esa-sceva/satcom-chunk-collection huggingface dataset:
_Article_  
**Thermal Stability, Combustion Behavior,**  
**and Mechanical Property in a Flame-Retardant**  
**Polypropylene System**  
**[PERSON] 1,2, [PERSON] 2 and [PERSON] 1,***  
1 Key Laboratory of Synthesis of Functional Materials and Green Catalysis, Colleges of Heilongjiang Province, Harbin Normal University, Harbin 150025, China; [EMAIL_ADDRESS]  
2 College of Material Science and Chemical Engineering, Harbin Engineering University, Harbin 150001, China; [EMAIL_ADDRESS]  
* Correspondence: [EMAIL_ADDRESS]; Tel.: +86-451-5893-9893  
Academic Editor: [PERSON]  
Received: 5 November 2016; Accepted: 27 December 2016; Published: 10 January 2017  
In order to comprehensively improve the strength, toughness, flame retardancy, smoke suppression, and thermal stability of polypropylene (PP), layered double hydroxide (LDH) Ni\({}_{0.2}\)Mg\({}_{2.8}\)Al-LDH was synthesized by a coprecipitation method coupled with the microwave-hydrothermal treatment. The X-ray diffraction (XRD), morphology, mechanical, thermal, and fire properties for PP composites containing 1 wt %-20 wt % Ni\({}_{0.2}\)Mg\({}_{2.8}\)Al-LDH were investigated. The cone calorimeter tests confirm that the peak heat release rate (pk-HRR) of PP-20%LDH was decreased to 500 kW/m\({}^{2}\) from the 1057 kW/m\({}^{2}\) of PP. The pk-HRR, average mass loss rate (AMLR) and effective heat of combustion (EHC) analysis indicates that the condensed phase fire retardant mechanism of Ni\({}_{0.2}\)Mg\({}_{2.8}\)Al-LDH in the composites. The production rate and mean release yield of CO for composites gradually decrease as Ni\({}_{0.2}\)Mg\({}_{2.8}\)Al-LDH increases in the PP matrix. Thermal analysis indicates that the decomposition temperature for PP-5%LDH and PP-10%LDH is 34 \({}^{\circ}\)C higher than that of the pure PP. The mechanical tests reveal that the tensile strength of PP-1%LDH is 7.9 MPa higher than that of the pure PP. Furthermore, the elongation at break of PP-10%LDH is 361% higher than PP. In this work, the synthetic LDH Ni\({}_{0.2}\)Mg\({}_{2.8}\)Al-LDH can be used as a flame retardant, smoke suppressant, thermal stabilizer, reinforcing, and toughening agent of PP products.  
polypropylene; layered double hydroxide; mechanical property; thermal stability; flame retardancy; composite
## 3 Results and Discussion  
### Plasma Parameters  
The intensity of a spectral line is proportional to the population density in the upper level of the associated transition. Variations in the strength of the lines emitted relate to the processes that take place in the plasma. Thus, the spectral was measured to determine the gas composition of the ethanol vapor microwave plasma.  
Figure 2 shows the emission spectrums of Ar-H\({}_{2}\) and Ar-ethanol-H\({}_{2}\) microwave plasma. The main luminescent groups in the plasma are H\({}_{\alpha}\) (656.19 nm), H\({}_{\beta}\) (486.25 nm), H\({}_{\gamma}\) (434.09 nm), CH (389.02 nm, 431.31 nm), C\({}_{2}\) (471.06 nm, 516.08 nm, 563.1 nm), and OH (308.75 nm). The intensity of H\({}_{\alpha}\) lines in both spectrums is almost equal, indicating a high H radical concentration in the plasma. H radicals can effectively etch the sp\({}^{2}\) carbon phase and graphite phase, which is conducive to the preparation of high-purity CNTs. The relative intensity of the spectral lines between 690 and 900 nm are all Ar I lines and almost equal strength between both spectrums, indicating that the ethanol does not change the energy state of the microwave plasma.
## Materials and Methods  
### LPJ Model  
As a tool used in this study, the Lund-Potsdam-Jena dynamic global vegetation model (LPJ) is a process-based, coupled, non-equilibrium biogeography-biogeochemistry model, which has adopted many features from the BIOME family of models [40; 41]. This model defines 10 different plant functional types (PFTs) to describe the vegetation composition in each grid cell. Each PFT has different forms of vegetation phenology (evergreen, summergreen and raingreen), leaf shape (broad-leaved and needle-leaved), climate zone (tropical, temperate and boreal), and photosynthetic pathway (C3 and C4). Different bioclimatic and biochemical parameters are set to account for the variety of structure and functioning among vegetation types. Key ecosystem processes such as vegetation growth, carbon allocation, resource competition, mortality, population establishment, fire disturbance, and litter decomposition are represented in the model to simulate the terrestrial vegetation dynamics and exchanges of carbon and water between the land and atmosphere. Details about the LPJ model can be found in [42; 43]. Now, the LPJ model has been widely used to calculate the global carbon budget [2], to assess the impact of plant water balance on agriculture [44; 45], to quantify the impact of climate change on agriculture productivity [46], and to estimate the bioenergy production potential [47]. It has acted as a tool to identify the contribution of permafrost soil to the global carbon budget [48] and to investigate the influence of fire on the terrestrial carbon cycle [49] and the regulation of the nitrogen cycle on the dynamic global vegetation, hydrology, and crop growth [50].
# SMC-CPHD Filter with Adaptive Survival Probability for Multiple Frequency Tracking
## 1 Introduction
Subsequently, in Section 4, cardinality compensation with the ICI method is additionally applied in the proposed filter structure to enhance the estimate performance of the cardinality. In Section 5, various simulations are performed to evaluate the proposed method's performance, and it is confirmed that the proposed method has better performance compared with conventional filtering methods. Section 6 summarizes the conclusions.
# A Novel Method of Emotion Recognition from Multi-Band EEG Topology Maps Based on ERENet
## 5 Conclusions  
A novel method for emotion recognition based on multi-band EEG topology is proposed in this paper. In this method, multi-band EEG topology maps are introduced by combining the frequency domain characteristics, spatial information, and frequency band characteristics of multi-channel EEG signals, which can clearly represent the changes in EEG signals on the scalp under different emotional states. Meanwhile, a novel emotion recognition network, ERENet, is proposed to learn feature representation from multi-band  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Number of Parameters** & **Training Time (Seconds)** & **Test Time (Seconds)** \\ \hline
3D-CNN [51] & 240,000 & 8200 & 9.69 \\ ERENet (Ours) & 25,024 & 900 & 0.94 \\ \hline \hline \end{tabular}
\end{table}
Table 8: The number of parameters, average training time, and average test time of 3D-CNN [51] and ERENet in the mixed-subject classification scenario.  
EEG topology maps. The experimental results on the DEAP dataset show that on the two classification tasks (low/high valence, low/high arousal), ERENet achieves a high accuracy of 95.38% and 95.09% in the intra-subject classification scenario, 68.32% and 67.97% in the inter-subject classification scenario, and 88.47% and 87.52% in the mixed-subject classification scenario. The proposed method outperforms most previous methods and is superior to other methods with similar parameters. In the future work, an EEG-based emotion recognition method that is more suitable for platforms with limited computing resources will be explored, and further research will be conducted on EEG-based emotion recognition in inter-subjects.  
Conceptualization, Methodology, software, investigation, data curation and writing--original draft preparation, Z.L.; modification and writing--review and editing, Z.L., J.Z. and E.E.O. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (Youth) under Grant No. 52001039, National Natural Science Foundation of China under Grant No. 52171310, Funding of Shandong Natural Science Foundation in China under Grant No. ZR2019 LZH005, Research fund from Science and Technology on Underwater Vehicle Technology Laboratory under Grant No. 2021 JGJQ-SYSJJ-LB06903.  
Not applicable.
# An Efficient Causal Group Communication Protocol for Free Scale Peer-to-Peer Networks
## 4 Discussion
### Protocols Designed for Plain Networks  
A plain peer-to-peer overlay network consists of a number of interconnected peers. Each peer communicates directly with other peers. In a broadcast group, each peer sends messages to every other peer in a group.
## 3 Proposed Method
### Residual-RepGhost-Dblock Module  
The RepGhost [42] introduced a bottleneck structure that utilizes the RepGhost module to generate and merge various feature maps through reparameterization, thereby eliminating the inefficient concatenate operation of Ghostnet and saving reasoning time. Inspired by the RepGhost bottleneck module, we propose a Residual-RepGhost-Dblock (RRD) module, which also adopts a bottleneck structure, as illustrated in Figure 3. Concretely, first, the input feature map is fed into the RepGhost module, reducing the channel numbers to half of the input feature map, the purpose of this process is to decrease the module's computational complexity and make the module more efficient. Secondly, the resulting feature map is fed into two paralleled depth-wise (DW) convolution blocks for feature extraction. The two depth-wise convolutions, both followed by BN and ReLU, use different dilation rates, one with a 3 \(\times\) 3 kernel and a dilation rate of 1, and the other with a 3 \(\times\) 3 kernel and a dilation rate of 2. By utilizing different dilation rates, the module can obtain multiscale features without incurring additional computational complexity that would have been associated with using larger convolutional kernels. The two convolutional results are then concatenated to generate a feature map with dimensions equivalent to the original feature map. Subsequently, the feature map is fed into a 3 \(\times\) 3 convolutional layer to extract more abstract image features. To enhance the network's sensitivity to both channel-wise and spatial-wise relationships, a coordinate attention (CA) [43] module is added to our proposed module. The CA attention module can focus the network's attention on the specific channels and spatial locations that are most informative, thereby improving the network's performance. After the CA module, a RepGhost module is employed to the features. Finally, the module adopts a residual structure where the input and output features are added to generate the output result. This residual structure enables the network to learn residual mappings and helps to prevent the problem of vanishing gradients, resulting in better network performance.
# Detecting Suicidal Ideations in Online Forums with Textual and Psycholinguistic Features
## 3 Materials and Methods
### Dataset  
In this study, we utilized the dataset created by [PERSON] et al. [19]. Each example consists of a unique identifier, post title, and body. This dataset does not include metadata such as the number of votes and comments that can be used as features. Therefore, the features were extracted from the available textual content. Any personal information such as a username was removed to protect the privacy of Reddit users. The dataset follows the binary annotation scheme and consists of 785 posts sourced from various subreddits: 175 were extracted from the r/SuicideWatch subreddit, 200 from r/Depression, 200 from r/Anxiety, and 210 from r/ShowerThoughts. Out of these extracted posts, 205 posts were labeled as suicidal and 580 posts as non-suicidal. The dataset exhibits class imbalance, which was addressed in this study through stratified sampling. This approach ensures that the training set reflects the ratio of suicidal and non-suicidal instances in the original dataset. We refrained from using undersampling, as it would result in a loss of data. Moreover, oversampling with synthetic examples was not employed to preserve the integrity of the information and the labels. Table 1 shows the distribution of the class labels in the dataset.  
This dataset was chosen since it was analyzed and annotated by experts in the mental health domain. Specifically, the annotation was carried out by two psychiatrists: The expert annotations ensure that every post labeled as suicidal genuinely reflects suicidal language. This, in turn, supports the clinical validity of the resulting models and strengthens the potential findings about the traits and behaviors of individuals with suicidal ideations.  
r/SuicideWatch is a forum where users share their suicidal thoughts and experiences and seek support. The researchers frequently use this subreddit to collect suicidal texts [9]. It is often regarded as a reliable and genuine source of suicide-related posts, since r/SuicideWatch is managed by moderators who remove any unrelated posts or any  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Subreddit** & \multicolumn{2}{c}{**Class**} & \multicolumn{1}{c}{**Total**} \\ \hline  & **Suicidal** & \multicolumn{2}{c}{**Non-Suicidal**} \\ \hline r/SuicideWatch & 150 & 25 & 175 \\ r/Depression & 48 & 152 & 200 \\ r/Anxiety & 7 & 193 & 200 \\ r/ShowerThoughts & 0 & 210 & 210 \\ \hline Total & 205 & 580 & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Distribution of the class labels in the dataset.  
content violating community guidelines, e.g., spam, abuse, or criticism. R/Depression and r/Anxiety are subcommunities of people discussing depression and anxiety, respectively, while the r/ShowerThoughts subforum is not related to mental health. On r/ShowerThoughts, the users share miscellaneous thoughts and insights. Table 2 exemplifies the snippets of posts from both classes.
Heat and Drought Have Exacerbated the Midday Depression Observed in a Subtropical Fir Forest by a Geostationary Satellite  
[PERSON]  
1 School of Geographic Sciences, Hunan Normal University, Changsha 410081, China; [EMAIL_ADDRESS]  
2 jia_luqun.edu.cn  
3 jia_luqun.edu.cn  
4  
[PERSON]  
1 School of Geographic Sciences, Hunan Normal University, Changsha 410081, China; [EMAIL_ADDRESS]  
2 jia_luqun.edu.cn  
3 jia_luqun.edu.  
the occurrence of midday depression [13; 14]. Furthermore, midday depression in plants is defined as the absence of an increase in carbon uptake with an increase in photosynthetically active radiation over the timescale of a day, leading to a decrease in productivity during the midday period [15]. Midday depression is a physiological phenomenon that plants have used to adapt to environmental stresses over a long period of evolution [16]. Although it regulates and protects the entire life cycle of plants, it comes at the cost of low energy utilization of sunlight at midday and temporary downregulation of physiological and biochemical activities in plants, leading to reduced carbon uptake and thus, lower photosynthetic yield [14; 17; 18], which can be reduced by 20 to 50 percent or more [19]. Therefore, the phenomenon of midday depression can be discerned by examining the Gross Primary Productivity (GPP) of plants, with the quantification of its impact on photosynthesis achieved through the analysis of characteristic daily fluctuations in GPP [20]. However, the meteorological conditions for the effect of midday depression on the daily fluctuations in GPP remain unclear based on observations of long-term positioning. Although advancements in remote sensing technologies and model simulations have rendered the high-resolution temporal simulation of GPP feasible in conjunction with remote sensing data [21; 22], the effects of high temperature and drought on midday and afternoon GPP inhibition are rarely analyzed on a finer timescale for several consecutive years. Negligence of critical responses may occur during coarser timescale analysis.  
In this study, we investigated the impact of climatic events on the midday depression of photosynthesis at a subtropical fir forest in Huitong, China. We used the photosynthetically active radiation data (ten minutes scale) from the Himawari 8 meteorological satellite in conjunction with ERA5-land data to estimate the GPP for this site from 2016 to 2022 and compared these estimates with the actual flux data measured using the eddy covariance technique at the site to verify the accuracy of the estimated GPP. Depending on the relevance between drought events and GPP fluctuations in the typical Chinese fir forest ecosystem, we hypothesize that drought events may increase the frequency of midday dormancy and thus reduce GPP in subtropical areas that have been stressed by summer drought for a long time. The purposes of this study are as follows: (1) to elucidate the intra-annual and inter-annual temporal characteristics and trends of midday depression; and (2) to estimate the impacts of various climatic events on the frequency of midday depression.
## 3 Experiments and Results
### Comparative Experiments
#### 3.2.3 Methodological Comparison and Discussion  
Compared to existing methods, our approach demonstrates significant advantages in complex anomaly reconstruction, background interference suppression, and small anomaly detection. The proposed MSAC achieves the collaborative modeling of global structures and local details through hierarchical feature fusion (21.1% AUC improvement), outperforming  
Figure 11: Anomaly detection visualization. (**a1,b1**) Histogram of the scores for both normal and abnormal test samples. (**a2,b2**) t-SNE visualization results. The horizontal (X) and vertical (Y) axes represent the dimensions of the reduced feature space (unitless) after applying t-SNE. In the figure, the pink and blue points represent the projected distributions of abnormal and normal samples in the feature space, respectively.  
GANomaly (F1: 69.9%) and f-AnoGAN (F1: 71.4%) with their single-scale reconstruction mechanisms. While MemAE (F1: 78.5%) exhibits limitations in complex rail environments due to its fixed prototype memory bank, the CASE reduces false positives by 37% through background noise suppression. For small-image area anomalies, the enhanced discriminator with E-JPU achieves 94.7% AUC via pyramid feature preservation and multi-dilated convolutions (dilation rates of 1, 2, 3, 4), surpassing SQUID (87.2% AUC) and validating the effectiveness of cross-scale fine-grained feature aggregation.
## 2 Materials and Methods
### Digital Twin of GPR Antenna  
Due to technical limitations, achieving a perfect match between computer-generated data and real system data is fundamentally impossible, leading to a discrepancy referred to as domain gap, which poses a significant challenge in the use of computer-generated data for training learning algorithms. In this work, the AM200 antenna system by IDS GeoRadar s.r.l. (Pisa, Italy) was utilized, and to enhance the transferability between these domains, a digital twin of the system was developed. This development employed Taguchi optimization, a methodology documented by [PERSON] and [PERSON] [13].  
Initially, the gprMax simulation environment was used to generically replicate the core components of the antenna and the experimental setups, with the determination of  
Figure 1: Working principle of ground-penetrating radar (GPR): Electromagnetic waves are partially transmitted and reflected at layer boundaries (**a**). Multiple individual measurements (**b**) are compiled into a two-dimensional representation (**c**), resulting in a B-Scan (**d**).  
Figure 2: The main components of the architecture of the developed methodology.  
their properties being the subsequent step. Reference measurements were then conducted by using the selected GPR system, focusing on measuring the antenna crosstalk and the reflection on a metal sheet. The measurement of antenna crosstalk, which is the signal that travels directly from the transmitting antenna to the receiving one, was carried out in a dedicated antenna laboratory to minimize interference, as illustrated in Figure 3a. The choice of metal sheet reflection as a measurement parameter was due to its high replicability in the simulation environment and the setup for measurement, which is depicted in Figure 3b.  
Through the application of an iterative optimization algorithm, an optimal combination of parameters was established. Consequently, the developed model not only captures the geometric details of the antenna system but also incorporates its essential physical properties, which is crucial to simulating electromagnetic wave propagation. While the information obtained may not cover the entire complexity of the antenna system, comparative measurements, as depicted in Figure 4, demonstrate a close correspondence between the actual antenna used and its digital twin.
## 4 Discussion  
In the case for the cladding-pumped SC generation, the pump light was coupled into a superposition of the core-guided mode and the fundamental cladding mode of the fiber since the input coupling mechanisms did not allow much freedom to select other desired modes. The selection of other superpositions was difficult to achieve and the resulting spatial output pattern of the pump was very stable over the course of the measurements once the pump's launching conditions were set. It is believed that the lowest-order cladding mode, shown in Figure 3c, was mostly excited due to the comparable intensity profile of the measured mode with the calculated mode. The CM\({}_{0,1}\) mode also maintained a flat phase profile that would match that of the pump laser near its focus. Both the spatial position of the pump, as well as the pump angle relative to the face of the fiber, were adjusted to produce the widest spectrum on the output. The blue, solid curve in Figure 5 shows the power spectral density for the same pump powers as in the core-pumped damage-limited case. Notice that the SC generation spectrum does not extend as far into the visible in the cladding-pumped case vs the core-pumped case under similar pump powers because the spatial mode size for the cladding-pumped mode is larger and the nonlinearity is therefore lower. However, due to the increased pump area in the cladding mode scenario, much higher pump powers were achieved before the fiber was damaged and a much brighter SC was produced (green solid curve in Figure 5). The spectral power density in the high-power cladding-pumped case showed a much larger SC generation in the visible regime most likely due to the large number of modes which are phase matched to the pump mode. The dynamics of SC generation did not follow the pump in the spatial pattern but they were influenced strongly by it. This is probably an effect of four-wave mixing, which allows for intermodal mixing at certain wavelengths if the phase velocity of the modes is similar; however, this is only speculation at the moment. Considering Figure 6c-d, the generated light follows the intensity distribution of the pump light, shown in Figure 2c, but when the generated light reaches shorter wavelengths, the spatial pattern becomes more spatially dispersed and at 550 nm there seems to be a transition to a more chaotic mode pattern.
# Interference Alignment for Cognitive Radio Communications and Networks: A Survey
## 6 Open Research Challenges
### Practical Implementation of IA in CR Networks  
Inadequate diversity of interference channels can possibly limit the relativity of the alignment. For instance, in the case where each CR has a single antenna and all channels are persistent across both time and frequency, the diversity of channels becomes limited. An open research problem is a practical achievable technique, which entails finite dimensions for the case of multiple non-intendedreceivers [134]. Hence, exploring innovative techniques for the optimization of linear precoders and alignment filters aimed at maximizing the sum-rate in low and moderate SNR regions is a vital future research challenge for practical implementation of IA in CR networks.