esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Fault Case Analysis
### External and Internal Leakage of Actuator  
As shown in Figure 17, leakage is one of the most prevalent failure types for actuators. Progressive failure is inherent in this process and cannot be avoided. In the description of the bathtub curve, it belongs to transition duration from the random failures period to the wearout period. Generally, it can be controlled by increasing tightness and performing regular inspections [51, 52]. The red dotted line in Figure 17 represents the leakage flow. Leaks can be internal or external. External leaks occur between the piston rod and cylinder, while internal leaks occur between the cylinder and piston. Consider the extension of a piston rod as an example. Flow loss occurs between these two kinds of gaps when high-pressure hydraulic oil forces the piston out of the actuator cylinder.  
Figure 17: Basic principle of actuator leakage.  
As shown in Figure 14, the fault simulation method of external leakage is to connect the oil return chamber of the actuator with the oil tank, and control the leakage amount through the adjustable flow valve. By the same token, the internal leakage is simulated by connecting the pressure chamber of the actuator and the oil return chamber in series through the adjustable flow valve. The larger the opening of the adjustable flow valve, the larger the leakage, and the larger the corresponding leakage liquid resistance.  
\[\left\{\begin{array}{ll}x_{Ex-l}=0.05+0.05(t-2)&2\leq t\leq 15\\ x_{In-l}=0.02+0.01(t-2)&2\leq t\leq 15\end{array}\right. \tag{38}\]  
where, \(x_{Ex-l}\) and \(x_{In-l}\) are the opening of the adjustable flow valve simulating external leakage and internal leakage, respectively. \(x^{\prime}\) range is 0 to 1.  
Figure 18a shows that the residual \([r_{1}\prime]\) exceeds the interval type (IT) lower threshold at 5.38 s, and external leakage of actuator cylinder is successfully diagnosed. However, the residual \([r_{1}\prime]\) does not exceed the absolute type (AT) lower threshold not tested, resulting in missed diagnosis. Figure 18c shows that the residual \([r_{3}\prime]\) exceeds the IT lower threshold at 8.32 s, and internal leakage of actuator cylinder is successfully diagnosed. However, the residual \([r_{3}\prime]\) does not exceed the AT lower threshold not tested, resulting in missed diagnosis.  
The residuals \([r_{2}\prime]\) and \([r_{4}\prime]\) in Figure 18b and d are basically no different from the normal operation of the system, which proves that the two threshold methods do not cause misdiagnosis. This also corresponds to \(\beta\) = [1,1,0].
# Application of Polymers as a Tool in Crystallization--A Review
## 2 Basic Research
### New Materials
#### 3.3.3 Miscellaneous Applications  
Recent years have shown that polymers are the most investigated materials for application in the biomedical field. Thus, it is good to mention publications in which polymers prevented or induced controlled crystallization of inorganic and low molecular weight organic compounds. [PERSON] et al. performed the experiments in which amorphous Ca\({}_{3}\)(PO\({}_{4}\))\({}_{2}\) composite was formed in the synthetic PEG-based hydrogel matrix [111]. Such composites are promising biomaterials to replace human and animal-derived bone scaffolds. [PERSON] et al. investigated confined crystallization of inorganic compounds performed in bowl-shaped polymeric stomatocytes compartments which provided shielding from the electron beam destroying effects during TEM experiments [112]. [PERSON] et al. used photochemical polymerization to obtain well-defined PVP copolymers to test the impact of hydrophobicity on ice recrystallization inhibition in a polymer system [113]. The obtained results can help to design new polymers for cryopreservation applications. [PERSON] et al. in their experiments have grown zinc oxide nanorods on the biodegradable PLA substrates using a low-temperature solution (70 \({}^{\circ}\)C) growth method. The obtained results can be useful in the preparation of environmentally friendly food packaging with antibacterial properties [114].  
As was mentioned earlier, the influence of polymers on crystallization of other polymers is a very broad field; therefore, in this review just one exemplary publication was referred in order to give the reader the full picture of the topic. The same situation concerns the application of polymers in the crystallization of proteins. This phenomenon is very popular and intensively researched nowadays. Therefore, in order to give just the glimpse of the eye for the interested reader, a few publications will be mentioned here. Namely, [PERSON] and [PERSON] in their review paper presented the role of molecularly imprinted polymers (MIPs) as nucleation-inducing substances for protein crystals [115]. [PERSON] et al. demonstrated the fabrication of hydrogel membranes displaying controlled chemical composition and nanostructure in the creation of crystals with enhanced diffraction properties at a lower protein concentration than the conventional technique [116]. [PERSON] et al. used ionic-liquid hydrogel composite membranes as material for supporting protein crystallization [117]. They proved that protein crystallization by ionic-liquid hydrogel composite membranes had the potential for biotechnological applications and could contain crystallized enzymes in working conditions. Moreover, [PERSON] wrote a review paper highlighting the relationship between polymeric surfactants' properties and their ability in designing nanomorphology [118]. Such an approach can be implemented to prepare biologically sustainable nanomaterials for use in nanomedicine.
## 2 Materials and Methods  
### General Procedures  
All commercially available solvents and reagents--thiophene-2-carboxaldehyde, 98+%; pyridine-4-carboxaldehyde, 97%; and furan-2-carboxaldehyde, 99%--were purchased from Alfa-Aesar (Heysham, UK). Reference compounds alendazole, \(\geq\)98% and ivermectin were obtained from Sigma-Aldrich (Steinheim, Germany). The course of reactions and the purity of products were tracked by thin layer chromatography (TLC) on pre-coated silica gel plates ALUGRAM SIL G/UV254, 0.20 mm thick (Macherey-Nagel, Duren, Germany), in benzene/methanol (3:1, \(v/v\)) as eluent and visualized using UV light (CAMAG UVLamp 4, Muttenz, Switzerland). The melting points (mp) were determined using an Electrothermal AZ 9000 3 MK4 apparatus (Stone, Staffordshire, UK) and were uncorrected. Infrared (IR) spectra of the compounds in a solid state were obtained on a Bruker Tensor 27 FT spectrometer (Billerica, MA, USA) in ATR (attenuated total reflectance) mode with a diamond crystal accessory. The spectra were referenced to air as a background by accumulating 64 scans, at a resolution of 2 cm\({}^{-1}\). Air was used as the background reference, and spectra were collected by averaging 64 scans at a resolution of 2 cm\({}^{-1}\). The \({}^{1}\)H and \({}^{13}\)C NMR spectra were acquired at room temperature (303 K) using a Bruker Avance 400 MHz spectrometer (Billerica, MA, USA) with DMSO-d\({}_{6}\) as the solvent. Chemical shifts (\(\delta\)) are reported in parts per million (ppm). Coupling constants J are given in Hertz (Hz), and spin multiplicities are given as singlet (s), broad singlet (br s), doublet (d), doublet of doublets (dd), triplet (t), triplet of doublets (td) and multiplet (m). The mass spectra were recorded using a Thermo Scientific Q Exactive Plus Hybrid Quadrupole-Orbitrap Mass Spectrometer (Waltham, MA, USA) Thermo Scientific (HESI HRMS) in positive mode. The spectra were processed using the Thermo Scientific FreeStyle program version 1.8 SP1 (Thermo Fisher Scientific Inc., Waltham, MA, USA). The microanalyses for C, H, and N were performed on PerkineElmer elemental analyzer, and satisfactory results within \(\pm\)0.4% calculated values were recorded for the novel compounds.
## 3 Application Scenario and System Model
### System Model
#### 3.2.2 Threat Model  
A threat appearance means its detection by a sensor node. The threats may be static or mobile, depending on the application semantics. If mobile, they are considered to move with a constant speed, but different threats may have different speeds. Mobile threats may also randomly change the direction of their movement. The appearance of threats is defined by either a given arrival probabilistic model or a deterministic model describing specific conditions of appearance.
# Systematic Evaluation of LibreSocial--A Peer-To-Peer Framework for Online Social Networks
## 5 Evaluation of Results
### Baseline Tests: Plugin Analysis
#### 5.1.3 Message and Data Rates Characteristics
The plugin actions in this class are associated with Filestorage, Forum, Photo, Voting and Wall plugins. Of particular interest is the Forum, Photo voting and wall plugins because they use DDSs to store data. Most of the plugin actions in this category make repeated calls for the DDSs relating to the data requested with each call resulting in significant messaging as the entire DDS is retrieved. 3. High message and high data rates: These tests have the largest overall impact on the message and data rates. The message rates range from 500 to slightly less than 23,000 messages/sec. The highest data rates recorded is 51.98 Kb/s observed for the plugin Filestorage store files action in the 500 node test with light workload. The actions in this classification are associated with Filestorage, Forum, Group, Messaging and Livechat. The actions, such as store files by the Filestorage plugin, or send message by the Messaging plugin generate high messages as well as data because they use DDSs. LibreSocial's modular design, which allows separation of the various OSN functions into plugins (or bundles) from the P2P core service components, supports the implementation of SkyEye [38; 39], a tree-based monitoring solution. From the collected monitoring statistics, it is demonstrated that there is a smooth synergy between the application layer and the underlying components, seen by the effect of each plugin on the data and messaging rates. The worst case test completion times for each plugin action are tolerable being on average about 7.5 and 11 secs/action for the light and medium loads irrespective of the network size. These times may be caused by the replication factor value and lower times can be anticipated with lower replication factor values, although such a move may significantly affect the retrieval times as will be demonstrated in the replication test (Section 5.4). The message and data rates are dependent on the plugin action performed. Actions that require storage of significant data tend to generate more messages as well as data overall, such as uploading files or photos. Also because of the manner in which DDSs are stored (distributed across the network), there is a significant messaging as the DDS items are being retrieved, which is expected. This interaction renders the conclusion that the storage mechanism composed of both the PAST for simple files as well and the DDS for complex data types, coupled with the caching and replication, integrate well within the application. With a maximum recorded network data rate 51.98 and 48.75 Kb/sec for the light and medium load tests, we believe that the network is capable of handling more and can easily scale up.
## 6 Discussions and Conclusions  
The microdrilling of fused silica using D-shaped PCD tools was carried out in order to produce microholes. In this study, it was found that the peak thrust force was related to edge chipping. Therefore, we had to decrease the peak thrust force (F\({}_{peak}\)) in order to achieve good edge quality. Compared to a cylindrical tool, a D-shaped tool was effective in reducing peak force and improving chip-discharge efficiency. In addition to the tool's shape, the surface roughness of the tool was also an important factor for reducing peak force. As the surface roughness of the tool increases, the peak thrust force decreases significantly. A variable feedrate was used to improve drilling speeds. A low feedrate was applied at the beginning of drilling to prevent edge chippings, and then a high feedrate was applied to increase drilling speeds. Consequently, drilling times could be reduced by 77% with maintaining edge quality. As the number of drillings increased, the surface of the tool became smoother and the thrust force increased. To make a rough surface again, EDM dressing was conducted. After dressing, the surface became as rough as that of a new tool, and thrust forces decreased. Electroplated microdrills also can be used to drill microholes in glass materials [14; 17]. However, when electroplated abrasives are worn out, the tool cannot be used any more. In this study, since the tool's shape is very simple and has a D shape, it is easy to regenerate the tool's bottom surface by EDM dressing and this can  
Figure 13: (**a**) Thrust force according to the number of drillings and (**b**) dressing process using WEDG (drilling conditions: axial feedrate 10 \(\upmu\)m/s; rotational speed of 50,000 rpm; dressing conditions: 100 V, 470,000 pF).  
increase the tool's life. In addition, D-shaped tools having a flat bottom can be used not only in drilling but also in milling. It is expected that microholes and microchannels in glass-based microfluidic devices can be produced with a single PCD tool.  
Conceptualization and methodology, B.H.K. and P.A.L.; formal analysis, B.H.K. and P.A.L.; writing--original draft preparation, B.H.K.; writing--review, B.H.K.; supervision, B.H.K.; funding acquisition, B.H.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Technology Innovation Program (20010984) funded by the Ministry of Trade, Industry and Energy (MOTIE), Korea.  
Not applicable.  
The authors declare no conflicts of interest.
## 5 Proposed Model
### Fuzzy-Logic Based Movement Decision
Figure 5: Example of selecting the next movement of the MA. where \(A\) and \(B\) are the linguistic values defined by the fuzzy sets on the ranges \(x\) and \(y\)[27]. The following Table 6 defines the fuzzy if-then rules. Figure 6 plots the degree of Membership, in the range of 0 to 1, versus the chance values of FLPPL. \begin{table}
\begin{tabular}{c c c c} \hline
**RSSI** & **Neighbours** & **Distance** & **Chance** \\ \hline Weak & Low & Far & Very Weak \\ Weak & Low & Medium & Weak \\ Weak & Low & Near & Little Weak \\ Weak & Medium & Far & Weak \\ Weak & Medium & Medium & Little Weak \\ Weak & Medium & Near & Little Medium \\ Weak & High & Far & Little Weak \\ Weak & High & Medium & Little Medium \\ Weak & High & Near & Medium \\ Medium & Low & Far & Little Weak \\ Medium & Low & Medium & Little Medium \\ Medium & Low & Near & Medium \\ Medium & Medium & Far & Little Medium \\ Medium & Medium & Medium & Medium \\ Medium & Medium & Near & High Medium \\ Medium & High & Far & Medium \\ Medium & High & Near & Little Strong \\ Strong & Low & Far & Medium \\ Strong & Low & Medium & High Medium \\ Strong & Low & Near & Little Strong \\ Strong & Medium & Far & High Medium \\ Strong & Medium & Medium & Little Strong \\ Strong & Medium & Near & Strong \\ Strong & High & Far & Little Strong \\ Strong & High & Medium & Strong \\ Strong & High & Near & Very Strong \\ \hline \end{tabular}
\end{table} 
Table 6: The Fuzzy rules of if-then. Figure 6: Output membership function of FLPPL. Therefore, the complete system model of FLPPL consists of three inputs with three membership functions and nine degrees of chance as shown in Figure 7.
## Appendix A Repeat Ground Tracks  
A satellite's angular speed and its orbit orientation is a function of time and orbit parameters describing the orbit shape and size. The time derivatives of the satellite speed and the orbit orientation are used to define the repeat ground track (RGT) ratio, as shown in Equation (A1).  
\[\tau=\frac{N_{S}}{N_{D}}=\frac{T_{G}}{T_{S}}=\frac{2\pi/\Big{(}\omega_{E}-\hat{ \Omega}\Big{)}}{2\pi/\Big{(}\dot{M}+\dot{\omega}\Big{)}}=\frac{\dot{M}+\dot{ \omega}}{\omega_{E}-\hat{\Omega}}=\frac{n+\Delta n+\dot{\omega}}{\omega_{E}- \hat{\Omega}}\] (A1)  
where \(N_{D}\) is the repeating cycle length in days, Ns is the number of satellite revolutions made the during that repeating cycle, \(T_{G}\) is the nodal period of Greenwich, \(T_{\rm S}\) is the orbital period of a satellite. The orbital rates are defined as follows: \(n\) is the mean motion of a satellite, \(dM/dt\) ( \(=n+\Delta n\)) is the perturbed mean motion, \(d\omega/dt\) is the drift rate of the argument of perigee, due to perturbations, \(\omega_{\rm E}\) is the rotation rate of the Earth, and \(d\Omega/dt\) is the nodal regression rate. Based on the definition of \(n=(\mu/\dot{a})^{1/2}\), these orbital rates are represented as the sum of a periodic term and a secular term each:  
\[\frac{\dot{\Omega}}{n}=-\frac{3J_{2}R_{E}^{2}}{2p^{2}}c-\frac{9J_{2}^{2}}{4p^{ 4}}c\bigg{[}\bigg{(}\frac{3}{2}+\frac{1}{6}e^{2}+e^{\prime}\bigg{)}-\bigg{(} \frac{5}{3}-\frac{5}{25}e^{2}+\frac{3}{2}e^{\prime}\bigg{)}+O\bigg{]},\] (A2)  
\[\frac{\dot{\omega}}{n}=\frac{3J_{2}R_{E}^{2}}{2p^{2}}\bigg{(}\frac{5}{2}s^{2}- 2\bigg{)}+\frac{9J_{2}^{2}R_{E}^{4}}{p^{2}}\bigg{[}\bigg{(}4+\frac{7}{12}e^{2} +2e^{\prime}\bigg{)}-s^{2}\bigg{(}\frac{103}{12}+\frac{3}{8}e^{2}+\frac{11}{2} e^{\prime}\bigg{)}+O\bigg{]}\] (A3)  
\[\frac{\Delta n}{n}=\frac{3J_{2}R_{E}^{2}}{2p^{2}}\bigg{(}1-\frac{3}{2}s^{2} \bigg{)}e^{\prime}+\frac{9J_{2}^{2}R_{E}^{4}}{4p^{2}}\bigg{[}\frac{1}{2}\bigg{(} 1-\frac{3}{2}s^{2}\bigg{)}^{2}e^{\prime}+\bigg{(}\frac{5}{2}+\frac{10}{3}e^{2} \bigg{)}-s^{2}\bigg{(}\frac{19}{3}+\frac{26}{3}e^{2}\bigg{)}+O\bigg{]},\] (A4)  
where \(s=sin\), \(s=sin\)\(i\), \(p\), and \(e^{\prime}=(1-e^{2})^{1/2}\). The symbol \(O\) represents higher-order terms depending on \(e^{4}\) and \(J_{4}/J_{2}{}^{2}\) which may be omitted for near-circular, Earth-centric orbits. Also, the second terms in the above equations negligible compared to the first terms for short-duration missions.
# Testing an \"IoT\" Tide Gauge Network for Coastal Monitoring
## 2 IoT Tide Gauge Network Design
### In-Water Pressure Sensor  
A Blue Robotics two-bar pressure and temperature sensor [19] was used for measuring water depths (see Figure 2b). It is based on the Measurement Specialties MS5837 2 BA gel-filled, compact, water-resistant sensor [20]. This is a low current (0.6 uA) 24-bit digital output I\({}^{2}\)C device. The sensor has a quoted 10-bar maximum mechanical pressure, with a standard operating pressure of 0-2 bar, giving an equivalent measuring range of 10 m of seawater (water depth pressure plus atmospheric pressure) with a water depth resolution of 0.16 mm. The Blue Robotics two bar sensor, although relatively expensive at E\(\sim\)70 when compared to buying just the pressure sensor (\(\sim\)E4), was chosen for testing since it was already fully waterproof and ready for installation. The pressure sensor was tested in the lab with a 4 m vertical tube of fresh water and performed within \(\pm\)1 cm when varying the water levels.
## 3 Path Model Design  
The main contribution of this paper is to design an effective path model for the mobile anchor node to acquire the locations of unknown nodes in the area. A preliminary and final model have been proposed to reach the final required goal. The proposed paths were designed to achieve the following:  
1. High localization accuracy;
2. Full coverage area;
3. Low power consumption;
4. Solving the problem of collinearity.  
The challenges of the first depend on many criteria, such as the environmental characteristics, indoor or outdoor, and the path trajectory model of the mobile anchor node. The second achievement is very important as the mobile node trajectory must ensure that the whole area of the network is reached; to achieve that goal, suitable paths were chosen to guarantee that all the unknown nodes receive at least three different messages from the mobile anchor node. The low power consumption challenge mainly depends on the path length, the obstacles that it needs to turn around, and the number of pausing points it stops at.  
To solve the problem of collinearity, the value of \(x\)-axis parameter is checked for each pausing point, which is used to obtain the location of the unknown node. If it is the same value, we replace any pausing point with another one that has a different \(x\)-axis value. The same process is carried out for the \(y\)-axis value parameter.  
Wireless sensor network model assumptions:  
1. The unknown nodes are spread in fixed locations.
2. Each node has a determined communication range which differs depending on the surrounding criteria.
3. The mobile anchor node traverses through the network deterministic path. It can move around any obstacle it meets through its journey.
4. The mobile anchor sends messages at each pausing point it rests at, and the unknown nodes in its scope receive the messages from it.
5. The mobile anchor node can determine its position at each pausing point.
6. The unknown node can compute its position via the position information from three different mobile node positions.
## 4 Data Analysis and Results  
This study utilized the two-stage methodology recommended by [61] for data analysis. The first step assessed reliability and construct validity, while the second examined the structure model among the latent constructs. Partial Least Squares (PLS) regression was used as the structural equation modeling tool, because it imposes minimum restriction on measurement scale, sample size, and residual distribution [62] SmartPLS Version 2.0 M3 [63] was used in our data analysis.
# Analysis of Bidirectional ADR-Enabled Class B LoRaWAN Networks in Industrial Scenarios
## 4 Adaptative Data Rate Implementation  
The proposal of this work is to enable the ADR mechanism for the previously mentioned deployment of LoRaWAN ns-3 modules provided by the authors of [8], which is the only one found supporting class B devices in the network. Some assumptions have been made in order to simplify the deployment at this point. While the standard ADR mechanism includes increasing or decreasing the transmission power when no DR change can be made according to Equations (1) and (2), this deployment starts with devices configured to transmit at maximum power, which is 14 dB according to regulations for the band used.  
This deployment assumes that no changes will be made to this parameter during operation.  
Regarding the downlink messages, acknowledgments in the destined windows RX1 and RX2 as defined in class A devices are disabled, as all downlink traffic is to be done during the beacon window defined by class B device operation.  
The ADR mechanism implemented establishes the number of message samples to calculate the maximum SNR as a variable that can be changed (SNR sample counter or \(SNR_{\kappa\kappa}\)), in order to test the implications of reducing this parameter, which affects the time it takes for a node to change its SF and therefore can have implications for the packet delivery ratio (PDR) and energy consumption. The typical value of \(SNR_{\kappa\kappa}\) in ADR implementations is 20 according to standard recommendations, which is why it has been used to illustrate Figures 5 and 6.  
The proposal of the ADR mechanism for downlink in class B devices addresses the energy optimization topic, which is always subject to improvements. The selection of class B is motivated by application requirements in some industrial scenarios, which require periodic and guaranteed downlink traffic, but this worsens the energy consumption with respect to class A devices, which can last longer by disregarding gateway- or application-initiated transmissions.  
The implementation tested shows the possibility of enabling an ADR mechanism on the gateway side, which means following the same scheme as regular ADR, the gateway uses the SNR of received messages to check if the channel conditions allow for higher DR/lower SF. It assumes that the gateway informs the node of the new SF for downlink messages on the first next class B slot available and then changes the SF accordingly for subsequent messages. Therefore, if DR for downlink messages is optimized, the sleeping times of devices can be increased and thus battery life can be increased.