esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Extension to Switching Topologies and Dynamic Leaders
From the analysis in (18)-(20), it is easy to verify that \(\bar{\mathbf{\Gamma}}(k)\) also is a stochastic matrix when \(\lambda>\lambda_{min}\) (\(\lambda_{min}>b^{2}/4\)). Define \(\bar{\Omega}(k)=\max\{y^{+}(k),\bar{w}^{+}\}\) and \(V_{2}(k)=\bar{e}^{+}(k)^{2}\), where \(\bar{e}^{+}(k)=\bar{\Omega}(k)-\bar{w}^{+}\). \[\Delta V_{2}(k+1)=\big{(}\bar{\Omega}(k+1)-\bar{\Omega}(k)\big{)}\big{(}\bar{ \Omega}(k+1)+\bar{\Omega}(k)-2\bar{w}^{+}\big{)} \tag{33}\]  
Rewrite \(y_{i}(k+1)\) as  
\[y_{i}(k+1) =\sum_{j:y_{i}(k)=y^{+}(k)}\hat{\gamma}_{ij}(k)y_{j}(k)+\sum_{j:y _{j}(k)<y^{+}(k)}\hat{\gamma}_{ij}(k)y_{j}(k)\] \[+\sum_{l=N+1}^{N+M}\hat{\gamma}_{il}(k)w_{l}(k) \tag{34}\]  
Following the same steps from (23) to (26), one concludes  
\[\Delta V_{2}(k+1) =0,\text{if }\bar{e}^{+}(k)=0.\] \[\Delta V_{2}(k+1) \leq 0,\text{if }\bar{e}^{+}(k)\
eq 0.\]  
One only needs to prove that there does not exist a time instant \(K_{2}\) such that \(\Delta V_{2}(k+1)\equiv 0\). Assume that \(\Delta V_{2}(k+1)\equiv 0\) when \(k>K_{2}\). Define \(\mathcal{S}_{2}(h)=\{i|y_{i}(K_{2}+h)=y^{+}(K_{2})\}\) and \(N_{2}=\operatorname{card}(\mathcal{S}_{2}(0))\). Since \(\Delta V_{2}(k+1)\equiv 0\), it means \(y^{+}(K_{2}+h)=y^{+}(K_{2})\) for all \(h>0\), i.e., \(\operatorname{card}(\mathcal{S}_{2}(h))>0\) must hold for all \(h>0\). According to Assumption 5, at least one agent in \(\mathcal{S}_{2}(h)\) whose neighbor's output is less than \(y^{+}(K_{2})\), i.e., there exists a certain follower \(y_{p}(K_{2}+h)\) satisfying \(y_{p}(K_{2}+h)\in\mathcal{S}_{2}(h)\) and \(s_{p}(K_{2}+h)\
eq 1\). From (27), one gets  
\[\operatorname{card}(\mathcal{S}_{2}(N_{2})) \leq\operatorname{card}(\mathcal{S}_{2}(N_{2}-1))-1\] \[\leq\operatorname{card}(\mathcal{S}_{2}(N_{2}-2))-2\] \[\cdots\] \[\tilde{\mathcal{T}}_{ii}(k)=1-\frac{d_{i}(k)\rho_{i}\phi_{i}(k)\widehat{\phi}_ {i}(k)}{\lambda+|\widehat{\phi}_{i}(k)|^{2}} \tag{32}\]0  
which contracts to \(\operatorname{card}(\mathcal{S}_{2}(h))>0\). Therefore, the assumption is violated. In summary, one concludes that \(\bar{e}^{+}(k)\) converges to 0. This completes the proof. When the leaders become time-invariant after time instant, one has \(\bar{w}^{+}=\max_{l}w_{l}\) and \(\bar{w}^{-}=\min_{l}w_{l}\), and the result in Theorem 4.2 will regress to the result in Theorem 4.2.
## 4 Presentation and Discussion of the Results
### Effective Identity Management  
As discussed in Section 2.4, Sybil and whitewashing are two problems that result from a lack of effective identity management. In [16, 18, 19, 40, 44], it is proposed to map the user on the e-commerce platform and its identifier on the blockchain. This way, the user is always the same in each platform, enabling the cross-analysis of its activity in all platforms, as well as its reputation score is coherent from one platform to another. Additionally, the aforementioned problems, Sybil and whitewashing, are also addressed because it is not easy to create new and false identities.  
In the case of permissioned blockchains, their management is ensured by a consortium of platforms [41, 42]. In order to be accepted in the consortium, a platform must follow the imposed rules. In terms of user management, the authors proposed a central authority for managing users, validating their identities, as well as certificate issuing.  
Due to its properties, blockchain-based reputation systems enable new models based on economic viability and community-driven collaboration, as well as a means for better identity management, which reinforces the effectiveness of existing algorithms for deriving reputation scores. These new models do not solve the problem of data quality and lack of confidence in the blockchain oracles, but they are empowered by the immutability and tamper-proof properties provided by the blockchain.
## 3 Results
### Analysis of Vegetation Resistance and Resilience to Drought  
The spatial distribution of vegetation resistance and resilience to drought in the study area is illustrated in Figure 8. Vegetation resistance in the West Liao River Basin exhibits significant spatial heterogeneity. Overall, resistance levels are relatively high, but lower in the eastern, central, and southern regions, where resistance indices mostly range between 5 and 10. In contrast, the western region shows higher resistance indices, generally exceeding 10, indicating stronger drought tolerance in these areas.  
Vegetation resilience indices in the basin range from 0.6 to 1.28. Regions with higher resilience are primarily located in the west and center, where vegetation recovers more rapidly after drought. Conversely, resilience is weaker in the eastern and southern regions, likely due to local climatic conditions, soil types, and vegetation characteristics.  
In summary, the spatial distribution of resistance and resilience reveals notable regional differences in vegetation response to drought. The western region demonstrates both high resistance and strong resilience, suggesting robust drought adaptation. In contrast, the eastern and southern regions exhibit weaker resistance and resilience, making them more vulnerable to drought impacts. This spatial heterogeneity is likely influenced by regional climate conditions, vegetation types, soil moisture, and human activities.
# Reviewing Automated Analysis of Feature Model Solutions for the Product Configuration
## 5 Discussion
### Efficient Diagnosis Solution  
FastDiag algorithm permits determining a preferred or leading diagnosis concerning a previously defined relevance order of constraints in the knowledge base. FastDiag follows the algorithmic structure and reasoning of QuickXplain for a different purpose, that is, the diagnosis detection without the calculation of MCS instances. Hence, FastDiag is based on conflict-independent search strategies [52]. Algorithms 3 and 4 give the pseudo-code of FastDiag functions. ```
1:if\(C=\emptyset\)or\(\textsc{InConsistent}(AC-C)\)then
2:\(return(\emptyset)\)
3:else
4:\(return(\textsc{FD}(\emptyset,C,AC))\)
5:endif
```  
**Algorithm 3**FastDiag\((C,AC):\)_diagnosis_\(\Delta\)  
Assuming that conflicts to diagnosis exist, If the conflict set \(C\) is non-empty, and \(AC\) without \(C\) is consistent, algorithm FastDiag calls and waits for the recursive results algorithm FD. FD first reviews the consistency of \(AC\) as a source of diagnosis. Because always \(AC\) contains \(C\) and does not contain \(D\), initially \(S\) is the constraints set with conflicts and \(D\) is empty, when \(D\) is not empty, and \(AC\) is consistent \(D\) is the source of conflict. When that base case is not accomplished, either because \(D\) is empty (such as at the beginning) or \(AC\) is consistent (this is only possible after removing elements from \(AC-D\) represents the last removed elements from \(AC\)), then \(AC\) is still in conflict, and \(C\) is a source of conflict. Then, FD reviews the size of \(C\) since if it were minimal (size 1), then \(C\) is the diagnosis. If \(C\) is not of minimal size, FD proceeds to partition \(C\) in the sets \(C_{1}\) and \(C_{2}\), of which the last one corresponds to the most preferred partition. Afterwards, FD calls FD over \(C_{2}\), \(C_{1}\) and \(AC-C_{2}\) to review if \(C_{2}\) is the diagnosis source, and if not so, to continue reviewing \(C_{1}\) with that goal. Tables 7 and 8 show the tracking execution of FastDiag on the Feature Model product configuration of Figure 7. The diagnosis corresponds to the solution of each MCS, in this case, {glchess, \(\
eg\)gnome}. In column \(AC\), the symbol \(\Gamma\) represents the consistent knowledge base of the Feature Model.
## 1 Introduction
To monitor agriculture, the environment, or water resources, using sensors deployed remotely at the site, we need to acquire the data wirelessly using a WSN. The available wireless connectivity systems, such as Zigbee, BLE (Bluetooth Low Energy), and WiFi, have very short range [18] compared to the geographical distributions of the water resources. Long-range wireless connectivity based on cellular networks, such as GPRS (General Packet Radio Service), 3G, WiMax, LTE (Long-Term Evolution), and NB-IoT (Narrow Band-IoT), lacks geographical coverage of most of the water resources due to large power requirements and infrastructural and operational costs. On the other hand, the long-range and low-power wireless technologies, such as LoRa (Long-Range), Sigfox, and Ingenu, are not capable of image-based monitoring. Lastly, the network topology to be used for the WSN depends on the geographical distribution and locations of the resources and the parameter to be monitored. Therefore, considering the limitations of wireless technologies, the need for various on-site sensors over the widely spread resources, and the lack of accessibility, this research proposes a lightweight dynamic auto-reconfigurable protocol (LDAP) to facilitate the implementation of the sensor network for real-time and long-term WARM applications. Some sensor-based solutions, including the presently available WSNs used for WARM applications, are described in the following section, followed in Section 4 by the problem formulation and the detailed description of the proposed LDAP. Section 5 describes the field trial of the LDAP for a WQM application, followed by Section 6, describing the performance of the LDAP in terms of features and WSN implementation. Section 7 concludes the paper with the future scope of LDAP applications.
# Adaptive Beamforming Applied to OFDM Systems
## 3 Proposed Method for OFDM Adaptive Antenna Array
Differently than the works presented in the literature, the RSC allows the semi-unsupervised mode, where the reference vector \(\textbf{\hat{s}}(n)\) combines pilot carriers with decided data carriers using the Decision Directed (DD) algorithm. The LMS algorithm is executed in the OFDM sample time, \(t_{s}\) (see Equation (1)), and this enables one to adjust the antenna array gains, \(\textbf{f}(m)\), faster than the works proposed in [19; 22; 32; 33; 34; 35]. The LMS implements the equation given as:  
\[\textbf{f}\left(m\right)=\textbf{f}\left(m-1\right)+\eta e\left(m\right) \textbf{u}\left(m\right) \tag{42}\]  
where \(\textbf{u}\left(m\right)\) (see Figure 3) is expressed as:  
\[\textbf{u}\left(m\right)=\left[ \begin{array}{c}u_{0}\left(m\right)\\ \vdots\\ u_{v}\left(m\right)\\ \vdots\\ u_{K-1}\left(m\right)\end{array} \right] \tag{43}\]and \(\eta\) is the adaptation step. It is important to observe that when \(n\leq N^{DD}(n=0,\ldots,N^{DD})\), the reference signal, \(\mathfrak{s}\left(n\right)\), uses just pilot carriers and zeros, and it creates a estimated version of the reference OFDM symbol, \(\mathfrak{s}\left(n\right)\). Differently than the works proposed in [19; 22; 32; 33; 34; 35], the reference signal, \(\hat{s}_{j}\left(n\right)\), does not need to wait for the C OFDM samples (or one OFDM symbol) to update (see Equation (42)).
## 3 Fabrication of Graded Index Glass Waveguides (Fraunhofer IZM)
### Two-Step Ion Diffusion Fabrication Process
The test waveguides had a length of 190 mm and each glass section contained one group of 12 parallel straight waveguides with a center-to-center channel pitch of 250 \(\upmu\)m. By varying the process parameters, one can vary the characteristics of the waveguide including the waveguide dimension, NA and distance of the maximum refractive index point from the glass surface, which in turn will affect the coupling and propagation losses of the waveguide. To this end, two different sets of test waveguide samples were produced with different diffusion times and silver salt melt concentration. These sets were given the internal designations \"set 1\" and \"set 7\" as the intervening five sample set processes were not completed. In particular the diffusion time from parameter set 7 was longer than that of set 1. Refractive near field (RNF) scans were conducted on both sets of waveguides to determine their cross-sectional refractive index profiles. Figure 8a,b respectively show the horizontal refractive index profiles of set 1 and set 7. Waveguides fabricated according to parameter set 1 showed a refractive index maximum shifted to a depth of around 15 \(\upmu\)m below the glass surface, while for waveguides fabricated according to parameter set 7, the index maximum was shifted to a depth of 30 \(\upmu\)m. The refractive index differences measured between core center and cladding were 0.025 for set 1 and 0.029 for set 7 with corresponding NAs of 0.27 and 0.3 respectively, and the size of the set 1 waveguides are smaller than that of the set 7 waveguides. These relative waveguide characteristics are an expected consequence of the longer diffusion time in set 7.
## 4 Protocol Description
### Route Establishment  
At periodic intervals of 30 s, each node broadcasts a BEACON message to its one-hop neighbors for the purpose of neighbor discovery, topology maintenance, time synchronization and route discovery to the gateway. The BEACONs are used to compute running estimates of the link qualities between each node and its one-hop neighbors. This estimated link quality is subsequently used to determine the forwarding set from the node to the gateway.  
Each sensor node is associated with a gradient (metric) towards the gateway node. The metric of an arbitrary node \(v_{i}\) is denoted as \(m_{i}\). Generally, packets flow from nodes with higher gradients to nodes with lower gradients. In our testbed, the gateway \(v_{g}\) is initialized with a metric value of \(m_{g}=0\); all other nodes in the network are initialized with a default invalid metric value of \(-1\). This metric information is piggybacked in the BEACONs that are transmitted by each node.  
Upon receiving a BEACON with a valid metric value (_i.e._, \(m_{i}\geq\) 0) from an arbitrary neighbor \(v_{i}\), each node \(v_{j}\) will update its metric value \(m_{j}\) to the gateway as follows: the metric of node \(v_{j}\) through the use of neighboring node \(v_{i}\) is given by \(m_{j}(i)=m_{i}+\Delta\), where \(\Delta\in\Re^{+}\). If the estimated link quality between \(v_{i}\) and \(v_{j}\) is above a pre-determined threshold \(T\) and the metric through \(v_{i}\) provides a better gradient to the gateway than the current metric (_i.e._, \(m_{j}(i)<m_{j}\)), \(v_{j}\) updates its metric, such that \(m_{j}=m_{j}(i)\). In our indoor testbed, we use the values of \(\Delta=10\) and \(T=80\%\). Due to the transient nature of the wireless links in the network, the neighbor list and metric of a node can expire if the node does not receive BEACONs from its neighbors after a period of time.
# Vinamecum: A Computer-Aided Method for Diagnoses of Pests and Diseases in the Vineyard
## 1 Introduction  
Grapevines (_Vitis vinifera_ and _Vitis_ spp.) are one of the most extensively grown and economically important woody perennial fruit crops in the world [1]. According to the FAO (2019) [2], the European continent, with 3.46 million ha and 26.7 million t, leads grape production worldwide and is followed by Asia (1.99 million ha and 29.51 million t), America (0.96 million ha and 14.4 million t), Africa (0.34 million ha and 4.89 million t), and Oceania (0.17 million ha and 1.97 million t). Its cultivation is limited by the climatic demands imposed by optimal plant development [3] and the incidence of diseases and pests, which can compromise its productivity [4; 5]. Chemical control has traditionally been used in conventional vititulture to control pests and diseases in the vineyard [6]. However, this practice is potentially leading to pollution [7] and human health issues [8]. For this reason, the use of phytosanitary products has been regulated in some countries. For example, in Europe, the Directive 2009/128/EC [9] established a framework for Community action to achieve the sustainable use of pesticides and the promotion of integrated pest management (IPM). IPM is an ecosystem-based strategy that focuses on the long-term prevention of crop pests and diseases through different techniques that include the use of resistant varieties, biological control, habitat management, modification of cultural practices and, when needed, judicious and timely use of chemical controls [10; 11]. To implement this strategy in vineyard management, it is necessary to have qualified technical personnel and provide specific information to farmers so that they can act under the premises of the IPM.  
The widespread growth of information and telecommunication technologies (ICTs) in rural areas offers new opportunities to provide more timely and low-cost information services to farmers, as well as assists in coordinating agricultural agents [12]. Moreover,the enormous progress of mobile devices has opened up a wide range of opportunities that were previously unfeasible. Their portability and computing performance are features that have allowed the development of innovative applications in fields such as medicine, sports, and agriculture [13]. However, in the field of viticulture, new technologies and modern management techniques are needed to ensure and facilitate a correct performance of the winegrowers in order to obtain a quality harvest and reduce the environmental impact. The goal of the present work was to develop a novel smartphone application, called Vihamecum [14], to facilitate a correct control of grapevine diseases and pests and boost IPM in vineyards. This application allows the identification of species suspected to act as pests or pathogens in the vineyard and incorporates technical information on their biological cycles, the different control strategies and images of the damages or symptoms they cause. The application was developed and implemented for mobile devices with the aim of maximizing its availability to users.
# Improved Exponential Phase Mask for Generating Defocus Invariance of Wavefront Coding Systems
## 4 Discussion  
The improved exponential phase mask exhibits good defocus invariance of MTF curves, as shown in the simulation results in Section 3. The area of MTF represents the imaging quality of the system, and that of the exponential phase mask has the smallest change with defocus, which guarantee image quality at different defocus values. However, from the simulation of Fisher information, that of the improved exponential phase masks shows higher than the sinusoidal phase mask, which means the PSF invariance is higher. As the Fourier transform of the PSF contains MTF and phase transfer function (PTF), the improved exponential phase mask has high MTF invariance but the PTF has a larger change with defocus. The main feature is to make the peak position closer to the origin and retain the high invariance of the MTF curves. The image simulation results confirm this conclusion.
# Telemedicine: A Survey of Telecommunication Technologies, Developments, and Challenges
## 4 Evolution of Communications Technologies for Telemedicine
### Mobile Networks  
The advancement of mobile communications technology from the second generation (2G) to the fourth generation (4G) and beyond has brought about its widespread adoption of telemedicine. The authors of [111] opined that the evolution of 3G and mobile technologies will be the main propelling force for the future development of telemedicine. 2G mobile communication used Time Division Multiple Access (TDMA); next, General Packet Radio Service (GPRS) came online making possible a 115 kbps data rate [111]. In, [74], the authors proposed transmission of patients's relevant physiological signs to a remote server using the GSM/GPRS network. As highlighted by [63], using GPRS may not be the best option for communication with a remote server; especially when high-bandwidth connectivity is the goal, using Universal Mobile Telecommunications System (UMTS) and Long-Term Evolution technology tends to provide much higher throughput. The work of [112] showed  
Figure 11: Use of Thuraya Phone for Telemedicine.  
that the application of GSM/GPRS for communication in telemedicine can provide high reliability and performance in remote monitoring of patients by caregivers.  
The mobile cellular networks used in communications technology have continued to evolve over time. The second-generation (2G) mobile network was based on the Global System for Mobile Communication (GSM). This has progressed to 3G, 4G, and 5G, with the next generation being 6G. Telemedicine has always leveraged the advancement and development of mobile networks. As such, the various communication techniques involved are discussed below and illustrated in Table 4. In certain scenarios, using all of the available mobile technologies may be required; as evidenced in [113].
# _Arthrospira platensis_ Cultivation in a Bench-Scale Helical Tubular Photobioreactor
## 2 Materials and Methods  
### Microorganism and Cultivation Medium  
The cyanobacterium used in this work, _Arthrospira platensis_ UTEX LB 1926, was acquired from the University of Texas Culture Collection. The following information on this strain is provided by the supplier ([[https://utex.org/products/utex-lb-1926?variant=309920](https://utex.org/products/utex-lb-1926?variant=309920)]([https://utex.org/products/utex-lb-1926?variant=309920](https://utex.org/products/utex-lb-1926?variant=309920)) 92299354#details, accessed on 20 January 2022): UTEX Number: 1926; class: Cyanophyceaeae; medium: Enriched Seawater Medium (ES); origin: San Diego, CA, USA; location: Del Mar Slough; isolation: [PERSON] in 1969; deposition: [PERSON] in 10/12/72; relatives: UTEX LB 1928; PCC 7345, PCC reference strain; ATCC 29408; notes: deposited as CY-42; 11/5/70 to [PERSON] from [PERSON]; renamed by [PERSON]; taxonomy available in [45]. The inoculum for the photobioreactor was prepared in the medium of Schlosser [46], containing (g L\({}^{-1}\)): NaHCO\({}_{3}\), 13.61; Na\({}_{2}\)CO\({}_{3}\), 4.03; K\({}_{2}\)HPO\({}_{4}\), 0.50; NaNO\({}_{3}\), 2.50; K\({}_{2}\)SO\({}_{4}\), 1.00; NaCl, 1.00; MgSO\({}_{4}\)? H\({}_{2}\)O, 0.20; CaCl\({}_{2}\): 2 H\({}_{2}\)O, 0.04. The pH was 9.6. All nutrients were dissolved in distilled water containing (per liter): 6 mL of metal solution (97 mg FeCl\({}_{3}\)-6 H\({}_{2}\)O, 41 mg MnCl\({}_{2}\): 4 H\({}_{2}\)O, 5 mg ZnCl\({}_{2}\), 2 mg CoCl\({}_{2}\)-6 H\({}_{2}\)O, 4 mg Na\({}_{2}\)MoO\({}_{4}\)? H\({}_{2}\)O), 1 mL of micronutrient solution (50.0 mg Na\({}_{2}\)EDTA, 618 mg H\({}_{3}\)BO\({}_{3}\), 19.6 mg CuSO\({}_{4}\): 5 H\({}_{2}\)O, 44.0 mg ZnSO\({}_{4}\)? H\({}_{2}\)O, 20.0 mg CoCl\({}_{2}\):6 H\({}_{2}\)O, 12.6 mg MnCl\({}_{2}\):4 H\({}_{2}\)O, 12.6 mg Na\({}_{2}\)MoO\({}_{4}\)? H\({}_{2}\)O), and 0.15 mg of B12 vitamin.  
Fed-batch cultivations were conducted in this medium lacking NaHCO\({}_{3}\) and Na\({}_{2}\)CO\({}_{3}\) by adding daily pure carbon dioxide as a carbon source, according to the pulse-feeding mode of operation.