esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experimental Results and Analysis
### Boundary Cell Simulation Experiments  
This paper further validates the method of this study using a larger [PERSON] circular experiment environment. The diameter of the circular experiment environment is 2 m and the rat also starts from the center of the experiment environment for the purposes of free exploration learning. The environmental plan diagram and the trajectory formed by the rat in completing the exploration are shown in Figure 9.  
Figure 8: Place cell response maps. (**a**) Place cells corrected by boundary cells. (**b**) Place cells uncorrected by boundary cells.  
Figure 10 shows the intercepted boundary cell discharge response plots at different times. It can be seen that as the rat explores the environmental boundary gradually and comprehensively, the number of activated boundary cells in response to the environmental boundary increases. Table 2 shows the correlation data between the number of activated boundary cells and the mean localization error at different times. It can be seen that the number of activated boundary cells tends to increase rapidly before 1600 s, while after 1600 s, the number of activated boundary cells gradually slows down and stabilizes as the rat explores the environment more fully. At 1800 s, the activated boundary cells can adequately represent the environmental boundary and its number remains largely unchanged while the localization error is stable at about 0.037 m. It can be seen that the proposed method in this paper is also well adapted to larger circular environments.  
Figure 10: The boundary cell response maps at different times.  
Figure 9: The environmental plan diagram and rat trajectory map. (**a**) The environmental plan diagram. (**b**) The rat trajectory map.
# Aquasafe: A Remote Sensing, Web-Based Platform for the Support of Precision Fish Farming
## 2 Materials and Methods
### Indicators
Setting a general rule for the acceptable wind speed limits is a challenge due to the varying factors that need to be taken into consideration, such as the type of fish, the location of the farm, and the specific conditions of the farm. According to empirical rules, the authors established a threshold where wind speeds exceeding 15-20 knots (8-10 m/s) and wind gusts exceeding 25 knots (13 m/s) are considered dangerous for the fish farm [54]. By using the warning tool, farmers can take measures such as reducing the amount of feed given to the fish, which reduces oxygen demand and decreases stress on the fish, in order to prepare for and respond to high winds and gusts. Through monitoring and managing wind conditions, fish farmers can minimize the negative effects on both the fish and the farm infrastructure, ultimately contributing to the sustainability and profitability of the farm.
## 2 Materials and Methods
### Synthesis of Triphenyl Imidazole Derivatives
#### 2.3.2 ABTS Radical-Scavenging Assay  
For the determination of the ABTS radical cation (ABTS\({}^{+}\)) scavenging activity, we used our implementation of the [PERSON] et al. and [PERSON] et al. (2017, 2018) method. ABTS\({}^{+}\) was produced by reacting an ABTS stock solution (7 mM in water) with 2.45 mM potassium persulfate. The resulting mixture was kept at room temperature in the dark for 16-18 h before its use. Methanol was used to dilute the ABTS\({}^{+}\) solution (150 \(\mu\)L) to give an absorbance of 0.7 \(\pm\) 0.02 at 754 nm. This value was taken as the initial absorbance (A1). For each sample, aliquots were prepared mixing 980 \(\mu\)L of the ABTS\({}^{+}\) methanolic solution with 20 \(\mu\)L of the samples at diverse concentrations. Each mixture was stirred, incubated at room temperature for 7 min, and its absorbance was read (754 nm). This value was considered as the final absorbance (A2). To calculate the radical-scavenging activity as a percentage of ABTS decoloration, the employed formula was:  
\[\%\text{ of inhibition}=[(\text{A}_{1}-\text{A}_{2})/\text{A}_{1}]\times 100\]  
All determinations were performed in triplicate. Results were expressed as EC\({}_{50}\), which represents the required concentration to diminish the absorbance of ABTS by 50%. Quercetin was used as the reference compound.
# Application of a MEMS-Based TRNG in a Chaotic Stream Cipher
## 2 Stream Cipher Algorithm  
### Skew Tent Map  
Most of the chaotic systems only present chaos for a certain set of initial parameters while other initial parameters lead to a periodic behavior that is not suitable for secure applications. The set of parameters that produces a chaotic behavior is not usually within a continuous region and it is often unknown [11]. The Logistic Map, despite being used in many of the proposed chaotic cryptosystems [12; 13], presents this problem. As an example, a bifurcation diagram of the Logistic Map, which represents several consecutive values of the sequences \(x_{i}\) as a function of the chaotic  
Figure 1: Overview of the full cryptosystem, including a chaos-based stream cipher and a sensor-based seed generator.  
parameter \(\gamma\), is shown in Figure 2a. Most values of \(\gamma>3.57\) exhibit chaotic behavior but there are some regions in white where the system presents a periodic behavior. Moreover, even in the chaotic regions there exist an infinite number of initial conditions that lead to periodic cycles [14]. Several methods have been capable to find some of the periodic windows [15; 16], but the whole set of parameters that produces periodic windows remains unknown. Therefore, it can be difficult to define the key space in this type of systems.  
In our work, we based our encryption algorithm on a Skew Tent Map since it is one of the simplest chaotic systems with a continuous region where all the parameters are capable of generating a chaotic (non-periodic) sequence. The Skew Tent Map (Figure 2b) [17] is given by  
\[f(x_{i})=x_{i+1}=\left\{\begin{array}{ll}x_{i}/\gamma&x_{i}\in[0,\gamma]\\ (1-x_{i})/(1-\gamma)&x_{i}\in(\gamma,\ 1]\end{array}\right. \tag{1}\]  
where \(x_{0}\) is the initial value of the \(\{x_{i}\}\) sequence and \(\gamma,\ x_{0}\in(0,1)\). For any value of \(x_{0}\) and \(\gamma\), the map exhibits a chaotic behavior, which makes it a good choice for a cryptosystem. Moreover, this algorithm is quite simple although the division operation can be difficult to implement in some platforms such as FPGA. Therefore, we suggest that the values of \(1/\gamma\) and \(1/(1-\gamma)\) should be calculated and saved and the successive values of \(x_{i}\) should be obtained using multiplications instead.
# New Generation Compact Linear Accelerator for Low-Current, Low-Energy Multiple Applications
## 2 LINAC 7 Accelerator Component Descriptions
### Low Energy Beam Transport  
In order to match the beam that the ion source generates to the input requirements of the radiofrequency quadrupole (RFQ), a low energy beam transport (LEBT) is used. Like the ion source, this element is built and in use. It consists of two solenoids that are used to transform the divergent beam form from the source into the convergent one that the RFQ requires. The vacuum vessel consists of a custom-made six-way cross. Four limbs that are in the same plane have a nominal diameter of 100 mm, and have CF flanges on the ends. The other two limbs are of a 40 mm nominal diameter and have quickCF flanges on the ends. The DN 40 limbs are used as the beam pipe, and a solenoid fits over each one of them. Of the DN 100 branches, two are used for beam diagnostics, one for the turbomolecular pump that generates the vacuum for the ion source and the LEBT, and the last for a vacuum gauge and a vacuum switch. The entire setup can be seen in Figure 4; the left side shows  
Figure 3: Einzel lens for the ECR ion source for LINAC 7 being measured after final assembly using a Zeiss coordinate measuring machine at TEKNIKER.  
Figure 2: Off-resonance ECR ion source for LINAC 7.  
a photograph of the system and the right side a cross-section of the CAD model with the elements labeled.  
A Faraday cup and a pepperpot are used as beam diagnostics in the LEBT--both were custom designed and built for this LEBT. Their size is such that they can capture the entire beam when deployed and fit entirely inside their respective DN 100 branches when retracted so that they do not interfere with the beam during normal operation. Standard motorized vacuum positioners are used to position the diagnostics.
# Prediction of Freeway Traffic Breakdown Using Artificial Neural Networks
## 3 Data Description
### Temporal and Spatial Data  
The stationary sensors installed on the highway collect traffic information from the corresponding road segments. Previous research has demonstrated the temporal and spatial correlation of traffic conditions in adjacent roadway segments [11; 21]. Therefore, traffic data from upstream, downstream, and ramps, from current and previous time intervals, have been collected for each segment of the roadway. A universal symbol is used to represent the traffic data:  
\[\mathrm{x}_{t}^{i}\]  
where:  
* x are traffic data such as flow rate (q), average speed (v), or average occupancy (o).
* t is the timestamp. Since the data are aggregated into 5-min intervals, \(t-1\) indicates 5 min before the current timestamp t.
* i indicates the segment of the road. The available values can be upstream (up), current (curr), downstream (down), or on-ramp (ramp).  
Figure 1: Study site and sensor location.  
Figure 2: Traffic breakdown example (data collected at I-235 WB mile maker 7, on 5 February 2022).
## 3 Results and Discussion
### Correlational Interactions  
Most pollutants in the environment and food sources with similar point sources have the tendency to correlate in terms of observed concentrations [35]. Metal pollutants also tend to show collinearity, especially if the source is due to anthropogenic activities. The PCA diagram in Figure 2A shows that there were various strong correlations between certain metals. The PCA and the correlogram show that there was a strong correlation between the presence of Pb and the presence of Cd, implying that their existence in the tap water is probably due to the plumbing material. These correlational observations have been presented elsewhere [35; 45]. The elements with a chance of leaching from cookware (Zn, Al, and Fe) were also strongly correlated, as were K, Ca, and Mg. The association of Zn, Al, and Fe with K, Ca, and Mg could not be explained, but there is a possibility of solid salt accumulation in the brewing pots that eventually degrades during the prolonged brewing of the concoction. The metal correlations that existed for samples from each town are presented in the supplementary materials as Figure S1, while the sample correlations are given in Figure S2. The PCA in Figure 2B also shows that 70% of the Durban samples were correlated with tap water concentrations, while only 20% of the Johannesburg samples had a strong correlation with tap water samples. The grouped information using the Tukey method in relation to ANOVA (\(p\leq 0.05\)) showed that samples collected from Johannesburg had metal concentrations significantly higher than in samples from Durban, except for Na (Table 1). The maximum concentration recorded (170 mg L\({}^{-1}\)) was still within the South African guideline limits. The variation in samples based on the city where the samples were collected is essential in understanding the potential sources of the metals in the concoctions. Regarding the metals with concentrations that were significantly higher in the concoctions than in the tap water, there is a chance that the metals in the Johannesburg samples entered during the preparation process or due to the origins of the herbs. More studies are required to have a better understanding of the higher concentrations observed in the Johannesburg samples.
# Concerto: Dynamic Processor Scaling for Distributed Data Systems with Replication
## 4 Design of Concerto
### Overview  
Concerto as presented here takes advantage of the fact that performance constraints are disparate across instances in distributed systems. Master instances have a great impact on user-perceived performance and, thus, necessitate high data processing capabilities. In contrast, as replica instances act as a substitute for the original corresponding dataset in a sudden failure of the master, they scarcely affect the user experience during normal operations. Based on this property, we present the novel DVFS policy called Concerto,which deliberately scales down the processor speed when they are used to process replicas. This policy can allow for energy savings with a minimal loss of performance.  
The Concerto power manager configures the kernel to use the userspace governor to control the processor speed as the governor allows a user process to adjust the processor speed as needed. In our implementation, the power manager associates each instance with the specific core on deployment time and shares the information with them. When an instance starts running, it figures out whether it is a master or a replica in distributed data systems, and it sets the frequency of associated core accordingly by making use of the sysfs interface. The sysfs is the pseudo-file system interface provided by linux kernel to adjust the frequency of CPU. By writing the proper number into the virtual file (cpufreq/scaling_mad_freq) internally linked with the processor frequency modulator, the user applications sets the processor speed as desired. Once the processor frequency is all set, the instance sets its CPU affinity to the corresponding core using the sched_setaffinity library [38]. By doing so, Concerto executes the master for the core to run at full speed and the replica for the core to run at slow speed.  
This architecture makes sense because modern processors typically have several cores and allow separate adjustments of the P-state levels for each core. In this study, the fast cores for the masters run at the full speed (2.20 GHz), while the cores assigned to the replicas are forcefully scaled down to a lower speed (1.0 GHz). The Concerto power manager automatically detects dynamic changes of the processor speed and resets the processor affinity of the data nodes as necessary.
# Automatic Short Text Summarization Techniques in Social Media Platforms
## 1 Introduction
### Existing Surveys  
This section offers an overview of previous surveys related to automatic short text summarization (ASTS) and compares them to our survey. [PERSON] and [PERSON] conducted a survey on event detection-based methods for Twitter streams, categorizing the methods based on event type, detection task, and detection method while also outlining commonly used features [7]. However, their survey is restricted to event-based methods for tweet streams and lacks the comprehensiveness of our study.  
[PERSON] and [PERSON] conducted a survey that focused on summarization techniques for microblogs, specifically extracting situational information from disaster events on Twitter [8]. [PERSON] and [PERSON] also proposed a survey studying various techniques for event detection from microblogs, reviewing methods based on the utilized techniques, applications, and the detected elements (events or topics) [9].  
[PERSON] et al. presented a survey on topic-based summarization techniques, primarily concentrating on current automatic evaluation methods for summarization techniques in social media [10]. Similarly, [PERSON] et al. surveyed event-detection methods for online Twitter data, classifying the methods based on shared common traits [11].  
Additionally, [PERSON] et al. presented a comprehensive survey on current metrics used for summary evaluation, highlighting their limitations and proposing an automatic approach for evaluating metrics without relying on human annotation [12].  
The existing literature on ASTS has predominantly focused on Twitter, leaving other social media platforms with limited attention. However, this review paper aims to bridge this gap by presenting a comprehensive taxonomy of ASTS techniques across multiple platforms, including Twitter, Facebook, and Sina Weibo.
# Real-Time Penetration Recognition Based on Voltage Signal in K-TIG Welding
## 1 Introduction
A multi-sensor sensing system has been developed by [PERSON] et al. [25] for the collection of voltage, current, and arc sound signals. A unique frequency peak has been discovered at 2-4 kHz, and its physical significance has been analyzed, indicating that it is related to the oscillation of the molten pool. Oscillation modes in the oscillation frequency of the molten pool have been extracted based on the algorithm, and different welding states have been analyzed to determine the specific mode for full penetration. Experiments have shown that the oscillation frequency between partial penetration and complete penetration differs. The combination of the identified frequency band and the proposed algorithm can be conveniently utilized to identify weld penetration. This paper proposes a novel method for identifying complete joint penetration in K-TIG welding by extracting specific frequency band characteristics from the arc voltage signal. To establish an acquisition system for collecting voltage signals during the welding process, Section 2 presents the welding experiments. Section 3 then analyzes the physical significance of the feature frequency and presents the feature frequency. The intensity difference of the feature frequency signal between the incomplete joint penetration and complete joint penetration scenarios is distinct, thus enabling the determination of the weld penetration status to a certain extent. In Section 4, step-change speed experiments are conducted to validate the findings of Section 3. The results demonstrate the effectiveness of the proposed method for identifying complete joint penetration in K-TIG welding; specifically, the feature frequency analysis accurately distinguishes the penetration status. Finally, Section 5 presents the concluding remarks on the proposed method for identifying complete joint penetration in K-TIG welding based on the arc voltage signal. The experimental results show that the proposed method can effectively evaluate the welding quality and has the potential to be applied in practical production environments. The proposed method is a valuable contribution to the field of welding quality control, and further research could extend this method to other welding techniques and applications.
## 3 Results and Discussion
### Dual-Culture Assay  
Yeasts are known to inhibit various moulds through the production of diffusible metabolites. The five yeasts tested displayed varying levels of growth inhibition against the three _B. cinerea_ strains, indicating that inhibition effectiveness varies depending on both yeast species and fungal strain (Figure 5).  
_Aureohasidium melanogaster_ (Y6) was the most effective, demonstrating 55%, 52%, and 40% inhibition against _B. cinerea_ B05.10, IWBT-FF1, and PPRI 30807, respectively, whereas the commercial fungicide Captan achieved 57%, 41%, and 34% inhibition (Figure 5A-C). _Sulomyces pyralidae_ (Y63) ranked second, inhibiting _B. cinerea_ B05.10, IWBT-FF1, and PPRI 30807 by 56%, 38%, and 35%, respectively. _Meyerozyma guillermondii_ (Y88) inhibited _B. cinerea_ strains B05.10, IWBT-FF1, and PPRI 30807 by 53%, 43%, and 15%, respectively. The reference strain _P. kluyveri_ (Y64) showed limited inhibition with an average activity of 24% against the three _B. cinerea_ strains.  
The results of this study align with those of [PERSON] et al. (2013), who also reported _A. melanogaster_ inhibiting _B. cinerea_, although the yeast strain exhibited lower efficacy in their study compared to this one. Similarly, [PERSON] et al. (2017) reported that _A. melanogaster_ inhibited a different strain of _B. cinerea_ by 55% in vitro, supporting the findings of this study.  
Previous work by [PERSON] et al. (2018) reported 100% inhibition of _S. pyralidae_ on _B. cinerea_ spore germination, while [PERSON] et al. (2018) found 62% inhibition under in vitro conditions, suggesting that _S. pyralidae_ is more effective at preventing spore germination than controlling established mould growth. [PERSON] et al. (2018) and [PERSON] et al. (2018) also reported antifungal activity of _M. guilliermondii_ against _B. cinerea_. The reference strain _P. kluyveeri_ (Y64) showed low inhibition activity, which agrees with observations by [PERSON] et al. (2018) who noted its relatively weak antagonistic effect. The inhibitory effect of the highest performing yeasts, _A. melanogaster_, _S. pyralidae_, and _M. guilliermondii_, may be attributed to their production of cell wall-degrading enzymes (Table 1), and their ability to compete with _B. cinerea_ for nutrients and space.  
Figure 5: Growth inhibition activity (expressed as a percentage) of five yeasts (details listed in Table 2) and Captan (Cap), a commercial fungicide against _Botrytis cinerea_ B05.10 (**A**), IWBT-FF1 (**B**), and PPRI 30807 (**C**) using the dual-culture assay. Values are means of three replicates and the standard deviations are also shown. Different letters indicate significant differences (\(p\leq 0.05\)) between treatments. The plates of negative control treatments only contained the respective moulds and were the references for determining growth inhibition.
## 3 Results
### In-Orbit Results
#### 3.2.1 CPD Instrument
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**Spectrum** & **Epoch UTC** & \begin{tabular}{l} **Geographic Location of the** \\ **Satellite** \\ \end{tabular} & \begin{tabular}{l} **L-Shell** \\ **(McIlwain)** \\ \end{tabular} & \begin{tabular}{l} **Dose** \\ **[uGy/h]** \\ \end{tabular} & \
\begin{tabular}{l} **Rate** \\ **Dose Rate [rad/s]** \\ \end{tabular} &
\begin{tabular}{l} **Flux** \\ **[particles/cm\({}^{2}\)/s]** \\ \end{tabular} \\ \hline
1 & 08 November 2018 & Lat [deg]: 25.98 & & & & & \\  & 0425:55 & Lon [deg]: 132.67 & 1.144 & 1.93 & 5.444 \(\times\) 10\({}^{-8}\) & 0.33 \\  & 042:05 & Altitude [km]: 609.33 & & & & \\  & 12 November 2018 & Lat [deg]: 25.55 & & & & & \\  & 0506:50 & Lon [deg]: 123.09 & 1.206 & 2.66 & 7.389 \(\times\) 10\({}^{-8}\) & 0.39 \\  & 0506:50 & Altitude [km]: 608.41 & & & & \\  & 12 November 2018 & Lat [deg]: 27.16 & & & & \\  & 0507:29 & Altitude [km]: 607.76 & & & & \\  & 18 November 2018 & Lat [deg]: 26.04 & & & & \\  & 0433:53 & Lon [deg]: 130.75 & 1.143 & 2.79 & 7.750 \(\times\) 10\({}^{-8}\) & 0.26 \\  & 04:33:53 & Altitude [km]: 604.32 & & & & \\  & 18 November 2018 & Lat [deg]: 25.11 & & & & \\  & 04:34:08 & Lot [deg]: 130.53 & 1.129 & 0.92 & 2.556 \(\times\) 10\({}^{-8}\) & 0.23 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The Liulin spectra datasets obtained during real-time operations of the instrument. The measured dose rate and flux where obtained from a total exposition time of 15.286 \(\mathrm{s}\) for each spectrum dataset. Epoch is in UTC even though the operations were conducted using the Japanese Standard Time (IST).