esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Materials and Methods  
### Overview  
The RAATM is designed to enable a small, lightweight AUV (and specifically the WIEVLE) to secure itself temporarily to the seabed, change depth by paying out and retracting the tether via an internal spool, transmit and receive electromagnetic signals over short distances, re-stow the anchor, and maneuver to another area to repeat the process as required. The mechanism is ideally suited to lightweight vehicles that need to maintain a smooth exterior to reduce drag or entanglement hazards, thus precluding traditional, heavy, external anchoring systems. The key design requirements, therefore, are minimal weight, internal stowability, reusability, and the ability to pay out varying lengths of tether and, thus, change depth without the aid of propulsive thrusters or active buoyancy compensation. The principal means of attachment to the seabed, which presumably consists of sediment, sand, or fine gravel in the operating area, is an anchor \"spike\", in the form of an auger, aided by an array of semi-flexible wire \"roots\" embedded with friction-enhancing bristles surrounding the base of the anchor assembly in a shallow pattern.  
The use of a screw-type anchor spike as a principal method of anchoring to the seabed proceeded naturally from the design requirements based on the intended host platform (the SAUV WIEVLE). The chief concern, however, for the use of the anchor spike alone was the risk of failure due to the anchor spike working loose from the sediment due to insufficient gripping strength or the inability to resist angled loads on the tether. A method of enhancing the design's gripping strength while fitting within the physical boundary constraints of a cylinder (the central space along the WIEVLE's vertical axis) was sought, and inspiration was taken from the method employed by sea grass to anchor in sand and resist continuously-varying tension loads from wave action--fine roots spread out over a wide surface area. Alternative designs, such as screw-type rigid or semi-flexible \"roots\" or expanding rigid mechanisms, such as those used to augment certain drywall anchors, were considered but ultimately abandoned due to the complexity of generating the necessary rotation in the case of screw-type anchor branches or the high probability of jamming in the case of folding rigid mechanisms. In both alternatives, a successful deployment seemed likely to be followed by a failed retraction; thus, a simple method of push-pull insertion and retraction was desired to satisfy the reusability requirement.  
The resulting mechanism operates through four states (I-IV), as depicted in Figure 2: (I) the _stowed_ position, (II) the _inject_ position, (III) the _rooted_ position, and (IV) the _tethered_ position. The principal assemblies of the mechanism include the spool and tether assembly, the anchor sleeve assembly, and the retractable anchor assembly, described in detail in Section 3.2.
## 5 Results
### In Situ Testing  
In October 2020, an experimental campaign of ambient vibration measurements was carried out to evaluate the main frequencies of the structure. Velocimetric stations were installed on the span at L/2, both at the center and on the east edge, at L/4 on the east edge and on the abutment (Figure 10).  
Experimental campaign has been performed using velocimetric stations characterized by a dynamic range equal to 144 dB, a digitizer characterized by a resolution equal to 24 bit, a sensor characterized by a frequency equal to 0.5 Hz. Velocimetric recordings have been acquired using a sampling frequency equal to 200 Hz for a total length of each acquisition equal to 900s. Figures 11 and 12 show the displacement time series recorded on the bridge at different points. It is possible to appreciate the difference in terms of level amplitudes among the span and the abutment for both horizontal and vertical components. During the experimental campaign, the structure exhibits a linear-elastic behavior characterized by the transfer functions [68] depicted on Figure 13.  
Figure 11: Displacement recordings: (**a**) on the abutment and (**b**) at L/4 on the east edge.  
Figure 10: Locations of the ambient vibration recordings.  
In order to evaluate the transfer function of the monitored bridge, the acquired recordings have been firstly corrected for baseline and filtered between 0.1-30 Hz using a band-pass filter. Secondly, the Welch spectra have been evaluated for each channel of each velocimetric recording and, finally, the transfer functions have been evaluated considering the station located at zero as the reference station. The first three eigenfrequencies characterizing the dynamic behavior of the monitored bridge are the following:  
I Mode: 0.92 \(\pm\) 0.01 Hz--vertical direction;  
II Mode: 1.01 \(\pm\) 0.01 Hz--transversal direction;  
III Mode: 1.33 \(\pm\) 0.01 Hz--vertical direction.
# VSFCM: A Novel Viewpoint-Driven Subspace Fuzzy C-Means Algorithm
## 4 Experimental Results
### UCI Data Sets

Table 5: Clustering results on UCI data sets. As can be seen from Table 5, the six algorithms can be divided into three grades, the worst is V-FCM and DVPFCM, the performance of FRFCM and ESSC is equivalent to or better than that of SCAD1, and the best is the proposed VSFCM algorithm. Although DVPFCM and V-FCM algorithms mentioned are generally inferior to the other three algorithms, they can achieve better clustering performance on the Iris and Letter Recognition (A, B) data sets measured by NMI and CR, respectively. This shows that for all data sets, no one algorithm is always better than others. Through comparison, we further notice that the best clustering performance indicated by NMI and CR is not always consistent with the best clustering performance indicated by other indicators. That is, the clustering performance with higher NMI and CR values does not necessarily possess higher XB, CH, and EARI values. Therefore, it is necessary to comprehensively evaluate the performance of clustering algorithms with different metrics. From Table 5, the following conclusions can be drawn:  
First of all, due to the low dimension of small data sets, which contributes to the small impact of weights on the results, V-FCM and DVPFCM (belonging to viewpoint-oriented fuzzy clustering algorithms) can get better results on these data sets. In addition, the viewpoint can guide the clustering algorithm to run in a more correct direction, so the NMI and CR indicators of V-FCM and DVPFCM perform better on some data sets. Secondly, for the weighted fuzzy clustering algorithms, SCAD, ESSC, and FRFCM with more complex structures have a great advantage in processing multi-dimensional data sets, owing to the efficiency and effect of clustering improved by the weight distribution. Finally, our proposed algorithm VSFCM is obviously superior to the other algorithms mentioned above. Because our algorithm well integrates the advantages of the two types of algorithms and successfully improves the clustering effect. In general, our proposed VSFCM algorithm is more ideal for obtaining initial cluster centers and has better performance in various clustering evaluation indicators. Table 6 reflects the dimension weight distribution results of the subspace algorithm carried out on the Wine data set, presenting in the order of the weight values of each cluster corresponding to the 13 features in the data. It can be seen from Table 6 that different subspace clustering algorithms may have different degrees of importance to the same feature. Similar results can be obtained with other UCI data sets. For multi-dimensional data sets, the reasonable distribution of dimension weights can improve the accuracy and efficiency of clustering, so our proposed VSFCM algorithm can achieve more ideal clustering results.
# A Virtual Network Resource Allocation Framework Based on SR-IOV
## 6 Conclusions  
This paper proposes a virtual network resource allocation method that can combine the advantages of I/O para-virtualization and SR-IOV technology. It can dynamically sense the load changes of VMs, use the hierarchical division method to limit the VF bandwidth, and allocate different levels of VF according to the bandwidth requirements of different workloads of VMs. In addition, by limiting the number of VFs to ensure the performance of network-intensive VMs, it can improve the overall network performance of the system. The load awareness of the VM is obtained by reading the pseudo file _/proc_ in VM and sending it to the VF Scheduler module of the privileged domain by means of _virtio-serial_ communication in KVM. The dynamic scheduling of VF adopts ACPI Hotplug technology and the active backup mode of _Bonding Driver_ technology to meet the dynamic switching of VF and para-virtualized NICs when the VM load changes. Our experiments show that our proposed virtual network resource allocation framework can effectively improve the overall network performance of the system.  
Our prototype system is implemented based on KVM and our comprehensive evaluation shows that the virtual network resource allocation framework proposed in this paper is effective since VF is always dynamically allocated to VMs with high network density. In addition, the allocation framework also can effectively improve system network performance, in which the average request delay can be reduced by more than 26%, and the system bandwidth throughput rate can be improved by about 5%.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] wrote the original draft, [PERSON] and [PERSON] edited and reviewed the paper, [PERSON] supervised this work.  
This work was supported by the National Natural Science Foundation of China (No. 2012 CB215202), the Fundamental Research Funds for the Central Universities of China (Nos. 106112016 CDJXZ168815, 106112017 CDJZRPY0101), and the Scientific and Technological Project of Chongqing (No. cstc2017 shmsA40003).  
The authors declare no conflict of interest.
# A Robust and Effective Two-Factor Authentication (2 FA) Protocol Based on ECC for Mobile Computing
## 4 Security Analysis
### Heuristic Analysis
#### 4.2.2 User Anonymity and Un-Traceability  
User anonymity refers to hiding part of the user's information during communication, and un-traceability means that the user's identity cannot be tracked. Practically, in order to obtain the user's identity during the communication session, \(\mathcal{A}\) needs to extract all parameters \(\{a_{i},A_{i},B_{i},X,P,n_{0}\}\) stored in \(SC_{i}\) and obtain \(\{M_{1},M_{2},K_{1}\},\{K_{3},M_{3}\}\) from \(U_{i}\) and \(S_{j}\), but no identity information is preserved in the user's smart card or conveyed over the open channel in the proposed protocol. For user traceability, \(M_{1}=H(ID_{i}\parallel K_{1}\parallel K_{2}\parallel V_{i})\) and \(M_{2}=E_{K_{2}}(ID_{i}\parallel V_{i})\) are variable. The user's real identity \(ID_{i}\) cannot be traced by \(\mathcal{A}\). Thus, user anonymity and un-traceability can be achieved.
## 3 Simulation Results and Discussion  
### Validation of Soil-Soil Interaction  
As described in Sections 2.3 and 2.5, the soil-soil interaction throughout the sand bed in the DEM model was validated by controlling its relative density and peak-state internal friction angle. It was determined to be 37.8\({}^{\circ}\) (measured from a biaxial cell prepared at a relative density of 80%), which exhibits a mean absolute error of 0.5% compared with the experimental value of 38\({}^{\circ}\) from a sample prepared at a relative density within a range of 80-90%.  
Figure 6: Pile displacement versus time for simulating the pile installation.
# Review of Structural Modal Tracking in Operational Modal Analysis: Methods and Applications
## 5 Discussion and Recommendations
### Modal Tracking Application  
The modal evolution of infrastructure is closely related to its structural type and environmental factors, among others, necessitating empirical tracking and analysis to obtain a comprehensive understanding of this pattern. Currently, long-term modal tracking has been extended to various fields, including long-span bridges, super high-rise buildings, stadiums, dams, heritage construction, and wind turbines. Among these, modal evolution studies are more prevalent for bridges and heritage construction, primarily focusing on the coupling between natural frequencies and the ambient temperature. In contrast, modal tracking of super high-rise buildings emphasizes multi-typhoon scenarios, and studies indicate that their natural frequencies are not necessarily sensitive to temperature.  
In certain cases, changes in modal parameters induced by environmental variations may obscure those caused by structural damage or degradation. Therefore, SHM based on modal tracking primarily revolves around two aspects: the elimination of environmental effects on modal parameters and service performance assessment utilizing modal variations. It is noteworthy that some studies on modal evolution have employed AMPE methods without utilizing the modal tracking frameworks discussed in Section 3.1. This suggests that AMPE methods are extensively applied in structural modal analysis, whereas standard modal tracking methods remain confined to specific scenarios. The limited adoption of modal tracking methods can be attributed to their relatively immature development, which is characterized by cumbersome procedures and insufficient automation. Consequently, there remains significant potential for advancement in both methodological development and practical applications of modal tracking in the future.
## 2 Materials and Methods
### Evaluation of Cytotoxicity and Antitumor Activity  
2.6.1. MTT and Neutral Red Assays  
The MTT assay was used to assess the metabolic activity of cells treated with BMNPs or BMNP-MTX conjugates based on the reduction of 3-(4,5-dimethylthiazol-2-yl)-2,4-diphenyl tetrazolium bromide (MTT) in a cellular mitochondria [30]. The neutral red uptake (NRU) assay was performed to determine the extent of cell viability with the measurement of the amount of neutral red (NR) accumulated in the lysosomes of the living functional cells [31]. Prior to both assay types, cell suspensions with a concentration of 1 \(\times\) 10\({}^{5}\) cells/mL were seeded on 96-well plates (TPP, Trasadingen, Switzerland) (100 uL/well) and cultured under standard conditions for 24 h. The cells were then treated with different concentrations of nanoparticles and BMNP-MTX conjugates--10, 50, 100 and 200 ug/mL) for 24, 48, 72 and 96 h. For this aim, 5 mg/mL nanomaterials were suspended in Dulbecco's phosphate-buffered saline (DPBS) and sonicated for 300 s. To achieve the test-concentrations, BMNPs stock suspensions were diluted in a cell culture medium. MTX served as a positive control for all in vitro cytotoxicity tests. The compound was assayed in the same concentrations as the nanoparticles. In addition, a control of untreated cells cultured for the same time period in a standard growth medium was analyzed in all experiments. All samples were analyzed in triplicates.  
At the end of every test period (24, 48, 72, 96 h), MTT (Merck KGaA, Darmstadt, Germany) or NR (Merck KGaA, Darmstadt, Germany) solution was added to the cell culture medium to reach a final concentration of 0.5 mg/mL for MTT and 0.005 mg/mL for the NRU assays. The plates were incubated for 2 h in the dark at 37 \({}^{\circ}\)C, 5% CO\({}_{2}\) and high humidity. After that, the culture medium was removed, and the cells were washed with DPBS. Formazan accumulated in MTT-treated cells was solubilized using 100 \(\upmu\)L/well dimethyl sulfoxide (DMSO, Merck KGaA, Darmstadt, Germany). The plates were incubated at room temperature under continuous mild shaking for 15 min. Absorbance was then measured at 570 nm using a SpectraMax i3x spectrophotometer (Molecular Devices, San Jose, CA, USA). For the NR assays, after washing with DPBS 100 \(\upmu\)L/well, aqueous solutions of ethanol and glacial acetic acid (50%:1%) were pipetted to the plates in order to extract the dye accumulated in vital cells. The culture vessels were incubated for 15 min at room temperature with continuous gentle shaking, which was followed by a measurement of absorbance at 540 nm using a SpectraMax i3x spectrophotometer (Molecular Devices, San Jose, CA, USA). The obtained data were presented as percent inhibition of cell viability and/or metabolic activity, which was determined based on absorbance units from treated cells and cells cultured under standard conditions without the addition of an extract. The concentration of the test sample inhibiting the viability/metabolic activity of 50% of the cells (IC\({}_{50}\)) was determined at 72 h.
## 3 Results and Discussion
### Design of Ink Properties
#### 3.2.1 Principal Component Analysis
The blend with an alginate ratio of 8% exhibits the highest printability for both stand and pore areas. Tan\(\delta\) of inks in group A is in the range from 0.35 to 0.5. Blends classified as Group B mainly behave as elastic gels (G\({}^{\prime}\) dominates) and present low tan\(\delta\) values. High tan\(\delta\) values and high viscosity recovery rates characterize the third class of inks (Group C). These are blends in which the liquid phase (G\({}^{\prime\prime}\)) predominates. The fact that they behave as liquids explains their ability to recover the initial viscosity after a reduction in shear rate. However, their liquid-like behavior due to the increased alginate ratio results in low printability, as was also shown by [PERSON] et al. [9]. Figure 7: (**a**) Biplot for PC1 and PC2 showing sample ’s scored and variables’ vectors; (**b**) Biplot for PC1 and PC3 showing sample ’s scored and variables’ vectors (**c**) Scores plot for PC1 and PC2 displaying the different groups of candidate inks marked with three different colors based on their rheological properties; (**d**) Scores plot for PC1 and PC3 displaying the different groups of candidate inks marked with three different colors based on their rheological properties. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Rheological Properties** & **Viscosity** & **n\_index** & **m** & **G\({}^{\prime}\) (Pa)** & **G\({}^{\prime\prime}\) (Pa)** & **tan\(\delta\)** & **V\_Recovery(\%)** & **Yield Stress** (Pa)** \\ \hline Printability window & [1000–4000] & \textless{}1 & [1000–3000] & [1500–4500] & [700–1500] & 0.45–0.5 & - & [2000–5000] \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Printability window: rheological properties. The high tan values combined with low to medium values of G\({}^{\prime}\), G\({}^{\prime\prime}\), and m result in poor printing behavior and could not be used as extrusion-based 3D printing inks despite their shear thinning behavior.
## 4 Experimentation and Results
### ANN Results  
From the trends and patterns of both indices, _ENE_ and _THD_, shown in Figures 9 and 12, it becomes evident that the application of a machine learning model for automatic fault severity diagnosis is feasible. As mentioned in Section 2.6, in this work, the ANN model is selected. After conducting thorough experiments aimed at achieving satisfactory classification results, the resulting NN architecture comprises three inputs (i.e., the index value of each vibration axis), twelve neurons in the hidden layer, and seven outputs, i.e., one for each SCT condition. This architecture follows the one presented in Figure 2. The training algorithm used is the scaled conjugate gradient. The total data were divided in 70% for training and 30% for validation. It is worth noting that two separate ANNs, each with the aforementioned structure, are used for each operating regime, as outlined in the proposed methodology in Figure 3. Figures 13 and 14 present the obtained confusion matrices, where accuracy total values of 90% are obtained.  
Figure 11: Steady-state spectra for (**a**) Vx, (**b**) Vy, and (**c**) Vz.  
Figure 12: Boxplots for the _THD_ index in (**a**) Vx, (**b**) Vy, and (**c**) Vz.  
Tables 3 and 4 show the accuracy, recall, specificity, precision, and F1-score metrics for the confusion matrices shown in Figures 13 and 14, respectively. These values are computed using the mathematical formulations of Section 2.6 by taking the values of one against all. As can be observed, most of the values are higher than 0.9 (90%), indicating the good performance of the proposed ANN models under different metrics. However, it is also evident that some signals are more difficult to accurately classify in terms of precision, e.g., 15 and 20 SCT classes in the transient state (Table 3). These values will be the reference during the development and application of new and more efficient machine learning-based models in terms of complexity and accuracy.  
Figure 14: Confusion matrix obtained for the diagnosis of the SCT condition using the steady-state data.  
Figure 13: Confusion matrix obtained for the diagnosis of the SCT condition using the transient-state data.  
Also, a \(k\)-fold cross validation with \(k=3\) is carried out in order to avoid possible biased results due to the random split of data [36; 37]. The obtained accuracy values are 90.1% (transient state) and 90.4% (steady state), showing highly similar results and, consequently, the reliability of the proposed ANN models. Although promising results have been obtained, there is still an opportunity to further research other machine learning-based models.
## 3 Results and Discussion  
### Optimization of Film Thickness Capillary Columns  
A series of silica-supported polymeric ionic liquids-based stationary phases were prepared as capillary columns (see experimental section) using the polymerization of the \(L\)-value-derived monomer AAIL **4** and DVB as the crosslinker for the coating of the silica surface (Figure 1). Column efficiency was evaluated using naphthalene as a soluble probe. Initially, several columns were prepared by varying the percentage of AAIL **4** in the absence of any crosslinking agent to form the corresponding linear PILs for the coating. As can be seen in Figure 2a, a percentage of 0.36% _w/v_ AAIL provided the best separation efficiency. This percentage corresponds to a linear PIL film thickness of 0.23 microns. Therefore, capillary columns were prepared with 0.36% _w/v_ of AAIL **4** for all subsequent studies.  
In order to better understand the effects of the cross-linker on the efficiency of PIL-based stationary phases, PILs with varying amounts of DVB as the cross-linker (i.e., 0, 10, 20, 30, 40, and 60% _w/w_, Figure 1) were prepared and their efficiency compared. The efficiencies obtained are shown in Figure 2b.  
As can be seen, all coated PIL columns possessed efficiencies of at least 1700 plates per meter. Moreover, the resulting columns were more efficient in the presence of the crosslinker and the efficiency increased with the amount of divinylbenzene added up to 20% _w/w_ of DVB (DVB:AAIL ratio) with an efficiency of 2700 plates per meter at 20% DVB that compares well with efficiencies shown by other IL-based GC columns [35; 49]. From this point, the number of plates per meter decreased significantly. This can be ascribed to the fact that for crosslinking degrees higher than 20% DVB, the interaction sites from AAIL located at the highly crosslinked regions become less accessible for the interaction with the analytes. Thus, some crosslinking is favorable to establish structurally well-defined and cooperative interaction sites, but polymerization with high crosslinking degrees can contribute not only to generate diffusional problems in the polymeric matrix but also to force less well-structured interaction sites, as has been demonstrated in polymer-supported catalysts [50; 51].