esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 TSN Network-Wide Scheduling--Approaches Overview, Challenges, and Future Directions
### Literature Analysis
#### 4.2.2 Diversity of Approaches  
Early works were mostly inspired by related fields such as TT-Ethernet and adapted solutions to make them work for TSN by, e.g., changing problem formulation constraints. More recently, solution approaches are becoming more diverse in applied techniques to solve the problem as well as in the use cases where TSN is applied. Figure 4 shows the number of related works on the y-axis for each given year. As can be seen, early works used mostly ILP and SMT problem formulations. However, starting in 2018, the number of heuristics and metaheuristics started to increase as researchers have been obtaining a better understanding of the problem. Approximative solution approaches (according to Figure 2) are interesting because they can provide reasonably good solutions in a shorter time than exact methods. As we will discuss later, algorithm runtime is an important metric when evaluating a given approach.  
We also notice in the last two years the use of constraint programming (CP)- and artificial intelligence (AI)-based methods to solve the scheduling problem. Reinforcement learning (RL) specifically seems a promising approach as such an approach can automatically learn optimal policies that fit the network topology and stream characteristics. However, there are several challenges when using AI-based methods. First, dealing with hard constraints is still  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Application Area** & **TSN Profile** & **Applicable Algorithms** \\ \hline
5 Gs Fronthaul/Xhaul & IEEE802.1 CM/de & [63] \\ \hline Industrial automation & IEC/IEEE 60802 & All with few exceptions \\ \hline Automotive & IEEE P802.1 DG & [29, 30, 34, 51, 59, 60, 80, 81, 95, 99, 101, 104, 106, 110, 111] \\ \hline Aerospace & IEEE P802.1 DP/SAE AS6675 & None \\ \hline Service provider & P802.1 DF & \\ \hline Audio video bridging & 802.1 BA & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Scheduling algorithm and TSN profile per application area.  
Figure 4: Evolution of approaches per year.  
challenging when using, e.g., deep reinforcement learning. Second, finding solutions that are robust to deviations in the input (such as nondeterministic switch behavior or end-host jitter) complicates the problem further. Finally, generalizing solutions learned for one set of streams to a different scenario remains an open challenge. Here, recent works in the area of neural combinatorial optimization (NCO) techniques could be interesting candidates to find robust network-wide schedules that can deal with hard constraints.
## 2 Methods
### Observational Data  
A Doppler lidar wind profiler (LeoSphere Windcube 100S, Leosphere, France) with high spatial resolution (\(\leq\)25 m) and temporal resolution (25 s) was used in the data assimilation system of the WRF model. The 134 AWSs in southern Taiwan (Figure 1) provided surface measurements of pressure, wind direction, wind speed, and precipitation. The wind information from 134 AWSs was adopted to understand the environment fields of the event day. The 12-h accumulated rainfall measurements from the 134 AWSs were analyzed and compared with model simulations with or without data assimilation of the lidar wind profiler at Pingtung Airport. Composite radar reflectivity maps were obtained from the Taiwan Central Weather Bureau (CWB; [[https://www.cwb.gov.tw/V8/C/W/OBS_Radar.html](https://www.cwb.gov.tw/V8/C/W/OBS_Radar.html)]([https://www.cwb.gov.tw/V8/C/W/OBS_Radar.html](https://www.cwb.gov.tw/V8/C/W/OBS_Radar.html)), accessed on 22 December 2021).  
Before assimilation in the WRF model, the data of wind profiler with high vertical resolution were processed by two steps: (1) quality control and; (2) vertical thinning of profile data. Firstly, a quality control method of Ref. [37] was performed on wind profile data. Wind data were eliminated as the wind speed measurements associated with a Carrier-to-Noise Ratio's outside the range of \(-25\) to \(5\) dB. Secondly, observations of the wind profiler were thinning as the data closed to the model vertical levels. This step provided help in reducing the negative impacts due to vertical correlation occurring in high-density observations [27; 28]. After the quality control and vertical thinning of wind profiler data at Pingtung Airport, the winds were separated into u (east-west direction) and v (north-south direction) components, and incorporated into model simulated data. Abnormal winds in Figure 2a were not found in Figure 2b, implying better data quality in the thinning profile than in the initial profile.  
A manually operated surface meteorological station in Pingtung (Figure 1) is also located in Pingtung Airport. To assess the effect of ATs near Pingtung Airport on the event day, hourly visibility and precipitation from the Pingtung station and hourly surface pressure and precipitation from the Cengwen, Yuemei, and Yanpu stations (Figure 1) were used. The last three stations, located in southern Taiwan in the cities of Tainan, Kaohsiung, and Pingtung, respectively, were selected as they recorded the most extreme 6-h accumulated precipitation during the event day.
## 4 Experiments
### Experimental Setup  
We set the resolution of the image input to 32 \(\times\) 128, with a batch size of 224, and conducted 20 training epochs. In the initial stage, we chose Adam [56] as the optimizer and used OneCycleLR to adjust the learning rate. After completing the training for the first 14 batches, we replaced OneCycleLR with Stochastic Weight Average (SWA). The batch size for all methods in the experiment is fixed at 224 with a training batch count of 20. All experiments were conducted in an environment with 6 NVIDIA Tesla V100 GPUs, utilizing Python 3.9.18 and Torch 1.13.1. The parameter settings for different methods in the experiment are outlined in Table 1.  
This article considers word accuracy the primary metric for measuring scene text recognition performance. The character set used in this paper includes 33 Uyghur characters, as shown in Figure 5.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Models** & **Optimizer** & **lr** & **Image\_Size** & **Patch\_Size** & **En\_Layer** & **De\_Layer** \\ \hline CRNN & Adam & \(5.1\times 10^{-4}\) & [32; 128] & – & – & – \\ TRBA & Adam & \(6.9\times 10^{-4}\) & [32; 128] & – & – & – \\ ViTSTR & Adam & \(8.9\times 10^{-4}\) & [224; 224] & [16; 16] & 12 & – \\ PARSeq & Adam & \(7.0\times 10^{-4}\) & [32; 128] & [4; 8] & 12 & 1 \\ CDistNet & Adam & \(4.0\times 10^{-4}\) & [32; 128] & – & 3 & 3 \\ MGP-tiny-char & Adadelta & 1 & [32; 128] & [4; 4] & 12 & – \\ \hline CEM(ours) & Adam & \(7.0\times 10^{-4}\) & [32; 128] & [4; 8] & 6 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experimental parameter configuration. En_layer represents the number of encoder layers, and De_layer represents the number of decoder layers.  
Figure 4: Examples of augmented images.
## 3 Experiments and Results Analysis
### Evaluation Criteria  
To evaluate the performance of the proposed model, the mean absolute percentage error (MAPE), root mean square error (RMSE) and R-squared (R\({}^{2}\)) were selected as evaluation indices. These statistical metrics are defined as follows:  
\[\text{MAPE}=\frac{1}{N}\sum_{t=1}^{N}\left|\frac{y_{t}-\hat{y}_{t}}{y_{t}}\right| \tag{23}\]  
\[\text{RMSE}=\sqrt{\frac{\sum_{t=1}^{N}(y_{t}-\hat{y}_{t})^{2}}{N}} \tag{24}\]  
\[\text{R}^{2}=1-\frac{\sum_{i=1}^{n}(y_{t}-\hat{y}_{t})^{2}}{\sum_{i=1}^{n}(y_{ t}-y^{2})^{2}} \tag{25}\]  
where \(N\) is the number of samples, and \(y_{t}\) and \(\hat{y}_{t}\) represent the actual value and the predicted value, respectively.
## 3 Results
### Microsurfacing Test Results  
#### 3.3.1 Preliminary Design of Microsurfacing Mixtures  
Several preliminary tests were performed for each microsurfacing mixture with two test repetitions per composition to determine the initial amounts of added water and cement. According to a previous study by RILEM TC 280-CBE, asphalt emulsion was fixed at 12% for all mixtures to estimate the starting percentages of added water and cement for performance testing. The results obtained at this stage for the mixtures produced with both asphalt emulsions are presented in the following paragraphs.  
The first microsurfacing mixture produced with asphalt Emulsion 1 used 10% water and 2.0% cement. This mixture showed poor workability, and molding the pizza and the ball was impossible. Then, the amount of cement was increased to 2.5%, allowing the pizza and ball samples to be shaped. However, the mixture still presented a dry aspect with a low consistency. Thus, a new mixture was prepared with 2.5% cement, increasing the amount of water to 11%. This composition presented improved consistency, fulfilling the expected results in both preliminary tests. The pizza cured after one hour, and the ball did not break after falling to the ground. Figure 9 shows the test samples of this final microsurfacing mixture with Emulsion 1.  
The first microsurfacing mixture produced with Emulsion 2 was based on the last composition studied for Emulsion 1, comprising 11% water and 2.5% cement. However, the water content was too high, delaying the pizza curing process. Thus, a new mixture was designed for Emulsion 2 with a lower water content (10%) and the same cement content (2.5%). This final mixture fulfilled the expected results in both preliminary tests: the pizza cured after one hour, and the ball did not break after falling from a 1.5 m height.
# Solving Multi-Document Summarization as an Orienteering Problem
## 1 Introduction  
Despite the availability of information today, users need tools that enable them to reach their desired content by automatically summarizing the important and relevant parts and discarding those that are similar. Text summarization, specifically multi-document text summarization (MDS), which creates a summary from a set of related documents, is a useful solution to the exponential growth of information on the Internet [1]. In more than half a century, several approaches have been used to automatically generate summaries, such as statistical and graph-based approaches. In addition, some summarization studies have followed a global selection approach of summary sentences whereby they are selected in a way that optimizes the overall score of the resulting summary. Studies in both global selection and graph-based approaches have achieved promising results (for more details, see Sections 2.4 and 2.6.)  
Motivated by the promising results of those studies, this paper proposes a novel graph-based MDS approach to produce extractive generic summaries that optimize information coverage objective. The summarization problem is reduced to an orienteering problem (OP), a variant of the traveling salesman problem (TSP) [2]. Different problems were modeled as an OP and many heuristics were proposed to approximate their solution [3, 4]. Reducing the MDS problem into OP enables obtaining the benefits from all these studies. The proposed approach is based on a swarm intelligence (SI) meta-heuristic--more specifically, an ant colony system (ACS) [5]--to find an approximate solution to MDS. ACS is a variant of ant colony optimization (ACO) algorithms which are considered among the best SI algorithms applied to TSP [5]. ACS was applied for single text summarization and short document summarization; however, to the best of our knowledge, it has not been studied for MDS.  
An MDS system, called MDS-OP, was implemented around the proposed solution. It was evaluated and tested on two benchmark corpora of DUC 2004 (Task 2) and multilingual multi-document summarization (MMS) task at MultiLing 2015, referred to as MultiLing 2015 (MMS task). Several performance evaluation metrics were used including ROUGE metrics [6], and AutoSummEG [7], MeMoG [8], and NPowER [9] methods. When compared to 26 rival systems, MDS-OP achieved the best F-measure scores on both corpora in terms of ROUGE-1, ROUGE-L (DUC 2004), and ROUGE-SU4 (MultiLing 2015).  
The remainder of this paper is arranged as follows. Section 2 briefly presents some related studies. Sections 3 and 4 describe OP and ACS, respectively. Section 5 describes the main steps of the proposed solution. Section 6 presents the experimental results. Finally, Section 7 concludes this study and outlines some future research directions.
# Heat Stress Affects H3K9 me3 Level at Human Alpha Satellite DNA Repeats
###### Abstract  
Satellite DNAs are tandemly repeated sequences preferentially assembled into large arrays within constitutive heterochromatin and their transcription is often activated by stress conditions, particularly by heat stress. Bioinformatic analyses of sequenced genomes however reveal single repeats or short arrays of satellite DNAs dispersed in the vicinity of genes within euchromatin. Here, we analyze transcription of a major human alpha satellite DNA upon heat stress and follow the dynamics of \"silent\" H3K9 me3 and \"active\" H3K4 me2/3 histone marks at dispersed euchromatic and tandemly arranged heterochromatic alpha repeats. The results show H3K9 me3 enrichment at alpha repeats upon heat stress, which correlates with the dynamics of alpha satellite DNA transcription activation, while no change in H3K4 me2/3 level is detected. Spreading of H3K9 me3 up to 1-2 kb from the insertion sites of the euchromatic alpha repeats is detected, revealing the alpha repeats as modulators of local chromatin structure. In addition, expression of genes containing alpha repeats within introns as well as of genes closest to the intergenic alpha repeats is downregulated upon heat stress. Further studies are necessary to reveal the possible contribution of H3K9 me3 enriched alpha repeats, in particular those located within introns, to the silencing of their associated genes.  
alpha satellite DNA; heterochromatin; euchromatin; transcription; heat stress; histone modification; epigenetics; gene silencing +
Footnote †: journal: Journal of the Royal Society Interface: Series A
# Harnessing the Potential of Emerging Technologies to Break Down Barriers in Tactical Communications
## 4 Use Cases
### Use Case 5: Electronic Warfare  
This scenario involves the utilization and manipulation of an adversary's electromagnetic spectrum, which includes actions like blocking or disrupting communications within that spectrum. It also encompasses intercepting, interrupting, and deciphering communications to gather intelligence from the enemy. With the increasing number of threats posed by adversaries, it has become imperative to cover the highest 5G frequencies (24-44 GHz) due to their expansive capacities and accelerated speeds.  
In this use case, it is crucial to emphasize the significance of blockchain technology, as it plays a central role in managing access and identity. This is essential for preventing potential breaches in communication security. Edge computing operates in a decentralized manner, positioning computation and data storage closer to where they are needed. This approach enhances response times and conserves bandwidth. The distributed characteristic helps the data to be more protected, more controlled, and that makes it more complicated for malicious access in electronic warfare. Through trusted computing, an external third party can trust the software running on your computer when your computer interacts with its server. This also helps in the validation and control of the data in a secure manner. Looking at the application layer, improving information transmission can be achieved through semantic communications for intruder detection and RIS to mitigate interference. SDR technology has become pivotal in communication during any combat operation, owing to its impressive performance and adaptability. This technology greatly bolsters electronic warfare with its multifaceted capabilities, including support for various waveforms, advanced cryptology, and heightened processing capabilities. This leads to superior real-time communication and decision making, all facilitated by a single radio.
## 3 Results and Discussion
### Effects of Water Micro-Reservoir in the Composite Membranes
This is supported by the increase in freezeable water content and the reduction in non-freezable water content in the N/n-HPS relative to the pristine Nafion membrane. The measured IEC values (Table 1) unveil not only the equilibrium accessibility to the pendant acid groups but also structural response in connection with the above assignment on hydrophilic channel. Both Nafion and N/n-HPS show the same IEC, implying no blockading action imposed by the n-HPS particles to the hydrophilic channels. Moreover, the composite membranes, N/c-HPS and N/s-HPS, showed IEC values of 0.82 and 0.88 mmol/g, respectively. The calculated value of IEC of N/s-HPS can be made using the measured IEC of Nafion membrane (0.75 mmol/g) and the measured equivalent mass of s-HPS (5.7 mmol/g) by the formula: \(0.5\%\times 5.7\) mmol/g \(+99.5\%\times 0.75\) mmol/g = 0.775 mmol/g. Obviously, this calculated value is well below the experimental IEC of N/s-HPS. This difference of \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Membrane** & **IEC** & **Water uptake** & **Melting** & **Freezable** & **Non Freezable** \\  & **(mmol/g)** & **(\%, 20 \({}^{\circ}\)C)** & **peak (\({}^{\circ}\)C)** & **water (\%)** & **water (\%)** \\ \hline Nafion & \(0.75\pm 0.01\) & \(28.9\pm 2.3\) & \(-22.0\) & \(13.8\) & \(15.1\) \\ N/n-HPS & \(0.75\pm 0.03\) & \(30.1\pm 2.2\) & \(-9.37\) & \(18.9\) & \(11.2\) \\ N/c-HPS & \(0.82\pm 0.02\) & \(32.5\pm 2.1\) & \(-10.7\) & \(20.2\) & \(13.3\) \\ N/s-HPS & \(0.88\pm 0.06\) & \(40.0\pm 3.3\) & \(-15.2\) & \(26.7\) & \(13.3\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Hydrophilic properties of Nafion and the composite membranes. Figure 6: Differential Scanning Calorimetry (DSC) investigation on the condensed state of water in various membranes. about 13.5% validates the role of s-HPS particles in broadening hydrophilic channel, which opened accessibility of those dead ends in the pristine Nafion matrix. A similar discrepancy also existed in N/c-HPS. In addition, the difference in IEC between N/s-HPS and N/c-HPS is 0.06 mmol/g, a far greater discrepancy than that between s-HPS and c-HPS (_i.e._, 0.0045 mmol/g). As found previously, the IEC value is largely affected by a strong acid rather than a weak acid [42].
## 1 Introduction
As the preceding review shows, the time-differenced carrier phase (TDCP) technique is selected to combine the single frequency GPS + BDS for fixing cycle slips, which consists in differencing successive carrier phases. It can eliminate the constant integer ambiguities, inner-system bias (ISB) and most of the common mode errors, which vary slowly within a short period of time like 1 s [21], and obtain precise position change at the millimeter level [22]. Compared to existing geometry-based methods, this paper offers several major contributions: (1) improved local analysis method (ILAM) is proposed and applied in time-differenced carrier phase (TDCP) algorithm to detect cycle slip. The method can effectively detect the number of cycle slips and the corresponding satellites. As the increase of the number of satellites in multi-constellation, detectable cycle slips number is more; (2) success probability and decimal test are utilized for cycle slips validation. The non-integer outilies can be detected, which avoids the error repairs and improves the reliability. The experiment based on GPS + BDS proves the effectiveness and the advantages in multi-constellation. The following section first describes the TDCP algorithm and then gives a detailed description of cycle slips detection with ILAM and repair by rounding with validation. In the subsequent section, the proposed method is verified with real receiver data and simulated cycle slips, and the conclusions follow.
# Study on the Wellbore Flow for Carbon Dioxide Fracturing
## 4 Results and Discussion
### Model Validation and Wellbore Temperature-Pressure Distribution  
The measured bottom hole temperature decreases with the injection of CO\({}_{2}\) as shown in Figure 4. In order to verify the reliability of the model, the data point with an injection time of 2 h is chosen. The displacement of CO\({}_{2}\) is 4 m\({}^{3}\)/min and the injection temperature and pressure are 258 K and 26.21 MPa, respectively. The measured and calculated values of bottom hole temperature and pressure are displayed in Table 2, while the errors are within 1%, which proves the rationality of wellbore temperature and pressure calculation.  
Previous studies have shown that displacement [27] is the key factor affecting temperature and pressure of CO\({}_{2}\) in the wellbore. The calculations of wellbore temperature and pressure distributions under difference displacement are shown in Figures 5 and 6.  
The pressure distribution in the wellbore under different displacement can be seen in Figure 5. It can be seen that the wellbore pressure increases linearly with well depth increasing, while pressure gradient increases first and then decreases with the increase of CO\({}_{2}\) displacement; as demonstrated in Figure 7, the bottom hole pressure increases first and then decreases with displacement increasing. This is because wellbore pressure is affected by both the gravity head and the flow friction. With the  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \(\mathbf{Q}\) **(m\({}^{3}\)/min)** & **Comparison Items** & **Measured Values** & **Calculated Values** & **Error (\%)** \\ \hline \multirow{2}{*}{4.0} & Bottom hole temperature (K) & 288.75 & 287.10 & 0.57 \\  & Bottom hole pressure (MPa) & 52.81 & 53.22 & 0.78 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Model validation of wellbore flow model (injection pressure is 26.21 MPa).  
Figure 5: Pressure distribution under different displacement.  
Figure 6: Temperature distribution under different displacement.  
CO\({}_{2}\) density and viscosity profiles are illustrated by Figures 9 and 10. It can be seen from the diagrams that the trends of the density and viscosity of CO\({}_{2}\) in the wellbore are matching. The density and viscosity of CO\({}_{2}\) both tend to rise first and then reduce along the flow direction under different displacement, and the density and viscosity under the displacement of 1.5 m\({}^{3}\)/min are lower than those under the displacement of 4.5 m\({}^{3}\)/min. This is related to the undulation of heat exchange and flow friction caused by displacement increasing.