esa-sceva/satcom-chunk-collection huggingface dataset:
# A Comprehensive Failure Risk Assessment Method of
## 4 Comparison Analysis  
The comprehensive failure risk assessment method of the component failure mode of machining center based on topology analysis proposed in this paper is a dynamic model. The comprehensive failure risk value corresponding to each component can be obtained at any time, and the influence of propagation failure risk on the component is considered. To show its effectiveness and credibility, this paper takes the machining center running for 2000 and 3000 h as an example, gives the comprehensive failure risk value considering the propagation failure risk, compares it with the traditional independent failure risk value [35], and obtains a comparison chart of the ranking trend of component risk values at different times, as shown in Figure 13.  
Figure 12: Comparison chart of ranking trends for each risk value of the component at 4000 h.  
Figure 13: Comparison diagram of the ranking trend of component risk values at different moments.  
According to Figure 13, it can be found that the ranking results of the risk value of the machining center components are different at different times, and the comprehensive risk value ranking results of the components at 2000 h is \(M>J>S>W>K>V>L>NC>G\). That is to say, at 2000 h, the component with the largest risk of failure is the tool magazine (M), followed by the feed system (J), and the component with the smallest risk of failure is the pneumatic system (G). The independent risk ranking result obtained by the method that does not consider the propagation risk is \(M>J>W>K>V>L>S>NC>G\). At 3000 h, the comprehensive risk value ranking result is \(M>J>S>W>K>V>NC>G\). The independent risk ranking result obtained by the method that does not consider the propagation risk is \(M>J>W>K>S>V>L>NC>G\). This shows that, at 3000 h, the component with the largest risk of failure is the tool magazine (M), followed by the feed system (J), and the component with the smallest risk of failure is the pneumatic system (G). The method proposed in this paper is different from the traditional independent failure risk calculation method. The main reason is that this paper considers the influence of the topological characteristics of the component and the influence of the propagation failure risk. In addition, because the frequency ratio of failure modes and the failure rate are dynamically changing at different times, dynamic ranking results will be given, which is more in line with engineering reality; thus, the method proposed in this paper is effective and feasible.
## 3 Results  
### Study Selection, Risk of Bias, and Testing Overview  
A total of 2866 articles were identified through searches of PubMed, Scopus, and Web of Science databases. After removal of duplicates and title/abstract screening, 59 full-text articles were assessed for eligibility. Ultimately, 17 studies met the inclusion criteria and were included in this scoping review (Figure 1).  
\begin{table}
\begin{tabular}{l l l} \hline
**Database** & **Search String** & **Results Found** \\ \hline PubMed & (“Clear aligners” OR Invisualign OR thermoform* OR orthodontic* OR & \\  & “thermoplastic appliance*” OR “orthodontic retainer*” OR “orthodontic splint*”) & \\  & AND (“Flexural Strength”[MeSH] OR “three-point bending” OR “three point & \\  & bending” OR “four-point bending” OR “four point bending” OR “biaxial flexural” & \\  & OR “mechanical properties” OR “flexural modulus” OR “elastic modulus” & \\  & LANGUAGE (english) & \\ \hline Scopus & TITLE-ABS-KEY (“clear aligners” OR invisalign OR thermoform* OR orthodontic*) & \\  & AND TITLE-ABS-KEY (“flexural strength” OR “three-point bending” OR “three point bending” OR “four-point bending” OR “four point bending” OR “biaxial flexural” OR “mechanical properties” OR “flexural modulus” OR “elastic modulus”) & \\  & AND SUBJAREA (mater OR dent OR eng) AND DOCTYPE (ar) AND & \\  & LANGUAGE (english) & \\ \hline WoS & TS = (“clear aligners” OR Invisualign OR thermoform* OR orthodontic*) & \\  & AND & \\  & TS = (“flexural strength” OR “three-point bending” OR “three point bending” OR “four point bending” OR “biaxial flexural” OR & \\  & “‘‘mechanical properties” OR “flexural modulus” OR “elastic modulus”) & \\  & AND WC = (“Materials Science” OR “Dentistry, Oral Surgery \& Medicine”) AND & \\  & DT = (Article) & \\ \hline \end{tabular}
\end{table}
Table 1: Databases and search strings.  
Risk of bias was assessed using the QUIN tool. Fifteen studies were rated as having medium risk of bias, and two studies were rated as having high risk of bias. No studies achieved a low risk of bias score. Most studies clearly described their aims and applied appropriate statistical analyses, but many lacked details regarding operator training, outcome assessor information, randomization procedures, or blinding (Table 2).  
The 17 included studies were published between 2008 and 2024. All studies assessed the flexural properties of thermoplastic materials used in clear aligner therapy. Mechanical parameters evaluated included flexural modulus, elastic modulus, stress-strain behavior, stress relaxation, and yield strength. All studies employed three-point bending tests, with variations in equipment, deformation speeds, span lengths, and specimen preparation methods (Table 3).
## 3 Design and Operation of Microgrids
### Components and Configurations of MGs
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Type** & **Advantages** & **Disadvantages** \\ \hline \multirow{6}{*}{**Grid-Connected Microgrid**} & Can provide backup power during & \multirow{2}{*}{\begin{tabular}{c} Requires a reliable connection to the main \\ power grid. \\ \end{tabular} } \\  & \begin{tabular}{c} Can help reduce strain on the main power \\ grid during peak hours. \\ \end{tabular} & \begin{tabular}{c} May not be able to operate independently for \\ extended periods of time. \\ \end{tabular} \\  & Can be more cost-effective than islanded & May not be able to provide power to remote \\  & microgrids, as it leverages the existing grid & areas without additional infrastructure \\  & infrastructure. & investment. \\ \hline \multirow{6}{*}{**Islanded Microgrid**} & Can operate completely independently from & \multirow{2}{*}{\begin{tabular}{c} Requires significant upfront investment \\ in infrastructure. \\ \end{tabular} } \\  & \begin{tabular}{c} the main power grid, providing power in \\ remote areas. \\ \end{tabular} & \begin{tabular}{c} Requires significant upfront investment \\ in infrastructure. \\ \end{tabular} \\  & \begin{tabular}{c} May be less cost-effective than \\ grid-connected microgrids, as it requires its \\ own infrastructure. \\ \end{tabular} \\  & \begin{tabular}{c} Can potentially be more reliable than \\ grid-connected microgrids, as it is not \\ dependent on the main power grid. \\ \end{tabular} & \begin{tabular}{c} May be less reliable than grid-connected \\ microgrids if backup power sources are \\ not available. \\ \end{tabular} \\ \hline \multirow{6}{*}{**Hybrid Microgrid**} & Can provide backup power during & \multirow{2}{*}{\begin{tabular}{c} Requires a reliable connection to the main \\ power grid. \\ \end{tabular} } \\  & Can operate independently from the main & \multirow{2}{*}{\
\begin{tabular}{c} Requires a reliable connection to the main \\ power grid. \\ \end{tabular} } \\  &
\begin{tabular}{c} Can be more reliable than grid-connected \\ microgrids, as it has backup power sources. \\ Can be more cost-effective than islanded \\ microgrids, as it leverages both grid \\ infrastructure and its own infrastructure. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A general comparison table among different types of microgrids.
# Extensive Experiments on Opportunistic Routing in Wireless Sensor Networks
## 1 Introduction
### Source Coding  
In wireless network communications, faulty equipment, congested routers, collisions, interferences, etc. can lead to a partial or complete loss of packets. Conventional wireless communications deploy reliability improving techniques such as full data replication or on-demand retransmission. These techniques are too expensive or even not possible due to very strict energy constraints and asymmetric wireless channels. Erasure Codes (EC) allow to enhance the reliability of data transmissions by transmitting redundant data [16; 17; 18; 19]. Applying such methods in WSNs faces the challenge of supporting more or less complex methods for tiny sensors. A tradeoff between (i) reliability achieved, (ii) energy, and (iii) delay overhead is investigated in [16]. The result is that ECs improve the communication reliability considerably with a small delays increase. The same conclusion is proved by our experiments (see Section 5.7).  
Preliminary results of ODYSSE have been partially published in [20]. In this present paper, a theoretical model and an extensive experimental evaluation are enriching [20]. The contributions of this paper are of different nature: algorithm design, theoretical modeling and extensive experimentations. More specifically, the major contributions of this work and the structure of the paper are:1 Design of ODYSSE: a distributed and adaptive duty-cycle based opportunistic routing protocol in WSNs. To the best of our knowledge, it is the first work which combines opportunistic routing, duty cycle and source coding in real testbed (Section 3). In particular, we will show that adapting the duty cycle to the application scenario is an efficient strategy for energy conservation in WSNs.
2 Reliability enhancement based on LDPC erasure codes [21]. The erasure codes are used to enhance reliability. We will justify that increasing the code rate allows to approach 100% of reliability. As increasing the code rate is limited by the hardware capacity, we provide some guidelines to optimize the LDPC codes implementation (Section 3.7).
3 Modeling of the average waiting time for any forwarder. The finding is interesting: selecting the first awake forwarder (independently of the progress towards the source that it provides) is more delay efficient than waiting for more replies (from potential other forwarders closer to the source) (Section 4). We show that there is a match between theoretical and practical forwarders waiting time (Section 5.3).
4 Deployment of a real 45-arduino WMSN testbed in the large-scale testbed FIT IoT-LAB [22; 23]. ODYSSE is implemented and evaluated using this experimental platform (Section 5). Experimental results highlight that the mechanisms that ODYSSE includes fit very well. Also, the adaptiveness of the duty cycle outperforms the basic version (infrequent events and random duty cycle).
# Strategies to Combat Multidrug-Resistant and Persistent Infectious Diseases
## 2 New Anti-Infectious Treatments against MDR and Persistent Bacteria
### Anti-Virulence Compounds  
Anti-virulence compounds inhibit bacterial virulence factors, thus preventing the development of infection without affecting bacterial growth. In 2013, [PERSON] and colleagues characterized a chemical compound called BFs ((_Z_)-4-bromo-5-(bromomethylene)-3-methylfuran-2(5_H_)-one) that was able to reduce persistence of _E. coli_ growth and revert the antibiotic tolerance of persisters [34]. BF8 is a QS inhibitor of _E. coli_ which disrupts _E. coli_ biofilms and renders associated cells more sensitive to ofloxacin. BF8 appeared safe to mammalian cells in vitro and showed no long-term cytotoxicity in vivo in a healthy mouse model.  
In 2013, [PERSON] and colleagues developed an acyldepsipeptide antibiotic, called ADEP4, which can activate the ClpP protease and, thus, cause the death of persistent bacterial cells by degrading around 400 proteins [35]. In addition, this ADEP4 was also found to be active against persisters in both planktonic and biofilm states. A combination of ADEP4 with rifampicin completely killed _S. aureus_ biofilms in vitro and in a chronic infection murine model in vivo.  
The first compounds able to reduce the formation of antibiotic-tolerant persister cells of _P. aeruginosa_ were identified by [PERSON] and colleagues [36]. Some of these compounds, such as M64, blocked thesynthesis of both pro-persistence and pro-acute MvfR-dependent signaling molecules. MvfR, also referred to as PqsR, is the global virulence QS transcriptional regulator of _P. aeruginosa_. M64 was found to be active against MDR strains of _P. aeruginosa_ that cause acute and persistent murine infections and it did not perturb bacterial growth, which limited selective resistance.  
Regarding _E. coli_, [PERSON] and colleagues [37] demonstrated that the AcrAB-TolC apparatus in _E. coli_ increases the DNA mismatch repair system, promoting spontaneous mutations that can lead to high-level resistance to antibiotics. Thus, inhibitors of the AcrAB-TolC efflux pump could not only re-activate the antibiotic sensitivity of _E. coli_ cells but could also restore their mutation rates, potentially improving current treatments.
## 3 Methods
### Land Use and Land Cover Classification and Associated Changes  
#### 3.2.1 Specifications  
To support land use planning in the Dilijan National Park, the production of standardized land use and land cover (LULC) maps that show the current baseline and highlight past changes and trends was necessary. The production was divided into eight epochs-for each of these epochs a dedicated map was produced. Table 2 lists all of these epochs as well as the EO input data used for production.  
The target resolution of the final maps corresponds to the resolution of the EO data that was used as an input for the production of each year. However, for the most recent year (2019) two separate thematic maps were produced: Firstly, a map in 30 m to achieve better comparability to previous epochs and secondly, a 10 m map to facilitate a potential future Sentinel-2 based monitoring system of the national park, which would require a 10 m thematic map as a baseline. Furthermore, the minimum mapping unit (MMU) of objects on the ground was chosen based on the production year as well. The year 2019 was specified to have an MMU of 0.25 ha and all other years (based on Landsat) have an MMU of 1 ha.  
Finally, the thematic content of the maps was specified in accordance with the stakeholders and covers the following classes:  
1. Forest
2. Agriculture (arable land and pastureland)  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Epoch** & **Satellite Data** & **Resolution** & **Comment** \\ \hline
2019 & Sentinel-2 & 10 m & Most recent situation \\
2015 & Landsat 8 & 30 m & Use of Landsat 5 (due to Landsat 7 SLC error) \\
2010 & Landsat 5 & 30 m & Use of Landsat 5 (due to Landsat 7 SLC error) \\
2005 & Landsat 5 & 30 m & Use of Landsat 5 (due to Landsat 7 SLC error) \\
2002 & Landsat 7 & 30 m & Status change from state reserve to national park \\
2000 & Landsat 7 & 30 m & \\
1995 & Landsat 5 & 30 m & Armenian Independence \\
1991 & Landsat 5 & 30 m & Armenian Independence \\ \hline \hline \end{tabular}
\end{table}
Table 2: Production epochs for the LULC maps and input satellite data.  
Settlements
* 4. Primary roads
* 5. Bare soil
* 6. Other vegetated areas
* 7. Water bodies
* 8. Rivers
# Wireless Networks under a Backoff Attack: A Game Theoretical Perspective
## 4 Problem Modelling as a Static Game
### Problem Description  
We use the network scheme in Figure 2 to model the CSMA/CA problem that arises when some stations modify their backoff procedure. There will be \(n_{1}\) normal stations (NS), which always follow the binary exponential backoff; and \(n_{2}\) malicious stations (MS), which can choose between using the binary  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Value** & **Parameter** & **Value** \\ \hline \(T_{p,s}\) & 256 bits & \(T_{p,1}\) & 8184 bits \\ MAC header & 272 bits & PHY header & 128 bits \\ ACK & 112 bits + PHY header & RTS & 160 bits + PHY header \\ CTS & 272 bits + PHY header & Bit rate & 1 Mbps \\ \(\delta\) & 1 μs & \(T_{s}\) & 50 μs \\ SIFS & 28 μs & DIFS & 128 μs \\ \hline \hline \end{tabular}
\end{table}
Table 1: Values used for simulation 1.  
exponential backoff or the uniform backoff. We denote by \(n\) the number of stations, with \(n=n_{1}+n_{2}\). All \(n\) stations are connected to a gateway, called server, which forwards their packets to a network. The stations communicate with the server: we only consider the uplink in the problem. Observe that this problem arises in a situation in which a star topology is used. For convenience, we will denote the malicious stations as clients.  
The players of the game will be the server on one side, and the clients on the other. Thus, there will be \(N_{p}=n_{2}+1\) players (where \(N_{p}\) denotes the number of players). Each client tries to maximize the throughput available to it, whereas the server tries to enforce that all stations in the network obtain a fair throughput. By fair, we mean that no station is getting a higher throughput at expense of others. Under the saturation condition imposed before, this means that all clients receive the same proportion of the total throughput.  
The clients will have two different actions: either they behave selfishly (\(s\)) by using the uniform backoff or they do not behave selfishly (\(ns\)) by using the binary exponential backoff. The server will also have two actions: it can detect (\(d\)) if the network throughput is begin fairly distributed or not to detect (\(nd\)). If the server detects and catches a client behaving selfishly, it will drop its packet, as a punishment. This means that the client has to send again the packet, and the higher throughput advantage it had obtained by modifying its backoff vanishes. We must also take into account that this detection procedure cannot be free of charge for the server: there must be a cost associated to the detection procedure in terms of computational resources. Two of the possible schemes that could be used to detect this selfish behavior are [12], which is based in Kolmogorov-Smirnov (K-S) statistics, and [11], which is based on a modified Cramer-von Mises (C-M) test [25]. To simplify the modellinfg, we will assume that the server is able to perfectly detect when a station behaves selfishly.
# Numerical 3D Modeling: Microwave Plasma Torch at Intermediate Pressure
## 3 Governing Equations
### Ambipolar Diffusion  
The particles of plasma diffusion were divided into two categories: ambipolar diffusion of charged particles (electrons, ions) and the diffusion of neutral particles or atoms. Among them, ambipolar diffusion is a unique characteristic of plasma; this movement occurs near the solid surface bordering the plasma, which controls the disappearance process of charged particles. In the initial free diffusion process, the electron diffuses much faster than the atom; thus, it reaches the vessel wall first and makes it negatively charged. Therefore, there are an equal amount of positive space charges in the plasma, causing charge separation. The positive and negative charges appear in pairs and produce a radial electric field pointing to the wall of the container. The radial electric field can inhibit the flow of electrons to the vessel wall and promote the ions to move toward the vessel wall, inhibiting the free diffusion of electrons and ions.  
The ambipolar diffusion coefficient is expressed by Equation (16):  
\[D_{a}\ =\ \frac{\mu_{\rm i}D_{\rm e}+\mu_{\rm e}D_{\rm i}}{\mu_{\rm i}+\mu_{ \rm e}} \tag{16}\]  
where \(\mu_{\rm i}\), \(\mu_{\rm e}\), \(D_{\rm i}\), and \(D_{\rm e}\) denote the ion mobilities, electron mobilities, ion diffusion coefficients, and electron diffusion coefficients, respectively. For a weakly ionized discharge, because \(\mu_{\rm i}\)<<\(\mu_{\rm e}\), use of the [PERSON] relation expressed by Equation (17):  
\[D_{\rm a}\approx D_{\rm i}(1+\frac{T_{\rm e}}{T_{\rm i}}) \tag{17}\]
# Robust and Reconfigurable On-Board Processing for a Hyperspectral Imaging Small Satellite
## 3 On-Board Processing Unit Design
### Hardware Design
The PC also has a high-speed connection to the S-band radio for faster downlink than from any other subsystem via the Controller Area Network (CAN) bus, and contains storage to which data can be buffered to from other subsystems. The power to all subsystems including the payload is controlled by the EPS.
# Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid
## 5 Experiments
### Characterizing Flexible Loads  
For the implementation of the DR programs, it is necessary to distinguish loads that are flexible and, therefore, manageable, from those that are not flexible. In residential environments, loads that may be considered flexible include:  
* Heating and cooling units
* Washing machines
* Dryers
* Dishwashers
* Water heaters  
while in the category of non flexible loads fall:  
* Lights
* Air circulation pumps for AC
* Televisions and decoders
* Computers
* Fridges and freezers  
The management of flexible loads such as washing machines and dishwashers is easily achievable (e.g., through smart plugs). The controlled interruption of the air conditioning units for short time does not have a particularly negative influence on perceived comfort conditions: switching off the heating and/or cooling for small periods does not produce an abrupt change in temperature in the rooms, but a gradual change which can be corrected as soon as the air conditioning system is reactivated. In residential buildings, there is a multiplicity of other electrical loads that are, however, discontinuous and are active for short intervals of time; their extreme variability makes them impossible to be included in the list of flexible loads. For other commercial buildings, the loads that may be considered flexible are only the AC units.  
The traces described in Section 5.2 have been divided between flexible and non-flexible load shares. The construction of such load profiles was carried out considering the average power absorbed by flexible (FLEX) loads and for non flexible loads (NOFLEX). Knowing the FLEX/NOFLEX load  
Figure 6: Total wind and solar energy production during a week.  
diagrams, it is then possible to use the traces to test PP-Overgrid applying the DR program to the flexible power only.  
Energy consumption often exhibits regular patterns, with similar daily and weekly patterns. In our experiments, we assumed that every 15 min the DSO checks the energy production and requests from the PP-Overgrid users a modification (up or down) in the global power consumption of the grid. We then simulate the behavior of the nodes (each with a different amount of flexible power) responding to the power change requests made by the DSO.
## 3 Analysis of Results for Optimal Model
### Result of Optimal Design Specification  
The results of the optimized LPM design under the conditions of Table 1 are presented in Table 2. The optimal design process, using LPM and the genetic algorithm, was carried out for a total of 250 generations with 50 individuals per generation. FEM analysis was performed at the optimal point, which is the maximal-efficiency point analyzed via LPM using the selected final model. In addition, FEM analysis was performed at the operating point in Table 1 to check whether the design requirements were satisfied. As a result, the efficiency at both analyzed points satisfied the requirement of \(\geq\)95%, and the analyzed torque at the design point was 17.2 Nm, which was larger than the reference torque of 16 Nm. The analytical result at the optimal point of LPM and the FEM analytical result were similar, thereby verifying the validity of the optimal design result. To compare with the experimental results, FEM analysis was also performed at the test point, and results are presented in Table 3.