esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 The Proposed Protocol
### The Protocol Design
#### 4.2.3 Peer-To-Peer Firmware Update Distribution  
The peer-to-peer firmware update protocol happens between devices with the same specifications and from the same manufacturer. The device's gateway will download from the other gateway that has been downloaded the new firmware. As shown in Figure 5, IoT gateway 2 requests an update from IoT gateway 1.  
* _OCF device initiating the firmware update._ For this part, see the explanation in Section 4.2.2.
* _Update availability check._ As shown in Figure 5, after receiving an update request from the OCF device \(i_{2}\), IoT gateway 2 will check the newest firmware update to the smart contract (\(M_{sc}\)) for this particular device by sending the \(U_{id}\). After that, \(M_{sc}\) will check the contract for compatibility with the request. If there is a firmware update contract for the device, \(M_{sc}\) will send the signed U stored in the contract. IoT gateway 2 will receive this message and verify the signature. If valid, it will send a request to IoT gateway 1 to check the availability of the firmware. IoT gateway 1 will search for the compatible update for this device in the local database. If available, it will send the signed U and challenge \(c\) to give the update notification; otherwise, it will send a signed NA (not available) message. After that, IoT gateway 2 will verify the signature. If verified and the message is not NA, it will continue; otherwise, the process will be terminated. The next step is comparing the \(U_{id}\) from IoT gateway 1 and \(U_{id}\) from \(M_{sc}\). If the value is equal, IoT gateway 2 will create a connection to IoT gateway 1 for downloading the firmware. Afterward, IoT gateway 2 can verify the binary file by comparing the hash of \(U_{bin}\) from the IoT gateway 1 and the \(U_{id}\) value. If the value is equal, IoT gateway 2 will forward it to the OCF device; otherwise, it will reject it.
* _OCF device downloading and upgrading._ For this part, see the explanation in Section 4.2.2.  
Like the direct update protocol, the peer-to-peer update protocol also provides the integrity service to the firmware update.  
Figure 5: Peer-to-peer firmware update distribution: gateway downloading a new firmware update from another gateway.
## 4 Conclusions  
The experimental results obtained from the pilot scale thermochemical energy storage prototype can be summarized in the following conclusions:  
1. The amount of the thermal energy produced by the reactor (0.49 kWh) and stored to the water tank (~0.4 kWh) were about the same order for both the fixed packed and the moving bed reactor operating modes.
2. The experimental ratio of the energy storage densities between the fixed packed and moving bed was found as 2.5:1 in favor of the fixed packed bed reactor.
3. The significant drop of the energy storage density for the moving bed reactor is explained by the reduced residence time of the solid in the reactor (~30 min), the discontinuities of the granular flow and the non-homogeneous sorption throughout the bed. The later drawback can be nevertheless improved by packing the material in a denser manner inside the reactor.
4. The solid residence time for the moving bed reactor is a limiting factor for the energy storage density of material. The prolonged contact of the tested solid with the humid air can result in overhydration, which dramatically tends to increase the viscosity of granular flow in the moving bed reactor.
5. The loss of the stratification in the water tank had a negative consequence on the prototype global performance and resulted in drop of the heat exchanger effectiveness from ~0.93 to ~0.5.
6. New energy management scenarios are being currently explored using other materials alongside with other technical solutions.  
Conceptualization, methodology, investigation and writing--original draft preparation, O.S.; composite material curation, writing--review and editing, E.C.; visualization, validation and review, N.H.; conceptualization, supervision, project administration, funding acquisition and review, M.F.  
This research was funded by European Regional Development Fund and Wallonia Region, project reference FEDER C3E2D-STOCC.  
Authors gracefully thank to the BE-SOL (Rochefort, Belgium) team for the partnership in manufacturing and mounting of the prototype installation. Authors acknowledge Solvay for the provision of Caso(r) granules.  
The authors declare no conflict of interest.
# Design and Test of Real-Time Detection System for Cleaning Loss of Rapeseed Harvester
###### Abstract  
Aiming to address the problem of low recognition accuracy in the current cleaning loss detection system of rapeseed harvesters, a rapeseed cleaning loss detection system was developed using the energy distinction method based on the principle of impact piezoelectricity. A signal processing circuit, centered around a hardware integral circuit and a triple voltage comparison circuit, was designed. The energy of the impact signals generated by rapeseed kernels and impurities was calculated through hardware integration. The distinction threshold for the energy of the impact signals generated by kernels and impurities under the operating wind speed of the cleaning system was found through experiments, and a fitting model relating the fan speed to the distinction threshold was constructed. A loss detection and counting system for rapeseed kernels was designed to realize the statistics and real-time display of rapeseed kernels regarding cleaning loss. Performance verification tests were conducted on mixtures of rapeseed kernels and impurities with different mixing ratios, and a field test was carried out on the platform of a 4 LZY-5.0Z rapeseed combine harvester. The test results showed that the accuracy of the designed loss detection system for kernel identification was more than 91.6%. Under operating conditions of 700, 900 and 1200 r/min fan speeds in the combine harvester cleaning system, the relative errors of the loss detection system compared to manual detection were 5%, 4.7% and 3.8%, respectively. The developed loss detection system for rapeseed kernels has high detection accuracy and good overall performance, which means it can provide feedback information for the control of the harvester.  
rapeseed harvester; cleaning loss; energy distinction method; hardware integration; detection +
Footnote †: journal: Applied sciences
# Dynamic Analysis on the Parametric Resonance of the Tower-Multicable-Beam Coupled System
## 4 The Numerical Analysis  
### Parameters of the Case  
As shown in Figure 3, the symmetrical cable and its anchored beam portion are selected with the same parameters. The parameters of the cables are consulted with [9,32], which are also referred from the actual bridges. The basic parameters of each component are presented in Tables 3 and 4.  
From Table 3, it is noticeable that the values of \(E_{i}l_{i}\) and \(E_{bi}l_{bi}\) are set relatively lower than the parameters of actual bridges to meet the requirements of the working conditions.
# Path Loss Model for 3.5 GHz and 5.6 GHz Bands in Cascaded Tunnel Environments
## 2 Path Loss Model for Cascaded Tunnels in Far-Field Region of Propagation
### The Joint Channel Model Based on Waveguide and SBR
According to (7), the average ELC can also be expressed as:  
\[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]2  
\[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]3  
\[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]4  
According to (10), the variable \(\rho\) can be rewritten as a function of the radius of curvature. \[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]5  
To ensure the safety of high-speed traveling, the radius \(R\) of the curved tunnel is usually required to be at least greater than 300 m. Therefore, the variable \(\rho\) can be simplified by the Maclaurin formula. \[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]6  
According to (14) and (18), the ELC can be rewritten as power function of \(R\). \[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]7  
\[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]8  
\[\Gamma_{1}=\frac{\cos\ \phi_{1}-\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}}{\cos\ \phi_{1}+\sqrt{\cos^{2}\phi_{1}+e_{r}^{*}-1}} \tag{7}\]9  
High-order modes become significant when \(\text{R}_{\text{x}}\) is located in the near-field region, complicating the propagation phenomena and making EL difficult to determine. However, when \(\text{R}_{\text{x}}\) is in the far-field region, the propagation is mainly dominated by the fundamental mode. In addition, the EL is directly proportional to the propagation distance along the curvature in (12), and there is power function relation between ELC and R in (19). Therefore, this paper proposes a path-loss model for cascaded tunnels in the far-field region. \[\phi_{1}=\frac{\pi}{2}-\frac{m\lambda}{2w},\quad m=1,\ 2,\ 3,\ \ldots \tag{8}\]0  
\[\phi_{1}=\frac{\pi}{2}-\frac{m\lambda}{2w},\quad m=1,\ 2,\ 3,\ \ldots \tag{8}\]1where \(d\) represents the distance from \(T_{x}\) to the curved tunnel, as shown in Figure 1, and \(d^{\prime}\) represents the distance from \(R_{x}\) to the straight tunnel. \(PL_{cascade}\) and \(PL_{straight}\) represent the path loss of the cascaded tunnel and straight tunnel, respectively. To ensure that the curvature is completely in the far-field region of propagation, \(d\) must satisfy (23).
# Discrimination of Smoke-Exposed Pinot Noir Wines by Volatile Phenols and Volatile Phenol-Glycosides
## 3 Materials and Methods
### Materials
#### 3.1.2 Chemicals and Reagents  
Standards of guaiacol (\(\geq\)98%), 4-methylguaiacol (99%), \(o\)-cresol (\(\geq\)99.5%), \(p\)-cresol (\(\geq\)99%), and \(m\)-cresol (99%) were obtained from Sigma-Aldrich (St. Louis, MO, USA). 2-Methylophenol-3, 4, 5, 6-\(d_{4}\) (guaiacol-\(d_{4}\); 98.5%), 2-methoxy-4-methylphenol-3, 5, 6-\(d_{3}\) (4-methylguaiacol-\(d_{3}\); 99.3%), \(m\)-cresol-\(d_{7}\) (98.7%), \(p\)-cresol-\(d_{7}\) (99.2%), and \(o\)-cresol-\(d_{7}\) (99%) were purchased from CDN Isotopes (Pointe-Claire, QC, Canada). Tartaric acid (AR grade) was purchased from Johnson Matthey Company (Heysham, Lancs, UK). Ethanol (HPLC grade) was purchased from Greenfield Global USA Inc. (Brookfield, CT, USA). Methanol (HPLC and LC-MS grade) and sodium hydroxide 10 N solution (30% \(w/w\)) were purchased from Fisher Scientific (Fair Lawn, NJ, USA). Citric acid, sodium chloride (ACS grade), and hydrochloric acid were purchased from EMD Millipore Corporation (Billerica, MA, USA). Milli-Q water was obtained from a Milli-Q purification system (Millipore, Boston, MA, USA).  
Synthetic wine was used to establish standard curves for quantifying volatiles. It was prepared by dissolving 3.5 g of tartaric acid in one liter of 12% aqueous ethanol and adjusting the pH to 3.2 with sodium hydroxide [38].
###### Abstract  
The antenna field of view, the angle range that can be accessed by scanning the main beam of a phased array, is one of the key performance prescriptions especially for space-borne aerials. The classical example of the full Earth, continental and subcontinental field of view of the geosynchronous satellite is indicative, and it extends to the medium and lower orbit multibeam telecommunication systems. There, a high-gain, very small beamwidth pencil beam should scan a given service area. At the same time, it should exhibit extremely low sidelobes in order not to present interference to adjacent geographical areas, served by neighboring beams, and keep its grating lobes out of the Earth's surface. High-throughput telecommunication satellites should comply with those prescriptions to be given permission for placement in orbit. Thus, the motivation for delivering solid methods for the design of limited-field-of-view array antennas is high. A proposal in this direction is presented in the work at hand. Indeed, in the present study a scaling transformation is used to map a wide-angle scanning array to a limited-field-of-view one. We start the design from a Full-Field-of-View array with the appropriate half-power beamwidth, sidelobe level, and directivity index, and then we enlarge it to attain the desired one with the limited-field-of-view pattern characteristics. The potential of the method is solid since it augments the limited-field-of-view design methods using the excellent performance of the respective full-field-of-view ones. As a result, the synthesis of a limited-field-of-view array can use any of the well-known array synthesis methods in conjunction with the right scaling. Additionally, one can employ design methods that rely on sampling of planar aperture distributions. Various design examples, employing both sampling of continuous apertures and utilizing classical full-field-of-view array synthesis methods, are included and presented in detail, verifying the merit of our approach.  
Keywords:limited-field-of-view antennas; scaling transformation; antenna array design method; satellite communications +
Footnote †: Copyright © 2024 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
## 3 Results
### Amino Acid Composition
The content of proline in pH-shift-processed isolates was lower than that in enzymatically produced hydrolysates in the case of roach (31.8 and 32.2 in isolates produced using acidic or alkaline pH shift vs. 38.4-40.2 mg/g protein in hydrolysates produced using Protamex, Neutrase, and Corolase, respectively), but not in the case of B. herring. The acidic and alkaline pH-shift-processed isolates from both fishes were more abundant in certain essential amino acids (EAA), such as isoleucine and phenylalanine. The essential to non-essential amino acid (NEAA) ratios were statistically significantly (\(p<0.05\)) higher in the pH-shift isolates (0.84, and 0.85, in acid- and alkali-extracted isolates of roach, and 0.85 in both acid- and alkali-extracted isolates of B. herring, respectively) compared with the raw material (0.79 in the case of roach and 0.77 in the case of B. herring). Studies by [PERSON] and [PERSON] [14], [PERSON] et al. [18], and [PERSON] and [PERSON] [19] also reported high EAA contents for protein isolated using pH shift from herring and by-products of rainbow trout, silver carp, salmon, cod, and herring. The statistically significantly higher (\(p<0.05\)) EAA to NEAA ratio of proteins extracted using pH shift (0.84-0.85) compared with the ratio in the fish raw material (0.79 and 0.77 in roach and B. herring, respectively) in the present study can likely be attributed to the removal of collagenous material and therefore the higher loss of the non-essential amino acids glycine, proline, and hydroxyproline than essential amino acids. The EAA to NEAA ratios in enzymatically produced hydrolysates (0.69, 0.70, 0.65 in Protamex, Neutrase, and Corolase hydrolysates of roach, and 0.67 in the case of all B. herring hydrolysates), on the other hand, were statistically significantly lower compared with the respective raw materials. Studies on enzymatically produced fish protein hydrolysates have generally reported amino acid contents meeting nutritional requirements for adults (FAO/WHO/UNU, 2007). For instance, [PERSON] et al. [10] reported increased EAA to NEAA ratios after the hydrolysis of yellow stripe trevally (_Selaroides leptolepis_) using Alcalase and Flavourzzyme. [PERSON] et al. [43] reported an increase in EAAs from 48% in the muscle to 58% of total amino acids in the hydrolysate of Sind sardine muscle, produced with pepsin. Some studies have, however, reported losses in tryptophan and other EAAs [9,44], as was the case in the present study. The observed decrease in EAA to NEAA ratio in hydrolysates compared with raw materials in the present study may be explained by loss of hydrophobic EAAs, valine, leucine, isoleucine, phenylalanine, methionine, and tryptophan to the sediment during centrifugation. All protein isolates and hydrolysates generally complied well with the FAO/WHO/UNU [20] recommendations for adults. In enzymatically produced hydrolysates of roach and B. herring, valine content was 31.8-32.7 and 30.1-30.7 mg/g protein, respectively, which was slightly below the recommended level of 39 mg/g protein, making valine the limiting amino acid.
# Application of Microgel as a Sorbent for Bisphenol Analysis in Liquid Food Samples
## 1 Introduction
A powdered and activated carbon embedded chitosan-polyvinyl alcohol composite (PAC/CS/PVA) hydrogel was presented by [PERSON] et al. [24]. They fabricated both hydrophobic/hydrophilic bifunctional sorbents for the removal of sulfamethoxazole and bisphenol A from water. The adsorption performance of PAC/CS/PVA hydrogel was investigated under different typical water matrices, which resulted in the conclusion that ions, such as Cu\({}^{2+}\), Cl\({}^{-}\) and SO\({}_{4}\)\({}^{2-}\), had an insignificant effect on the adsorption of bisphenol. Unfortunately, until now, no paper presented the application of microgel for bisphenols sorption in complex food samples. In a previous article [28], we described the synthesis and characterization of environmental sensitive microgel, which showed very good sorption for bisphenols. Therefore, this paper investigates the application of the microgel as a novel sorbent for the preconcentration of four common bisphenols (Figure 1). The extraction procedure was optimized and used on food samples, which might be exposed to bisphenol contamination due to the package in which they were stored. To the best of our knowledge, it is the first report about the application of microgels as sorbents for bisphenols preconcentration in complex samples. Various factors affecting adsorption and desorption steps for the preconcentration of BPF, BPE, BPA and BPB were investigated and optimized. Finally, the developed procedure was employed to determine these analytes in different liquid food samples.
# Protection of Digital Elevation Model--One Approach
###### Abstract  
The quality of DEMs is especially being considered based on the spatial resolution of the created digital models and the type of terrain of the interest area. DEM analysis was performed specifically for LiDAR-based DEMs, as well as a comparison with results obtained using the radar recording method (Shuttle Radar Topography Mission). The application of DEM data for security-sensitive systems requires the fulfillment of security requirements, such as authenticity, integrity, confidentiality, and non-repudiation. For this purpose, the authors have developed a model for non-repudiation and protecting DEM data. The model simulation shows it is possible to detect even the smallest changes made in the transmission or the DEM location, as well as proving the data authenticity and non-repudiation of the sender. DEM data security testing has shown that DEM data is effectively protected from the source of origin to the end entity location.  
DEM; GIS; LiDAR; integrity; non-repudiation; security; PKI 2022 12 9898. [[https://doi.org/10.3390/app1219989](https://doi.org/10.3390/app1219989)]([https://doi.org/10.3390/app1219989](https://doi.org/10.3390/app1219989))
# Satellite Image Super-Resolution by 2D RRDB and Edge-Enhanced Generative Adversarial Network +
## 2 Related Works
### GAN Methods for Image SR  
GAN [2] is a deep learning model which is composed of two networks. One is the Discriminating Network and the other is the Generative Network. Inspired by GAN, researchers have conducted active research on it. Recently, some effective and practical techniques have been applied to low-level computer vision tasks, including image SR [26]. For instance, [PERSON] et al. [3] proposed a realistic single-image SR using GAN (SRGAN), which uses adversarial loss to push the reconstruction result to the natural image. [PERSON] et al. [4] improved the generator on the basis of SRGAN, and the RRDB network architecture is proposed. The BN layer is removed from the architecture, and the idea of relativity GAN is borrowed to let the discriminator predict the authenticity of the image instead of \"whether it is a fake image\". Finally, the perceived loss is also improved. These improvements have brought better visual quality and more realistic and natural textures. [PERSON] et al. [5] proposed an Edge Enhanced Network (i.e., EEGAN) architecture based on GAN. This method is used to provide robust satellite image SR reconstruction and an adversarial learning strategy that is insensitive to noise. This method retains enough edge information to bring better results to the final SR image.
# Fluid Net Models: From Behavioral Properties to Structural Objects
## 6 Reduction Rules
* From the net in Figure 13d, if \(p_{4}\) and \(p_{3}\) are not used, then necessarily, \(p_{11}\) and \(p_{10}\) should be in the original problematic T-coverture. Thus, the recovered T-coverture at this point is \(\mathcal{T}_{\mathcal{C}_{8,101,18}}=\left\{p_{8},p_{10},p_{11}\right\}\). * From the net in Figure 13c, we can see that place \(p_{6}\) is an essential cover of the net; thus, it should be in the original T-coverture. Hence, the recovered T-coverture at this point is \(\mathcal{T}_{\mathcal{C}_{8,101,18,6}}=\left\{p_{6},p_{8},p_{10},p_{11}\right\}\). * From the net in Figure 13b, places \(p_{9}\) and \(p_{12}\) cannot be part of the problematic configuration, they represent P-semiflows in this net. Hence, the T-coverture at this point is \(\mathcal{T}_{\mathcal{C}_{8,101,18,6}}=\left\{p_{6},p_{8},p_{10},p_{11}\right\}\). Figure 14: Particular examples of reduction rules preserving problematic configurations from [16]. * From the net in Figure 13a, place \(p_{7}\) is an essential cover, so it must be in the configuration. The previously removed place \(p_{9}\) was involved in a pre-fusion of transitions, which in this net means that place \(p_{2}\) (\"absorved\" in the pre-fusion) cannot be used. In this net, either place \(p_{1}\) or \(p_{9}\) can restrict the flow of transition \(t_{1}\). Hence, we have two B-Problematic configurations, \(\mathcal{C}_{1,8,10,11,8,6,7}\) and \(C_{9,8,10,11,8,6,7}\). These last configurations are the two B-Problematic configurations that the original net has. A similar procedure can be carried out to obtain the nB-Problematic configuration of the original net from the reduced one. These reductions provide an important insight about the roots of undesired behaviors. In particular, these reductions maintain the problematic configurations of those having choice places interacting inadequately with join transitions. In our running example, one B-Problematic configuration of the reduced net \"captures\" two B-Problematic configurations of the original net. This is because both configurations have the same problem in common, namely, the interaction between \(p_{8}\) and \(t_{3}\) is not adequate. A further discussion of this fact is also presented in [16].