esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Whether spin-polarized electrons can be efficiently injected into semiconductor materials is one of the key technologies to realize spintronic devices [1; 2; 3; 4; 5; 6]. Previous studies have shown that magnetic materials with high spin polarizability can effectively inject spin-polarized electrons [7; 8; 9; 10]. Half-metallic ferromagnets with a high Curie temperature and nearly 100% spin polarizability undoubtedly become the most ideal spin electron injection source for semiconductors. Among the two different spin channels of half-metallic ferromagnets, one spin channel is metallic, while the other is insulating or a semiconductor [11]. Half-metallic ferromagnets are widely used in spin diodes, spin valves, and spin filters because of their unique electronic structure [12; 13; 14; 15].  
Since the first half-metallic ferromagnet was predicted by theory, after more than 30 years of development, half-metallic ferromagnetic materials have become a hot topic in materials science and condensed matter physics. Up to now, half-metallic ferromagnets have been found mainly as follows: ternary metal compounds represented by Heulser alloy [16; 17; 18; 19], magnetic metal oxides [20; 21], perovskite compounds [22; 23], dilute magnetic semiconductors [24; 25], zinc-blende type pnictides and chalcogenides [26; 27], organic-inorganic hybrid compounds [28; 29]. Even some two-dimensional materials have half-metallic ferromagnets [30; 31; 32; 33].  
Prussian blue analogs are a class of metal-organic frameworks with a simple cubic structure, whose chemical formula can be expressed as A\({}_{2}\)M[M(CN)\({}_{6}\)] (A = alkaline metal ions, zeolitic water; M/M\({}^{\prime}\)= Fe, Co, Mn, etc.) [34]. Prussian blue analogs often have simpler molecular configurations due to the existence of vacancy defects. In Prussian blue analogs, there is a large space between metal ions and -CN- groups, which can effectively accommodate alkali metal ions such as Li\({}^{+}\), Na\({}^{+}\), and K\({}^{+}\). The open structure of Prussian blue analogs makes it exhibit excellent electrochemical performance [35; 36; 37].  
The magnetic study of Prussian blue analogs has also attracted people's attention for a long time. In 1999, [PERSON] et al. reported a compound KV[Cr(CN)\({}_{6}\)] with a Curie temperature as high as 376 K [38]. In 2003, [PERSON] et al. proposed that electrochemical methods could be used to control the magnetism and Curie temperature of Prussian blue analogs [39]. They also pointed out that it was feasible and promising to control the magnetism of Prussian blue analogs by light. Half-metals have also been found in these compounds by studying the magnetism. Two well-defined Prussian blue analogues are predicted as half-metallicity using first principles [40]. In the present study, we will study the structure, elasticity, and magnetic properties of a new Prussian blue analogue GaFe(CN)\({}_{6}\) under pressure and predict that the compound is half-metallic.
###### Abstract  
Multiple-Input Multiple-Output (MIMO) systems are characterised by increased capacity and improved performance compared to the single-input single-output (SISO) systems. One of the main challenge in the design of MIMO systems is the detection of the transmitted signals due to the interference caused by the multiple simultaneously transmitted symbols from the multiple transmit antennas. Several detection techniques have been proposed in the literature in order to reduce the detection complexity, while maintaining the required quality of service. Among these low-complexity techniques is the Lattice Reduction (LR), which can provide good performance and significantly lower complexity compared to Maximum Likelihood (ML) detector. In this paper we propose to use the so-called Element-based Lattice Reduction (ELR) combined with K-Best detector for the sake of attaining a better Bit Error Ratio (BER) performance and lower complexity than the conventional Lenstra, Lanstra, and Lovasz (LLL) LR-aided detection. Additionally, we propose a hardware implementation for the ELR-aided K-Best detector for a MIMO system equipped with four transmit and four receive antennas. The ELR-aided K-Best detector requires an extra 18% increase in power consumption and an extra 20% in area overhead compared to a regular K-Best detector dispensing with ELR, where this increase in the hardware requirements is needed in order to achieve a 2 dB performance improvement at a bit error rate of \(10^{-5}\).  
MIMO; Lattice Reduction; detection +
Footnote †: journal: Sensors. Actuator Netwro. **2018**, 7, 22; doi:10.3390/jsan7020022
# Design of an Isolated Bidirectional Symmetric Resonant Converter
); [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, I-Shou University, Kaohsiung 84001, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, I-Shou University, Kaohsiung 84001, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, Cheng Shiu University, Kaohsiung 84347, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, Cheng Shiu University, Kaohsiung 84347, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, Cheng Shiu University, Kaohsiung 84347, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, National Formosa University, Hu-Wei, Yunlin 63201, Taiwan; [EMAIL_ADDRESS] (Y.-H.Y. ); [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, I-Shou University, Kaohsiung 84001, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, I-Shou University, Kaohsiung 84001, Taiwan; [EMAIL_ADDRESS] (Y.-D.C.)1 Department of Electrical Engineering, Cheng Shiu University, Kaohsioperation, they are not suitable for bidirectional converter designs [11; 12; 13]. In the bidirectional power transfer applications [14; 15; 16], the LLC resonant converter is forced to turn into LC resonant, owing to the magnetizing inductance being clamped by the output voltage. Thus, the voltage gain is limited to be less than 1 in the backward power transfer mode, and only zero-voltage switching (ZVS) of power switches can be achieved. The lack of zero-current switching (ZCS) on the secondary rectifying devices leads to a reduction of conversion efficiency and is unsuitable for wide voltage range applications. Plus, the bidirectional LLC resonant converter is always unsymmetrical and thus results in the difficulty of a bidirectional design. Moreover, LLC only possesses the LC feature in the reverse operating mode and has limited operating range, with the voltage gain being less than 1.0. Therefore, the CLLLC design is more suitable for a bidirectional converter with wider wide operating range [17]. An isolated type bidirectional resonant converter is developed in this paper to tackle the inherited problems faced. Compared with the bidirectional LLC resonant topology, the developed bidirectional symmetric resonant converter allows the voltage gain to be greater than 1 in the reverse mode and achieves soft switching at a full range of load as well as keeps high conversion efficiency in large power applications. Moreover, the symmetric circuit topology makes the circuit design easier and suits the bidirectional operation and wide voltage range applications. This research principally aims at realizing a CLLLC topology, which is more suitable than LLC in accomplishing bidirectional conversion. A detailed bidirectional resonant converter design procedure is revealed, and the component parameters are derived theoretically and then validated in practice. Finally, an isolated type bidirectional resonant converter is implemented with its performance being exhibited.
# Analysis and Experimental Validation of Efficient Coded OFDM for an Impulsive Noise Environment
## 5 Performance Analysis
### Network Performance Analysis  
In this section, we examine the overall traffic rate, the PDR and the average delay of the packets. The following annotations are used:  
* \(\{X\}_{LOS1}\) corresponds to the case of the LOS situation and when the emitter and the receiver are both positioned at 1 m from the noise source.
* \(\{X\}_{NLOS1}\) is the case of the NLOS situation and when the transmitter and the receiver are both located at 1 m from the impulse source.
* \(\{X\}_{LOS2}\) represents the case of the LOS situation and when the emitter is placed at 1.90 m from the source and the receiver at 1.80 m.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Fields Types** & **Components** & **Values (Bytes)** \\ \hline \multirow{2}{*}{Frame Control Field} & Type/Subtype & 1 \\  & Version & 1 \\ \hline Duration ID & Duration & 2 \\ \hline \multirow{4}{*}{Addresses} & Destination address & 6 \\  & Source address & 6 \\  & Broadcast address & 6 \\ \hline \multirow{2}{*}{Sequence control} & Fragment number & 1 \\  & Sequence number & 1 \\ \hline \multirow{2}{*}{Logical Link Control} & DSAP & 1 \\  & SSAP & 1 \\ \end{tabular}
\end{table}
Table 4: FCF and LLC sub-frame format.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Fields Types** & **Components** & **Values (Bytes)** \\ \hline \multirow{2}{*}{Header} & Header revision & 1 \\  & Header pad & 1 \\  & Header length & 2 \\ \hline \multirow{2}{*}{Flag} & Present flags & 4 \\  & Flags & 1 \\ \hline Rate & Data rate & 1 \\ \hline \multirow{2}{*}{Channel} & Channel frequency & 2 \\  & Channel flags & 2 \\ \hline \multirow{2}{*}{Signal} & SSI signal & 1 \\  & SSI noise & 1 \\ \end{tabular}
\end{table}
Table 3: RadioType header subframe format.  
\(\{X\}_{NLOS2}\) corresponds to the case of the LOS situation and when the emitter is positioned at 1.90 m from the source and the receiver at 1.80 m.  
where \(\{X\}\) is either \(\mu\) or PDR.
# An Efficient SC-FDM Modulation Technique for a UAV Communication Link
## 5 Experiments and Performance Measures
### Performance Measures
#### 5.2.3 Pulse Shaping  
The pulse shaping can be used to make the transmitted signal more suitable for the communication channel. In general, pulse shaping is important to ensure the correspondence of a signal in its frequency band. In this paper, a raised-cosine (RC) and root raised-cosine (RRC) pulse shaping filters are used to get the desired spectrum.  
To perform the frequency response of the RC filter, we use the following equation:  
\[H_{RC}(f)=\left\{\begin{array}{ll}T,&0\leq|f|\leq\frac{1-\alpha}{2T}\\ \frac{T}{2}\Bigl{\{}1+\cos\Bigl{[}\frac{\pi T}{\alpha}\Bigl{(}|f|-\frac{1- \alpha}{2T}\Bigr{)}\Bigr{]}\Bigr{\}},&\frac{1-\alpha}{2T}\leq|f|\leq\frac{1+ \alpha}{2T}\\ 0,&\text{otherwise}\end{array}\right. \tag{13}\]where \(f\) is the frequency, \(T\) is the symbol period, and \(\alpha\) is the roll-off factor and its value can be between 0 and 1. The representation of the time domain of this filter is given by:  
\[h_{RC}(t)=\frac{\sin(\frac{\pi t}{T})\cos\frac{\pi a\pi t}{T}}{\frac{\pi t}{T} \left[1-\left(\frac{2 at}{T}\right)^{2}\right]}, \tag{14}\]  
where \(t\) is the time. Equations (13) and (14) are used to realize the frequency and impulse responses of the RC filter. Then, the frequency domain transfer function of the RRC filter can be written as:  
\[G_{RRC}(f)=\sqrt{H_{RC}(f)}. \tag{15}\]  
The impulse response of the RRC filter is given by:  
\[g_{RRC}(t)=\frac{\sin(\frac{\pi t}{T}(1-\alpha))+\frac{4 at}{T}\cos(\frac{\pi t }{T}(1+\alpha))}{\frac{\pi t}{T}\left[1-\left(\frac{4 at}{T}\right)^{2}\right]}. \tag{16}\]  
Finally, the performance of each modulation scheme for SC-FDM and OFDM can be measured by calculating the different values of the above-mentioned parameters. To achieve the comparative results that are presented in the following section, the simulation parameters and the data that were collected from the GCS were utilized as the inputs of the system performed with MATLAB.
# Efficient Deep Learning-Based Detection Scheme for MIMO Communication Systems
## 2 MIMO System Model  
In a MIMO system, the signals are transmitted using multiple antennas at the transmitter and receiver. Let \(s\in\mathcal{A}\) be an \(M\)-ary modulated symbol, \(N_{t}\) the number of Tx antennas, and \(N_{r}\) the number of receiving (Rx) antennas, respectively. Then, a vector of multiple symbols \(\mathbf{s}\in\mathbb{C}^{1\times N_{t}}\) transmitted simultaneously in the \((N_{r}\times N_{t})\) MIMO systems can be expressed as  
\[\mathbf{s}=\begin{bmatrix}s_{1},&s_{2},&\cdots&s_{N_{t}}\end{bmatrix}^{T}. \tag{1}\]  
Let \(\mathbf{r}\in\mathbb{C}^{N_{r}\times 1}\) be the vector of received symbols arriving at each one of the \(N_{r}\) receiver antennas, which can be expressed as  
\[\mathbf{r}=\begin{bmatrix}r_{1}\\ r_{2}\\ \vdots\\ r_{N_{r}}\end{bmatrix}=\begin{bmatrix}h_{1,1}&h_{1,2}&\cdots&h_{1,N_{t}}\\ h_{2,1}&h_{2,2}&\cdots&h_{2,N_{t}}\\ \vdots&\vdots&\ddots&\vdots\\ h_{N_{r},1}&h_{N_{r},2}&\cdots&h_{N_{t},N_{t}}\end{bmatrix}\begin{bmatrix}s_{ 1}\\ s_{2}\\ \vdots\\ s_{N_{t}}\end{bmatrix}+\begin{bmatrix}n_{1}\\ n_{2}\\ \vdots\\ n_{N_{r}}\end{bmatrix}, \tag{2}\]  
where each element \(h_{i,j}\in\mathbb{C}\) represents an impulse response of the channel link from the \(i\)-th transmission antenna to the \(j\)-th receiving antenna, so each channel response belongs to a channel matrix defined as \(\mathbf{H}\in\mathbb{C}^{N_{r}\times N_{t}}\). Without loss of generality, the evaluation of the system is based on a quasi-static correlated fading channel with Rayleigh distribution where its elements are assumed to be complex Gaussian random variables with zero mean and unit variance, \(\mathcal{CN}(0,1)\). An equivalent expression of (2) can be defined as  
\[\mathbf{r}=\mathbf{Hs}+\mathbf{n}, \tag{3}\]  
where \(\mathbf{s}\in\mathbb{C}^{1\times N_{t}}\) and \(\mathbf{n}\in\mathbb{C}^{N_{r}\times 1}\) represent the additive white Gaussian noise (AWGN) samples at each \(j\)-th receiving antenna. We assume that the noise is identically independent distributed with variance \(N_{0}\) denoted \(\mathcal{CN}(0,N_{0})\).
## 5 Experiments
### Experimental Results
#### 5.6.1 Results of Clause Segmentation  
We adapted the discourse parser DisCoDisCo [17] to the clause segmentation task and conducted an ablation study on different features, e.g., lemma, syntactic dependency, parts-of-speech, and static word embedding fastText, to explore which contributed more to the performances. The experimental results of the clause segmentation task are reported in Table 10, as well as the performances of previous works on the discourse segmentation task for comparison. From the results, we made the following observations:  
* Compared with the 98.4-100 IAA scores on clause segmentation mentioned in Section 3.3.3, the adapted DisCoDisCo model achieved satisfactory performances, i.e., 91.3 F\({}_{1}\)-scores.
* In the ablation study of different embedded features, the static word embedding fastText, which gained a 4.9 F\({}_{1}\)-score improvement, contributed the most to all features, although other features also had positive impacts on the performances.
* In the discourse segmentation task, the DisCoDisCo model outperformed the Gum-Drop model on the GUM and RST-DT datasets. Although GumDrop performed better than DisCoDisCo on the STAC dataset, its performance sharply declined with 14.7 F\({}_{1}\)-scores when removing extra gold features. Thus, we chose to apply the DisCoDisCo model to the clause segmentation subtask.
* Experimenting with the same model DisCoDisCo, performances on clause segmentation had about 3-5 F\({}_{1}\)-scores, lower than on the discourse segmentation, indicating that the performance gaps could be attributed to the corpora. From the statistics in Table 6, an average of 3.1 clauses constitute a sentence in HCA-AMR2.0, more than  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layer** & **Hyper-Parameter** & **Value** \\ \hline \multicolumn{3}{c}{**Clause Parsing Model**} \\ \hline Word Embedding & pretrained language model & 768/1024 (base/large) \\ \hline \multirow{2}{*}{FFN} & hidden\_size & 512 \\  & dropout & 0.2 \\ \hline \multirow{6}{*}{Trainer} & optimizer & AdamW \\  & learning rate & 2e-4, 1e-5 \\  & weight decay & 0.01 \\ \cline{1-1}  & batch size (\# spans/actions) & 5 \\ \cline{1-1}  & \# epochs & 20 \\ \cline{1-1}  & patience of early stopping & 5 \\ \cline{1-1}  & gradient clipping & 1.0 \\ \cline{1-1}  & validation criteria & RST-Parseval-_Full_ \\ \hline \hline \end{tabular}
\end{table}
Table 9: _Cont._that in GUM (2.3 EDUs), STAC (1.1 EDUs), and RST-DT (2.6 EDUs). Besides, only HCA-AMR2.0 contains a certain number of weblog data, which are less formal in English grammar and may cause more obstacles for the DisCoDisCo model.
# Joint User-Slice Pairing and Association Framework Based on H-NOMA in RAN Slicing
## 2 System Model  
### Network Model and Assumptions  
We consider a two-tier downlink H-NOMA cellular network which consists of wireless backhaul and radio access networks with a single infrastructure provider (InP), where 1 st tier consists of an MBS while 2 nd tier models SBSs. The set of BSs is denoted as \(b=\{1,\ 2,\ -\ldots\ \mathcal{B}\}\) when \(b=1\) is a MBS. However, \(b\
eq 1\) is a SBS. We assume that the out-band operation mode is operated on the HetNet system. Thus, non-line-of-sight (NLOS) backhaul and access links are operated on different carriers; thus, separation in the frequency domain is provided to achieve efficient spectrum usage [43; 44]. Also, we assume that all BSs utilize the same frequency band [45], resulting in SBSs being underlined by spectrum sharing with one MBS. Let \(l=\{l_{1},\ l_{2},\ l_{3},\ \ldots,\ \mathcal{Z}\}\) and \(e=\{e_{1},\ e_{2},\ e_{3},\ \ldots,\ E\}\) denote the set of uRLLC and eMBB UEs, respectively, are randomly distributed over the entire network area. The set of all UEs containing uRLLC UEs and eMBB UEs is represented by \(U=\mathcal{L}\ U\ E\), where the number of eMBB UEs is represented by \(u\in U=\{1,\ 2,\ldots,k\}\) and the set of uRLLC UEs are indicated by \(u=\{k+1,\ \ldots,\ U\}\). We assume the total transmitted power's MBS is equally distributed between WBH and RAN as \(P_{1b}\) where \(b\in B,\ b\
eq 1\) and \(P_{1}^{\text{N}}\),respectively. Each BS will have \(N_{b}\) physical resource blocks (PRBs) in RAN, distributed amongst its attached users depending on the available system band. We suppose that the overall transmitted power of each BS's RAN is allocated evenly over the available PRB (\(P_{b}^{n}\)). In this system design, we slice and assign PRBs as virtual resources into two RAN slices to serve uRLLC, and eMBB users, as illustrated in Figure 2. The set of all slices is denoted by \(s\in\mathcal{S}=\{1,\ 2\}\), where \(s=1\) refers to the uRLLC slice and \(s=2\) is the eMBB slice. Each slice \(s\) has its own set of users denoted by \(I_{s}\), let \(t=\cup_{s}^{\delta}I_{s}\) where \(\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \
## 3 Results
### Technical Performance Results
#### 3.1.4 Thermogravimetry  
The bound water contents of the pastes up to the age of 90 days are plotted in Figure 8a. It was observed that the bound water values (per 100 g of cement) for the three pastes incorporating slag were similar up to the age of 90 days and higher than those of pure Portland cement paste, especially at later ages. They were also lower than those of the quartz-blended mixtures (especially at 1 day). The higher bound water content of the blended pastes compared to the pure cement paste is an indication of the availability of more water for cement hydration (due to the replacement of part of the cement with the slags/quartz). However, comparing the 1-day bound water of the slag-blended pastes with that of the pure Portland cement paste and the paste containing quartz indicates the presence of a retardation effect by the slags. This could probably be due to the presence of heavy metals such as lead and zinc, which have previously been reported to have a retardation effect on cement hydration [40; 41; 42].  
The portlandite contents of the pastes up to the age of 90 days are plotted in Figure 8b. It was observed that the portlandite content of the blended pastes were higher than that of pure Portland cement paste at all ages, which is an indication of more hydration reactions (due to the availability of more water for cement reactions). This is in agreement with the bound water results. However, except for the age of 1 day, the slag-blended pastes appeared to have formed equal or higher portlandite contents compared to the paste incorporating quartz.
## 2 Experiment I: Directivity-Controlled Auditory Distance in Auralized Rooms  
Considered beampatterns up to the third order are based on frequency-independent beampattern designs by a combination of Legendre polynomials \(g_{i}(\theta)=\sum_{n=0}^{i}(2n+1)\;a_{n}\;P_{n}(\cos\theta)\), using max-\(\mathbf{r}_{\text{E}}\) weights that are common in Ambisonics (cf. [11; 12])  
\[a_{n}=\frac{P_{n}[\cos(\frac{137.9^{\circ}}{i+1.151})]}{\sqrt{\sum_{n=0}^{i}( 2n+1)\;[P_{n}(\cos\frac{137.9^{\circ}}{i+1.51})]^{2}}}. \tag{1}\]  
This exhibits a relatively narrow main lobe and sufficiently suppressed side lobes for any beam order \(i\).  
The proposed beampattern designs vary:  
\(A\): the beam order \(i\) from three to zero for \(g_{i}(\theta)\) and \(g_{i}(\pi-\theta)\); \(B\): the ratio \(a/b\) of two opposing beams: \(a\,g_{3}(\theta)+b\,g_{3}(\pi-\theta)\); \(C\): the angle \(\alpha\) of a beam pair: \(g_{3}(\theta-\alpha/2)+g_{3}(\theta+\alpha/2)\).  
Table 1 lists all tested beampattern designs in particular, which differently modify the amount of diffuse, lateral, and direct energy, thus the D/R ratio. Each beampattern indicated by the index 1 and 7 corresponds to a 3 rd-order beam facing towards and away from the listening position (\(A_{1}=B_{1}=C_{1}\), \(A_{7}=B_{7}=C_{7}\)). Furthermore, beam pairs indicated by indices 1/7, 2/6, and 3/5 of each design are identical in their shape but horizontally rotated by 180\({}^{\circ}\). Figure 1 shows the beampatterns \(A_{1\ldots 4}\), \(B_{1\ldots 4}\), and \(C_{1\ldots 4}\) normalized to constant energy.  
\begin{table}
\begin{tabular}{c c l} \hline  & \(A_{1/7}\) & 3 rd-order max-\(\mathbf{r}_{\text{E}}\) beam to/off listener \\ \(A\) & \(A_{2/6}\) & 2 nd-order max-\(\mathbf{r}_{\text{E}}\) beam to/off listener \\  & \(A_{3/5}\) & 1 st-order max-\(\mathbf{r}_{\text{E}}\) beam to/off listener \\  & \(A_{4}\) & omnidirectional beampattern \\ \hline \(B\) & \(B_{1\ldots 7}\) & 3 rd-order max-\(\mathbf{r}_{\text{E}}\) beams to and off listener linearly blended at \([\infty,6,3,0,-3,-6,-\infty]\) dB \\ \hline \(C\) & \(C_{1\ldots 7}\) & two 3 rd-order max-\(\mathbf{r}_{\text{E}}\) beams horizontally arranged \\  & at \(\pm 30^{\circ}\;[0,1,\ldots 6]\) with respect to the listener \\ \hline \end{tabular}
\end{table}
Table 1: Properties of tested beampattern designs \(A\), \(B\), and \(C\).