esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Test Results and Analysis
### Hysteresis Characteristics  
Hysteresis curves from the test are shown in Figure 7, where F represents the horizontal load and \(\Delta\) represents the horizontal displacement. Figure 7 shows the following:  
(1) The hysteresis curve for each specimen is full and spindle-shaped. There is no notable pinching, and the hysteresis performance is stable.  
(2) Before the lateral drift increases to \(1/250\), the hysteresis curve of each specimen essentially changes linearly, and there is no residual deformation after the load is removed. This means that the specimen is in an elastic state. When the horizontal lateral drift increases gradually and the horizontal load is reduced to zero, the displacement becomes non-zero, which means that the specimen develops residual deformation at this moment.  
(3) The loading and offloading curves in the first cycle and the second cycle of the same grade lateral drift for each specimen essentially coincide, which means that the accumulated damage of each specimen is small.  
(4) Specimens CFST-DT and CFST-MC have fuller hysteresis curves and higher bearing capacities.  
Figure 6: Failure modes of specimens. (**a**) failure of CFST-N; (**b**) detailed measurement of CFST-N; (**c**) failure of CFST-HS; (**d**) detailed measurement of CFST-HS; (**e**) failure of CFST-VS; (**f**) detailed measurement of CFST-VS; (**g**) failure of CFST-SR; (**h**) detailed measurement of CFST-SR; (**i**) failure of CFST-DT; (**j**) detailed measurement of CFST-DT; (**k**) failure of CFST-MC; and (**l**) detailed measurement of CFST-MC.  
Figure 7: _Cont._Skeleton curves of specimens are shown in Figure 8. Before the horizontal force of each specimen reaches 0.6 times the peak load, the skeleton curve is approximately linear. After the horizontal force exceeds 0.6 times the peak load, the specimen is in a completely elastoplastic state, and the skeleton curve becomes nonlinear. After the horizontal force reaches the peak load, the skeleton curve of each specimen enters a declining section; however, the declining section of each specimen has a different degradation speed. Specimen CFST-N has the fastest degradation speed in the declining section. When the lateral drift reaches 1/25, the bearing capacity has dropped to 62.8% of the peak load. Specimen CFST-MC has the slowest degradation speed in the declining section. When an identical lateral drift is reached, the bearing capacity decreases to 88.4% of the peak load. The test results show that the axial load ratio is a major influence factor on the specimen degradation speed in the declining section. When the axial load ratio is higher, the second-order effect has a greater impact on the bending resistance and stability of the structure. At the later stages of loading, specimen CFST-N shows severe local buckling of the steel tube base, and the bearing capacity declines rapidly.  
Figure 7: Measured and FEA model load versus displacement relations. (**a**) CFST-N; (**b**) CFST-HS; (**c**) CFST-VS; (**d**) CFST-SR; (**e**) CFST-DT; and (**f**) CFST-MC.
## 4 Conclusions  
Mg- or Zn-doped GaN films were obtained via radio-frequency magnetron sputtering on silicon substrates at room temperature, using laboratory-prepared targets with Mg-doped or Zn-doped GaN powders. X-ray diffraction patterns showed the possible presence of nano-crystallites with an average of 7 nm for the GaN films, which could be related to the peaks broadening. SEM micrographs for the GaN films demonstrated good adherence to  
Figure 10: Raman scattering of the Zn-doped GaN films deposited by radio-frequency magnetron sputtering.  
Figure 9: Raman scattering of the Mg-doped GaN films deposited by radio-frequency magnetron sputtering.  
silicon non-native substrate, as well as homogeneity. X-ray photo-electron spectroscopy for the GaN films showed the presence of a small amount of magnesium (2.10 mol%), and zinc (1.15 mol%) with binding energies of 1303.18, and 1024.76 eV, respectively. Additionally, TEM micrographs demonstrated a homogeneous crystalline growth and the obtaining of a GaN hexagonal structure. The resistivity values obtained (057 \(\Omega\)cm for Mg-doped GaN films, and 0.45 \(\Omega\)cm for Zn-doped GaN films), are approximated to the literature values for p-type GaN films. Photoluminescence spectrum for the Zn-doped GaN films had energy emissions located in a range from 2.89 to 3.0 eV (429.23-413.50 nm), which was related to excitons bound to the Zn acceptors. On the other hand, Mg-doped GaN films showed emission in the blue-violet band with a range from 2.80 to 3.16 eV (443.03-392.56 nm), which was related to the recombination of the deep donors of gallium vacancies occupied by magnesium atoms (MgGa), with acceptors MgGa. The results showed by XPS, TEM, resistivity, and photoluminescence might be an indicator of the obtaining of p-type samples.  
Conceptualization, E.G.; methodology, software, formal analysis, investigation, writing--review, G.G.; validation, A.M.H.; investigation, writing--original draft preparation, C.M.; funding acquisition, project administration, supervision, R.G.; resources, G.A.H.; resources, E.R.; resources, J.A.L.: software, M.R.; validation, J.A.R.; validation, Y.D.R.; formal analysis. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability StatementData is contained within the article.  
The authors gratefully acknowledge the technical support of CNyN-UNAM for the characterizations performed, particularly to [PERSON], [PERSON], [PERSON], and [PERSON]. This research was partially supported by CONACyT (Mexico), CIDS-ICUAP-BUAP, and UTPuebla.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Cooking Loss and Texture Profile Analysis  
Cooking losses are presented in Table 11, and significant differences (\(p<0.001\)) were observed between treatments. Samples in the HF6 treatment exhibited higher cooking losses compared to samples in the HF0 and HF4 treatments, which showed similar losses. The increased cooking losses in the samples from the HF6 treatment might be attributed to their lower sodium chloride content, resulting in reduced solubilisation of myofibrillar proteins [75]. However, unlike the findings of the present study, the addition of hempseed cake in meat balls, chicken meat sausages, and pork meat burger patties, as well as the addition of hemp flour in pork meat loaves, resulted in lower cooking losses [17; 18; 19; 20]. [PERSON] et al. [20] attributed reduced cooking loss to dietary fibre from hempseed meal and linked lower cooking losses in meat balls to the poor protein solubility of hemp cake. [PERSON] et al. [19] attributed the lower grilling losses observed in their study to the protein content of hemp-based products.  
In texture profile analysis, hardness, springiness, cohesiveness, gumminess, and chewiness are examined. The hardness value represents the peak force obtained during the initial compression of a product. Springiness, also referred to as elasticity, indicates how well a product rebounds physically after being deformed during initial compression. Cohesiveness indicates a product's ability to withstand a second deformation relative to its behaviour during the first deformation. Gumminess (hardness \(\times\) cohesiveness) and chewiness (gumminess \(\times\) springiness) are described as the energy required to chew a product [20; 76]. As shown in Table 11, the addition of hemp flour significantly affected (\(p<0.001\)) hardness, while there was a moderate effect (\(p<0.05\)) on cohesiveness and gumminess. Springiness and chewiness were not affected by the addition of hemp flour (\(p>0.05\)). [PERSON] et al. [18] reported higher but not significantly different hardness values in cooked meat balls containing increasingly higher levels of hemp cake. The same authors found that the other examined parameters, i.e., springiness, cohesiveness, gumminess, and chewiness, were not affected by enrichment with hemp seed cake. Similarly, [PERSON] et al. [17] reported that the incorporation of hemp flour led to an increase in the firmness of pork meat loaves, while the other textural characteristics remained unaffected. On the other hand, [PERSON] et al. [20] found that addition of increasing amounts of hemp seed meal resulted in lower hardness values in cooked chicken sausage. Additionally, the other textural characteristics were similarly affected. All the cited researchers [17; 18; 20] reported that changes to texture profile depend mainly on the amounts of and interactions between all components in the meat batter as well as water binding components such as protein and dietary fibre.
# Marine Internet for Internetworking in Oceans: A Tutorial
## 5 Internetworking Strategies of Marine Internet
### Reliable Backup with Satellites  
Both ICNs and WANETs are working well in water areas near coastlines, which are just very small portion of the ocean. For example, the water area 100 km away from the coastline only accounts for 9.6% of the ocean surface, as mentioned above. For marine Internet users sparsely distributed in remote water areas, the basic communication services for security and distress rescue operation as well as maritime production should be guaranteed. Since satellites are the only option available now in this situation, they can be used as a reliable backup solution for emergency when no other networks are available. For big buyers, satellites can be a reliable solution of pervasive Internet access anytime, while probably as the last option for other users.
## 3 CFD Simulations
### CFD Results
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Position** & **Angle [\({}^{\circ}\)]** & **TM0 Mean Residence Time (s)** & **TM75 Mean Residence Time (s)** \\ \hline
0 & – & 16.98 \(\pm\) 1.83\% & 21.26 \(\pm\) 5.32\% \\
1 & 0 & 65.70 \(\pm\) 0.71\% & 70.34 \(\pm\) 2.03\% \\
2 & 45 & 65.99 \(\pm\) 0.98\% & 69.69 \(\pm\) 2.12\% \\
3 & 90 & 67.89 \(\pm\) 0.95\% & 69.61 \(\pm\) 2.05\% \\
4 & 135 & 68.27 \(\pm\) 0.89\% & 70.31 \(\pm\) 1.89\% \\
5 & 180 & 70.55 \(\pm\) 0.54\% & 71.50 \(\pm\) 1.75\% \\
6 & 225 & 68.81 \(\pm\) 0.47\% & 72.75 \(\pm\) 1.69\% \\
7 & 270 & 67.98 \(\pm\) 0.44\% & 71.49 \(\pm\) 1.92\% \\
8 & 315 & 66.13 \(\pm\) 0.42\% & 71.66 \(\pm\) 1.95\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Impact of the injection position on the mean residence time. Positions of injections 0–8 are depicted on Figure 11. In all cases, samples of 500 particles reflecting the Rosin–Rammler distribution parameters determined in the experimental part were injected at the liquid surface in a circular area around the corresponding points. Figure 10: Dependency of the mean residence time with respect to the position angle (see Figure 11 on the left) along the perimeter of circle with 3/4 of the vessel radius. The inlet flow rate used to obtain these data in CFD simulations was 0.5 L/s. When searching for an optimum (maximum) mean residence time, we might be interested in the radial coordinate as well. Figure 12 shows such dependency of the mean residence time at angular position, corresponding to point 5 in Figure 11. The mean residence time is monotonically decreasing towards the center of the fish tank. In addition, Figure 13 illustrates CFD results describing the impact of the pellet's density on the mean residence time of the pellets injected at position 5 (see Figure 11). It is clear that, for densities closer to the density of water (998.2 kg/m\({}^{3}\) in our simulations), the mean residence time increases substantially. Therefore, if there is a need for a particular residence time, such dependency could provide necessary information. For different geometrical and operating parameters, we can expect similar results, even though quantitatively different. Figure 12: Dependency of the mean residence time on the dimensionless radial position (angular position corresponds to point 5). The inlet flow rate used to obtained these data in CFD simulations was 0.5 L/s. Figure 13: Dependency of the mean residence on the density of pellets for both types of pellets, TM0 and TM75. The injection position corresponded to number 5 (see Figure 11), that is on the opposite side of the water inlet. The inlet flow rate used to obtain these data in CFD simulations was 0.5 L/s.
# A Decentralized Framework for Managing Task Allocation in Distributed Software Engineering
## 3 The Proposed Task_Auc_ Framework  
The process of task allocation is of substantial importance for the research and industry practitioners. Blockchain is an open and distributed ledger that holds transactional records, ensuring security, transparency, and decentralization. Each block consists of the cryptographic hash of the previous block, a timestamp, and a set of transactions, and a nonce in the block header. All transaction records (current and previous) are stored in the crypto currency. A smart contract, which is a piece of the computer program, is built on top of crypto currencies, allowing users to write and execute contracts on the blockchain.  
Smart contract execution needs a certain amount of gas that is to be purchased using Ether. The behavior of a smart contract is determined by the execution flow of the source code. This execution is triggered by a transaction consuming gas that is converted into the amount of Ether, charged as the transaction fee. The outline of the proposed Task_Auc_ approach is sketched in Figure 1. The task auction and allocation is performed in a decentralized manner, where all the communication and coordination is conducted using a blockchain. The project manager (representing the organization) will be responsible for announcing the tasks through the auction process, checking the validity of bids, bids' evaluation, and winner announcement using smart contracts that do not involve any third-party dependence. The proposed framework models developers as bidders. A bid in this system refers to an offer made by a developer to show his/her willingness to take up the particular task. On the other hand, a bidder is the person (here, developer) who has presented the bid. Project managers or organizations who/which are willing to distribute or allocate tasks are modeled as auctioners, and developers who are willing to pick tasks of their preference are modeled as bidders. Once the task to be distributed is identified, the project manager broadcasts it with essential information. The developers can then decide and make an informed decision according to their preferences. With the use of the blockchain technology, developers can make the most of their effectiveness by keeping minimum interaction and communication with the project managers.
## 3 Results
### Characteristics of the Water Vapour and Liquid Water  
The integral water vapour content in the atmosphere and the liquid water content in the cloud can lead to refraction, scattering, and the attenuation of radio waves in the atmosphere. Therefore, the detection of water vapour and liquid water content in the atmosphere is not only of great significance in the fields of active detection, aerospace, and satellite communication, but also has guiding significance and application prospects in short-term weather forecasting and artificial modification. In Figure 8, the _PWV_ had no obvious change during the daytime from 11:00 to 17:00 (UTC+8). The average _PWV_ values for clear-sky and snowy-sky conditions were 0.40 cm and 0.44 cm, with related RMSE biases of 0.04 cm and 0.03 cm, respectively. For the time period before 11:00, the _PWV_ continuously increased as the run raised, which can be attributed to water vapour condensing as longwave radiation spread outward from the ground during the daytime. As the sun went down, _PWV_ values gradually decreased by approximately 0.1 cm. Compared with [PERSON] et al. [31], the _PWV_ values in sunny and precipitation (or snow) environments in winter only accounted for 26.70% and 18.33% of the corresponding values in the summer monsoon. Similarly, the _LWC_ in winter was one order of magnitude lower than the average in summer. The peak value of _LWC_ on snowy days appeared several hours after the sun rose and before the sun set, namely, 14:00 and 17:00 (UTC+8). The extreme _LWC_ value on snowy days was approximately 0.11 mm.  
Figure 7: Statistical characteristics of stability indices (from 8:00 to 20:00 monsoon) season under different weather conditions. (**a**) _CAPE_, (**b**) _DCAPE_, (**c**) _CIN_, (**d**) _MVV_. The \(t\)(h) is expressed in UTC+8.
## 2 Materials and Methods
### Pre-Emptive Braking Control
#### 2.4.1 Expectation Speed  
The desired speed while cornering is the maximum speed at which the centrifugal force required for the motorcycle to navigate the turn does not exceed the maximum lateral force provided by the road. Assuming constant speed and ideal road conditions, the motorcycle is simplified as a rigid body, neglecting lean angle, tire nonlinearity, and suspension variations. According to the principle of force balance, the centrifugal force acting on the wheel is given by (6), where \(m\) is the mass of the motorcycle, \(V\) is the speed, and \(R\) is the turning radius. The maximum lateral force, determined by the road friction, is expressed in (7). By combining (6) and (7), the desired speed for navigating a curve with radius \(R\) can be derived in (8).  
\[F_{c}=\frac{mV^{2}}{R} \tag{6}\]  
\[F_{y}=\mu mg \tag{7}\]  
\[V_{r}=\sqrt{\mu gR} \tag{8}\]  
Here, \(\mu\) represents the road friction. When calculating the maximum safe speed for a motorcycle in a corner, the basic centrifugal force equation overlooks several nonlinear aspects of motorcycle dynamics. Motorcycles typically lean into corners to counteract centrifugal forces, and this lean angle influences the distribution of lateral forces and tire grip. Tire type and condition, as well as suspension stiffness and damping, significantly  
Figure 5: Dual PID control.  
influence lateral friction and motorcycle stability. Considering these neglected factors, the actual safe speed may be lower than the calculated value.
# Fault Tolerant DHT-Based Routing in MANET
###### Abstract
\begin{table}
\begin{tabular}{p{113.8 pt}|p{284.5 pt}} \hline
**Term/Symbol** & **Description** \\ \hline Anchor Node (AN) & A node that holds the mapping information of other nodes. A source node has to retrieve the mapping info. from the AN before initiating a data session with destination. Any node in the network can act as AN. \\ \hline Logical Identifier(LID) & A unique ID that identifies a node in the logical structured network and, represents the node relative position in the logical structure. \\ \hline Logical Space (LS) & The LIDs are drawn from the LS. The LS represents a range of valid LIDs and forms a structured logical network i.e., tree, chord etc. \\ \hline Logical Space Portion (LSP) & Nodes in the logical network maintain a disjoint portion of LS called LSP. The LSP denotes relative position of a node in the logical network and acts as LID. \\ \hline Mapping Information/Index Information & The mapping info. (i.e. (UID), LID) pair) provides mapping between permanent identifier (IP/MAC) and LID. The mapping information are maintained at AN. \\ \hline Logical Network (LN) & The interconnection of nodes based on their LIDs is called logical network. \\ \hline Store Mapping Info. (SMI/SII) packet & After computing LID, a joining node stores its mapping information on AN by forwarding SMI packets in the network. \\ \hline Universal Identifier (UID) & A unique identifier of a node that remains constant in the network life time. UID can be the IP or MAC address. \\ \hline Mapping Request (MREQ) packet & A source node retrieves the mapping info. from the AN by sending MREQ packets in the network. \\ \hline Mapping Reply packet (MREP) & The AN shares the requested mapping info. by sending MREP packet. \\ \hline N(v) & It represents 1-hop neighbors of node v excluding node v, called open neighborhood of node v. \\ \hline N[v] & It shows 1-hop neighbors of node v including node v, called close neighborhood of node v. \\ \hline LSR & It stands for Lookup Success Ratio. \\ \hline E2E & E2E stands for End-to-End lookup delay. \\ \hline \end{tabular}
\end{table} 
Table 1: Definitions/Abbreviations used in DHT routing.
## 3 Results and Analysis
### Wear Resistance Test of Boronizing Layer  
Table 9 shows the mass loss of the boronizing samples in friction and wear test for the three cases (single boronizing, rare earth boronizing, rare earth boronizing, rare earth boron-chromium co-boriding). Test force: 100 N, rotating speed: 200 r/min, test time: 60 min, record the sample mass loss data every 10 min. It can also be seen from Table 8 that the mass loss of the single boronizing sample is the largest, and that of the rare earth boron-chromium co-boriding is the smallest.  
Among them, in the 60 min wear time, the mass loss of single boronizing is 22.3 mg, that of rare earth boronizing is 9.2 mg, and that of rare earth boron-chromium co-infiltration is 6.1 mg. Among them, the mass loss of single boronization is 3.7 times that of boron-chromium rare earth co-infiltration, and 2.4 times that of rare earth boronization, which shows that the wear resistance of rare earth boron-chromium co-infiltration is relatively better. This is due to the fact that the addition of rare earth increases the activity of boron atoms, which provides a channel for the active boron atoms to diffuse into the material, thereby improving the boronizing efficiency. And at the same time, Cr\({}_{2}\)O\({}_{3}\) strengthens the metal bonds in the local area of the B-B atomic bond, which improves the quality of the boronizing layer. is improved, thereby improving the wear resistance of the boronizing layer.