esa-sceva/satcom-chunk-collection huggingface dataset:
# Practical Application of Mesh Opportunistic Networks
## 4 Results
### Survey
#### 4.1.2 Group Communication  
When covering informational and/or audiovisual events in a professional sphere, it is of interest to establish a group communication channel among all the team members involved. In this context, participants considered that, if they had not used the protocol described here they would have used: WhatsApp (seven participants), Signal (four), Telegram (one), SMS (one) and iMessage (one). Again, some participants proposed various alternatives. In this context, the following benefits of the goTenna network were highlighted: the location of all the team members on the map; the use of the'shout' option to communicate with any user other than their own contacts; and the independence from mobile data networks or coverage, thereby guaranteeing a connection in crowded environments. The fact that it is a free system that does require payment to use the network was also mentioned. Among the disadvantages for this type of group communication were the initial complexity of configuration; the fact that audiovisual elements other than texts cannot be sent (audios, videos, photographs); the need to purchase an extra device; and the fact that the system does not track the user, who has to constantly report changes in location within the app. This is very interesting, because goTenna does facilitate localization if the user gives permission. However, what happened here is that the coordinator (GT7) frequently requested the observers to give their location in order to explicitly test the system. In opportunistic mesh networks the sending of a location can be ignored for privacy, and it is not necessary to identify the intermediate nodes since they are terminals that simply act as repeaters in the network, helping to extend the signal. Indeed, the privacy of a decentralized network is one of its most interesting features.
## 2 Problem Definition and Assumptions  
In large metropolitan areas, particularly those with high transit demand, an integrated transit system consisting of rail lines and a number of feeder routes connected at different transfer stations is essential. Consequently, designing a proper feeder network that can provide access to an existing rail system and coordinate the schedule of transit service can be a significant issue.  
The development of improved integrated intermodal systems can result in a higher quality of service and passenger satisfaction by providing better coverage, reduced access time, minimal delay and shorter travel times. From the transit operators' point of view, the operating costs may be reduced by an overall coordination between different public transport modes. Profit can also be increased by shorter route maintenance and eliminating the duplication of routes by trains and buses.  
This study is focused on designing a set of feeder bus routes and determining operating frequency on each route, such that the objective function of the sum of the operator, user and social cost is minimized. The mathematical formulation of the improved model and the details of the constraints are presented in the following sections.  
An intermodal transit network consisting of a rail line and feeder bus routes connecting the transfer stations is assumed to serve the examined area. The optimal transit system will be determined based on an assumed route structure (_i.e._, one rail line and feeder bus routes are linked with straight lines between nodes) and the peak hour demand situations in the entire service area. To formulate the mathematical model for an intermodal transit system and its application in the case study, the following assumptions are made:  
1. The transit network was designed with feeder buses and a fixed rail line.
2. Transit demand is assumed to be independent of the quality of transit service (_i.e._, fixed demand). The demand pattern for feeder bus routes is many-to-one.
3. The location of nodes (_i.e._, bus stops and rail stations) is given. Some of the model parameters (e.g., vehicle sizes, operating speed, cost) are specified.
4. All feeder routes can be used in both directions for the transit service.
## 3 Results
### Fermentation Traits of \(L\). _chinensis_ silage for Ensiling 90 d
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Item**} & \multirow{2}{*}{**Length**} & \multicolumn{4}{c}{**Additive**} & \multirow{2}{*}{**SEM**} & \multicolumn{4}{c}{**_p-Value_**} \\ \cline{3-3} \cline{5-10}  & & **Control** & & **SU** & **LP** & **SU+LP** & **Length** & **Additive** & **Interaction** \\ \hline \multirow{2}{*}{pH} & 1–2 cm & 4.20 \({}^{\text{\text{AB}}}\) & 4.00 \({}^{\text{\text{BB}}}\) & 4.06 \({}^{\text{\text{BB}}}\) & 3.88 \({}^{\text{\text{EB}}}\) & \multirow{2}{*}{0.014} & \multirow{2}{*}{\textless{0.001}} & \multirow{2}{*}{\textless{0.001}} & \multirow{2}{*}{\textless{0.001}} \\ \cline{2-3} \cline{5-10}  & 4–5 cm & 4.64 \({}^{\text{\text{AA}}}\) & 4.58 \({}^{\text{\text{AA}}}\) & 4.14 \({}^{\text{\text{BA}}}\) & 3.99 \({}^{\text{\text{BA}}}\) & & & \\ \hline \multirow{2}{*}{Lactic acid (g/kg)} & 1–2 cm & 32.53 \({}^{\text{\text{BA}}}\) & 40.20 \({}^{\text{\text{BA}}}\) & 51.77 \({}^{\text{\text{AA}}}\) & 38.50 \({}^{\text{\text{b}}}\) & \multirow{2}{*}{0.801} & \multirow{2}{*}{\textless{0.001}} & \multirow{2}{*}{\textless{0.001}} & \multirow{2}{*}{\textless{0.001}} \\ \cline{2-3} \cline{5-10}  & 4–5 cm & 4.60 \({}^{\text{\text{BB}}}\) & 3.77 \({}^{\text{\text{BB}}}\) & 34.36 \({}^{\text{\text{AB}}}\) & 37.03 \({}^{\text{\text{a}}}\) & & \\ \hline \multirow{2}{*}{Acetic acid (g/kg)} & 1–2 cm & 6.37 \({}^{\text{\text{BB}}}\) & 3.53 \({}^{\text{\text{BB}}}\) & 5.97 \({}^{\text{\text{BB}}}\) & 13.50 \({}^{\text{\text{a}}}\) & \multirow{2}{*}{0.433} & \multirow{2}{*}{\textless{0.001}} & \multirow{2}{*}{0.007} & \multirow{2}{*}{0.002} \\ \cline{2-3} \cline{5-10}  & 4–5 cm & 18.70 \({}^{\text{\text{A}}}\) & 19.83 \({}^{\text{\text{A}}}\) & 21.90 \({}^{\text{\text{A}}}\) & & & \\ \hline \multirow{2}{*}{Propionic acid (g/kg)} & 1–2 cm & 10.47 \({}^{\text{\text{a}}}\) & 8.87 \({}^{\text{\text{b}}}\) & 7.90 \({}^{\text{\text{BB}}}\) & 9.33 \({}^{\text{\text{ab}}}\) & \multirow{2}{*}{0.186} & \multirow{2}{*}{0.017} & \multirow{2}{*}{0.589} & \multirow{2}{*}{0.008} \\ \cline{2-3} \cline{5-10}  & 4–5 cm & 9.57 & 9.70 & 11.27 \({}^{\text{\text{A}}}\) & 9.97 & & & \\ \hline \multirow{2}{*}{Butyric acid (g/kg)} & 1–2 cm & 1.23 & 1.53 & 1.76 & 1.56 & \multirow{2}{*}{0.212} & \multirow{2}{*}{0.672} & \multirow{2}{*}{0.235} & \multirow{2}{*}{0.678} \\ \cline{2-3} \cline{5-10}  & 4–5 cm & 0.70 \({}^{\text{\text{b}}}\) & 1.00 \({}^{\text{\text{ab}}}\) & 2.63 \({}^{\text{\text{a}}}\) & 1.03 \({}^{\text{\text{ab}}}\) & & \\ \hline \multicolumn{3}{c}{Means with in the same row (\({}^{\text{\text{\text{a}}}-\text{\text{\text{\text{\text{\text{\text{\text{\text
## 4 Results and Discussion
### The Baseline Leveling Experiment
#### 4.1.1 Tilt Detection  
The first step in eliminating microgravity coupling in torsional oscillations is detection. In this paper, an inverted pendulum is used to test the tilt angle of the torsional reference plane. As shown in Figure 12, after shielding airflow disturbances, using a stationary optical platform, and recording for a long time, a capacitive displacement sensor detects the periodic sawtooth wave variations at the end of the inverted pendulum, with an amplitude of 10-15 nm. When converted with a 5 cm arm length and a 1\(\times\) tilt amplification factor, this corresponds to at least 0.2-0.3 \(\upmu\)rad of tilt variation in the reference. However, no effective thrust was applied to the torsional system during this period.  
It is observed that the displacement variation occurs with a period of several hundred seconds, which is caused by the periodic operation of the water cooling system used for the vacuum pump. Due to temperature changes affecting the tilt angle of the platform reference, the inverted pendulum detects long-term drift under triangular wave modulation.
## 3 Empirical Analysis
### Topological Properties of the CATN
#### 3.2.1 Temporal Attributes of Nodes and Edges
Overall, the temporal variation of airline routes and flights in China highlights the challenges in the operational capacity of the CATN, particularly in handling peak traffic. These limitations lead to flight schedule delays, and airports resort to scheduling \"red-eye flights\" to accommodate all daily flights, consequently increasing the risk of aviation operations. Furthermore, evaluations of various representative airports reveal that they continue to encounter these constraints, although their operational capacities vary. Therefore, when developing flight optimization plans, it is crucial to optimize them based on the distinct operational capacities of different airports.
# Developing Quantum Trusted Platform Module (QTPM) to Advance IoT Security
## 2 Preliminaries  
### Trusted Platform Modules (TPMs)  
TPMs and similar silicon-integrated security solutions offer promising approaches to address IoT security weaknesses. TPMs provide hardware-based security for storing cryptographic keys, authenticating devices, and ensuring secure communication between IoT devices [11]. They enhance node authentication with improved energy efficiency, making them suitable for applications with strict safety standards [12]. Silicon-integrated security solutions, which are part of the larger system-on-chip (SoC), bridge service-level security functionalities with hardware-anchored protection, offering increased security for IoT devices [13]. These approaches complement existing embedded security technologies by enforcing the principle of least privilege and actively monitoring system communications to detect and mitigate policy violations. Overall, hardware-based security solutions like TPMs and integrated SoC security functions play a crucial role in ensuring the integrity, trustworthiness, and reliability of IoT systems.  
TPMs can be combined with distributed object storage to provide secure and highly available key management solutions, offering a cost-effective alternative to traditional hardware security modules (HSMs) [14]. TPMs also serve as a foundation for trust, key generation, and authentication in cloud-based cryptographic key management systems (CKMS) [15]. In mobile ad hoc networks, TPMs can be used for protected storage and management of multiple node keys generated using identity-based cryptography [16]. The importance of standardized encryption key management (EKM) systems is emphasized, with proposals for protection profile modules based on common criteria to enhance security and consumer confidence [17]. These studies highlight the versatility of TPMs in addressing various key management challenges across different network environments.  
TPM plays a crucial role in device authentication across various domains. In smart grids, TPM integration enhances IoT device security through attestation and X.509 certificates, ensuring device authenticity and software integrity [18]. For medical sensor networks, a novel sidechain-based TPM (s-TPM) authentication method offers improved security resilience and energy efficiency compared to traditional protocols such as LEAP and TinySec [19]. TPM can also be used for SSL client authentication by issuing certificates to TPM-generated keys, such as attestation identity keys (AIK) and binding keys (BK), enabling secure device identification [20]. To authenticate the TPM chip itself, a method utilizing the public endorsement key and unique processor responses has been proposed [21]. These approaches collectively demonstrate TPM's versatility and effectiveness in enhancing device authentication across different applications.
# Model Parallelism Optimization for CNN FPGA Accelerator
## 3 Approach
### Inside Shuffle  
To alleviate the problems mentioned above, channel shuffle was employed to compensate for the accuracy of the CNN model. Since channel shuffle requires the exchange of data between groups of channels, it imposed new synchronization points while compensating for accuracy.  
When using model parallelism, some neural networks need synchronization points because their network structure inherently requires communication to remove data dependencies. For example, the _ShuffleNet_ structure used in this paper comprised 16 blocks, which meant that 16 synchronization points were needed when distributing the inference of _ShuffleNet_.  
Is it possible to retain the shuffle feature without adding synchronization points? For neural networks that need synchronization points, we modified the channel shuffle so that it did not add new synchronization points. The details of this process are shown in Algorithm 1.  
```
Input: data: output from the upper layer  I_input: Store a portion of the data needed for each device, I_input \(\subset\) data  N: a parameter for internal shuffle of data Output: result: reordered data is used to provide to the next layer 1.Create local variable I_input 2.Read data from Channel to I_input 3.for i = 0, 1,..., Channel/(N*Device_Number) do
4 for j = 0, 1,..., Ndo
5 for k = 0, 1,..., input_size do
6  Convert the one-dimensional array I_input into a three-dimensional array (i, j, k)
7  Transpose(i, j) #Tranpose(\(\cdot\)) is used to exchange data
8  Store result to the channel in the original order.
9  endfor
10  endfor
11 endfor
```  
**Algorithm 1** Inside-Shuffle.  
Figure 3: Group convolution (different colors represent different groups).  
First, it is necessary to comprehend the implementation of the original channel shuffle process. Channel shuffle is the \"reorganization\" of the feature map after group convolution. The data of each group are divided into n parts and exchanged with each other to ensure that the information flows between different groups.  
Next, we introduce inside shuffle, as depicted in Algorithm 1, wherein each block uses residual learning, which guarantees the interactivity and protects the integrity of the information by directly bypassing the input information to the output. Its function is similar to that of channel shuffle.  
In a word, the inside shuffle algorithm divides the data of each group into n parts, and intra-group exchange is used instead of inter-group exchange, so that no new synchronization points are added while the \"reorganization\" feature is retained.
# LoRa, Zigbee and 5G Propagation and Transmission Performance in an Indoor Environment at 868 MHz
## 3 Methodology
### Zigbee Measurement Descriptions
#### 3.3.2 Receiver XBee Module  
This module was configured with the aim of establishing wireless communication with the sending node and, therefore, acting as a receiver at the maximum speed allowed by the module. The received data were analyzed through another Pycom module which obtained, by serial communication, the data received by the XBee receiver module. In this way, as with LoRa, the characters sent were known and, therefore, knowing which data were badly received for a given sampling time, it was possible to estimate the quality rate of the signal generated by the emitting XBee module. Likewise, the value of the signal power (RSSI) with which the data was received was captured.
# Review of Propulsion System Design Strategies for Unmanned Aerial Vehicles
## 4 Discussion
### Literature Analysis
In any case, the solution must be identified in terms of the choice of propulsion technology that better suits (e.g., by efficiency, costs, or dimensions) the application in question, considering the specific data of the UAV to be designed and the peculiarities of each technology. Considering the use of electric motors, two electric motors are used currently in drones: brushed and brushless DC motors. For smaller UAVs, the choice falls most commonly to Brushless DC motors (BLDC) then brushed DC motors, because of the high power density, efficiency, reliability, speed, ease of control, low maintenance costs, and long lifetime [128]. Nevertheless, brushed motors can be also used to propel micro aircraft, and brushless motors are used for low-power UAVs (some watts) as well as for high-power UAVs (tens of kilowatts). The speed control of a BLDC motor is then usually managed by the Electronic Speed Control (ESC), based on an electronic circuit that regulates the speed. The choice of the energy source represents another fundamental aspect of the functional design of the propulsion system. Possible solutions are batteries (among which there are different types such as Li-ion, alkaline, LiPo, NiCd, etc. ), capacitors, supercapacitors, electrolytic capacitors, solar cells, and fuel cells, which can be used alone, but also combined in a configuration called hybridization [27; 129]. These different solutions have different potentials in terms of specific power and specific energy, as well analyzed by [PERSON] et al. [128], and hybridization allows combining advantages and performances and balancing their limitations. When different energy sources are used in a UAV, the real-time power splitting among the available sources must be managed by a Power Management System (PMS), which can be implemented with an active or a passive strategy [130]. The choices to be made in the functional design phase for the energy aspect therefore also concern the aspects of the solution to be adopted for energy management, depending on the chosen energy sources and storage systems [131; 132]. The analysis of the scientific literature emphasized a remarkable variability in works' number and main topics with respect to the drone size, although few research works focused in particular on medium-sized UAVs, e.g., with a mass at take-off close to 25 kg, which in the Italian regulation represents a crucial threshold strongly affecting the design process. Nonetheless, the high number of works concerning the sizing and optimization of the propulsion system reflects the importance of this element within the design process. Regarding the contents of the papers, evaluated thanks to the set of parameters defined with the second taxonomy, the main results of the literature review are briefly reported in the following sections.
## 4 Results Analysis
### Model Application
#### 4.2.2 Discussion of Problem II  
Problem II is the design suggestions for the structural assessment test of the supercharger for a turbine impeller. As can be seen from the test protocols for the 120-h structural test and the 350-h complete test of the supercharger, the sensitive parameters (temperature and speed) are different for both tests, and thus the cumulative load is different. Firstly, we should calculate the cumulative load ratios for the 350-h test and 120-h test. Secondly, we should calculate the cumulative load for the new complete engine test and use the load ratios to obtain the cumulative load required for the new test of the supercharger. Then, we will need to improve the test profile based on the 120-h calibration parameters. Finally, based on the above degradation model, we can verify that the new assessment test of the supercharger meets the new complete engine test requirements. We can take the change of the complete engine assessment test to 500 h as an example:  
* Calculate the cumulative load ratio. According to the 120-h structural test and 350-h complete machine test, it can be calculated that the cumulative load ratio is: \(L_{120}/L_{350}=0.4467\).
* Calculate the cumulative load required for the new structural assessment test. According to the ratio 0.4467, when the complete engine test reaches 500 h, the 350 h test is designed to do 50 cycles. Then, one can calculate the cumulative load of the required supercharger structure assessment experiment.
* Design the new supercharger assessment test. The 120 h calibration parameter assessment test is roughly divided into two stages. The first stage (5/6) is the uniform speed rotation. The second stage (1/6) applies the alternating stress. Based on the rotation speed, it is calculated that the test time of the supercharger structure assessment required to pass the 500 h complete engine test is 172 h.
* Validation based on the degradation model. According to the method in Section 3 of this paper, \(\sigma_{172}=767\) MPa \(<\sigma_{500}=1014\) MPa; that is, the supercharger's 172 h of structural assessment can meet the requirements of the 500 h complete machine test assessment.  
* Suggestions for the design of the 500-h assessment test: to facilitate the actual operation of the project, it is recommended to use a multiple of 10 as the actual intensive assessment time, i.e., take the assessment time of 180 h.
# Two-Step Enzymatic Synthesis of Structured Triacylglycerglycerols from ARASCO+
## 3 Results and Discussion
### Ethanolysis of Coconut Oil  
The lipase from the fungus Thermomyces lanuginosus has been identified as an excellent biocatalyst for the transesterification reactions of oils and fats when immobilized on hydrophobic supports because of the strong interaction between the support and the hydrophobic pocket around the active site of this lipase [32; 33]. The lipase from the fungus _Thermomyces lanuginosus_ immobilized on Immobead 150 was used to obtain FAEEs via the transesterification of soybean oil with ethanol at a 1:6 molar ratio and 15% lipase load based on the oil weight at 37 \({}^{\circ}\)C for 4 h, producing an around 70% yield of FAEEs [34]. The same lipase showed a higher transesterification yield (72%) to produce FAME from algal oil than other assayed lipases such as immobilized lipases from _R. miehei_, _C. rugosa_, and _Pseudomonas cepacia_[35]. _T. lanuginosus_ lipase immobilized in Immobead 150 (a hydrophobic support) was selected in the current work to produce FAEEs from coconut oil via the transesterification with ethanol, and the distribution of reaction products is shown in Table 1. The addition of water into the reaction medium of the enzyme-catalyzed ethanolysis of TAG may have a significant impact on the lipase activity rate, and it has been reported that the lipase from _T. lanuginosus_ and other lipases are more efficient when some water is available in the reaction medium [36]. Because of that, the ethanolysis of coconut oil using the Thermomyces lanuginosus lipase was carried out either with added water (4.0 wt% based on oil weight) or without added water to check for potential differences in FAEE yield. Actually, although residual unreacted TAGs from coconut oil were not fully separated from FAEEs by TLC and, thus, they were quantified together, from a practical view, it is simpler and cheaper to use entire ethanolysis products from coconut oil as the substrates for the synthesis of STAG instead of including purification steps for FAEEs, which would involve time-consuming and expensive processes. In this work, the highest proportion of FAEEs (considering residual unreacted TAGs) was achieved after 24 h of ethanolysis without added water (94.6% of reaction products) (Table 1). Although that value was not significantly different from those obtained after 12 and 24 h with added water (92.8 and 93.2% of reaction products, respectively), the addition of water led to the production of FFAs in the reaction medium, which were not detected when ethanolysis was carried out in the absence of added water. Therefore, the ethanolysis of coconut oil for 24 h without added water was selected to obtain FAEEs as the substrates for the synthesis of STAGs.