esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Route Generation Methodology
### Higher-Level Path Generation: Genetic Algorithm (GA)
#### 2.3.1 Foundation and Basic Principles  
Like the ACO algorithm, the GA was developed to solve discrete optimization problems [21] but has also demonstrated success in continuous optimization. The GA belongs to the evolutionary class of metaheuristics. The GA mimics the evolutionary process using crossover and mutation operators, and survival of the fittest. Over the course of many generations, the solutions will continue to improve until the termination condition is met. The overall flow of the GA is visualized in Figure 4.  
The GA requires a solution to be encoded into a structure called a chromosome, where each gene contains important information used to calculate the fitness of the solution. A population consists of a collection of chromosomes, and the fitness of a chromosome is used to quantify how good a solution is.  
Initially, a population of randomized chromosomes is created, and then the fitness of each member is evaluated. This means that the average fitness in the first generation is bad since there has not been any constructive reward system applied. To improve the fitness of the population, GA operations such as selection, crossover, and mutation can be used.  
To select parents, a roulette-style selection is commonly used. This means that chromosomes with a better fitness are more likely to be selected for reproduction. A roulette-style selection can be used to choose two unique parents to perform the crossover and mutation.  
Figure 3: The proposed scanning radius scheme for the ants using a hypothetical sensor radius (highlighted in yellow). As shown in the figure, only three nodes have been selected to achieve 55% area coverage because of adjacent nodes that are covered by the sensor’s scanning radius.  
The crossover operation occurs when a crossover point is selected in the chromosomes, and the genes from each chromosome are spliced together with respect to the crossover point. This process creates two unique children that can then be mutated. The mutation randomly changes one (or several) of the genes in a chromosome with respect to the problem constraints. Typically, the probability of crossover is larger than the probability of mutation. A large crossover probability allows the population to efficiently explore the solution space, while the low mutation probability allows each chromosome to search the local vicinity of the solution space.
## 3 Two-Layer Singular Value Decomposition
### Two-Layer Singular Value Decomposition Based on Number Characteristic of Effective Singular Values  
Step 1: Signals \(y_{1}\), \(y_{2}\)., \(y_{n}\) are AM-FM Signals.  
Step 2: Apply SVD to \(y_{1}\), \(y_{2}\)., \(y_{n}\) respectively, retain the SCs with the first 250 singular values, \(\overset{\sim}{\mathbf{A}}_{n}=\sum\limits_{i=1}^{250}\mathbf{A}_{i}\) and purified signal \(\overset{\sim}{x}_{n}\) can be obtained.  
Step 3: Equations (1)-(5) are applied to \(\overset{\sim}{x}_{n}\), the \(I\overset{\sim}{x}_{n}\) can be obtained, which is the IF of \(\overset{\sim}{x}_{n}\).  
Step 4: Apply SVD to \(I\overset{\sim}{x}_{n}\), retain the SCs with the first 7 singular values, \(\overset{\sim}{\mathbf{A}}_{n}=\sum\limits_{i=1}^{7}\mathbf{A}_{i}\) and purified signal \(\overset{\sim}{I\overset{\sim}{x}_{n}}\) can be obtained. That is to say, instantaneous frequency \(f_{c}+\sum\limits_{q=1}^{3}f_{d_{q}}\cos(2\pi f_{m_{q}}t+\theta_{q})\) which has the largest three \(f_{d_{q}}\) are kept [26,27], by neglecting the minor frequency components with low amplitudes [4].  
Step 5: \(\overset{\sim}{I\overset{\sim}{x}_{n}}\) can be shown in the Hilbert Spectrum.  
Step 6: Then, remove the direct component of \(\overset{\sim}{I\overset{\sim}{x}_{n}}\) via zero mean processing, then utilize Fast Fourier Transform (FFT) to this signal.
# A Reinforcement Learning Method for a Hybrid Flow-Shop Scheduling Problem
## 4 MDP Framework for HFSP
### Reward Function Representation Based on Machining Time  
Distinguishing an optimal policy from other ones is the reason why action-value, or \(Q(s,a)\), is adopted, whose ability to express has a strong dependence on the representation of the reward function. In addition, to achieve plummy learning results and improve learning convergence speed, reward function representation is pivotal.  
The ultimate goal of Q-learning is to maximize the cumulative reward, and the objective function is to minimize the machining time of all workpieces in this paper. Namely, the reward function is negatively correlated to machining time. For uniform representation, at the same time, a linear reward function is proposed, so the reward function in reinforcement learning for HFSP is defined as what follows:  
\[r(s,a)=-\omega\times c_{-}t_{i,j,l}+b, \tag{17}\]  
\[c_{-}t_{i,j,l}=FT^{\prime}_{j,l}-BT_{j,l}, \tag{18}\]where \(c_{c}\_t_{i,j,l}\) is the waiting time of workpiece \(J_{i}\) before finishing being machined on machine \(l\) at stage \(j\) if workpiece \(J_{i}\) chooses action \(a\) in stage \(j-1\) and transfers to machine \(l\) at stage \(j\). \(FT^{\prime}_{j,l}\) is the updated finishing time after machine \(l\) at stage \(j\) being selected by action \(a\):  
\[FT^{\prime}_{j,l}=FT_{j,l}+t_{i,j,l}. \tag{19}\]  
Note that \(BT_{j,l}\) is the time when machine \(l\) begins to work, which is not necessarily equal to \(ST_{i,j,l}\), \(\omega\) and \(b\) is a positive constant, making the reward function negatively correlated with \(c\_t_{i,j,l}\). Generally, it takes two to five to distinguish the reward function of good action from others.
###### Abstract  
Afforestation of former agricultural land poses a real challenge for foresters because soil life is often severely limited by the loss of natural soil fungal diversity. In addition, former agricultural soils have low levels of fungal species typical of forest soils, which have a unique microbiome that plays a protective role (antagonists, plant growth promoters, mycorrhizal fungi, etc.). This study aimed to determine the effect of using organic material in the form of bark compost, wood waste, and sawdust to improve the soil mycobione of soils that have been damaged by their agricultural use. This study used experimental plots established 20 years ago, and we compared the biodiversity of the treated soils with that of the control soils by analysing soil samples with powerful molecular methods. Next-generation sequencing analysis of DNA extracted from soil samples and subsequent analysis of their species composition and biodiversity showed that the mycobione of soil fungi has been altered by the addition of various forms of organic material. The proportion of fungi belonging to the Ascomycota decreased in favour of species from the Basidiomycota and Mucoromycota. The dominant fungal groups in the soil of the control area were _Sagenomella_, _Wilcaxina_, _Oidiodendron_, _Melinomyces_, and _Penicillium_. Enrichment with organic matter by adding bark compost under the roots led to an increase in _Penicillium_, _Inocybe_, and _Amphinema_. The application of bark compost on the surface led to an increase in the dominance of _Inocybe_ fungi in the soil. The mycobione of the plant to which woody debris was applied was characterised by a marked dominance of fungi of the genera _Russula_, _Oidiodendron_, and _Penicillium_. Similar ratios were found in the plant to which sawdust was applied, where the fungi _Melinomyces_, _Penicillium_, _Oidiodendron_, and _Russula_ dominated. A comparative analysis of fungal diversity with the Shannon diversity index showed that the most diverse fungal communities were found in the sawdust plant (6.56), while the control sample (a soil sample from an agricultural area where no organic material was applied) had an index of 5.71. After the treatments, more potential antagonists against pine pathogens and mycorrhizal fungi were found to form beneficial symbiotic relationships with them. In our opinion, the results of this study show that it is worthwhile to introduce different forms of organic matter to post-agricultural land to improve soil biodiversity and mycorrhizal associations of pine roots with fungi to ensure the sustainability of the first generation of forests created.  
species diversity; pathogens; saprobes; mycornhize associations; NGS; relative abundance; Venn diagrams; OTUs; Shannon diversity; Bray-Curtis dissimilarity index +
Footnote †: journal: Applied Sciences
# MIMO Relaying UAVs Operating in Public Safety Scenarios
## 1 Introduction
### Communication Procedure Using Sidelinks  
D2D is established using the PC5 interface. The basic procedure to connect elements in the network is performed in three steps: Discovery, Synchronization, and Communication. Discovery includes the steps for finding UEs and non-user devices. The protocol stack includes MAC and PHY layers and uses the sidelink reference signal received power (S_RSRP) in all subchannels to select the relay UAV available to establish the connection.  
Synchronization refers to the protocol message exchange and connection configuration. Both control signals that configure sidelink identification are the primary and secondary sidelink synchronization signals (SPSS) and (SSSS), respectively, in frequency and time known as the sidelink synchronization signals (SLSS) and the master information block-sidelink (MIB-SL), which is used for information. A header field in the SLSS signal (SLSS ID) at the receiver UE identifies a connection between the transmitter and the relay in LTE.  
The synchronization requirement relationship is described in Equation (1).  
\[\text{S\_RSRP}-MinSrsrp>syncRef_{fltrs} \tag{1}\]  
where the S_RSRP is the sidelink reference signal received power measured, \(MinSrsrp\) is the minimal signal power configured in the UE and \(syncRef_{fltrs}\) is the preconfigured threshold available and the relay and in the UE.  
This procedure is necessary because both UEs are not connected together and the receiving UE needs information from the MIB (e.g., sl-bandwidth, in-coverage status, directFrameNumber). The strongest S_RSRP is selected as the \(syncRef_{fltrs}\) UE. Sender synchronization is required when the resource pool associated with transmission (Tx) is not from a neighboring cell or from an in coverage UE. UAV usability provides the reference signal to other devices by taking advantage of the line-of-sight (LoS) UAV characteristics.  
Figure 2: Public safety scenarios available in device to device communication using UAVs.
## 4 Discussion
### GPP Variation and Its Relationship with Climate Zones  
GPP principally occurs through the photosynthesis and an endothermal reaction processes, which requires a distinctive activation of energies from different ambient temperatures [64; 65]. Therefore, the relationship between temperature, precipitation sensitivity and GPP is attributable to the energy required in different temperature zones, the reason why the apparent response of GPP to precipitation and temperature is confounded by the positive correlation between GPP variations and precipitation and between GPP and LST (Figures 8 and 9).  
By encountering the effects of evapotranspiration and water stress on GPP change, results indicated high GPP trend values (from both modelled GPP and observed GPP values) in the humid zones (AI > 0.65 and AI > 0.75) as the UNEP and UNESCO classifications.  
This effect of AI on GPP variations confirmed the discussed effects of climate factors (precipitation and land surface air temperature) in the Section 4.1 (Figure 11).  
Generally, the spatial gradients of regional climate zones from hyper-arid to humid and GPP variations in Figure 10 indicated a consistency of the fact that GPP or carbon uptake through photosynthesis processes increase with the increase of precipitation and  
Figure 11: Scatter plots indicating the trend GPP change per climate zone; (**a**) represents variations of GPP per UNESCO Aridity Index, and (**b**) indicates variations of GPP per UNEP Aridity Index.  
Figure 10: Comparison of temporal variations in GPP and climate factors (air temperature and precipitation). (**a**) Annual mean GPP with annual mean precipitation, and (**b**) annual mean GPP with annual mean land surface air temperature.  
temperature. These results converge with previous studies that examined the effect of climate factors on GPP variations using an inter-comparison of multiple models [66; 67], where they concluded that GPP varies proportionally with precipitation and temperature. Our results pointed out that the spatial and temporal variations of GPP were mainly controlled by the temperature and precipitation variability.  
Previous studies reported that global warming will significantly influence many ecosystem shifts in the 21 st century during the pre-industrial period and reported that the temperature is expected to increase by \(\sim\)1.5 \({}^{\circ}\)C and 2 \({}^{\circ}\)C [13; 68; 69]. Therefore, the investigation of the effects of the climate factors on GPP variations in this study indicated that, currently, temperature affects GPP variations at 65%, while precipitation acts upon GPP variations at 60%. Thus, the current study reflects the implication of positive feedback between climate warming and the GPP variability alerting that may regulate or manage the rate of the carbon sequestration process. The knowledge from this study could help to better understand future climate effects on carbon fluxes (carbon pools/stock), carbon sequestration and environmental management processes under different ecological systems and climate variability.
# Dental Applications of Optical Coherence Tomography (OCT) in Cardiology
## 3 Applications of OCT
### Caries Therapy
#### 3.3.2 Remaining Dentin during Caries Removal  
Opening the pulp chamber during caries removal of deep lesions or tooth preparation is a major risk in the maintenance of the pulp vitality and the tooth, and should therefore be avoided. However, during the treatment of dentin areas close to the pulp, an atrogenic opening of the pulp complex is sometimes difficult to prevent due to the unknown and invisible location of the pulp chamber.  
In contrast to an introduced indirect measuring method based on the determination of the electrical resistance of the residual dentin (prepometer(tm), Hager and Werken, Duisburg, Germany), the  
Figure 14: (**a**) Extracted human molar before; and (**b**) after fissure sealing with Helioseal. (**c**,**d**) In cross-sections through ROI 1 and 2 occlusal caries beneath the sealer can be identified (L). Using SD-OCT, carious lesions (L, shadow) can be localized (**e**,**g**) before; and (**f**,**h**) after sealing. The sealer (S) has penetrated into the fissures, is inhomogeneously distributed and adapted to the enamel surface with (**f**, white arrows) or (**h**) without interfacial gap; (**f**) The bright signals reveal an interfacial gap (white arrows) between sealant and enamel. Monitoring will reveal changes over time.  
OCT offers great potential for imaging the outline of the pulp chamber. The remaining dentin thickness and pulp geometry, e.g., pulp horns, can be visualized in vitro during dental procedures using optical coherence tomography [56; 57; 58; 59]. We found that the roof of the pulp chamber could be displayed using SD-OCT at a mean distance through dentin of 850 \(\upmu\)m, whereas the minimum remaining dentin thickness which could be imaged was 45 \(\upmu\)m (Figure 15), and is in accordance with [PERSON] et al. [57]. Therefore, the OCT technique could be a valuable diagnostic tool during dental treatment and help prevent accidental pulp exposures by estimating the remaining dentin thickness.
## 3 Materials and Methods
### Communication Layer
#### 3.7.1 GPRS  
General Packet Radio Service (GPRS) is a very widely deployed wireless data service, available with most GSM networks. It offers throughput rates of up to 114 kbps, enabling mobile handsets to access online services at a similar speed to a dial-up modem, but with the convenience of being able to connect from almost anywhere. GPRS enables people to enjoy advanced, feature-rich data services, such as e-mail on the move, multimedia messages, social networking and location-based services.  
The RaspBerry-Pi is connected to a GPRS modem, which allows establishing a communication with the remote server. When the software sends an instruction to send data, the Raspberry-Pi switches on the modem and send the files. The modem used is the Huawei E220 USB dongle modem [48]. A similar modem is also connected to the server in such a way to receive the data coming from the hub.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **WiMAX** & **ADSL** & **Wi-Fi** & **GPRS** & **Satellite Communication** \\ \hline
**Wireless?** & Yes & No & Yes & Yes & Yes \\ \hline
**Distance Covered** & Up to 70 km & Everywhere & & & Up to 5 km & Everywhere the \\  & from the CPE & with cable & & from the BS & signal satellite is on \\ \hline
**Subscription Costs** & About 20\(\copy\) & About 20 \(\copy\) & About 20\(\copy\) & About 20\(\copy\) & About 100\(\copy\) \\
**Availability in** & & & & & \\
**rural area** & Medium/High & No & No & Medium & Yes \\ \hline \hline \end{tabular}
\end{table}
Table 3: WiMAX _vs._ other communication technologies.
# A GNSS/5G Integrated Three-Dimensional Positioning Scheme Based on D2D Communication
## 3 Results
It is also obvious that the improvement is slight as we increase the number of the particles under circumstance of conducting the DBSCAN process in advance. Moreover, it is clear that the improvement of RMSE is really small when the number of the particles exceeds 100. Thus, to guarantee the performance, as well as to save the computational resources, we choose 100 particles in our numerical simulation. Figure 8: RMSEs versus the number of particles. Figure 7: Positioning results of a moving MU.
# Supporting Immersive Video Streaming via V2X Communication
## 2 Bandwidth Allocation for Diverse Streaming Services in V2X Communication
Real-time applications, which require immediate transmission and are highly sensitive to delays, are prioritized to prevent user dissatisfaction due to interruptions. Conversely, video segments of non-real-time applications can be pre-downloaded during less congested road sections. Furthermore, RSUs prioritize the bandwidth needs of premium users over regular users. This means that bandwidth allocated to regular users may be reallocated to premium users to ensure superior service quality. If bandwidth demand remains unmet or if bandwidth originally assigned to regular users is reassigned to premium users, RSUs activate the \"Vehicle Fleet Bandwidth Coordination\" module to establish a cooperative fleet. This module utilizes V2V communication to relay content, effectively using the remaining bandwidth in non-congested road sections. During video application operation, the vehicle's \"Bandwidth Calculation for Vehicle Video Applications\" module continuously monitors network conditions and adjusts bandwidth usage. When the vehicle traverses congested road sections with heavy network traffic, the module dynamically adjusts the video quality to decrease bandwidth demand and prevent video stuttering, thereby maintaining user satisfaction. Conversely, in non-congested road sections, the module enhances the video quality of real-time videos to ensure stable and smooth playback, providing users with an enhanced viewing experience across different network environments. For non-real-time video, segments will be preloaded as much as possible to ensure playback at the expected time frames.
## 3 Results and Discussion
### Angular Characteristics
#### 3.3.2 Lasers with an Unstable Cavity
Figure 11: Angular energy distribution of Raman lasers: a—with flat cavity, b and c—with unstable cavities, where the radius of the convex mirror curvature is 2000 and 750 mm, correspondingly. Figure 12: Imprints of the radiation from an unstable-cavity laser, obtained using a 250 mm lens. We are continuing to study and optimize Raman lasers with unstable cavities with the goal of obtaining angular divergence which is close to diffraction-limited divergence.
## 2 Wireless Body Sensor Networks and QoS
### QoS in Wireless Body Sensor Networks
#### 2.2.3 Mechanisms for QoS in WBSNs  
Any method that improves the system performance in terms of QoS can be considered as a QoS mechanism, and a number of such mechanisms are available [10]. Table 4 summarizes these mechanisms along with their supported QoS. Adaptability includes user level adaptability, as well as the network's level. Existing works in WBSNs may include one or more of these mechanisms. For instance, the authors in [11,18,19] have considered collision management, error control and service differentiation. The dynamic nature of wireless links or channels of WBSNs or BANs is a challenging issue in providing QoS. Hence, from the QoS perspective, MAC protocols are more important than others (e.g., routing protocols, transport protocols). It is clear from Table 4 and existing works [10,11,18,19,20] that error recovery is one of the strongest mechanisms that can support most of the QoS requirements listed in Table 3, including network lifetime and real-time data delivery by avoiding retransmissions. ARQ, FEC and NC are the three main error recovery mechanisms.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Priority Level** & **Cardiovascular** & **Asthma and Allergy** & **Diabetic** & **Heart-Attack** \\ \hline Level one & Blood pressure & Oxygen saturation (\(S_{p}O_{2}\)) & Blood glucose & ECG \\ Level two & ECG & \(CO_{2}\) & Blood pressure & Blood pressure \\ Level three & Blood glucose & ECG & \(S_{p}O_{2}\) & \(S_{p}O_{2}\) \\ Level four & \(S_{p}O_{2}\) & Blood pressure & \(CO_{2}\) & \(CO_{2}\) \\ Level five & \(CO_{2}\) & Blood glucose & ECG & Blood glucose \\ Level six & Gyroscope & Gyroscope & Temperature & Temperature \\ Level seven & Temperature & EEG & EEG & EEG \\ Level eight & EEG & Temperature & Gyroscope & Gyroscope \\ \hline \hline \end{tabular}
\end{table}
Table 2: Importance level of physiological signals in some medical applications.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**QoS Requirements** & **Network/User Perspective** & **Metric Involved** \\ \hline Real-Time Data Delivery & Both & Delay \\ Reliable Data Delivery & Both & Packet loss rate (PLR) \\ Adaptive to user Queries & User/Application & Sensor priority \\ Network Lifetime & Network & Energy efficiency \\ Adaptive to Network Channel Conditions & Network & Packet error rate (PER) \\ \hline \hline \end{tabular}
\end{table}
Table 3: QoS requirements for WBSNs from network and user perspectives.