esa-sceva/satcom-chunk-collection huggingface dataset:
# Positively Charged Lipid as Potential Tool to Influence the Fate of Ethosomes
## 3 Results and Discussion
### In Vitro Cytotoxicity Studies  
The in vitro bioassay was performed on human keratinocytes (NCTC-2544 cells) to investigate if the inclusion of DOTAP in ethosomal systems affected cell viability. It is well known that cationic lipids improve transfection [43] due to the increase in electrostatic interactions between cellular membranes and vesicles but it is noteworthy that this could influence cell viability. To further investigate this aspect, in vitro studies were performed.  
The non-differentiated keratinocytes cell line was chosen as a model, assuming a cutaneous topical administration of the realized samples. NCTC-2544 cells were treated with different vesicular formulations at increasing concentrations with reference to lipidic amounts (0.01, 0.1, 1.0 and 10.0 \(\upmu\)g/mL) for 24 h, 48 h and 72 h.  
As can be seen in Figure 4, all samples tested, i.e., conventional ethosomes, formulation D and formulation I, showed appropriate safety, thus indicating a good biocompatibility of the realized samples, with keratinocytes cells up to lipid concentrations of 10 \(\upmu\)g/mL, as the cell viability was found above 70% within 72 h.  
Figure 4: Evaluation of cytotoxicity of ethosomal systems on NCTC-2544 cells through MTT test after 24 h, 48 h and 72 h of treatment. Conventional ethosomes, formulation A (**a**), ethosomes made of PL90G:DOTAP 10:0.5 molar ratio, formulation I (**b**) and ethosomes PL90G:DOTAP 10:1 molar ratio, formulation D (**c**) have been used for this study. Results are expressed as the mean value of three different experiments \(\pm\) standard deviation. * \(p\) value < 0.05 with respect to control (untreated cells).  
Previous studies in the literature reported that cationic lipids with ester bonds in the linker zone, such in the case of DOTAP, showed less cytotoxic effects in cultured cells [44; 45; 46]. Surprisingly, in this study, cationic ethosomes made of DOTAP at a 10:0.5 molar ratio (Figure 4b) and 10:1 molar ratio (Figure 4c), not only showed low cytotoxic effects, but they also seemed to show great safety profiles on NCTC 2544 cells at 72 h until a lipid concentration of 1.0 ug/mL when compared to profiles recorded from conventional ethosomal samples (Figure 4a).
## 4 Discussion
However, our results and previous studies showed that different RFs are variably influenced by the variation in the CECT phase used to extract the RFs, as could be seen from the range of CCC values obtained; (iii) The dataset includes scans collected with different hardware and settings, which could also confound the effects of imaging phase on the RFs and the calculations of ComBat estimates. The lack of significant improvement despite using ComBat harmonization was also previously reported [17; 18; 19]. Our results add to the current evidence on the limited reproducibility of RFs across different scanning settings and strengthen the call for harmonization tools designed explicitly for the RFs. The other principal aim investigated in this study was to assess the impact of the imaging phase on the predictivity of RFs. For this aim, we investigated the ability to predict overall survival in RCC patients. Interestingly, there was no statistically significant difference between the non-contrast phase and arterial phase RF's predictive performances, while both significantly outperformed the predictions based on the late phase RFs. Repeating the analysis one thousand times ensured that we achieved a distribution representing the actual predictive ability [41]. Performing the analysis a single time could show one of the extreme end performances and would not represent the actual predictive performance. It also allows the identification of robust RFs in a given dataset. Predictions based on different imaging phase RFs were not similar, which indicates the inability to substitute imaging phases within a single radiomics study. RFs extracted from the arterial phase seem to have the highest predictive ability of overall survival in RCC lesions. While meticulous and comprehensive statistical methods were used in this study, several limitations remain. The number of available scans, especially for the survival analysis, was limited, which limits the generalizability of the findings. In addition, the patients were scanned in different medical centers using different imaging vendors and parameters, which could significantly affect the predictive performance of RFs. However, since the three phases for each patient were acquired using the same imaging parameters, the differences in the predictive performance across the different phases could be assumed robust. Future studies are recommended to include a more significant number of patients, with the addition of inter-scanner reproducibility analyses to assess the predictive ability of RFs in RCC patients accurately.
# A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications
###### Abstract  
The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions.  
Keywords:harmony search algorithm; meta-heuristic optimization algorithms; optimization problems; clustering applications +
Footnote †: journal: Applied Sciences
## 4 Discussion
Next, we discuss yet another key model simplification, namely the use of elastic microstresses for strength upscaling. During compressive loading tests, microcracks develop first in ITZs, which eventually bridge the inter-aggregate cement paste and lead to material failure [14]. Considering progressive stress redistributions due to progressive ITZ damage typically requires computationally quite expensive numerical simulations coupled with damage laws involving numerous parameters. Mean field homogenization-based micromechanical models are, up to this point, not able to incorporate non-homogeneous interface damage given the lack of analytical solutions of the corresponding matrix-inclusion problem--such solutions are currently only available for two-dimensional circular inclusions [48]. As an alternative, the proposed model and several of its predecessors [21; 30; 49], do quantify the ultimate strength of mortars and concretes based on elastic stresses obtained from micromechanics concentration relations referring to non-damaged microstructures. The question whether the such-obtained elastic microstresses allow for reasonable strength approximations can only be answered by comparing model predictions to independent experiments. Regarding conventional mortars and concretes, sufficient validation of the proposed strength model has been performed in [PERSON] et al. [21], such that the extension to recycled concretes seems credible. Finally, it is interesting to discuss model-predicted failure in case of symmetric biaxial compressive loading, with the corresponding macroscopic loading reading as \(\mathbf{\Sigma}=-\Sigma\left(\underline{\varepsilon}_{x}\otimes\underline{ \varepsilon}_{x}+\underline{\varepsilon}_{y}\otimes\underline{\varepsilon}_ {y}\right)\). Related model predicted biaxial compressive strengths, for the benchmark compositions, are by approximately 6% larger than the uniaxial compressive strength, since deviatoric stresses in critical hydrates slightly decrease and beneficial volumetric hydrate stresses slightly increase (see also [PERSON] et al. [30] for related discussions at cement paste level). While biaxial compressive strength results on recycled concrete are, to the authors' knowledge, not available in the literature, the magnitude of the predicted biaxial-to-uniaxial strength ratio falls well within experimentally observed intervals for conventional concrete [50]. Notably, the model does not qualify for discussing macroscopic tensile stress states, given that the hydrate failure criterion (1) with strength parameters (2) was designed, by [PERSON] and [PERSON] [37], to reproduce failure during _compressive_ nanoindentation tests.
## 3 The PFAC Measurements and the FRM Uncertainty Analysis
### Absolute Coordinates Constituent  
In the PFAC, a network of continuously operating GNSS stations distributed in western Crete and Gavdos (Figure 4) provides absolute geodetic coordinates and velocities for reference points at each Cal/Val site. According to FRM requirements, redundancy of the scientific equipment has to be ensured. This implies that at least two instruments should operate side by side to measure the same parameter to ensure that any potential errors and drifts in the operations are identified. For example, Table 2 presents the coordinates and velocities for the two GNSS receivers operating at the CDN1 transponder Cal/Val site (CDN0 and CDN2) and the two operating at the Gavdos sea-surface facility (GVD7 and GVD8). All sites have been processed using the GAMIT scientific software, which applies relative positioning techniques [25]. The reference epoch of these coordinates and velocities is 2013.5 and the geodetic frame used is the ITRF 2014. In order to assess the values for the ellipsoidal height for each pair of the GNSS receivers (i.e., the CDN0 with the CDN2 and the GVD7 with the GVD8) their antenna reference points have to be geodetically tied together but also connected to other reference control points in the vicinity. This task is achieved through precise leveling that provides height differences with uncertainty of the order of \(\pm 1\) mm. These levelling surveys are carried out on a semi-annual basis as well as during a major event (i.e., GNSS antenna replacement, earthquake, etc.). The derived uncertainty of GNSS processing is given in Table 2. The final value for uncertainties in the determination of absolute coordinates for the reference benchmarks on each Cal/Val site are used as input in the processing chain to derive the FRM constituent uncertainty. Figure 4: Location of the geodetic GNSS network that provides absolute coordinates of the PFAC Cal/Val sites (left, map of west Crete). Example photos from the main sea-surface Cal/Val facility in Gavdos and the CDN1 transponder Cal/Val site on the mountains of Crete. Operations of two GNSS receivers at each Cal/Val site ensures redundancy and reliability of observations. GNNS Processing Constituent  
The positioning results presented in Table 2 are those derived by relative positioning processing. Using the same GNSS observations, the alternative technique of Precise Point Positioning (i.e., GIPSY scientific software [26]) is also applied to derive solutions for the coordinates and velocities of the same GNSS stations. Processing of the same GNSS observations with different processing strategies ensures validity of the derived absolute positioning values, and follows the FRM4 ALT study recommendation to use multiple approaches to arrive at the same result [24]. The results of different processing strategies are shown in Figure 5 for the GVD8 Cal/Val site in Gavdos.
# Trusted GNSS-Based Time Synchronization for Industry 4.0 Applications
## 4 Trusted Computing
### Trusted Computing Base  
Trusted Computing (TC) is used in this paper as per the Trusted Computing Group's (TCG) definition: a set of interoperable technologies to achieve a level of trust in the behavior of an embedded system. The core element of TC is the hardware Root of Trust called Trusted Platform Module (TPM). A TPM is a tamper resistant piece of cryptographic hardware integrated with the system board that implements primitive cryptographic functions on top of which more complex features can be built in accordance with TCG specification TPM 2.0 [47]. The final objective for the application of TC in this work is to enable nodes to measure and prove their integrity cryptographically, i.e., prove that the software running is the intended one and it has not been tampered with, to the other nodes involved in the synchronization distribution. Integrity measurement is therefore the process the nodes adopt to collect and digest the information about the integrity of their software and configuration for the purpose of being attested/verified. The three main hardware Roots of Trust to make the node a Trusted Computing Base (TCB) are:  
1. _Root of Trust for Measurements_ (RTM): the Core Root of Trust for Measurements (CRTM) that act as the Trust Anchor; it is commonly implemented by the initial bootloader secure code executed at power up or hardware reset;
2. _Root of Trust for Storage_ (RTS): the TPM that provides 1. a set of Platform Configuration Registers (PCRs) to securely accumulate the integrity measurements in form of hashes, and 2. a key hierarchy architecture to securely store objects protected via encryption by the TPM on the file system;
3. _Root of Trust for Reporting_ (RTR): the TPM that signs the values of a PCR set using an Attestation Key bound to the Endorsement Key, i.e., a resident key that represents the TPM identity and that guarantees the origin and the integrity of the PCR values shared for the purpose of attestation.
# LoRa Communication Using TVWS Frequencies: Range and Data Rate
## 5 Discussions
TVWS offers a large band that can accommodate more channels and this can also be one approach to tackle interference. In addition, LoRa hardware that supports these frequencies is available. Thus, with these developments, TVWS will emerge as a viable option for LoRa-based applications.
# A Resilient Large-Scale Trajectory Index for Cloud-Based Moving Object Applications
## 2 Related Work
### MapReduce-Based Contributions
The pruning of partitions during a Spark job depends on an internal pruning mechanism and is achieved by tracking local trees' identifiers and updating the hash table accordingly. Neither the global index nor the local index supports the temporal dimension. Consequently, UMOi does not support temporal queries. For trajectory retrieving queries, UMOi depends on a secondary index that scans the whole dataset to index objects based on their identifiers. On the other hand, RMOI uses machine learning models to predict the best locality pivot based on many factors. The global index of RMOI is a single hierarchical structure, where the top part follows a k-d-B-tree splitting mechanism and the bottom part is an R-tree. Both global and local indexes support temporal indexing and querying. RMOI uses different partitions pruning that depends on the Spark built-in filter transformation. In addition, it leverages the partitioning mechanism to serve trajectory retrieving queries without using a secondary index. Finally, the locality is an essential key to improve the performance and enhance the adaptation capability. The nature of a trajectory (consecutive timestamped spatial points) creates contradictory domains, which can be seen in spatial locality and object locality. As a result, some of the previous contributions optimize their systems to contain this contradiction by focusing on spatial locality and spatial queries (e.g., range query, k-NN, etc.) with an object-based auxiliary index, or by narrowing it down to a particular operator and building an ad hoc index for that purpose. To the best of our knowledge, no work has been conducted on trajectory indexing for distributed environments that would simultaneously balance the losses and gains of both localities and target a large variety of queries.
# Automated Processing of fNIRS Data--A Visual Guide to the Pitfalls and Consequences
## 4 Discussion
### LF De-Noising Methods
However, as described in Section 2.4.4, we did not choose the best possible SSD measure, due to hardware constraints. Various papers have shown increased performance with shorter source-detector separation (e.g., 8.4 mm for the adult head [42], or 6 mm versus 13 mm [60])) and additionally region specific SSD measurements [43]close to the detector [61]. Therefore, our results underestimate the success rate of SSD de-noising. However as long as hardware constraints remain and SSD measures are not directly integrated into the fiber probes, difficulties to use the optimal SSD measure remain. This difficulty includes the sparing, not only of one fiber for the SSD measure and optimally one fiber for each region, but also losing a long distance measurement in the same area with instruments, in which the gain is not adjusted pair-wise (e.g., TechEn). One variable of many, not addressed in this analysis, is the scaling algorithm. Many exist, including adaptive filtering [53; 62], least square minimization (LSM) [63], independent component analysis [64], and Kalman filtering [54], all of which can impact a study's results. In fact, [PERSON] et al. [54] showed improved results with the Kalman filter in comparison to the traditional adaptive filter. In this study, we evaluate the three aforementioned methods of de-noising, namely SSD*, PCA, and GloAvg, as these are accepted methods that can be easily implemented in any research setting, by users with varying levels of fNIRS experience. One de-noising method not studied here, which has been shown to effectively reduce the physiological noise in fNIRS studies, is the monitoring of systemic physiology (respiration, End-Tidal CO2, arterial blood pressure, and ANS responses), with the goal of removing that component from the hemodynamic signal of interest [65; 66; 67]. When possible, monitoring systemic physiology can be considered to limit the possibility of false positives and false negatives. The analysis here, however, offers a comparison of de-noising methods that could be used in scenarios that do not allow for the monitoring of systemic physiological parameters.
## 2 Materials and Methods
### Compression Experiments  
Specimens (3D-printed elementary models) were stored at room temperature for over 24 h before conducting compression experiments. The compression force and displacement of specimens were measured by a universal testing machine (Changchun Kexin instruments Co. Changchun, China). The testing speed was set to 2 mm/min and the capacity of the force cell was 1 kN.
## 3 Numerical Simulation
### Numerical Modeling  
#### 3.3.1 Geometric Modeling, Meshing and Boundary Conditions  
A three-dimensional finite element model is established according to the project's actual burial depth, the boundary error induced by the freezing wall's influence range, and the complexity of the model calculation. The freezing pipe has dimensions of \(\varphi\)108 mm \(\times\) 10 mm, and a size model with dimensions of 30 m \(\times\) 10 m \(\times\) 30 m is selected for the calculation.  
The numerical model calculation adopts a user-defined free tetrahedral grid with an adaptive mode. The mesh size around the freezing pipe is reduced to reduce calculation error and improve convergence. The mesh size can be appropriately increased in the boundary region, where the temperature change due to the freezing pipe is not directly affected. This approach ensures a reasonable division of the mesh density. The numerical model ultimately consists of 216,339 cells.  
The initial temperature of the model is set to the actual working temperature, which corresponds to the original ground temperature of the actual working condition, i.e., 18 \({}^{\circ}\)C. The initial condition of the moisture field is set to saturation S = 1 and combined with the test parameters of the most unfavorable soil layer in the working condition; the initial water content is set at 40%. To closely mimic the working conditions, gravitational acceleration is set to g. The boundaries around the model are adiabatic and have a constant temperature, while the cooling plan defines the boundary conditions at the freezing pipe. The boundaries around the moisture field are set as zero flux boundaries, considering internal migration. The bottom boundary is a fixed-displacement boundary, and the normal displacement is constrained all around, as shown in Figure 3.
# Influencing Factors of Motion Responses for Large-Diameter Tripod Bucket Foundation
## 3 Experimental Setup and Test Procedures
### Experimental Setup  
The experiments were conducted in the harbor basin at the National Engineering Research Center for Inland Waterway Regulation of Chongqing Jiaotong University in China. The dimensions of the basin are 30 m long, 20 m wide, and 1.2 m deep. A plate-type wave maker driven by an electronic-hydraulic servo system was installed at one end of the basin; a wave-absorbing equipment was fixed at the other end to eliminate the effect of wave reflection. Regular and irregular waves with a period of 0.5-5 s, wave height of 0.02-0.25 m, and a maximum water depth of 0.8 m can be generated by the experimental facility.  
A schematic of the experimental setup is shown in Figure 6. The LDMBF structure, supported by the positive pressure of interior air relative to the outside atmosphere pressure, was placed on the water surface at a distance of 10 m from the wave maker. To limit the structure within a certain range of motion without affecting the wave-frequency motion, the model was anchored using a horizontally placed soft-spring arrangement at the bow and stern [21].  
As shown in Figure 7, combined with the several calibration bars attached to the side-wall surface of bucket foundation, an exhaust valve to transfer air inside and outside of the structure was fixed on the top cover of each bucket foundation to adjust the draught.  
The experimental data reported by [PERSON] et al. show different wave amplitudes in heave and pitch RAO. No significant difference was observed between the wave amplitudes of 8 mm and 20 mm, thus concluding that the system is linear within the range of wave amplitudes tests [13]. Because the target geometry scale factor in this study is 1/25, the scales for wave height and water depth are also 1/25, and the scale for the wave period is 1/5. The wave height in the laboratory tests was fixed at 0.08 m. The model wave period was in the range 1.0-3.0 s, while the prototype wave period was 5.0-15.0 s, within the range of most wave periods for wind-generated waves. In ship dynamics, the magnification factor of oscillating motion of a ship in waves is not only related to the inherent characteristics of the structure and frequency of wave disturbing forces or moments, but also to the ratio of the wavelength (L) to the length of the ship [29; 30; 31]. In this study, the outermost distance from one bucket to the other, S, was selected to compare the test results. All the wave conditions tested in the experiment are listed in Table 4. The normalized L/S varied from 1.15 to 6.96. The three water  
Figure 6: Sketch of the experiment setup for multibucket foundation.  
Figure 7: Model of a single bucket foundation.  
depths are 0.40 m, 0.45 m, and 0.50 m with 0.18 m draft. Three drafts of 0.16 m, 0.18 m, and 0.20 m with 0.5 m water depth were evaluated in this study.
# Development of Security Rules and Mechanisms to Protect Data from Assaults
## 3 Proposed Algorithm
### Data Encryption Process
#### 3.2.1 Bit Reversing  
Bits reversing is the process of reversing all bits so that if there is a man-in-the-middle attack, the attacker cannot obtain the original data due to reversing the bits, and the attacker has access to data that have no link to the original data.