esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Occlusal Stability  
Occlusal stability is critical for patients with reduced periodontal tissues to avoid occlusal trauma and a worsening condition of dental and periodontal tissues. Perfectly calibrated occlusion in periodontal patients is required to complete orthodontic treatment. However, this is very difficult to achieve on a microscale. It is believed that CAs may result in imperfect occlusal contacts due to the thickness of the aligners [43]. Alternatively, imperfect occlusal contacts are believed to self-repair as a result of the settling phenomenon within 3-6 months upon completing the treatment. In turn, the studies by [PERSON] et al. [31] and [PERSON] et al. [44] have shown that immediately after completing the treatment and as a result of the settling phenomenon, a similar effect is achieved in terms of the quality of occlusion in the FA and CA groups. However, due to the limited number of studies in this area, no firm conclusions can be drawn.  
The insufficient number of studies comparing the effects of CA and FA treatment in periodontal patients makes it impossible to unequivocally answer the question whether patients would benefit more from CA treatment than FA treatment. The effects observed in many studies with individuals with healthy periodontium are promising. In particular, with a reduced rate and extension of apical root resorption, reductions in PI, PD and gingival recession encourage further research in this area. On the other hand, FAs are a better solution for high tooth mobility and significant incisor inclination. It should also be remembered that the periodontal condition must be stable prior to the initiation of orthodontic treatment, and maintaining proper hygiene is crucial to obtain a positive treatment effect.  
The limitations of this review include the following: an insufficient number of studies among periodontal patients, different age groups in the analyzed studies, different types of malocclusion, various types of orthodontic appliances used, assorted observation periods, varying types of indications used to assess the periodontal condition, and high risk of bias, partly resulting from the specificity of the orthodontic treatment (difficulty in achieving double blinding). It is important to remember that there is a discrepancy between statistical and clinical significance; in case of differences in measurement values smaller than 1 mm, there is no significant clinical impact. Similarly, with periodontal indicators where the differences are smaller than 1, it is a challenge to note clinical difference.
## 4 Streed-Net
### Cascading Hierarchical Block  
A connection section between the encoder and the decoder is provided to handle the temporal relationships among the frames. Unlike what is proposed in other works that combine the use of CNN with the use of RNN such as LSTM [45], STREED-Netimplements a Cascading Hierarchical Block with CMU (CMU) [11], which computes the hidden representation of the current state directly using the input frames of both previous and current time steps, rather than what happens in recurrent networks that model the temporal dependency by a transition from the previous state to the current state. This solution is designed to explicitly model the dependency between different time points by conditioning the current state on the previous state, improving the model accuracy; incidentally, it also reduces training times.  
The fundamental constituent of CMU architecture is the MU [46], which is a non-recurrent convolutional structure whose neuron connectivity, except for the lack of residual connections, is quite similar to that of LSTM [47]; the output, however, only depends on the single input frame \(h\). Formally, MU is defined by the following equation set:  
\[g_{1}=\sigma(W_{1}*h+b_{1}) \tag{10}\] \[g_{2}=\sigma(W_{2}*h+b_{2})\] (11) \[g_{3}=\sigma(W_{3}*h+b_{3})\] (12) \[u=tanh(W_{4}*h+b_{4})\] (13) \[MU(h;W)=g_{1}\odot tanh(g_{2}\odot h+g_{3}\odot u) \tag{14}\]  
where \(\sigma\) is the sigmoid activation function, \(*\) the convolution operator and \(\odot\) the element-wise multiplication operator. \(W_{1}\sim W_{4}\) and \(b_{1}\sim b_{4}\) are the weights and biases of the respective convolutional gates and \(W\) denotes all MU parameters.  
CMU incorporates three MU. Unlike MU, CMU accepts two consecutive frames as input to model explicitly the temporal dependencies between them. The more recent frame in time is inputted to a MU to capture the spatial information of the current representation. The older frame is instead processed by two MU in sequence to overcome the time gap. The partial outputs are then added together and finally, thanks to two gated structures containing convolutions along with non-linear activation functions, the output of the CMU (\(X_{t}^{l+1}\)) is generated. CMU is described by the following equations:  
\[h_{1}=MU(MU(E_{(t-1)}^{l};W_{1});W_{1}) \tag{15}\] \[h_{2}=MU(E_{t}^{l};W_{2})\] (16) \[h=h_{1}+h_{2}\] (17) \[o=\sigma(W_{o}*h+b_{o})\] (18) \[X_{t}^{l+1}=o\odot tanh(W_{h}*h+b_{h}) \tag{19}\]  
where \(W_{1}\) and \(W_{2}\) are the parameters of the MU in the left branch and of the MU in the right branch respectively, \(W_{o}\), \(W_{h}\), \(b_{o}\) and \(b_{h}\) are the weights and biases of the corresponding convolutional gates. The cascading hierarchical block uses CMUs to process all frames at the same time (see Figure 4):  
\[X_{cmu}=CascadeCMU(E^{(L+1)}) \tag{20}\]  
where \(X_{cmu}\in\mathbb{R}^{N\times M\times\mathcal{C}^{\prime}}\).
## 4 Training and Simulation
### Comparative Analysis of the Control Effects in the MBS Simulations
#### 4.3.1 Running Stability on a Straight Track  
Figure 8 presents the simulation results for the active guidance performed in the straight line at 120 km/h. Under the control of the Hoo algorithm, the maximum lateral displacements observed in the front and rear wheelsets were 2.21 mm and 1.93 mm, respectively. In contrast, the PER-MADDPG controller demonstrated superior performance, reducing the maximum lateral displacement to 1.15 mm for the front wheelsets and 1.05 mm for the rear wheelsets. This considerable improvement signifies enhanced straight-line centering capabilities. Similarly, marked reductions were observed in the yaw angles; the maximum yaw angles of the front and rear wheelsets decreased from 3.47 mrad and 1.45 mrad, respectively, under Hoo control to 1.23 mrad and 0.95 mrad, respectively, when controlled by PER-MADDPG. This reduction in both lateral displacement and yaw angle  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Algorithm** & **Final Mean** & **Standard Deviation** & **Training** & **Sampling** & **Training** \\  & **Reward** & **of Final Reward** & **Episodes** & **Policy** & **Framework** \\ \hline PER-MADDPG & 8.05 \(\times\) 10\({}^{5}\) & 2.96 \(\times\) 10\({}^{4}\) & 5 \(\times\) 10\({}^{5}\) & Off-policy with & \\  & & & & PER & CTDE \\ MADDPG & 7.31 \(\times\) 10\({}^{5}\) & 4.92 \(\times\) 10\({}^{4}\) & 5 \(\times\) 10\({}^{5}\) & Off-policy & CTDE \\ MAPPO & 6.48 \(\times\) 10\({}^{5}\) & 2.02 \(\times\) 10\({}^{4}\) & 5 \(\times\) 10\({}^{5}\) & On-policy & CTDE \\ DDPG & 5.76 \(\times\) 10\({}^{5}\) & 6.64 \(\times\) 10\({}^{4}\) & 5 \(\times\) 10\({}^{5}\) & Off-policy & SA \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comprehensive evaluation of the trained MARL and DRL algorithms.  
also led to a noticeable decrease in wheel-rail wear numbers. The maximum wear numbers for the front and rear wheelsets decreased from 83.93 N and 77.21 N under Hoo control to 59.44 N and 56.16 N under PER-MADDPG control, with the average values decreasing from 15.8 N and 10.9 N to 7.7 N and 5.9 N, respectively. Thus, the proposed active control algorithm effectively reduced wheel-rail wear by more than 40%. Furthermore, the PER-MADDPG controller maintained maximum control torques of 467.1 N\(\cdot\)m and 408.2 N\(\cdot\)m for the front and rear wheelsets, respectively, and the average control torques were 183.9 N\(\cdot\)m and 164.1 N\(\cdot\)m, respectively, well within the controller's design capacity of 2 kN\(\cdot\)m. The comparative results of the cosimulation show that the PER-MADDPG controller significantly improves the straight-line stability of IRWs relative to the model-based controller, as evidenced by the reductions in lateral displacement and attack angle, as well as in wheel-rail wear, thus validating the performance of the proposed algorithm.
# Measurement of Instantaneous Mass Flow Rate of Polypropylene Gasification Products in Airflow
## 3 Data Processing Procedure
### Mass Flow Rate at GG Outlet  
When heated air flows through the PP sample, the PP material undergoes gasification, and gasification products mix with the passing air flow. Moreover, the gasification products are partly oxidized by air (combusted in air), leading to heat release. This heat causes additional gasification of the sample, thus increasing the amount of gasification products in the gas mixture. The task is to determine the increased mass flow rate of the gas mixture at the GG outlet. In test fires, the mass flow rate of gas mixture was determined using a sonic nozzle installed at the GG outlet. The gas flow stagnation pressure \(P_{\text{0 out}}(t)\) and stagnation temperature \(T_{\text{0 out}}(t)\) measured upstream of the nozzle allow the calculation of the choked-flow mass flow rate \(G_{\text{out}}(t)\):  
\[G_{\text{out}}(t)=\mu_{2}\frac{P_{\text{0 out}}(t)}{\sqrt{T_{\text{0 out}}(t)}}A _{2}^{*} \tag{3}\]  
where \(A_{2}^{*}\) is the cross-sectional area of nozzle throat. The presence of sonic velocity in the nozzle throat is checked against the measured static-to-total pressure ratio in each test fire. Typical values of this ratio range from 0.5 to 0.6, which allows taking the area \(A_{1}^{*}\) for further calculations with an error below 1%. The main difficulty of Equation (3) is to determine a value of constant coefficient \(\mu_{2}\), which depends on the thermophysical properties of the gas mixture:  
\[\mu_{2}=\sqrt{\frac{\gamma*}{R^{*}}\bigg{(}\frac{2}{\gamma*+1}\bigg{)}^{\frac {2\gamma+1}{2\gamma-1}}} \tag{4}\]  
where \(\gamma^{*}\) and \(R^{*}\) refer to the gas mixture flowing through the sonic nozzle and depend on the unknown mixture temperature, pressure, and composition. Figure 7 shows typical values of \(\mu_{2}\) depending on temperature and initial composition of the PP-air system at 1 MPa obtained by iterations using the Astra 4 code [27]. As can be seen, \(\mu_{2}\) varies from 0.0404 to 0.0300 (kg\(\cdot\)K/J)\({}^{1/2}\). This variation leads to a change in the calculated mass flow rate of gas mixture by 30%. Noteworthy, when the pressure varies from 0.1 to 1.0 MPa, the value of \(\mu_{2}\) changes by less than 3%. The present authors' experience in processing experimental data shows that coefficient \(\mu_{2}\) can be considered constant with a good accuracy (see below).  
Figure 6: Example of determining the air mass flow rate \(G_{\text{in}}(t)\) in one of test fires (test fire #4, see below): (**a**) time history of pressure in the air storage vessel (solid curve) and its approximation (dashed curve) according to Equation (1), and (**b**) time history of the air mass flow rate according to Equation (2).
## 4 Post Processing  
This section explains the post processing of the raw data that were collected from the ultra-wideband channel sounder measurement. It includes the extraction of the channel impulse responses from the received waveforms. The data were subjected to post processing using SystemVue software [27] and MATLAB Toolbox. The channel impulse response (CIR) was extracted by cross correlation between the received waveform and the transmitted arbitrary waveform signal. the space-alternating generalized expectation-maximization (SAGE) algorithm [28, 29] was used to extract the parameters of the MPCs, including the path delay and path gain. It allowed an iterative determination of the maximum-likelihood estimation. The SAGE algorithm resolved the MPCs by an interference-cancellation, where the MPCs that were already estimated were subtracted from the considered signal.
# Implementation of the 3-30-300 Green City Concept: Warsaw Case Study
###### Abstract  
In recent years, the \"3-30-300\" concept by Professor [PERSON] has been gaining popularity, outlining what makes a city \"green\" and what we should strive for. This concept suggests that from every apartment, at least three trees should be visible, 30% of the city's surface should be covered with greenery, and the nearest park or forest should be no more than 300 m away. However, the lack of detailed guidelines makes the implementation of this concept a significant challenge. The goal of the research presented here was to adapt this concept for Warsaw (Poland) and assess whether it can be considered a green city. We defined parameters such as the maximum distance for visible trees as 20 m and determined what counts toward the 30% green areas. The results showed that 57.82% of apartments in Warsaw have a view of at least three trees, while only 5.44% do not meet this criterion, and the rest meet it only partially. Parks and forests cover 19.95% of the city, while all green areas combined cover 42.01%. Additionally, 45% of buildings are located within 300 m of a park or forest. Ultimately, full compliance with the \"3-30-300\" concept applies to 22.19% of buildings, while only 12.66% meet the criteria when considering only parks and forests. This indicates that, while Warsaw is relatively green, not all of its areas fulfill these criteria.  
3-30-300 concept; Warsaw green city; spatial analysis Article
# Isothermal Drying Process and its Effect on Compressive Strength of Concrete in Multiscale
## Materials and Methods
### Test Procedures  
#### 2.2.1 Isothermal Drying Process  
After being taken out of the standard curing laboratory, specimens were wiped with a wet cloth and then wrapped with two layers of plastic film for 48 h to ensure uniform distribution of water in specimens. Then, half of the samples of each mixture were weighed and then equally spaced in the oven, which was preheated to 105 \({}^{\circ}\)C, until no more mass was lost, with the water loss and deformation during the drying process being measured, while the other half was still wrapped and placed at room temperature. Oven-drying was used for specimen drying in this study because all evaporable water is removed [20,21] at this temperature and this drying method is widely used by researchers [7,9,10,12].  
Drying operations were well-controlled to maintain the oven temperature within 105 \(\pm\) 1 \({}^{\circ}\)C and no heating rate was used. The air blower was always on to keep the oven dry. Specimens were weighed at regular intervals until the mass no longer changed. Each weighing was done within 5 minutes. The moisture content \(\omega_{\text{t}}\) and the saturation degree \(S_{\text{r}}\) of the specimen during drying process can be calculated according to Equations (1) and (2).  
\[\omega_{\text{t}}=\frac{m_{\text{t}}-m_{\text{d}}}{m_{0}}\times 100\% \tag{1}\]  
\[S_{\text{r}}=\frac{m_{\text{t}}-m_{\text{d}}}{m_{0}-m_{\text{d}}}\times 100\% \tag{2}\]  
where \(m_{0}\), \(m_{\text{t}}\), and \(m_{\text{d}}\) represent the mass of the specimen before drying, during drying, and after drying, respectively.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Material** & **Water/Cement Ratio** & **Cement/kg** & **Water/kg** & **Fine Aggregate/kg** & **Coarse Aggregate/kg** \\ \hline \multirow{4}{*}{cement paste} & 0.35 & 1498 & 524 & - & - \\  & 0.38 & 1434 & 545 & - & - \\  & 0.41 & 1375 & 564 & - & - \\  & 0.35 & 690 & 242 & 1381 & - \\ mortar & 0.38 & 676 & 257 & 1352 & - \\  & 0.41 & 663 & 272 & 1326 & - \\  & 0.35 & 368 & 129 & 735 & 1252 \\ concrete & 0.38 & 364 & 138 & 727 & 1239 \\  & 0.41 & 360 & 148 & 720 & 1225 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Mix proportions of cement paste, mortar, and concrete.  
Figure 1: Grading curves of (a) fine aggregate and (b) coarse aggregate.
# A Filter-Based and Parallel Unknown Tag Identification Protocol in Open RFID Systems
## 7 Conclusions  
This paper investigated the problem of unknown tag identification in open RFID systems and proposed a filter-based parallel unknown tag identification protocol (FPUI), which can address the unknown tag identification problem completely and efficiently. FPUI first separates known tags from unknown tags by constructing an RSQF-based fingerprint filter, deactivating all known tags and eliminating false positives. Then, it effectively identifies unknown tags by using a CDMA-based parallel identification scheme. A theoretical analysis was conducted to optimize the parameters for minimizing the total execution time. Meanwhile, many simulation experiments were carried out to evaluate the performance of the proposed protocol. The simulation results indicated that the proposed protocol comparatively outperformed the existing advanced protocols.  
Investigation, H.L. and J.L.; Methodology, R.G. and C.H.; Project administration, X.T., S.S. and J.L.; Writing--original draft, X.W. All authors have read and agreed to the published version of the manuscript.  
This research was financially supported by the National Natural Science Foundation of China (Nos. 61702257, 61272418), the Open Foundation of State Key Laboratory for Novel Software Technology for Nanjing University (No. KFKT2021B15), the Jinling Institute of Technology High Level Talents Research Foundation (No. jit-b-202118), and the Major Project of Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 18 KJA520003, 21 KJA120001).  
Not applicable.  
The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.  
Figure 9: The deactivating accuracy with respect to \(n\).
## 3 Results and Discussion
### Effect of pH and Competitive Ion  
pH optimization tests were done with the pH ranging between 2 and 7; the results are presented in Figure 1. The results clearly show that the optimum pH value for adsorption is 4 and that removal efficiency is slightly lower with pH values of 6 and 7. There is no removal capacity with a pH value of 2.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Brunauer–Emmett–Teller**} & \multicolumn{3}{c}{**Barrett–Joyner–Halenda**} \\  & & \multicolumn{3}{c}{**(BET)**} & \multicolumn{3}{c}{**(BJH)**} \\ \hline \multirow{2}{*}{**Sample**} & \multirow{2}{*}{**Yield [\%]**} & \multirow{2}{*}{**TC [\%]**} & **Specific** & **Pore** & **Average** & **Micropore** & **Mesopore** & **Macropore** \\  & & & **Surface** & **Volume** & **Pore Size** & **[\%]** & **[\%]** & **[\%]** \\  & & & **Area** & **[m\({}^{2}\)/g]** & **[cm\({}^{3}\)/g]** & **[nm]** & **[nm]** & **[\%]** & **[\%]** \\ \hline Birch carbon & 10 & 97 & 860 & 0.61 & 2.8 & 14 & 84 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characterization results of produced activated carbon sample.  
The effect of competitive ions was studied using a Zn solution prepared from ZnCl\({}_{2}\) or ZnSO\({}_{4}\) within a pH range of 2-6. The results clearly show that the adsorbed amount of Zn and the removal percentage seem to be dependent only on pH value and not on the competitive ions (Cl\({}^{-}\) or SO\({}_{4}\)\({}^{2-}\)). Thus, adsorption towards the biomass-based activated carbon is selective.
# New Insights into the Biology of the Emerging Tembusu Virus
## 3 Epidemiology
### Vertebrate Host  
The first presence of TMUV in a vertebrate host was reported in 2000 in chicks in Malaysia [5]. The TMUV host range was then reported to be similar to avian hosts of the avian influenza virus, which has caused disease in poultry in over 50 countries worldwide since 1997 [41]. TMUV was mostly isolated from ducks in industrial farms. However, the presence of the virus in free-grazing ducks has been reported in Thailand and may play an important role in the spreading of the virus through avian fauna [42]. Besides ducks, a wide range of birds including geese, chickens, sparrows and pigeons are naturally infected by TMUV (Table 2). These wild birds are likely to play a crucial role in the spread of the virus to farm birds, not only via arthropod vectors but also as a result of close contact or expercoration between animals. Several members of the flavivirus family, such as DENV and ZIKV, induce pathology in humans [43; 44]. However, the presence of TMUV in humans or other vertebrates is not well documented. TMUV infections in humans and non-human primates were mainly detected by post-infection serological surveys, and the pathogenesis in mammals remains unclear [45]. Finally, it is not yet known whether vertebrates other than birds can serve as reservoirs or amplifying hosts, or whether they are potentiel dead-end hosts with viral loads insufficient for active transmission to mosquito vectors. Moreover, as for other flaviviruses, a high percentage of TMUV-infected individuals may be asymptomatic or present with only weak symptoms, thereby hiding the spread of the virus in the human population and the risk for a potentially large outbreak. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Country/Location of Origin** & **Species** & **Year** & **References** \\ \hline Kuala Lumpur, Malaysia & _Cx. tritieniorhynchus_ & 1955 & [24] \\ \hline Malaysia & _Cx. vishmui_ & 1970 & [2] \\ \hline \multirow{3}{*}{Kamphaengphet Province, Thailand} & _Cx. gelidus_ & \multirow{3}{*}{[25]} \\  & _Cx. triteniorhynchus_ & & \\  & _Cx. vishmui_ & & \\ \hline Chiang Mai Province, Thailand & _Cx. triteniorhynchus_ & 1992 & [1] \\ \hline Kamphaeng Phet Province, Thailand & _Cx. vishmui_ & 2005 & [37] \\ \hline Shandong Province, China & _Cx. pipiens_ & 2010–2012 & [38] \\ \hline Yunnan Province, China & _Cx. triteniorhynchus_ & 2012 & [39] \\ \hline Shandong Province, China & _Cx. spp_ & 2012 & [40] \\ \hline Sing Buri Province, Thailand & _Cx. triteniorhynchus_ & 2015 & [36] \\ \hline Kanchanaburi Province, Thailand & _Cx. quinquefasciatus_ & 2015 & [34] \\ \hline Taipei, Taiwan & _Cx. annulus_ & 2019 & [26] \\ \hline Taichung, Taiwan & _Cx. triteniorhynchus_ & 2019 & [26] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Mosquito species found infected by TMUV.