esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Results and Analysis
### Packet Delivery Rate  
Figure 14 shows the PDR of CAMs received on \(OBU2\) (the vehicle). PDR is approximately 100% for both 5G and hybrid, irrespective of the distance. For DSRC and C-V2X PC5, due to the transmission power selection for Cohda MK6 (DSRC) and MK6c (C-V2X PC5) modules, PDR stays approximately 100% till \(D_{thr1}\) and \(D_{thr2}\), respectively. Whereas, PDR is badly affected for both DSRC and C-V2X PC5 if the CAM transmissions continue beyond these distance thresholds. Even though the PDR for 5G is similar to that of hybrid scenario, Figure 12 suggests that the performance in terms of CAM transmission latency is far better for the hybrid as compared to the 5G only scenario. Moreover, the hybrid algorithm tries to maximize the transmissions in the 5.9 GHz ITS band, rather than utilizing the 5G band.
## 4 Application of the Design Method
### Selection of the Isolator Numbers and Sizes  
Gravity analysis is conducted to obtain the axial force of the columns and shear walls at the ground story, in order to determine the sizes and numbers of the isolators under these columns and shear walls. As mentioned above, the \(\sigma^{8}\) of isolators under the columns and the corner of the core tube are recommended to be approximately 10-12 MPa and 8-10 MPa, respectively. To achieve these, the sizes and the diameters of the isolators under the columns and the shear walls are determined as follows:  
(1) The area of the isolators under the columns except those under the corner columns is required to be no less than 1,452,250 mm\({}^{2}\). Hence, two isolators with diameter of 1000 mm are adopted, with the corresponding value of \(\sigma^{8}\) found to be approximately 11 MPa. The identical numbers and diameters of the isolators under the corner columns are adopted here for convenience, although a relatively lower \(\sigma^{8}\) with a value of 9.1 MPa is achieved.  
(2) The area of the isolators under the corner of the core tube is required to be no less than 1,491,500 mm\({}^{2}\). Two isolators with diameter of 1000 mm are also used, leading to the value of 9.5 MPa for \(\sigma^{8}\).  
(3) For the external and inner shear walls, the isolators with a diameter of 1000 mm and 900 mm are adopted, respectively. This difference in diameters is attributed to the fact that the axial force of the external shear walls is larger than that of the inner shear walls.  
Based on the above discussion, the sizes and numbers of isolators are determined and the process is schematically illustrated in Figure 14. In addition, the \(\sigma^{8}\) value of each isolator is also presented in Figure 14.  
Figure 14: Compressive stress of isolators under gravity load.
# DEEDP: Document-Level Event Extraction Model Incorporating Dependency Paths
## 5 Experiments and Analysis
### Results on MUC-4  
**Baselines.** We conducted a comparison experiment to verify the effectiveness of our method on the MUC-4 with the following baselines: pipeline-based or manual feature engineering based methods. [PERSON] [35] applied a sentential event recognizer to decide which sentences should be selected for event extraction and then used multiple plausible role filler recognizers to extract arguments as role fillers for formulating event records. [PERSON] [36] proposed a multi-stage approach for event extraction, which divided the processing procedure into the following: identifying narrative document, detecting event sentence, and noun phrase analysis. Cohesion Extract [37] first performed event arguments recognition in the processing text and took them as candidate role fillers, and then a cohesion sentence classifier was applied to refine the candidate set. [PERSON] [38] formulized the DEE as a neural seq-to-seq learning task and proposed a multi-granularity reader framework to dynamically aggregate semantic information from local sentence to the whole document by applying the advanced pre-trained language model BERT [29]. [PERSON] [16] proposed a MRC based event extraction framework for DEE, which can directly extract event records in a machine reading manner without performing sentence-level event arguments extraction.  
**Main Results.** Table 2 presents the main results on the benchmark MUC-4. From the comparison results, we can observe the following: (1) compared with other baselines, MMR achieved significant improvements, proving that the multi-granularity encoder benefits DEE; and (2) our proposed method, DEEDP, achieved +1.77 and +0.84 F1-scores over MMR for the head noun and extract match, respectively. This can be attributed to the semantic enhancing strategy introduced by using _TF-M_ encoder.  
In short, DEEDP effectively handles the long-distance dependencies problem between arguments by using a multi-granularity encoder, which helps in tackling the challenge of arguments-scattering for DEE. In addition, DEEDP introduces a novel Syntactic Feature Attention mechanism to explicitly model the semantic information of interdependency between tokens, which helps enhance the document-aware representations for each entity and improves the performance on document-level role filling tasks.
# Visible Spectrum and Infra-Red Image Matching: A New Method
## 5 Conclusions  
Textural and intensity changes between visible spectrum and infrared images degrade the performance of feature points. The proposed method overcomes such changes by training a regression model on correct feature point descriptor matches. It uses the regression model to align the descriptors prior to their descriptor matching. The experimental results show that the proposed method gives promising results. It gives relatively better results on RGB-NIR images compared to VS-LWIR images. The experimental results show that the proposed method obtains on average matching scores of 60% and 27% on RGB-NIR and MSD datasets, respectively, whereas HoDM obtains 45% and 16% average matching scores, respectively. The proposed method also achieves average precision scores of 81% and 37% and performs better than HoDM, which achieves 68% and 23% precision scores on RGB-NIR and MSD datasets, respectively. The experiments are also performed with different state-of-the-art feature matching strategies. The experimental results show that the proposed method also demonstrates better matching and precision scores with them compared to other descriptors.  
Conceptualization, S.S. and A.B.; methodology, S.S., and A.B.; software, S.S.; Data curation, A.B., validation, A.B.; formal analysis, S.S. and A.B.; investigation, S.S. and A.B.; resources, A.B.; writing--original draft preparation, S.S. and A.B.; writing--review and editing, S.S. and A.B.; visualization, A.B.; project administration, A.B.; funding acquisition, A.B. All authors discussed the results and contributed to the final manuscript. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
The authors declare no conflict of interest.
## 2 Engineering Background  
Zhangshuanglou Coal mine, located in the city of Xuzhou, Jiangsu Province in China, is a typical kilometer-deep mine that also encounters coal burst risk during excavation. The main factors influencing coal burst risk are coal seam depth, geological structure, as well as thick-hard roof. The longwall face LW23908 is the eighth working face in the No. 23 mining district, where the shallow area (south side) was finished and tuned into gobs; the coal pillars between coal faces are 5 m on average; a simplified schematic is shown in Figure 1. LW23908 exploits coal seam No. 9, which is 0.1-4.0 m thick in the whole mine, an average of 2.1 m, with a dip angle of 22\(\sim\)26\({}^{\circ}\). The stratum in this panel is a monoclinic structure inclined towards NW, which is from the tail entry to the head entry in Figure 1. The size of the LW23908 is 190 m wide and 1180 m long, and the depth is over 1000 m, ranging from 1055 m to 1150 m. The immediate roof is gray-black mudstone with an average thickness of 1.0 m, and the main roof is a 40.8 m thick gray-white fine sandstone composed of quartz and feldspar. The features of the roof and floor strata are shown in Table 1. Both the coal seam and main roof have bursting liability tested based on the national standards of \"Methods for test, monitoring, and prevention of rock burst-part 1: Classification and laboratory test method on bursting liability of roof strata, and part 2: Classification and laboratory test method on bursting liability of coal\". The results are shown in Tables 2 and 3.  
Figure 1: Sketch layout of LW23908.  
The coal burst risk degree of LW23908 is moderate based on the geological and mining technical conditions using the composite index method proposed by Prof. [PERSON] [29]. The dominant factor is the thick hard main roof which would cause severe dynamic disturbance to the coal seam during rupture and collapse, especially when the gob is a square, which is also named the \"square effect\" of the hard roof in some China coal mines. Historical data and experience of adjacent workfaces in the area also proved the \"square effect\" phenomenon; therefore, the mechanism, monitoring, and control of the \"square effect\" is the key to ensuring the safety of LW23908.
## 3 Literature Review
### Population Coverage  
Census data collection has long been a concern due to its limitations in accurately covering all forms of living arrangements for individuals within a region or country. The guidelines set forth by the United Nations for enumeration recommend canvassing households, but this approach overlooks individuals who lack proper living arrangements, such as homeless communities, frequent travellers, and nomadic groups who do not associate themselves with a fixed location [11].  
Unfortunately, these gaps in census data have real-world consequences. For example, during Pakistan's 2017 census, approximately 1.5 million people from Karachi were reported missing from the count [12]. Similarly, in the United States, the 2010 census missed 1.5 million children from minority communities, particularly 2.1% of Black Americans and 1.5% of Hispanics [13]. These discrepancies highlight the need for a more comprehensive and inclusive data collection approach.  
The transparency, quality, and accuracy of data are also pressing challenges in the current census system, as is the need to safeguard personally identifiable information (PII) [6]. The sensitivity of these data makes it crucial to adopt robust data protection measures to ensure privacy and prevent misuse.  
Efforts have been made to address the issue of \"difficult-to-enumerate\" population groups. The UN principles suggest incorporating the place of count for the census and whether it represents the individuals' usual residence, aiming to reduce miscounts of children and frequent travelers [1]. While this is a step in the right direction, it still falls short of accounting for dynamic variables and requires a more comprehensive and adaptable approach that encompasses homeless, stateless, and refugee groups.  
Another significant concern is over-coverage, which occurs when there is duplication in the data, leading to individuals being counted more than once. This could happen with individuals having multiple jobs or addresses [12]. Although over-coverage can be managed, it may not always be handled in the most efficient manner.
# Conceptual and Technical Design Aspects of Accelerators for External Injection in LWFA
## 2 Requirements for the Externally-Injected-Electron Bunch
### Transverse Matching of Electrons with the Plasma Bubble  
Assuming a constant focusing channel, the Courant-Snyder (C-S) parameters for a matched emittance-dominated beam are given by [27]:  
\[\beta_{x}=\beta_{y}\simeq 1/\sqrt{K_{r}} \tag{3}\]  
\[\alpha_{x}=\alpha_{y}\simeq 0, \tag{4}\]  
where \(K_{r}\) is the focusing strength, which in the blow-out regime is given by:  
\[K_{r}=k_{p}^{2}/(2\cdot\gamma), \tag{5}\]  
where \(k_{p}\) is the plasma wavenumber and \(\gamma\) is the beam relativistic parameter. It has to be noted that the matched \(\beta\) is energy-dependent. This means that while the beam is accelerated, its spot size must decrease according to \(\sigma_{0}\propto E^{-1/4}\).  
A mismatch of the injected beam will cause an increase of the beam normalized emittance according to [28]:  
\[\epsilon_{n,fin}=\frac{\epsilon_{n,init}}{2}\left(\frac{1+\alpha^{2}}{\beta^{ \star}}+\beta^{\star}\right) \tag{6}\]  
with \(\beta^{\star}=\beta/\beta_{m}\) expressing the discrepancy between the input \(\beta\) and the matching value \(\beta_{m}\).  
The requirement for the matched C-S parameters can be relaxed by introducing properly-shaped ramped plasma electron density profiles at the entrance (and at the exit) of the plasma chamber, which complete the matching to the main acceleration channel [29].  
The strong focusing of the fields inside the plasma bubble also has important implications for the necessary transverse alignment of the bunch trajectory with the plasma wake-field. More specifically a pointing stability of a few micrometers is required.
# A Customer-Centric View of E-Commerce Security and Privacy
## 1 Introduction
### Motivation  
Differences in the banking system, legal framework, and user sensitivity toward security can impact the customer's perception of security and privacy. Most studies conducted to understand customer perception originate from developed countries, such as the USA, the UK, Singapore, China, and Poland. These countries have a lot more exposure to technology, and they have been blessed with a more reliable banking systems and robust legal infrastructures [14; 15; 16; 17]. Therefore, it is scientifically interesting to explore the factors determining customer perception regarding the security of e-commerce applications in a developing economy. Consequently, we conducted an empirical study in Pakistan, a developing nation, to understand how e-commerce customers in Pakistan perceive security related to e-commerce and trust in online shopping. Positive perception can help to foster secure behavior in e-commerce usage whereas a negative perception may lead to limited usage of e-commerce by consumers. We used the protection motivation theory (PMT) as a theoretical model for our study.  
PMT was developed by [PERSON] [18] to better understand fear and explain how people react to it. Perceived vulnerability, severity, response efficacy, self-efficacy, and response cost are the key constructs of PMT, and their joint impact helps in determining intentions to protect against such a threat [18]. Perceived vulnerability refers to the likelihood of being affected by the threat, perceived severity highlights the severity of the threat in case of impact, response efficacy refers to the usefulness of mitigation strategies, self-efficacy refers to the ability to carry out mitigation strategies, and response cost refers to the cost incurred to execute mitigation strategies. This theory has been applied in many domains to explain the behavior of people in different situations such as health risks [19; 20; 21], flooding, and typhoons [22]. Similarly, PMT has also been used in different cybersecurity contexts [23; 24; 25]. We, thus, used this theory in our work to understand the customer's perception regarding the security of e-commerce websites in Pakistan. We used perceived vulnerability, perceived severity, response efficacy, and response cost to understand the customer's perception of security and privacy in Pakistan. The contribution of our study presents empirical insights into customers' perceptions and trust in e-commerce in Pakistan. On the basis of the empirical data, we present a model to improve the trust and security perception of e-commerce among Pakistani customers.  
The remainder of the paper is structured as follows: related work is discussed in Section 2 and research design is presented in Section 3; Section 4 presents the results, followed by a discussion in Section 5 and a conclusion in Section 6.
## 6 Results
The comparison between the graph in Figure 7 and the same graph for case A in Figure 3 highlights that the exploitation of end-user flexibility increases the feasible upper limits (>3 MW), while the lower limit (about \(-3.5\) MW) increases the potential flexibility offered to the TSO, but, taking into account only the feasible points, the availability in such a region is not modified between case A and B. In the other feeders (except the dedicated feeder D3) in case B, a slight increase in the unfeasible point occurrence appears, but it is important to remark again that it depends on the more extensive range of market potential obtainable with the end-user involvement. In other words, with the end-user participation, the potential flexibility volume increases, and, consequently, a bigger number of unfeasible points can be detected. However, the total feasible energy available for the TSO is bigger in comparison with the case with the participation of the DG units only. The comparison of the potential active power profiles of the feeder R2, reported in Figures 5 and 8 for cases A and B, respectively, show that in the last case, the area formed by the (feasible) green points close to the expected profile is bigger than the first one(Figure 8 vs. Figure 5). In addition, in the case of B, the potential active power reaches the +3.5 MW, and some reverse flow conditions (especially in the autumn season--Figure 8) appear. In contrast, in the other case (case A), such potential is limited to \(0.6\div 3.4\) MW (Figure 5). Figure 8 also shows that the operating points close to +3 MW need reactive support (Q control--orange points) to solve the technical violations. However, over this value, feasible conditions can still be found. The same comments can be made for the other feeders. Figure 7: Potential P profile during all representative days, feeder R1—case B (“DG + end-users”). Only the single feeders have been discussed regarding the flexibility until this point. However, the entity that offers flexibility products to the TSO is the substation described in Figure 2. Concerning the whole substation, in Table 4, some aggregated results are reported for the two cases (A-B) simulated, differentiated between the upward and downward parts. The results show that despite the great potential (i.e., 9 GWh/year in upward and 42 GWh/year in downward--case A), the grid limitations reduce the flexibility that can be offered without incurring in DSO blocks. The reductions are, respectively, 10% in upward and 12% in downward; similar values have been obtained for case B. Furthermore, extra costs have to be considered. The quantity is different for the upward and downward BIDS according to the different DER availability reported in Table 1. To sum up the different behaviour, a unitary price has been calculated, with and without the extra cost relevant to the reactive support needed in the orange points. The unitary price derives from the combinations of the different offers (DG and end-users). Regarding the results reported
## 2 Biosynthesis and Precursors of Terpenoids
DXS 1-deoxy-D-xylulose-5-phosphate synthase; DXR 1-deoxy-D-xylulose 5-phosphate reductio isomerase; CMS 2-C-methyl-D-erythht 4-phosphate cytidylyltransferase; CMK 4-diphosphocytidyl-2-C-methyl-D-erythht 1 kinase; MCS 2-C-methyl-D-erythht 2, 4-cyclodiphosphate synthase; HDS 4-hydroxy-3-methyl-but-2-enyldiphosphate synthase; HDR 4-hydroxy-3-methyl-but-2-enyldiphosphate reductase; GPPS geranyl pyrophosphate synthase; GGPPS geranyligeranyl pyrophosphate synthase; STPS sesquiterpene synthase; LPP linalyl pyrophosphate; NPP neryl pyrophosphate; GAO germacrene A oxidase; GAS germacrene A synthase; CTS costunolide synthase; PTS parthenolide synthase; LNS linalool synthase; LMS limonene synthase; PES pinene synthase; MCS myrcene synthase. As representative examples of terpenoids: linalool, limonene, \(\alpha\)-pinene, \(\beta\)-myrcene, germacrene A, germacrene A acid, costunolide and parthenolide are illustrated in chemical structure. C15 sesquiterpenoids are derived from FPP by the action of farnesyl pyrophosphate synthase (FPS), and is the common precursor of all sesquiterpenoid lactones (STLs). Sesquiterpene synthase (STPS) catalyzes the cyclisation of FPP in the first step of STL biosynthesis [39]. They are mainly located in the cytosol and are characterized by their plasticity, showing the capacity of multiple substrate utilization. Germacrene A synthase (GAS) is one of the best-characterized STPS, converting FPP into germacrene A (GA). Germacrene A oxidase (GAO), a cytochrome P450-like enzyme, converts GA into germacrene A acid (GAA). To produce costunolide, GAA is further oxidized by the costunolide synthase. Furthermore, to produce the end product of parthenolide, this costunolide catalyzes the epoxidation of the C4-C5 double bond. Figure 1 depicts the overall biosynthetic pathway and intermediate chemical structure of monoterpenoids and sesquiterpenoids [40].
## 4 Implementations with DSD Reaction Networks
### Brink Controller with Indirect PAR (BC-IPAR)  
The difference between BC-IPAR and BC is the reaction mechanism \(U+U^{*}+R_{r}\xrightarrow{\delta_{c}}2U\). Many reactions in BC-IPAR of Equation (18) have been designed to correspond to DNA reactions, according to Equations (23)-(25). Then, for the reaction \(U+U^{*}+R_{r}\xrightarrow{\delta_{c}}2U\) in Equation (18), it can be represented abstractly as the following ideal reactions:  
\[\begin{array}{l}U^{*}+R_{r}\to U^{*}\cdot R_{r}\\ U+U^{*}\cdot R_{r}\to U+U\end{array} \tag{27}\]  
Equation (27) can be transformed into  
\[\begin{array}{l}U^{*}+L_{6}\xleftarrow{q_{12}^{\frac{q_{12}}{2}}}H_{6}+Sp17 \\ R_{r}+H_{6}\xrightarrow{q_{\max}}O_{9}+Sp18\\ O_{9}+T_{9}\xrightarrow{q_{\max}}U_{*}\cdot R_{r}+Sp19\\ U+L_{6}\xleftarrow{q_{13}}H_{7}+Sp20\\ U_{*}\cdot R_{r}+H_{7}\xrightarrow{q_{\max}}O_{10}+Sp21\\ O_{10}+T_{10}\xrightarrow{q_{\max}}2U\end{array}\Bigg{\}} \tag{28}\]  
**Remark 4**: _Let \(i\), \(n\), \(x\), \(y\) and \(z\) be variable sets such that \(i\in(1,2,\ldots,13)\), \(n\in(1,2,\ldots,21)\), \(x\in(1,2,\ldots,6)\), \(y\in(1,2,\ldots,7)\) and \(z\in(1,2,\ldots,10)\). For DNA realization, \(G_{x}\), \(T_{x}\) and \(L_{y}\) represent auxiliary substances involved in the reactions, \(O_{z}\) and \(H_{y}\) denote intermediate substances, and \(Spn\) indicates the inert wastes produced by the reactions that do not interact with other substances._In addition, \(C_{\max}\) indicates the initial concentration of auxiliary substances, \(q_{\max}\) represents the maximum strand displacement rate, and \(q_{i}\) denotes the reaction rate obtained by the corresponding DNA implementations. The auxiliary species \(G_{x}\), \(T_{x}\) and \(L_{y}\) involved in Equations (20)-(28) are initialized to the maximum concentrations to prevent their consumption from affecting the kinetic process. In addition, both for auxiliary species \(G_{x}\) and \(T_{x}\) are irreversibly consumed.