y.C. and Z.Z.; writing--review and editing, Z.Z. and K.N.; visualization, Z.Z. and K.N.; supervision, Y.C.; project administration, Z.Z.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Natural Science Foundation of China (Grant No. 61963023 and No. 61841303) and the Tianyou innovation team of Lanzhou Jiaotong University (Grant No. TY202003).  
Not applicable.  
Informed Consent Statement:Informed consent was obtained from all subjects involved in the study.  
The study did not report any data.  
The authors declare no conflict of interest.
# Photoluminescence of _Cis_-Polyacetylene Semiconductor Material
###### Abstract  
Photoluminescence (PL) is one of the key experimental characterizations of optoelectronic materials, including conjugated polymers (CPs). In this study, a simplified model of an undoped _cis_-polyacetylene (_cis_-PA) oligomer was selected and used to explain the mechanism of photoluminescence (PL) of the CPs. Using a combination of the ab initio electronic structure and a time-dependent density matrix methodology, the photo-induced time-dependent excited state dynamics were computed. We explored the phonon-induced relaxation of the photoexcited state for a single oligomer of _cis_-PA. Here, the dissipative Redfield equation of the motion was used to compute the dissipative excited state dynamics of electronic degrees of freedom. This equation used the nonadiabatic couplings as parameters. The computed excited state dynamics showed that the relaxation rate of the electron is faster than the relaxation rate of the hole. The dissipative excited-state dynamics were combined with radiative recombination channels to predict the PL spectrum. The simulated results showed that the absorption and emission spectra both have a similar transition. The main result is that the computed PL spectrum demonstrates two mechanisms of light emission originating from (i) the inter-band transitions, corresponding to the same range of transition energies as the absorption spectrum and (ii) intra-band transitions not available in the absorption spectra. However, the dissipative Redfield equation of the motion was used to compute the electronic degrees of freedom of the nonadiabatic couplings, which helped to process the time propagation of the excited dynamic state. This excited dynamic state shows that the relaxation rate of the electron is faster than the relaxation rate of the hole, which can be used for improving organic semiconductor materials for photovoltaic and LED applications.  
Keywords:undoped _cis_-polyacetylene (_cis_-PA); photoluminescence (PL); nonadiabatic coupling; electron; hole; relaxation +
Footnote †: journal: Applied Sciences
## 6 3D Integration and Assembly
### Matrix Vertical Fiber Coupling  
Fiber coupling is one of the major problems associated with a co-package system [49; 50]. The challenge is to develop a fiber connector that will enable coupling to 16 single-mode fibers simultaneously and that can be assembled on a high-volume scale. The design used is a vertical coupling as dictated by the assembly and integration scheme of the L3 MATRIX device. A two-lens relay approach is used with one lens on the back surface of the SiP and the second lens on the fiber array. Light is reflected by the grating coupler (Figure 11) through the BOX and the silicon substrate. The emerging beam is tilted at 10\({}^{\circ}\), and the lens  
Figure 19: Chiplet mimic interposer (**A**) showing the SiP assembly area in purple and the package assembly area in green. A single interposer cell is shown in (**B**) with the bumps over the SiP transmit cell. The 100-ohm termination design for the modulator is shown in (**C**); the resulting silicon is in (**D**).  
Figure 20: The package design showing the RF routing (**left**) and the actual substrate front and back sides (**right**) showing the bump area and the BGA matrix as well as the cutout hole.  
design was carried out such that the light path is rotated back to the normal axis, Figure 21. The lenses are in a 2 \(\times\) 8 layout as dictated by the SiP layout. The first lens array is a flip-chip assembled on the back surface of the SiP die using alignment marks. The second lens array is aligned with a fiber array and aligned to the lower array actively. A fully passive alignment of 16 single-mode fibers remains still a significant challenge.
## 2 Characterization and Modeling of the Fault Ride-Through Process in Doubly Fed Wind Turbines
### Structured Model of Electromechanical Transient of Doubly Fed Wind Turbine
#### 2.2.2 Normal Operation Active and Reactive Power Control Module
In Figure 7, Ut is the real-time voltage at the parallel network point; \(I_{\text{dmax}}\) and \(I_{\text{dmin}}\) are the maximum and minimum values of active current; \(I_{\text{dmax}}\) and \(I_{\text{qmin}}\) are the maximum and minimum values of reactive current; \(U_{\text{max}}\) and \(U_{\text{min}}\) are the maximum and minimum values of output voltage; \(K_{\text{{\it{sp}}}}\) and \(K_{\text{{\it{pi}}}}\) are the integral coefficients of the active control ratio; \(K_{\text{{\it{up}}}}\) and \(K_{\text{{\it{ui}}}}\) are the integral coefficients of the reactive control ratio; and \(K_{\text{{\it{up}}}}\) and \(K_{\text{{\it{ui}}}}\) are the integral coefficients of the voltage control ratio.