esa-sceva/satcom-chunk-collection huggingface dataset:
# Converging Telco-Grade Solutions 5G and beyond to Support Production in Industry 4.0
## 2 Stakeholder and System Interoperability
### Ecosystems of Industrial Production
#### 2.1.2 Comparison of Industrial and Residential 5G  
There is a significant difference between mobile network services provided for public or industrial purposes. Although both are based on existing 3 GPP standards, the use-case and user requirements are fundamentally different; therefore, the architectural solutions will be diversified [8]. The comparison is summarized in Table 1.  
The **subscriber** in the case of the existing mobile networks is mainly the human population, and to a lesser extent IoT devices. They utilize mobile services in a relatively large area. In contrast, Industry 4.0 users will be mostly machines, operating in a well-defined geographical area.  
Figure 3: The Industry ecosystem’s members.  
The nature of **subscription** is also different. Traditional mobile network subscribers pay every month based on subscription type or data usage. Thus, service pricing can be fine-tuned based on network resource utilization per user basis. In the case of industrial solutions, it is expected that the entire industrial solution will pay a service fee for the service. Regardless of the devices' data or resource utilization, or which use-case has a temporary high demand, pricing is not followed by a direct financial change. Industrial subscription fees will be much simpler and more stable than traditional public network pricing.  
The number of available **mobile network services** will be much more limited for industrial solutions. Machine Type of Communication is unlikely to need a voice, SMS/MMS, and roaming service in addition to a data connection. On the other hand, an industrial service must be operational throughout the life cycle of the factory. The fluctuation of services based on existing essential services, such as OTT (Over-The-Top), is also expected to be low for industrial mobile networks. However, the high reliability and stability of existing ones are vital.  
**SIM fluctuation** and user churn will be close to zero for industrial services, or at least it will not be typically seasonal. A machine connected to an industrial 5G network solution is expected to use one SIM card throughout its life cycle.  
In terms of **reliability**, industrial networks must perform well above the requirements of existing public mobile networks and services. **Troubleshooting** time commitments should also be adjusted to industrial needs. The transmission of data or voice packets in the current public mobile networks works on a best-effort basis, so there is no guarantee for the services based on them. In the case of a public user complaint, the user cannot enforce any obligation on the NO. In contrast, it is inevitable to make commitments and define **Service Level Agreements (SLAs)** regarding the required services on the factory site. SLAs can include several metrics depending on the use-case requirements; the most fundamental ones are the bandwidth, latency, and availability.
# A Real Case of Implementation of the Future 5G City
## 3 Future 5G City Use Cases
### The 5G Project Use Cases
#### 3.2.8 Agriculture 2.0  
Another aim is the certification and enhancement of the _Made in Italy_ brand, with the application of innovative solutions for traceability of the production chain in the Agro-Food sector. Technology based on blockchain and precision agriculture will be used, e.g., drones connected to the 5G network for transmission in time real of trusted data that reinforce the authenticity and consistency of information, to ensure the authenticity of the production. The experimentation involves the entire production chain: cultivation, irrigation, fertilization, and harvesting.
## 2 Materials and Methods
### MOORA Method
#### 2.3.3 Reference Point Approach  
In this approach, initially, the maximum value in the column of each maximized criterion and the minimum value in the column of each minimized criterion in the normalized matrix A are designated as the \"reference point\". Subsequently, these values for each column are subtracted from all values in that column, and the differences are calculated. These differences represent the distances to the reference points and are depicted as shown in Equation (28).  
\[r_{i}-x_{ij}^{*} \tag{28}\]  
Here, \(r_{i}\) is defined as the reference point of criterion \(i\).  
The ranking of the alternatives is determined by applying the \"Tchebycheff MinMax Metric\" formula to the new matrix containing the distances to the reference point. Equation (29) contains the Tchebycheff Min-Max Metric formula [22].  
\[\min_{j}\biggl{\{}\max_{i}\biggl{(}\Bigl{|}r_{i}-x_{ij}^{*}\Bigr{|}\Bigr{)}\biggr{\}} \tag{29}\]  
According to this formula, the maximum values in each row of the matrix of differences are determined, and the alternative with the smallest value among these maximum values is ranked as the best alternative, while the alternative with the highest value is ranked as the worst alternative.
# An Unsupervised Machine Learning Approach for UAV-Aided Offloading of 5G Cellular Networks
## 3 UAV-BS Deployment Process (UDP)
### Clustering Selection Process (CSP)  
At this point, the exact \(K\) candidate 2D locations for the placement of UAV-BSs have been identified by the UCP subprocess. The second subprocess of the UDP is called the cluster selection process (CSP). CSP determines which of the \(D\) out of \(K\) subsets of UEs should be offloaded from the macro-cell infrastructure onto the \(D\) available UAV-BSs; therefore, for the best selection of \(\binom{K}{D}\), the following weighted score (WS) function is considered:  
\[WS_{k}=an_{k}+(1-a)d_{k} \tag{3}\]  
where \(d_{k}\) is the distance between the medoid of cluster \(k\) and the nearest macro cell, \(n_{k}\) is the number of users belonging to cluster \(k\), and \(a\) (\(0\leq a\leq 1\)) is the weighting factor [23]. Since \(d_{k}\) and \(n_{k}\) are disparate and in most cases \(d_{k}\) is quite larger than \(n_{k}\), their corresponding values considered for the WS function are normalized using the following expression:  
\[X_{norm}=\frac{X-X_{min}}{X_{max}-X_{min}}, \tag{4}\]  
where \(X\) is a value of the corresponding feature under normalization, \(X_{max}\) and \(X_{min}\) are the maximum and the minimum value of this feature, respectively, and \(X_{norm}\in[0,1]\) is the final normalized value [24]; therefore, the final expression of WS function used in CSP is:  
\[WS_{norm}^{k}=an_{norm}^{k}+(1-a)d_{norm}^{k}. \tag{5}\]  
Finally, CSP can be formulated as a maximization problem expressed as follows:  
\[\begin{split}\underset{Z}{\text{max}}&\sum_{k=1}^{ K}z_{k}WS_{norm}^{k},\\ \text{s.t.}&\sum_{k=1}^{K}z_{k}=1,\\ & z_{k}\in\{0,1\},\quad 1\leq k\leq K,\end{split} \tag{6}\]  
where \(Z=\{z_{1},z_{2},...,z_{K}\}\). Concerning the value of \(z_{k}\), with \(1\leq k\leq K\), in case a UAV-BS deployed in the cluster \(k\) then \(z_{k}=1\), otherwise \(z_{k}=0\). The operation of the CSP subprocess, which solves the optimization problem (6), is summarized in Algorithm 2.  
```
1:input: Available number of UAV-BSs \(D\) and the set of formed clusters of users \(S\)
2:for each \(S_{k}\in S\)do
3: Calculate the weight score \(WS_{norm}^{k}\) of \(S_{k}\) using (5)
4:endfor
5: Sort in descending order the elements of set \(S=\{S_{1},S_{2},\ldots,S_{K}\}\) based on the corresponding weight score \(WS_{norm}^{k}\) of each cluster \(S_{k}\)
6: From the ordered set \(S\), select the first \(D\) clusters \(S_{1},\ldots,S_{D}\)
7:output: The \(D\) clusters \(S_{1},\ldots,S_{D}\), where the available UAV-BSs should be deployed into the coordinates of the medoids of each cluster to maximize the objective function of (6)
```  
**Algorithm 2** Clustering Selection Process (CSP).
###### Abstract  
Bark beetles commonly produce de novo terpenoid pheromones using precursors synthesized through the mevalonate pathway. This process is regulated by Juvenile Hormone III (JH III). In this work, the expression levels of mevalonate pathway genes were quantified after phloem feeding--to induce the endogenous synthesis of JH III--and after the topical application of a JH III solution. The mevalonate pathway genes from _D. rhizophagus_ were cloned, molecularly characterized, and their expression levels were quantified. Also, the terpenoid compounds produced in the gut were identified and quantified by Gas Chromatography Mass Spectrometry (GC-MS). The feeding treatment produced an evident upregulation, mainly in acetoacetyl-CoA thiolidase (_AAACT_), 3-hydroxy-3-methylglutaryl-CoA synthase (_HMGS_), 3-hydroxy-3-methylglutaryl-CoA reductase (_HMGR_), phosphomevalonate kinase (_PMK_), and isopentenyl diphosphate isomerase (_IPPI_) genes, and males reached higher expression levels compared to females. In contrast, the JH III treatment did not present a clear pattern of upregulation in any sex or time. Notably, the genes responsible for the synthesis of frontalin and ipsdienol precursors (geranyl diphosphate synthase/farnesyl diphosphate synthase (_GPPS_/_FPPS_) and geranylgeranyl diphosphate synthase (_GGPPS_)) were not clearly upregulated, nor were these compounds further identified. Furthermore, trans-verbenol and myrtenol were the most abundant compounds in the gut, which are derived from an \(\alpha\)-pinene transformation rather than de novo synthesis. Hence, the expression of mevalonate pathway genes in _D. rhizophagus_ gut is not directed to the production of terpenoid pheromones, regardless of their frequent occurrence in the genus _Dendroctonus_.  
mevalonate pathway; _Dendroctonus_; juvenile hormone III; pheromone production
###### Abstract  
Satellite network awareness is a key technology for obtaining the status of onboard resources and supporting efficient network management. However, the dynamic characteristics of the network topology results in dynamic transmission delays of awareness data, while the instability of satellite-ground links poses challenges in selecting awareness reporting nodes. Therefore, a dynamic reporting nodes selection method for network awareness based on active-passive integrated network telemetry (DRNSM-APINT) is proposed. Specifically, an APINT model is built which can dynamically select the optimal reporting node and reduce awareness time through the bidirectional aggregation of telemetry packets along the service path. To address the requirements of various services, flexible division strategy through virtual boundaries and the integration of APINT models are combined to achieve customized selection of multiple reporting nodes on each path. Additionally, a lightweight Q-learning algorithm is proposed to dynamically solve the above issue with lower computational complexity. The simulation results demonstrate that the DRNSM-APINT method can decrease the awareness time by 34.5% and improve the overall awareness performance by 17.1%, thereby significantly enhancing the timeliness performance and dynamic characteristics of network awareness.  
low-Earth-orbit satellite network; network awareness; dynamic reporting nodes selection; active-passive integrated network telemetry; lightweight Q-learning algorithm +
Footnote †: journal: Applied sciences  
Article
## 5 Network Management Architecture of the Proposed Topology
### Performance Management  
The performance management of WSNs monitors the performance of the network and keeps resource consumption as low as possible, especially the use of energy. One of the major performance issues of the WSN is event reliability, which is defined as the number of unique data packets received by the sink node. For optimum performance, the management system sets the data generation rate of the sensors and may also keep some nodes in the sleep state and others in the normal live state.  
Performance management consists of monitoring network devices and links in order to determine utilization. Utilization may vary depending on the device and link; it may include processing load, network card utilization, packet-forwarding rate, error rate, or packets queued. Monitoring utilization helps to ensure there is available capacity. Monitoring the network performance assists in identifying current and future bottlenecks and aids in capacity planning. Tracking the utilization of network resources by each user is the goal of accounting management. The primary function of this information is to bill users for their use of the network and its resources. This information can be used to establish metrics and quotas. The usage information also helps the network manager to allocate network resources properly. It is also helpful to see typical user behaviour as then atypical behaviour can be identified and addressed. Atypical behaviour may indicate a security breach or intrusion or may be an indication of a future device problem.
## 3 Measurement Setup and Results
### Measurement Results
Figure 11: Comparison of (**a**) S11, (**b**) S22, (**c**) S12, (**d**) S22, (**e**) MSG/MAG, and (**f**) stability factor among the measurement (blue circle), the conventional model (pink dashed line), and the proposed model (red line) from 0.2 to 67 GHz under \(\rm{V_{ds}}=28\) V, \(\rm{V_{gs}}=-1.6\) V.  
Figure 12: _Cont._  
Figure 12: Comparison of **(a)** S11, **(b)** S22, **(c)** S12, **(d)** S22, **(e)** MSG/MAG, and **(f)** stability factor among the measurement (blue circle), the conventional model (pink dashed line), and the proposed model (red line) from 0.2 to 67 GHz under \(\rm{V_{ds}}=20\) V, \(\rm{V_{gs}}=-1.2\) V.  
Figure 9:0 _Cont._  
As shown in Figures 11-13, the proposed model improves the S12 accuracy due to the modified \(\mathrm{C_{ds}}\) circuit considering the source via effect. The improved S12 accuracy compared to the previous model allows the proposed small-signal model to predict more similar MSG/MAG and stability factor to measurements at frequencies above 20 GHz. Although there is still room for some improvement depending on the bias, it can be seen that the trend is more similar to the measurement than before. It is worth noting that the proposed small-signal model tends to precisely match the measurements, especially near the operating bias of the power amplifier.
###### Abstract  
Background: Baobab fruit is valued for its nutritional and medicinal benefits. Although it is acknowledged that baobab pulp is beneficial for health, studies that link its nutraceuticaltical properties to the ability to eliminate reactive species (ROS and RNS) are scarce. Methods: The nutritional profile and the antioxidant properties of baobab pulp extracts from Angola were evaluated. Thus, for the first time, the evaluation of in vitro scavenging capacity against the most physiologically relevant reactive oxygen species (ROS) and reactive nitrogen species (RNS) were the focus of investigation.  
Results: Angolan fruit pulp presented high contents of ash (8.0%) and total dietary fiber (52%). Vitamin E content was reported for the first time in fruit pulp. Green solvents were used to quantify bioactive compounds and antioxidant activity. Hydroalcoholic extracts exhibited the highest contents of phenolics (1573.0 mg/100 g) and flavonoids (768.7 mg/100 g). Thus, hydraolcoholic extracts showed higher antioxidant activity, and higher scavenging capacity for ROS (O\({}_{2}\)\({}^{\bullet}\)-, H\({}_{2}\)O\({}_{2}\), HOCI, ROO\({}^{\bullet}\)) and RNS (\({}^{\bullet}\)NO, ONOO\({}^{-}\)), being most active for \({}^{\bullet}\)NO and ONOO\({}^{-}\). Conclusion: For the first time, Angolan baobab fruit was described in respect to its nutritional contribution as well as its positive antioxidant effects, both as a functional food and as a nutraceuticaltical ingredient.  
baobab fruit; nutritional profile; dietary fiber; vitamin E (HPLC-DAD-FLD); phenolics; flavonoids; antioxidant activity; ROS and RNS scavenging assays
###### Abstract  
This paper presents an efficient three-dimensional (3D) Dubins path design and a new continuous curvature path-smoothing algorithm. The proposed 3D Dubins path is a simple extension of the 2D path and serves as a reference path generator to guide the proposed smoothing algorithm. In the smoothing algorithm, the reference path is approximated by several cubic Bezier curves to generate a parametric path that simultaneously satisfies curvature continuity and maximum curvature requirements. The algorithm also provides a criterion to select a required number of Bezier curves to strictly meet the maximum curvature constraint. Therefore, our algorithm can be used for 3D path-following applications in many areas such as aerospace and robotics. The numerical simulation results show that the proposed algorithm produces a continuous curvature path that passes through all waypoints with a slight increase in path length compared with the original 3D Dubins reference path.  
Bezier curve; continuous curvature; Dubins path; path planning; path smoothing; waypoint
## 3 Results and Discussion  
### Compressive Strength  
Figure 6 shows the compressive strength test results before and after high temperature exposure of the steel fiber reinforced cement composites with polymer (%). The maximum compressive strength was 37.2 MPa with 0.5% polymer after high temperature exposure, and a lower value was observed at 1.5% polymer as compared to that at 0% polymer. A high percentage of polymer added during mixing affects the compressive strength after high temperature exposure, owing to an increase in voids. When compared to 0% polymer SIFRCCs, the compressive strength in 1.5% polymer is lower, owing to voids created in the SIFRCCs after exposure to a high temperature. The weight loss of the SIFRCCs owing to the high temperature may decrease the compressive strength [18]. A comparative analysis of the compressive strength characteristics by polymer incorporation rate after high temperature exposure showed that the compressive strength was higher at 0.5% polymer than at 0%, but the compressive strength of other specimen decreases after exposure to high temperature. The steel fibers were effective in reducing the degradation of compressive strength of the concrete after exposure to the high temperatures [15]. The compressive strength decreased was significant after exposure to high temperature in comparison with SIFRCCs without polymer, because the polymer that melts during  
Figure 4: Time–temperature curve of the KS F 2257 (ISO 834) standard [35].  
Figure 5: Specim after exposure to high temperature.  
high temperature exposure create voids and moisture passes through the created pores. This creates channels to alleviate internal vapor pressure inside the concrete, thus preventing explosive spalling and reduces the failure of the concrete model. Moreover, polymer added mixture should result in an increase of the compressive strength of SIRRCCs before exposure to high temperature, but the increased difference in compressive strength is moderate.
## 3 Results and Discussion
### Influence of Wetlands on Water Quality  
3.5.1. Thermotolerant Coliforms  
When comparing Thermotolerant Coliforms at the inlet and outlet of the Pantanal region, a pronounced downward trend is observed in most of the years studied. Additionally, it is also noted that the values for Thermotolerant Coliforms were above the permissible limit for Class 2 at the inlet stations, so that at the mouth of the Miranda River with the Paraguay River, the values remained below the limit of 200 MPN/100 mL (Figure 9).  
The results corroborate those found by [39], who analyzed the effectiveness of natural wetlands in retaining nutrients, sediments, and microbial pollutants in two wetland areas, one natural and the other channelized (anthropized), located in a region of intense agrogural use. The authors found that the natural wetland area reduced about 68% of _E. coli_ between the inlet and outlet of the natural wetland area, while the channelized wetland area retained 25% of the coliforms between the inlet and outlet. [PERSON] et al. [40] found an average reduction of 79% in the years ranging from 2007 to 2010 at the outlet of the wetlands in the Toenepi basin, a region predominantly characterized by dairy farming in the North of New Zealand.  
Figure 9: Spatial variation of the average Thermotolerant Coliforms (MPN/1000 mL) at the monitoring stations in the Pantanal (IA07, IA14, IA15, IA16, IA17).  
The retention and reduction in coliforms and other types of microorganisms in wetlands may be associated with sedimentation along with suspended particulate matter and also with adsorption to aquatic vegetation. The infiltration of contaminated floodwaters into firm soil is another factor that reduces the quantity of these microorganisms in surface waters. Exposure of organisms to ultraviolet solar radiation present in the water column significantly reduces the quantity of these organisms, especially in shallow waters [39; 40].
# Real-Time Volumetric Ultrasound Research Platform with 1024 Parallel Transmit and Receive Channels
## 3 Results
### Electronics Characterization  
Compared to our older \"DiPhAS\" ultrasound system generations [23; 24], new receiver modules as well as transmitters with two short-circuited outputs were used in this system to increase the transmit and receive bandwidth. To be able to characterize the transmit bandwidth, the amplitudes of the transmit signal were analyzed in a frequency range between 0.3 and 40 MHz, with a signal length of 1 cycle. The transmitted signals were measured with an oscilloscope at the front-end output pins. It is shown that the pulsers can be operated up to a frequency of 25 MHz without significant amplitude decreases (Figure 9).  
To determine the receive bandwidth, the high-pass filter integrated in the receiver module was deactivated. Then, a sinusoidal signal, generated by an external signal generator, was fed into the transducer connector of the system. Whereas in older DiPhAS generations the signals were already significantly attenuated below 1 MHz, here the \(-\)3 dB limit is undercut below 300 kHz (Figure 9). Overall, the system can therefore be operated in a frequency range between 300 kHz and 25 MHz, provided that in the upper frequency range the sampling of 80 MS/s is still acceptable in the respective application.  
Another innovation in the development of the 1024-channel electronics was the implementation of an FPGA-based transmit signal generation with a high delay and frequency resolution of 2.08 ns (using a clock of 480 MHz). This was verified by generating and analyzing two signals with the smallest possible phase shift at the output pins of a front-end board using an oscilloscope (Figure 10). In addition to the time shift of two transmit signals, the spectrum of the excitation frequency of the Vermon 32 \(\times\) 32 element Matrix Array of 2.82 MHz was also recorded to demonstrate the frequency accuracy.  
Figure 9: Transmit bandwidth (**a**) and receive bandwidth (**b**).  
Probably the most important feature of the parallel connection of four 256-channel systems to one 1024-channel ultrasound electronics is the guarantee of completely synchronous operation. The developed synchronization scheme has already been sufficiently described in Section 2. To analyze the synchronization of the four parallel sub-systems and to exclude any phase shift or jitter with a set zero-delay plane wave ultrasound beam, one transmit signal of a randomly selected channel was measured from each 256-channel system, which were then compared with each other in time (Figure 11).  
Figure 11: Phase equality of a zero-delay signal on all four synchronized systems.  
Figure 10: Delay and frequency resolution of two 2.82 MHz transmit signals shifted by 2 ns in the time domain (different oscilloscope resolutions) (**a,b**) and the spectrum of the transmit signal (**c**).  
The trigger is released at the rising edge of the master system. The other signals are static to the triggered signal. No phase shift could be detected.