esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Analysis of Results
### Comparative Analysis of Numerical Simulation Data  
Based on the numerical simulation results, the following main conclusions can be drawn:  
1. As the burial depth of the shield tunnel changes, the surface settlement also varies. Specifically, as the burial depth increases, the soil arch effect at the surface gradually diminishes. Within the burial depth range of 29 m to 37 m, surface settlement is controlled between \(-1.0\) mm and 2.5 mm, indicating a relatively minor change. Moreover, beyond three times the tunnel diameter, surface settlement decays to the stability threshold of \(\pm 0.2\) mm, with changes in surface settlement gradually stabilizing.
2. By comparing the effects of silo pressure on surface settlement, it is observed that when silo pressure ranges from 120 kPa to 180 kPa, surface settlement remains between \(-1.0\) mm and 1.5 mm. The variation in surface settlement due to changes in silo pressure is within \(\pm 0.2\) mm, suggesting that after grouting and strengthening of the surface soil, the impact of silo pressure on surface settlement becomes almost negligible.
3. When grouting pressure is between 350 kPa and 450 kPa, surface settlement is maintained between \(-1.0\) mm and 1.5 mm. Changes in grouting pressure result in surface settlement variations within \(\pm 0.2\) mm, indicating that after grouting and reinforcing the surface soil, the influence of grouting pressure on surface settlement is nearly negligible.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Programmes** & \
\begin{tabular}{c} **Depth of burial of** \\ **Tunnels (m)** \\ \end{tabular} & **Radius of the Tunnel (m)** & **Grouting Pressure (kPa)** &
\begin{tabular}{c} **Pressure on Soil** \\ **Chamber (kPa)** \\ \end{tabular} \\ \hline Scenario 1 & 35 & 3.1 & 350 & 166 \\ Scenario 2 & 35 & 3.1 & 380 & 166 \\ Scenario 3 & 35 & 3.1 & 400 & 166 \\ Scenario 4 & 35 & 3.1 & 430 & 166 \\ Scenario 5 & 35 & 3.1 & 450 & 166 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Shield parameters at different grouting pressures in Reinforced Soils.  
After the soil above the shield tunnel is grouted and reinforced, the factors of tunnel depth, grouting pressure, and soil chamber pressure have less influence on the change in surface settlement during shield tunnel excavation, and the effect of early grouting and reinforcement of the soil on the reduction in surface settlement is significant.
# A Novel Channel Calibration Method for Bistatic ISAR Imaging System
## 4 Experimental Results and Analysis
### Estimation of Channel Characteristics  
#### 4.1.1 Parameters Specification  
The system parameters of the bistatic ISAR imaging system are shown in Table 1.  
The RIGIDSPHERE 2 (LCS4) was selected as the calibration satellite, as it is a standard spherical satellite. Its two line elements (TLE) are provided by the Space Surveillance Network (SSN) of America, which are listed in in Table 2.  
The epoch time of initial orbital elements is on 10 August 2018 at 20:24:39.85. Setting transmitting station at the city Beijing and the receiving station at the city Nanjing. The visible time slots for the bistatic radar is from 22:08:46 to 22:21:19. The calibration satellite echoes are collected during the visible segment.
# Public-Key Cryptography Based on Tropical Circular Matrices
## 4 Security and Parameter Selection
### RM Attacks  
[PERSON] and [PERSON] [26] improved the original scheme and proposed a public-key cryptosystem based on the semidirect product of the tropical matrix semiring. Let \(S=(M_{k}(\mathcal{Z}),\oplus,\otimes)\) be the tropical semiring of \(k\times k\) tropical matrices over \(\mathcal{Z}\). It can be seen that \(S\times S\) is a semigroup under the operation \(\circ\) given as  
\[\begin{array}{c}(\forall(M_{1},H_{1}),(M_{2},H_{2})\in S\times S)\\ (M_{1},H_{1})\circ(M_{2},H_{2})=((M_{1}\oplus H_{2}\oplus M_{1}\otimes H_{2}) \oplus M_{2},H_{1}\oplus H_{2}\oplus H_{1}\otimes H_{2}).\end{array}\]  
Using the semigroup \((S\times S,\circ)\), [PERSON] and [PERSON] proposed an improved tropical public-key cryptosystem. However, cryptanalysis of the improved tropical public-key cryptosystem was successfully implemented using a simple binary search by [PERSON] and [PERSON] [27]. A partial order on \(S\) is defined as  
\[(\forall X,Y\in S)X\leq Y\text{ if }x_{ij}\leq y_{ij}\;\forall i,j\in\{1, \cdots,k\}.\]  
It can be easily observed that for the operations \(\circ\), if \((M,H)^{p}\) is denoted by \(\left(M_{p},H_{p}\right)\), then the sequence \(\left\{M_{p}\right\}\) is monotonically decreasing, i.e., \(M_{1}\geq M_{2}\geq M_{3}\geq\cdots\) and so on. Algorithm 2 gives the pseudocode description of RM attack.  
```
Input: \(M,H,A\in S\), where \((M,H)^{m}=(A,H^{m})\), for some positive integer \(m\) (\(1\leq m\leq r\)). Output: \(m\). (1) Let \(left=1\) and \(right=r\); (2) Execute the following loop when \(left\leq right\). (i) \(mid=left+(right-left)/2\) (ii) Compute \((M,H)^{mid}=(P,Q)\). If \(P<A\), \(right=mid-1\); If \(P>A\), \(left=mid+1\); If \(P=A\), output \(m=mid\).
```  
**Algorithm 2**RM Attack algorithm  
In our cryptosystems, there is no tropical matrix addition operation \(\oplus\) and the partial order cannot be used. Thus, our cryptosystems can resist RM attacks. We compare the security among relevant cryptosystems in [24; 26] and our proposed cryptosystem. The comparison results are depicted in Table 1.
## 2 Materials and Methods  
### Plant Materials  
A total of seven populations developed from crossing of _indica_ rice were used. For primary mapping, the previously developed three RIL populations were already used to analyze grain quality and yield-related traits, including Teqing/IRBB lines (TI), Zhenshan 97/Milyang 46 (ZM) and Xieqingzao/Milyang 46 (XM), respectively [37; 38; 39; 40; 41]. Teqing, Zhenshan 97 and Xieqingzao are female parents, while IRBB lines and Milyang 46 are male parents. All of the parental lines have been widely used in commercial breeding and production of three-line hybrid rice in China, among which Zhenshan 97 and Xieqingzao are maintainer lines and used as early-season varieties, others are restoreer lines and used as middle-season rice varieties in the middle-lower reaches of Yangtze River basin. For TL phenotypic data of 203 lines in 2009 and 2010 and genetic maps with 127 markers, spanning 1198 cM were used to identify QTLs for yield heterosis [38]. In this study, extra two years' phenotypic data were added, and genetic linkage map had been updated to comprise 135 markers spanning 1345 cM [42]. For ZM, phenotypic data of 243 lines in 1999 and 2000 and genetic map with 158 makers, spanning 1288 cM were used to detect QTLs for yield traits [10]. In this work, phenotypic data for two more years were added. Genetic linkage map had been updated to consist of 256 markers and span 1815 cM [39]. For XM, phenotypic data of 209 lines was not used in any QTL mapping for NGP, NSP, and SF. A genetic map consisting of 240 markers and spanning 2080 cM [39], and phenotypic data of three years were used in this study.  
For further mapping and validation, four RH-derived populations were used, and they were derived from one RH of the cross TQ/IRBB52 as described below and illustrated in Figure 1. One F\({}_{7}\) plant carrying 13 heterozygous segments distributed on 10 chromosomes was selected and selfed to produce S\({}_{1}\) population consisting of 251 individuals, which was named Ti52-2. QTLs were determined from data generated from the S\({}_{1:2}\) and S\({}_{1:4}\) families of Ti52-2. QTLs for heading date had been detected using Ti52-2 in previous study [42].  
Three RHs were selected from Ti52-2 covering _qNGPS5.5_, _qNGP9.1_ and _qNGP12.1_, respectively. The first one carried three heterozygous segments, which were RM18927\(-\)RM274 on chromosome 5, RM20731 on chromosome 6 and pTA248\(-\)RM5926 on chromosome 11. The second one included four heterozygous segments, which were RM12210 on chromosome 1, RM23662\(-\)RM1896 on chromosome 9, RM6704\(-\)RM7300 on chromosome 10 and RM1233\(-\)RM5926 on chromosome 11. The last one consistedof two heterozygous segments, which were RM16252\(-\)RM335 on chromosome 4 and RM3246\(-\)RM511 on chromosome 12. They were selfed to produce three S\({}_{1}\) populations designated ZC5, ZC9 and ZC12 consisting of 216, 203 and 241 plants, respectively.
# Recent Advances in the Heterologous Biosynthesis of Natural Products from _Streptomyces_
## 5 Strategies for the Construction of a Biosynthetic Gene Cluster
### Promoter Engineering  
The promoter is one of the most important factors for the heterologous expression of BGCs at the transcription level. Each host has different promoter systems. Therefore, after the engineering host, powerful and suitable promoters should be selected for developing heterologous expression systems. When the BGCs are cloned to vectors, the powerful and suitable promoter can replace the native promoter. This helps to enhance or activate the heterologous expression of BGCs.  
The most suitable part of the promoter activity relies on the \(-10\) and \(-35\) regions. These regions determine the strength of the RNA polymerase binding. There are three types of promoters in _Streptomyces_. A type I promoter includes the \(-10\) element (5'-TANNNT-3') and \(-35\) element (5'-TTGNC-3') with an 18-19 nucleotide spacer length [157,158], such as the _lrdB_ promoter from _S. coelicolor_[159]. In contrast, a type II promoter contains the \(-10\) element, similar to type I, and other elements (5'-TGTC-3') with a different spacer length [160], and a type III does not display the typical \(-10\) and \(-35\) sequences that are present in different types [157,161].  
Native promoters were used in studies for a long time, but they do not work at a wide range of transcription levels. Based on the properties of native promoters, powerful synthetic promoters were developed and selected for the expression of the target gene at a high level. Promoter engineering is performed by changing the sequence between the \(-10\) and  
Figure 3: Schematic diagram of the BGC cloning methods. The in vivo cloning methods include TAR, PIRS, LLHR, and ExoCET systems, while the in vitro cloning methods include CATCH, SIRA, and SSRTA assembly. RE, restriction enzymes; _kanR_, kanamycin restriction gene gene; _ampR_, ampicillin restriction gene; _tetR_, tetracycline restriction enzyme; gRNA/Cas9, guide RNA/Cas9; T4 polmerase.  
\(-35\) regions of a native promoter. Several native promoters have been studied and used to drive the expression of genes in _Streptomyces_, such as inducible promoters _tipAp_ from _S. lipidans_ 66 [162] and _nitAp_ from _Rhodococcus rhodochrous_ J1 [163], and the constitutive promoters _ermEp_ from _Streptomyces erythraeus_[164], _SF14p_ from _Streptomyces ghanaensis_ phage I19 [165], and _kasOp_ from _S. coelicolor_[166]. The activity of promoter _thlM4p_ from _Streptomyces chattanoogensis_ L10, which was selected via a transcriptome-based screening method, was seven times stronger than the promoter _ermE*p_[167]. Many synthetic promoters were developed; among them, _ermE*p_ and _kasO*p_ were widely used in the gene expression in _Streptomyces_. [PERSON] et al. demonstrated that the _kasO*p_ promoter is stronger than the _SF14p_ promoter, which is stronger than the _erm*p_ promoter, as seen from the production level of actinorhodin when used in _S. coelicolor_[166].
## 3 Strain Gauges and Distributed Optic Fiber Strain Measurements
### Distributed Fibre Optic Sensor vs. Strain Gauge  
Conversion from Rayleigh and Brillouin frequency shift measurements to strain along the optic fiber have been studied [15; 16]. The conversion coefficient has been found to be \(-6.452~{}\mu\epsilon/\mathrm{GHz}\) (\(-0.155~{}\mathrm{GHz}/\mu\epsilon\)) and \(19.72~{}\mu\epsilon/\mathrm{MHz}\) (\(0.0507~{}\mu\epsilon/\mathrm{MHz}\)) for Rayleigh and Brillouin frequency respectively. [PERSON] et al. [14] argued that the induced radial strain needs also be considered in the conversion when hydrostatic pressure is applied during the measurement. Based upon the strain measurements carried out on several metals (with higher stiffness than the optic fiber, which is mainly Quartz), they proposed a formula which contains both the radial and longitude strains. In this study, it is noted that the baseline frequency shift values (sensor B) are much smaller than the corresponding rock-based measurements, especially for Rayleigh frequency shift, reflecting that the Berea/Tako sandstone is significantly less stiff than Quartz. It is, therefore, decided to use the simple coefficients for conversion calculation.
###### Abstract  
Opportunistic mobile social networks (OMSNs) have become increasingly popular in recent years due to the rise of social media and smartphones. However, message forwarding and sharing social information through intermediary nodes on OMSNs raises privacy concerns as personal data and activities become more exposed. Therefore, maintaining privacy without limiting efficient social interaction is a challenging task. This paper addresses this specific problem of safeguarding user privacy during message forwarding by integrating a privacy layer on the state-of-the-art OMSN routing decision models that empowers users to control their message dissemination. Mainly, we present three user-centric privacy-aware forwarding modes guiding the selection of the next hop in the forwarding path based on social metrics such as common friends and exchanged messages between OMSN nodes. More specifically, we define different social relationship strengths approximating real-world scenarios (familiar, weak tie, stranger) and trust thresholds to give users choices on trust levels for different social contexts and guide the routing decisions. We evaluate the privacy enhancement and network performance through extensive simulations using ONE simulator for several routing schemes (Epidemic, Prophet, and Spray and Wait) and different movement models (random way, bus, and working day). We demonstrate that our modes can enhance privacy by up to 45% in various network scenarios, as measured by the reduction in the likelihood of unintended message propagation, while keeping the message-delivery process effective and efficient.  
privacy; OMSN; trust; routing; selection mode; one simulator; efficiency
## 4 Routing Strategies  
In the following discussion let \(\mathcal{G}(\mathcal{N},\mathcal{L})\) be the graph representing an OBS network, where \(\mathcal{N}\) is the set of nodes, and \(\mathcal{L}\) the set of unidirectional fiber links. We define a path over which a burst must travel, \(v\), as a connected series of directed links, written as \(v:s(v)\to d(v)\), from source node \(s(v)\) to destination node \(d(v)\). The set of paths that can be used by a burst from \(s\) to \(d\) is defined as \(\mathcal{V}_{s,d}=\{v:s(v)\to d(v)\mid s=s(v),d=d(v)\}\) and the set including all \(\mathcal{V}_{s,d}\) is defined as \(\mathcal{V}\). We also define \(p_{l}^{v}=1\) if link \(l\in\mathcal{L}\) is included in \(v\), \(p_{l}^{v}=0\) otherwise, and \(q^{v,v^{\prime}}=1\) if the two paths \(v\) and \(v^{\prime}\) share at least one link. When taking a specific node as a reference point, a link coming out of that node can be denoted as \(l_{out}\) and a link coming into that node can be denoted as \(l_{in}\). The total number of elements in \(\mathcal{N}\), \(\mathcal{L}\) and \(\mathcal{V}\) is denoted by \(N\), \(L\) and \(V\). A demand matrix \(\mathbf{T}\) can be considered, where \(t_{s,d}\) represents a relative load from source node \(s\) to destination node \(d\). Although the traffic demands are included in the formulations for a demonstrative purpose, still they are skipped in the performed simulations.  
We consider three path selection strategies: MCL, MEC and SBPR. These strategies are formulated in three ILP problems for which a single path for each pair of nodes must be selected. That is, for the overall network and for each strategy, \(N(N-1)\) paths must be chosen and resources allocated for burst delivery. For each strategy, input information includes a set of \(K\) eligible paths which are computed in advance. The optimization problems are solved in our simulation model by CPLEX optimizers, and the results obtained are used to populate the routing tables in order to achieve a global contention reduction.
# Experimental Evaluation of Rigidity Center
## 2 Materials and Methods
### Rigidity Center Calculation  
As previously mentioned, in-plane slab displacements (two displacement values at each floor level) were recorded during the tests. If both displacements of a slab were the same, then rigidity center was at the centroid. Otherwise, rigidity center should be calculated considering the unequal displacements.  
The displacements of the columns and shear walls were calculated using the two displacement values obtained at the points close to the corners of each slab (Equation (1)) (Figure 11). As slabs were stiff and assumed to have a rigid diaphragm, linear equation was used. From the displacements obtained, the stiffnesses of the columns and shear walls (Equation (2)) were transformed into shear forces at the centers of the elements (Equation (3)). By taking the centroid of the shear forces, location of the rigidity center was calculated (Equation (4)). In these equations, \(d_{zi}\) is the displacement magnitude at the relevant point of the relevant slab, \(x_{i}\) is the distance of the relevant point from the reference axis, a and b are the constants, \(F_{\mathrm{i}}\) is the shear force, \(k_{\mathrm{i}}\) is the bending stiffness of the relevant element, \(E_{\mathrm{i}}\) is the _modulus of elasticity_ of the relevant element, \(I_{\mathrm{i}}\) is the moment of inertia of the relevant element, and \(L_{\mathrm{I}}\) represents the net height of the relevant element [40].  
\[d_{zi}=ax_{i}+b \tag{1}\]  
Figure 10: The building after the test.  
Figure 9: Special trigger device.
# LogEDL: Log Anomaly Detection via Evidential Deep Learning
## 4 Methodology
### LogEDL
#### 4.5.2 ENN Head  
After the Transformer Encoder, each log key is represented as a semantic vector. To detect anomalous sequences, we propose an evidential neural network head (ENN head) based on an uncertainty mechanism, as shown in Figure 4. This module includes two fully connected (FC) layers, which are used to learn the evidence of contextual patterns across the entire sequence. Given a sequence of semantic vectors, \(H=\{h_{1},\cdots,h_{t},\cdots,h_{T}\}\), the evidence \(E=\{e_{1},\cdots,e_{t},\cdots,e_{T}\}\) for this sequence is learned in two layers of FC after the ENN head. Note that we have the last layer of hidden states as output, denoted as  
\[e_{t}=\sigma(w_{2}\sigma(w_{1}h_{t}+b_{1})+b_{2}) \tag{1}\]  
where \(w_{1},w_{2},b_{1}\), and \(b_{2}\) are the trainable parameters of the input \(h_{t}\), and \(\sigma\)\((\cdot)\) is the ReLU function.  
When we obtain the evidence \(e_{t}\), it can efficiently learn the information about the mask position of the input log sequence about the context and use the last step of the hidden state of the output as a representation of the context pattern of this log key position. To achieve this goal, we propose MMSM to model normal sequences, followed by log sequence-wise contrastive learning for representation learning, and further, utilize an evidential neural network module to derive an anomaly detection criterion for identifying anomalous sequences.
## 2 Methodology
### Selection and Validation of the Calculation Engine  
This study has been conducted using ClimateStudio 1.8, a graphic interface which uses the Radiance Render calculation engine [66]. This engine incorporates dynamic metrics for the current sky concept [67] and is widely adopted by the scientific community and designers [41; 56]. Its validation was carried out in previous studies through adherence to the CIE (International Commission on Illumination) Test Cases [46; 68; 69; 70; 71], along with the inclusion of comparisons with annual lighting values derived from real sky conditions [72]. One of these comparisons involves the monitoring of an existing test cell situated in Seville, one of the study locations. This test cell was specifically designed to mimic a household room with similar characteristics [41; 42; 56; 73].  
The comparison conducted in these previous studies in Seville verified that the \(DA\) values obtained for different thresholds (100, 250, and 500 lux), both during annual monitoring and through simulation using Radiance, resulted in a standard deviation of less than 10% (95% confidence level) in all cases, with an average standard deviation of 6.6% [41; 42; 56].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**WWR** & **Windows Position** & **Reflectance** & **Orientation** & **Location** & **Metrics** \\ \hline \(15\%\) (15) & Centered (C) & Bright (B) & North (N) & Seville (SEV) & \(DA_{300}\) \\ \(25\%\) (25) & Upper (U) & Dark (D) & South (S) & Barcelona (BCN) & \(DA_{500}\) \\ \(35\%\) (35) & & & & & \(CSA\) 1 \\ \(45\%\) (45) & & & & & \(CSA\) 2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Variables and metrics considered for the development of the calculation models.  
Figure 6: Relationship between \(CS\) and illuminance, according to the spectral irradiances depicted in Figure 5. The circles mark the calculated \(CS\) values for 300 and 500 lux with mainly clear skies, while the diamonds mark these \(CS\) values for intermediate skies.  
These validation procedures allow for the affirmation of the tool's accuracy and suitability for its intended applications.
# Method for Determining the Susceptibility of the Track
###### Abstract
The practical laboratory study is given by the 1:2.5 scaled physical model of one sleeper and the corresponding ballast layer box. The measurements of ballast pressure and deformations under the vibration loading in the ballast layer and the photogrammetric recording of the ballast flow are carried out. Damage to the track superstructure at the turnout is more complex than damage to sections of track and occurs at a much faster rate. The degradation process of the turnout is caused by the higher dynamic impacts of rail vehicles at the track discontinuities. In the crossover section, the most dangerous defects are non-adhesion of the needle to the resistor, chipping on the rolling surface of the needle and the resistor. In the crossover section, defects and damage to the turnout necessitating restricted operation include: crushing of the crossover bow, cracking of the crossover, and run-off in the wing rail glides. The turnouts in the cross member section are subjected to uneven dynamic loading, causing transverse cracks at the strongcrete turnouts. In experimental studies, the susceptibility is assumed as an element between two points (two masses)--most often the susceptibility is assumed as a Voigt model (parallel combination of stiffness and damping). The results obtained for stiffness (especially in a railway turnout) in the form of dry friction damping are functions that have not been determined experimentally in any of the known publications. The purpose of this paper is to outline a new method for testing the susceptibility of railway pavements, which is based on the principle of vibration-based damping determination. The method is completely non-destructive, requiring no disassembly of any pavement element.