esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 System Model and Simulation Setup
### Simulation Setup  
In this study, multiple UAV-based network structures are simulated in the OPNET modeler. OPNET is considered the optimal simulation tool with the most implementation capabilities compared with other simulation software [41]. It is used for complex network modeling and simulation. It has a user friendly graphical user interface, visual effects, a drag and drop module import facility, and all types of network devices that are used for building a specific network. If the performance of the network is not satisfactory, the OPNET modeler can find bottlenecks in service, network, or data flow. Moreover, NS-2, NS-3, and others need to write scripts in either C++, TLC, or Python, which is difficult for the complex network. Thus, OPNET 14.5 is used for network modeling and simulation in this article.  
There are four simulation scenarios considered in this study, as described in Table 4. The network model of UAVs developed in the OPNET simulator is shown in Figure 2. Thenetwork model in Figure 2 contains 30 nodes as represented by UAV-1, UAV-2, \(\ldots\), and UAV-30, which are placed randomly within a 1000 m \(\times\) 1000 m geographical area. For scenarios 1 and 2, UAV speed is considered at 40 m /s and an altitude of 200 m. Moreover, in scenarios 3 and 4, UAV speed is applied at 30 m /s and an altitude of 50 m. Extended rate PHY327 (802.11 g) is used as the underlying MAC layer with a data rate of 24 Mbps for scenarios two and four. In the same manner, 1 Mbps data rate is used for scenarios one and three. AODV, OLSR, DSR, GRP, and E-OLSR are considered as routing protocols' performance comparisons.  
The MANET mobile node is changed to become a UAV node, as shown in Figure 3. The node model is applied to each node and every simulation scenario. Every square denotes a process model that handles packets. traf_src is applied to create a data packet and is forwarded to the lower layer. traf_src discards the packet if it already exists in the lower layer. The rsvp (resource reservation protocol) belongs to the transport layer used to cache resources over a network. The ip and ip_encap modules relate to the network layer. ip_encap encapsulates the transport layer segment. The ip module is used for addressing the individual device, reading the routing table, and sending IP data packets. The physical layer comprises wlan_port_tx_0_0 and wlan_port_rx_0_0. Here, wlan_port_tx_0_0 denotes the wireless transmitter, while wlan_port_rx_0_0 is the wireless receiver, and a_0 is the antenna module. The rest of the modules comprise OPNET process modules.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Scenario Name** & **UAVs** & **Altitude** & **Speed** & **Data Rate** \\ \hline Scenario 1 & 30 & 200 m & 40 m /s & 1 Mbps \\ Scenario 2 & 30 & 200 m & 40 m /s & 24 Mbps \\ Scenario 3 & 50 & 50 m & 30 m /s & 1 Mbps \\ Scenario 4 & 50 & 50 m & 30 m /s & 24 Mbps \\ \hline \hline \end{tabular}
\end{table}
Table 4: Simulation scenarios.  
Figure 2: Simulation scenario of UAVs network model.
###### Abstract
simplified method). The simplified method is traditionally used, but the recent availability of freeware programs such as CUFSM [10] and GBTUL [11] is expected to change the picture, since they allow obtaining accurate local-distortional-global bifurcation loads with a negligible computational and time cost. This change is already noticeable in North America, where the American Iron and Steel Institute has sponsored research that, in part, has led to the development of CUFSM (see Appendix 2 of [12]). For the particular case of lipped channels, which are profusely used in practice, EN 1993-1-3 provides analytical formulas for the distortional bifurcation load (simplified method). However, as shown in this paper, the results can differ significantly from those obtained with an accurate numerical method, both on the safe and unsafe sides, even for typical cross-section geometries. To the authors' best knowledge, the papers most closely related to this topic are those by [PERSON] and [PERSON] [13; 14], where resistances obtained from experiments (not bifurcation loads), taken from the literature [15; 16; 17], are compared with values obtained using EN 1993-1-3 (simplified and numerical methods) for columns [13] and beams bent about the major axis [14] only. Moreover, in these papers, a limited set of lipped channels were analyzed, thus there is still the need for an in-depth investigation into the accuracy of the simplified method. This work aims to fill this gap. This paper presents the results of a parametric study that assesses the accuracy of the simplified method in EN 1993-1-3 for calculating the distortional buckling (bifurcation) load of standard lipped channels subjected to axial force, major and minor axis bending. A wide range of parameter values is considered, covering common commercial products and corresponding to a total of 24,000 cases. The accuracy is measured with respect to the \"exact\" values, obtained using the numerical method, more specifically semi-analytical linearized buckling analyses using Generalized Beam Theory, which are also allowed in EN 1993-1-3. The outline of the paper is as follows. Section 2 discusses the fundamental aspects related to the calculation of the distortional buckling loads using the numerical and simplified methods prescribed in EN 1993-1-3. The results of the extended parametric study carried out are presented and discussed in Section 3. The paper closes in Section 4 with the concluding remarks.
## 7 Comparison with Some Studies  
In this section, the path loss model extracted parameters and RMS delay spread are compared with some previous studies of 5G propagation channel models for different environments and scenarios. Because of the inherent differences in the modeling methodology--for example, the threshold employed in the algorithms of post processing and the measurements range--these parameters may not be directly comparable. However, the effect of the environments on the channel characteristics can be observed from the similarities and contrasts in different propagation models. The path loss exponent, standard deviation, RMS delay spread, and some auxiliary parameters in this work are compared with some literature in Table 4. In Table 4, the values of the propagation parameters are reported within range (lower-upper), implying that the propagation studies of the listed works provide different LOS and NLOS scenarios (single frequency, multi-frequencies, vertical and horizontal and combined antenna polarizations, environment partitioning, and directional and omnidirectional model). The lower range of PLE (\(n\)) is identical for all of the studies. In this study, the lower range of PLE is 0.4 in the outdoor environment (LOS scenario) at a 19 GHz frequency, indicating that the MPCs added up constructively from both side walls along the outdoor office (a waveguiding effect), and the antenna has a wide-beam at this frequency, which can collect more paths. The upper range of the PLE is 1.5 at 38 GHz for the NLOS scenario in the outdoor environment. In the literature [32], the largest upper PLE (\(n=4.6\)) is reported at 38 GHz for an NLOS outdoor environment. In the literature [27], the PLE (\(n=1.89\)) is reported at 28 GHz for a LOS outdoor environment. In the literature [15], the largest upper PLE (\(n=4\)) is reported at 73 GHz for vertical-horizontal polarization in an open plan (large hall) indoor environment. However, in this work, the upper PLE (\(n=1.5\)) is investigated at 38 GHz for an I2O environment. This value indicates that the PLEs for all of the frequencies are lower than the FSPL exponent of 2, because of constructive interference and the wave guiding effects of the radio wave propagation along the studied environment. Note that the reported values of the ABG model parameter results are in consonance with the reported values in the literature [15]. Similarly, the RMS delay spread values are also in consonance with the mean values of the RMS reported results in the literature [33].
# Smart-Median: A New Real-Time Algorithm for Smoothing Singing Pitch Contours
## 2 Materials and Methods
### Evaluation Method
#### 2.4.4 F0 Frame Error (FFE)  
FFE is the proportion of frames within which an error is made. Therefore, FFE alone can provide an overall performance measure of the accuracy of the pitch detection algorithm [32]. This metric calculates the percentage of points in the estimated pitch contour that are within a _Threshold_ distance of corresponding points in the ground truth pitch contour (4):  
\[FFE=\frac{\sum_{i=0}^{N}\begin{cases}1&\left|\frac{SM_{i}}{GT_{i}}\right|\leq \text{{Threshold}}\\ 0&\text{{otherwise}}\\ \end{cases}}{N}\times 100 \tag{4}\]  
where \(N\) is the total number of frames/points.  
For the _Threshold_, in studies such as [1], a constant value, e.g., 16 Hz, was used as an acceptable variation from the ground truth. However, as is discussed by [PERSON] and [PERSON] [5], a fixed distance from the ground truth may not be a good approach, because the perceptual effect of 16 Hz is different when the estimated pitch is 100 Hz compared to 1000 Hz. However, it is also common to use a percentage, usually 20%, as the threshold [20], and a similar approach is used in this study.  
Higher values of this metric indicate a higher similarity between the smoothed pitch contour and the ground truth pitch contour.  
It should be mentioned that there are other algorithms for finding the similarities between pitch contours, such as those of [PERSON] [13], [PERSON] [14], and [PERSON] et al. [15]. However, these aim to determine perceptual similarity between two pitch contours. In other words, those researchers were seeking to determine the similarity of one melody to another. The purpose of the current paper is not to ascertain the overall similarities between two tunes, but rather the numerical relationship between each point on two different pitch contours. Therefore, those algorithms were not suitable for this study.
## 4 Evaluation and Analysis
### Experimental Results
#### 4.3.5 Application of Loop Closure Detection  
To validate the practical effectiveness of the proposed method in the vSLAM localization problem, we integrate MetricNet with a localization method and use its estimations to optimize the VO's prediction. To ensure the reasonableness of this experiment, we only perform the optimization by adding loop closure constraints to trajectories where MetricNet predicts the existence of closed loops. For this experiment, we use one of the most influential outdoor VO/SLAM benchmarks, KITTI [57], as the experimental dataset. Following the commonly used train/test split in deep VOs, we adopt Sequence 00, 02, 08, and 09 of the KITTI dataset to fine-tune the MetricNet and utilize Sequence 05 and 06 to perform the evaluation. ContextAVO [58] is adopted as the visual front-end, with pose graph optimization implemented in g2o [59] as the back-end.  
The visualization results are illustrated in Figure 15. It can be seen that the trajectories optimized based on associations from loop closure detection effectively reduce the cumulative error and drift. Despite some inconsistent information changes between query and matched images, i.e., dynamic objects and occlusions, the prediction of MetricNet remains promising. This suggests that MetricNet is able to provide correct and effective associations for place recognition in localization applications.
# A Survey of Routing Protocols in WBAN for Healthcare Applications
## 3 Classification of Routing Protocols for WBAN
### Cluster-Based Routing
#### 3.4.1 Dual Sink Approach Using Clustering (DSCB)  
[PERSON] et al. [30] proposed a cluster-based dual sink node routing protocol DSCB, its greatest innovation is the use of dual sink nodes. Through routing analysis of some single sink. This study found that there were many shortcomings, such as congestion, high data transmission failure rate, limited coverage, and NLOS communication, which could not adapt to a dynamic environment. In the actual application of WBAN, limb movement causes a shadow effect, and the transmission interruption caused by shadow effect needs to wait for it to disappear, before it can continue to transmit, which causes a great transmission delay. Once the interruption occurs in the emergency data period, it causes transmission failure and endangers life. The method of double sink can improve the negative consequences of the shadow effect, balance the network load of a single sink node, and improve the practicability of the WBAN.  
DSCB protocol fixes the nodes in the network, and the two Sink S\({}_{1}\) and S\({}_{2}\) are located on the front and back of the human body, respectively, which are defined as cluster head (CH), in advance. Cluster 1 and Cluster 2 are composed of other nodes on the front and back of the human body, respectively. When the node has emergency data, it communicates directly with the corresponding CH node. If it is general data, it transmits through a multi-hop mode. The cost function CF is used to select the next hop node. Considering the distance, residual energy, and transmission power, the formulae is:  
\[C.F_{n}=\frac{d}{E_{Residual_{n}}*T.P_{n}} \tag{10}\]  
where \(d\) represents the distance between the node and the sink, \(E_{Residual_{n}}\) represents the residual energy of the node, and \(T.P\) represents the transmission power. The simulation results show that the protocol reduces the transmission delay, improves the stability of the network, and improves the energy efficiency and reliable transmission.
## 2 Materials and Methods
### Determination of Phenolic Compounds
#### 2.3.2 Phenolic Profile Analysis by HPLC-UV-VIS  
The concentrations of ten phenolic compounds including phenolic acids (caffeic, chlorogenic, gallic and rosmarinic acids) and flavonoids (quercetin, naringenin, kaempfer, rutin, hyperoside and naringin), were determined by the method described by [PERSON] et al. [27] by HPLC (1220 Infinity II, Agilent Technologies, Santa Clara, CA, USA). Detection was performed using a UV-VIS detector (1220 Infinity II, Agilent Technologies, Santa Clara, CA, USA) at a wavelength of 280 nm on a C18 column (250 \(\times\) 4.6 mm) (Phenomenex, Torrance, CA, USA) at a temperature of 30 \({}^{\circ}\)C. The mobile phase consisted of ultra-distilled water with 0.1% glacial acetic acid (A) and acetonitrile with 0.1% glacial acetic acid (B). The gradient flow was as follows: 0 min, 8% B in A; 2 min, 10% B in A; 27 min, 30% B in A; 50 min, 90% B in A; 51-56 min, 100% B in A; and 51-60 min, 8% B in A. The flow rate was set at 0.8 mL/min, and the injection volume was 20 \(\mu\)L.  
The phenolic content of the plant sample was calculated from the calibration curve of standard solutions in methanol prepared at the different concentrations: gallic acid and caffeic acid (10-80 \(\mu\)g/mL), chlorogenic acid and rosmarinic acid (10-160 \(\mu\)g/mL), quercetin, naringenin, kaempfer, rutin, hyperoside and naringin (2.5-40 \(\mu\)g/mL) and expressed as mg/100 g freeze-dried vegetable sample \(\pm\) SD. Identification of the phenolic compounds in the sample was performed by comparison of retention times with standard reference solutions and by the standard addition method. Analyses were conducted in triplicate.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Vegetable**} & \multicolumn{4}{c}{**Time of Technological Processes [min]**} \\ \cline{2-5}  & & **Sous-Vide** & & **Steaming** \\  & **80.0 \({}^{\circ}\)C** & **85.0 \({}^{\circ}\)C** & **90.0 \({}^{\circ}\)C** & **100 \({}^{\circ}\)C** \\ \hline Beetroot & 96.0 & 69.0 & 45.0 & 20.0 \\ Red cabbage & 61.0 & 42.0 & 35.0 & 10.0 \\ Red pepper & 53.0 & 32.0 & 28.0 & 14.0 \\ Green pepper & 43.0 & 34.0 & 32.0 & 8.00 \\ Kale & 14.0 & 17.0 & 6.00 & 13.0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Time of raw vegetables processing using the steaming and the sous-vide method.  
The HPLC-UV-VIS method was validated according to the International Conference on Harmonization Guideline Q2 (ICH) for linearity, precision, the limit of detection, and the quantification (LOD and LOQ, respectively) [28].
## 6 Practical Implications  
This pilot has demonstrated the suitability of integrating real-time forecast with observations of rainfall, river level/flow and precomputed representations of flood magnitude and exposure to warn responders of imminent flooding with adequate alert lead times in a short, steep, flashy tropical Pacific catchment. Indeed, this was exemplified by the extreme rainfall and subsequent flooding on 18 December 2020. In this case, responders were alerted up to 24 h lead time, enabling an evidence-based evacuation of affected residents several hours before the Vaisigano River overtopped its channel.  
While the developed FDSS tools have proven effective in helping to inform evacuation response decisions which minimize the threat of injuries and loss of life, key challenges to guide future work include, but are not limited to:  
* Implementing a regular programme of flow gaugings, in particular during and after high flow events to improve existing rating curves and unit hydrograph calibrations used in the FDSS predictive models;
* Statistical downscaling of NWP models for Samoa to finer grid resolutions, as well as more frequent real-time updates consistent with the GFS/ECMWF forecast frequencies (e.g., [44; 45]). This includes the refinement of rainfall IDF's at key sites and ingestion of additional forecast models where available for Samoa;
* Application of new impacts/exposure forecasting techniques using statistical, precomputed, metamodeling approaches (e.g., [46; 47; 48]); and
* Assessing community perspectives in relation to warnings communications and response behaviour to progress towards the integration of a more people-centred approach to early warnings systems (e.g., [49; 50; 51]).  
Nevertheless, the FDSS provides a first order solution towards impacts-based forecasting for the Samoa region which is consistent with Pacific [16; 18] and international [17] efforts. Future extension of the framework to build on the capabilities developed in this pilot would help to safeguard the effectiveness of the FDSS in minimizing flood threats to injury, lives and livelihoods in Samoa, with potential applications to similar SIDS contexts.
# Experimental Study on Chromaticity Control in Visible Light Communication Systems
## 3 Research on RGB LEDs Dimming
### Dimming Experiment
However, as the distance increases, the light intensity decreases, indicating that the distance has a significant impact on the light intensity, and verified the conclusions obtained from the simulation. Maintain a distance of 50 cm, as shown in Figure 15, to measure the light intensity at different positions on the receiving surface. The light intensity at direct light is the largest. At the edge of the receiving surface, the light intensity is the smallest, with a maximum illumination value of up to 1500 lx. The illuminance value on the receiving surface is uniform at 400 lx-1200 lx, which meets the requirements of the 300 lx-1500 lx illuminance value formulated by the International Organization for Standardization, with uniformity and lighting effect. Figure 14: Change in light intensity with distance under different color temperatures. Figure 13: Variation of illuminance and color index with color temperature. To verify the accuracy of the simulation results, the proportions of RGB LEDs were adjusted to 0.6:0.28:0.12, 0.5:0.32:0.19, 0.47:0.33:0.2, and 0.45:0.34:0.21 via the driver circuit, which were consistent with the simulation proportions. The color temperatures of the mixed white light measured using the HP350 spectral illuminometer were 3472 K, 5670 K, 6530 K, and 7260 K, which were almost equal to the simulated color temperatures. Figure 16 shows the measured spectrogram, and Figure 17 shows the position information of the mixed white light on the CIE 1931 chromaticity diagram. At this time, the chromaticity coordinates are (0.4043, 0.3846), (0.285, 0.3333), (0.3117, 0.3335), and (0.3038, 0.3098), which are very close to the simulated chromaticity coordinates, indicating that the mixed white light has a good effect. multiplexing can be used for multiplexing transmission, thereby improving the communication performance of the system. Three channels of PWM are generated by the STM32 to drive three kinds of LEDs, and then the three colors are mixed into white light in a certain proportion for output and transmission in the indoor channel. At the receiving end, monochromatic radiation is separated from the white light with corresponding filters to form three channels, and receiving signals using a 905 nm silicon avalanche photodiode detector and displayed on the oscilloscope; Then, measure the received optical power using an OPHIRPD300-UV optical power meter and record the data using a computer; finally, measure the color temperature and light intensity of the mixed white light using a spectral illuminometer. The RGB LEDs visible light communication system designed in this article can achieve high-speed data communication through three parallel signals, and use the PWM dimming method to output white light to achieve chromaticity control. The experimental setup is shown in Figure 19.
## 2 Results and Discussion
### MICs  
In the first step, we decided to determine the antimicrobial activity of 10 previously selected compounds by determining their minimal inhibitory concentration (MIC) values (Table 2). We noticed that dioscin (MIC = 64 ug/mL) was the most active one, followed by amentoflavone and hypericin (both with MIC = 128 ug/mL), and aescin (MIC = 256 ug/mL). The remaining six compounds showed no antibacterial activity against _H. pylori_ J99 in the concentration range used in this study (MIC > 256 ug/mL). Despite numerous studies on the anti-inflammatory [35; 36; 37] and antitumor [38; 39; 40; 41] activity of dioscin or diosgenin (an aglycone form of dioscin), the data on their antimicrobial action are very scarce. Among the few articles available, three concerning fungi [42; 43; 44] and one indicating activity against anaerobic bacteria [45] could be found. For this reason, we believe that the results obtained by our team bring the aspect of novelty in the context of using dioscin in anti-bacterial therapy.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Compound** & **Class** & **AG [kcal/mol]** & **\(K_{1}\) [\(\mu\)M]** \\ \hline Dioscin & Saponine glycoside & \(-\)9.8 & 0.122 \\ \hline Zexanthin & Carotenoid & \(-\)8.9 & 0.527 \\ \hline Glycyrrhizic acid & Saponine glycoside & \(-\)8.8 & 0.620 \\ \hline Ginsenoside Rg3 & Saponine glycoside & \(-\)8.6 & 0.858 \\ \hline Robinin & Flavone glycoside & \(-\)8.6 & 0.858 \\ \hline Amentoflavone & Biflavonoid & \(-\)8.5 & 1.009 \\ \hline Hypericin & Naphthodianthrone & \(-\)8.5 & 1.009 \\ \hline Procyanidin A2 & Proanthocyanidin & \(-\)8.5 & 1.009 \\ \hline Procyanidin C1 & Proanthocyanidin & \(-\)8.2 & 1.642 \\ \hline Aescin & Saponine glycoside & \(-\)8.2 & 1.642 \\ \hline \hline \end{tabular} The inhibition constants were obtained with the Autodock Vina software as described in the Section 3.1.3.  
\end{table}
Table 1: Virtual screening hits, their binding free energies, and theoretical inhibition constants (at T = 310.15 K).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Tested Compounds** & **MIC [ug/mL]** \\ \hline Dioscin & 64 \\ \hline Hypericin & 128 \\ \hline Amentoflavone & 128 \\ \hline Aescin & 256 \\ \hline Glycyrrhetinic acid & \(>\)256 \\ \hline Ginsenoside Rg3 & \(>\)256 \\ \hline Procyanidin A2 & \(>\)256 \\ \hline Procyanidin C1 & \(>\)256 \\ \hline Robinin & \(>\)256 \\ \hline Zexanthin & \(>\)256 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Minimal inhibitory concentration (MIC) values of 10 selected compounds of natural origin against _H. pylori_ J99.