esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Datasets and Evaluation Metrics
### HDR Image Quality Assessment  
HDR images can represent a significantly wider range of luminance and contrast compared to traditional LDR formats. This has driven much research in HDR processing, such as acquisition/generation [43], compression [90; 91], and quality assessment [92]. Image quality assessment is crucial for the development and comparison of algorithms, and the metrics used can be divided into Full-Reference (FR), which require the complete original image; No-Reference (NR), which do not require any reference; and Partial-Reference (PR) or Reduced-Reference (RR), which use a subset of information from the reference. Even so, it is difficult to apply metrics originally designed for LDR to HDR images, as they need to be revised or adapted [93]. The literature includes studies on metrics designed for the HDR, including [94], which provides a comprehensive comparison of multiple metrics; ref. [82], which subjectively evaluates the quality of reconstructions from a single image; and ref. [93], which discusses the performance of full-reference (FR) metrics in HDR scenarios. The following topics present relevant metrics in the HDR reconstruction scenario separated into two basic categories: metrics exclusive to HDR and LDR metrics that can be applied to HDR images.  
Table 2 summarizes the metric information that has been described in this section.
## 2 Materials and Methods
### Feature Ranking Algorithms  
After extracting the features, all features are not equally important. The feature importance was computed using supervised feature ranking algorithms [40]. The feature importance ranking (FIR) algorithm was developed in MATLAB [41]. The importance of the computed features was measured using an empirical receiver operating characteristic (EROC) curve and a random classifier slope. The greater the ROC value indicate the more important feature.
# Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics
## 2 Methodology  
### Research Framework  
Considering that the identification of risk factors of ship navigation is subjective and the research on the transmission of risk factors is still scarce in the current research, this paper proposes a new method to quantitatively analyze the risk factors of ship navigation in traffic-intensive waters and the transmission process of key risk factors by combining the cloud model, entropy weight method, and infectious disease dynamics.  
Figure 1 shows the technical route of causal analysis of risks in ship navigation systems in traffic-intensive waters, which consisted of two major steps. In the first step, the cloud model and entropy weight method were used to identify the key factors affecting the risk of navigation systems. The cloud model [34] is especially suitable for complex systems with uncertainty, complexity, and randomness, while the entropy weight method [35] is able to order the parameters in a ship navigation system. The construction of the model is as follows: Firstly, based on the analysis of the characteristics in traffic-intensive waters, risk index systems of ship navigation in traffic-intensive waters was proposed, and then the risk factor data were collected. Moreover, the cloud model was used to mine the risk characteristic parameters of the ship navigation system, and the key factors affecting the risk of ship navigation were selected. Through analyzing the key data by using the entropy method, the correlation data of the risk of ship navigation was obtained. After that, the corresponding correlation values were obtained by sorting the associated data. Finally, the key factors affecting the safety of ship navigation can be determined.  
In the second step, the transmission of key risk factors of the ship navigation system was described by using the infectious disease dynamics method. The construction of the model is as follows: Firstly, the membership sequence of risk index was substituted. Based on that, susceptible node, exposed node, infective node, and removal node were introduced into the analysis process of risk causes transmission according to the dynamic mechanism of infectious diseases. Finally, the risk causes transmission analysis model was constructed.  
Figure 1: Flowchart of causal analysis of risks of ship navigation systems in traffic-intensive waters.
## 2 Materials and Methods
### Networks Similarity Cutoff Analysis  
The optimal similarity threshold for the HSPN was set up by analyzing the network parameters/topology behavior at varying the pairwise similarity cutoffs between nodes (peptides). HSPNs representing the ABFPs were built with the Euclidean distance metric, but changing similarity threshold from 0 (no cutoff) to 0.95. The exploration was performed from the minimum cutoff 0, where all possible similarity relationships (edges) are displayed, increasing to 0.3, 0.4, etc. until 0.95; only edges with similarity values higher than the applied threshold are shown in the network.  
The resulting HSPNs at each similarity cutoff are exported as GraphML files from StarPep toolbox (v1.0-zip distribution) to be imported in Gephi v0.10 [38]. Gephi allows the calculation of a comprehensive set of network parameters not implemented in StarPep toolbox v1.0, such as average degree, density, modularity, average clustering coefficient (ACC), number of communities and singletons, network diameter, and average path length at each similarity threshold. The joint analysis of all these network properties together with the visual mining of the resulting network topologies was considered to determine the optimal value (File S1 of Supplementary Materials). The optimal cutoff should draw the most informative network topology that best represents/models the ABF chemical space. These exploratory analyses will be addressed in detail in the Results and Discussion sections.
## 5 Conclusions  
Additive manufacturing (AM) is a cost-effective and efficient method for producing durable components for hydrogen technology. This study evaluates the mechanical performance of additively manufactured 316L stainless steel in various processing conditions, including as-built, post-processed, and as-rolled for comparison, to assess its suitability for hydrogen technology.  
The study employed 316L stainless steel specimens as electrodes in a water electrolysis cell for oxyhydrogen gas production. The key findings showed that AM 316L stainless steel electrodes produced a higher HHO gas flow rate compared to as-rolled electrodes, with the highest production rate observed in post-processed heat-treated (PPHT) electrodes. PPHT electrodes significantly improved HHO gas production efficiency, achieving values between 62.11% and 63.63%.  
The study also evaluated the performance of AM 316L stainless steel for hydrogen storage applications by assessing hydrogen embrittlement indicators based on the loss of elongation at fracture and Charpy impact toughness with and without electrochemical hydrogen charging. The specimens were tested under various conditions, including room and cryogenic temperatures. The key findings showed that AM 316L stainless steel showed higher resistance to hydrogen embrittlement compared to as-rolled material. The HT2 specimens with the best resistance at room temperature were suitable for manufacturing pressure vessels for hydrogen gas storage, while HT1 specimens with the highest resistance at cryogenic temperatures were ideal for liquid and cryo-compressed hydrogen storage.  
The final section of this investigation involved determining the burst pressure of a Type 1 pressure vessel constructed from as-built AM 316L stainless steel using finite element analysis (FEA) with ANSYS Workbench. Using the findings of experimental mechanical testing, the analysis estimated a burst pressure of 81 MPa using the explicit dynamic module and 70 MPa using the static structural module. These results demonstrate additive manufacturing's great potential for creating metallic pressure vessels with outstanding performance.  
Conceptualization, R.R. and S.A.; Project administration, R.R.; Methodology, R.R., M.A., K.S., S.M., G.E. and Y.G.Y.E.; Investigation, R.R., M.A., K.S.; Software, M.A. and K.S.; Validation, M.A. and K.S.; Formal analysis, S.M. and G.E.; Resources, R.K. and Y.G.Y.E.; Writing--original draft, M.A., K.S., S.M. and G.E.; Writing--review & editing, R.R.; Supervision, S.A.; Visualization,S.A., S.M. and R.K.; Funding acquisition, S.A. All authors have read and agreed to the published version of the manuscript.  
This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP2503).  
Not applicable.  
The data presented in this study are available on request from the corresponding authors.  
The authors declare no conflicts of interest.
# Numerical Study on Cooling Performance of a Steam-Cooled Blade Based on Response Surface Method
## 1 Introduction
[17] performed a comprehensive response analysis and sensitivity analysis of the cooling performance of a gas turbine based on deep learning data modelling, and the results showed that the model can provide accurate predictions and had a fast response time. In addition, in the cooling of turbine blades at high temperatures, steam has better advantages over air due to its better heat transfer properties [18; 19]. [PERSON] et al. [20] showed that better internal cooling performance of gas turbine blade can be obtained using steam cooling compared to air cooling. [PERSON] et al. [21] comparatively studied the cooling performance of blades under three cooling schemes (open-circuit steam, air and closed-circuit steam cooling) and showed that steam cooling has higher cooling efficiency compared to air cooling. The above literature shows that response surface models can be used to predict the cooling performance of turbine blades well and that steam has better cooling efficiency than air, but very little literature has explored the effect of steam-cooled blade operating parameters on its cooling performance. In this paper, in order to refine the steam-cooled blade with five internal cooling channels, the blade cooling system was considered as a complex system, and the system can be precisely adjusted by changing the parameters such as mainstream inlet temperature, mainstream outlet pressure, mainstream inlet to outlet pressure ratio, temperature ratio and flow rate ratio of cold gas to mainstream. Secondly, most of the existing studies in the investigation of the cooling performance of the blade, most of the evaluation indexes used only cooling efficiency. While in this paper, in order to explore the cooling performance of the blade in more detail, adding the index that can visually reflect the cooling effect of the turbine blade--dimensionless temperature and the index that can reflect the cooling uniformity of the turbine blade--temperature non-uniformity. Therefore, in this paper, based on the combination of experimental design and response surface modeling, the flow-solid conjugate heat transfer method was used to numerically study the steam-cooled high-temperature turbine blade, and the distribution rules of the cooling efficiency, dimensionless temperature and temperature non-uniformity of the steam-cooled blade under different inlet temperature of the mainstream, mainstream outlet pressure, pressure ratio of the mainstream inlet to outlet, temperature ratio and flow ratio of steam to mainstream were investigated. The difference of cooling performance between the steam-cooled blade and the air-cooled blade under different working parameters was investigated, and the empirical equation of the cooling performance of the steam-cooled blade was obtained by fitting the response surface model, based on which the significance of the effect of working parameters on the cooling performance of the steam-cooled blade was also investigated.
## 6 Conclusions and Future Work
### Conclusions  
In conclusion, we propose a novel matrix profile algorithm for time series subsequence all-pairs similarity search. The proposed novel matrix profile is obtained in three phases. In the beginning, we preprocess and represent data sets by preventing time series issues such as amplitude, scaling, temporal warping, noise, and outliers. Then, we go through the distance determination process for neighboring nodes using the z-normalized Euclidean distance method. The last phase consists of the immediate neighbor detection process used to determine the values required for the matrix profile index. The NMP has good qualities such as simplicity, high speed, parallelizability, and a lack of parameters. Another advantage is its accuracy. The last expression is used to calculate the accuracy values. The accuracy of using NMP is 99.5% with a maximum time series length. Additionally, the run-time execution for the NMP algorithm is computed, and the time required for the novel matrix profile is compared to that of other existing state-of-the-art algorithms. The results show that the proposed NMP is the best choice for solving the all-pairs similarity search problem. Additionally, we show that our algorithm has implications for many current tasks, such as motif discovery, discord discovery, shapelet discovery, and semantic segmentation, and new pathways can be opened up for science, including computing various definitions of time series set differences.
## 2 Theoretical Background
### Virtual Knowledge Graph Mapping and Tooling Ecosystem  
By supporting the entire life cycle of the VKG approach, various data integration systems or tools have been developed, implemented, and used by the [PERSON] report [8]. We classified these integrated systems to support virtualization into four groups: (i) integrated systems that utilize query reformulation to answer _SPARQL_[44] queries over VKGs; (ii) mapping engineering tools such as _PROMPT_[45] for assisting mapping design; (iii) federations for accessing federated queries across several data sources; iv) query formulations tools to facilitate interaction with VKGs [4; 29]. In recent times, numerous VKGs query answering systems have been developed in academia and industry [4], such as _D2 RQ_[46], Mastro [18], Morph [47], Ontop [48], Oracle Spatial and Graph [49], Startdog [50], and Ultrawrap [51]. Utilizing these query and response systems facilitates data virtualization by industry standards and query optimization, both critical for delivering high speeds [29].  
According to the practitioner's observations [4], ontologies and mapping are key classifications for developing complex artifacts, which are fundamental components of VKG systems, leading to developing domain-centric AI-powered applications (e.g., conversational agents, semantic search engines, recommended systems) in various fields. Based on these classifications and detailed analyses of how mapping techniques are represented, several mapping editors are employed, categorized as text and graphical editors [4]. Text editors handle the textual representation of mapping, typically based on R2 RML [52] or an alternative system [29]. These text editors are often integrated into ontology editors like Protege or used independently, such as in the IDE Stardog Studio. In graphical editors, users define mappings by linking database schema columns with characteristics, properties, and classes from the ontology vocabulary. Notable graphical editors in this category include Map-On [53], MapVOWL [54], RMLEditor [55], and SQuaRE [29; 56].
# Development of an L-Band SAR Microsatellite Antenna for Earth Observation
## 3 Antenna Gain Estimation
### Effect of Ribs  
Next, losses regarding the effect of ribs and subsequent quasi-parabolic surface are estimated using the microstrip antenna as feed element. The reflector has supporting ribs that are parabolic in shape and wire mesh stretched between them; that means that the surface between two ribs is a quasi-parabolic area. This gore shape causes phase error loss and their periodicity produces extra sidelobes. Consequently, the focal point of the parabola becomes a spread focal region, within which the feed position has to be optimized [17]. The new feed location that minimizes peak gain loss is at \(+1.5\) cm from the focal point after optimization. Equation (7) calculates the minimum number of gores \(N_{G}\) for a given antenna diameter \(D\), _f/D_ ratio, wavelength \(\lambda\), and peak-to-peak phase deviation \(\delta\) across the gore. As the number of ribs increases, phase error losses decrease, as the surface becomes closer to a perfect paraboloid. For the current parabolic configuration, using a \(10\)-dB taper feed, at least \(11\) ribs are needed to keep gore losses below \(0.5\) dB.  
\[N_{G}=\sqrt{\frac{800-500(\frac{f}{D}-0.4)}{\delta}\frac{D}{\lambda}} \tag{7}\]  
When accounting other factors than antenna losses, such as mechanical stability, risk of deployment failure and stowage space, \(24\) supporting ribs were estimated necessary. After simulating the antenna pattern accounting ribs and gore surface, there was no significant impact on the shape of the main pattern, with peak losses of \(\eta_{gore}=0.63\) dBic and a slight increase in the sidelobes to \(-19.2\) dB.
## 3 Control Design
### Proposed Control
#### 3.2.2 Adaptive Sliding Mode Control with a Backstepping Technique Based on RBFNN (ABSMC)  
The virtual control (14) is represented as follows:  
\[x_{3d}=J(x_{1})^{-1}\bigg{(}C(x_{1},x_{2})x_{2s}+G(x_{1})+M_{0}(x_{1})\dot{x}_ {2s}-K_{1}s_{1}+\hat{D}_{1}-\eta_{1}\text{tanh}\bigg{(}\frac{s_{1}}{\psi_{1}} \bigg{)}\bigg{)} \tag{33}\]  
Additionally, the control input (21) is also rewritten as follows:  
\[U={F_{2}}^{-1}(x)\bigg{(}\dot{x}_{3d}-F_{1}(x)-K_{2}s_{2}-\lambda_{2}e_{3}-s_{1 }-\hat{D}_{2}-\eta_{2}\text{tanh}\bigg{(}\frac{s_{2}}{\psi_{2}}\bigg{)}\bigg{)} \tag{34}\]Then the Lyapunov function candidate is defined as  
\[V_{3}=V_{2}+\frac{1}{2}\left(\sum\limits_{i=1}^{2}trace\Big{(}\widetilde{W}_{i} ^{T}\Gamma_{1i}^{-1}\widetilde{W}_{i}\Big{)}+\widetilde{m}_{ei}^{T}\Gamma_{2i}^ {-1}\widetilde{m}_{ei}+\sum\limits_{i=1}^{2}\widetilde{\sigma}_{i}^{T}\Gamma_{3 i}^{-1}\widetilde{\sigma}_{i}\right) \tag{35}\]  
where \(\Gamma_{ij}\in R^{3n\times 3n},(i=1,\ldots,3,j=1,2)\) are positive definite matrices.  
**Assumption 2.**_The reconstructed errors, \(\phi_{i}=\widetilde{W}^{T}{}_{i}\mu_{m}\widetilde{m}+\widetilde{W}_{i}^{T}\mu_ {\sigma}\widetilde{\sigma}+{W_{i}}^{*T}v+\epsilon_{i},(i=1,2)\), in the mechanical dynamics and hydraulic dynamics are bounded by \(\left\|\phi_{i}\right\|_{1}<\hat{\eta}_{i}\)._  
**Theorem 1.**_The hydraulic manipulator is presented by (9), the indirect adaptive backstepping sliding mode control is designed by (33), (34), and the adaptive laws for the RBFNN parameters are chosen as (36)-(38) such that all the tracking error states (\(s_{1}\) and \(s_{2}\)) converge to zero in a finite time. The stability and robustness of the proposed control and the adaptive laws are guaranteed via the Lyapunov theory._  
\[\dot{\hat{W}}_{i}=tr\Big{(}\Gamma_{1i}\Big{(}(-1)^{i+1}\hat{\eta}_{i}s_{i}^{T}+ \Lambda_{1i}\ \mathrm{W}\ ^{\ast}\!\!  
where \(\kappa=\min\Bigl{(}\lambda_{\min}(\Xi),\lambda_{\min}\Bigl{(}M_{1}^{-1}K_{1}\Bigr{)},\lambda_{\min}(K_{2}),\lambda_{\min}\bigl{(}\Gamma_{\bar{\imath}}\Lambda_{\bar{ \imath}}\bigr{)}\Bigr{)}\), \((i=1,2,3,j=1,2)\) and \(C_{\varepsilon}=\frac{1}{2}(\phi_{i}-\eta_{i}sign(s_{i}))s_{i}+m_{ei}^{*T} \Lambda_{i}m^{*}{}_{ei}+\frac{1}{2}trace\bigl{(}W_{i}^{*T}\Lambda_{i}W^{*}{}_{ i}\bigr{)}+\frac{1}{2}\sigma_{i}^{*T}\Lambda_{i}\sigma_{i}^{*}\).  
From (41), and [34], we can conclude that the controlled system is ultimately uniformly bounded.
# New Insights on Mechanical Stimulation of Mesenchymal Stem Cells for Cartilage Regeneration
## 5 Conclusions  
Designing tissue engineering strategies for articular cartilage requires a thorough control of stem cell fate. The latter can be achieved through a more traditional approach using growth factors or, as suggested by the studies discussed above, by applying precise extrinsic mechanical loads, able to mimic the environment within the joint. Therefore, mechanical loading has been proposed as an alternative strategy to induce MSC chondrogenesis without the use of exogenous factors. Depending on the stimulus applied, promotion of specific tissue-related elements can be achieved. It can be concluded that shear stress and hydrostatic pressure, which exert their maximum effect on the superficial zone of the tissue, can increase type II collagen synthesis. Superimposed compression is, instead, the leading promoter of glycosaminoglycan production, since these components are directly involved in structural maintenance following perpendicular stresses. As a future prospective, functionalized bioengineering needs to take into account that de novo tissues should not lack the excellent organization of the cartilage that is critical for their role. A more in-depth study of the effects of different forces imposed on MSC cultures could represent a possible key to creating the original cartilage disposition with parallel collagen fibers in the superficial zone and perpendicular alignment in the thicker layer. Another aspect that should be investigated is the exact biomolecular mechanism by which the cells respond positively to friction and pressure. Tribology offers paramount principles to follow in order to understand and truly benefit the regenerative sciences.  
Conceptualization, S.R. and G.M.; writing--original draft preparation, S.R.; G.L.; writing--review and editing, M.A.S.; visualization, S.R.; supervision, G.M. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the University Research Project Grant (Triennial Research Plan 2016-2018), Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, Italy.  
The authors declare no conflict of interest.