esa-sceva/satcom-chunk-collection huggingface dataset:
# Electronically Controllable Phase Shifter with Progressive Impedance Transformation at K Band
## 1 Introduction  
Antenna arrays have been one of the most used structural strategies for the design of directive antennas in microwave ranges with demanding radiation requirements [1]. In the last years, planar substrate-based antennas have been present in many phased array designs due to the low manufacturing costs, easy integration, and low weight and profile [2; 3]. This is particularly of interest in array structures such as reflectarrays and transmitarrays. In the case of the reflectarrays, the conformed reflectors are replaced by planar array structures that introduce at each array cell the desired phase shift, whose value is the one provided by the corresponding point of the equivalent reflector [4]. The transmitarrays are based on the same working principle, but the structure replaced by the periodic array is a lens instead of a reflector [5]. Both options have become a real alternative in reception/transmission systems whose specifications imply demanding requirements in terms of matching, directivity, gain, radiation pattern, or aperture efficiency [6]. The phase shifting strategy for both reflectarray- and transmitarray-based antennas depends on the system architecture and is typically obtained by a phase-delay circuit at each radiating cell of the array [7; 8]. This phase shift can be fixed in design, yielding a passive device, or tunable, yielding an active antenna. The tunable nature of the phase shifter can be provided either mechanically or electronically [6; 9]. Many of the designs of electronically controllable phase shifters are based on reflective inductance-capacitance (LC) tunable circuits [10], most of them focused on frequencies up to 3 GHz [11; 12; 13; 14]. This latter approach is the one that guides this work, leading to the design of electronically reconfigurable phase shifters at higher microwave ranges [10]. In this paperwe present a K band electronically tunable phase shifter based on reflective circuits with progressive impedance transformers and varactors. These impedance transformers provide an enhanced frequency bandwidth and an increase in the phase variation produced in the phase shifter [15].  
The relevance of our work is based on the combination of three main aspects, which are: the use of impedance transformers for increasing the phase variation range, the unitary phase shifter cascading, and the high operating frequency (18 GHz). These three elements combined confer interest to our work and provide a significant contribution related to previous works, such as [10] and [15]. In particular, the idea of using of impedance transformers proposed in [15] is now validated through prototypes. The document is organized as follows: Section 2 depicts the phase shifter working principle and presents the shifter design, while Section 3 presents the validation through the manufacture and measurement of a prototype. Finally, conclusions are outlined in Section 4.
## 7 Results and Discussion
### Results
#### 7.2.1 Throughput  
Every cluster group has a cluster head in the proposed scheme based on various factors (i.e., node mobility, the distance between node and base station and residual energy). Figure 8a,b shows throughput versus the number of rounds with different mobility speeds of nodes. It can be observed from the graphs that the throughput decrease with the increasing mobility speed of the nodes. It is due to the nodes dropping out of the cluster, which leads to frequent link disconnection. Furthermore, our proposed schemes CRP-GR and CRP-G provide better throughput as compared to FBCFP, TEEN and LEACH. The throughput of our proposed scheme is better due to optimum cluster head selection and best next hopping node selection with reinforcement learning. Similarly, decreasing packet loss is also improving throughput. The average performance of the proposed schemes CRP-GR and CRP-G with respect to throughput is 78% and 71%, while the existing schemes, such as FBCFP, TEEN and LEACH are 63%, 48% and 35% accordingly.
# Megalos: A Scalable Architecture for the Virtualization of Large Network Scenarios +
## 3 A Model of Container-Based Virtual Network and Its Scalability
### Scalability Requirements  
We assume to have at disposal a cluster of several physical or virtual _nodes_ which can be anywhere in the Internet. Each container is allocated to a specific node.  
We consider several scalability requirements. Some of them are well-known for any distributed architecture. For example: containers should be as ephemeral as possible and ready to be replaced by another instance at any point of time. Also, it should be possible to change the number of cluster nodes depending on the workload and according to real-time metrics. Finally, the physical allocation of containers should be distributed among the nodes according to a load balancing policy.  
Some other requirements are specific of our domain. Namely, consider two interfaces \(i_{1}\) and \(i_{2}\) of containers \(c_{1}\) and \(c_{2}\), respectively. Suppose that \(i_{1}\) and \(i_{2}\) are assigned to the same virtual LAN and that \(c_{1}\) is allocated to node \(n_{1}\) and \(c_{2}\) is allocated to node \(n_{2}\). The traffic between \(i_{1}\) and \(i_{2}\) should not be received by any node different from \(n_{1}\) and \(n_{2}\). Ifthis requirement is not satisfied, the traffic would risk to flood the entire infrastructure, impairing any scalability goal. Hence, once containers are allocated to nodes, we have two types of LANs; _intra-node LANs_ and _inter-node LANs_. The former are LANs whose interfaces are all assigned to containers allocated to the same node, while the latter are LANs whose interfaces are assigned to containers allocated to at least two different nodes. In each moment, it should be possible to determine the allocation of containers to nodes and, for each LAN, whether it is inter-node or intra-node. Also, for each LAN (inter- or intra-node), which are the nodes containing the interfaces allocated to that LAN.
# Resilience in the Internet of Medical Things: A Review and Case Study
## 6 A Case Study: Remote Patient Monitoring of a Heart Patient in the IoMT Networks
### Proposed Methodology
#### 6.3.4 Proposed Architecture by Using the Combination of MSA + SDN + ML  
The proposed architecture by using the integration of ML, SDN, and MSA technologies is shown in Figure 7. We have represented four different regions of patients that are connected to one IoMT network. An SDN controller with all its functionalities, such as route optimization, rule placement, monitoring, resource and recovery management, and traffic classification, takes place at its specific location. However, at any point, a failure at the controller node will break the communication with the different regions. This creates the situation of a single point of failure in the IoMT network. To avoid this situation of complete breakdown and the single point of failure of the controller, we have a backup route ready (represented through the red links in Figure 7) to transfer the data with a tolerable delay. This backup route uses the microservices architecture with the combination of ML and SDN to decentralize the functionality required for resilience into different nodes. By doing this, resilience features (monitoring (M), control (C), diagnosis (D), and recovery (R)) can be distributed across different nodes and provide resilience to each region.  
These backup routes (represented through the red links in Figure 7) interconnect different networks through specialized routers that consist of a software stack of SDN and ML technologies. These technologies are containerized and deployed through the microservices in this setup. These routers can share the routing information about the active nodes with each other so that the alternate routes can be determined in the case of failure.  
Monitoring of data traffic and real-time detection of anomalies can be conducted by running an ML model script in these routers. Furthermore, traffic management can be conducted by configuring the SDN controller by installing the Open vSwitch on these  
Figure 7: Proposed architecture by using the combination of SDN, ML, and MSA.  
routers. Now, we can integrate the ML model with the SDN controller and modify the data traffic according to the situation. It can create real-time topology information that maps out all the active connected nodes during the failure.  
This architecture provides the availability to the IoMT networks for urgent medical data transmission in the fault or failure scenario.
# Uncertainty Analysis Based on Kriging Meta-Model for Acoustic-Structural Problems
## 1 Introduction
The spectral stochastic method is also an alternative solution for stochastic problems. The basic concept of this method is to use a series expansion to model the relationship between the uncertainty of the input and output variability. The generalized polynomial chaos (gPC), one of the spectral stochastic methods, has already been applied in the modeling of uncertainty in various areas, such as structural dynamics [21], fluid dynamics [22] and acoustics [23; 24]. Generally when using computationally expensive simulation codes in complex engineering problems, it becomes impractical to perform a large number of simulations for the purpose of uncertainty quantification or design optimization. A better alternative lies in the use of approximations of the original models, which are often called meta-models. A surrogate model can be understood as a \"model of model\". It is a statistical model of the response surface of a simulation model. A surrogate model describes the relationship between inputs (i.e., model's adjustable parameters) and outputs (i.e., the performance measure of the simulation model) [25]. Surrogate models have primarily been developed for approximating deterministic simulations. Recent developments have explored their use in probabilistic analysis [26; 27; 28] and design optimization [29; 30; 31]. In [32], the authors performed a comprehensive study regarding the application of meta-models in mechanical systems. Response surface methodology (RSM) [33; 34; 35], Kriging [36; 37; 38] and neural networks [39; 40] are the most commonly used meta-models. This work presents the harmonic analysis of vibro-acoustic systems with taking into account uncertainties in geometrical and material parameters. The Kriging method is investigated to approximate the original model by representing the relationship between input parameters and output responses. In the proposed probabilistic method based on surrogate model, deterministic FEM are carried out to obtain the physical response of the system. MCS is performed by using Kriging meta-model in order to study the performance of the vibro-acoustic problems.
## 2 Electron Cyclotron Resonance, Cyclotron Autoresonance, and Brillouin Diagrams
### Beam-Wave Synchronism and Brillouin Diagrams
operating the gyrotron in a single mode regime (i.e., without exciting spurious parasitic modes). This subject is discussed in detail in the recently published comprehensive review paper [36]. At resonance, the electrons of the beam interact efficiently with the operating mode. As a result of this interaction, depending on their phase with respect to the wave, some of them lose energy and thus transfer part of their rotational kinetic energy to the wave, while the rest gain energy at the expense of the wave energy. Due to the dependence of the cyclotron frequency on energy (see Equation (5)), the former (with decreased \(\gamma\)) rotate faster in contrast with the latter (with increased \(\gamma\)), which rotate slower. This leads to azimuthal bunching of the electrons. With proper synchronization, when the operating frequency exceeds the cyclotron frequency, the formed bunch slips in phase toward the decelerating phase of the cavity mode, where the electrons lose energy due to _bremsstrahlung_ and transfer it up to the wave. The mechanism described is known as _electron cyclotron maser instability_, and accordingly, the gyrotrons are also called electron cyclotron masers (CRMs). Recall that \"maser\" stands for microwave amplification by stimulated emission of radiation. It should be mentioned, however, that this term is more or less an archisn nowadays, since the gyrotrons have already advanced to the THz frequency band. An adequate description of the physics of the underlying mechanism from a quantum mechanical point of view and in the framework of the relativistic electrodynamics can be found in numerous publications and monographs (see, e.g., [16; 17; 18; 19; 20]).
## 2 A New Security ANM Framework
### Distribution Security Constrained Optimal Power Flow  
The third layer consists of solving a multi-period distribution security constrained optimal power flow (D-SCOPF) for the day-ahead time horizon. The secure optimum settings for preventive and corrective control actions (available to the DSO) will be obtained from the solution of the D-SCOPF. For the results presented in this paper, historic load/generation profiles will be used, rather than actual day-ahead time series values. Only the critical case scenarios (i.e., extreme cases of load/generation variations) will be considered in this layer in order to maintain computational efficiency. In this way, the D-SCOPF algorithm will run over the set of all binding contingencies for the selected critical case scenarios. Furthermore, the optimisation problem will be solved in three stages: Normal operation (pre-contingency), short-term, and long-term post-contingency, as shown in Figure 1.  
The corrective controls are divided into short-term (VSC), long-term (LTC), and demand-shift, and DG curtailment. In the demand shift control scheme, a price \(\pi_{ds}\) will be paid to consumers in order to achieve the demand-shift services required by the DSO, \(P_{shift}\). In the DG-curtailment scheme, a compensation price, \(\pi_{dg}\) is set. Therefore, the DSO will pay to the DG owners the required curtailed power, \(P_{curt}\), at this price. The proposed D-SCOPF scheme also takes into account the cost  
Figure 2: The flowchart of steady-state security assessment.  
of power transfer losses, \(P_{loss}\), at the forecast energy market price, \(\pi_{em}\). It is assumed that \(\pi_{ds}>\pi_{dg}\) because it is desirable to reduce the levels of demand shifting than the levels of DG power curtailment, in prioritising consumer welfare. Consequently, the objective function of the proposed D-SCOPF algorithm is formulated as:  
\[F=\sum_{m\in\mathcal{M}_{c}}\Big{[}\sum_{w\in W}\pi_{dg}^{m}P_{curt\{w\}}^{m}+ \sum_{b\in N}\pi_{ds}^{m}P_{shift\{b\}}^{m}+\sum_{l\in L}\pi_{em}^{m}P_{loss\{ l\}}^{m}\Big{]} \tag{1}\]  
The details of the optimisation problems (power equations and constraints) are provided in Appendix A. This optimisation problem can be solved in the three stages: Normal operation (pre-contingency), short-term, and long-term post-contingency (refer Figure 1).
## 1 Introduction
During the process, the smooth orthogonal projection from a high dimension phase space to a low dimension one, a new weight matrix is put forward to achieve a better denoising effect by adding back the bias in this paper, which has been proved effective after multiple experiments. [PERSON] et al. [35] proposed the concept of the average entropy parameter in the application of measuring the complexity of one dimensional time series, namely permutation entropy (PE). It was an algorithm study about describing irregular and nonlinear systems [36], which cannot, or are hard to be, quantitatively described, in a relatively simple way. The PE has the advantages of simple calculation, strong anti-noise ability, and high sensitivity to signal change. The entropy derived methods can also be applied to the weak signal detection [37; 38], and the detection of the dynamic mutation of the complex system. When an abnormal failure or different kinds of faults occur in gear and bearing parts during their operation process, the influence of the nonlinear factors and signal complexity are different [39; 40; 41; 42]. So the vibration signals obtained from the mechanical system will also change, resulting in different values of PE. The PE is essentially used to describe the aggregation extent of phase vectors [43] in the high dimensional space. As for gear and bearing parts, different fault types have different degrees of faults. The smaller value of entropy means the lower complexity of fault signals, namely, the more serious the fault type is, the smaller its entropy, owing to a better predictability of fault signals. Thus, PE can be adopted to classify the different kinds of gear and bearing faults. This paper proposes a novel approach to conduct fault classification of gear and bearing signals, based on the smooth local subspace projection denoising and PE. The proposed novel weighting matrix is verified to be better than the existing weight matrices. The organization of this paper is as follows: Section 2 introduces the basic principles and characteristics of a smooth local decomposition and an algorithm, as well as the concept of PE. It then describes the theory of the fault classification method based on the smooth local subspace projection and PE. Section 3 introduces the numerical experiments of the smooth local subspace projection, and simulation researches of PE, which both can prove the effectiveness of the algorithm. Section 4 presents the processing of _Case Western Reserve University Bearing Data_ and its applications to gear signals of the Drivetrain Diagnostics Simulator, in order to verify the validity of the proposed approach described in this paper. The conclusions of the studies and necessary discussions are given in Section 5.
## 3 Key Generation  
Our proposed key generation scheme will only depend on the _seed_ of the generator. This seed, which we will refer to as _stop_time_, represents the end of the iterations cycle of the Henon system. For security measures, the patient's medical device will synchronize the initial conditions of the Henon equations using wired links with the trusted device. In addition, they can be pre-implemented in the system's devices before use. Therefore, the attacker will not have the second needed input to generate the desired key, even if he/she succeeded to eavesdrop the seed. The generation of the key on the device will be simple, however, on the attacker's device, it is going to be a complicated process. The main device will generate the seed on its side, then it will communicate it to the second end of  
Figure 3: Henon Attractor for \(x_{0}=0.1\) and \(y_{0}=0.1\).  
the system. Afterwards, the encryption key will be generated independently on both sides from the communicated \(stop\_time\) to be as shown in Figure 4. In order to reduce the computation cost of the algorithm, the data values will not be represented on the same number of bits as the key length, but on a fixed point representation of 2Q30 or 2Q14, i.e., the data has 2 bits integer and 30 bits fraction, or 2 bits integer and 14 bits fraction, respectively. This utilization of low precision among the variables of the Henon system will avoid the extra use of memory and computational resources. Hence the low resources of the device would not become a problem for the algorithm execution. The encryption key with length \(m\) will then be the concatenation of the last binary \(l\) values generated by the Henon equation, such that \(m=32\times l\) or \(m=16\times l\).  
For statistical reasons and to ensure a better security and randomness in the generated keys, the second key \(\mathbf{Y}\) will be the result of the XOR operation of the raw keys \(\mathbf{X}\), and \(\mathbf{Y}\) generated from the equations as shown in Figure 5.  
The seed (or \(stop\_time\)) will be generated as a function of the system clock. Another way which is much more secure but more complex, is to use the exclusive characteristics of the wireless channel through the physical layer security to generate a common random seed based on the channel gain or phase [26; 27; 28; 29]. Also, the manufacturer will define a non-short time lapse after which the \(stop\_time\) (seed) value will expire. When it terminates, a new request with a new value will update the Henon system's seed of the devices. This contributes to the improvement of the system's security while lowering the computational costs.
# Screening of Scaffolds for the Design of G-Quadruplex Ligands
## 3 Results and Discussion  
### Chemistry  
Several small molecules have been reported in the literature as ligands/drugs for the targeting of G4 structures, including new chemotypes [22]. Among the several classes of ligands, synthetic heterocycles have proven to be a promising scaffold for the design of G4 binders and stabilizers, in particular, fused aromatic compounds.  
Herein, we describe the chemical synthesis, full characterization and in vitro evaluation of four different aromatic scaffolds containing oxazole, acridine, naphthalene and phenanthroline moieties. The naphthalene and phenanthroline derivatives were synthesized as shown in Schemes 1 and 2, with low to high yields, i.e., 11-89%, respectively (experimental section). All starting compounds were commercially obtained and most of these derivatives were easily obtained with a high degree of purity, as confirmed for NMR analysis. Naphthalene derivatives (Napht-3 and Napht-5) were synthetized by following a two-step route, previously reported by [PERSON] et al. [16]. Firstly, a condensation between 1-naphtaldehyde and diethylenetriamine and tetraethylenopentamine, followed by in situ reduction in the formed mine with sodium borohydride, gave derivatives Napht-3 and Napht-5 with 79% and 11% yields, respectively (Scheme 1). The phenanthroline derivatives were synthetized using procedures already described (Scheme 2) [17; 18; 19]. The synthesis of 7,10-dimethylpyrazino[2,3-f][1,10]phenanthroline (DPPZ) was done by initial oxidation of 2,9-dimethyl-1,10-phenanthroline with potassium bromate in sulfuric acid solution, affording 2,9-dimethyl-1,10-phenanthroline-5,6-dione. After that, the dione reacted with ethylenediamine by condensation to give DPPZ with a yield of 60%. The 2,9-dicarbomethoxy-1,10-phenanthroline (COOCH3) was synthetized from the oxidation of 2,9-dimethyl-1,10-phenanthroline to the aldehyde, which was oxidized to a dicarboxylic acid derivative and converted to PhenCOOCH3 by Fisher esterification, in a yield of 53%. The phenyl (ISO-1 and Ter-1), quinoline (Quin-1) and acridine derivatives (C5 NH2 and C8 NH2) were synthesized as previously described [15; 20].  
**Scheme 1.** Chemical synthesis of naphthalene derivatives.