esa-sceva/satcom-chunk-collection huggingface dataset:
# Context-Aware Data Dissemination for ICN-Based Vehicular Ad Hoc Networks
## 2 Related Work
In summary, compared with the existing works related with VANET based on ICN, in this paper, we deal with the broadcast storm problem caused by the large number of both content request and response messages in ICN, and solve the problem by both suppressing the forwarding of the messages in a certain area, and by reducing the number of hops the packets traverse in VANET with the goal of improving the bandwidth usage, content delivery rate, and response time.
# Multilayered Network Model for Mobile Network Infrastructure Disruption
## 5 Routing in DRONET Layer  
The routing in DRONET layer is composed of two stages. The first stage is the Initial and search for MANET nodes to obtain positions of all nodes and possibly all MANET networks in the area. The second stage is routing itself, where the UAV communicates with MANET gateway nodes and within other Drones in order to provide a backup network for critical data transmission.  
Figure 10: The MANET Layer routing flowchart.
# Trends in Performance Limits of the HOT Infrared Photodetectors
## 5 2D Material Infrared Photodetectors
Due to high mobility, up to 3000 cm\({}^{2}\)/Vs, bP is a proper candidate for high sensitivity and fast speed photodetection. Recently published paper indicates that low bandgap 2D noble metal dichalcogenides could be novel platform for 300 K LWIR detectors [47]. From the practical applications point of view, the most important aspect is the stability of the material determining the reliability and lifetime of the device. This is a main disadvantage of most 2D materials. Due to only one or several-atoms thick of the active detector layer, 2D materials are susceptible to ambient environment (especially bP degrades quickly under 300 K conditions). The role of different ambient species has remained debatable [55]. The layered bP devices are still in development stage with many unsolved issues and ideas [56]. On the contrary, the air- stability properties have been demonstrated for noble metal dichalcogenides [47].
# Optimized Downlink Scheduling over LTE Network Based on Artificial Neural Network
## 5 Experimental Results
### Normalized Proportional Fair (PF) Algorithm
Overall, the results suggest that the GRNN-RBFNN hybrid model may be a more effective and accurate algorithm for downlink scheduling in an LTE network compared to the traditional PF algorithm. However, as with the results presented in Figures 4 and 5, it is important to note that the results presented in Figure 6 may be specific to the particular network scenario and conditions used in the study and can be directly applicable to other network environments.
# A Machine Learning Approach to Support Treatment Identification for Chari I Malformation
## 3 Results
\begin{table}
\begin{tabular}{l c c c c} \hline
**Measurement** & **Manual** & **Automatic** & **Difference** & **Paired Difference** \\ \hline Brain Area & 15,990 \(\pm\) 1523 & 15,632 \(\pm\) 1251 & 0.4\% (\(p\) = 0.27) & 6.5\% (\(p<0.05\)) \\ PF Area & 3343 \(\pm\) 702 & 3003 \(\pm\) 415 & 16.6\% (\(p<0.05\)) & 20.7\% (\(p<0.05\)) \\ Cerebellum Area & 2043 \(\pm\) 392 & 1895 \(\pm\) 363 & 7.0\% (\(p<0.05\)) & 16.4\% (\(p<0.05\)) \\ C/PF & 0.62 \(\pm\) 0.11 & 0.63 \(\pm\) 0.06 & \(-\)0.7\% (\(p=0.92\)) & 12.9\% (\(p=0.49\)) \\ PF/B & 0.21 \(\pm\) 0.03 & 0.19 \(\pm\) 0.02 & 12.4\% (\(p<0.05\)) & 16.7\% (\(p<0.05\)) \\ LenT & 42.1 \(\pm\) 15.7 & 40.5 \(\pm\) 6.1 & \(-\)0.5\% (\(p=0.82\)) & 23.1\% (\(p=0.47\)) \\ LenC & 46.6 \(\pm\) 12.6 & 46.3 \(\pm\) 8.5 & 0.8\% (\(p=0.52\)) & 13.3\% (\(p=0.46\)) \\ LenFM & 42.7 \(\pm\) 10.4 & 40.7 \(\pm\) 9.9 & 5.9\% (\(p=0.30\)) & 25.5\% (\(p=0.18\)) \\ DiaAntP & 74.8 \(\pm\) 20.3 & 75.5 \(\pm\) 6.5 & 7.2\% (\(p<0.05\)) & 12.1\% (\(p<0.05\)) \\ H\_PF & 56.6 \(\pm\) 12.4 & 52.3 \(\pm\) 7.9 & 6.9\% (\(p<0.05\)) & 14.1\% (\(p<0.05\)) \\ LenH & 15.9 \(\pm\) 7.7 & 11.8 \(\pm\) 4.3 & 14.4\% (\(p<0.05\)) & 31.9\% (\(p<0.05\)) \\ AngT & 1.13 \(\pm\) 0.23 & 1.08 \(\pm\) 0.16 & 1.3\% (\(p=0.24\)) & 15.1\% (\(p=0.18\)) \\ DPoFM & 38.3 \(\pm\) 6.5 & & & \\ DCCFM & 62.3 \(\pm\) 6.6 & & & \\ DFFM & 27.9 \(\pm\) 4.7 & & & \\ \hline \end{tabular}
\end{table} 
Table 1: Morphological measurements obtained manually or automatically (mean \(\pm\) std) and percentage difference of medians (either not paired or paired, with significance inspected respectively with Wilcoxon rank sum and signed rank tests). Areas are measured in pixels covered by the region, lengths in pixels and the angle in radiants. The number of processed MRIs is 58. Figure 5: Boxplots of the standard scores (median, quartiles, range and outliers indicated with diamonds) of the features grouped by the two classes of interest: patients showing improvements due to the surgical operation vs. no improvements. Each row stems from a different group of patients: (i) patients with syringomyelia at diagnosis, considering the automatic (**a**) and manual (**b**) delineation; (ii) patients without syringomyelia, using automatic (**c**) and clinical (**d**) measurements; (iii) all subjects together (with and without syringomyelia), using automatic features (**e**) and manual measurements (**f**). Figure 6: Bars providing the occurrence of features among the Leave-One-Out cross-validation strategy. Each row indicates a different group of patients: (i) patients with syringomyelia at diagnosis, considering the automatic (**a**) and manual (**b**) delineation; (ii) patients without syringomyelia, using automatic (**c**) and clinical (**d**) measurements; (iii) all subjects together (with and without syringomyelia), using automatic features (**e**) and manual measurements (**f**).
# A Study on the Roof-Cutting and Pressure Releasing Technology of Roof Blasting
## 4 Engineering Applications of Hard Roof Blasting
### Analysis of the Test Results  
#### 4.3.1 Coal Wall Stress Analysis  
Each group of stress receivers was spaced 0.5 m apart, and the burial depths were 8 m and 14 m, respectively. The shallow hole was close to the blast hole side. The initial value of the stress measuring point installation was set to 5 MPa, and the alarm triggered when the stress in the deep hole exceeded 12 MPa or the stress in the shallow hole exceeded 10 MPa. Two sets of stress receivers, located at the deep hole and the shallow hole, were placed on the coal wall at an interval of 20 m, and 15 groups of sensors were installed on the coal wall. During the blasting test, the stress receivers corresponding to the position of the borehole were numbered c3 and c4. The receiver was 180 m away from the working surface, and the specific layout is shown in Figure 10.  
The stress receiver output a set of data every minute. Three groups of stress-monitoring values were extracted to analyze the changes in coal seam pressure caused by blasting, creating a stress curve with the mean value, as shown in Figure 11.  
Overall, the closer to the working face, the greater the stress value. The stress at c3, c4, and c5 has a small variation range, but the stress at c1 and c2 significantly fluctuates. It shows that the roof rock layer is broken after blasting, and the range of the broken zone is about 20 m, close to the distance between the two sets of stress gauges. The radius of the crack zone of a single-hole blasting is about 5 m. The roof pressure is released to the depth of the coal seam and the working face, which can achieve a better pressure relief effect.  
Figure 10: Coal seam stress receiver layout.
## 2 Overview European XFEL
### The Experiment Hall and Ancillary Instrumentation
#### 2.4.2 Optical Lasers for European XFEL  
The usage of synchronized optical laser pulses is foreseen at all scientific instruments and opens various possibilities for time-resolved pump-probe studies and laser-controlled manipulation of electronic relaxation and excitation processes. A dedicated development has been initiated to meet the requirements of delivering 800 nm radiation, 10-100 fs pulse duration, 0.1-4.5 MHz selectable pulse delivery and 0.1-1 mJ pulse energy. After the successful completion of a first design phase [34] the implementation of three pump-probe burst-mode optical (PP) lasers systems was started, each serving one beam line area. The final amplification of the laser pulses employs the Non-collinear Optical Parametric Amplifier (NOPA) scheme. Three NOPA stages allow providing highest pulse energies at reduced repetition rate, 3.25 mJ for 0.1 MHz, and reduced pulse energies at highest repetition rate, 0.08 mJ at 4.5 MHz. A Pockels cell and polarizer before the NOPA amplifiers enable picking of arbitrary pump pulse sequences from the amplified burst at frequencies up to 4.5 MHz. An additional output delivers 1030 nm pulses with energies up to 40 mJ at 0.1 MHz and duration of 400 ps or 800 fs (compressed). Full performance of the system has been demonstrated recently [35]. In order to synchronize the delivery of optical laser and X-ray pulses, RF and optical lasers a laser-based synchronization system [36] is employed with the goal of reaching an accuracy better than 20 fs rms [37].  
The PP lasers are placed in dedicated laser rooms at each beam line. Laser beams are transported to dedicated instrument laser hutches (ILH) adjacent to the X-ray experiment areas. The separation from the X-ray hutch provides the possibility to work on these systems without disturbing the X-ray program. In the ILHs, e.g., delay stages, frequency conversion optics, and laser diagnostics are placed. Laser pulses are transported in a time stretched mode and final compression occurs close to the experiment location. Particular care needs to be taken with respect to the dispersion management of the optical laser pulses in order to achieve the shortest pulse duration.
# Road Safety Management of Uncontrolled Access Points:
## 2 Materials and Methods
### Identification and Selection of Traffic Accidents Attributable to an Access Point
#### 2.1.1 Upstream Functional Area  
The upstream functional area is identified by the distance LdxtTOT and it is the sum of the distance traveled during the perception-reaction time (Lpr) and the distance related to the deceleration manoeuvre (Ldx). LdxtTOT is defined as follows:  
\[\mathrm{L_{dxTOT}}=\mathrm{L_{pr}}+\mathrm{L_{dx}}=\mathrm{v_{1}}\cdot\mathrm{ t_{pr}}+\frac{\mathrm{v_{1}^{2}}-\mathrm{v_{2}^{2}}}{2\mathrm{d}} \tag{2}\]  
where:  
* v1 is the design speed of the main road (in this study v1 = 70 km/h and v1 = 50 km/h for rural and urban areas, respectively);
* v2 is the final speed of the vehicle turning into the access point. This speed must guarantee a safe and comfortable entering manoeuvre; thus, it must be compatible with the radius of the turning curve. In this study v2 = 0 given that: (i) the transition does not have a curved radius shape for several accesses, (ii) in some situations, the limited entry width of the access point does not allow the simultaneous circulation of two vehicles, (iii) for access points with a small entry width, the presence of a stopped vehicle exiting the access does not allow the on-coming vehicle to complete the manoeuvre;
* d is the deceleration rate (2.00 m/s2 for both rural and urban areas [37]);
* tpr is the perception/reaction time. For access decisions, this parameter is affected by several conditions, such as the complexity of the context and the access design [38]. A review of the studies in this field allowed us to assume tpr = 2.8 s for the rural context [24] and tpr = 1.5 s for the urban one [39; 40].
# Numerical Parametric Studies on the Stress Distribution in Rocks around Underground Silo
## 1 Introduction  
In Korea, the Wolsong Low and Intermediate Level Radioactive Waste Disposal Center (WLDC) at Gyeongju in North Gyeongsang province has a plan to construct a facility with a total capacity of 800,000 drums. The WLDC site is located in the southeast of the Korean Peninsula (see Figure 1) [1]. The first phase of the facility, an underground silo for the disposal of low- and intermediate-level radioactive waste (LLW) with a capacity of 100,000 drums, was completed in 2014 (see Figure 2) [2; 3; 4]. Low-level radioactive waste mainly consists of items such as filters, work clothes, gloves, and replacement parts for devices used routinely in nuclear power plants. Intermediate-level radioactive waste includes radioisotope (RI) waste generated by hospitals, industries, and research institutes. Low- and intermediate-level radioactive waste must be managed safely and according to strict protocols for a certain period of time in accordance with government regulations and guidelines. Such waste is permanently disposed of in the WLDC.  
It is essential to conduct a safety evaluation that comprehensively considers various types of impact on sites under construction or on the operation of nuclear facilities such as nuclear power plants, low- and intermediate-level radioactive waste disposal facilities, and spent fuel storage [5; 6; 7; 8]. The Wolsong LILW facility's first phase was constructed 130 m below sea level, and consists of six sils, 50 m in height and 23.6 m in diameter (see Figure 3) [3; 9]. Many studies have been carried out and published to verify its safety assessment since the facility was completed [9; 10].  
Figure 1: Location of the WLDC site in Korea.  
Figure 3: Side view of underground construction of LILW disposal facilities.  
Figure 2: Layout of LILW disposal facilities.  
Large-scale earthquakes occurred in 2016 and 2017 in Gyeongju and Pohang, respectively. Both arears are near the WLDC, and interest in the stability of the underground silo increased significantly [11; 12]. However, unfortunately, there has been little research on the stress distribution in the rocks around the underground silos used as LILW disposal facilities [13].  
Therefore, this paper presents numerical parametric studies on the stress distribution occurring in the surrounding rock mass around an underground silo which was constructed as a facility for the disposal of low- and intermediate-level radioactive waste. The 2D axial symmetric finite element model was used. The 3D finite element model was also used to verify the reliability of the 2D axial symmetric model. Finite element analyses of the underground silo were performed under various changes in the value of Ko, and the numerical results obtained through these analyses were also examined.
# A New Method for Detecting Onset and Offset for Singing in Real-Time and Offline Environments
## 3 The Proposed Algorithm
### Calculating the Summation of Slopes in the following Line  
In singing, transitions can be observed as the singer moves from one note to another. An example of this is outlined between the two pairs of orange-colored lines in Figure 4.  
Figure 3: Analyzing the pitch contour. (**a**) The original pitch contour of three notes, the first two notes are the same, and the third one is lower than the previous notes, (**b**) the stretched estimated values for the fundamental frequencies in (**a**), and (**c**) the slope of the pitch contour computed using differentiation. The red lines show the possible points for offsets, and the green lines are possible onsets.  
Figure 2: The effect of stretching on pitch contour’s slopes. (**c**,**d**) are the stretched pitch contours of (**a**,**b**), respectively.  
In this step, the summation of the following points' slopes is calculated to find the transitions at each point. In other words, as far as the direction of the line (upward, downward, or straight) in the stretched pitch contour remains the same, the slopes between every two consecutive points would be added to each other. The algorithm is depicted in Figure 5, where \(i\) is the current point in this figure.  
The algorithm commences by computing the cumulative sum of the consecutive points in the slope representation. In other words, their amplitudes, the values on the \(y\)-axis in  
Figure 4: Points’ statuses on a pitch contour. There are three notes: F4, F4, and E4, in order, sung by a professional female singer. The average pitch frequencies of the notes are 399, 362, and 323 Hertz, respectively.  
Figure 5: Calculating the summation of the following slopes of the differentiated contour.  
Figure 3c, are summed. According to the evaluation of several manually annotated onsets, offsets, and transitions, it is observed that there is a sharp upward or downward movement between two consecutive notes in a pitch contour. Therefore, a heuristic function implemented using decision logic is applied to assess how much change happens after each new point. In addition, it is found how many consecutive points have the same sign as the current point's slope: that is, how many of the successive values are heading in the same direction. The function denotes this in Figure 5, which is named Number of Same Slope Direction \((Point_{i})\).  
Therefore, the algorithm, at this point, detects when the slope changes sign.
## 2 Methods
### MVSS Beamforming Imaging  
Figure 1 shows the workflow of MVSS beamforming, which is divided into three parts: (1) signal delay; (2) superposition with calculated weights from minimum variance matrix in subarrays; and (3) imaging and processing, including time-depth conversion and shot stacking. The detailed mathematics can be found in Appendix A.  
First, the signal delay times are calculated according to the distance from the target point to each receiver and the background velocity. At the top of Figure 1 is a target point in the detection area. The waves reflected from the target point are received by the array, which is arranged in a straight line. The signals recorded by the receivers have different arrival times because the receivers are situated at different distances from the target point. Thus, delay processing (\(\tau_{1}\dots\tau_{5}\)) is applied to these signals so that the fluctuations from this target point are aligned on the time axis.  
Second, the signals from different receivers are superimposed with an MVSS beamformer. Calculating the superposition (\(\sum\)) with weights (\(\omega_{1}\dots\omega_{5}\)) of the delayed signals amplifies the signals from the target point while suppressing the reflections from other scattering points in the imaging area. The weights are calculated from a minimum variance matrix of subarrays with diagonal loading to enhance robustness. The weights are designed to minimize the output interference-plus-noise power while maintaining a distortionless response to the target signal. Then, the CF is used as a weight matrix to enhance the image, which can obviously amplify the reflection signals.  
Finally, after performing time-depth conversion and stacking the images of all shots, we obtained the beamforming result. Underground structures can be determined by the amplitudes in the image, where a higher amplitude corresponds to a greater possibility of a reflection interface or a stronger reflection.
## 3 Preliminaries
### BoX-MACProtocol in MAC Layer  
The proposed protocol incorporates an existing medium access control (MAC) protocol at the MAC layer inspired by the BoX-MAC scheme [53]. BoX-MAC offers two operational modes: one that utilizes acknowledgments (ACKs) and another that does not. In this study, we adopt the ACK-enabled mechanism, where data are transmitted directly alongside the beacon. Each node operates on an independent duty cycle without requiring synchronization among nodes. However, the entire network follows a common sleep interval. BoX-MAC is a sender-initiated protocol, meaning that transmissions are triggered by the sender node. Upon waking, a node passively listens to the channel to determine if it is occupied. If no data are queued for transmission, the node remains silently active, continuing to monitor the channel until the active period expires.  
We selected BoX-MAC due to its widespread support in the Castalia simulator and its ability to work with asynchronous duty-cycled WSNs. In line with the FCM-OR design,  
Figure 2: System model.  
Box-MAC minimizes idle listening and does not require global synchronization. By decreasing forwarder redundancy at the routing layer, we mitigate its disadvantages, which include increased ACK traffic and limited adaptability under high contention.  
On the other hand, if a node has a packet to transmit, it first verifies the channel's availability. Once the channel is clear, the node immediately sends the packet and waits for an acknowledgment (ACK) from the receiver. The node continues transmitting the packet periodically in this sequence until an ACK is received. Upon receiving the ACK, the sender terminates further transmissions from the MAC layer. If no ACK is received within a predefined timeout period, the transmission process is halted. An example of the data transmission process implemented in the BoX-MAC protocol is illustrated in Figure 3.
## 4 Discussion of FE Results
### Damage Mechanism  
For the global and local analysis of parametric FE results, a key role is assigned to the detailing of stress peaks distributions and damage initiation/evolution in all the joint components. For the examined TTC configurations, the collapse detection of PO specimens was typically associated to a combination of:  
* crushing phenomena in timber (in the region of screws);
* progressive yielding of screws and
* damage of the CZM contact (screw-to-timber interface).  
A relevant example is proposed in Figure 9 (S#1 specimen with \(\alpha=-15^{\circ}\), at an imposed slip \(s=12\) mm). In the direction of the grain, the wooden fibers were generally subjected to high stresses peaks in a limited region only, when moving far away from the fasteners. This can be noticed in the crushed (red) regions of Figure 9a. The STSs in use, moreover, commonly failed due to the occurrence of two plastic hinges (Figure 9b), and this is in line with the experimental observations reported in [6]. For all the examined TTC joints, finally, a primary role was recognized for the CZM contact, being responsible of the final slope for the collected force-slip curves. In Figure 9c, in this regard, the non-dimensional CSMAXCRT parameter is shown (1 = fully damaged or 0 = undamaged interface). This parameter, for most of the examined joints, was observed to reach its maximum unitary value of failure with an extension up to \(\approx\) 1/3 rd the nominal length L for the STSs in use.  
Figure 9: _Cont._