esa-sceva/satcom-chunk-collection huggingface dataset:
# Probabilistic Modeling of Congested Traffic Scenarios on Long-Span Bridges
## 5 Discussion  
This study extended the probabilistic model of extreme response scenarios to account for congested traffic conditions, demonstrating its flexibility and broad applicability to various traffic situations on long-span bridges. A key finding is the necessity of adjusting key parameters when applying the model to congested traffic. For instance, the cell size used for the vehicle distribution on the bridge deck was reduced from 20 m, as used in free-flow scenarios, to 10 m to reflect the shorter inter-vehicle gaps in congested conditions. Moreover, while the contribution of light vehicles is typically negligible in free-flow conditions, they play a significant role in congested traffic. The study shows that neglecting light vehicles in congested traffic can result in a load effect loss of up to 24%, making their inclusion essential for accurate simulation and safety evaluation.  
The comparison of extreme response scenarios under free-flow and congested conditions reveals that heavy vehicles are less frequent in congested traffic but tend to cluster in outer lanes, especially under extreme loading conditions. This behavior necessitates the continued use of a non-stationary Poisson distribution for vehicle location modeling. Additionally, this study confirms that the probabilistic model remains capable of efficiently simulating extreme response scenarios under congested traffic at a significantly lower computational cost compared to direct micro-simulation using the CA method.  
In summary, the model demonstrates its robustness and adaptability to different traffic conditions, providing accurate predictions of extreme response scenarios with minimal computational effort. These findings underscore the model's potential for use in real-time traffic monitoring and bridge safety assessments under varying traffic conditions, especially as congested traffic becomes increasingly common on long-span bridges. Future work could focus on refining the model to account for additional factors influencing the bridge response under congested conditions, such as vehicle type and load distributions over time. Furthermore, the practical implications and contributions of the simulation results to the design and structural safety evaluation of bridges were demonstrated through a practical application of the model in a comparative analysis between observed extreme response scenarios under actual traffic conditions and model loading scenarios specified in representative international codes. The results highlight the inadequacy of the applicability of existing codes in assessing the response to highway traffic for long-span cable-stayed bridges, being too conservative in some cases and under-conservative in others [41].
# Multiservice Loss Models in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic
## 4 The Generalized f-MC-MC Model  
In this section, we present the f-MC-MC model which generalizes the f-MC-SC model by taking into consideration the grouping of RRHs in different clusters based on their RRUs capacity, thus forming a multi-cluster of RRHs.
# Camera-Based Continuous Heart and Respiration Rate Monitoring in the ICU
## 2 Materials and Methods
### Measurement Setup  
Video recording utilized two camera types: RGB and NIR. The RGB camera (3860-C-HQ Rev. 2, IDS GmbH, Obersulm, Germany) was configured for 32 fps 484 \(\times\) 274 pixel resolution with 2\(\times\) binning and 12-bit depth. To ensure adequate brightness of the face, the RGB camera's automatic shutter function was run once every minute, and the ROI for the brightness target was set to the face ROI detected with a face detector [22]. All other camera functions were disabled. The NIR camera (UI-3370 CP-NIR-GL, IDS GmbH, Obersulm, Germany) operated at 16 fps 1920 \(\times\) 1080 resolution with 8-bit depth. The lower frame rate was chosen to allow a longer shutter time, which was set to 66 ms to allow sufficient brightness of the NIR image during the night. Again, all other functions were disabled. Both cameras were equipped with a fixed 8 mm focal length lens (M118 FM08, TAMRON, Saitama City, Japan) with a fully open aperture.  
Mounting the cameras above the patient's bed would be ideal, as they would not obstruct the staff, and the higher angle of incidence could reduce the chance that staff would occlude the view of the patient. However, altering the ICU room to mount the cameras on the ceiling was not feasible for this study. Instead, a mobile camera setup on a medical cart was placed at the foot end of the bed. This allowed a single setup to be used for data collection in multiple ICU rooms, and as the setup was mobile, it could be moved out of the way if needed by the staff. The three cameras and a baby monitor (DVM-71, Alecto, Kerkrade, The Netherlands),  
Figure 1: Flowchart of the complete methodology of heart and respiration rate extraction. Details on each processing step can found in the section step beneath each block. An asterisk indicates an adaptation has been made to the existing method [5,10,20,21]. A plus sign indicates a new contribution.  
of which only the NIR light source was used, were mounted close together on the cart at a height of 2 m and were aimed such that patient visibility could be ensured regardless of bed height and headrest adjustments. Each of the cameras collected approximately 2 GB/min of video data for a total of approximately 5.8 TB of video per 24 h per patient. Therefore, a laptop with 8 TB of external storage was used to collect and store video data of one patient. After a recording was finished, the video data were transferred to another storage location and processed offline. Some patients were also seated in a chair next to the bed for a part of the recording, in which case the setup was moved so that they were still within the field of view. If during a recording a moment of privacy was needed, the cameras were covered. The complete measurement setup can be seen in Figure 2.
## 3 Results and Discussion
### Results of ANOVA  
The numerical results of the ANOVA for the treatments shown in Tables 1-3 are shown in panel (a) \(F\) and \(F_{crit}\) and panel (b) \(p\)-value. The abscissa of Figure 11 (condition) is explained in Table S5. The number of replicates was 3. If  
\[F<F_{crit} \tag{2}\]  
or, if \(p\)-value, \(p\), satisfies  
\[p>\alpha \tag{3}\]  
where in the present case,  
\[\alpha=0.05 \tag{4}\]  
the null hypothesis was accepted. As such, the null hypotheses were accepted for all of the cases in Figure 11 and Table S5 in either case of Equation (2) or Equation (3). This means that there were no significant differences among Pot Nos. 1-7 in Table 1 or Table 2 or among Pot Nos. 1-8 in Table 3.  
Figure S6 shows statistical significance of differences between group means according to Pot Nos. (Groups). One can see that one cannot be sure that the difference between means is statistically significant when standard error bars overlap much, e.g., panels (a), (g), (i), (k), (l), and (n) of Figure S6. This is consistent with the fact that p-values are 0.899, 0.868, 0.943, 0.960, 0.950, and 0.915 for panels (a), (g), (i), (k), (l), and (n) of Figure S6, respectively, which are large values. On the other hand, even though the error bars do no overlap so much in panels (b), (c), (d), (e), (f), (h), (j), (m), and (o), the differences are not statistically significant, whose p-values are 0.339, 0.336, 0.456, 0.269, 0.495, 0.611, 0.569, 0.333, and 0.386, respectively.  
Figure 10: Effect of types and concentrations of chelating agents on the absorption of (**a**) Cd and (**b**) Zn in _Gazania_. BLK represents the pot for no addition of heavy metals (i.e., Al, Pb, Bi, and Ni) as well as no addition of chelating agents (i.e., Pot No. 1 in Table S2).
# An Improved Genetic Algorithm with Adaptive Variable Neighborhood Search for FJSP
## 2 Mathematical Model of FJSP  
A FJSP problem can be described as follows:  
There are \(n\) jobs \(J=\{J_{1},\,J_{2},\,\ldots,\,J_{n}\}\), which are processed on \(m\) different machines \(M=(M_{1},\,M_{2},\,\ldots,\,M_{m})\). Each job \(J_{i}\) contains \(n_{i}\) non-preemptable ordered operations, expressed as the operation set \(O_{i}=\{O_{i,1},\,O_{i,2},\,\ldots,\,O_{i,n_{i}}\}\). L is the total number of operations of all jobs. Each operation \(O_{i,j}\) selects the machine to be processed from a set of available machines (this paper studies the partial FJSP (P-FJSP), machine set \(M_{i,j}\in M\). If it is a total FJSP (T-FJSP), the machine set \(M_{i,j}=M\)). The processing time of the operation on different machines \(t_{i,j,k}\) (\(1\leq i\leq n,\,1\leq j\leq n_{i},\,1\leq k\leq m\)) is predefined. The optimization goal of FJSP is to select the machine \(M_{k}\) from the machine set \(M_{i,j}\) for each operation \(O_{i,j}\), and determine the start time \(st_{i,j}\) and completion time \(f_{i,j}\) of each operation, and minimize the completion time of all machines, see the Equation (1).  
\[f=\min(\sum_{i=1}^{n}\max(ft_{i,n_{i}})) \tag{1}\]  
FJSP processing also satisfies the following constraints and assumptions (5 and 6 are assumptions):  
* All machines are available at time 0, and each operation can be processed at time 0;
* At a certain time, one operation can only be processed by one machine at a time. Once the operation is completed, the machine can be used in other operations;
* Once the processing begins, it cannot be interrupted;
* There are no successive constraints on the operations of different jobs, and there are successive constraints between the operations of the same job;
* The setting time of the machine and the transportation time of the operation are negligible;
* There are no emergencies (such as machine failures, new orders, etc.).
# Research on Leaf Area Density Detection in Orchard Canopy Using LiDAR Technology
## 4 Discussion
However, the measurement system in this research had difficulty covering the top regions of the fruit tree canopies, failing to obtain more comprehensive three-dimensional information. This will be further considered for different application scenarios in later research. In an orchard cultivated using the horizontal trellis system, when the leaf area density in the sampling area is lower than 4 m\({}^{2}\)/m\({}^{3}\), the relative measurement error is 10.14%. This indicates that the leaf area density detection algorithm based on leaf fitting performs well within the leaf area density range of 1.0 m\({}^{2}\)/m\({}^{3}\) to 4.0 m\({}^{2}\)/m\({}^{3}\), demonstrating the applicability of the algorithm proposed in this research. This result is significantly better than that obtained using the ultrasonic method [10; 15] and also superior to the result based on the method of measuring the number of leaves using point cloud counting [26]. However, as the leaf area density increases, the degree of overlap between leaves intensifies, significantly affecting the leaf fitting effect and leading to a gradual increase in errors. Due to the high degree of overlap, the scanning of leaf point clouds within the canopy is incomplete, which may result in an insufficient number of basic point clouds for leaf fitting. Consequently, during the fitting process, these leaves may merge with surrounding leaves or be filtered out as noise, thereby introducing errors into the detection of the leaf area density. To further verify the reliability of our conclusions, we plan to conduct orchard experiments at different stages in later research. The characteristics of tree canopy leaves vary in orchards at different stages. By conducting experiments at various times, we can obtain more comprehensive data to evaluate the stability and accuracy of our proposed canopy density detection method and the related conclusions. The results of laboratory-simulated canopy validation experiments were superior to those conducted in an actual orchard with horizontal trellis cultivation. The mathematical calculation model (Formula 4) used in this research for orchard canopy leaf area density was derived from the results of laboratory-simulated canopy experiments. In these simulations, the arrangement of the artificial leaves only considered the scenario where the leaves were facing the LiDAR directly. However, in real situations, the growth angles of the leaves and the scanning angles of the LiDAR often have an impact on the detection results [30], particularly during the clustering process, where point clouds from leaves at different angles can lead to significant errors. In future research, a multi-sensor fusion algorithm will be incorporated to compensate for errors caused by angular variations.
# A Geo-Clustering Approach for the Detection of Areas-of-Interest and Their Underlying Semantics +
## 5 Discussion and Conclusions
### Conclusions and Future Work  
Concluding, we feel that this work leaves many open research issues towards improvements of the overall results, therefore we attempt to present those that we consider the most important. First of all, the tile size has been selected upon a combination of a heuristic approach and a trial-and-error process. Further research may focus towards the selection of optimal tile size for any given city. The algorithm's robustness for the extraction of the top-\(k\) representative tags may further be investigated. Moreover, since this paper exploited the city of Athens as its use case, the proposed methodology should be investigated to additional cities with varying geospatial, cultural and economic characteristics. Also, the temporal dynamics and variations of tags should be investigated and more specifically assess how they affect the creation of a geo-cluster at various time intervals, periods or even seasons. Other remaining issues are the detection of popular POI categories within an AOI (i.e., geo-cluster feature extraction), the creation of personalized recommendations in accordance with a users' previous travel history and her/his personal characteristics (e.g., age and/or gender) and the exploitation of location-based checkins by aggregating several social networks. Finally, as far as user evaluation is concerned, a more thorough one with a significantly larger and heterogeneous population could be able to reveal preferences of specific user groups and/or general tendencies within the city under investigation.  
**Author Contributions:** [PERSON] and [PERSON] conceived the initial idea. [PERSON] and [PERSON] designed the experiments; [PERSON], [PERSON] and [PERSON] wrote the paper. [PERSON] and [PERSON] collected the data. [PERSON], [PERSON] and [PERSON] analyzed the data and performed the experiments.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Case Study and Results
### Tap Ratio Setting  
Figure 12 shows the deviation of the tap ratio at the substation transformers, obtained in all 26 critical case scenarios, in comparison to the average tap settings. The deviation of the tap ratio was calculated for each of the analysed three configurations (base case, P2P, and MVDC) and was calculated as: \(\triangle r=r-\overline{r}\). The average of the tap settings, \(\overline{r}\) obtained in the base case, with P2P configuration and with MVDC configuration were 1.029, 1.025, and 1.029, respectively. In all three configurations, tap ratios operated at higher values of \(r\) during high-demand at low DG generation (scenarios 1-16 of Table 2) in comparison to the scenarios with lower demand and higher DG generation (scenarios 17-26 of Table 2). The base case presents the highest deviations of the tap ratio and less tap ratio deviations obtained with the hybrid configurations (P2P and MVDC). This was because the VSCs in the hybrid AC/DC system could provide fast remedial actions of reactive power support, especially during short-term periods. The MVDC configuration presents the least deviations due to the active power transfer flexibility between multiple feeders through the MVDC network.
## 2 Mathematical Programming Model
### Assumptions  
* Once the satellite's observation and data transmission activities begin, they must not be interrupted.
* Each satellite is equipped with only one solid-state storage and battery resource. Without considering the uncertainty of resource consumption such as solid-state storage and batteries on board, the storage capacity and energy of the satellite are limited.
* The satellite operates in a playback mode, which means it first captures images and then transmits the imaging data to the ground station.
* Satellites can simultaneously perform imaging and data downlink operations.
* The attitude transition time of the satellite between two targets is a fixed value. A fixed attitude transition time needs to be satisfied between two data transmission missions from a satellite to different ground stations, and similarly, a fixed transition time needs to be satisfied between two data transmission missions from ground stations to different satellites.
* Since the energy consumption of satellite attitude maneuvers is relatively small compared to imaging and data transmission missions, the energy consumed by satellite attitude maneuvers is not considered in this study.
* Each satellite carries only one sensor.
* Ignoring the factors that affect observation tasks, such as cloud cover, solar angle, and other meteorological conditions.
* It is necessary to select a satellite with an appropriate side view angle for imaging in order to meet the user's requirements for the quality of the target image.  
Figure 1 shows a diagram of the example scenario.
# Study on the Machinability of Ni-Based Superalloy by
###### Abstract  
To explore the milling characteristics of Ni-based superalloy under minimal quantity lubrication (MQL), a single-factor experiment was adopted to investigate the milling machinability of GH4169 Ni-based superalloy. The influences of milling parameters and cooling methods on workpiece surface roughness, milling force, and surface hardness were analyzed. The results showed that the milling parameters and cooling methods have significant effects on the milling machinability of GH4169 Ni-based superalloy. The milling force was \(F_{y}>F_{x}>F_{z}\), and the milling force decreased first and then increased with the increasing cutting speed. The surface roughness, surface hardness, and work hardening rate of the workpieces decreased with the increasing cutting speed and increased with the increasing feed per tooth and radial cutting depth. The milling parameters had a nonsignificant effect on the depth of the work hardening layer in GH4169 Ni-based superalloy. The order of cooling methods to obtain the minimum surface roughness and minimum milling force is nanofluid MQL \(>\) MQL \(>\) air cooling \(>\) no cooling.  
minimal quantity lubrication; GH4169 Ni-based superalloy; milling machinability; milling parameters; cooling methods
# Comparison and Identification of the Aroma-Active Compounds in the Root of _Angelica dahurica_
## 2 Results and Discussion
### Comparison of Quality of Aroma Compounds by the Different Extraction Methods  
As shown in Table 1, 31 common aroma compounds were identified in all three samples. A total of 34, 38, and 26 aroma compounds were extracted from Hangbaizhi, Qibaizhi, and Bobaizhi, respectively, by SPME; 15, 17, and 15 aroma compounds were extracted by P&T; 29, 38, and 22 aroma compounds were extracted by SBSE, while 29, 33, and 23 aroma compounds were extracted by DHS. The variety of compounds extracted by P&T was the lowest, whereas those extracted by the other methods were not significantly different.  
As shown in Figure 2, the volatile compounds extracted by the four different headspace extraction methods were different. P&T was unable to extract aromatics, alcohols, aldehydes, ketones, and acids from Hangbaizhi but extracted those compounds from Qibaizhi and Bobaizhi in low amounts. However, the amounts of these aroma compounds extracted from the three kinds of _A. dahurica_ using SPME, SBSE, and DHS were all higher than those obtained using P&T. This result indicated that although these aroma compounds were present in Hangbaizhi, P&T may not be a suitable method for extracting the aroma-active compounds from _A. dahurica_. In addition, SPME, SBSE and DHS effectively extracted the terpen and aldehydes. However, these three methods were not ideal for the extraction of aromatic species, alcohols, ketones, acids, and esters. Although there may have been low contents of these compounds in the samples, it is likely that the headspace extraction method may not effectively extract all types of aroma compounds; thus, incorporating a solvent extraction step into the method may be necessary. The SPME method is simple and consumes a small amount of material, while the SBSE and DHS methods require cold trapping technology, which not only consumes a larger amount of material but is also expensive. Thus, future research focusing on the extraction of aroma-active compounds from the roots of _A. dahurica_ should be carried out using the SPME method.  
Figure 1: Types of flavor compounds extracted by SPME, P&T, SBSE, and DHS from Hangbaizhi, Qibaizhi and Bobaizhi.  
Figure 2: Quantities of the different kinds of flavor compounds extracted by SPME, P&T, SBSE, and DHS from the three kinds of _A. dahuriaa_: (**A**) Hangbaizhi, (**B**) Qibaizhi, and (**C**) Bobaizhi.
# Performance Evaluation of a Mesh-Topology LoRa Network
## 5 Proposed Approach: LoRaMesh  
For the purpose of this research article, we developed LoRaMesh, a novel LoRa-based multi-hop network protocol. The proposed network protocol is based upon LoRaWAN with changes and additions made to the packet headers and transmission scheduling, and additional reception windows. The right-hand side of Figure 2 provides an overview of the proposed mesh network. Nodes in the network can either act as up-link-only nodes (asillustrated by nodes 3, 5, and 6 in the figure), or have the additional functionality of being a relay node (as illustrated by nodes 1, 2, and 4 in the figure). Relay nodes receive LoRa packets from their assigned child nodes, queue the data in a buffer, and re-transmit the collected data, forwarding it to the next relay node or the gateway, if within reach. Relay nodes, as opposed to gateways, are single-channel devices and are mostly power-constraint. This research article will focus only on the up-link performance of the network; however, down-link messages could potentially be implemented in future work.