esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Test Results and Analysis
### Durability
A row vector of fuzzy membership degree is formed for each evaluation factor, and the fuzzy appraisal matrix \(Z\) of \(k\) factors is established, as shown in Equation (9):  
\[Z= \begin{bmatrix}z_{11}&z_{12}&\dots&z_{15}\\ z_{21}&z_{22}&\dots&z_{25}\\ \cdot&\cdot&\cdot&\cdot\\ z_{k1}&z_{k2}&\dots&z_{15}\end{bmatrix} , \tag{9}\]  
The size of the matrix \(Z\) is consistent with the number of the evaluation factors and the grades. The vector of the evaluation result in the Criteria layer \(C\) was first calculated based on the weight vector of the alternatives in the AHP. The overall evaluation result of the goal layer \(R_{d}\) was then quantitatively calculated by Equation (10):  
\[R_{d}=(W_{C}\times Z_{C})\times[1\;2\;3\;4\;5]^{T}, \tag{10}\]  
The structure is in good condition when the value of \(R_{d}\) is close to 1. Based on the evaluation method mentioned above, a single girder, S2-G4, is taken as an illustration example for the durability evaluation. Following the evaluation criteria, the appraisal grade of each indicator in the Alternatives layer was first obtained according to  
Figure 12: Hierarchical structure of the durability evaluation. Figure 13: Membership function in the fuzzy mapping. the measurements in the field test, as summarized in Table 8. The pairwise comparison matrix in each layer is shown in Figure 14, and the weight vector of the Criteria layer \(W_{C}\) can be calculated as [0.0576 0.5132 0.3319 0.1153]. The overall evaluation results \(R_{d}\) of the girder segments S2-G4-1, S2-G4-2, S2-G4-3, S2-G4-4, and S2-G4-5 are 2.6406, 1.7740, 2.4977, 2.6575, and 1.5098, respectively. The maximum value of \(RD\) is 2.6575, which indicates that the S2-G4 girder is within the moderate deterioration condition. A total of 75 hollow slab girder segments shown in Figure 4 were evaluated using the durability evaluation method. The distribution of the \(R_{d}\) values is shown in Figure 15. A total of 69.3% of the girder segments are within the mild deterioration condition, and 98.7% of the girder segments are within the moderate deterioration condition after 25 years' service life. The difference of the durability performance between each span is not obvious.
# Detection and Mitigation of RPL Rank and Version Number Attacks in the Internet of Things: SRPL-RP
## The Proposed Protocol
### SRPL-RP Implementation
#### 3.4.1 Rank and Version Number Attacks Detection  
A node table is used to access the ranks of the parent, child, and neighbor nodes. The node needs first to satisfy the parent and child rank relationship. The parent should have a lower rank value compared to that of the child. Then, the NCR is compared with its NPR and NPVR. The node's rank is comparatively evaluated against child and sibling rank, by following Algorithms A1 and A2 in the appendix section, as referred to in Figure 1 in Section 3. In Algorithm A1, if the minimum rank among sibling nodes that are deduced from minimum PST is greater than the NCR, then the node is  
Figure 2: Protocol Model Flowchart, Phase Five.  
considered a malicious one; otherwise, it is considered a legitimate node. Similarly, in Algorithm A2, if the minimum rank among child nodes that are summed together with PST is greater than or equal to the NCR, then the node is considered a malicious one; otherwise, it is considered as a legitimate node.  
On the other hand, a version number attack is detected if the version number node is greater than the default root node's version number (240). The NCR is compared with its NPR (the parent rank must be lower than the current rank). Similarly, the node rank is compared with its NPVR. If the NPVR is lower than the NPR, then the network is stabilized, and the version field of each node in a table needs to be checked (after receiving the DIO). Otherwise, the node needs to update its version number. If half of the neighbor nodes in the neighbor table list have the same version number, then the version number in the DIO message of the current node is updated. Then, the version number is changed to the same majority version number in the list by checking the condition (version!= 240) in Algorithm A3 found in the appendix section, referred to in Figure 2 in Section 3.
## 4 Discussion
### Practical Implications  
The findings of this study support the incorporation of health monitoring systems on assembly lines, such as wearables, pointing to the most important parameters to be monitored in real-time. These systems could provide critical data to be used in the adjustment of workloads, task rotation, or prompt breaks to manage fatigue and reduce long-term health risks. For instance, reports of the workers' general status could be sent to the occupational physician and alert workers and supervisors of any alarming situation. In the construction industry, some studies have already included this type of monitoring, determining task demand by resorting to respiratory measures [71]. Additionally, alert systems based on HRV were implemented to activate when signs of fatigue were detected, thereby informing supervisors that workers required a break [72]. Regarding ergonomic intervention, these measurements could be used to leverage risk quantification tools, making them more comprehensive of the various domains affecting workers, not only accounting for biomechanical risks.
# Secure Speech Content Based on Scrambling and Adaptive Hiding
## 3 Proposed Scheme
### Hiding Module
#### 3.1.2 Binary Representation (Dec to Bin)  
The purpose of this block consists in representing in binary format the samples of the scrambled secret signal (for instance 8 or 16 bits). These bits will hide in the host signal through an adaptive LSB scheme. The output of this block is a chain of binary values of length equal to the total samples of the input signal multiplied by its resolution in bits.
### Factors Influencing Water Production
#### 4.2.3 Groundwater Stability Index  
The solubility of the groundwater medium refers to whether it has the ability to continuously dissolve soluble carbonate rocks. Currently, the commonly used method for determining this is the groundwater stability index method. The stability index of a groundwater medium can be determined by the following formula.  
\[pH_{S}=pK_{2}-pK_{S}-\lg[\ALK]-\lg[Ca^{2+}]+p \tag{4}\]  
\[p=\frac{2\sqrt{2.5\times 10^{-5}C}}{1+\sqrt{2.5\times 10^{-5}C}} \tag{5}\]  
\[S=pH_{\text{t}}-pH_{\text{s}} \tag{6}\]  
ALK--The alkalinity of the water sample, mol/L:  
\(PK_{2}\)--Logarithmic value of the second-order dissociation constant of carbonic acid:  
\(PK_{S}\)--Logarithm of the dissociation constant of calcium carbonate:  
\(\text{Ca}^{2+}\)--Molar concentration of calcium ions, mol/L:  
Figure 6: Relationship between average water production and porosity.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{Well} & \multicolumn{2}{c}{Groundwater} & \multirow{2}{*}{\(D\) Value} & \multirow{2}{*}{Porosity (\%)} & Total Water Content & Fault Fractal & Sand–Mud \\  & Stability Index & & & (10,000 m\({}^{2}\)) & Dimension & Ratio \\ \hline SY25 & 3.54 & 1.80 & 5.40 & 1.88 & 0.50 & 3.00 \\ SY29 & 3.78 & 1.68 & 4.79 & 1.20 & 0.70 & 0.54 \\ SY30 & 3.71 &  
_C_--Total dissolved solids, mg/L:  
_p_--Correction coefficient for salt content in water:  
_S_--Groundwater medium stability index, where _pH_\({}_{\text{I}}\) is the measured value.  
The solubility of a water medium worsens with increased \(S\), indicating stronger precipitiability and greater water medium stability [35]. A smaller stability index for a groundwater medium, on the other hand, infers greater solubility for the water medium. In the Shouyang Block, the stability index of the coal seam water medium varies between 2.94 and 4.47, with an average value of 3.63. The average water production decreases as the groundwater stability index increases, indicating that the wells with greater water production in the block are associated with the solubility of the limestone (Table 3; Figure 7).
## 2 Background and Key Features
### UAV Communication
#### 2.2.4 Ad Hoc Network Communication  
Ad hoc networking is a network model without the need for fixed infrastructure, allowing UAVs to establish communication links through multi-hop transmission between nodes. This technology is suitable for scenarios where multiple UAVs work collaboratively, such as post-disaster search and rescue, group reconnaissance, and other missions. In [38], to improve the performance of UAV networks in dynamic tasks, the authors introduced a cluster-based fault-tolerant routing technique. This technique divides UAVs into multiple communication clusters, allowing other nodes to quickly take over when some nodes fail, preventing link interruptions. In [39], the authors proposed a large-scale, decentralized, full-duplex ad hoc network for UAV communication, enabling each UAV node to have independent routing and forwarding capabilities and allowing each node to transmit and receive data simultaneously, enhancing system resilience and data transmission efficiency. The authors also proposed a cluster-based hierarchical architecture and distributed access technology, effectively improving the network's robustness and bandwidth utilization, suitable for complex flight missions and dynamic environments.
## 2 Fundamentals of the DC Microgrid
### Data Communication Flow  
Communication networks are crucial in power systems, forming a fundamental monitoring and control infrastructure. The information network in an islanded DC microgrid facilitates prompt data information exchange among the DER controllers. Data transmission relies on the type of communication topology, typically characterized by a sparsely connected network. Graph theory provides a mathematical representation of the communication network, as shown in (3):  
\[\mathcal{G}=\{\mathcal{V},\mathcal{E}\,\mathcal{A}\} \tag{3}\]  
where the set of converters is denoted as \(\mathcal{V}\), the communication edge set is represented as \(\mathcal{E}\subseteq\mathcal{V}\times\mathcal{V}\), and \(\mathcal{A}\in\mathbb{R}^{N\times N}\) depicts the adjacency matrix. Let \(k_{ij}\) represent the entities of \(\mathcal{A}\). Then, \(k_{ij}=1\) if \((v_{j},v_{i})\in\mathcal{E}\), and \(k_{ij}=0\) if \((v_{j},v_{i})\
otin\mathcal{E}\). The Laplacian matrix \(\mathcal{M}\) of graph \(\mathcal{G}\) is constructed using the components \(\mathcal{M}_{ii}=\sum_{i=j}k_{ij}\), and \(\mathcal{M}_{ij}=-k_{ij}\) for \(i\
eq j\)  
Figure 1: DC microgrid model.  
Define \(Sym(\mathcal{M})=\frac{1}{2}(\mathcal{M}+\mathcal{M}^{T})\), and let \(\hat{R}_{1}\),..., \(\hat{R}_{N}\) represent the eigenvalues of \(Sym(\mathcal{M})\). It follows that zero is a distinct eigenvalue of both the Laplacian matrix, \(\mathcal{M}\), and \(Sym(\mathcal{M})\) if the graph \(\mathcal{G}\) is strongly connected and weight-balanced. With no loss of generality, we represent \(0=\hat{R}_{1}\leq\hat{R}_{2}\leq\hat{R}_{3}\leq\ldots\leq\hat{R}_{N}\), where \(\hat{R}_{i}\) denotes the \(i\)th eigenvalue.  
This paper assumes a strong and weight-balanced connectivity among the converters in the communication graph. Due to the two-directional communication channel between any two converters, this requirement can be easily fulfilled as long as all converters are interconnected. Suppose there is an exchange of information between vertices \(i\) and \(j\). The attainment of consensus on the variable \(s\) is defined by \(s_{i}(t)-s_{j}(t)\to 0\), and this consensus is realized based on the first-order consensus expressed in (4):  
\[\dot{s}_{i}=-\sum_{j\in Nj\
eq i}k_{ij}(s_{i}-s_{j}) \tag{4}\]  
Considering the topology of the communication network utilized in the proposed control architecture, as depicted in Figure 2, it is apparent that every node possesses a minimum of one communication link. The matrix \(A\) signifies the composition of connections between nodes, with its elements represented by \(k_{ij}\). Here, \(j\) denotes the neighboring node, while \(i\) represents the local node. In matrix A, nodes without connections are clearly indicated by a zero value. The communication matrix possesses dynamism, allowing any disconnected node \(s\) to transition to a state of zero value.
# New Results on Neutrosophic Extended Triplet Groups Equipped with a Partial Order
## 1 Introduction  
Groups play a very important role in algebraic structures [1; 2; 3], and have been applied in many other areas such as chemistry, physics, biology, etc. The concept of neutrosophic set theory is proposed by [PERSON] in [4], which is the generalization of classical sets [5], fuzzy sets [6], and intuitionistic fuzzy sets [5; 7]. Neutrosophic sets have received wide attention both on practical applications [8; 9; 10] and on theory as well [11; 12]. The main idea of the concept of a neutrosophic triplet group (NTG), is defined in [13; 14]. For an NTG \((G,*)\), every element \(a\) in \(G\) has its own neutral element (denoted by \(neut(a)\)) satisfying \(a*neut(a)=neut(a)*a=a\), and there exists at least one opposite element (denoted by \(anti(a)\)) in \(G\) relative to \(neut(a)\) satisfying \(a*anti(a)=anti(a)*a=neut(a)\). Here, \(neut(a)\) is not allowed to be equal to the classical identity element as a special case. By removing this restriction, the concept of neutrosophic extended triplet group (NETG), is presented in [13]. Many significant results and several studies on NTGs and NETGs can be found in [15; 16; 17; 18; 19; 20]. On the other hand, some algebraic structures are equipped with a partial order that relates to the algebraic operations, such as ordered groups, ordered semigroups, ordered rings and so on [21; 22; 23; 24; 25; 26; 27; 28].  
Regarding these developments, as the motivation of this article, we will consider what it is like to endow a NETG with a partial order and introduce the concepts of partially ordered NETGs and positive cones. Then we consider a question: is a subset \(P\) of a NETG \(G\) the positive cone relative to some compatible order on \(G\) if \(P\) satisfies some conditions? To solve this problem,we investigate structure features of partially ordered NETGs and try to characterize the positive cones. Finally, we study properties of homomorphisms and quotient sets in partially ordered NETGs, and discuss the relationships between homomorphisms and congruences. In particular, the quotient set equipped with a special multiplication and a partial order provides a way to obtain a partially ordered NETG. All these results lay the groundwork for investigation of category properties of partially ordered NETGs.  
The rest of this paper is organized as follows. In Section 2, we review some basic concepts, such as a neutrosophic extended triplet set, a neutrosophic extended triplet group, a weak commutative neutrosophic extended triplet group and a completely regular semigroup, and several results were published in [16; 19]. In Section 3, we define a partially ordered neutrosophic extended triplet group and partially ordered weak commutative neutrosophic extended triplet group. Several of their interesting properties of partially ordered neutrosophic extended triplet group and partially weak commutative neutrosophic extended triplet group are explained. The homomorphisms and quotient sets of partially ordered neutrosophic extended triplet group are shown in Section 4. Finally, conclusions are given in Section 5.
# Conversation-Based School Building Inspection Support System
## 3 Methodology
### Display Module (D-Module)  
The D-module presents the inspection reports visually to lower the inefficiency and difficulty for managers to analyze data for making high-quality decisions. Managers need to understand both the routine damage and post-earthquake damage of school buildings and determine the budget allocation for building retrofits. The D-module supports managers in selecting digitalized reports, analyzing the reports, and visualizing the results to support decision-making.  
The dashboard is designed to be accessed with a web browser, and features two views:  
1. Summary view, which shows an overview of inspection reports utilizing data visualization;
2. Detailed view, which lists all the school inspection reports and provides the full report content of the selected report.  
The manager can switch between the two views, interact with the dashboard, and select one of the events on the dashboard. Both views consist of interactive maps to show the geographic distribution of inspection results. Additionally, colors are utilized for indicating the number, amount, or scale of different statistics, emphasizing the severity of damage or the progress of inspections.  
For the summary view, the D-module retrieves the inspections of the selected event from the database and performs data visualization for obtaining the summary of the event. The dashboard reveals the completeness of inspections in different districts with a colored map and the total amount of damage in different checklist categories. The manager utilizes the information shown on the dashboard to make decisions about allocating budgets and resources to retrofit the damaged school building.  
In the detailed view, the map demonstrates the number of critical schools in the affected areas by coloring them, while a table lists all schools and their reports. By clicking one of the areas on the interactive map, reports of schools in that specific area are selected and highlighted to emphasize their severity levels. The reports show the detailed damage, supporting the manager in efficiently determining which schools still have inspections in progress and to consume the reports in detail.  
Figure 2: Two-phase damage locating process.
# Cyclic Detectors in the Fraction-of-Time Probability Framework
## 2 Materials and Methods
### Cyclic Statistical Functions Estimators  
In this section, estimators for the FOT cyclic statistical functions considered in Section 2.2 are presented. These estimators are obtained by considering finite time-averages in place of the infinite-time averages present in the definitions of the FOT statistical functions [1] (Chapter 13), [2; 36] (Section 5.6). Moreover, for the cyclic CDF and the cyclic pdf, kernel-based estimators are proposed here for the first time.  
In the FOT approach, the randomness (variability) of the estimate depends on the choice of the central point of the finite observation interval (i.e., \(t_{0}\) in (1) with \(T\) finite; that is, without the limit operation) [36], [2] (Section 5.6). In the almost-periodic case, one estimates the Fourier coefficients of almost-periodic functions. Thus, \(z(t)\) in (1) is a sinusoidally weighted version of the second-order lag-product \(x(t+\tau)\ x(t)\) or of the indicator function \(\mathrm{u}(\xi-x(t))\). Statistical functions of estimates for \(t\in[t_{0}-T/2,t_{0}+T/2]\) are built considering estimates in smaller observation intervals \([u-b/2,u+b/2]\), with \(b\ll T\), and averaging these estimates when \(u\) ranges within \([t_{0}-T/2+b/2,t_{0}+T/2-b/2]\)[36]. An example is provided in Section 2.6.3.
# Comparative Transcriptomics for Pepper (_Capsicum annuum_ L.) under Cold Stress and after Rewarming
## 2 Materials and Methods
### Sequencing Reads Mapping and Identification of DEGs  
Raw reads were statistically analyzed using SOAPnuke and filtered using Trimmomatic [29]. Clean data were obtained by removing low-quality reads, reads containing adapter sequences, and reads with excessive unknown base N content. Then, clean data were aligned to the pepper reference genome sequence (Zunla-1) using HISAT [30]. The gene expression levels were quantified with fragments per kilobase million (FPKM) method using RSEM [31]. Genes with an adjusted \(p\)-value (Q-value) \(\leq\) 0.01 and a \(\mid\)log2 fold change (FC)\(\mid\geq\) 1.5 were identified as DEGs by using DESeq2 [32; 33].
## 5 Discussion
### Organic Matter Enrichment Mechanisms and Depositional Models of Various Lithofacies
However, the enhancement of terrigenous debris input also has a negative impact on organic matter enrichment. High terrigenous debris input can disrupt the redox conditions in the water column, leading to changes in the relatively reducing environment and preventing the well-preserved formation of organic matter. Similarly to Al content, the increase in paleo-productivity accompanies the increase in terrigenous debris input; therefore, it does not lead to the organic matter enrichment. Meanwhile, the lack of correlation between the proxy for original primary productivity and TOC content indicates that paleo-productivity is not the primary factor for organic matter enrichment in the Da'anzhai Member shale. Building upon the outcomes of paleoenvironmental reconstruction, we delve into the sedimentary patterns of shale within distinct lithofacies in the study area (Figure 10). The sedimentary environments of ORA and ORM appear to be relatively similar, both indicative of deposition under warm and humid conditions. This climatic setting aligns with the occurrence of the Toareian Oceanic Anoxic Event (T-OAE), characterized by a global temperature rise and heightened greenhouse effects leading to increased rainfall [46; 54; 55; 56]. During this period, the paleo-depth of the lake likely remained relatively high, resulting in low water salinity and fostering a relatively reducing sedimentary environment at the lake bottom. The conducive conditions facilitated the preservation of organic matter beneath the water, ultimately forming organic-rich shale. The primary distinction in the sedimentary environment between ORA and ORM lies in the magnitude of terrigenous debris input. In comparison to ORM, ORA exhibits a higher influx of terrigenous debris, introducing a greater amount of clay minerals and contributing to the distinctive characteristics observed in ORA. Figure 10: Conceptual model that explains sedimentary environment and pore system evolution of Da’anzhai Member induced by T-OAE. (**a**) Sedimentary environment of T-OAE response section; (**b**) sedimentary environment of T-OAE unassociated section. OPA predominantly originated in a hot and arid environment, characterized by a relatively shallow paleo-depth of the lake and comparatively higher salinity [36; 65]. However, these conditions were not adequate to induce distinct water column stratification. Furthermore, the low paleo-depth failed to generate a relatively reducing environment at the lake bottom. Despite the substantial influx of terrigenous debris, which heightened paleo-productivity to some extent, it also interfered with the original redox condition of the water, impeding the efficient preservation of the formed organic matter. This interference primarily contributed to the formation of OPA.