esa-sceva/satcom-chunk-collection huggingface dataset:
# Adaptive Coherent Receiver Settings for Optimum Channel Spacing in Gridless Optical Networks
###### Abstract  
In this paper, we propose a novel circuit and system to optimize the spacing between optical channels in gridless (also called flexible-grid or elastic) networking. The method will exploit the beginning-of-life link margin by enabling the channel to operate in super-Nyquist dense wavelength division multiplexing mode. We present the work in the context of software-defined networking and high-speed optical flexible-rate transponders. The clock recovery scheme allows the mitigation of jitter by decoupling the contribution of high-jitter noise sources from the clock recovery loop. The method and associated algorithm are experimentally verified where a spectrum gain of up to 2 GHz in spacing between two channels in the Media Channel (MC) is obtained compared to conventional clocking strategies. We showed that the improvement is equivalent to increasing throughput, in a data-center interconnect scenario, by up to 300 giga-bits per second per route.  
optical communications; networks optimization; coherent communications; phase-locked loop; gridless wavelength selective switch; software-defined networks +
Footnote †: journal: Future Internet
## 2 Materials and Methods  
### Image Acquisition  
In total, four cadaver heads were scanned with a multipurpose X-ray system (Multitom Rax, Siemens Healthcare). The 3D CBCT has an amorphous silicon flat detector with a cesium iodide scintillator of \(43\times 43\) cm area and has an image matrix of \(1420\times 1436\) pixels with a pixel size of 296 \(\upmu\)m (both after binning of \(2\times 2\)). The reconstructed voxel size was 0.5 mm (isotropic). The maximum diameter of field of view for reconstruction was 23 cm. Reconstruction is based on a filtered back projection algorithm ([PERSON], [PERSON], [PERSON]) with additional correction methods to compensate for noncircular movement [19]. The X-ray tube (OPTITOP; Siemens Healthcare) has a 0.6 mm focal spot. Various tube voltages (90, 100 and 121 kV) and dose levels (DLs) can be selected as setting parameters resulting in different scan protocols. Preset and selectable DLs are 278, 548, 1090, 2180 nGy. The X-ray tube target material is tungsten. The DL serves as the target DL for the automatic exposure control. The aim is to keep the dose at the image receptor constant for all projections. The tube current is modulated by the system and was between 44-374 mAs. The detector and tube are attached to two telescopic arms with a hinge. While moving along a predetermined trajectory, fluoroscopic images are acquired. The trajectory is defined by its position and scanning angle range. All scans were performed after geometric calibration of the trajectory. For the upright trajectory, a set of 512 images were acquired with a framerate of 8 fr-s\({}^{-1}\), resulting in a scan-time of 20 sec over a 187-degree arc-travel (system version VE30B, product status 2017).  
First, one cadaver head was examined with all available scan parameters to obtain an impression of image quality and radiation exposure. Three different tube-voltage settings (90, 100 and 121 kV) and four different DLs (278, 548, 1090 and 2180) were evaluated, each DL with and without pre-filtrationof the X-ray beam with a 0.2 mm copper filter (\"Cu\") to constrict the energy spectrum. Images were reconstructed in 2 mm axial and coronal slice thickness and post-processed with three different image \"kernels\" ranging from soft to hard (\"smooth\", \"medium\", \"bone\"). Additional post-processing was performed with and without the metal artifact reduction (MAR) algorithm [20].  
The subsequent scans of the three remaining heads were performed to further optimize image quality for selected protocols (121 kV) based on the results of the first cadaver head. Four different DLs (278, 548, 1090 and 2180), pre-filtration with 0.2 and 0.3 mm copper and tin (Sn) (0.4 mm) were evaluated.  
To find protocols with the best compromise between image quality and radiation exposure for preoperative surgery a mean computed tomography volume index (CTDI\({}_{\text{vol}}\)) of 8 mGy was considered the upper limit [21].
# A Novel Approach to Reach Impedance Matching in Wireless Power Transfer Systems
## 6 Conclusions  
In this paper, it was proven theoretically that the transfer efficiency represented by scattering parameters can represent the traditional electrical transfer efficiency in the limit case. Furthermore, the optimal parameter expression was obtained. In addition, based on the Neumann formula, the numerical calculation method of the coaxial coil mutual inductance of parallel square coils and the concentric square coil with an included angle was obtained, and its accuracy was verified using the commercial software Maxwell. Finally, the four-coil WPT system experiment verified that the transfer efficiency can be maximized by adjusting the included angle between the load coil and the \(Rx\) coil, and the distance between the driven coil and the \(Tx\) coil. When compared to the situation prior to optimization, the maximum improved efficiency was improved by 11%. Angle adjustment can  
Figure 11: (**a**) Maximum transfer efficiency at various transmission distances, (**b**) Optimal \(d_{12}\) and \(\varphi\) at various transmission distances.  
be realized simply in engineering applications, and the impedance matching of this system can be realized through angle adjustment in order to achieve maximum transfer efficiency. However, the coil structure in this paper was based on the PCB process, thus the power level of the system was limited and it is only applicable to portable devices, implanted medical devices and other low-power application scenarios. Meanwhile, the control of the angle has not been automated, which will be the next research goal. If this can be implemented, the integration and intelligence of the wireless transmission technology will be promoted.  
[PERSON] and [PERSON] conceived and designed the study; [PERSON] and [PERSON] gave the theoretical and data analysis; [PERSON] and [PERSON] gave the design of coils; [PERSON] and [PERSON] revised the whole manuscript; [PERSON] gave the financial support during the research; [PERSON] wrote the paper.  
This research was supported by the National Key R&D Program of China (Grant No. 2018 YFB0106300), Scientific Projects of State Grid Corporation of China under Grant No. 0231132705, Huazhong University of Science and Technology.  
The authors declare no conflicts of interest.
## 3 Discussion
(2015) reported the constitutive expression of _AtGPPS.SSU2_ and found its involvement in monoterpene biosynthesis [16]. This finding indicates that we cannot neglect the role of _CpGPPS.SSU2_ in scent biosynthesis in the wintersweet flower and suggest further investigations. All genes/enzymes involved in the MEP pathway are known to have a transit peptide for their plastid targeting. The subcellular localization experiments in _Catharantthus roseus_ and _Litsea cubeba_ displayed the plastidial localization of GPPS/GGPPS [12; 18; 33]. On the other hand, there are few reports which support the mitochondrial, cytosolic, and endoplasmic reticulum localization of this pathway's genes [26]. In the present study, the subcellular localization assay revealed that _Cp_GPPS.SSU1, _Cp_GPPS.SSU2, _Cp_GGPPS1, and _Cp_GGPPS2 proteins have strong GFP signals in the chloroplast region similar to the previous findings of GPPS.SSU1 from _A. majus_, GPPS.SSU2 from _C. annuum_ and GGPPSs from _A. thaliana_[14; 26]. However, the GFP fluorescence of _Cp_GPPS protein was not observed in the chloroplast, likely because it is localized in the mitochondria (Figure 4), consistent with the previous result of homodimeric GPPS in _C. roseus_[12]. These results support the chloroplast localization of _CpGPPS.SSU1_ and _CpGPPS.SSU2_ genes, further suggesting the functional involvement of these genes in monoterpene biosynthesis and metabolism. In the heterodimeric GPPS gene, LSU is active and functional itself, while SSU is inactive and needs to interact with the LSU for functioning [9; 12]. Through Y2H assay, both the _Cp_GPPS.SSU1 and _Cp_GPPS.SSU2 showed interaction with _Cp_GGPPS2. Moreover, _Cp_GPPS.SSU2 also interacted with the _At_GGPPS11 (Figure 5). These results support the possibility of heterodimeric GPPS existence in the wintersweet plant and warrant speculation that the SSU of heterodimeric GPPS could have a role in modifying or accelerating the product specificity of LSU or GGPPS. These assertions are consistent with previous suggestions. For instance, following the bacterial genetic complementation assay, when _Li_GPPS.SSU1 and _Li_GPPS.SSU2 were individually co-transformed with catalytically active _Li_GGPPS, both SSU interacted and reduced the carotenoid contents [34]. Moreover, when _Am_GPPS.SSU1_ was transformed in tobacco, it act as a modifier and increases the GPP, as well as monoterpene biosynthesis, at the expense of GGPP-derived compounds, i.e., gibberellins, chlorophyll, and carotenoids [14]. On the other hand, _Mn_GP._SSU1_ act like an accelerator when overexpressed in tobacco, as it promotes shoot branching and early flowering by an elevated content of cytokinin and gibberellin. [PERSON] et al. [18] reported that the virus-induced gene silencing of _CaSSU2_ led to a reduction in carotenoid content in red pepper fruit. However, the knowledge about this phenomenon remains unknown in wintersweet. In the future, all _Cp_GPPS/GGPPS candidate genes need to be further investigated by exploiting techniques such as _in vitro_ enzymatic assays and genetic transformation to obtain deeper insights.
# Asynchronous Gathering in a Dangerous Ring +
## 1 Introduction  
### Premise  
In networked systems that support autonomous mobile agents, a main concern is how to develop efficient agent-based _system algorithms_; that is, to design algorithms that will allow a team of rather \"simple\" agents to cooperatively perform complex system tasks. A main approach to reach this goal is to break a complex task down into more elementary operations. Example of these primitive operations are _traversal, search, gathering_, and _election_. The coordination of the agents necessary to perform these operations is not necessarily simple or easy to achieve [1].  
In fact, the computational problems related to these operations are definitely non-trivial, and a great deal of theoretical research is devoted to the study of the conditions for the solvability of these problems and to the discovery of efficient algorithmic solutions. At an abstract level, these environments, which we shall call _distributed mobile systems_, can be described as a collection \(\mathcal{E}\) of mobile computational entities, called _agents_, operatingin a graph \(G\). The agents have local computing capabilities and bounded storage, have limited means of communication, execute the same algorithm, and can move from node to neighboring node. The research concern is on determining what problems can be solved by such entities, under what conditions, and at what cost [2].  
We consider the computationally difficult environment where the agents are _anonymous_, in the sense that they have no identifiers, and they are _asynchronous_, in the sense that every action they perform takes a finite, but otherwise unpredictable, amount of time (decided by a worst-case adversary). Each node of the network, also called a _host_, provides a storage area called a _whiteboard_ for incoming agents to communicate and compute; the whiteboards are accessed using fair mutual exclusion.  
For such environments, we focus in this paper on a fundamental problem in distributed mobile computing, _gathering_, in the (simplest) fully symmetric topology, the _ring_ network. We consider its solution in the presence of a severe security threat, a _black hole_: a network site where a harmful process destroys all incoming agents without leaving a trace. A black hole models a computer that is accidentally off-line or a network site in which a resident process (e.g., an unknowingly-installed virus) deletes any visiting agents or incoming data upon their arrival, without leaving any observable trace; similarly, any undetectable crash failure of a site in a network transforms that site into a black hole (e.g., see [3]).
## 2 Principle of Linearity Improvement
### Circuit Behaviors under \"Reverse Uplift\"  
As for a Gilbert-cell-based active mixer, the gain compression point is mainly determined by the transconductance stage, which is used as a V/I converter (converting voltage changes to current changes) and directs the current into the switching core. Under this requirement, both the MOSFETs (metal-oxide-semiconductor field-effect transistors) and the BJTs (bipolar junction transistors) are biased in the amplification area so the input signal needs to be small, otherwise the working state of the transistors will be changed. However, when the problem of gain compression is analyzed, the effect of large signal will have to be considered. In this case, the input stage is no longer just a V/I converter, but also a gate/base pumped active mixer with a single transistor, as shown in Figure 3a,b. Therefore, when the input signal is strong enough, the fundamental signal component makes the transistor work in the switching state and becomes the LO (local oscillator) source of this mixing mode, as represented by Equation (3), and the second harmonic signal component fed back to the input at the same time becomes the small input signal, as expressed by Equation (4). At this time, if the fundamental component is strong enough to make the transistor act as an ideal switch, \(K\) in Equation (5) will be approximately equal to \(\frac{2}{\pi}\).  
Figure 2: Different trends of Gain. (**a**) \(T_{1}>0\), (**b**) \(T_{1}<0\).  
In summary, in the case of small signal input, the Gilbert mixer's operating mode is conventional, but in the case of considerable signal input, it is a superposition of the two operating modes, so the new curve of gain compression is also a superposition of the two curves, as shown in Figure 4. As the amplitude of the input signal increases, the mode of the single transistor gate/base pumped reaches the optimal local oscillator condition, and the second harmonic is mixed as a small signal to generate a new gain component. The existence of \"reverse uplift\" is predicted by Equation (7).  
In order to generate \"reverse uplift\", the key is mixing the fundamental with the second harmonic. Therefore, while amplifying the fundamental signal, it is necessary to simultaneously develop a strong second harmonic signal in the transconductance stage of the Gilbert-cell. As shown in Figure 5, where \(gm\) represents the small-signal transconductance of fundamental, \(gm_{2}\) represents the small-signal transconductance of the second harmonic, and \(gm_{3}\) represents the small-signal transconductance of the third harmonic. Regardless of the BJT or MOS transistor, \(gm_{2}\) rises rapidly in the sub-threshold region due to the \"exponential\" characteristic and the \"square law\" characteristic, and a peak value exists, which should be selected for this design. At the same time, the value of \(gm_{3}\) is close to zero, so its effect can be ignored reasonably.  
Figure 4: Superposition of the two modes.  
Figure 3: Circuit behaviors under “reverse uplift”. (**a**) Traditional mode, (**b**) switching mode.
## 3 Aim, Materials, and Methods
### Multi-Enhancement Command and Scheduling Model for Communication Network
#### 4.2.3 Emergency Command  
Emergency command utilizes cutting-edge information technologies including integrated remote sensing, 5G technology, big data analytics, GIS (geographic information system), artificial intelligence (AI), and digital twin simulation to facilitate disaster monitoring, analysis, decision-making, planning generation, and command execution. This is achieved by integrating unmanned aerial vehicles (UAVs), remote-sensing analysis techniques, video surveillance [41], and other technical equipment into the rural natural disaster monitoring system; leveraging GIS geographic information technology and AI recognition algorithms for the comprehensive collection of disaster site resources and data; employing big data analytics for intelligent analysis in conjunction with duty systems and expert support systems to holistically assess the disaster situation; utilizing a natural language processing-based AI model [41; 42] to formulate emergency command plans; harnessing 5G technology for real-time information sharing with the platform enabling command vehicles, as well as individual digital devices and other sensing devices on-site to establish an interactive real-time digital twin scene [43]; and thereby assisting in command decision-making processes while achieving accurate and timely emergency command execution.
## 6 Proposal for a Standardized Switching Frequency  
In this study, a new insight arises for fair efficiency comparisons of different MPC control algorithms. When the performance of the different MPC algorithms is the topic of the study, then the switching frequency variation should be standardized according to the given parameters. Hence, a proposal of how these standards should work is provided as follows:  
Until now, all the FCS-MPC algorithms, which are considering an objective in the CF to obtain a fixed switching frequency, still suffer from small to medium variation range. However, most of the researchers are calculating the average switching frequency while neglecting how much the variation is. Hence, it is unclear whether the switching changes are high, medium, or low. Secondly, some of the similar works calculate the overall system efficiency where the passive filter is included, and hence, it is unclear if the filter or the control algorithms introduce the losses. Therefore, two essential guidelines are proposed here; the switching frequency variation should be \(\pm\)1000 Hz around the desired average frequency as this range does not affect the efficiency significantly. Furthermore, FCS-MPC usually has some states which hit high-frequency values rarely during the steady-state or transient operation. Therefore, the proposal suggests to neglect them as they are very few and do not influence the overall performance. Finally, it should be clearly mentioned whether the loss measurements are for the whole system, or if they are related to the converter only. Based on that, all the measurements in this work included the loss in the complete power system.
# A Novel Deep Learning Stack for APT Detection
## 1 Introduction  
Due to the complexity and dynamical behaviour of APT attacks, we propose a system architecture for a novel prototype that takes into account the behaviour of these sophisticated attacks while detecting anomalies. Thus, we need to consider following issues: (i) outliers; (ii) data dimensions; (iii) non-linear historical events; (iv) underlying hidden interconnections; and (v) previously unknown attacks. To capture outliers caused by APT, the system must deal with the above-mentioned issues effectively. Therefore, we need to develop a stack of Deep Learning (DL) methods where each layer has its own purpose instead of having one single method. Finally, the system requires a data fusion function where all detected hostile outliers are collected and combined. The system architecture must be carefully planned, empirically tested and optimised as well as the correct data representation for the input must be selected.  
APT attack is a sophisticated network attack, with the purpose of long-term espionage or maximal destruction for target systems and networks. It has multiple functionalities, which are developed to avoid detection for as long as possible. Some of those functionalities include multiple simultaneous attack vectors with different phases, masquerading as communication data, random changes in execution time intervals, horizontal and vertical connections and mimicking legitimate traffic [1]. A common way to execute APT is via spear-fishing email spoofing attack but, if there exists an insider threat, it can be executed even inside the target network [2, 3].  
To the best of our knowledge, this type of system architecture has not been presented yet in academic research, even though APT attack detection methods have been proposed.  
Next, in Section 2, current detection problems are briefly discussed. Then, in Section 3, data properties and how they relate to detection process are presented. Section 4 describes the DL detection stack with details and preliminary complexity evaluation is included in Section 5. The paper concludes with Sections 6 and 7 is reserved to suggestions for future works.
# Guaranteeing QoS for NOMA-Enabled URLLC Based on \(\kappa\)-\(\mu\) Shadowed Fading Model
## 4 Simulation Results and Analyses
In Figure 7d, when the target delay is 0.1 ms and the distance to the center of the coverage area is 200 m, the user achieves \(\varepsilon_{\text{$\
u$}}^{\text{$\
u$,UB}}\)=\(10^{-7}\) with \(\text{EE}_{\text{dB}}=40\) bit/J in the OMA system. Under the same conditions, the user in the PD-NOMA system can arrive at the same UB-QDVP with \(\text{EE}_{\text{dB}}>40\) bit/J, which is an \(\text{EE}_{\text{dB}}\) improvement of 4.9% over that of the OMA system. Furthermore, the user in the CF mMIMO system achieves a 6.25% increment in \(\text{EE}_{\text{dB}}\) compared with that of the OMA system. When \(\text{EE}_{\text{dB}}=27.65\) bit/J, the target delay is 0.1 ms and the distance to the center of the coverage area expands to 1000 m, the UB-QDVPs of the user in both PD-NOMA and OMA systems are greater than \(10^{-7}\). However, the UB-QDVP of the user in the CF mMIMO system is less than \(10^{-7}\) and is 99.6% lower than that of the PD-NOMA system. Hence, the CF mMIMO approach is a prospective technology that can improve EE while ensuring that the target delay and reliability meet the URLLC QoS requirements. At the same time, it can greatly decrease the UB-QDVP and improve user reliability, thereby ensuring ultrareliable communication for all users covered.
## 1 Introduction
Therefore, the three-dimensional (3D) characteristics of the damage zone are presented and used in a 3D frequency domain finite element model [34] to simulate the scattering phenomenon of fundamental incident A\({}_{0}\) Lamb mode sent towards the damaged zone. The latter has been modeled as a right, circular, conical-shaped geometry with decayed material stiffness properties. Instead of only studying the backward and/or forward scattering [35], the present work investigates the scattering characteristics in different directions, where the frequency of the incident Lamb mode is chosen below A\({}_{1}\) cut-off. It is found that in composite plates, the directivity of scattered A\({}_{0}\) mode depends on the defect diameter to wavelength ratio, and on the through thickness of the conical damage as well. The numerically predicted scattered wave fields are compared with experiment measurements showing good agreement. Finally, the numerical finite-element-based-scattering characteristics is discussed for different geometrical parameters with a view towards modeling impact damage using conical-shape geometry with decay material properties.