esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Mathematical Formulation
### Coordinate Transformation
#### 3.2.1 Single Element  
An antenna designed for Ka-band satcom applications is presented [31] and is used as reference in the next. As an example, the receiver band (17.7-20.2 GHz) [32] is chosen. It is worth mentioning that this single element does not represent the final antenna solution but acts as a quasi-real scenario (e.g., realistic simulated pattern). This scenario accounts for the non-ideal hemispherical radiation of common patch radiators. Other types of antennas may be investigated, particularly solutions integrating the TX and RX parts. Additionally, mutual coupling and the integration of the antenna into an array are not considered in this work.  
The HFSS model of the patch antenna is shown in Figure 4. The antenna has 2 connectors to stimulate double circular polarization, left-hand and right-hand (LHCP, RHCP), which is typical in satellite communications. The respective far field used for array calculations is depicted in Figure 5 for both polarizations. In the numerical results, only one CP polarization is considered for the sake of brevity, as both polarizations radiate a similar far field.  
Figure 4: HFSS model of the patch antenna working in the receive Ka frequency band and used as element pattern for the array computation.  
Figure 5: Realized gain of the patch antenna for both LHCP and RHCP at \(\varphi=0^{\circ}\) (red and blue lines) and \(\varphi=90^{\circ}\) (green and magenta lines).  
Indeed, it is worth mentioning that the patch exhibits asymmetrical radiation, deviating from the ideal hemispherical/isotropic radiation and its maximum value is 6.2 dBiC. When compared with an ideal cosine distribution, the quasi-real radiation diverges significantly. To compensate for the asymmetrical radiation, the element is rotated by 180\({}^{\circ}\) to ensure symmetrical steering along both axes. For rotation and array far-field computation, cartesian electric field \(\underline{\tilde{E}}_{c}\big{(}\tilde{\theta},\tilde{\varphi}\big{)}=\big{\{} \tilde{E}_{x},\tilde{E}_{y},\tilde{E}_{z}\big{\}}\) is exported by HFSS. In this scenario, \(\underline{\tilde{E}}_{c}\big{(}\tilde{\theta},\tilde{\varphi}\big{)}\) corresponds to the non-rotated field (e.g., the antenna is looking at zenith), where \(\big{(}\tilde{\theta},\tilde{\varphi}\big{)}\) are the spherical coordinates in the non-rotated coordinate system. It is worth emphasizing that the electric field has no information on impedance mismatch and radiation efficiency. These losses are omitted in consideration of the fact that normalized directivity is used as Figure of Merit (FoM) for FoV calculation.
# Advanced Scale-Propeller Design Using a MATLAB Optimization Code
### Literature Review  
High propulsive efficiencies can be achieved on propellers used on full-scale crewed aircraft, such as the C-130] Super Hercules, and there are two main reasons why this is the case. Firstly, the propellers tend to have complex variable pitch mechanisms, which allow the propeller to operate at peak efficiency under different flight conditions. Such mechanisms are costly, complex and too heavy to include within small propellers for attributable uncrewed aircraft. Variable pitch mechanisms are also required to control helicopter rotors, which is why these rotors tend to have a constant angle of twist along the blade.  
Secondly, full-scale aircraft propellers tend to have large diameters, which leads to greater chord lengths. As will be explained later in this study, large diameter propellers operate in higher Reynolds (Re) number regimes, which enable greater efficiencies to be achieved, in contrast to smaller propellers which operate at lower Re numbers. Therefore, creating propeller geometries that permit higher efficiencies to be reached, whilst not inducing large mass and cost penalties, would lead to significant improvements in performance.  
A previous research project at the University of Southampton resulted in a MATLAB code being developed which optimised propeller geometry for given operating conditions [4]. This work was used as the basis for the Mejzlik propeller online performance program [5]. Another research project examined the low Reynolds number propeller problem, but instead focused on using overlapping propellers as a solution [6]. However, neither of these projects attempted to design a single propeller which could operate at high efficiencies in low Reynolds number regimes.  
The earliest analytical work on propellers was performed by [PERSON] and [PERSON] in the 19 th century. The theory developed was intended for use on marine propellers. The theory they developed later became known as Actuator Disk Theory (ADT)--or axial momentum theory. Whilst this doesn't include any detailed propeller aerodynamics, this theory allows designers to develop rough performance and sizing requirements.  
ADT is based on a number of assumptions:  
* The rotor is modelled as an actuator disk, which adds momentum and energy to the air;
* There is no inflow or outflow through the wake boundary;
* The flow is steady, incompressible and inviscid;
* The flow is one dimensional and uniform;
* The flow is uniform through the disk and wake;
* The disc does not impart any swirl to the flow.  
Using inviscid flow theory and taking a force balance across the actuator disk, the thrust can be easily calculated. For a given thrust, the induced axial velocity can be calculated according to Equation (1).  
\[w_{axial}=\sqrt{\frac{V^{2}}{4}+\frac{T}{2 pA}}-\frac{V}{2} \tag{1}\]
# Evaluation of Radio Access Protocols for V2X in 6G Scenario-Based Models
## 4 Analysis of Performance Results
### Discussions and Perspectives  
The 802.11p protocol, although it has an established infrastructure, faces limitations in security, latency, and data rates. On the other hand, 802.11 bd offers significant improvements in these metrics and is particularly important for URLLC communication applications that characterize autonomous driving. It is worth noting that the 802.11p protocol was implemented specifically to perform reliably against channel interference in V2V communications, while 802.11 bd prioritizes latency reduction. 802.11p was optimized for high-speed vehicular communications, while 802.11 bd has been implemented for a wide range of applications and usage scenarios. Although the tests were carried out in a rural LOS scenario, it is important to note that 802.11 bd tends to be more susceptible to interference and noise from other wireless networks operating in the same frequency bands. In contrast, 802.11p operates in a reserved band, resulting in less interference and therefore better DR performance.  
Furthermore, 802.11 bd brings significant improvements compared to its predecessor, 802.11p, for autonomous driving, making communication safer. For example, in the blind spot warning application, 802.11 bd offers faster and more accurate detection, allowing  
Figure 5: Comparison of (**A**) PER vs. SNR and (**B**) PER vs. distance for LTE-V2X and NR-V2X with payload of 375 bytes.  
vehicles to receive immediate alerts when another car is nearby, thus reducing the risk of collisions.  
Regarding 3 GPP protocols, the results indicate that NR-V2X outperforms LTE-V2X, partly due to its design that prioritizes compatibility with future innovations. The advances featured in NR-V2X guarantee long-lasting interoperability and adaptive support, providing significant improvements in emerging applications such as driving assistance, including automatic parking and cooperative emergency braking. It is therefore essential that governments encourage the advancement of transportation infrastructures to drive V2V communication and the adoption of V2X in general.
## 4 Computational Experiments
### Illustration of Two Practical Cases  
Two typical networks for facility location were selected to test the proposed algorithm. The first was a case with 95 cities distributed in Hunan Province in China, noted as H-95, and the distribution of the cities is presented in Figure 1a. Each city represents both a demand node and a potential location for opening a new facility. The distance between each two nodes was assumed to be the greatest circle distance, which was calculated through their practical longitudes and latitudes. The excepted demand of each customer node was estimated through the population in the city. In each scenario, the realizing demand of each node was assumed to have three possible levels, which were the excepted demand, 25% higher, or lower than the excepted demand. In the experiment of the 95-node instance, 100 possible scenarios for the demands were generated by randomly selecting a demand level for each node.  
The second case was based on 668 demand nodes distributed in the urban area of Changsha in China, noted as C-668, which are presented in Figure 1b. Among the 668 nodes, 150 nodes were selected as the potential locations for opening new facilities. The distance between each pair of two nodes was estimated by the Manhattan distance based on their practical longitudes and latitudes. The excepted demand in each node was estimated by the population surrounding the demand node. In this case, the realizing demand of each node in a scenario was assumed to have five possible levels, which were 50%, 75%, 100%, 125%, and 150% of the excepted demand. Additionally, 100 possible demand scenarios were generated through randomly selecting a demand level for each node.  
In both the H-95 and C-668 cases, the probability that each scenario may occur was generated randomly, and \(\sum\limits_{s\in S}q_{s}=1\). The cost \(c_{ij}\) was set as the distance between node \(i\) and \(j\).
# Influence of Pre-Ionized Plasma on the Dynamics of a Tin Laser-Triggered Discharge-Plasma
## 5 Summary  
In conclusion, we studied the effect of laser-current delay on tin LTD plasma by experiments and theory. Due to the expanding of the pre-ionized plasma, multiple pinches may occur when the delay is larger. The shape of the spectra and 13.5 nm (2% band) intensity varies with the delay. Spectrum simulations predict that the 13.5 nm intensity reaches the maximum when the electron temperature is close to 30 eV, where the ratio of Sn\({}^{10+}\) ions is highest. With fixed discharge energy but higher laser-current delay, lower vapor velocity leads higher electron temperature and higher intensity 13.5 nm emission in the 2% band, which increases about 120%. The EUV CE increases from 0.5% to 1.1% when the delay increases from 0.7 to 5 \(\upmu\)s. The results show stronger dependence of the 13.5 nm intensity on the laser-current delay. By tuning the delay, the bandwidth of the UTA is narrower as well. Moreover, the stability of the 13.5 nm emission decreases as well.  
Figure 7: Relationships between 13.5 nm intensity in the 2% band (a, red circular) as well as spectral purity (b, blue star) and laser-current delay.  
**Author Contributions:** The authors have worked together to complete this research.  
**Funding:** We acknowledge funding from the Fundamental Research Funds for the Central Universities (No. 2572018 BC18), and Northeast Forestry University Students' Innovation and Entrepreneurship Training Program (No. 201610225100).  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Experiment and Analysis
The maximum relative amplitude error of 1.40% in the multi-frequency situation is not larger than the single-frequency situation; that means the number \(K\) of signal frequencies does not affect the amplitude estimation accuracy of the proposed method. Compared with an FPGA-based method in the literature [25], this software implementation of the DLIA can estimate multiple signals' amplitudes.Moreover, the method [25] can only track the fixed and known frequency of one signal, while this proposed method can estimate the varying frequencies of a measured signal automatically. Under the same SNR condition, the relative amplitude error of this proposed method is less than 1.7% which is better than the 2% of the FPGAbased method [25].
## 2 Localization Algorithm based on Spring Model (LASM)
### Patches for the basic localization algorithm (LASM(P))
#### 2.3.3 Patch C for node variation  
With the increase of the exploration area and working time on the moon, there are more nodes adding to or leaving from the network. How to deal with these nodes after the network has been localized?  
When a new blind node adds in the network, it communicates with its neighbors and then obtains their positions and distances between itself and its neighbors. First, the positions of its neighbors are fixed. Then, the new node calculates its position using the proposed LASM algorithm. After that, small movements are made for the other nodes in the network using LASM. When a new anchor node adds in the network, it communicates its position to its neighbor nodes. These neighbor nodes use the LASM to adjust their positions again.  
When a new blind node adds in the network in the LASM process of its neighbor nodes, it first calculates its approximate position using (16). Then it broadcasts its position to its neighbors using LASM to estimate its position. Its neighbor nodes receive its position, and then add it in the calculation of total force.  
When a node leaves from the network after the LASM process, if the network is immobile (which means that the nodes in the network don't move once being deployed), the positions of the other nodes need not be changed. Therefore, nothing needs to be done on the positions of the other nodes. If the network is mobile, the other nodes will be relocalized using the proposed LASM algorithm.  
When a node leaves from the network suddenly during the LASM process, may its neighbor nodes run into a deadlock because they are waiting for the leaving node's position information? The answer is no. In the LASM process, a time threshold can be set for each sensor node. If it does not receive all the neighbors' position information in the time threshold, it will just use the positions of the remaining neighbor nodes to calculate its velocity, acceleration and position. Therefore, the LASM algorithm can perform well in dynamic networks with nodes adding and leaving rapidly.
## 1 Introduction
### Trochoidal Milling  
#### 1.2.1 Research of Trochoidal Milling  
Trochoidal milling is an effective method not only for milling complex workpieces but also for milling relatively simple grooves. Compared to standard linear grooving, trochoidal grooving allows a single milling cutting tool to machine a groove of the desired width, at least a greater width than the diameter of the milling cutting tool, the production of the groove being limited only by the wear of the milling cutting tool. Multi-blade cutting tools can also be used to allow large table shift. In addition, very high cutting speeds and feeds can be applied at a relatively small radial depth of the cut [9; 10].  
Currently, trochoidal milling offers the most extensive opportunities with which it is possible to remove a greater volume of material in less time (compared to conventional milling). This technology can be applied for the production of deep grooves, pockets or high workpiece sides, with high process reliability and long tool life, although the workpiece material is usually hard to machine [10; 11; 12]. The evolution of knowledge and skills related to the possibilities of modern machining has taken about half a century, but the development of machining has gradually accelerated. Basic knowledge in the field of trochoidal machining in professional practice can be dated to this millennium. Materials harder to process are widely used in the aircraft, automotive, shipbuilding and energy industries for the production of complex and varied components; therefore, materials based on nickel, titanium and steels with improved mechanical properties have been investigated in order to understand the factors degrading the machining process thoroughly. In recent decades, various milling methods have been investigated and analysed to increase productivity [1; 13; 14; 15], the subject of the investigation also included the following aspects: high-speed machining with respect to the removed material [2; 13; 14]; simulation methods aiming to implement different control models and the real behaviour of machines to eliminate machine failure and downtime [16; 17]; adjusting tool feeds aiming to optimize the production cycle time; process monitoring to evaluate tool wear for titanium or nickel-based alloys [1; 18]. The possibilities of the predictive model are control of the machining process in order to reduce vibrations, increase the stability of the cut and efficiency of the cutting process [19]; and trochoidal milling in connection with finish operations in machining superalloys based on nickel [20; 21; 22].
## 5 Experiments  
This section describes the experimental details. The datasets used in the study were selected due to their open access availability [42], varying levels of difficulty [28], and their usage in other studies in the literature [11; 28; 31; 37]. Detailed information about the datasets is provided in Table 3. All datasets listed in Table 3 were obtained from the UC Irvine Machine Learning Repository [42]. The datasets used in this study were divided into two groups: training and testing sets. The training and testing data ratios were set to 80% and 20%, respectively.  
In the experimental study, the proposed bWSO algorithm was compared with eight widely preferred population-based algorithms from the literature [11; 24; 28; 31; 37]. The algorithms used in this comparison include AAA [11], BAT [14], FA [15], GWO [16], MFO [17], MVO [18], PSO [19], WOA [20]. To ensure a fair comparison, AAA, BAT, FA, GWO, MFO, MVO, PSO, WOA, and bWSO algorithms were executed on the same platform. The experiments were conducted on a Windows 10 operating system equipped with an Intel(R) Core(TM) i7-10750H CPU @ 2.60 GHz (6 cores, 12 logical processors) and 16 GB of RAM. Coding was performed using Python (version 3.7.3 64 bit) programming language within the Visual Studio Code (Version 1.92.2) editor. The EvolopyFS library was utilized in the experimental studies [43]. EvolopyFS is a Python-based library containing frequently used metaheuristic optimization methods. The experiments were carried out with a population size of 30, 500 iterations, and 30 runs.  
The hyperparameter values of all algorithms used in the experiments were determined based on default settings that are commonly used in the relevant literature and have been proven effective in previous studies. In particular, the parameters chosen for the WSO algorithm are those recommended in the original study [13] and selected after comprehensive parameter analyses. This approach was adopted to reduce the need for additional optimization of parameter settings and to ensure a fair comparison among different algorithms. Thus, the focus of the experiments was on comparing the fundamental performance of the algorithms. The hyperparameter values of all algorithms are presented in Table 4.  
Figure 4: The block diagram of the proposed bWSO method.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Algorithm** & **Hyperparameters** & **Values** \\ \hline \hline \multirow{8}{*}{WSO} & \(f_{max}\) & 0.75 \\  & \(f_{min}\) & 0.07 \\  & \(p_{max}\) & 1.5 \\  & \(p_{min}\) & 0.5 \\  & \(tau\) & 4.11 \\  & \(a_{0}\) & 6.25 \\  & \(a_{1}\) & 100 \\  & \(a_{2}\) & 0.0005 \\ \hline \multirow{4}{*}{AAA} & \(\Delta\)_Share force_ & 2 \\  & \(e\)_Energy loss_ & 0.3 \\ \cline{1-1}  & \(A_{p}\) Adaptation & 0.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Hyperparameters values used in all algorithms.
# The Less Known Cyclins--Uncovered
## 7 Cyclin J  
Cyclin J was originally observed in a yeast two-hybrid screen for embryonic proteins that interact with Cdk2. Although the amino acid sequence of cyclin J most resembles that of the A-type cyclins, it lacks the destruction box and other consensus motifs identified in all mitotic cyclins. Cyclin J is a protein encoded by the CCNJ gene, which is localized in position q24.1 on the human chromosome 10 [59].  
In normal cells, cyclin J mRNA exists in the embryo before cellularization but, as opposed to other cyclins, is not present in late embryogenesis. [PERSON] et al., 2000 [60] showed that cyclin J is identified in the early embryo as a form of an active complex with Cdk2. During later embryonic development both cyclin J and the associated kinase activity are decreased before downregulation of cyclins A, B, B3 and E occurs. To study the importance of cyclin J in the syncytial embryo, the authors used peptide aptamers with the ability to specifically inhibit Cdk2 activity and applied them into embryos. The results showed that both peptide aptamers and cyclin J antibodies inhibit divisions in the early embryos [60].  
In normal cells, cyclin J is localized in early embryos and ovaries, where it regulates their normal development. [PERSON] et al., 2014 [61] studied ovarian mutants Drosophila melanogaster CycJ\(-/-\), Armi\(-/-\) and CycJ\(-/-\) Armi\(-/-\)[61]. The authors confirmed that no changes in the structure were observed in the CycJ\(-/-\) ovaries. This suggests that cyclin J is not essential for oogenesis. However, in Armi\(-/-\) ovaries they showed alterations in a structure such as ovarian malformations and only two egg chambers production. Double mutants were unable to produce eggs. Changes in their structure were also observed, i.e., the production of only one egg chamber, which contained various germline cells in excess [61].  
In the case of cancer cells, [PERSON] et al., 2016 [62] further implicate that the inhibition of CCNJ favors the reduction in proliferation of breast (BC) and gastric cancers (GC) cells in vitro and promotes chemosensitivity to trastuzumab and lapatinib in BC model [62]. In the previous research, it was also demonstrated that cyclin could be a novel prognostic marker of HCC and acute myeloid leukemia (AML) [63; 64].  
In the further in silico analysis, it was demonstrated that CCNJ is the target of miRNA-146a (miR-146a). Moreover, cell mitosis occurring during oncogenesis and embryogenesis is controlled by CCNJ. In the case of cisplatin (DDP)-resistant lung cancer cell lines, A549 and SPC-A1 transfection with miR-146a followed by treatment with DDP resulted in an intensified response to DDP by inducing cell cycle arrest and apoptosis [65; 66].