esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Numerical Examples and Results
### Coupled Fluid-Structure-Thermal Analysis  
Coupled fluid-structure-thermal analysis is conducted for the clamped HCS plates at sea level with air density \(\rho_{a}\) = 1.225 kg/m\({}^{3}\) and reference Mach number \(M_{a}\) = 3.0. Figure 9 illustrates the effects of temperature change (\(\Delta T\) = 100) and aerodynamic pressure on the first two dimensionless natural frequencies.  
Figure 8: Effects of geometric parameters of (**a**) number of unit cell; (**b**) inclined angle; (**c**) facesheet thickness; (**d**) corrugation thickness on critical temperature change and dimensionless fundamental frequency with temperature change \(\Delta T\) = 100.  
Figure 9: Effects of temperature change (\(\Delta T\) = 100) and aerodynamic pressure on the first two dimensionless frequencies of the clamped HCS plate.  
For the HCS plates only subjected to thermal loads, the natural frequencies are affected only by the temperature changes. As the temperature increases, the natural frequencies decrease due to the reduced overall stiffnesses caused by the thermal-induced initial stresses. When the sandwich plates are only subjected to aerodynamic loads, the unsteady aerodynamic pressure generates the damping and stiffness that are related to the aerodynamic pressure and with the change of the dynamic pressure, the first two natural frequencies gradually approach to each other. The dynamic pressure corresponding to the coincidence of the first two consecutively varying frequencies is the critical dynamic pressure. For the HCS plate subjected to both thermal and aerodynamic loads, on the one hand, the increasing dynamic pressure causes the first two natural frequencies to coincide with each other and on the other hand, the temperature change causes the decrease in the natural frequencies, resulting in a reduction in the critical dynamic pressure.  
For a given temperature field, the dynamic stabilities of the HCS plate under fluid-structure-thermal coupling mainly depend on the imposing aerodynamic pressure, which are measured by the critical dynamic pressure. It is seen from Figure 9 that the critical dynamic pressure reduces with the additional thermal effects.
# Computational and Communication Infrastructure Challenges for Resilient Cloud Services
## 3 Resilience Challenges
### Network Infrastructure
#### 3.1.3 Network Assessment  
The main factors impacting network performance are network latency, congestion, infrastructure parameters (QoS, filtering, routing), and network node health. Network evaluation involves reviewing and analyzing network statistics represented by these factors. This qualitative and quantitative process that measures and defines the performance level of a given network allows administrators to optimize the network service quality with subsequent decisions [38].  
Network assessment is an effective method for identifying performance gaps, enhancement opportunities, and network functionality. The information gathered during a network assessment can assist administrators in making critical IT infrastructure decisions.
## 5 Mfd Structure and Function  
Mfd is a multi-domain protein that undergoes a large conformational change regulated by ATP binding and hydrolysis during its functional cycle [24]. Composed of eight domains (D1a, D1b, D2, D3, D4, D5, D6 and D7), Mfd is organized around four distinct functional regions as follows (Figure 2D). The UvrB homology module is located at the N-terminus of Mfd and is made up of domains D1a, D1b and D2). The RNA polymerase interacting domain (RID) consists of domain D4. Domains D5 and D6 together constitute the translocae module, whereas domain D7 is responsible for auto-inhibition via interaction with domain D2. These functional regions enable Mfd to play role in the removal of stalled RNAP, as well as the recruitment of the NER apparatus.  
The N-terminal UvrB homology module (D1a, D1b and D2) exhibits structural and sequence similarity to domains 1a, 1b and 2 of UvrB [50]. Upon DNA binding, the UvrB homology module was observed to undergo a large swivel motion compared to its position in apo-Mfd; this structural change has been proposed to link the recruitment of UvrA to the dissociation of Mfd from DNA [75]. In place of the highly conserved \(\beta\)-hairpin that has been shown to be important for damage binding in UvrB, Mfd harbors a short loop. In addition, the UvrB homology module of Mfd lacks ATPase motifs [76]. As a result, the UvrB homology module of Mfd lacks ATPase activity and is incapable of DNA unwinding and binding to DNA lesions [76]. Within the UvrB homology module, domain D2 provides the binding surface for UvrA [26] and is the most highly conserved region between Mfd and UvrB.  
Domain D4, the RNAP interaction domain (RID), has structural similarity to the Tudor-like domain, a part of bacterial elongation factor that interacts with the \(\beta\)-subunit of the RNAP [50]. RID is not unique to Mfd; it is also found in a family of CarD transcription factors. In both Mfd and CarD, the RID is used to interact with subunit \(\beta\)1 of RNAP [24].  
Domains D5 and D6 of Mfd are homologous to RecG, the bacterial motor protein that couples ATP hydrolysis to double-stranded DNA translocation. However, unlike other helicases, domain D5 and D6 of Mfd cannot separate the DNA strands [77]. In RecG, the crucial structural element TRG (translocation in RecG) motif couples ATP hydrolysis with rigid-body motion of two translocae domains for translocation on the DNA strands [78; 79]. In Mfd, the TRG motif is located at the end of domain 6. Substitution of key residues in the TRG motif of Mfd impaired the ability of Mfd to displace RNAP, suggesting that the TRG motif is essential for the displacement of RNAP [80]. A structure of Mfd in complex with DNA also revealed that TRG is involved in Mfd translocation [75], supporting the above hypothesis.  
Domain D7, located at the C-terminus of Mfd, is an auto-inhibitory domain. Domain D7 interacts with domain D2 and occludes the UvrA binding interface in apo-Mfd [50; 76]. Domain D7 undergoes a large conformational change in the presence of ATP, resulting in the extended Mfd structure with exposed UvrA binding surface [26].
## 3 Atomic Norm in the Spherical Domain  
From the framework developed in [53], an atomic set where the elements are the groundwork of depiction to the signals is evaluated. For SH signals, the atomic set \(\Gamma\) is a function of the atoms in SH vectors \(\mathbf{Y}(\psi)\) and the signals is expressed as a sum of different atoms  
\[\mathbf{g}=\sum_{q=1}^{Q}u_{q}\mathbf{Y}(\psi_{q}),\qquad\mathbf{Y}(\psi_{q})\in\mathbf{ \Gamma}. \tag{13}\]  
Equation (13) is known and considered to be atomic decomposition. Evaluating the most sparse atomic decomposition of \(\mathbf{g}\) will always give the \(l_{0}\) SH atomic norm as  
\[\|\mathbf{g}\|_{\mathbf{\Gamma},\mathbf{0}}=inf\Big{\{}K\Big{|}\mathbf{g}=\sum_{q=1}^{Q}u\psi_ {q}\mathbf{Y}(\psi_{q}),\mathbf{Y}(\psi_{q})\in\mathbf{\Gamma}\Big{\}}. \tag{14}\]  
Recovering the wave within a convex optimization framework, reference [53] opined a convex heuristic of the \(l_{0}\) atomic norm, expressed as  
\[\|\mathbf{g}\|_{\mathbf{\Gamma}}=\inf\{t>0:x\in t\;conv(\Gamma)\}, \tag{15}\]where \(conv(\Gamma)\) is the convex hull of \(\Gamma\). Therefore,  
\[\|g\|_{\Gamma}=\inf\biggl{\{}\sum_{q=1}^{Q}u\psi_{q}|g=\sum_{q=1}^{Q}u\psi_{q} \boldsymbol{Y}(\psi_{q}),\boldsymbol{Y}(\psi_{q})\in\Gamma\biggr{\}}, \tag{16}\]  
which is called the SH atomic norm, and the respective dual norm \(\|\cdot\|_{\Gamma}^{*}\) becomes [54]  
\[\|g\|_{\Gamma}^{*}=\sup_{\begin{subarray}{c}R_{e}\bigr{\{}Tr\big{[}g^{H} \partial\big{]}\big{\}},\\ \|g\|_{\Gamma}\leq 1\end{subarray}}R_{e}\big{\{}Tr\big{[}g^{H}\partial \big{]}\big{\}}, \tag{17}\]  
For the covariance matrix, different atomic norms type are already proposed [55; 56; 57]. This article develops another atomic norm of the covariance matrix for DoA estimation using SAA.  
Observing the multiple measurement vector model, an ideal (no noise) covariance matrix in Equation (12), \(\boldsymbol{R}=\sum_{q=1}^{Q}u_{q}\boldsymbol{BY}^{H}\big{(}\psi_{q}\big{)} \boldsymbol{\rho}_{q}\), then the SH atomic set is defined as  
\[\Gamma:=\Big{\{}\boldsymbol{B},\boldsymbol{Y}^{H}(\psi_{q})\rho\Big{|}\psi \in,\ \|\boldsymbol{\rho}\|_{2}=1\Big{\}}. \tag{18}\]  
Furthermore, the spherical harmonic \(l_{0}\) norm of the covariance matrix \(\boldsymbol{R}\) can be described as  
\[\|\boldsymbol{R}\|_{\Gamma,0}=\inf\biggl{\{}I|\boldsymbol{R}=\sum_{q=1}^{Q}u_ {q}\boldsymbol{BY}^{H}(\psi_{q})\boldsymbol{\rho}_{q}.v_{q}\geq 0\biggr{\}}, \tag{19}\]  
the SH atomic norm of \(\boldsymbol{R}\) is expressed as  
\[\|\boldsymbol{R}\|_{\Gamma}=\inf\biggl{\{}\sum_{q=1}^{Q}u_{q}|\boldsymbol{R}= \sum_{q=1}^{Q}u_{q}\boldsymbol{BY}^{H}\big{(}\psi_{q}\big{)}\boldsymbol{\rho} _{q}.v_{q}\geq 0\biggr{\}}, \tag{20}\]  
The section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn.
## 1 Introduction  
Modern technology has allowed us to connect with other individuals in more ways than ever before. Through asynchronous and synchronous methods of interpersonal communication media, our interactions are no longer limited to face-to-face conversations [1, 2]. What's more, the interconnectivity of this digital age has brought about shifts in how we experience and encounter one another. Mobile cell phone short messaging services and computer facilitated social networking, both forms of virtual communication, have transformed personal communications and somewhat replaced conventional means of social exchanges. The United States is at the forefront of this communication revolution, with other countries such as those in Europe exponentially increasing socially interactive communications [3]. However, new issues and concerns arise with technological advancements; unintended and unanticipated consequences often emerge. For instance, while virtual communications were intended to ease the way by which we connect [1, 2], they have also been misused and known to facilitate harmful behaviors [4]. Media attention has focused on virtual peer violence in the form of cyber harassment and cyber bullying, and it has highlighted the damaging effects such victimization has had some youth [5, 6, 7]. These consequences parallel those found in real world victimization [8]. Yet little research has investigated whether such behavior exists among adults, particularly in the context of intimate relationships, and whether the virtual acts are perceived as innocuous in nature or injustices that need to be addressed. Given the transformations that have taken place in our communication, and given that intimate aggression is not an uncommon experience for young adults, it is thought that social media may present new avenues for aggression, with acts in the virtual world mimicking those in the \"real world\".
## 2 The DM Source Preparation via ZPC Operations
### The ZPC-Based DM Source Preparation
We note that we can obtain the effect of the ZPC operation on the DM source from the derived covariance matrix \(\gamma_{AB_{1}}\). The parameter \(Z_{N}^{\prime}\), which can be calculated from modulation variances of the initially prepared coherent states, demonstrates the relation of the modes \(A\) and \(B_{1}\) for source preparation. In what follows, we will show the effect of \(Z_{N}^{\prime}\) on the performance of the CVQKD system. In addition, there are the other similar operations, such as local Gaussian operation [34], photon subtraction and addition operations [35], which can be used for improving entanglement of a two-mode state. These operations, whether they are Gaussian or not, may be similarly employed for source preparation while considering performance improvement of the CVQKD system. However, due to the elegant structure of the ZPC operation that can be conventionally integrated with the practical quantum system, in this paper, we consider the ZPC-based DM source preparation for extending the maximal transmission distance of the CVQKD system.
## 3 Results and Discussion
### Humidity Control Experiments in Airtight Boxes
(**c**) Same desiccant after being enclosed in a 70 L airtight box with the ionic membrane for 5 days. Figure 6: Relative humidity and temperature in the 230 L airtight box at elevated initial humidity levels for 4 desiccant column bags, the ionic membrane alone and the combination of the ionic membrane and 4 desiccant bags. The trend of the humidity in the airtight boxes under the influence of silica desiccants or/and membrane with time resembles an exponential decay, and it can be modeled as:  
\[\rm{f=ae^{-bt}+c} \tag{3}\]  
where a is the amplitude of the exponential term, b is the decay rate and c is the value that the exponential decay will reach at infinity. The lifetime (\(\tau\)) is the inverse of the decay rates, and it represents the time required for the function to be decreased by 1/e factor. The half-life t\({}_{1/2}\) = \(\rm{\tau ln2}\) is the time required for the function to reach half its initial value. Since b, \(\tau\) and t\({}_{1/2}\) can be directly derived from each other, only one parameter needs to be mentioned. For the rest of the article, only t\({}_{1/2}\) will be mentioned, but the other two measured parameters can also be found in the tables below. The exponential decay fittings for the data from Figures 4b and 6 are given in Table 1. The R\({}^{2}\) values of the fit are close to 1, which indicates the function matches the measured data. By observing the \(\tau\) and t\({}_{1/2}\) values of the exponential term, it can be verified that the combined operation of the desicants and the membrane yielded a better performance. For the 70 L box, the t\({}_{1/2}\) value was approximately halved from 1.27 h to 0.67 h. The plateau value c for the combined configuration was also slightly decreased from 15.7% RH to 15% RH. The combined configuration also decreased the \(\tau\) and t\({}_{1/2}\) values compared to the four silica desiccant columns/bags for the 230 L box experiment, but the change was not significant. More specifically, t\({}_{1/2}\) dropped from 3.01 h to 2.97 h. The c value decreased from 26.9% RH to 22% RH. In the case of the stand-alone operation of the membrane in the 230 L box, the t\({}_{1/2}\) value was quite high, at 10.75 h, while the c value was calculated to be 26.9, the same value as in the case of the four-desiccant-bag configuration. The performance of the membrane in the 230 L box could have been affected by the remaining RTV silica sealant products, even though it was left to outgas for 2 weeks.
## 4 Discussion
This property gives rise to the function of its antibacterial activity. Several research results have shown that NK-lysins possess wide antibacterial activities against Gram-positive and Gram-negative bacteria. A report showed that porcine NK-lysin has high activity against _Escherichia coli_ and _Bacillus megaterium_ and moderate activity against _Acinetobacter calcoacticus_ and _Streptococcus pyogenes_[26]. Human granuolysin, a T cell product, exhibits antimicrobial activity towards _Escherichia coli_ and _M. tuberculosis_[2]. Bovine NK-lysins have shown extensive antibacterial activity, especially against _E. coli_ and _Staphylococcus aureus_[1; 30]. However, there are only few reports on the antibacterial activity of NK-lysins from aquatic species. Only the Japanese flounderNK-lysin proteins have been identified to have antibacterial activity against various Gram-negative bacteria [29]. In the current study, although three distinct mKLs all consisted of 76 amino acids, they showed diversity in amino acid sequences. We independently tested the antibacterial activities of the three mKLs and determined that all three mKLs have antibacterial activity against both Gram-positive bacteria _Staphylococcus aureus_ and Gram-negative bacteria _E. coli_, but it is limited against _S. aureus_. For eukaryotic proteins in prokaryotic expression systems, the formation of disulphides is one of the crucial caveats associated with the protein correctly folding which will influence production activity. So it is necessary to know whether the disulphides have been completely correctly formed or the difference between antibacterial activity against Gram-positive and Gram-negative bacteria is existed in future study.
# Optimization of Stop Plan for Skip-Stop Operation on Suburban Railway Line
## 6 Conclusions  
In this paper, a 0-1 integer programming model is built for optimizing the stop plan and departure frequency of a suburban railway under a skip-stop operation mode. The model takes the stop plan of an express train and the departure frequencies of both express and local trains as decision variables, the upper and lower limits of train departure frequency as the constraints. The optimization objectives of the model are to minimize the total passenger travel time and the total number of operating trains. Meanwhile, a solution algorithm based on a genetic algorithm is proposed to solve the model. On the basis of previous research, this paper mainly focuses on schedule adjustment, optimization of a stop plan and frequency under the overtaking condition, which can maximize the line capacity. A case of Jiangjin Line in Chongqing is used to show the reasonability and effectiveness of the proposed model and algorithm. The results show that total travel time in E/L mode with the overtaking condition is significantly reduced compared with AS mode and E/L mode without the overtaking condition. Although the number of trains in the optimal solution is more than other modes, the E/L mode with the overtaking condition is still better than other modes on the whole. Increasing the station stop time can enhance the superiority of E/L mode over AS mode.  
The research results of this paper can provide a reference for the optimization research of skip-stop operation under overtaking conditions and provide evidence for urban rail transit operators and planners. There are still some aspects that can be extended in future work. Firstly, this paper assumes that passengers take the first train to arrive at the station, whether it is the express train or local train. In reality, the passenger's choice of train is a probability problem, therefore the passenger route choice behavior  
Figure 10: Comparison of different \(t_{z}\) values.  
considering the train congestion should be considered in future studies. Moreover, genetic algorithms have the characteristics of obtaining partial optimal solutions rather than global optimal solutions. The optimization problem of the genetic algorithm for solving skip-stop operation optimization models is also an important research tendency.  
Both authors took part in the discussion of the work described in this paper. Writing--original draft preparation, J.X.; methodology, J.X.; writing--review and editing, Q.L.; data curation, X.H., L.W. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors thank [PERSON] and [PERSON], for their constructive comments and suggestions in this study.  
The authors declare no conflict of interest.
## 1 Introduction
For example, in an environmental monitoring application, a large number of sensors can be randomly deployed over a monitoring region to monitor temperature, humidity or air quality. Instead of reporting data frequently, sensors in such application only need to report their readings to the sink periodically. Hence, this scenario motivates us to use a mobile sink to collect data. The remaining part of this paper is organized as follows: Section 2 presents the network environment and problem formulations of our approach, while Section 3 presents the details of the proposed _EBDC_ mechanism. Sections 4 and 5 investigate the theoretical analysis and the performance of the _EBDC_ mechanism, respectively. Finally, the conclusions of this paper are given in Section 6.
# Secure and Lightweight Cloud-Assisted Video Reporting Protocol over 5G-Enabled Vehicular Networks
## 3 Preliminary
### Attribute-Based Encryption Scheme
#### 3.1.3 ABE.KGN  
ABE.KGN(\(ABEmk\), \(\Gamma\)) algorithm outputs the shared secret for the decryption keys under the attribute set \(\omega\), which consists of a master secret \(ABEmk\) and the access tree \(\Gamma\).  
* Based on access tree \(\Gamma\), allocate index to every node other than root.
* A polynomial \(q_{node}(x)\) over \(Z_{q}^{*}\) is set in top-down manner for each node where each polynomial is of degree \(d_{node}-1\) and \(d_{node}\) is considered as the threshold value of the node.
* Set \(q_{root}(0)=s\) for the root node.
* Set \(q_{node}(0)=q_{parent}(index(node))\) for every node with a leaf, where \(index(node)\) represents the node's index value.
* Suppose \(\Gamma\) contains \(n\) leaves, for every leaf node \(leaf_{f}\) (\(1\leq f\leq n\)), a secret share for the decryption key is generated as \(D_{leaf_{f}}=q_{leaf_{f}}(0)\cdot t_{i}^{-1}\) where \(i\) represents the attribute linked to \(leaf_{f}\) and \(l_{i}\) a random number for \(i\) taken in ABE.Setup.
* Output \(D=\{D_{leaf_{f}}\mid leaf_{f}\in\Gamma\}\).
## 3 Results and Analysis
### Correlation between Leaf Spectra and Derivative Spectra and Chlorophyll Content in Leaves  
As shown in Figure 7, the leaf reflectance spectral data, and its first derivative spectral data, were subjected to single correlation analysis with chlorophyll relative content values, respectively. The correlation coefficient between the original spectral reflectance and CCI value, the first derivative spectrum and CCI value on each spectral channel was calculated. The correlation curve between the original spectrum of _Quercus aquifoloides_ leaves and the CCI value of the relative content of chlorophyll has the best correlation between the wavelength of 509-650 nm, and this wavelength was just the strong absorption band of chlorophyll. The correlation was almost zero at 761 nm, i.e., the original spectrum hardly reflects chlorophyll content information after 761 nm. The correlation between the first derivative spectrum and CCI value was the best and most stable at 450-500 nm, and the correlation in other spectral channels fluctuates greatly.  
Correlation between Leaf Spectral Parameters and Chlorophyll Relative Values of Quercus aquifoloides at Different Altitudes  
Spectral parameters can better reflect the spectral characteristics of green vegetation, and they are sensitive to changes in chlorophyll content [43]. It is pointed out that there is an exponential function relationship between chlorophyll content and the reflectance spectral characteristic parameters such as red edge slope, blue edge slope and green peak reflectance [44; 45; 46; 47; 48]. Therefore, we used 13 typical spectral characteristic variables of plants and chlorophyll content of leaves for correlation analysis. Table 2 showed that there was a certain correlation between spectral parameters and relative chlorophyll content. Among them, the correlation between RES, BES, YES, YEP, RGP, RWSB, REA, BEA, YEA, LCI and chlorophyll relative content value has reached significant level. The correlation degree of green peak reflectance is the largest among all spectral parameters, which showed that RGP  
Figure 7: Correlation analysis and comparison of leaf spectrum, first derivative spectrum data and CCI value of relative chlorophyll content of _Quercus aquifoloides_.  
was the most sensitive to the relative chlorophyll content of _Quercus aquifolioides_. The change of this parameter can be used to characterize the change of chlorophyll content of _Quercus aquifolioides_ at different altitudes.