esa-sceva/satcom-chunk-collection huggingface dataset:
# _remote sensing_
## 3 Related Data and Correction Models in Cal/Val of Altimeters
### Tidal Differences
The RMS and RSS differences between the interpolated tidal signal and in situ tide gauge are computed by Equations (5) and (6):  
\[\text{RMS}=\langle(\frac{1}{\text{N}}\sum_{k=1}^{\text{N}}\left(\text{VEC}_{ \text{tide}}^{\text{k}}\right)^{2})\rangle^{1/2} \tag{5}\]  
\[\text{RSS}=\langle(\frac{1}{\text{S}}\sum_{k=1}^{\text{S}}\left(\text{RMS}^{ \text{k}}\right)^{2})\rangle^{1/2} \tag{6}\]  
where the VEC\({}_{\text{tide}}^{\text{k}}\) is the vector difference at a specific location;  
N is the total number of tide gauges;  
RMS\({}^{\text{k}}\) is the RMS of constituent k.  
The precision of the six tide models is very close to one another (Table 3), in which the HAMTIDE12 tide model is the most accurate one in this area. The EOT20 tide model has some difficulties in modelling the tides in this region, and the problem occurs in the B329 tide location and K1 tide component. As the parameters of this tide model are not covered the Hong Kong area, the extrapolation is used to obtain the tidal parameters. After excluding the Hong Kong tide gauge, RSS of the GOT4.10, EOT20, and HAMTIDE12 decrease a bit, while the other tide models increase (RSS* in Table 3). Therefore, when using tide models in the Cal/Val of altimeters in WSCS, the GOT4.10 and HAMTIDE12 are recommended. The DTU16, NAO99 ib, and FES2014 can also be used carefully by the EOT20 model. In this research, the HAMTIDE12 tide model was used to correct the tidal difference between the ATGs and the footprints of the altimeters.
## 3 Biosynthesis of Aromatic and Isoprenic Precursors of Prenylquinones in Parasitic Protozoa
### Parasite-Specific Isoprenoids: Phytyl Pyrophosph  
As seen, the isoprenoid elongation process can produce chains of different sizes but there is also an isoprenic chain with a different degree of saturation, the phytyl-pyrophosphate [123] (Figure 4). Phytyl-pyrophosphate is produced by a reduction of GGPP by geranylgeranyl diphosphate/geranylgeranyl-bacteriochlorophyllide reductase in plants which is not putative in parasites. This isoprenic moiety is typical of photosynthetic organisms and is constituent oftocopherol, PK, chlorophyll and phytilated proteins [123]. Phytylated quinones have already been discovered in _Leishmana_ and _Plasmodium_ organisms [54; 64]. The incorporation of [3H]-GGPP in phytylated prenylquinone strongly suggests that both parasites possess an active pathway for phytol biosynthesis. Moreover, the incorporation of [3H]-phytol into phytylated quinones in both parasites suggests an active phytol phosphorylation process for the salvage of phytol, which is typical of some photosynthetic organisms [123]. Since phytol/phytyl-PP metabolism is absent in humans, last commented phytol-related pathways should be considered a great drug target that is still unexplored.  
Figure 4: Isoprenic chain elongation/reduction. Isoprenic chain chemical structures and its elongation/reduction pathways. Continuous arrows indicate a single enzymatic step and discontinuous arrows indicate several enzymatic steps. Enzymatic steps are better described in the text. Structures sourced from Kyoto Encyclopedia of Genes and Genomes database [87].
## Appendix A
Additionally, in agreement with the previously obtained results in Equations (20) and (22) we conclude that if values \(K(\overrightarrow{X},{I_{0}}),\ \widetilde{K}(\overrightarrow{Z}, \overrightarrow{Y},{I_{0}})\) depend on the intensity \({I_{0}}\), then the function \(I=F_{I}({I^{\prime}})\) becomes non-linear. Indeed, in this case, Equations (17) and (18) to determine \({I_{0}}\) as the intensity function \({I_{0}}\) cease to be linear. The following presents the key parameters of the SPAS-02 ([[http://activespectr.com/sites/default/files/docs/spectrometer-spas-02-brochure.pdf](http://activespectr.com/sites/default/files/docs/spectrometer-spas-02-brochure.pdf)]([http://activespectr.com/sites/default/files/docs/spectrometer-spas-02-brochure.pdf](http://activespectr.com/sites/default/files/docs/spectrometer-spas-02-brochure.pdf)) accessed on 15 February 2022) and SPAS-05 ([[https://spas05.com/sites/default/files/docs/spektrometr-spas-05-buklet.pdf](https://spas05.com/sites/default/files/docs/spektrometr-spas-05-buklet.pdf)]([https://spas05.com/sites/default/files/docs/spektrometr-spas-05-buklet.pdf](https://spas05.com/sites/default/files/docs/spektrometr-spas-05-buklet.pdf)) accessed on 10 March 2022) emission spectrometers, which were used to test the proposed algorithm:  
* Paschen-Runge optical configuration;
* Rowland circle diameter: 330 mm;
* inverse dispersion: 1.4 nm/mm;
* diffraction grating: 2100 lines per mm;
* a system of multi-element CCDs with a total number of channels exceeding 25,000 and a channel size of about 8 \(\upmu\)m;
* spectral range: 174 to 455 nm (non-vacuum version: 185 to 457 nm);
* automated profiling with drift correction;
* spectral resolution not exceeding 0.05 nm.
## 2 Materials and Methods
### Methods
#### 2.2.12 DAPI and F-Actin Staining  
In this study, two fluorescent dyes, 4\({}^{\prime}\),6-diamidino-2-phenylindole (DAPI), and phalloidin, were utilized to observe the viability and structural components of U87 MG and T98G cells. DAPI is a fluorescent dye that binds specifically to adenine-thymine (AT)-rich regions of DNA within the cell's nucleus. It enables researchers to visualize the nucleus and assess the viability of cells based on the integrity of their DNA. Phalloidin is a toxin derived from the death cap mushroom that has the ability to bind specifically to F-actin filaments. It stabilizes these filaments and allows for visualization with fluorescent conjugates. U87 MG and T98G cells were grown in 24 well plates under four different conditions: the control (no treatment), methioninease treatment, etoposide treatment, and a combination of the methioninease and etoposide treatment. Etoposide was administered at a concentration of 40 \(\upmu\)M for U87 MG cells and 29 \(\upmu\)M for T98G cells. L-methioninease was administered at a concentration of 5.792 units/mL for U87 MG cells and 5.215 units/mL for T98G cells, which were their respective IC\({}_{50}\) values. After 24 h of incubation, the cells were imaged. The cell culture medium was removed, and the cells were washed twice with PBS. Paraformaldehyde solution (4%) was added to each well and incubated for 20 min at room temperature. The cells were then washed twice with PBS. Next, PBS containing 0.1% Triton X-100 was added to the cells and left for 10 min to permeabilize the cell membranes. The cells were washed twice with PBS. The DAPI and phalloidin-iFluor \({}^{\mathrm{TM}}\) 488 conjugate was diluted in PBS containing 1% Bovine Serum Albumin (BSA) at a 1:1000 ratio. The staining solution was added to the wells and incubated for 30 min in the dark at room temperature to label the nuclei and F-actin filaments. The cells were then washed twice with PBS containing BSA. Finally, the cells were observed under fluorescent light using a Leica DM IL LED inverted microscope (Leica Biosystems, Wetzlar, Germany).
## 5 Experimental Results
### Crosstalk Characteristics  
Signal transmission lines were designed based on the results of the crosstalk analysis in section 3.3. The layout of the signal transmission lines is shown in Figure 8. The pitch of the electrical respectively connector pads is 0.5 mm, width and space of the signal transmission lines are 90 and 120 \(\upmu\)m, respectively. The pitch is smaller than of our previous form-factor AOC [7]. Reduction of the pitch leads to an increase of crosstalk between adjacent channels. Therefore, ground vias were provided along each signal transmission line with no gap for electromagnetic field shielding. Figure 9 shows the measured ICR characteristic of a signal transmission line. The measured ICR at the Nyquist frequency (12.89 GHz) is about \(-\)53 dB. According to the analysis result shown in Figure 4, that ICR value indicates that crosstalk jitter can be suppressed to less than 0.01 UI.  
Figure 6: Photograph of fabricated AOC.  
Figure 7: Measured vertical cavity surface emitting laser (VCSEL) temperature.
###### Abstract  
Inhibition of HIF-prolyl hydroxylases (PHD1, PHD2, and PHD3) causes the stabilization of hypoxia-inducible factor-1\(\alpha\) and -2\(\alpha\) (HIF-1\(\alpha\) and HIF-2\(\alpha\)) to regulate various cell signaling pathways. Hypoxia-inducible factor (HIF) is crucial in regulating signal responses mediated by hypoxia. HIF regulates the transcription of many genes involved in the response to hypoxia and ischemic insult. Our current work investigates the protective effects of PHD1 knockout in mice against myocardial infarction. **Study Design:** Myocardial infarction (MI) was induced by left anterior descending coronary artery (LAD) ligation (8-12-week-old mice) in both wild-type (WT) and PHD1 knockout (PHD1\({}^{-/-}\)) mice. WT sham (S) and PHD1\({}^{-/-}\)S group mice underwent surgery without LAD ligation. Thirty days post-surgery, cardiac functions were measured by echocardiogram. Mice in all the groups were euthanized at various time points for tissue collection post-MI 8 h (gel shift and microarray analysis), 4 days (Western blot analysis), 7 days (blood vessel density), or 30 days (histological analysis). For microarray analysis, WTMI and PHD1\({}^{-/-}\)MI group mices' heart tissue was used for RNA isolation, then hybridization to a GeneChip\({}^{\text{TM}}\) Mouse Gene 1.0 ST Array as per the manufacturer's instructions. Bioinformatic analysis was performed using the transcriptome analysis console (TAC) to generate a list of differentially regulated genes, followed by ingenuity pathway analysis. **Results:** The study findings revealed a significant increase in vessel density (capillary and arteriolar density) in the PHD1\({}^{-/-}\)MI mice compared to those with WTMI. The echocardiographic examination demonstrated that the PHD1\({}^{-/-}\)MI mice group had an increased ejection fraction and fractional shortening than the WT mice 30 days post-MI. HIF-1\(\alpha\) DNA binding activity was higher in PHD1\({}^{-/-}\)MI mice than in WTMI. The Western blot analysis showed a significant increase in the expression of HSPA12B in the PHD1\({}^{-/-}\)MI compared to WTMI mice. Bioinformatic analysis using TAC software, Version 4.0.2.15 (1.5 fold, \(p<0.05\)) showed 174 differentially regulated genes. **Conclusions:** In conclusion, our study showed PHD1 knockout activates several important molecules and signaling pathways, resulting in increased angiogenesis and cardioprotection against myocardial infarction.  
**Keywords:** prolyl hydroxylase-1; myocardial infarction; HIF-1\(\alpha\); cardiac functions; pathway analysis
# A Novel Method of Local Anode Effect Prediction for Large Aluminum Reduction Cell
## 6 Conclusions  
A local anode effect prediction method is proposed through the study of the fluctuation detection and prediction of anode rod current. The fluctuation of real-time current is monitored using the density test method with time-sliding window, and the improved GRU-LSTM neural network model and ARIMA algorithm are used to predict the current of fluctuating and non-fluctuating anode rod, respectively. A local anode effect level strategy based on the anode rod current prediction is proposed from the mechanism of local anode effect occurrence. Thus, we can better detect different anode rods current conditions and more accurately predict the arrival time and level of the anode effect, so that we can be more fully prepared for the appearance of the anode effect or have more sufficient time to take corresponding measures to avoid the occurrence of the anode effect. Simulation experiments based on actual industrial aluminum plant data advance the local anode effect prediction time to 5-10 min. Compared with LSTM and CNN-LSTM networks, the GRU-LSTM network is more accurate in predicting anode current and can effectively predict the occurrence of anode effect. The research in this paper is based on the anode effect prediction problem in large-scale aluminum electrolytic cells, which provides another new option for solving the anode effect prediction problem and lays the foundation for future research on active anode effect extinction work. It contributes to the smooth operation of aluminum electrolytic cells, green operation, and reduction of resource waste.  
Conceptualization, J.C. and Q.L.; methodology, Z.L. and B.L.; software, Z.L.; validation, Q.Y., R.H. and H.L.; formal analysis, J.C. and X.L.; investigation, B.L. and X.L.; resources, Q.L. and B.C.; data curation, J.C., R.H. and X.L.; writing--original draft preparation, B.L.; writing--review and editing, J.C. and Z.L.; visualization, Z.L. and J.C.; supervision, Q.L. and Q.Y.; project administration, H.L. and B.C.; funding acquisition, J.C. and Q.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the China Postdoctoral Science Foundation, grant number 2021M690798; Guizhou Province Science and Technology Plan Project, grant number [2021] General 085; National Natural Science Foundation of China, grant number 62273033; Chinese Society of Academic Degrees and Graduate Education, grant number 2020 MSA117.  
Not applicable.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Number** & **Area** & **N** & **Level** \\ \hline
1 & Area1 & 0 & I \\
2 & Area3 & 5 & III \\
3 & Area6 & 3 & II \\
4 & Area1 & 2 & II \\
5 & Area4 & 1 & II \\
6 & Area2 & 6 & III \\
7 & Area4 & 2 & II \\
8 & Area5 & 7 & III \\
9 & Area1 & 2 & II \\ \hline \end{tabular}
\end{table}
Table 3: Local anode effect level.
## 4 Results
#### Classification Results  
The \(3\times 3\) confusion matrix for the best model (EfficientNetB4) is presented in Figure 7 with three rows and columns related to three different classes of vehicles. The rows represent the actual labels and columns represent the predicted labels. From the confusion matrix, it is understood that that the EfficientNetB4 model shows better performance in terms of handling non-over-volume goods carriers and non-goods carriers compared to over-volume goods carriers.  
[EfficientNetB4]. Over Vol.--Over-volume goods carriers, Non-over vol.--Non-over-volume goods carriers, Non-goods--Non-goods carriers.  
The size of the collected images is adjusted with the help of the image data generator class from the Keras library. The deep CNN models are trained on dimensions 224, 240, 300, and 380, and the best performance dimensions are presented in Table 5. From Table 5, it can be observed that the training performance of MobileNetV2 and VggNet were acceptable, but these models performed below par with the test data. In this work, the authors observed that the ResNet and EfficientNet architectures produced better performances for the training, validation, and testing sets. In detail, ResNet50 and EfficientNet [B0][B3][B4] performed similarly, with accuracies of 96%, 94%, 96%, and 96%, respectively. ResNet was  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Model** & **Loss** & **Accuracy** \\ \hline EfficientNet [B4] & 0.1 & 0.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: _Cont._  
Figure 7: The \(3\times 3\) confusion matrix for the best model.  
very effective with respect to accuracy, but it had high computational costs. EfficientNet architectures were effective with lower computational costs. Considering the FLOPS of each model, it is evident that EfficientNet [B0] was very effective with a trade-off between the computational costs of 0.7 billion FLOPS and the average accuracy of about 94%. The compound scaling method in EfficientNet architectures carefully balances network width, depth, and resolution to achieve better accuracy and efficiency. Powered by this compound scaling method, we demonstrated that EfficientNet scaled up very effectively, surpassing ResNet, VggNet, and MobileNet with an order of magnitude fewer parameters and FLOPs on our dataset.
# Design of Multi-Mode Antenna Array for Use in Next-Generation Mobile Handsets
###### Abstract  
In this study, a new design of a tri-band multiple-input-multiple-output (MIMO) antenna array is proposed for fifth-generation (5G) cellular systems. Its structure is composed of eight identical planar-inverted F antenna (PIFA) elements placed at different edge corners of the handset mainboard with overall dimensions of \(150\times 75\) mm\({}^{2}\). The PIFA elements and ground plane of the MIMO antenna system are arranged on the back layer of the platform, which makes the design easy to integrate with the handset circuit. For S\({}_{11}\leq\) -10 dB, the radiation elements of the MIMO design operate at the frequency ranges of 2.5-2.7 GHz, 3.4-3.75 GHz, and 5.6-6 GHz covering the long-term evolution (LTE) 41, 42/43, and 47 operation bands, respectively. The array achieves better than 15 dB return loss results across the three operating bands. The presented antenna array not only exhibits multi-band operation but also generates the polarization diversity characteristic, which makes it suitable for multi-mode operation. The proposed antenna array was simulated and experimentally tested. Fundamental characteristics of the proposed design are investigated. It offers three band S-parameters with acceptable isolation and dual-polarized radiation with quite good efficiency and gain results. Besides this, the total active reflection coefficient (TARC) and envelope correlation coefficient (ECC) results of the PIFAs are very low over the bands. In addition, the radiation characteristics of the MIMO antenna in the presence of the user and handset components are studied. Moreover, a new and compact phased array millimeter-wave (MM-Wave) antenna with broad bandwidth and end-fire radiation is introduced which can be easily integrated into the smartphone antenna system. Due to its good performance and simple structures, the proposed smartphone antenna array design is a good candidate for future multi-mode 5G cellular applications.  
5G; future handsets; modified PIFA; multi-antenna system; multi-band operation +
Footnote †: journal: Sensors
# High-Precision Pseudo-Noise Ranging Based on BOC Signal: Zero-Bias Mitigation Methods
## 7 Conclusions  
In this paper, the digital reception model of the BOC signal is analyzed. The analysis models of resolution error, the zero-bias of the digital code phase discriminator and the digital subcarrier phase discriminator are established. The propagation error relationship between the code tracking loop and the subcarrier tracking loop is derived, indicating that the sampling distortion error of the BOC signal, under noncommensurate sampling conditions, mainly depends on the zero-bias of the code phase discriminator. The statistical analysis model of the zero-bias of BOC signal is established, and the analytical expression of the statistical standard deviation of the zero-bias is derived. Two zero-bias mitigation methods based on the receiver parameters are proposed. The quantitative relationship between the zero-bias, the sampling frequency and correlation interval of the receiver are also introduced. The zero-bias mitigation methods, based on a quantitative relationship, can adapt different constraints and flexibly design parameters. In addition, this work uses simulations to verify the existence of limited bandwidth, the Doppler frequency offset, and thermal noise. Thus, the simulation fully validates the effectiveness of the proposed method.  
The work presented here was carried out in collaboration with all authors. [PERSON] made the research theme, designed the methods, and wrote the paper. [PERSON], [PERSON] and [PERSON] carried out the experiments, analyzed the data, and prepared the draft. [PERSON] worked on reviewing the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 61601485.  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, and in the decision to publish the results.
## 3 Experimental Section
### Polymerizations  
The reactions were carried out in a 150 mL jacketed glass reactor equipped with a reflux condenser and mechanical agitation in accordance with the following procedure: the required quantities of water, SDS and APS were charged into the reactor, subjected to 650 rpm agitation and bubbled with argon for 1 h, after which the temperature of the solution was raised to 70 \({}^{\circ}\)C and the addition of the organic phase composed of toluene and monomers started at a pre-determined dosing rate using a KD Scientific from Sigma-Aldrich syringe pump. After the end of the organic phase addition the reaction was allowed to proceed for a given time (post-addition period). Due to the large sample amounts required for all characterizations a series of runs were carried out for the two organic phase dosing rates (_Fo_) studied, that is to say, 0.05 and 0.15 g/min. For a given _Fo_, the addition period in the polymerization was divided in 5 intervals and the complete polymerization was considered as the interval 6. Then a run (in duplicate) for each interval was carried out, stopping the polymerization and collecting all the latex at the end of each of them. For 0.05 g/min polymerization the intervals 1, 2, 3, 4 and 5 included from the beginning of organic phase addition to _t_r equal to 0.23, 0.41, 0.58, 0.84 and 1, respectively. For 0.15 g/min polymerization, \(t\) values for the same intervals were 0.14, 0.36, 0.53, 0.76 and 1.This way, the amount of latex obtained was enough to make all the required characterizations.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & **M1** & **M2** & **M3** & **M4** & **M5** & **M6** & **M1R** & **M2R** & **M3R** & **M4R** & **M5R** & **M6R** \\ \hline Water (g) & 90.68 & 90.65 & 90.90 & 90.51 & 90.58 & 90.35 & 90.40 & 90.60 & 90.51 & 90.74 & 90.66 & 90.83 \\ SDS (g) & 4.75 & 4.50 & 4.54 & 4.58 & 4.53 & 4.60 & 4.50 & 4.50 & 4.51 & 4.57 & 4.59 & 4.63 \\ APS (g) & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 & 0.04 \\ Organic Phase (g) & 7.60 & 13.70 & 19.20 & 28.40 & 34.00 & 34.00 & 7.70 & 13.70 & 19.10 & 28.30 & 34.00 & 34.00 \\ \hline \multicolumn{10}{c}{Organic Phase Composition} \\ \hline Toluene (wt. \%) & 24.92 & 24.89 & 24.68 & 25.02 & 25.34 & 24.50 & 24.95 & 24.59 & 25.00 & 24.94 & 24.72 & 24.96 \\ St (wt. \%) & 60.04 & 60.37 & 60.43 & 59.95 & 59.65 & 60.63 & 60.13 & 60.48 & 59.95 & 59.79 & 60.44 & 60.06 \\ DVB (wt. \%) & 15.04 & 14.74 & 14.89 & 15.03 & 15.01 & 14.87 & 14.93 & 14.93 & 15.05 & 15.27 & 14.84 & 14.98 \\ \hline \end{tabular}
\end{table}
Table 4: Formulations used in the polymerizations at the organic-phase dosing rate of 0.05 g/min.  
Tables 4 and 5 include the formulation for all the runs carried out in this study. For both \(F_{o}\) studied, the runs stopped at the end of the intervals 1, 2, 3, 4 and 5 were named as M1, M2, M3, M4 and M5, respectively. The run that includes the complete polymerization was named as M6. The suffix R was used to identify the replicates of the runs.