esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Numerical Results
### Visibility and CO/CO\({}_{2}\) Concentration Variation Inside the Stand  
Visibility within a fire-affected space is determined by the concentration and opacity of smoke particles that absorb and scatter light. In the early stages of a fire, visibility is quickly reduced due to the accumulation of fine particles. Visibility is closely correlated with concentrations of carbon monoxide and dioxide, as high levels of these toxic gases inherently lead to very low visibility and thus hostile evacuation conditions for occupants.  
Figure 14 shows the distributions of oxygen (O\({}_{2}\)), carbon dioxide (CO\({}_{2}\)), and carbon monoxide (CO) concentrations within the simulated fire in the stand at times 720 and 1280 s. At T = 720 s, observations indicate a reduced O\({}_{2}\) concentration, below 12%, corresponding to the onset of an incomplete burning stage, where oxygen remains sufficient to support combustion reactions. This consumption of O\({}_{2}\) is reflected in elevated levels of CO\({}_{2}\) and CO, indicating a combustion cycle in which the incomplete burning of wood generates measurable levels of toxic gases.  
Considering the ventilated burning regime, well-defined evacuation flows reveal that hot gases are systematically discharged, initially favoring the maintenance of fuel combustion. However, at T = 1280 s, a partial recovery of O\({}_{2}\) concentration and a decrease in temperature are observed, correlated with reduced CO\({}_{2}\) and CO concentrations in the simulated space. This indicates that the fire is entering a stagnation/regression phase, driven by both the depletion of the fuel source and the oxygen necessary for sustained combustion.  
When comparing gas concentrations with the thermal distribution, a combustion dynamic influenced by the availability of oxygen is observed, where its reduction plays a crucial role in decreasing the intensity of the simulated fire.
# Feedback Devices for Cardiopulmonary Resuscitation: A Narrative Review
## 2 Classification of Feedback Devices for Cardiopulmonary Resuscitation
### Audio-Visual Feedback Devices
Moreover, the True-CPR device can enhance the proportion of full chest release during compression [18]. Research evaluating the use of the True-CPR device on a basic life support (BLS) ambulance in Barcelona showed that the device significantly improved the quality of chest compression performed by emergency technicians without increasing the time of the first defibrillation [19]. Corscience's Feedback Sensor Push (COR_CPR-RRB) is a sophisticated device for monitoring chest compression. It delivers precise measurements of compression depth and frequency, thereby enabling comprehensive data collection, analysis, and transfer. Notably,  
Figure 2: (**a**) Zoll Pocket CPR, (**b**) Cardio First AngelTM, (**c**) True-CPR, (**d**) Palm CPR feedback device. the device can be integrated with a host system, such as a defibrillator or monitor, further enhancing its utility [25]. Beauty, a device developed by Medical Feedback Technologies, offers real-time audio feedback regarding the efficacy of chest compression during the process of cardiopulmonary resuscitation (CPR) through the utilization of pressure sensors. This device serves as a guiding mechanism for medical professionals to precisely calibrate the depth of chest compression. Moreover, an audible alert is activated upon the achievement of a compression depth of 5 cm [26]. CPR-1100 CPR Assist, developed by [PERSON], presents chest compression depth and frequency information. This device employs orange lights to indicate the recommended compression frequency and blue lights to signify the desired compression depth. Furthermore, [PERSON]'s CPR-1100 CPR Assist establishes a Bluetooth connection with a computer for the purpose of recording the quality of chest compression. Moreover, CPR-1100 CPR Assist exhibits compatibility with defibrillators through a Bluetooth connection [27]. The Sunlife Palm CPR chest compression feedback meter, developed by China Suzhou Shangling Research, provides indicator lights on the top to give feedback on compression depth by quantity and color and feedback on compression rate by R light color. The Palm CPR is shown in Figure 2d. The device can connect to a mobile terminal to monitor, record, and provide real-time feedback on the quality of cardiopulmonary resuscitation, including the patient's physiological parameters and the rescuer's performance indicators. These data can be used for real-time resuscitation and quality improvement projects after resuscitation is completed in the system scale [28]. Studies have shown that Palm CPR has good consistency in average compression depth, moderate consistency in average frequency and depth compliance times, but poor consistency in rebound times [22].
## 4 Performance Evaluation and Discussion  
In this section, we start with the explanation of the proposed model's establishment where the necessary parameters including \(\{\alpha_{P},\alpha_{R},\alpha_{RP}\}\), \(\{\beta_{1},\beta_{2},\beta_{3}\}\) and \(\{\lambda_{1},\lambda_{2}\}\) are numerically determined. Afterward, we briefly present the evaluation and discuss the prediction performance of our model. The evaluation was two-fold. First, the prediction performance of the proposed model was quantitatively and qualitatively assessed on test videos in a specific database [12]. Second, a subjective test was conducted to evaluate how well the predicted cumulative QoE correlates with subjective cumulative evaluation at different moments of a streaming session. Finally, the complexity of the proposed model was also analyzed for real-time cumulative QoE prediction.
## Materials and Methods
### Data about City Variables  
Data depicting the variables of all 82 cities were obtained from the latest database of National Bureau of Statistics of China [26]. We employed city variables that were documented officially for all cities since the time of July 2019. As a result, four parameters (e.g., economy, public facility, habitation, and environments) were used in this study (Table 1). Economic parameters included government expenditure and resident income, which may affect financial status of local universities through tax investment at the national and local scales, respectively [27; 28]. Public facilities covered aspects of communication, transportation, health care, education, and regional culture, which were all related to university students [29; 30; 31]. Parameters of habitation included the aspects that reflected the socializing and life utilities, which were found to be closely related to perceived satisfaction at campus [2; 14]. Environment parameters (e.g., air pollution, water pollution, and garbage disposal) that may impact satisfaction under some given industrialization were extracted from databases of each local bureau [2; 13; 14; 15; 16].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Variables** & **Unit** & **Parameter** \\ \hline \multirow{4}{*}{Economy} & Yuan & GDP per capita \\ \cline{2-3}  & \(\times 10^{4}\) Yuan & Public financial expenditure \\ \cline{2-3}  & \(\times 10^{4}\) Yuan & Corporate profit of enterprises above designated scale 1  \\ \cline{2-3}  & Individuals & Population of employees of C\&T work-units 2  \\ \cline{2-3}  & Yuan & Average wage of enrolled employees of work-units \\ \hline \multirow{4}{*}{Public facility} & \(\times 10^{4}\) Households & Number of internet wideband accesses \\ \cline{2-3}  & Individuals & Real number of end-of-year taxicabs \\ \cline{2-3}  & Individuals & Numbers of hospitals and health-centers \\ \cline{2-3}  & Individuals & Number of regular institutions of higher education 3  \\ \cline{2-3}  & \(\times 10^{3}\) Individuals & Collection of books in public libraries \\ \hline \multirow{4}{*}{Habitation} & km\({}^{2}\) & Total area of residential lands \\ \cline{2-3}  & \(\times 10^{4}\) Individuals & End-of-year population of registered residents \\ \cline{2-3}  & ha & Total area of green space in C\&T parks \\ \cline{2-3}  & \(\times 10^{4}\) Tons & Domestic water consumption by residents \\ \cline{2-3}  & \(\times 10^{4}\) Kilowatt-hour & Electricity consumption of C\&T residents \\ \hline \hline \end{tabular}
\end{table}
Table 1: Specific parameters used in city variables about economy, public facility, habitation, and environment.
# Nanomaterials for the Abatement of Pharmaceuticals and Personal Care Products from Wastewater
## 4 Removal of PPCPs by Non-Conservative Methods Envisaging the Use of Nanomaterials
### Reaction with Nanoscale Zero Valent Iron  
In the last two decades, nanoscale zerovalent iron (NZVI) particles have been considered a promising nanomaterial to remove a wide range of contaminants including heavy metals, pesticides and chlorinated solvents from both groundwater and wastewater [57; 58; 59].  
Usually, NZVI particles are formed by a metallic iron core covered by an iron oxide/hydroxide shell. They are generally suspended in a colloidal dispersion and stabilized by a biopolymer [60; 61] or a surfactant and, thanks to the highly specific surface area, can degrade contaminants faster than (commercial) millimetric Fe\({}^{0}\). Several degradation pathways can occur at the surface of the NZVI, which generally lead to the reduction of the contaminant and the consumption and oxidation of the metallic core (Figure 8).  
Very recently, NZVI and commercial iron powder were applied during sludge anaerobic digestion for the removal of 19 different types of PPCPs. They showed good efficiency in the presence of chlorinated PPCPs, whereas no significant improvement was reported for the other types of PPCPs [62].  
Figure 8: Sketch of a core–shell iron based nanoparticle for water remediation.  
Even more recently, [PERSON] et al. have shown that NZVI with a sulfur based shell, (S-NZVI) is able to degrade florfenicol (FF), which is considered a target molecule for ABs. The removal efficiencies were good in groundwater, river water, seawater, and wastewater [63]. In their interesting system, the shell is formed by Fe\({}_{\mathrm{x}}\)S\({}_{\mathrm{y}}\), which has a higher affinity with the hydrophobic part -Cl and -F group on FF compared to the more hydrophilic iron oxides-hydroxides and also facilities electron transfer due to a lower bandgap than Fe\({}_{\mathrm{x}}\)O\({}_{\mathrm{y}}\).
# A Survey of Wi-Fi 6: Technologies, Advances, and Challenges
## 4 OFDMA in Wi-Fi 6
### Advances on the MAC Layer  
Wi-Fi 6 introduces OFDMA to synchronously transmit multiple flows over disjoint RUs. MAC mechanisms have to be adapted to support multiple transmissions in parallel. Wi-Fi 6 extends the MAC layer so that legacy devices are still supported. In the following,  
Figure 8: Preamble format in Wi-Fi 6 depends on the frame type.  
we first introduce the extensions of the RTS/CTS mechanism, detail downlink and uplink transmissions, and then elaborate on the integration of the new mechanisms with EDCA.
# Fuzzy-Based Control System for Solar-Powered Bulk Service Queueing Model with Vacation
## 6 Methodological and Technical Details
### Fuzzification and Membership Function Design  
In the methodology, service quality, energy availability, waiting time, and cost metrics were represented as fuzzy linguistic variables (e.g., _Low, Medium, High_). These were modelled using trapezoidal membership functions based on historical data ranges and expert input. This fuzzification step provided the foundation for uncertainty modelling.
## 4 Experiments
### The Number of Frames  
We continue to explore the impact of the number of consecutive frames in the input on the results, including the 16 frames adopted in this paper, fewer frames of 8, and more frames of 32. Note that when using 8 and 32 frames as input, the adaptation of the feature dimension in the last stage of the model's encoder was required.  
The results are shown in Table 6, where we compare the model's performance (PSNR and SSIM loss) and efficiency (latency and frequency). When the input was eight frames, optimal computational efficiency could be achieved, but the model's performance was not optimal. With 32 frames as input, computational efficiency was the poorest, and the model's performance was slightly lower than that with 16 frames as input. One possible reason is that the preceding 15 frames already provided sufficient temporal and spatial information to assist the current frame in completing the point cloud super-resolution task. Further input did not contribute effectively to predicting the current frame and might even introduce certain conflicts. Therefore, considering both model performance and efficiency, 16 frames as input are optimal.
# Grammatically Derived Factual Relation Augmented Neural Machine Translation
## 4 Experiment
### Main Results and Analysis
#### 4.2.2 Evaluating Hyper-Parameters for Linear Interpolation  
For the Linear Interpolation method, we studied the effect on WMT18 (En-Tr) and NC11 (En-De and De-En) by varying the value of \(\lambda\). The results of three test sets with different hyper-parameter values for \(\lambda\) are shown in Figure 4. When \(\lambda\) increased from 0 to 0.4, the BLEU scores improved by +1.23, +0.57 and 1.11 over the baseline model, respectively. This means that the proposed method is effective for the NMT model. Subsequently, larger values of \(\lambda\) reduced the BLEU scores, which indicated that excessive biased factual relation information may be weak when translating the target sentence.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & **WMT18** & **NC11** & & \multicolumn{2}{c}{**IWSLT14 (De-En)**} & \multicolumn{2}{c}{**IWSLT15 (En-Vi)**} \\ \cline{2-9}  & **En–Tr** & **En–De** & **De–En** & **Total** & **Valid Set** & **Test Set** & **Valid (Test 2012)** & **Test (Test 2013)** \\ \hline / & / & / & / & ELMo [32] & / & / & / & 29.30 \\ \hline / & / & / & / & SWAR [35] & / & / & / & 29.09 \\ \hline Mixed Enc [33] & 9.60 & / & / & CVT [32] & / & / & / & 29.60 \\ \hline Multi-Task [33] & 10.60 & / & / & C-MLM [38] & 36.93 & 35.63 & 27.85 & 31.51 \\ \hline Transformer [1] & 13.13 & 25.00 & 26.60 & Transformer [1] & 35.27 & 34.41 & 27.45 & 30.76 \\ \hline +Multi-Task [8] & 14.00 & 24.80 & 26.70 & Tied-Transform [36] & / & 35.53 & / & / \\ \hline +S\&H [8] & 13.00 & 25.50 & 26.80 & Dynamic Conv [30] & / & 35.20 & / & / \\ \hline +LISA [24] & 13.60 & 25.30 & 27.10 & Macaron [37] & / & 35.40 & / & / \\ \hline +PASCAL [29] & 14.00 & 25.90 & 27.40 & BERT-fused [39] & / & 36.11 & / & / \\ \hline Our Approach & 14.73\({}^{\dagger}\) & 25.91\({}^{\dagger}\) & 28.10\({}^{\dagger}\) & Our Approach & 36.89\({}^{\dagger}\) & 36.10 & 27.90\({}^{\dagger}\) & 31.53\({}^{\dagger}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Performance of different machine translation approaches on various datasets.  
Figure 4: BLEU scores of the Linear Interpolation method on the WMT18 (EN-Tr), NC11 (En–De) and NC11 (De–En) test sets with different values of \(\lambda\). The dashed line denotes the result of the baseline.
## 5 Experimental Results and Analysis  
The analysis of our experimental results is mainly divided into two parts. The first part focuses on the performance analysis of jamming sample signals generated by the  
Figure 3: Algorithm architecture.  
LACGAN network, verifying whether a GAN can learn the time-frequency features of jamming signals when applied in communication environments. The second part aims to verify the anti-jamming decision-making effect of a GA-DQN, testing whether the DQN model can improve its decision-making accuracy and convergence speed after pre-training with experience sample signals generated by a GAN.
# High Resolution Brillouin Sensing of Micro-Scale Structures
## 3 Distributed Brillouin Sensing Techniques
The dashed red line indicates the progress in spatial resolution of correlation domain techniques since their introduction in 1999. It becomes clear from this plot that the highest spatial resolutions so far belong to this technique. This plot does not include all the works in the field of distributed Brillouin sensing, which is rather vast and out of the scope of this review, but only gives an indication of the progress in the time domain and correlation domain Brillouin distributed sensing techniques in terms of the spatial resolution capabilities.
## 3 Results and Discussion
### Comparison of Grinding Characteristic between Untreated and Pre-treated Converter Steel Slag
#### 3.3.2 Grinding Efficiency of Untreated and Pretreated Steel Slag  
The specific surface areas of untreated and pretreated steel slag under different grinding times are shown in Figure 6.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Iron mineral phases**} & \multicolumn{3}{c}{**Proportions of iron mineral phases (\%)**} \\ \cline{2-4}  & **Untreated steel slag** & **PMS-steel slag** & **SMS-steel slag** \\ \hline Metallic iron \& magnetite & 2.38 & 1.18 & 0.45 \\ Hematite/imonite & 13.11 & 13.05 & 6.67 \\ Sulfide & 0.04 & 0.04 & 0.04 \\ Sidefeiter & 2.52 & 2.26 & 1.98 \\ Iron silicate & 0.21 & 0.10 & 0.06 \\ Total & 18.26 & 16.63 & 9.20 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Total analysis results of iron mineral phases in converter steel slag.  
Figure 5: The technical flow process of recycling iron-rich phases in steel slag.  
Figure 6: Specific surface areas (SSA) of steel slag under different grinding time: (**a**) SSA vs. grinding time; (**b**) linear fitting of SSA.  
As shown in Figure 6, the specific surface areas of untreated and pretreated steel slag are gradually increased with increasing grinding time, and starting from 50 min grinding time, the tendency to increase is slowed down due to the agglomeration of fine particles. The specific surface area of pretreated steel slag is obviously higher than that of untreated steel slag after the same grinding time. For example, the specific surface area of untreated steel slag is only 360 m\({}^{2}\)/kg after 60 min grinding, while that of pretreated steel slag reaches 361 m\({}^{2}\)/kg after 40 min grinding, thus 20 min grinding time is saved. The relationship of specific surface area vs. grinding time was fitted, and the result is as follows:  
\[SSA=124.7\text{ln}\ t-155.85\left(R^{2}=0.9605\right)\ \text{(Untreated steel slag)} \tag{1}\]  
\[SSA=157.44\text{ln}\ t-207.28\ \left(R^{2}=0.9906\right)\ \text{(Pretreated steel slag)} \tag{2}\]  
From the above fitted result, it can be seen that the relationship of specific surface area with the logarithm of grinding time shows a good linear relationship. After applying derivation calculus to the above equations, we can get the increasing speeds of specific surface area:  
\[\frac{dSSA}{dt}=\frac{124.7}{t}\ \text{(Untreated steel slag)} \tag{3}\]  
\[\frac{dSSA}{dt}=\frac{157.44}{t}\ \text{(Pretreated steel slag)} \tag{4}\]  
It is obvious that the grinding speed of pretreated steel slag is higher than that of untreated steel slag.
# Non-Thermal and Thermal Physical Procedures--Optimistic Solutions in the Winemaking Industry
## 2 The Use of Non-Thermal Techniques in Winemaking Optimization
### High-Pressure Processing  
The impact of high-pressure processing in winemaking was poorly examined. Table 2 illustrates some of the published results that correlate the operating conditions of the work equipment with parameters assessed in accordance with the study goals. [PERSON] et al. [50] found no effect on total phenolic content, pH, color parameters, or antioxidant activity in Pinot noir and Sauvignon blanc samples. The physicochemical structure of the wine samples tested over two months of storage after a treatment that can induce >6 log reductions of _Brettanomyces bruxellensis_ indicates that this technique represents a potential preservation strategy, according to the authors.  
Sensorial-wise, authors have analyzed the development of the spoilage volatile phenols 4-ethylguaiacol and 4-ethylphenol, which give _Brettanomyces_ off-aromas, and it was shown to be effectively inhibited by this treatment. Small dosages of SO2 could be necessary, nonetheless, in order to protect wine color and total phenolic content and improve the quality of the treated wine beyond six months of storage [51]. According to [PERSON] [52], high-pressure processing has demonstrated efficacy in the pasteurization of wine by quickly inhibiting wine-spoiling yeasts and bacteria. This method can be used to stop fermentation or manage undesired microbial development through its antiseptic effect and  
Figure 5: Co-occurrence of the keywords found in the existing research on the use of pulse electric fields in winemaking. The size of node signifies the number of occurrences, while the distance of the linking lines characterizes the relation between two nodes. The color of the items indicates the cluster to which they belong.  
stabilize and protect the quality of the final wine until consumption, reducing the use of SO2 at different phases of wine production. Compared to sterile filtration, this innovative method is cost-effective as sterile filters are not necessary and the possible sensorial impact on the final product is inexistent. Furthermore, the authors postulated that there is little impact on the wines' physico-chemical and sensory character. In another study, [PERSON] & [PERSON] [53] obtained similar results in Chardonnay wines, where 15 s at 200 MPa resulted in the inactivation of _Brettanomyces bruxellensis_ (>6 log reduction).