esa-sceva/satcom-chunk-collection huggingface dataset:
# Design and Switching Characteristics of Flip-Chip GaN Half-Bridge Modules Integrated with Drivers
## 2 Module Design and Fabrication  
The equivalent circuit diagram of the integrated GaN half-bridge module is shown in Figure 1. Every driver loop includes a driver die, 1 \(\Omega\) resistor, and 1 uF capacitor. The power loop of the module consists of GaN enhancement-mode (e-mode) HEMTs with a threshold voltage (\(V_{th}\)) of 1 \(V\), breakdown voltage (BV) of 650 V, and on-resistance (R\({}_{\text{on}}\)) of 100 m\(\Omega\). The module uses AlN as the substrate material for decent heat dissipation performance.  
To reduce the trace length of the driver loop and obtain lower inductance, two modules were fabricated with integrated driver dies. The difference between these two modules is that the driver loops of the two modules were packaged either by the wire bonding process or using flip-chip technology. A microscope photograph of the driver loop packaged by wire bonding is shown in Figure 2a. The diameter of the bonding Au wire was 20 \(\upmu\)m. The capacitor and resistor were interconnected with the substrate by surface mount technology (SMT) in this module. The distance between the out terminal of the driver and the gate of the HEMT device was more than 4 mm. As shown in Figure 2b, the driver die in the other module was packaged by flip-chip technology through gold balls. The diameter of the gold balls was approximately 60 \(\upmu\)m. A capacitor was set on the reverse side of the substrate by SMT, and a tantalum nitride (TaN) film was used as the gate resistor on the substrate. The distance between the out terminal of the driver and the gate of the HEMT was as short as 1.3 mm.  
Figure 1: Schematic of the integrated GaN half-bridge module.  
A microscope photograph of the power loop is shown in Figure 3. In order to reduce the parasitic inductance of the power loop, the HEMTs were packaged in the module by flip-chip technology. There were 36 gold balls on the source and drain pads, and two gold balls on the gate pad. The parasitic inductance of the power loop was extracted using an Agilent E4980A Precision LCR Meter, which was measured as 3.4 nH. This shows that the module integration achieved ultra-small parasitic inductance of the power loop.
# Buckling Analysis of Piles in Multi-Layered Soils
## 4 Conclusions  
As expected, the proposed approach was demonstrated to be of general use, because developing in Fourier series the stiffness distributions of the different layers of a non-homogeneous soil allows for the handling of many different stiffnesses of the different layers as a single non-uniform stiffness distribution function. Additionally, this feature can be used to determine boundary conditions. In this way, pinned, clamped, or partially clamped ends of piles can be assigned by varying the stiffness and thickness of the soil at that level.  
Furthermore, the Rayleigh-Ritz method successfully solved complex buckling analysis problems, where a pile usually crosses several soil layers. Indeed, adopting the Rayleigh-Ritz method effectively simplifies the variational problem of minimum to a minimisation problem of the function of the coefficients of the Fourier development describing the second-order displaced shape y(x) of the pile subject to buckling.  
The robustness and efficiency of the proposed method have allowed for the solving of many different cases of buckling analyses of piles in multi-layered soils. In order to  
Figure 7: (**a**) Second-order displaced shape of Sap2000 buckling analysis model with horizontal springs correspondent to soil stiffness of that level. (**b**) Second-order displaced shape of analytical variational approach and buckling load of a pile in a multi-layered soil. (**c**) Configuration of the soil layers provided by [9].  
understand how different soil layers with varied depths and stiffnesses can affect the critical buckling load, some examples were reported to highlight some crucial cases. It has been confirmed that pile buckling is unlikely to occur unless some voids or very soft layers are interposed between stiffer layers. Unfavourable boundary conditions at the pile top (not enough of it clamped to the foundation) and at the pile bottom (insufficient embedding of the pile's lower end in a stiff layer) have the effect of decreasing buckling load.  
Since the proposed method is valid for vertical piles with constant cross-sections, in future research the cases of tapered piles, inclined piles, as well as the effect of imperfections will be investigated.  
Conceptualization, L.F., G.F.G. and M.S.; methodology, L.F. and M.S.; Software, L.F., M.S. and A.H.; Validation, and formal analysis, E.C., M.D., G.F.G. and A.H.; Writing, L.F., M.S., A.H. and M.D.; Funding: L.F. and M.D. All authors have read and agreed to the published version of the manuscript.  
This work was developed under the financial support of the Italian Ministry of University and Research (MIUR), PhD PON RI XXXIII Cycle, CUP: F22J17000110007.  
The authors declare no conflict of interest.
# Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks
## 2 Recent Research Direction for D2D Communications  
Before we dig deep on the applications of ML in D2D communication, we have to highlight the future research directions for D2D communication in both sub 6 GHz and mmWaves bands, as summarized in Figure 2, which are given as follows.
###### Abstract  
A significant share of the conversion of thermal into electrical energy is realized by steam turbines. Formerly designed for continuous operation, today's requirements include extended part load operation that can be accompanied by highly unstable flow conditions and vibrations within the control valve of the turbine. The prediction of the flow at part load conditions requires large computational efforts with advanced turbulence modeling in order to compute the flow at a reasonable accuracy. Due to the unsteadiness of the flow, the evaluation of the numerical results itself is a major challenge. The turbulent structures require statistical approaches, of which the use of Spectral Proper Orthogonal Decomposition (SPOD) has proven itself as a powerful method. Within this paper, the application of the method on a critical operating point with a temporal excitation of pressure oscillations observed in the experiments with dry air is presented. Using SPOD, the dominating flow phenomena were isolated and flow structures visualized.  
CFD; SPOD; steam turbine; unsteady flow; valve +
Footnote †: This manuscript is an extended version of our meeting paper published in the Proceedings of the 14 th European Turbomachinery Conference, Gdansk, Poland, 12-16 April 2021.  
flow varies significantly with the choice of the numerical setup [1; 6]. Higher-order turbulence modeling is required in order to account for different flow features and the validation of CFD data against test results, favorably for the same geometry, is needed for the validity of results. In return, using a validated numerical setup can help understand findings in the experiment as it allows insight into the three-dimensional flow field and its structures.  
The comparison of CFD results against experimental data can be a challenge on its own. Because of the random nature of the turbulent flow, instantaneous flow conditions are difficult to compare and statistical measures are needed. While minimum and maximum values as well as the time average are rather simple to compute, evaluating the temporal behavior of the flow is challenging. Due to the grid requirements of the numerical analysis and the resulting computational effort, numerical results can usually capture only a short physical time span and low frequency effects are often not captured.  
For higher frequencies, the chaotic nature of the turbulent flow makes it difficult to identify dominating and reoccurring structures in the flow field, even though they are initially captured by Fourier transformations. To evaluate the random flow, statistical methods are required to analyze the flow field with respect to the temporal and spacial evolution of reoccurring flow effects. Within this study, Spectral Proper Orthogonal Decomposition (SPOD), as published by [PERSON] et al. [7], was used, which has proven itself to be a powerful method of isolating and visualizing reoccurring flow features. Its application on a critical operating point with temporal periodic pressure trends is assessed in this paper.
## 6 Conclusions  
In this paper, we have presented the ROR routing protocol, which addresses the issue of the reliability of node-to-node link quality in CRSN. Utilizing an energy-efficient technique, the strategy uses the common route reply strategy in traditional AODV to create virtual clusters around the next hop nodes of the selected routes. This further configures the nodes in the network in order to maximize the utilization of the geographical forwarding, while ensuring reliable node-to-node links at the point of data transfer. Theoretical analysis, which closely follows simulation results, shows that the strategy is able to transmit data to the sink in fewer hops than the closest node to the transmitting node metric, which is usually utilized for route search operations in similar schemes. This is because the strategy is designed to the select the nodes in the transitional region that exhibit the highest forwarding values. The simulation study shows that ROR can ensure a stable reliability in the network of above 95% at moderate PU channel activity and network load. This reliability is greatly affected by PU activity and moderately affected by the network load. Although the implemented receiver contention priority scheme can stabilize packet end-to-end latency at moderate network load and PU activity, ROR experiences a gradual increase in the latency with network density. This is primarily because of the increase in eligible nodes participating in receiver contention at each region and the PU activity. Further simulation studies for comparison have also revealed the favorable implications of adopting this strategy in terms of throughput, goodput, latency and energy. The scheme is also able to avoid the creation of routing hot spots in the network by its decentralized forwarding technique, thereby reducing packet drop due to network load, as against the compared approach. All these make ROR a favorable scheme that has the ability to improve the overall network quality of service for CRSNs.
# Research on Space Maglev Vibration Isolation Control System Modeling and Simulation
## 5 Conclusions  
The findings of this study are summarized as follows:  
By designing the aircraft as a relatively independent and organically combined platform module and payload module, non-contact maglev technology is used to achieve dynamic and static isolation design of the two modules, achieving a vibration isolation effect in space. At the same time, high-precision active control of the payload module is adopted; the master-slave collaborative control strategy meets the requirements of a high-performance payload. Based on a uniform magnetic field design, high-precision force control performance is ensured by adjusting the current accuracy. Through maglev vibration isolation system modeling and simulation analysis, the maglev vibration isolation effect of the non-contact maglev mechanism is outstanding, significantly improving the control performance of the space platform.  
Based on the uniform magnetic field design, high-precision force control performance is ensured by adjusting current accuracy. To ensure high linearity of the actuator force output, the magnetic field part of the magnetic circuit structure must have strong uniform strength characteristics.  
Interdisciplinary joint simulation of electric, magnetic, and structural aspects was conducted on the magnetic levitation isolation system. By conducting physical testing and  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No.** & **Item** & **Index** & **Result** \\ \hline
1 & Force Range & \(\geq\)\(\pm\)10 & \(\geq\)\(\pm\)10 N \\ \hline
2 & Force Accuracy & 0.5 mN & 0.5 mN \\ \hline
4 & Frequency response characteristic & 200 Hz & \textgreater{}200 Hz \\ \hline
5 & Magnetic field intensity & 4455 & \textless{}7000 Gs \\ \hline
6 & Non-uniformity of magnetic field & 0.8\% & \textless{}1\% \\ \hline
7 & Magnetic field temperature drift & \textless{}0.3\%/\({}^{\circ}\)C & \textless{}0.3\%/\({}^{\circ}\)C \\ \hline \hline \end{tabular}
\end{table}
Table 7: Testing and Calibration Result.  
Figure 15: Actuator prototype sample.  
calibration, and designing a testing and calibration system, it has been proven that the system meets the design requirements, achieving 0.15 mA high-precision current control technology and 0.5 mN driving force control technology.  
The measurement under the dynamic itinerary will continue in the future.  
Conceptualization, J.W.; Methodology, J.W.; Validation, M.Y.; Formal analysis, M.Y.; Investigation, M.Y.; Writing--original draft, M.Y. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.  
The authors declare no conflict of interest.
# Research on Sentiment Analysis of Online Public Opinion Based on RoBERTa-BiLSTM-Attention Model
## 3 Model Construction
### So-Pmi  
Commonly used Chinese sentiment dictionaries have limitations in terms of coverage and domain-specific vocabulary, e.g., commonly used dictionaries may not be able to accurately identify and categorise some new words with sentiment tendencies on the web or words that change their sentiment tendencies during specific, unexpected events. In addition, deep learning algorithms require a large amount of labelled data for training, and labelling data requires high labour and time costs. Therefore, this study used the SO-PMI algorithm to construct a supplemental event dictionary and merged it with commonly used dictionaries to emotionally annotate the data, improve the accuracy of event-specific emotion annotation, and reduce the annotation cost.  
SO-PMI, i.e., the sentiment orientation point mutual information algorithm, classifies the sentiment orientation of a word by judging the probability of the word appearing simultaneously with the seed word. If the probability of the word appearing at the same  
Figure 1: A framework for categorising emotions.  
time with the positive word is high, it is judged as a positive affective word; if the probability of the word appearing at the same time with the negative word is high, it is judged as a negative affective word; if the probabilities are comparable, it is judged as neutral. The following is the determination formula:  
\[PMI=log_{2}\bigg{(}\frac{P(word1,word2)}{P(word1)P(word2)}\bigg{)} \tag{1}\]  
\[SO-PMI_{j}=\sum_{i=1}^{num(pos)}PMI(word,pos_{i})-\sum_{i=1}^{num(neg)}PMI(word, neg_{i}) \tag{2}\]  
where \(PMI\) is the point mutual information formula, \(P(word1)P(word2)\) is the joint probability, and \(SO-PMI_{j}\) is the sentiment point mutual information formula, which is used to judge the sentiment tendency of word \(j\).
## 4 Discussion
[35] evaluated the effect of pyrocatechol against plant pathogens that are commonly found in soil. The activity was measured in diameter (mm) of the inhibition zones present on agar medium in Petri plates. In the case of the bacteria _Pseudomonas putida_, _Corynebacterium xerosis_, and _Pseudomonas pyocyanine_, the inhibitions were 31.3, 21.6, and 20.6 mm, respectively, with 0.1 mL from a 10 mM pyrocatechol solution. In contrast, for the fungi _Fusarium oxysporum_ and _Pentiillium italicum_, the inhibition zones were 29.8 and 26.5 mm, respectively, with the same volume of solution. [PERSON] et al. [36] evaluated the antimicrobial activity of pyrocatechol against _Escherichia coli_, _Salmonella typhi_, _Pseudomonas aeruginosa_, _Staphylococcus aureus_, and _Bacillus cereus_, obtaining minimum inhibitory concentrations of 0.67, 0.67, 1.3, 1.6, and 1.8 mg mL\({}^{-1}\), respectively. These results suggest that pyrocatechol has antibacterial and antifungal activities, showing that this compound is efficacious against different types of bacteria. The research results cited above are consistent with the findings of the current investigation, where pyrocatechol had biological but not insecticidal activity against bacteria and fungi. However, it had insecticatic activity, increasing the durations of the larval and pupal periods and probably stimulating the feeding habits. Other studies of biological effects include [PERSON] et al. [37], who reported the total inhibition of mycelial growth of _Pentiillium cyclobium_, a phytopathogenic fungi, at 350 ppm. [PERSON] et al. [38] tested nonanal against _Sclerotinia sclerotium_ and observed inhibition of the germination of the mycelial plug, suggesting that this molecule has antifungal effects. [PERSON] et al. [39] found an attractant effect of nonanal at 10 mg mL\({}^{-1}\) in adults of _Harmonia axyridis_ (Coleopterarica: Coccinellidae), a predatory insect as a biological control against _Myzus persicae_ and _Aphis gossypii_ (Hemiptera: Aphididae). [PERSON] et al. [40] studied the response of _Pediculus humanus capitis_ (Phthiraptera: Pediculidae) to nonanal, finding that it has an attractant effect at 0.001 mg ml\({}^{-1}\) but repellency at 10 mg mL\({}^{-1}\). [PERSON] et al. [41]found that _Solanum tuberosum_ emitted green leaf volatile compounds, including nonanal, under the attack of _Leptinotarsa decemilinetata_ (Coleopterara: Chrysomelidae) as a defense method; however, it acts as an attractant for predators of this insect. The studies cited above show that nonanal is part of green leaf volatiles in some plant species, acting mainly as an attractant to some insects (mainly predators) and as a repellent against others. However, to the best of our knowledge, this is the first report of nonanal activity against the fall armyworm. Finally, the results show that LC\({}_{50}\) was lower in nonanal (200 ppm), followed by CHCl\({}_{3}\)Sc extract (1504.03 ppm) and pyrocatenhol (3339.3 ppm). This could indicate that nonanal has an integral part in the insecticidal and insecistatic effects of CHCl\({}_{3}\)Sc extract against _S. frugiperda_.
# Parameter Optimization Method for Metal Surface pBRDF Model Based on Improved Strawberry Algorithm
## 2 Polarization Bidirectional Reflection Distribution Function Model
Based on the above analysis, the multi-parameter pBRDF model of metal surfaces can be expressed as:  
\[F_{j,k}=\frac{\left(q-1\right)\left(\sqrt{2}\sigma\right)^{2q-2}\cdot\min(1. 0,\frac{2 cos\alpha cos\theta_{r}}{cos\beta},\frac{2 cos\alpha cos\theta_{i}}{ cos\beta})}{4\pi cos\theta_{i}cos\theta_{r}\ cos^{4}\alpha[tan^{2}\alpha+\left( \sqrt{2}\sigma\right)^{2}]^{q}}M_{j,k}^{s}+\frac{k_{d}}{\pi}(cos\theta_{i} cos\theta_{r})^{c}M_{j,k}^{d}+k_{v}\frac{1}{\sqrt{2\pi}\sigma_{v}}exp\left( \frac{-\theta_{r}^{2}}{2\sigma_{v}^{2}}\right)M_{j,k}^{v} \tag{6}\]  
Figure 1: BRDF coordinate system. where \(n,k,\sigma,k_{s},k_{d},k_{v},q,c\) and \(\sigma_{v}\) are the unknown parameters to be retrieved. Generally speaking, the polarization degree of the reflected light from metal surfaces can be expressed by the degree of polarization (DOP). Assuming that the Stokes vector of the incident light is an unpolarized natural light and can be represented as \(E_{i}= \begin{bmatrix}1&0&0\end{bmatrix} ^{T}\), where the circularly polarized component of natural light is extremely small and can be ignored [20], and then, the Stokes vector of the outgoing from a metal surface \(E_{r}\) can be calculated as follows:  
\[E_{r}= \begin{bmatrix}S_{0}\\ S_{1}\\ S_{2}\end{bmatrix} =F_{j,k}\cdot E_{i}= \begin{bmatrix}I\\ Q\\ U\end{bmatrix} =\left[ \begin{array}{c}F_{00}^{s}+F_{00}^{d}+F_{00}^{v}\\ F_{10}^{s}\\ F_{20}^{s}\end{array} \right] \tag{7}\]  
The DOP value can be derived as follows:  
\[DOP=\frac{\sqrt{Q^{2}+U^{2}}}{I}=\frac{\sqrt{{F_{10}^{s}}^{2}+{F_{20}^{s}}^{2} }}{F_{00}^{s}+F_{00}^{d}+F_{00}^{v}} \tag{8}\]  
When the incident direction and observation direction are coplanar, DOP can be rewritten as:  
\[DOP=\frac{F_{10}^{s}}{F_{00}^{s}+F_{00}^{d}+F_{00}^{v}} \tag{9}\]
## 3 Results and Discussion
### Quaternary Nitrides as Superconductor
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Binary Nitride**} & \multicolumn{2}{c}{**Ternary Nitride**} & \multicolumn{2}{c}{**Quaternary Nitride**} \\ \hline
**Composition** & **Predicted T\({}_{\text{C}}\) (K)** & **Composition** & **Predicted T\({}_{\text{C}}\) (K)** & **Composition** & **Predicted T\({}_{\text{C}}\) (K)** \\ \hline NbN & 9.5 & Nb\({}_{0.51}\)Ti\({}_{0.49}\)N & 11.09 & Nb\({}_{0.35}\)Ta\({}_{0.23}\)Ti\({}_{0.42}\)N & 17.57 \\ \hline HfN & 6.6 & Nb\({}_{0.89}\)Hf\({}_{0.11}\)N & 7.71 & Nb\({}_{0.34}\)Ta\({}_{0.23}\)Ti\({}_{0.43}\)N & 17.55 \\ \hline ReN & 5.7 & Nb\({}_{0.9}\)Re\({}_{0.1}\)N & 7.90 & Nb\({}_{0.28}\)Ta\({}_{0.26}\)Ti\({}_{0.46}\)N & 17.53 \\ \hline ScN & 5.67 & Nb\({}_{0.35}\)Sc\({}_{0.68}\)N & 10.39 & Nb\({}_{0.32}\)Ta\({}_{0.34}\)Ti\({}_{0.34}\)N & 17.53 \\ \hline TaN & 5.84 & Nb\({}_{0.89}\)Ta\({}_{0.11}\)N & 7.91 & Nb\({}_{0.34}\)Ta\({}_{0.21}\)Ti\({}_{0.45}\)N & 17.52 \\ \hline TiN & 4.71 & Nb\({}_{0.42}\)Ti\({}_{0.58}\)N & 11.11 & Nb\({}_{0.32}\)Ta\({}_{0.28}\)Ti\({}_{0.40}\)N & 17.51 \\ \hline VN & 5.81 & Nb\({}_{0.35}\)V\({}_{0.65}\)N & 7.90 & Nb\({}_{0.32}\)Ta\({}_{0.26}\)Ti\({}_{0.42}\)N & 17.50 \\ \hline ZrN & 6.52 & Nb\({}_{0.83}\)Zr\({}_{0.17}\)N & 9.18 & Nb\({}_{0.28}\)Ta\({}_{0.28}\)Ti\({}_{0.44}\)N & 17.46 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Predicted best Tc values for the quaternary superconductors. Compositions in the table show that when there is a balance among the Nb, Ti, and Ta elements of the quaternary systems, it will offer better superconductivity. The table also shows that there is much improvement in the Tc values in the quaternary systems when compared to the binary systems. Figure 9: Phase diagram for predicted Tc in the Nb-Ti-Ta-N alloy system. This diagram represents the compositional dependence of the predicted Tc in the quaternary Nb-Ti-Ta-N system. The predicted Tc values are color-coded, as indicated by the gradient legend on the right, ranging from 4.7 K (blue) to 17.6 K (red).