esa-sceva/satcom-chunk-collection huggingface dataset:
# A Medical Image Encryption Scheme for Secure Fingerprint-Based Authenticated Transmission
## 1 Introduction
Subsequently, the reference image has been recreated along with an encrypted singular value vector and encrypted fingerprint feature vector through the 2D-Inverse Discrete Wavelet Transform (2D-IDWT) to obtain the final watermarked image, which is a visually meaningful encrypted image. Finally, the EHR has been embedded in the final watermarked image through the Least Significant Bit (LSB) algorithm, which is a steganography technique commonly used to directly encode the information in the host image [19]. The main research contributions of the proposed visually image encryption scheme are described below. * Ensure the visual security of medical image transmission through a watermarking process. * Protect the medical image and the physician's fingerprint through an encryption scheme to make the proposed scheme resistant to white-box attacks. * Ensure the medical image's authenticity using the physician's fingerprint. * Perform a proposed scheme simulation to evaluate the quality of the reconstructed medical image, the quality of the watermarking, and the accuracy of the reconstructed fingerprint feature in terms of peak signal-to-noise ratio (PSNR), mean structural similarity index measure (MSSIM), distance of histogram intersection, and the relative error. * Perform a critical security analysis to evaluate the resistance of the proposed scheme to brute-force attacks. * Compare the proposed scheme's performance with other visual encryption schemes to validate its effectiveness. The paper is organized as follows: Section 2 introduces the related works and their limits; Section 3 describes the proposed scheme; Section 4 analyzes the quality performance of the proposed scheme; and Section 5 gives the conclusions and future developments.
# New Space Engineering Design: Characterization of Key Drivers
## 3 Results and Discussion
### Discussion per Application Domains  
Following the last step of the research methodology in Figure 1, this section contextualizes the identified design drivers and enablers within representative New Space application scenarios, demonstrating their practical relevance in real-world settings.  
Table 3 summarizes the three application domains discussed in the following sections.  
\begin{table}
\begin{tabular}{c} \hline
**Application Domains** \\ \hline LEO constellations of small satellites \\ Operations and servicing in space \\ Space exploration \\ \hline \end{tabular}
\end{table}
Table 3: Relevant application domains of New Space.
###### Abstract  
Transmission lines are usually located outdoors and are subjected to wind loads year-round. When a fire occurs, transmission towers are exposed to the combined effects of fire and wind loads. This paper investigates the impact of high temperatures on the bearing capacity of transmission tower-line systems under wind load and explores the effects of uneven horizontal spacing distribution and changes in the elevation of the target tower on the bearing capacity of the tower-line system. The failure criteria for transmission tower components at high temperatures were determined by considering the constitutive relationship of steel at ambient temperature and the variation patterns in material strength and elastic modulus with temperature. A finite element model of the transmission tower-line system was established using ABAQUS (2023). This paper studied the effects of temperature, uneven horizontal spacing distribution, and changes in the elevation of the target tower on the response of the transmission tower-line system by comparing collapse-resisting wind speeds and collapse processes under various conditions. The research indicates that the load-bearing capacity of the transmission tower-line system decreases as temperature increases. When the temperature exceeds 400 \({}^{\circ}\)C, the collapse-resisting wind speed of the transmission tower drops sharply. At temperatures above 600 \({}^{\circ}\)C, the transmission tower may collapse even at the annual average wind speed. In addition, the uneven horizontal spacing distribution and changes in the elevation of the target tower have an adverse effect on the stability of the transmission tower-line system. It is recommended to choose steel materials with higher fire resistance or apply fire-resistant coatings to existing steel, and to avoid extremely uneven spacing distributions and excessively high target tower elevations.  
transmission tower-line system; fire; multi-hazard; collapse-resisting wind speed Article
## 4 Results and Discussion  
### Partition LSF Walls  
Regarding the partition LSF walls, Figure 6 displays the surface-to-surface or conductive thermal resistances (\(R_{\text{cond}}\)) computed for several external surface thermal resistances (\(R_{\text{se}}\)) within the range of 0.0-0.20 m\({}^{2}\)-K/W, making use of the four evaluated FEM computational tools.  
Figure 5: Measured heat flux values and surface temperatures over time when sensors are located at the highest height (see Figure 4b) for the LSF facade: (**a**) Sensor position 1, near the steel stud. (**b**) Sensor position 2, in the middle of the wall cavity.  
Figure 6: Partition LSF wall: conductive thermal resistances (\(R_{\text{cond}}\)) for different external surface thermal resistances (\(R_{\text{se}}\)) and their percentage variation, computed using (**a**) THERM, (**b**) FLIXO, (**c**) PSIPLAN, and (**d**) ANSYS.  
As expected, the lowest \(R_{\text{cond}}\) value is provided for the smaller \(R_{\text{se}}\), i.e., assuming a null value. Regarding the THERM software (Figure 6a), the computed surface-to-surface thermal resistance is 1.5237 m\({}^{2}\cdot\)K/W. When the \(R_{\text{se}}\) value is increased up to 0.20 m\({}^{2}\cdot\)K/W, there is also a non-linear increase in the \(R_{\text{cond}}\) value (greater increment for smaller \(R_{\text{se}}\) values), reaching a maximum value of 1.6467 m\({}^{2}\cdot\)K/W, which corresponds to an increase of +0.123 m\({}^{2}\cdot\)K/W (+8.1%). Notice that for the other evaluated computational tools, i.e., FLIXO (Figure 6b), PSIPLAN (Figure 6c) and ANSYS (Figure 6d), the trend is very similar, as are the computed values.  
To better visualize and compare the results for the several tested FEM computational tools, Figure 7 displays all the obtained \(R_{\text{cond}}\) values in a single plot, as well as the averaged computed values for each external surface thermal resistance value. This graph makes it clearer that the thermal resistances computed by THERM, PSIPLAN and ANSYS are very similar, while the ones provided by the FLIXO algorithm are slightly smaller.  
Looking now at the averaged \(R_{\text{cond}}\) values, the trend is very similar to the one previously observed in Figure 6, i.e., there is a non-linear increase ranging from the minimum (1.520 m\({}^{2}\cdot\)K/W) up to a maximum conductive thermal resistance of 1.643 m\({}^{2}\cdot\)K/W, corresponding to an increase of +0.123 m\({}^{2}\cdot\)K/W (+8.1%). Notice that these average thermal resistance increments (absolute and percentage) are the same as those previously observed and discussed in relation to the THERM software (Figure 6a).
# Distributed Energy Sharing for PVT-HP Prosumers in Community Energy Internet: A Consensus Approach
## 3 Basic Knowledge of Consensus Algorithm
### Graph Theory  
Consider a CEI with \(N\) PVT-HP prosumers, a CHP operator and utility grid. A directed connected graph \(G=\{V,E\}\) is used to represent the communication topology of the CEI, where \(V\) is the node set and \(E\subset\{V\times V\}\) is the edge set. The prosumers set, CHP operator set and utility grid set are expressed as \(V_{P}\), \(V_{CHP}\) and \(V_{G}\), respectively. A directed edge from \(i\) to \(j\) is denoted by an ordered pair \((i,j)\in E\), which means that if and only if (iff) node \(j\) can receive messages from node \(i\). The in-neighbors of the \(i\)th node is denoted by \(N_{i}^{+}=\{j\in V|(j,i)\in E\}\) and \(|N_{i}^{+}|\) is the cardinality of in-neighbor set of node \(i\). Similarly, the out-neighbors of the \(i\)th node is denoted by \(N_{i}^{-}=\{j\in V|(i,j)\in E\}\) and  
Figure 1: Structure of Community Energy Internet (CEI) with photovoltaic-thermal and heat pump (PVT-HP) prosumers.  
\(|N_{i}^{-}|\) is the cardinality of out-neighbor set of node \(i\). Since it is obvious that node \(i\) can obtain its own state information, each node belongs to both its in-neighbor and out-neighbor set, i.e., \(i\in N_{i}^{+}\) as well as \(i\in N_{i}^{-}\)[24]. It is worth noting that the communication network is strongly connected, i.e., any two nodes have directed path between them.
# Soriasis--A Cancer Risk Factor?
## 3 Results
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Cancer Types \({}^{*}\)**} & **Psoriasis** &
\begin{tabular}{c} **Other Dermatoses** \\ \end{tabular} & **Chi2 Test** & **Odd Ratio** & \multicolumn{2}{c}{**Relative Risk**} \\ \cline{2-9}  & _n (\%)_ & _n (\%)_ & \(p\) & **OR** & **95\%CI** & **RR** & **95\%CI** \\ \hline CNS & 3 (7.5\%) & 2 (0.5\%) & 0.001 & 16.09 & 2.61–99.4 & 15.0 & 2.58–86.9 \\ Upper aerodigestive & 4 (10.0\%) & 9 (2.3\%) & 0.006 & 4.81 & 1.41–16.41 & 4.43 & 1.43–13.75 \\ Endocrine & 3 (7.5\%) & 10 (2.5\%) & 0.076 & 3.15 & 0.83–11.97 & 2.99 & 0.86–10.43 \\ Bladder & 3 (7.5\%) & 10 (2.5\%) & 0.076 & 3.15 & 0.83–11.97 & 2.99 & 0.86–10.43 \\ Lung & 3 (7.5\%) & 12 (3.0\%) & 0.136 & 2.61 & 0.71–9.68 & 2.49 & 0.73–8.47 \\ Prostate & 3 (7.5\%) & 21 (5.3\%) & 0.351 & 1.46 & 0.42–5.12 & 1.43 & 0.44–4.57 \\ Breast & 4 (10.0\%) & 29 (7.3\%) & 0.533 & 1.42 & 0.47–4.26 & 1.38 & 0.51–3.72 \\ Colorectal & 5 (12.5\%) & 40 (10.0\%) & 0.242 & 1.28 & 0.48–3.46 & 1.25 & 0.52–9.98 \\ Cervical & 2 (5.0\%) & 16 (4.0\%) & 0.764 & 1.26 & 0.28–5.69 & 1.25 & 0.30–5.23 \\ Liver & 1 (2.5\%) & 8 (2.0\%) & 0.833 & 1.25 & 0.15–10.28 & 1.25 & 0.16–9.72 \\ Blood & 5 (12.5\%) & 58 (14.5\%) & 0.726 & 0.90 & 0.34–2.38 & 0.86 & 0.37–2.02 \\ Cutaneous lymphomas & 2 (5.0\%) & 41 (10.3\%) & 0.285 & 0.46 & 0.11–1.98 & 0.49 & 0.12–1.94 \\ Melanomas & 1 (2.5\%) & 53 (9.8\%) & 0.048 & 0.17 & 0.002–1.29 & 0.19 & 0.03–1.32 \\ Kaposi sarcoma & 1 (2.5\%) & 57 (14.3\%) & 0.036 & 0.15 & 0.002–1.14 & 0.18 & 0.02–1.23 \\ \hline \hline \end{tabular} \({}^{*}\) Only the cancer types detected in both study groups were included.  
\end{table} 
Table 2: Association of psoriasis with some cancer types.
# Road Crash Analysis and Modeling: A Systematic Review of Methods, Data, and Emerging Technologies
## Appendix A PRISMA 2020 Checklist  
This appendix provides a detailed assessment of how our systematic review addresses each item in the PRISMA 2020 checklist for systematic reviews and meta-analyses.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Item** & **PRISMA Element** & **Status** & **Location/Comments** \\ \hline
1 & Title & ✓ & Document title clearly identifies this as a systematic review: “Road Crash Analysis and Modeling: A Systematic Review of Methods, Data, and Emerging Technologies” \\
**ABSTRACT** & & & \\ \hline
2 & Abstract & ✓ & Abstract Section includes background, objectives, data sources, study selection criteria, data extraction, synthesis methods, results, limitations, conclusions, and funding statement \\
**INTRODUCTION** & & & \\ \hline
3 & Rationale & ✓ & Section 1, “Introduction”, and Sections 1.1 and 1.2. Describes importance of crash data analysis, gaps between research and practice, and need for comprehensive methodological review \\
4 & Objectives & ✓ & Section 1.2, “Scope and Objectives”. Clear statement to “systematically examine established and emerging analytical approaches” with dual purposes outlined \\
**METHODOS** & & & \\ \hline
5 & Eligibility criteria & ✓ & Section 2.1, “Eligibility Criteria”. Clear inclusion/exclusion criteria for studies with methodological contributions \\
6 & Information sources & ✓ & Section 2.2, “Information Sources and Search Strategy”. Google Scholar as primary source, citation searching, and rationale for database selection \\
7 & Search strategy & ✓ & Section 2.2. Lists search terms. \\
8 & Selection process & ✓ & Section 2.3, “Selection Process and Data Collection” + PRISMA flow diagram. Clear description of screening process \\
9 & Data collection process & ✓ & Sections 2.3 and 2.4. Description of data extraction focusing on methodological characteristics \\  & & & Section 2.4, “Data Items and Study Characteristics”. Lists extracted elements: methodological approaches, data sources, and performance metrics \\
11 & Study risk of bias assessment & ✓ & Section 2.5, “Risk of Bias Assessment”. Adapted quality assessment for methodological research \\
12 & Effect measures & \(\circ\) & Not applicable for methodological review that does not meta-analyze effect sizes \\
13 & Synthesis methods & ✓ & Section 2.6, “Synthesis Methods”. Description of qualitative and quantitative synthesis approaches \\
14 & Reporting bias assessment & \(\circ\) & Limited applicability for methodological reviews \\
15 & Certainty assessment & & Section 2.7 “Assessment of Evidence Quality”. Adapted approach for methodological research \\ \hline \hline \end{tabular}
\end{table}
Table 10: PRISMA 2020 checklist assessment for road crash analysis systematic review.
## 3 MWD Positioning Method Based on Dual-Electrode Current Excitation
### Analysis of the Current Proportion in the Target Well Casing  
It is assumed that the length of the upper/lower electrodes is similar to the radius of the borehole in the model, and it is equivalent to the \(P_{u}\) point and \(P_{d}\) point in the formation. The excitation current forms a loop between points \(P_{u}\) and \(P_{d}\). Since the ranging tool between points \(P_{u}\) and \(P_{d}\) is wrapped or coated with insulation material externally and equipped with the insulation sub internally, the total load impedance of the current source output current between electrodes \(P_{u}\) and \(P_{d}\) is composed of three equivalent resistors in parallel, namely, the formation equivalent resistance (\(R_{el}\)), the mud equivalent resistance in the outer annulus of the drilling tool (\(R_{em}\)), and the target well casing loop equivalent resistance (\(R_{ec}\)). The \(R_{ec}\) is composed serially of an equivalent formation resistance from the upper electrode to the casing, the casing internal resistance, and an equivalent formation resistance from the lower electrode to the casing. The casing current strength equals the current amplitude flowing over \(R_{ec}\).  
In the case of uniform formation (where the electrical conductivity of a single geological structure is unchanged) and regular borehole comparison (where the casing resistance is relatively easy to calculate), the equivalent resistance is calculated as follows.  
\[\left\{\begin{array}{l}R_{ef}\approx\frac{R_{f}}{2\pi}\frac{L-2r_{d}}{r_{d}}\\ R_{em}\approx\frac{R_{e}L}{\pi(r_{d}^{2}-r_{t}^{2})}\\ R_{ec}\approx\frac{R_{f}}{2\pi}\left(\frac{d+L\cdot\sin(\theta)/2-2r_{d}}{(d+L \cdot\sin(\theta)/2)\cdot r_{d}}+\frac{d-L\cdot\sin(\theta)/2-2r_{d}}{(d-L \cdot\sin(\theta)/2)\cdot r_{d}}\right)+\frac{L\cdot\cos(\theta)}{2\pi r_{c}h_{c }c_{c}}\end{array}\right. \tag{2}\]  
In the formula, \(R_{f}\) represents the formation resistivity, \(\Omega\cdot\)m; \(\sigma_{c}\) is the conductivity of the casing, S/m; \(R_{m}\) stands for mud resistivity, \(\Omega\cdot\)m; \(r_{d}\) denotes the borehole radius of the drilling well, m; \(r_{t}\) is the radius of the drilling well ranging tool, m; \(r_{c}\) indicates the casing radius of the target well, m; and \(h_{c}\) represents the casing wall thickness, m.  
As part of the excitation current is returned through the mud channel and the near-borehole formation reflux, according to [PERSON]'s law and the current shunt calculation method involving three equivalent resistors in parallel, combined with Equation (2), the current attenuation factor \(k_{c}\) of the output current strength \(I_{s}\) of the current source can be obtained to eliminate the influence of the mud channel and formation shunt. The calculation in Formula (3) is as follows:  
\[k_{c}=\left(R_{ef}\|R_{em}\right)/\left(R_{ef}\|R_{em}+R_{ec}\right) \tag{3}\]  
As shown in Equation (3), the range of \(k_{c}\) values is [0, 1]. The lower \(k_{c}\) value results in more current shunting from the mud channel and the formation near the borehole, leading to a decrease in the casing current.
## 3 Material Systems
Various alignment techniques enable the achievement of oriented structures for enhanced or anisotropic optical properties, demonstrated in mechanically aligned polymer films showing polarized emission. Surface modification strategies prove essential for controlling interfacial properties, particularly in multilayer devices or hybrid systems, as shown in the use of polyelectrolyte layers to modify electrode interfaces in light-emitting devices [95,96]. The successful development of effective materials requires careful balancing of multiple factors. Optical performance requirements must be weighed against processing compatibility considerations, while environmental stability remains a crucial concern for practical applications. For instance, the development of air-stable blue-emitting polymers has required careful molecular design to prevent oxidation of fluorene units while maintaining high photoluminescence quantum yields. Cost considerations and scalability of both synthesis and fabrication processes play vital roles in determining commercial viability, as demonstrated by the industrial adoption of solution-processable light-emitting polymers in display applications. This complex interplay of factors necessitates an iterative approach to material development, where molecular design and processing strategies are continuously refined based on performance feedback and application requirements. The continued evolution of these design strategies, coupled with an improved understanding of structure-property relationships, enables increasingly sophisticated control over optical properties in polymer-based photonic materials.
## 3 Creep Compression Characteristics of Gagne Backfill Materials
### Analysis of Test Results  
Multi-stage creep compression tests were conducted on gangue backfill materials (Figure 4a). The creep test data were processed using [PERSON]'s method [36; 37], thus attaining the creep compression curve clusters of gangue backfill materials (Figure 4b).  
Analysis of Figure 4 shows the creep curves of specimens of gangue backfill materials at each applied stress include instantaneous deformation, attenuated creep deformation, and steady creep deformation. At a low applied stress, the deformation rate of creep curves begins to attenuate after experiencing instantaneous deformation, and then, after a period  
Figure 4: Deformation curves of gangue backfill materials in creep compression tests: (**a**) multi-stage loading curves, (**b**) creep compression curve clusters.  
of time, the specimens enter a steady creep stage at a rate of zero, whereafter the creep deformation does not change any longer. At a high stress, the creep rate of creep curves begins to attenuate after experiencing instantaneous deformation. In time, the curves also enter the steady creep stage at a non-zero rate (i.e., low rate and small deformation).  
As the applied load increases, the instantaneous strain and creep strain in specimens both increase gradually. As the loading stress increases from 5 MPa to 10, 15, and 20 MPa, the instantaneous strain of gangue backfill materials grows to 1.56, 1.91, and 2.17 times the original value, and the creep strain rises to 2.37, 3.67, and 4.96 times the original value.
# Assessment of Interventions in Fuel Management Zones Using Remote Sensing
## 1 Introduction
This approach can be used to analyze any FMZ type that roughly follows the specifications, dimensions, shape, and purpose; (2) a set of software tools that given the vector information about the FMZs and a set of satellite images can extract metrics from the time- series patterns, and estimate if the FMZs was or not maintained properly with a high degree of accuracy. This paper is organized as follows: Section 2 describes the experimental processing pipeline, showing how the data was acquired and processed, how the FMZs were clustered, and how the data sets were created. Section 3 shows and compares the results by pairing multiple algorithms with different data sets. Finally, Sections 4 and 5 presents the discussion and conclusions.
# Investigating the Effect of Motion Capture Suits on the Test-Retest Reliability of Gait Parameters
## 2 Materials and Methods
### Protocol  
Participants were asked to walk on a Motek R mill m-gait dual-belt instrumented treadmill [12] for 120 s at a set velocity of 1.5 m/s. Treadmill walking was chosen to allow for the collection of multiple gait cycles as opposed to collecting overground walking, which heavily restricts the number of gait cycles we can measure.  
Participants completed 6 walking trials, during which markers were placed either in suited or unsuited conditions (three of each). The MOCAP suit given to each participant was of the appropriate size to ensure proper fitting and all participants were checked by the researcher to ensure proper fitting of the suit. The order of suited or non-suited trials was randomised. Static calibration trials lasting 10 s were captured before each walking trial with participants holding their arms up in a t-pose.  
Markers were placed on their body according to the CGM2.3 model, with 55 markers either attached onto their skin (non-suited) or onto a Velcro suit (suited), with placement dictated by Vicon documentation [13]. The non-suited condition required participants to wear shorts and a skin-tight top. The suited condition required participants to wear both halves of an Optitrack MOCAP suit and slippers (NaturalPoint, Inc., Corvallis, OR, USA) in sizes best fitting the participant. Participants were checked to ensure the suit was worn properly by the researcher. Trainers were worn during all trials. Data were captured using a 12 camera Qualisys Miqus M3 system (200 Hz) [14]. Before and after each trial, markers were placed and removed. Rest periods were provided in order for any skin blemish from previous markers to fade. One researcher with \(\sim\)2 years of MOCAP marking experience attached markers to the participants.