esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Testing
### Test Setup and Protocol
#### 2.2.1 Monotonous and Cyclic Load Application  
During the testing of the specimens, the increase of the horizontal load was controlled by manually entering the displacement of the horizontal press. In the case of a monotonous load, the curve of the displacement increment was programmed so that the horizontal press rested for a certain time (1 min) after each 10 mm displacement increment in order to check the measuring points (Figure 5). These pauses during the test were also necessary to determine the development of cracks and to mark and measure their widths.  
Figure 4: Effect of the vertical press rotation to a horizontal force component.  
The quasi-static cyclic load input report was preformed according to the guidelines given in [40].  
The following guidelines were adopted in the testing protocol:  
* In total, two load cycles were performed for each load (displacement) amplitude;
* More than six load cycles (8 cycles) have been carried out until the lowest damage limit
* The value of the maximum amplitude was determined from the monotonous testing of the elements
* The number of load input cycles was more than 10 (22 cycles)
* Each subsequent load amplitude is approximately increased according to the following expression:  
\[\alpha_{\text{i+1}}=1.4\ \times\ \alpha_{\text{i}} \tag{1}\]  
where \(\alpha_{\text{i}}\) is the amplitude of the previous step and \(\alpha_{\text{i+1}}\) is the amplitude of the next step.  
A cyclic curve was formed according to the above guidelines and then applied with a computer-controlled horizontal press by entering a displacement cycle from 0 to 100 mm.  
The displacement was increased until the moment of failure of the concrete in the compression section at the bottom of the column. After the maximum horizontal displacement was reached and all the measuring points were recorded, the horizontal press was returned to its initial position, followed by the unloading of the vertical press.  
The maximum displacement of the top of the column was 100 mm for all monotonically tested specimens. In all tested specimens, failure occurred in the compressive area of the concrete in the lower section of the column.
# Connectivity Analysis in VANETs with Dynamic Ranges
## 4 Discussion
### Distribution of Ranges
#### 4.1.4 Weibull Distributed Ranges  
In Figure 5, Weibull range distribution captures a rural fading environment where, with a LOS more significant stable connectivity can be sustained for a typical VANET network. When \(C=2\), this represents Rayleigh fading distribution with no LOS (typical urban and suburban areas) while as \(C>2\) the fading worsens and this is due to shadowing effects of nearby trees, neighbor vehicles among other issues such as big vehicles obstructions that add to the path-loss effects. We use \(\alpha=(2.4,5]\) provided that the vehicle arrival rates and densities are fixed and the power reception will be affected by mainly multipath fading. We see that the typical communication ranges are within an average of 50 m as in Figure 5a.
# Effect of Excitation Beam Divergence on the Goos-Hanchen Shift Enhanced by Bloch Surface Waves
###### Abstract  
The Goos-Hanchen (GH) shift is simulated and experimentally studied when the Bloch surface wave is excited in the forbidden band of a one-dimensional photonic band-gap structure for an excitation beam with different divergence. By changing the beam waist radius, a correspondingly changed Goos-Hanchen shift curve can be observed, where with a larger waist radius and the corresponding less divergence of the excitation beam, a greater GH shift that is closer to the Artmann estimation is obtained. The experimental demonstration of this phenomenon agrees well with the theoretical simulation.  
Goos-Hanchen shift; Bloch surface wave; one-dimensional photonic band-gap Article
# Accident Risk Analysis of Gas Tankers in Maritime Transport Using an Integrated Fuzzy Approach
## 1 Introduction
Even though a considerable number of studies have been conducted on individual risk categories in gas tanker operations, with a particular focus on explosion risk analysis, fuel leakage mechanisms, and operational safety procedures, there remains a paucity of holistic approaches that simultaneously address the interplay of these factors [11]. In particular, the extant literature frequently fails to consider the interdependence and cumulative effects of mechanical, human, and environmental risks. This finding is of particular significance when considering the possibility of a domino effect in accident progression. To address this gap, the present study proposes a novel hybrid risk assessment model that integrates the Fuzzy Delphi Method, Fuzzy DEMATEL, and Fault Tree Analysis (FTA). This integrated approach facilitates the identification and prioritisation of risks based on expert judgment. It also enables the mapping of causal relationships among risks and the simulation of potential accident scenarios. The objective of this study is to enhance the predictive capability of existing models and to support gas tanker operators in developing more robust and proactive safety strategies. The subsequent sections of the paper are structured as follows: Section 2 provides a comprehensive review of the extant literature on gas tanker safety, explosion risk, leakage control, and operational protocols. The third section delineates the methodological framework and provides a rationale for the utilisation of Fuzzy Delphi, Fuzzy DEMATEL, and FTA methodologies. The findings derived from expert input and modelling are presented in Section 4. A discussion of the implications and limitations is offered in Section 5. Finally, Section 6 concludes with recommendations for improving operational safety and future research directions.
# A Dynamic Framework for Community-Facility Siting with Inter-Community Competition
## 4 Empirical Study  
### Study Area  
To validate BOMSDM's effectiveness, 83 communities in the central area of Shaoxing City (including four urban villages) were selected as a study case (area 53,826,540 m\({}^{2}\)), as illustrated in Figure 2. Like most cities, this region represents typical residential spatial differentiation [74]. These residential zones are fragmented into communities of varying sizes, with the largest community spanning 3,807,589 m\({}^{2}\) and the smallest at 47,807 m\({}^{2}\). These characteristics render the area suitable for testing the model proposed. The residential spatial differentiation contributes to enlarging the results and scope of two objectives, while differences in community sizes can examine the impact of facility-community allocation constraints on overall efficiency and fairness.  
In 2019, Shaoxing became one of the pilot cities for \"Zero Waste Cities\". Funded by the district-level government, the allocation of recycling stations was carried out as an essential community facility. By 2020, a total of 79 stations were constructed, each allocated to one community (four urban villages were not required to build recycling stations, but the residential buildings within them needed to be covered by services). However, some of the stations incurred losses due to poor site selection, leading to closures or relocation [75], leaving only 72 stations remaining by the end of 2023. The realistic solution of recycling stations can serve as a reference for testing the effectiveness of the BOMSDM.  
Figure 2: Distribution of communities within the study area.
# Using Improved Brainstorm Optimization Algorithm for Hardware/Software Partitioning
## 5 Experiments and Discussion
### Comparisons between IBSO and Several Heuristic Algorithms
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Nodes**} & \multicolumn{2}{c}{**BSO**} & \multicolumn{2}{c}{**GA**} & \multicolumn{2}{c}{**ABC**} & \multicolumn{2}{c}{**PSO**} & \multicolumn{2}{c}{**AFSA**} \\ \cline{2-10}  & \(\alpha\) & \(\beta\) & \(\alpha\) & \(\beta\) & \(\alpha\) & \(\beta\) & \(\alpha\) & \(\beta\) & \(\alpha\) & \(\beta\) \\ \hline
50 & 4.0\% & 11.3\% & 4.3\% & 26.4\% & 12.7\% & 14.6\% & 8.9\% & 34.6\% & 0.0\% & 84.4\% \\
100 & 5.5\% & 1.9\% & 5.6\% & 37.0\% & 7.6\% & 26.2\% & 7.4\% & 38.6\% & 0.1\% & 86.6\% \\
150 & 8.0\% & 2.3\% & 7.2\% & 39.7\% & 14.5\% & 30.2\% & 12.8\% & 40.0\% & 0.0\% & 86.6\% \\
200 & 10.0\% & 6.2\% & 5.7\% & 40.3\% & 14.5\% & 30.6\% & 9.8\% & 40.1\% & 1.4\% & 86.3\% \\
300 & 9.9\% & 2.1\% & 6.3\% & 38.9\% & 18.6\% & 31.8\% & 12.2\% & 39.1\% & 1.0\% & 86.8\% \\
500 & 16.8\% & 0.2\% & 11.3\% & 39.8\% & 25.9\% & 33.5\% & 14.6\% & 40.2\% & 2.1\% & 85.9\% \\
700 & 14.1\% & 2.8\% & 9.3\% & 43.6\% & 25.0\% & 38.5\% & 12.1\% & 43.5\% & 1.3\% & 86.1\% \\
1000 & 6.7\% & 5.6\% & 5.0\% & 41.6\% & 21.4\% & 37.9\% & 6.8\% & 42.4\% & 0.0\% & 83.4\% \\ Average & 9.4\% & 4.1\% & 6.7\% & 38.4\% & 17.5\% & 30.4\% & 10.6\% & 39.8\% & 0.7\% & 85.8\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparisons between the IBSO, BSO and four original heuristics algorithms. Figure 7: Comparison of experimental results in solution quality and running time. the AFSA. In addition, we applied two improved BSO algorithms to hardware/software partitioning. The two improved algorithms include the brainstorm optimization with chaotic operation (BSOCO) [28] and advanced discussion mechanism-based brainstorm optimization algorithm (ADMBSO) [29]. BSOCO and ADMBSO were also tested by the eight benchmarks and the algorithms are terminated after 1000 iterations. Based on the experimental results, the values of \(\alpha\) and \(\beta\) of BSOCO and ADMBSO are calculated and shown in Table 5.  
It can be seen form Table 5 that the solution quality of BSOCO and ADMBSO is better than that of BSO, but their running time was also longer. That means BSOCO and ADMBSO can successfully improve the search ability of the original algorithm, but they also increased the algorithm complexity. Compared with BSOCO and ADMBSO, IBSO shows better search ability and higher algorithm efficiency. Different from BSOCO and ADMBSO, the improvements of IBSO mainly focus on improving the performance of solving the discrete optimization problems. Therefore, IBSO is more suitable for solving the hardware/software partitioning problem.
## 4 The Security of QOT
### Privacy for [PERSON]
#### 4.1.2 Analysis on the Probability of Getting a Conclusive Bit for Malicious Bob  
Assume that the malicious [PERSON] has the ability of separating \(n\) photons by photon number splitting attack. For a single photon, the successful probability of optimal measurement to distinguish the two non-orthogonal states is \(1-cos\varphi\), which has been proved in Refs. [56; 57; 58]. For \(n\) photons, a malicious [PERSON]'s probability of distinguishing the non-orthogonal sates is  
\[p^{\prime}(n)=1-cos^{n}\varphi. \tag{6}\]  
Then, a malicious [PERSON] using photon number splitting attack and optimal measurement for single-photon can get a conclusive bit with the probability of  
\[p^{\prime}_{con}(\mu)=\sum_{n=1}p_{n}(\mu)\times p^{\prime}(n)=1-e^{-\mu(1- \frac{\sqrt{3}}{2})}. \tag{7}\]  
Here we consider that the malicious [PERSON] has an ideal detector, the quantum efficient \(\eta^{\prime}_{D}\) of which is 100%. Thus, \(\mu^{\prime}=\mu_{S}\eta_{C}=\frac{\mu}{\eta_{D}}\). Assume that the protocols are executed over atmospheric channel, the quantum efficiency \(\eta_{D}\) of an honest [PERSON]'s detector is 80% and this kind of detector has already been realized in the laboratory [54; 55]. The cheating [PERSON]'s probability of getting a conclusive bit is  
\[p^{\prime\prime}_{con}(\mu)=1-e^{-\frac{5p}{4}(1-\frac{\sqrt{3}}{2})}, \tag{8}\]  
which can be seen in Figure 3. A malicious [PERSON] can get about \([1-e^{-\frac{5p}{4}(1-\frac{\sqrt{3}}{2})}]N\) conclusive bits.  
Figure 2: The probability that an honest [PERSON] gets conclusive bit changing with \(\mu\).
## 5 Results and Discussion  
### Importance Analysis and Results of Level 1 Indicators  
As illustrated in Figure 3, Security and Privacy (0.4094) emerges as the most critical indicator within the level, followed by Learning and Operation (0.2674), Information Architecture (0.2052), Interaction Experience (0.0823), and finally, Emotional Design (0.0357). This reflects the highest level of concern users have for the protection of personal information and financial data security when using second-hand transaction apps. Furthermore, the ability to simply and conveniently use the software, easily find the information users seek, and the interface attractiveness are all important criteria for evaluating second-hand transaction apps. Although Emotional Design holds a lower weight, it plays a subtle yet significant role in enhancing user loyalty and establishing brand image. Therefore, in the design and development of second-hand transaction apps, comparatively more focus should be placed on protecting user information and assets as well as facilitating a convenient and comfortable software usage experience than on enhancing user loyalty and building a brand image.
# Denial-of-Service Attacks on Permissioned Blockchains: A Practical Study
## 6 Discussion
### Key Findings from Experimental Attacks
* Selective disruption via boycott and collusion: Attacks such as the certificate revocation by compromised MSPs or colluding orderers refusing to commit transactions allowed for a selective DoS. These attacks evaded detection while severely impacting specific users or disrupting the network-wide throughput. They highlight the need for better monitoring, accountability, and proactive certificate lifecycle management.
# A Survey of Generative AI for Detecting Pedophilia Crimes
## 2 Background
### Comparative Technical Analysis
#### 2.4.2 Implementation and Fine-Tuning Challenges  
Despite their capabilities, the practical implementation of these LLMs reveals distinct challenges related to safety, bias, and resource requirements.  
ChatGPT faces several known issues. The model can be vulnerable to \"jailbreaking\", where carefully crafted prompts are used to bypass its safety protocols and generate undesirable outputs [12]. It is also susceptible to perpetuating biases present in its training data and can sometimes struggle with logic and reasoning [12]. Furthermore, operating ChatGPT for certain applications can incur significant computational costs, potentially limiting its adoption [12].  
The primary challenges associated with Gemini are related to its safety features and developmental stage. Its safety filters have been found to operate inconsistently across different languages and scenarios, with censorship being applied unpredictably, which raises concerns about its reliability [13]. As a more recent model, Gemini's limited exposure to extensive real-world data may hinder its ability to address nuanced biases when compared to more mature models [12].  
LLaMA, on the other hand, exhibits a strong and consistent \"optimistic bias\" in its outputs, tending to rate scenarios positively regardless of their negative context [13]. A significant practical challenge is its hardware requirements; while compact versions can be run locally, the more extensive models demand impractically long periods to generate responses on personal computers, making them inaccessible to the average user [13].  
The technical comparison in Table 1 is directly relevant to the context of detecting crimes related to pedophilia. It is crucial to understand the architectural differences, strengths, and limitations of leading LLMs--such as ChatGPT, Gemini, and LLaMA--to assess their suitability in sensitive domains like online grooming and CSAM detection. For example, Gemini's multimodal capabilities allow for the simultaneous analysis of image- and text-based content, which is essential for identifying disguised CSAM across platforms. Similarly, LLaMA's lightweight architecture may enable local deployment for privacy-sensitive scenarios, such as client-side filtering. Thus, this comparative overview informs model selection based not only on performance, but also on legal, ethical, and operational constraints in real-world deployments.
## 5 Results and Discussion
### Modified Tip Resistance  
The tip resistance of the test shafts TS1 and TS2 was obtained by subtracting the side resistance of lower shaft segments from the O-cell load. The percentage of the tip resistance and side resistance of shafts TS1 and TS2 in the total equivalent top load at various loads is demonstrated by Figure 11.  
As shown in Figure 11, the grouted shaft TS2 has a higher percentage of tip resistance compared to the control shaft TS1 under various loads. Furthermore, the ratio of tip resistance to total load for test shafts TS1 and TS2, which reached ultimate bearing capacity, was 23.83% and 34.26%, respectively. This result shows that the tip resistance of the shaft can be mobilized more rapidly and fully after grouting, and the side and tip resistance are mobilized in a more synchronized and coordinated manner due to the pre-mobilization of the grouted cement.  
Pre-mobilization refers to mobilization of \"negative\" side resistance along the length of the shafts in proportion to the magnitude of the bi-directional force induced during grouting, with simultaneous consumption of an equal magnitude of tip resistance. The net effect of pre-mobilization is to improve the \"stiffness\" of the load-displacement response at  
Figure 10: Shaft resistance and shaft–soil relative displacement response in different depth soil layers. (**a**) Depth of 0–4.4 m. (**b**) Depth of 10–16.4 m. (**c**) Depth of 16.4–29.4 m.  
intermediate loads without changing the ultimate resistance for the post grouted drilled shafts. In order to maximize pre-mobilization, it is advantageous to maximize the bi-directional force due to the grout pressure. Nevertheless, ground improvement at the shaft tip and enlargement of the shaft tip could increase the ultimate tip resistance [21; 30].  
As shown in Figure 7, due to the insufficient grouting pressure, the preloading failed to fully mobilize the negative friction along the shaft TS3. Since the formation of the grout bulb at the tip of shaft TS3 was smaller than that of test shafts TS2 and TS4, resulting in lower stiffness and bearing capacity of test shaft TS3 compared to that of the other grouted test shafts.
# Defects in Silicon Carbide as Quantum Qubits: Recent Advances in Defect Engineering
## 4 Conclusions  
The remarkable potential of silicon carbide (SiC) and its point defects for quantum applications has been convincingly demonstrated over the past decade. Notable advancements have been made in defect engineering, particularly in the precise and reproducible creation of color centers such as the silicon vacancy and divacancy. Techniques such as focused ion beam (FIB) implantation and femtosecond laser writing have emerged as powerful tools. These methods offer enhanced control over the spatial localization and density of defects, which is essential for scalable quantum device fabrication. Further cost-effective improvements are anticipated with the advancement of fabrication methods that eliminate the need for pre- or post-fabrication annealing.  
Additionally, a significant milestone in defect engineering has been the achievement of optical charge state control in divacancy centers, marking a critical step toward reliable quantum operation. The level of understanding and control achieved for defects such as the silicon vacancy and divacancy has not yet been reached for other, newly emerging defects. However, these emerging defects may still find unique applications within the broader field of quantum technologies, even if not directly as qubits.  
Among the different polytypes, 4H-SiC continues to lead the field due to the availability of high-purity material and well-established fabrication protocols. Nonetheless, the potential of other polytypes, such as 3C-SiC and 6H-SiC, remains largely untapped. These materials present unique properties and opportunities that warrant further investigation, as they may offer alternative pathways for the development of scalable quantum technologies. In the ongoing search for promising defect candidates, machine learning (ML) and artificial intelligence (AI) tools are expected to play a significant role.  
This research received no external funding.  
The data are contained within the article.  
The author declares no conflicts of interest.
## 2 Designed Methodology
### Stage 2: BESS Integration and EMS Optimization  
#### 2.8.1 BESS Integration and Modelling  
According to the literature [4; 7; 21; 22], installing a BESS is very useful for EVCS micro-grid systems. The degradation of BESSs has an important influence on the total cost of the operation [20; 21], and the BESS constraints have to be considered by the EMSs. Thus, the BESS is modelled in order to represent the mentioned constraints and degradation.  
Electric Model  
A battery is usually characterized by the open-circuit voltage of the battery pack, and the internal resistance of the battery pack. Using these parameters and knowing the power  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Parameter** & **Value** \\ \hline \(P_{cP}\) & 0.85 \\ \(P_{cSOC}\) & 0.85 \\ \(P_{mP}\) & 0.01 \\ \(P_{mSOC}\) & 0.01 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Evolution probability parameters for the charging schedule optimizer GA.  
of the BESS (given by the EMS), the current of the BESS, \(I_{BESS}\), can be calculated as in Equation (5), taken from article [25]:  
\[I_{BESS}=\frac{U_{BESS}(\text{SOC})-\sqrt{U_{BESS}^{2}(\text{SOC})-4\cdot P_{ BESS}\cdot R_{BESS}(\text{SOC})\cdot(-sign(P_{BESS}))}}{2\cdot R_{BESS}(SOC)} \tag{5}\]  
where \(U_{BESS}\) is the open-circuit voltage of the battery pack, \(R_{BESS}\) is the internal resistance of the battery pack, and \(P_{BESS}\) is the power output of the battery pack. Then, the battery SOC is obtained by using the coulomb counting method represented in Equation (6) [25]:  
\[SOC_{BESS}(k)=SOC_{BESS}(k-1)-\frac{I_{BESS}(k-1)\cdot\Delta t}{C_{BESS0}} \tag{6}\]  
where \(\Delta t\) is the time step of 15 min between the actual and previous states of charge, \(C_{BESS0}\) is the initial capacity of the battery in Ah, and \(k\) is the actual time step.