esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experiments  
### Vibration Characteristic Experiments  
To validate the accuracy of the theoretical analysis and test the characteristics of the proposed motor, a prototype motor has been fabricated according to the above-proposed structure parameters. Figure 6d is the photo of the prototype. The scanning laser Doppler vibrometer (PSV-400-M2, Polytec, Waldbornn, Germany) was adopted to measure the vibration characteristics in the frequency range from 0 kHz to 50 kHz of the motor. Notably, in several close vibration peaks, only choosing the vibration peaks of the frequencies of 24.429 kHz and 24.476 kHz could coincide with the vibration mode of the above theoretical analysis. The modal shapes and vibration spectra of Mode A and Mode B are shown in Figure 7.  
The results of the vibration test and the finite element simulation are shown in Table 4. The prototype working modal frequencies of Mode A and Mode B are 24.429 kHz and 24.476 kHz. The relative deviation of the prototype working frequency and the finite element simulation result is less than 1%. The vibration test result agrees well with the FEM analysis calculated result, and this testifies to the rationality of the design method presented in this paper.  
Figure 6: The elliptical trajectories and prototype of the stator: (**a**) The displacement response of the center point along \(OX\), \(OZ\) direction; (**b**) The steady motion of the center point in \(XOZ\) plane; (**c**) The elliptical trajectories of driving foot; (**d**) The prototype of proposed motor.
## 2 Notes on the Theory, Method and Data
### Method  
We compute and plot the strike angles \(\theta\). The combed \(\theta\) co-identify oil, gas and groundwater deposits; these sources are often located together. Where combed, we can expect the oil and gas or water deposits, but unfortunately not only this, because--as is well known--the gravity signal used solely by itself does not provide a unique information. There is no direct relationship meaning that the combed strike angles define \(TD\)s (Section 2.2). They rather indicate the changed porosity of the local material, which may well be owing to the impact force in the case of an impact event, or they can be combed due to geological/tectonic processes. It is evident that close cooperation with regional specialists is always needed to resolve the local/regional problem.  
Figure 2: Tutorial: the strike angles are here also “combed”, but into a (semi)circular shape, creating a “halo” (on land) around the impact crater—in this case, Chicxulub, North Yucatan (partly on land, partly in shallow waters). The EIGEN 6C4 gravity field model was used. (**a**) An extensive area around the crater with highly combed values is affected by the impact event (generating post-impact changes concerning oil and gas deposits, groundwater, cenotes—the red dots in (**b**) depending on the size of the particular crater (in turn on size and energy of the impactor) and the local material [1]. It is not by chance that half of the impact craters known in North America possess economic minerals (e.g., [14; 15]).  
Nevertheless, the combed strike angle provides an easily accessible criterion and a simple preliminary diagnostic tool for the respective presence of oil and gas (hydrocarbon) or groundwater localities. They should be included in the pre-prospection phase because they can help to lower the risk of incorrect prediction. For our results and discussion about them, see Section 3.  
As for the groundwater and paleolakes, there is a negative \(\Delta g\) and second radial derivative \(T_{zz}\), compression in \(vd\) inside the objects and combed \(\theta\). However, we know that the gravity signal is not unique and that similar characteristics appear also for wide and deep river valleys, such as parts of the Nile, canyons such as the Great Canyon, faults such as Lake Vostok, Baikal and similar, etc. (see [1] and references therein).  
The first step of our method to detect such an object is to transform the difference in the gravity anomalies between its assumed deepest and highest place to the difference in the heights to make the maximal estimate where the object can be located and how large/deep it might be. Sometimes, several iterations are needed. The second step is to use a topography model and the geographic positions of archaeological sites, leading eventually to a fine-tuning of the level, extent and shape of the object to keep the archaeological site at its shore for the time interval in question. This also requires a few iterations. For more details on our method, results and discussion, see Section 4.
## 5 Research Progress on Key Technologies of IPPCS
### The Strength Criterion of the Pressurized Capsule Structure Based on Shakedown  
#### 5.1.1 Problems of Conventional Strength Criterion  
The pressurized capsule configuration is generally composed of a cylinder, a cone and a sphere. Under the action of internal pressure load, the local area of the shape change (shape transition zone) will produce a large stress concentration, as shown in Figure 10. When the internal pressure load reaches a critical value, the stress of these stress concentration areas will quickly approach the yield limit strength of the material. Completely eliminating these stress concentration areas through structural strengthening will cost a lot of weight, which is not conducive to reducing the weight of the structure [23; 24].  
Figure 9: Structural comparison of shape transition zone between WPPCS and IPPCS.  
In practice, such as the internal pressure overload test of the pressurized capsule, it is found that the pressurized capsule structure can still bear stable internal pressure load after local plastic deformation, but it is not known what is the limit of stable internal pressure load after plastic deformation of the pressurized capsule structure, and it is also not known whether the stable load is safe and reliable.
# 3D-Printed Accessories and Auxiliaries in Orthodontic Treatment
## 4 Discussion
### Contemporary Use of 3D-Printed Accessories in Orthodontics
#### 4.1.1 Various Auxiliary Devices  
A variety of personalized orthodontic accessories, such as distalizers [26; 27], power arms [28], powerchains [29], or support devices for impacted teeth [30; 31; 32; 33] can be fabricated using 3D printing technology.  
One such example is a biocompatible individualized distalizer made from photopolymeric resin as an aesthetic alternative to conventional methods. This was produced through 3D printing and can be applied in a tooth-borne hybrid method for treating Class II unilateral malocclusions [26]. It is also possible to create a library with various sizes of 3D-printed distalizers, which enables the possibility of personalizing distalizers at any time when needed [27].  
Another study examined the clinical results from using various 3D designed and printed orthodontic power-arms. This promises more consistent treatment outcomes and thus more effective orthodontic care. When comparing the 3D printed power-arms with manually crafted or pre-fabricated ones, it is evident that biocompatible AM overcomes many of the common obstacles faced by non-AM power-arms, such as patient discomfort, loss of attachment, or aesthetic handicap [28].  
[PERSON] et al. presented the possibility of producing individualized 3D-printed elastic chains with the predefinition of exact forces needed. This could be a possible next step for force-driven planning of orthodontic treatment [29]. The other two case reports described the disimpaction of amines by bone-anchored customized 3D-printed metal devices. In both cases, the device was used for the traction of impacted canines with satisfying results [34; 31].
## 3 Results  
### Growth and Biomass Production of microalgae  
As expected, the _T. weissflogii_ peak cell density (_k_) improved significantly (_p_ < 0.05) when the nitrogen concentration increased from 111.25 to 890 \(\upmu\)M. According to the sigmoidal curve model (Table 2), the highest NaNO\({}_{3}\) (N4) concentration produced the largest cell density (>12.5 \(\times\) 10\({}^{6}\) cells mL\({}^{-1}\)) at the end of the exponential phase. However, the highest NH\({}_{4}\)Cl (C4) concentration yielded a similar cell density (-6% less) but with a higher proportionally constant (_r_) (0.385 vs. 0.275 h\({}^{-1}\)). Accordingly, the estimated time to reach half of the maximum cell density (_t\({}_{k/2}\)_) occurred 33 h earlier for C4 compared with N4. In general, _T. weissflogii_ reached _t\({}_{k/2}\)_ 7-30 h earlier when the nitrogen source was NH\({}_{4}\)Cl. The exponential rise model (Table 3, bottom) also confirmed higher final cell densities (_a_ parameter) for N4 and C4, but they were not significantly different. Within this model, the estimated growth rate (_b_ parameter) was not significantly different among similar concentrations of different nitrogen sources. Diatom _T. weissflogii_ treated with NaNO\({}_{3}\) and NH\({}_{4}\)Cl concentrations of 222.5 and 445 umol L\({}^{-1}\) (N2, N3, C2 and C3), respectively, achieved population duplication times (_PDT_)! 56 h, which suggests that moderate salt concentrations provided concentrations close to the optimum nitrogen amounts required for cell duplication, i.e., neither limited nor in excess. With the 890 um treatment, NaNO\({}_{3}\) reached a plateau in biomass production (~0.4 mg mL\({}^{-1}\)) around day 12 and remained at similar levels until day 18. By contrast, the treatment with 890 um NH\({}_{4}\)Cl reached a similar peak value (~0.4 mg mL\({}^{-1}\)) until day 15 but rapidly decreased at day 18. The rest of the treatments did not exceed a biomass concentration of 0.250 mg mL\({}^{-1}\). The cell density (cell mL\({}^{-1}\)) correlated positively with the dry weight measurements (mg mL\({}^{-1}\)) for both nitrogen sources. For NaNO\({}_{3}\), the slope was 2.45 \(\times\) 10\({}^{-8}\) mg cell\({}^{-1}\)
## 2 Materials and Methods  
### Materials  
For the production of the nanoemulsions, olive pomace oil (OPO), sunflower oil (SFO), and corn oil (CO), produced by Minerva S.A. Greece, fish oil (FO) produced by Orkla Health AS, and canola oil (CLA) produced by Fytler Ltd. were bought from a local provider. They were selected as the lipid phase of the nanoemulsions due to their advantageous composition, cost-effectiveness, and availability. These oils, chosen for their ability to form stable nanoemulsions and their well-recognized health benefits, align with the study's focus on maximizing resource efficiency and functionality. Polyoxyethylene (20) sorbitan monopalmitate (Tweet 40 (T40), PubChem: 87560417) was purchased from Acros Organics (Fair Lawn, NJ, USA). For analytical methods, Folin-Ciocalteu's reagent, gallic acid, 2,2-diphenyl-1-picrylhydrazyl radical (DPPPH), and sodium carbonate, were purchased from Sigma Aldrich Chemical Co. (St. Louis, MO, USA), and petroleum ether, acetonitrile (HPLC grade), water (HPLC grade), methanol (HPLC grade), acetone, acetic acid, iso-octane, and p-anisidine were purchased by Acros Organics (Fair Lawn, NJ, USA). Enzymes and reagents used in the INFOGEST protocol were purchased from Sigma-Aldrich Chemical Co (St. Louis, MO, USA). Lycopene extracts from tomato pomace were obtained with 100% ethyl acetate using fixed-bed semi-batch extraction, and polyphenols extracts from olive pomace were obtained using a mixture of water/methanol at a 40:60 ratio, as described by [PERSON] et al., 2024 [33], (Figure 1).
## 3 Design of NexoNet System
### Design Goal  
Based on the above analysis of the current state of OSM and blockchain incentive mechanisms, the NexoNet we proposed should meet the following design goals:  
* Data Security and Information Autonomy: Users' transaction data should be recorded on the blockchain, utilizing blockchain and cryptographic technologies to ensure data transparency, immutability, traceability, verifiability, and resistance to censorship. Furthermore, there should be no centralized organization storing and controlling users' personal information in any form. Users' private information should be distributed and stored locally, and when participating in network activities, necessary personal information is provided in an encrypted form using private keys.
* Effective Incentive: Designing an effective and fair incentive mechanism to encourage user participation in the system is a primary focus of this research. In the NexoNet, users' participatory actions in the network should be recorded and stored on the blockchain. A multiple incentive mechanism reasonably assesses and quantifies user participation, rewarding users accordingly to encourage participation.
* User-Centricity: All platform regulations during its operation are autonomously decided by its users, with each user being an owner of the system. Users participate in the system's daily operations and decision-making processes through voting, sharing in all value and profits generated by the system.
* System Security and Efficiency: As a public blockchain system, the blockchain consensus mechanism must be able to tolerate various forms of attacks in a completely open network environment. Therefore, in the face of massive node participation, the blockchain system must be resilient against all types of attacks and maintain efficiency and scalability.  
In the subsequent sections of this paper, through the introduction and evaluation of the incentive mechanism based on user participation assessment algorithm and the PoAP consensus mechanism, how the NexoNet fulfills the design goals set forth in this section will be demonstrated.
## 3 Physical (PHY) Layer and Media Access Control (MAC) in IoT  
The physical link layer is used for wired or wireless connectivity of different devices. The connection can be token based or it can be managed by datalink layer. In both cases, permission is granted for packet transmission or reception by the media access control (MAC) schemes [22]. There are four main characteristics of the PHY layer that are considered for setting up a connection between a transmitter and a receiver in IoT that includes modulation scheme, transmission mode, channel encoding data rates/throughput, and MAC protocol.
## 2 Materials and Methods
### Characterization Methods  
The LOC was tested on an Army Ballistic Missile Agency (ABMA)-type impact tester under 98 J impact energy, referring to ASTM D2512-9. X-ray photoelectron spectroscopy (XPS) was performed on Thermo Scientific K-Alpha (Thermo Fisher Scientific, Waltham, MA, USA) to detect C, O, N and P elements before and after liquid oxygen impact. Scanning electronic microscopy (SEM) was performed on JSM-7001F equipment (JEOL, Tokyo, Japan) to study the fracture morphology and char residues. The surfaces of the samples were cleaned with ethanol before testing and a layer of carbon was sprayed to improve electrical conductivity. The automatic vacuum carbon injection instrument was utilized to spread a carbon layer onto the surface of specimens. The carbon injection process mainly consists of installing carbon rod, putting it into the sample table with the sample to be tested, vacuuming and carbon injection.  
The bending properties were tested with the INSTRON 5967 electronic universal material testing machine (INSTRON, Norwood, MA, USA) at a loading rate of 2 mm/min. The bending samples were shaped into strips with the dimensions of 60 mm \(\times\) 15 mm \(\times\) 3 mm, referring to GB/T 2567-2008. Single-edge notch bend (SENB) test was measured on same equipment to determine fracture toughness (\(K_{IC}\)) at a speed of 1 mm/min referred to ASTM D5045-99. SENB samples were shaped into cuboids with dimensions of 44 mm \(\times\) 10 mm \(\times\) 5 mm, and the notch and crack were prefabricated before the test. The \(K_{IC}\) value was calculated according to the following formula:  
\[K_{IC}=\frac{SP_{Q}}{DW^{3/2}}f\left(\frac{a}{W}\right) \tag{1}\]  
in which \(f(a/W)\) is calculated referring to the following formular:  
\[f\left(\frac{a}{W}\right)=\frac{3(a/W)^{1/2}\left[1.99-(a/W)(1-a/W)\times\left( 2.15-3.93a/W+2.7a^{2}/W^{2}\right)\right]}{2(1+2a/W)(1-a/W)^{3/2}} \tag{2}\]  
in which \(P_{Q}\) represents the break load, \(S\) represents the span (40 mm),\(f\) represents the geometrical correction coefficient of the polynomial, \(D\) and \(W\) represent the sample thickness (5 mm) and sample width (10 mm), and \(a\) represents the length (5 mm) of the crack. Impact strength was tested on the RXJ-50 impact tester (China) with sample dimensions of 80 mm \(\times\) 10 mm \(\times\) 4 mm, referring to GB/T 2567-2008. At least five samples of each component were prepared for parallel testing.
## 2 Materials and Methods--Porosity Classification and Fracture Identification
### Pixel-Wise k-IN Approach to Determine Rock Fractures and Pores  
As we discussed earlier, our primary objective is to find the regions (\(\mathcal{H}_{i}\); \(\forall_{i}\)) (with irregular shapes) within a given grayscale image (\(\mathcal{G}_{i}\in\mathcal{M}\)) that contains all contiguous dark pixels. Our secondary objective it is to later classify the region as a pore or a fracture. In the current work, we identify a region as \(\mathcal{H}_{i}\) containing a contiguous collection of 100 or more dark pixels (at least of area 100 \(\times\) 4.4 um\({}^{2}\), see Figure 1a,c). However, readers are encouraged to modify this convention based on the quality of available rock image  
\begin{table}
\begin{tabular}{c c c} \hline  & **Accuracy** & **Error Rate** \\ \hline Deep-CNN (Masked RCNN) & 0.093 (mAP) & -NA- \\ \hline Deep-CNN (Masked RCNN Detectron2) & 0.59 (mAP) & -NA- \\ \hline Deep-CNN (Yolo5 Conf 0.5-0.9) & 0.395 (mAP) & -NA- \\ \hline Custom Object CNN & 24.9\% & 85.1\% \\ \hline \multicolumn{3}{c}{\(\alpha=1\), \(\beta=1.11\), \(\gamma=0\), \(\delta=0\)} \\ \hline \multicolumn{3}{c}{\(k\)-IN} & 84.9\% & 15.1\% \\ \hline \multicolumn{3}{c}{\(\alpha=1.03\), \(\beta=0.95\), \(\gamma=0.43\), \(\delta=0.43\)} \\ \hline \multicolumn{3}{c}{\(k\)-IN} & 89.1\% & 10.9\% \\ \hline \multicolumn{3}{c}{\(\alpha=1\), \(\beta=1.11\), \(\gamma=0.45\), \(\delta=0.45\)} \\ \hline \multicolumn{3}{c}{\(k\)-IN} & 81.2\% & 18.8\% \\ \hline \multicolumn{3}{c}{\(\alpha=0.9\), \(\beta=1\), \(\gamma=0.45\), \(\delta=0.45\)} \\ \hline \multicolumn{3}{c}{\(k\)-IN} & 79.9\% & 21.1\% \\ \hline \end{tabular}
\end{table}
Table 1: Comparing the accuracy of the proposed \(k\)-IN with that of the supervised deep-CNN approach. Here, we found the accuracy of the proposed approach outperforms the deep-CNN.  
Figure 2: (**a**) Collection of raw CT-scan image samples of carbonate rock. The samples are grayscale images. (**b**) Sample raw CT-scan images. (**c**) Pre-processed CT-scan image samples with already marked boundary with red color.  
samples, problem definitions, and necessary geophysical properties of the respective rock sample (such as porosity, etc.).
* Information about the shape geometry of \(\mathcal{H}_{i}\) is extracted from the significant shape descriptors such as the shape boundary (sensing the abrupt change in the intensity level using intensity gradients), perimeter(\(\mathcal{H}_{i}\)), major(\(\mathcal{H}_{i}\)), minor(\(\mathcal{H}_{i}\)), shape variations of \(\mathcal{H}_{i}\) with respect to circle (\(\mathcal{V}_{c}(\mathcal{H}_{i})\)) and ellipse (\(\mathcal{V}_{c}(\mathcal{H}_{i})\)) of the same perimeters, etc. The induced logic to classify any \(\mathcal{H}_{i}\) as a pore or a fracture is discussed later in the current subsection.
# A Feasibility Study of the Drive-By Method for Damage Detection in Railway Bridges
## 3 Plan of the Simulations  
For a comprehensive assessment of the feasibility of the drive-by monitoring system, the dynamic response of the two types of trains is analyzed when crossing the four bridge models in different operational conditions. For each bridge/train couple, parameters such as train speed, sensor position, damage severity, and damage location are changed individually, to investigate the impact of each parameter on the performance of the algorithms for damage detection and localization. The last part of the simulations plan is aimed at evaluating possible aspects that may affect the feasibility of the method, such as track irregularity, ballast degradation, and the differences in the track stiffness that the train encounters when entering the bridge.
## 6 Numerical Results
### Linear Stability Analysis  
The modal properties of the undamped model were first analyzed. The first natural mode was found to be anti-symmetric (defined by Equation (11) for \(n=1\)) and the corresponding natural frequency is \(\omega=2.12\) rad/s. The second natural mode was found to be symmetric (defined by Equation (13) for \(n=1\)) and the natural frequency is \(\omega=3.91\) rad/s (see Figure 3).  
The critical conditions corresponding to the antisymmetric and symmetric modes are shown in Table 1. It is observed that the bridge galloped in its first antisymmetric natural mode, in corresponding of which the critical wind velocity assumed the minimum value \(U_{c}=34.13\) m/s.  
Since the critical velocities corresponding to the antisymmetric and symmetric modes were sufficiently far from each other, nonlinear interactions between modes, leading to multimodal galloping, were excluded.  
It was observed that the quasi-steady theory was valid in the case study considered. Indeed, the natural frequency of the first crosswind vibration mode was \(n_{0}=\omega_{c}/2\pi=0.33\) Hz, while the vortex-shedding frequency was \(n_{s}=1.02\) Hz at the critical galloping velocity \(U_{c}=34.13\) m/s, according to a Struhal number \(S_{t}=0.06\) (as indicated by [54] for a rectangular cross-section with a 2:1 aspect ratio) and a deck width of 2 m. Note that the quasi-steady theory worked mainly due to the narrow width of the cross section.
# A Novel Crowdsourcing-Assisted 5G Wireless Signal Ranging Technique in MEC Architecture
## 2 Background and Related Work
### Environment Perception Fingerprint Collection
#### 2.2.1 Traditional Street Scanning Method  
The traditional environment perception fingerprint acquisition method usually adopts the street scanning method, that is, to scan the signal ranging device and collect the wireless signal characteristics at each environment perception in the target area. This method requires a professional surveyor to remain at each environment perception for a period of time to ensure that a comprehensive wireless signal signature is gathered. However, due to the heavy workload and time-consuming nature of the process, this approach often struggles to achieve comprehensive data acquisition in practice, especially over large areas.
## 3 Results and Discussion
### Influence of Maximum Allowable Displacement Analyses  
To clarify the effect of allowable displacement on stand-up time, argillite stone was analysed with a set of input data expressed as Young's modulus E = 15.2 GPa; Poisson's ratio v = 0.3; GSI = 40; and tunnel depth H = 200 m. Values of allowable displacement varied in a range from 20 mm to 100 mm with a step of 20 mm. Figure 11 confirms the effect of the allowable displacement of tunnel walls on stand-up time. Accordingly, the increase in the values of the allowable displacement of tunnel walls results in the increase  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Rock Type** & \begin{tabular}{c} **Young’s Modulus** \\ **E, (GPa)** \\ \end{tabular} & \
\begin{tabular}{c} **Poison’s Ratio** \\ **v** \\ \end{tabular} \\ \hline \multirow{4}{*}{
\begin{tabular}{c} Aleurolite \\ (siltstone) \\ \end{tabular} } & 6.2 & 0.07 \(\div\) 0.40 \\ \cline{2-3}  & 14.0 & 0.28 \(\div\) 0.37 \\ \cline{2-3}  & 23.5 & 0.18 \(\div\) 0.32 \\ \hline \hline \end{tabular}
\end{table}
Table 4: General properties of material.  
Figure 10: Various values of stand-up time correspond to different qualities of rock using Young’s modulus.  
of stand-up time of unsupported tunnel spans. Thus, the values of allowable displacement strongly depend on the types of rock material surrounding the tunnel. To sum up, the findings are in agreement with those published in [3].