esa-sceva/satcom-chunk-collection huggingface dataset:
# Airline Network Planning Considering Climate Impact: Assessing New Operational Improvements
## 3 Results
### ATRISO Scenario  
Besides incorporating the ATR20 in the objective function, ISO operation is also considered in this scenario. The same set of KPIs is used in this case, and only the KLM and TAP networks are considered. The pair-wise comparison was implemented for ATRISO versus ATR. The yearly aggregated results are presented in Figure 6.  
This case study reveals that ISO implementation can provide environmental and operational benefits to airlines. For KLM, operating ISOs causes the network's total ATR20 and ATR100 to be decreased, as depicted in Figure 6. Moreover, ISOs can help airlines expand their network and serve more ODs without adding more aircraft. KLM has a 5% reduction in ATR20 with no significant profit changes compared to the ATR scenario. However, additional take-offs and landings cause a 5-10% increase in HC and CO. Conversely, the TAP study shows a slight increase in ATR20 and ATR100 after incorporating ISO OIs into its network planning process. The observed rise is not directly due to implementing ISOs, but rather a network expansion, resulting in more flights, passengers, and ODs served, as presented in Figure 6b. While a higher number of flights would increase ATR20, ISO OI helps to mitigate most of the effect. Similarly to KLM, TAP experiences a peak in CO and HC due to ISO implementation. The most frequently used ISO airports are GUU, TOF, and BXR for the KLM and CVU and MVF for the TAP case study. A list of candidate ISO airports which are more frequently visited on a weekly basis is reported in Tables A1 and A2 for representative airlines.  
In the TAP case study, the similar relative increase amount in the px served, px connected, and seats offered suggests that the extra capacity which is provided at the network level by introducing the ISO flights is almost fully used to transport additional passengers. The increase in the RPK also shows that ISO flights can improve the revenue at the network level as the narrowbodies could operate on a route which was only possible using a widebody.  
Based on the results shown in Tables 2 and 3, it appears that the total percentage of ISO-adopted routes is constrained by the extra DOC associated with it. Our analysis indicates that ISO flights are more frequently scheduled in S-high than in S-Low due to the higher average airfares during the former season. Additionally, we found that implementing ISO using a narrowlyod aircraft is more likely to be feasible from a DOC perspective than with a widebody aircraft, as the additional cost is significantly lower. In the other words,  
Figure 6: Average annual changes in the KPIs for ATRISO compared to ATR: (**a**) assessment of the climate KPIs (%); (**b**) assessment of the non-climate KPIs (%).  
constraints at the network level determine where and when an ISO would be feasible and significantly affect the implementation results.
# Equivalent Circuits for Microwave Metamaterial Planar Components
## 4 Experimental Determination of the Metamaterial Nature of a Resonator
The above considerations are a confirmation that a nominal fractal or metamaterial-inspired structure needs to be examined in detail, including the entire geometry, to confirm the possible metamaterial response because other details, like the feeding line, the boundaries, and the coupling mechanisms, in the case of multiple resonators, are essential components of the entire framework. In particular, when many resonators are coupled together, the importance of the feeding line decreases, leading to a vanishing \(Im(Z_{2}^{\prime})\), like in the case of an ordinary resonating structure.
# Image Motion Measurement and Image Restoration System Based on an Inertial Reference Laser
## 3 Image Motion Measurement System and Experimental Environment  
### Image Motion Measurement Experimental System  
The principle of the image motion measurement experimental system based on an inertial reference laser is shown in Figure 3. The simulated image target was placed on the focal plane of the collimator to simulate a target at infinity. After being illuminated by the integrating sphere, the image target was imaged on the CCD by the camera optical system. The parallel light pope and image target were installed on a vibration isolation platform to isolate the influence of ground micro vibrations and to ensure the stability of the target light. The camera system (including the inertial reference laser unit) was installed on a 6 degrees of freedom platform to simulate the free boundary state of the camera on orbit, and the simulated micro vibrations generated by the vibration exciter were applied to the camera.  
The main lens of the camera used in the experiment had an optical aperture of 330 mm and focal length of 3300 mm. The CCD resolution was 1024 \(\times\) 1024 pixels with a pixel pitch of 12 \(\upmu\)m. Figure 4 shows that the camera was integrated with an inertial reference laser unit, a corner cube prism, and a PSD. To verify image motion measurement accuracy, an additional Hartmann wavefront sensor was integrated, which could directly measure image motion by imaging the sub-aperture image at a high speed and by calculating the offset of each frame. The root mean square (RMS) value of the image motion measurement accuracy of the Hartmann wavefront sensor was higher than 0.1 pixels.  
Figure 4: 3D model of the camera.  
Figure 3: Schematic diagram of the image motion measurement system based on an inertial reference laser.
## 3 The Proposed Local-Moment-Driven Robust Reversible Data-Hiding Scheme
### Embedding Method
#### 3.1.1 Checkboard Scanning Based Pixel Grouping Using Local Moment  
For embedding the secret data, the image (\(I^{MSB}\)) is partitioned into equal-sized non-overlapping blocks, preferably of \(3\times 3\) pixels, starting from pixel position \((2,\ 2)\) to \((h-1,w-1)\). Then, \(x\)-set pixels (orange color shown in Figure 1 such as \(S_{x}=\{x_{1},\ x_{2},\ x_{3},\ x_{4},\ x_{5}\}\)) of the first block are segregated into two groups that are based on the local moment of each pixel, and moment-of-moment of the block, using the following Equations (8)-(10), respectively.  
\[\mu_{i,j}=\left[\frac{1}{4}\big{(}y_{i,j-1}+y_{i-1,j}+y_{i,j+1}+y_{i+1,j}\big{)}\right] \tag{8}\]  
Here, \(y_{i,j-1},\ y_{i-1,j},\ y_{i,j+1},\ \text{and}\ y_{i+1,j}\) are the surrounding pixels for the reference pixel, e.g., \(x_{i,j}\), for which the local moment (\(\mu_{i,j}\)) is calculated. For example, the local moment (\(\mu_{3}\)) for pixel \(x_{3}\) can be calculated as follows when the pixels are numbered as in Figure 1:  
\[\mu_{3}=\left[\frac{1}{4}(y_{1}+y_{2}+y_{3}+y_{4})\right] \tag{9}\]\(y_{1}\), \(y_{2}\), \(y_{3}\), and \(y_{4}\) are the surrounding pixels for the reference pixel (\(x_{3}\)) as per Figure 1. Next, the moment-of-moment of the block (\(B_{k}\)) can be calculated using Equation (10) as follows:  
\[\Omega_{k}=\left[\frac{1}{N}\sum_{m=1}^{M}\mu_{m}\right] \tag{10}\]  
where \(N\) denotes the count of pixels in the \(x\)-set of the block (\(B_{k}\)) and \(m\) denotes the \(x\)-set pixel number of \(B_{k}\) when the pixels are scanned in raster-scan manner. Next, the \(x\)-set pixels of \(B_{k}\) are tagged and grouped into two groups, \(F_{G}\) and \(S_{G}\), by using Equation (11).  
\[x_{m}=\left\{\begin{array}{ll}F_{G},&\text{if }\mu_{m}<\Omega_{k}\\ S_{G},&\text{else}\end{array}\right. \tag{11}\]  
Therefore, every pixel (\(x_{m}\)) from \(S_{x}\) of \(B_{k}\) is grouped either into the first group (\(F_{G}\)), when the local moment (\(\mu_{m}\)) is less than the moment of moment (\(\Omega_{k}\)) for the \(S_{x}\), or into the second group (\(S_{G}\)) as per Equation (11). Next, the embedding of secret information in each of the groups (\(F_{G}\), \(S_{G}\)) is carried out using the embedding strategy introduced in Section 3.1.2. The process of grouping and embedding is repeated for the \(y\)-set pixels (white color shown in Figure 1 such as \(S_{y}=\{y_{1}\), \(y_{2}\), \(y_{3}\), \(y_{4}\}\)) with the updated block. Embedding in each and every block of the image, the marked-MSB plane (\(I^{tMSB}\)) is obtained, which is concatenated with \(I^{LSB}\) to obtain the final stego-image (\(I^{\prime}\)).
## 1 Introduction
Notably, ZIF-8, which was obtained by the reaction of Zn\({}^{2+}\) with 2-methylimidazole as linker, has gained great interest in membrane utilization due to its high chemical and thermal stability [14; 15; 16]. [PERSON] et al. added 0.4 % (w/v) ZIF-8 nanoparticles to a TFN membrane with an 162% permeance increase while maintaining a high salt rejection [17]. However, the interfacial nanogaps that were present in the functional layer of the decorated membrane cannot be fully avoided [18]. ZIF-8 has a small aperture with a size of 3.4 A and a comparatively large cavity with a size of 11.6 A [19]. The small aperture of ZIF-8 can serve as an effective filter to separate hydrated cations of Mg\({}^{2+}\) (4.28 A) through a size sieving effect [20; 21]. Although there is a significant variation on the reported values of hydrated Na\({}^{+}\) (between 2.99 and 3.58 A), in general, the hydrated cations with larger crystal radii have weaker hydration shells, so that the detachment of the hydration shell would occur when ions pass the solution-membrane interface [22; 23]. Consequently, ZIF-8 has the right size to separate dehydrated Na\({}^{+}\) (0.95 A) and hydrated Mg\({}^{2+}\)[24; 25]. Different from the previously reported strategy to form a dense cationic charged layer by chemical modification, this study presents an interfacial polymerization strategy with nanoparticles to separate monovalent and multivalent ions. Porous ZIF-8 was used as a nanofiller underneath the surficial functional layer to separate monovalent ions. The influence of the ZIF-8 content on the desalination performance was explored to determine the optimal preparation parameters.
## 4 Evaluation and Result
### Test Bed  
A test bed was configured to verify the performance of the proposed design schemes. Figure 10 shows a schematic of the test-bed configuration, and Figure 11 shows an image of the actual configuration. For a BER Tester (BERT), the ONT-606 was used. The ONT-606 is an optical network test apparatus that can transmit actual data using the embedding optical transceiver, can be tested from the physical layer to the medium access control(MAC) layer, and can only be tested by connecting data signals to an external evaluation board. Two 25 Gbps BERT electrical channels are connected via cable to the transmission and receive connectors of the QSFP28 evaluation board. The QSFP28 evaluation board includes a cage section capable of carrying the QSFP28 type optical transceiver, a high-speed data line capable of transmitting four channels of 25 Gbps signals, and switches for controlling QSFP28 hardware pins. A temperature chamber was used to verify the environmental stability of the fabricated QSFP28 optical transceiver. The test temperature is 0\({}^{\circ}\) to 70\({}^{\circ}\) based on the optical transceiver case temperature. Furthermore, the interface device enables the PC to act as a host system using the I2C interface for testing the optical transceiver. The interface device interconnects the I2C interface and USB serial communications. Additionally, we implemented the host graphical user interface(GUI) program for testing. Kerterex USB-910H of KETEREX Integrated was used as the interface device [21].  
The QSFP28 optical transceiver is embedded on the evaluation board for the long-distance transmission test, and self-loopback is tested using a 40 km single mode fiber (SMF) cable. The PAM4 optical transmission signal of the QSFP28 optical transceiver used to measure and optimize another PAM4 optical transmission signal was also measured using a wideband oscilloscope with a built-in photo-to-electric converter. The firmware design then tested whether the QSFP28 optical transceiver reliably drives the detailed components and operates in accordance with the standards. In addition, a performance reliability evaluation was ensured by conducting tests within the industrial temperature environment required by the standard using a temperature chamber.  
Figure 8: QSFP28 fabricated PCB with mounted parts.  
Figure 9: QSFP28 optical transceiver case housing.
## 2 Materials and Methods
### Spectral Preprocessing Methods  
The noise caused by the equipment and the interference of the fluorescence background in the Raman signal could affect the detection results. Therefore, five pretreatment methods were applied to preprocessing the original Raman spectra in this paper [19]. Among them, the Savitzky-Golay (S-G) smoothing algorithm uses a weighted average method to quantify the data in the moving window by polynomial least squares fitting, which emphasizes the central role of the center point [20]. The basicidea of the multiplicative scatter correction (MSC) algorithm is to use an ideal spectrum to represent the spectrum of all samples and to correct the original spectra with the slope and intercept of linear equations [21]. The principle of the standard normal variation (SNV) algorithm is that the scattering intensity values of each wavelength point satisfies a certain distribution in each spectrum, and the spectral correction was carried out according to this assumption [22]. The idea of the de-trending (DT) algorithm is that the spectral absorbance and wavelength are first fitted into a trend line \(d\) according to the polynomial; then, the trend line \(d\) is subtracted from the original spectra \(x\) to achieve the effect of this trend [23]. The first-derivative can eliminate the interference from other backgrounds and distinguish the overlapping peaks in the spectrum, which improves spectral resolution, sensitivity, and the signal-to-noise ratio of the spectra to a certain extent [24].
## 2 Methodology and Materials
### Optimization Method
#### 2.7.1 Data Processing  
The data processing is performed by designing an LSTM model corresponding to data sequence (\(x\)) and time step (\(t\)). The LSTM algorithm is chosen due to its memory cell architecture that retains information over longer sequences and avoid issues such as vanishing gradients, making it ideal for capturing long-term dependencies in highly dynamic and nonlinear datasets. With this, the sampling frequency of LSTM input data is specified ten second over one year. From Figure 5, data analysis is performed using the LSTM parameters of operation block: memory cell \(c\), and hidden cell \(h\), input gate (\(i_{t}\)), forget gate (\(f_{t}\)), input node (\(g_{i}\)), and output gate (\(o_{t}\)). Output response \(o_{t}\) is calculated by Equations (12) to (16) at time \(t\)[36].  
\[f_{t}=\sigma\Bigl{(}w_{fx}x_{t}+w_{fh}h_{t-1}+b_{f}\Bigr{)} \tag{12}\]  
\[i_{t}=\sigma(w_{ix}x_{t}+w_{ih}h_{t-1}+b_{i}) \tag{13}\]  
\[g_{t}=\tau\Bigl{(}w_{gx}x_{t}+w_{gh}h_{t-1}+b_{g}\Bigr{)} \tag{14}\]  
\[c_{t}=c_{t-1}\odot f_{t}+g_{t}\odot i_{t} \tag{15}\]Here, \(w\) and \(b\) are weighted vectors and bias of the particular gates, \(\odot\) presents elementwise/dot multiplication; \(\sigma\) and \(\tau\) are sigmoid and tangent activation functions respectively.
## 3 Methods
### Control Barrier Function  
Control barrier functions are generally used for guaranteeing safety. CBF formulates safety by ensuring the invariance of a particular set, meaning staying within this safe set. Specifically, we examine a set denoted as \(\mathcal{C}\), which represents a superlevel set of a continuously differentiable function \(H(x)\).  
**Definition 2** ([38]).: _Consider a continuously differentiable function \(H(x):\mathbb{R}^{n}\rightarrow\mathbb{R}\) with the following properties:_  
1. _The zero-superlevel set of_ \(H(x)\) _is denoted as_ \(\mathcal{C}\)_, i.e.,_ \(\mathcal{C}=\{x\mid H(x)\geq 0\}\)_._
2. \(\
abla H(x)\) _is nonzero for all_ \(x\) _on the boundary of_ \(\mathcal{C}\)_, which is denoted as_ \(\partial\mathcal{C}\)_._ _If there exists a coefficient_ \(\mu\)_, i.e.,_ \(\mu>0\)_, that satisfy the following constraint:_ \[\sup_{u\in\mathcal{U}}[\dot{H}(x,u)+\mu H(x)]\geq 0\] (8) _for all_ \(x\in\mathcal{C}\)_, then, the function_ \(H(x)\) _is termed a Control Barrier Function, and any Lipschitz continuous control law_ \(u\) _that satisfies the above constraint will render the set_ \(\mathcal{C}\) _safe, meaning that it is control invariant._  
Noting that the derivative of the Barrier function \((H(x))\) function is:  
\[\dot{H}(x,u)=L_{f}H(x)+L_{g}H(x)u \tag{9}\]  
Both CLFs and CBFs are continuously differentiable functions. However, they serve distinct purposes. CLFs are mainly used to ensure system stability. On the other hand, CBFs are designed to enforce safety constraints to ensure that the system remains within safe regions of the state space.
# MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks
## 4 Proposed Mitigation Mechanism for Jamming Attacks
### Routes Reconfiguration
The DSR routing protocol was specifically designed to be used in Mobile Ad hoc Networks (MANETs) and makes the network self-organizing and self-configurable, and implements two mechanisms to discover and maintain routes from source to destination: Route Discovery and Route maintenance. The AODV routing protocol was designed for Ad Hoc networks and only maintains the route information that needs a node to determine the next-hop, but not the entire route; it is based on the information that nodes have about their active neighbors. The mechanisms in AODV used to discover and maintain the routes are: Route request, Route reply, Route error and Route reply. In contrast, the MPH protocol is a proactive protocol that does the reconfiguration of routes through hierarchies, starting from a root node. In this way, nodes establish new links by exchanging hierarchy values to establish relationships between parents and children. The maintenance of routes is carried out by discovery packets of neighbors for each period of time previously established. Modifications for the AODV and DSR protocols resulting in the modified AODV-M and DSR-M protocols are shown in Algorithm 3. Where AODV is when the Route Discovery is Hop-by-Hop and DSR is Source Routing; AODV-M and DSR-M is reflected in the Detection testing algorithm step. Modifications for the MPH protocol resulting in the modified MPH-M protocol are described in Algorithm 4. Again, MPH-M is reflected in the Detection testing algorithm step. Figure 2: Coverage range of the jammer node and its influence in its neighbors. ```
for each node \(i\)do  Node \(i\) turns on;  SEND HELLO packet;  RECEIVE ACK packet;  Detection testing algorithm (Algorithm 2); if TRAFFIC packet then ifNode \(i\) does not have this route then  Route discovery;  SEND RREQ packet;  RECEIVE RREP packet; else  Route maintenance;  SEND TRAFFIC packet;  end if if  a CONTROL packet is received from Node \(j\) then  REMOVE Node \(j\) from neighbor table;  else  DO nothing;  end if if a route expires then  SEND RERR packet; else  DO nothing;  end if  end for
```  
**Algorithm 3**The proposed modified protocols: AODV-M and DSR-M.  
```
for each node \(i\)do  Node \(i\) turns on; \(Discovery.time=0\);  SEND HELLO packet;  RECEIVE ACK packet;  Detection testing algorithm (Algorithm 2); if\(Discovery.time\%10==0\)then ifNode \(i\) does not have this route then  Route discovery;  SEND HELLO packet;  RECEIVE ACK packet; else  DO nothing;  end if ifTRAFFIC packet then ifNode \(i\) does not have this route then  SEND TRAFFIC packet to its parents; else  SEND TRAFFIC packet to specific parent;  end if if a CONTROL packet is received from Node \(j\)then  REMOVE Node \(j\) from neighbor table; else  DO nothing;  end if
```  
**Algorithm 4**The proposed modified protocol: MPH-M.
# Security Assessment of Agriculture IoT (AIoT) Applications
## 5 Discussion  
The following questions need to be discussed, and answers can be found by further research. Additional threat analysis work is necessary to identify existing and new vulnerabilities in agriculture.  
What are the special vulnerabilities and cyber threats in agriculture that are not known and covered in this form by the IACS domain experience? The answer to this question defines (a) the need of a totally new cybersecurity standard for agriculture or (b) indicates that adaptions and extensions of already well-known cybersecurity standards will be sufficient. From our point of view, a dedicated cybersecurity standard for agriculture will be necessary, because of the totally different security conditions on the field segment and the farm segment in comparison to that of the security situation, provided by a well observable plant building.  
The future problem is not the theft of a single field device and its subsequent manipulation for cybercriminal activities. Much more, there will be many IoT devices in the field in future installations which offer an attractive base for botnets. Because even the simplest sensor will contain a powerful processor with its own OS and extensive additional functions, these field IoT devices will require periodic software updates, which can be carried out using Over-the-Air (OTA) programming techniques.  
Using Single Sign-On (SSO), Multi-Factor Authentication (MFA), and access broker structures to hide the real data storage location. An access broker reduces the attack surface to a very restricted system access port. A well-established approach of such a data access philosophy is provided by the MQTT protocol, which supports a publish-subscribe network protocol. The data exchange is only possible via an access broker, which authorizes the data traffic and monitors the data flow (intrusion detection).
# Characterization and Use of Char Produced from Pyrolysis of Post-Consumer Mixed Plastic Waste
## 2 Materials and Methods
### Adsorption Tests  
#### 2.4.1 Experimental Procedure  
For adsorption tests, the lead stock solution was first prepared by diluting appropriate quantity of lead nitrate salt in deionized water until the concentration of 500 mg/L was obtained. Afterwards, dilution was made to prepare 50 mL of a 10 mg/L lead solution. Then, the diluted solution was added to the reactor, which was connected to a pH meter, stirred at 300 rpm and maintained at room temperature. The pH was adjusted to 5 by using a 0.1 M HCl solution. Then, 0.05 g of char was added to the lead solution and pH was controlled to avoid it increases over 6-6.5 (above this value the chemical precipitation of the metal in the form of hydroxide occur). Preliminarily tests (here not included) were performed at different operation times (5, 15, 30, 60, 120 and 240 min) to choose the time at which equilibrium was reached. According to the results of these experimental experiments no differences between samples collected at 120 and 240 min was observed. Therefore, a time of 120 min was left to elapsed, which is sufficient to reach equilibrium. After the contact time, the solid was separated by filtration and the concentration of lead in solution was analyzed by atomic absorption spectrophotometry using a Perkin-Elmer AAnalyst 200 spectrophotometer (Perkin-Elmer, Waltham, MA, USA).  
The adsorption capacity of the solid and the percentage of metal removal were determined by the following equations,  
\[q_{e}=\frac{C_{i}-C_{f}}{m}.V \tag{3}\]  
\[\% Removal=\frac{C_{i}-C_{f}}{C_{i}}.100 \tag{4}\]  
where \(q_{e}\) is the adsorption capacity, mg/g; \(C_{i}\) is the initial lead concentration, mg/L; \(C_{f}\) is the final lead concentration, mg/L; m is the mass of adsorbent solid, g.  
Since the best result in terms of adsorption capacity was obtained with the solid resulting from pyrolysis at 550 \({}^{\circ}\)C, the equilibrium of the adsorption process was studied, performing tests with different initial concentrations of lead (2.5, 5, 10, 20 and 40 mg/L) maintaining the rest of the operating conditions at the same values indicated above. All experiments were done by duplicate and, as for pyrolysis, average values are provided in the results and discussion section.  
The equilibrium results obtained for the solid resulting from pyrolysis at 550 \({}^{\circ}\)C were adjusted to different adsorption isotherm models, which are described below.