esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion  
Modern oil paintings have a complex composition, with a mixture of inorganic and organic materials [30]. For these reasons, the choice of the best method for controlling painting biodeterioration is critical for successfully treating contaminated artworks. Biocidal treatments are usually employed for controlling microbial growth and their efficacy as well as their drawbacks have been widely discussed in literature [3]. One of the well-knowndrawbacks is the difficulty in applying antimicrobial compounds without damaging the pictorial layers [31; 32]. However, natural products, such as essential oils and plant derivatives, due to their biocidal activity, represent a useful tool in the control of biodeterioration of cultural heritage, without negative environmental and human impacts.  
Previous studies reported that the major components of oregano EO are the terpen thymol and carvacrol [33], whereas the principal component of clove EO is eugenol [34]. The antimicrobial activity of oregano is mainly due to the presence of thymol and carvacrol. Actually, this activity is based on the molecular hydrophobicity of terpenes which promotes the partition of the EOs in the lipids of the cell membrane, leading to membrane permeabilization and leakage of cytoplasmic content [35]. Furthermore, thymol acts on fungi, modifying the morphology of the hyphae and causing their aggregation, with consequences on the diameter of the hyphae themselves and on the breakdown of the cell barrier [36]. Eugenol is an amphipathic hydroxyphenyl propene, active against fungi and a wide range of Gram-negative and Gram-positive bacteria [37]. The mechanisms of action are different and include changes in the morphology and disruption of the cytoplasmatic membrane, the production of Reactive Oxygen Species (ROS) and the inhibition of some essential enzymes, such as proteases, histidine carboxylases, amylases, and ATPases [37].  
In this framework, the aim of the study was to determine whether oregano and clove EOs could be applied in cleaning procedures for oil canvas paintings attacked by microorganisms. For the study, an oil canvas with a visible microbial attack was selected. Once the fungi and bacteria colonizing the canvas were identified, the isolates were exposed directly and indirectly to the selected EOs.  
The results showed that the biocidal effect of EOs' volatile components were effective on the isolates, suggesting their potential for possible application in a real cleaning procedure.
# Design of an SVM Classifier Assisted Intelligent Receiver for Reliable Optical Camera Communication
## 5 Experimental Results
### Classifier Performance  
We have classified accurate data transmitting region from all the possible captured LED regions detected by CNN using the trained SVM classifier. Based on the selected features, the SVM classifier provides an accurate LED region for demodulation. Thus, the other communication performances are greatly dependent on the classification that results in separated LED regions. Therefore, to evaluate classifier performance, we have shown the ROC curve for different kernel functions as shown in Figure 8. The communication distance and the exposure time \(T_{e}\) were set to 30 cm and 976.6 \(\upmu\)s, respectively. In addition, two LEDs have been used where one was data transmitting LED. The area measured under the ROC curve known as AUC is larger for the RBF kernel than others. Consequently, the classification accuracy is also larger for the RBF kernel.  
In Table 3, we have presented overall accuracy and measured AUC values considering the different kernels and no. of data transmitting LEDs. To evaluate classifier performance, one additional non-data transmitting LED has been used with the data transmitting LEDs for each case. During the experiment, for a certain number of image frames, we have calculated the amount of 'TRUE' data transmitting LED and amount of 'FALSE' data transmitting LED recognized by the classifier. We have also calculated the amount of 'TRUE' non-data transmitting LED and amount of 'FALSE' non-data transmitting LED. Later, we have calculated accuracy and AUC using programming in the Python 3.7 environment. The maximum accuracy is recorded as 94.92% for the RBF kernel and the lowest accuracy of 79.87% is achieved for the sigmoid kernel. Moreover, we have also given a bar plot to show the comparison among key performance parameters varying exposure time \(T_{e}\), while the amount of data transmitting LED was one, as shown in Figure 9. For the exposure time 976.6 \(\upmu\)s, all the performance indexes are high. However, the achieved performance has validated that our scheme is capable of recognizing accurate LED regions.  
Figure 8: ROC curve of SVM classifier for **(a)** RBF kernel; **(b)** linear kernel; **(c)** polynomial kernel; and **(d)** sigmoid kernel.  
Figure 9: Comparison among precision, recall, F1 score varying exposure time (\(T_{e}\)).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No. of Data Transmitting LED** & **Linear** & **RBF** & **Polynomial** & **Sigmoid** \\ \hline \multirow{3}{*}{One} & Accuracy & 92.09 & 94.92 & 89.45 & 80.93 \\ \cline{2-6}  & AUC & 0.89 & 0.94 & 0.87 & 0.79 \\ \hline \multirow{3}{*}{Two} & Accuracy & 90.05 & 93.10 & 87.91 & 81.36 \\ \cline{2-6}  & AUC & 0.85 & 0.91 & 0.83 & 0.81 \\ \hline \multirow{3}{*}{Three} & Accuracy & 87.76 & 89.91 & 88.13 & 79.87 \\ \cline{2-6}  & AUC & 0.84 & 0.88 & 0.85 & 0.77 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Classifier performance (accuracy and AUC) analysis with a different no. of LEDs.
# Effects of Parameters of Air-Avid Structure on the Salt-Frost Durability of Hardened Concrete
## 1 Introduction  
Deicing salt inducing salt-frost damage to road and bridge concrete in cold regions has been an important adverse factor for the durability of concrete structures. Earlier studies have pointed out that micro-air-void structures in concrete exert important effects on durability [1]. The osmotic hypothesis [2] proposed by [PERSON] and [PERSON] in 1953 further shows confirmation of how an air-void structure affects the frost resistance durability of concrete. Air entrainment has been proved to be an effective measure for improving the frost resistance and the salt-frost resistance of concrete. After air entrainment in the concrete, air voids are able to effectively buffer diverse stress generated in cement mortars, thus taking on the function as a buffer airbag [3]. The research of [PERSON] [4] shows that too high air content causes a less stable air-void structure and forms continuous air voids, raising the absorption amount of water during freezing and thawing, which is disadvantage to frost resistance. At present, air-void testing technology [5] has been gradually developed from a single index (i.e., air content of fresh concrete in the early stages into multi-index, such as air-void spacing factor and air-void specific surface area of hardened concrete currently). This also leads to in-depth researches on the salt-frost resistance of concrete. A number of studies [6; 7; 8] have found that the necessary condition to protect concrete from frost damage is not the air content, but, rather, a good air-void structure in hardened cement pastes, especially the air-void spacing factor. It is generally believed that concrete has good frost resistance when the air-void spacing factor is less than 0.25 mm. Previous studies [9; 10] also reveal that, except for air-void structures, surface conditions also have great effects on the salt-frost resistance of concrete. Even if the air-void spacing factor of the concrete is smaller than0.25 mm, salt-frost durability can be dramatically reduced if the surface performance of the concrete is attenuated in the process of plastering and usage. Furthermore, salt-frost durability of concrete under coupling effects in the load environment is different from that in a single environment [11]. This study mainly analyzed the air-void structure in concrete by using an air-void analyzer (AVA) and a tester for parameters of the air-void structure in hardened concrete, and discussed the influence laws of air content and parameters of the air-void structure on the salt-frost durability of concrete. In addition, in view of the salt-frost durability of concrete, control indexes (i.e., appropriate air content and air-void spacing factor) were put forward.
## 4 Numerical Results and Discussion
### Evolution of Transient Dynamic Response of Blade off
#### 4.2.1 Time-Domain Response Characteristics  
The time-domain responses at different nodes are respectively shown in Figures 10-12, and corresponding motion orbits are depicted in Figure 13. It can be seen that when the sudden unbalance is applied on the rotor, i.e., the blade off occurs at the moment \(t=0.05\) s, the amplitude of the transient response increases suddenly and quickly reaches a peak point, then oscillates downward within a certain time range, and finally decays to a stable value after several revolutions due to the damping existing in the system. Obviously, the system response finally presents a typical synchronous vibration state due to the large steady-state unbalance excitation remaining. Figures 10-12 also show that the tendency of the vibration amplitude at different positions over time is basically the same. The above-mentioned vibration amplitude  
Figure 9: Energy distribution corresponding to the first three modes. (**a**) First order. (**b**) Second order. (**c**) Third order.
# Training Tasks vs. Match Demands: Do Football Drills Replicate Worst-Case Scenarios?
###### Abstract
The progression and periodisation of training loads represent another critical component in ensuring that players are adequately prepared for the most physically demanding phases of match play [11]. Therefore, it is essential to consider peak physical demands when designing training sessions. Nonetheless, research has shown that relying solely on average values tends to lead to underestimation of the maximum demands encountered during competition. To overcome this limitation, an alternative approach has been adopted that focuses on identifying the periods within a match when the highest physical demands for each variable occur. This approach is commonly referred to as \"worst-case scenarios\" (WCSs) [12]. Identifying these WCSs enables the optimisation and individualisation of training loads, supporting more precise and demand-specific planning for competitive performance [13; 14]. Initial analyses of worst-case scenarios (WCSs) relied on fixed-length time windows, segmenting the match into uniform intervals from start to finish--for example, one-minute periods such as 0:00-0:59, 1:00-1:59, and so forth until the end of the match. However, contemporary approaches have shifted toward the use of rolling averages, which identify the specific time frames during which peak intensities occur. For instance, the highest distance covered may be observed between 15:25 and 16:25, while the peak sprinting effort might occur between 24:49 and 25:49, with similar patterns emerging across other performance variables [15]. While WCS are commonly analysed over durations of 1, 3, 5, or 10 min [16], focusing on the 1 min WCSs during training sessions may be particularly useful for preparing players to meet the peak physical demands encountered in competitive match play [17]. The primary aim of this comparative and longitudinal study is to determine which types of training tasks best replicate the physical demands of WCSs observed in official matches within a one-minute time window. Specifically, the study analyses and compares six external load variables--total distance (DIST TOTAL), high-speed running distance (>21 km/h; DIST 21), sprint distance (>24 km/h; DIST 24), high-intensity accelerations (ACCs), high-intensity accelerations (DECs), and high metabolic load distance (HMLD)--across different training tasks and playing positions. We hypothesise that certain training tasks, particularly those with reduced pitch size and specific constraints (e.g., small-sided games), will replicate worst-case scenario demands more accurately than others, especially in terms of DIST 21, DIST 24, and HMLD. Moreover, we expect that the degree of replication will differ significantly between playing positions, reflecting the positional specificity of physical demands.
# Transient Attitude Motion of TNS-0#2 Nanosatellite during Atmosphere Re-Entry
## 1 Introduction  
Passive attitude control systems are quite popular for nano, pico, and femto-satellites due to strict limitations in terms of mass, size, cost, and energy. These systems utilize natural magnetic, gravitational, or aerodynamic torques to provide the passive stabilization required for missions. Each type of passive stabilization provides different satellite attitudes. Gravitational torque aligns the minimum moment of inertia axis along the nadir direction. Magnetic torque provides tracking of the local geomagnetic field direction by the onboard magnetic dipole. Each type of passive attitude control system is effective on different altitudes. The ratio between the magnitudes of these major environmental torques changes as the satellite orbit evolves. This transforms into changes of the attitude motion regimes during a satellite's lifetime. These regimes of the passively controlled satellites have well-studied both theoretically and experimentally onboard a large number of satellites with gravitational [1; 2; 3; 4], magnetic [5; 6; 7; 8; 9; 10] and aerodynamic [11; 12; 13; 14; 15] control systems. The transient motion between the magnetic and aerodynamic attitude stabilization regimes during the orbit altitude degradation has not been investigated experimentally yet to the best of our knowledge. This is due to the extremely short time between the entering of the dense upper atmospheric layers and the satellite operation termination due to heating. Telemetry gathering is a difficult task for this period. Therefore, the sensor measurements necessary for the attitude motion reconstruction are rarely available for the last weeks of the satellite operation. Technological Nano Satellite TNS-0 #2 utilized GlobalStar antennas [16]as its main data transfer device. This provided frequent communication sessions even during the last days of the mission in the upper atmosphere.  
The nominal satellite attitude was a passive magnetic stabilization. The longitudinal axis of the satellite was approximately directed along the local geomagnetic induction vector with a deviation no greater than 12 degrees. The satellite had a relatively elongated geometry with significant displacement between the centers of mass and pressure. The influence of the aerodynamic torque rapidly increased as the satellite entered the dense layers of the atmosphere. On 10 August 2019, the magnetic stabilization changed to an almost chaotic motion with a high angular velocity. Aerodynamic stabilization was achieved in about two weeks. This motion was maintained until its breakdown in the atmosphere on 6 September 2019. Chaotic tumbling was observed during the breakdown.  
The structure of the paper is as follows. First, the TNS-0 #2 description is presented. Then, the attitude motion equations (taking into account the magnetic and aerodynamic torques) are provided and a short explanation of the motion reconstruction technique is given. This technique is then applied to process the telemetry received during the magnetic stabilization, transient motion, and aerodynamic stabilization.
## 2 Materials and Methods
### Gas Adsorption Measurement  
The adsorption isotherms of the tested gases were measured using the volumetric method. The adsorption of pure gas in the prepared materials was measured using a simple apparatus shown in Figure 2 constructed in our laboratory.  
The thermostated part of the apparatus consisted of two chambers with calibrated volumes, \(V_{1}\) and \(V_{2}\), separated by a valve. The pressure in the apparatus was measured  
Figure 2: Design and schema of the experimental apparatus for gas adsorption capacity measurement.  
using a pressure transducer. A heated box maintains a constant temperature of the entire system during the absorption experiment.  
Before the experiment, a weighed amount of the sample was placed in the adsorption chamber, \(V_{2}\). First, to remove dissolved gases and impurities, the apparatus chambers were evacuated at least 5 h at temperature 80 \({}^{\circ}\)C. Subsequently, the system temperature was set to the thermostat at the required experimental value. Chamber \(V_{2}\) was closed, while volume \(V_{1}\) was filled with the studied gas at the desired pressure \(p_{1}\) (from zero to approximately 400 kPa). At the start of the sorption measurement, volumes \(V_{1}\) and \(V_{2}\) were connected, and the pressure inside the apparatus was monitored by a computer. The pressure initially dropped immediately to a certain value because of the interconnection of the chambers. Subsequently, the pressure decreased further, albeit more slowly, owing to the adsorption of gas in the sample material. The time required to attain equilibrium was approximately 3 h.  
The amount of gas adsorbed in the material was calculated from the balance as the difference between the initial and equilibrium amounts of gas in the system:  
\[N_{(adsorbed)}=N_{(gas\ initially)}-N_{(rest\ gas\ in\ equilibrium)} \tag{1}\]  
\[N_{(adsorbed)}=\frac{p_{1}V_{1}-p_{eq}(V_{1}+V_{2}-V_{x})}{RT} \tag{2}\]  
The ideal gas state Equation (3) is used for the moles in the gas-phase calculation (\(N\) gas mole number):  
\[N=\frac{pV}{RT} \tag{3}\]  
The adsorbed amount is related to the material weight \(m\) to determine the adsorbed phase concentration \(q\):  
\[q=\frac{N_{(adsorbed)}}{m} \tag{4}\]
## 5 Energy Result Analysis and Reliability Evaluation
### Reliability Evaluation  
Based on the above analysis, the transferred energies measured by the aluminum honeycomb and pin-rod devices were used as the performance parameters for the reliability evaluation of the pin puller.  
According to Section 4.1, the required energy or the lower specification limit of the pin puller is \(L=12.411\) J. From the measurement results in Section 4.2, it can be seen that the average value of the transferred energy measured by the aluminum honeycomb device is \(\overline{X}_{1}=125.183\) J and the standard deviation is \(S_{1}=13.626\) J, while the average value of the transferred energy measured by the pin-rod device is \(\overline{X}_{2}=197.917\) J with the standard deviation of \(S_{2}=19.493\) J.  
The \(K\) factors can be calculated as:  
\[K_{1} =\left(125.183-12.411\right)/13.626=8.276K_{2} =\left(197.917-12.411\right)/19.493 = 9.517\]  
The sample sizes of the two tests are \(N_{1}=11\) and \(N_{2}=18\), respectively. Substituting \(N\) and \(K\) into the Equation (6), the reliability of the pin puller can be obtained as:  
\[R_{1}=t_{1}\Bigg{(}\sqrt{\frac{11}{12}}\times 8.276\Bigg{)}=\ \ 0.9999935986\ \ R_{2}=t_{1}\Bigg{(}\sqrt{\frac{18}{19}}\times 9.517 \Bigg{)}=\ \ 0.9999999765\]  
Regarding the above reliability as the lower confidence limit of the reliability of the pin puller, the corresponding confidence level can then be calculated as:  
\(\gamma_{1}=0.9845\), \(\gamma_{2}=0.9950\) It is obvious that the high reliability of the pin puller has been verified by the tests of two devices. Even if the aluminum honeycomb device provides a conservative evaluation, the reliability reached 0.9999935986 (with a confidence level of 0.9845), while the reliability reached up 0.9999999765 using the pin-rod device. Therefore, the pin puller can be reliably used in key missions in aerospace fields.
# Topic-Specific Emotion Mining Model for Online Comments
## 5 Conclusions  
In recent years, online shopping platforms have accumulated massive numbers of online comments regarding products. Topic-level emotion mining of online comments helps companies and consumers to fully grasp the emotional state of purchasers on all aspects of products, which can effectively guide them to formulate marketing strategies and make consumption decisions. Different from the traditional topic model, this paper proposed a Topic-Specific Emotion Mining Model involving timestamps, aspects, and opinions, which considered the connections between words to better represent the comments. Our model, proven by the experimental results, is able to reduce computation time, improve the accuracy of topic-level emotional classification, and has highly semantic results for human understanding.  
Our main conclusions can be stated as follows:  
1. Since each comment was described as a bag of aspect-opinion pairs by including interword relationships, our model implemented the reduced-dimensional representation of comments, which greatly cut computation time.
2. The Topic-Specific Emotion Mining model constrains words' emotion and topic by adding interword relationships to improve the accuracy of sentiment classification at the topic level. Meanwhile, the number of topics in our model that are adaptively determined by calculating perplexity has also improved the emotion accuracy of the topic level.
3. In comparison with the output of the mainstream emotional topic models, our model containing rich semantic information is more interpretable.  
The next step is to apply our model to the topic-level emotion mining for various online products. Certainly, our model is applicable to all kinds of data besides our experimental dataset. At present, our method is based on the characteristics of online comments and takes aspect-opinion pairs as the input of the model. The main application area is Chinese online comment emotion mining. The method we have proposed needs to be improved in the following two aspects. Firstly, optimization of the extraction method of aspect-opinion pairs is necessary, and secondly, the scope of application of the model needs to be extended. In the future, we can consider the dependency relationship between words in sentences and use dependency parsing to optimize the extraction of aspect-opinion pairs. For texts in other fields, we should specifically analyze text features and incorporate appropriate interword relations in order to obtain the most accurate results of emotional mining in more fields. By doing so, we can extend the application scope of the model.  
Conceptualization, Y.Y.; Methodology, Y.Y.; Supervision, X.L.; Writing--original draft, Y.Y.  
The research work reported in this paper was supported in part by the National Science Foundation of China under grant NO. 91746203, 61471232 and 61625304. This work was jointly supported by the Shanghai Science International Cooperation Project under grant NO.16550720400.  
The authors declare no conflict of interest.