esa-sceva/satcom-chunk-collection huggingface dataset:
# Resolving Persistent Packet Collisions through Broadcast Feedback in Cellular V2X Communication +
## 5 Conclusions  
In LTE V2X Sidelink Mode 4 and NR V2X Mode 2 that utilize SPS for resource allocation, packet collisions may last for seconds on end if two or more transmitters select the same resource, which can be concerning for driving safety. As HARQ feedback is not supported for broadcast transmission in either LTE V2X or NR V2X, the half-duplex transmitters by themselves cannot realize the packet losses induced by the persistent packet collisions. This paper proposes a feedback scheme for the broadcast traffic. Because broadcast receivers can lie in various distances and channel conditions, in principle they can provide conflicting feedbacks as to whether a packet collision actually occurred. This is one of the reasons why the current standard framework has not specified a broadcast feedback mechanism. However, this paper demonstrates that designing an effective broadcast feedback mechanism is feasible. The keys to designing one is to first define the region of interest, then understand the relations between RSSI, SINR, and IBE conditions for the feedback provider. Extensive simulation shows that a carefully designed feedback scheme can indeed solve the persistent packet collision problem by practically eradicating them while maintaining the packet reception ratio. Finally, by way of reserved bits or the reservation pointers in the SCI, the proposed scheme can be implemented without excessively modifying the current standard cellular V2X framework. As the safety communication in V2X heavily depends on the broadcast transmission, the proposed scheme that improvesits reliability can be a small but significant building block. In the future, further work is necessary to expand the application of the proposed feedback scheme to other problems in broadcast V2X communications, such as half-duplex and hidden-terminal problems.  
Conceptualization, H.K. and Y.Y.; methodology, H.K.; software, Y.Y.; validation, H.K. and Y.Y.; formal analysis, H.K.; investigation, Y.Y.; resources, Y.Y.; data curation, H.K.; writing, H.K.; visualization, Y.Y.; supervision, H.K.; project administration, H.K.; funding acquisition, H.K. Both authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A2C3011888).  
Not applicable, the study does not report any data.  
The authors declare no conflict of interest. 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.
# Effects of Different InGaN/GaN Electron Emission Layers/Interlayers on Performance of a UV-A LED
## 3 Results and Discussion
The threading dislocation (TD) density can be calculated from the FWHMs of the XRD rocking curve (002) and (102) by Equation (1) [22]. \[\mathrm{N}=\frac{\beta^{2}}{4.35*|b|^{2}} \tag{1}\]  
where N is the TD density, \(|b|\) is the magnitude of the Burgers vector (\(\mathrm{b_{e}}=\frac{1}{3}\big{(}11\overline{2}0\big{)}\)and \(\mathrm{b_{s}}=\langle 0001\rangle\), respectively) [23], and \(\beta\) is the FWHM of the XRC. According to Equation (1), the density of screw dislocation in the GaN layer is \(1.48\times 10^{8}\), \(1.42\times 10^{8}\), and \(1.25\times 10^{8}\) cm\({}^{-2}\), and density of edge dislocation is \(5.60\times 10^{8}\), \(5.09\times 10^{8}\), and \(4.31\times 10^{8}\) cm\({}^{-2}\) for UVLED-I, -II and -III, respectively. After fabrication of the UVLED chip based on the material structures with InGaN/GaN/AlGaN MQWs grown on Al\({}_{2}\)O\({}_{3}\) substrates, optical and electrical device performance was characterized. Figure 6a shows the current-voltage (I-V) curves measured from all of the fabricated UVLEDs in linear scales. The measured I-V characteristics show a voltage turn on at 3.19, 3.15, and 3.12 V for UVLED-I, II, and III, respectively. The lower forward voltage can be attributed to the low surface resistivity and low leakage current, forming a high current injection in the MQWs. The output powers of UVLED-I, II, and III are estimated to be 0.89, 1.04, and 1.21 mW, respectively, at a fixed injection current of 300 mA. As observed in Figure 6b, UVLED III shows 1.5 times greater light output power at 300 mA compared to UVLED-I. The inserts in the figure are the fabricated UVLED chip and light emission image at 300 mA injection current. Figure 6c shows the PL spectra of UVLEDs consisting of EELs and ILs with GaN barriers grown with TEGa and TMGa. The PL spectra were measured at room temperature using Nd:YAG laser (\(\lambda\) = 266 nm) with laser source power of 2 mW. As shown in Figure 6c, the PL spectra intensity of the UVLEDs with the TEGa-grown EELs and ILs was much higher than that of the UVLEDs grown with TMGa. The integrated PL intensity of UVLED-III increased by 2.8 times compared with that of UVLED-I. In addition, Figure 6d shows a comparison of the electroluminescence (EL) intensity of the UVLEDs at an injection current of 300 mA. The light intensity increased by 1.9 and 2.3 times for UVLED-III compared to UVLED-II and I, respectively. This enhancement of PL and EL emission intensity can be attributed to the low impurity density and the high crystal quality of epitaxial layers resulting in higher light extraction efficiency in UVLEDs. Figure 5: High-resolution X-ray diffraction (HR-XRD) rocking curves (**a**) of the (002) reflection and (**b**) the (102) reflections for the full structures UVLED-I, -II, and III.
## 5 Results and Discussion
### All Soils
(1997) [64] provide a suitable upper bound for the proposed empirical relation of this study. The other twenty-one correlations were constrained by these three functions. Furthermore, the proposed curve of the present study lies closest to that proposed by [PERSON] (1996) [26]. This study also explored correlating the shear wave velocity to corrected SPT-N values by applying several correction factors (Figure 4B). These correction factors are for the rod length (\(C_{R}\)), sampling method (\(C_{S}\)), borehole diameter (\(C_{B}\)), energy ratio (\(C_{E}\)), and overburden pressure (\(C_{N}\)). There are different equations for the correction of SPT-N values (\(N_{1}\))\({}_{60}\), but the equation applied in this work is as follows:  
\[N_{60}=N\times C_{R}\times C_{S}\times C_{B}\times C_{E} \tag{12}\]  
\[\left(N_{1}\right)_{60}=N_{60}\times C_{N} \tag{13}\]  
For overburden pressure correction, we adapted the equation proposed by [PERSON] et al. (1992) [69], which is as follows:  
\[C_{N}=\frac{2.2}{1.2+\frac{C_{R}^{\prime}}{P_{a}}} \tag{14}\]  
\(\sigma^{\prime}\)\({}_{vo}\) is the effective overburden pressure at the depth in kPa, and \(P_{a}\) is the reference pressure equal to 100 kPa. Rod length correction (\(C_{R}\)) was applied using the factors provided by [PERSON] et al. (2001) [70]. A sampling method (\(C_{S}\)) correction factor of 1 was used, as most SPT drillings in the Philippines utilize standard samplers. Borehole diameter (\(C_{B}\)) and energy ratio (\(C_{E}\)) factors were applied following the scheme of [PERSON] (1986) [71]. After the application of these correction factors, non-linear regression analysis was employed again, to determine the empirical function to correlate V\({}_{\text{s}}\) and corrected SPT-N values. Figure 4: _Cont._  
The determined correlation from the data is  
\[\mathrm{V_{s}=61.77(N_{1})_{60}}^{0.4528} \tag{15}\]  
This relation has a regression coefficient R\({}^{2}\) = 0.5685, indicating a moderate correlation, which is slightly lower than the regression coefficient when uncorrected SPT-N values are used in the analysis. This suggests that uncorrected SPT-N values correlate shear wave velocity better than corrected values. Figure 4: **(A). ** Uncorrected SPT-N and V\({}_{\mathrm{s}}\) pairs for all soils and the determined empirical correlation. (**B**). Corrected SPT-N and V\({}_{\mathrm{s}}\) pairs for all soils and the determined empirical correlation. (**C**). Comparison of the proposed empirical correlation for all soil types and other published works [8; 9; 12; 13; 14; 15; 16; 21; 23; 26; 28; 30; 34; 35; 52; 53; 57; 61; 63; 64; 65; 67; 72].
# Wavelet-Based Analysis of Motor Current Signals for Detecting Obstacles in Train Doors
## 5 Experimental Results
### Soft-Object Scenario  
Soft-object detection was tested by initiating door closure and placing an object between the doors approximately 30 cm above the bottom of the door. The current, norm, and peak profiles initially followed a similar pattern to the no-obstacle case until the object was detected. As shown in Figure 15a, at sample 375, the motor current increased to 2.53 A, leading to a rise in the W9 and peak amplitudes to 46.8 and 10.4, respectively. These observations from the figure satisfied the soft-object detection condition specified in the algorithm, prompting the door-closing program to halt.  
Additionally, Figure 15b illustrates the corresponding force signal, where the measured force on the soft object reached 105 N, matching the simulated value. These results validate the system's capability to detect and identify soft obstacles effectively.  
Figure 15: Results of soft-obstacle detection experiment. (**a**) W9 and peak amplitudes showing the response at the detection point; (**b**) motor current and force signals demonstrating the increased current and force at sample 375, triggering the detection condition and halting the door-closing program.
## 3 Proposed Algorithms
### Input Information Encoding  
One of the basic points during the modeling process of a natural problem is the way with which the factors which affect it will be encoded. What is more, one of the basics prerequisites is the possibility for the user to control some of the parameters so as to form the case to be solved.  
As far as the genetic algorithm developed is concerned, in every chromosome a possible solution to the problem of coverage and k-coverage in encoded, while the final solution of the problem represents the optimal positions where the nodes should be placed. The position of each node in the two-dimensional space is defined by a pair of coordinates (x, y) and if the number of the sensor nodes is M, then M pairs of coordinates are required to specify their positions. Also, if there are N points that require k-coverage, then N triad of values is needed, where every triad is composed by the coordinates of the point in the area and the k number which defines the necessary coverage for the point. All the aforementioned variables along with the number of nodes, the space limits, the sensing ranges of the nodes, and the sampling steps that are necessary in order to calculate the algorithm constitute the information which is encoded in every chromosome in the genetic algorithm. Respectively, as far as the PSO based algorithm is concerned, the same information is encoded in the particles of the swarm. The velocity and the position of each particle of the swarm were calculated according to Equations (1) and (2):  
\[V_{ij}(t+1)=w*V_{ij}+c_{1}*r_{1}*\left(y_{ij}(t)-x_{ij}(t)\right)+c_{2}*r_{2}* \left(\hat{y}_{j}(t)-x_{ij}(t)\right) \tag{1}\]  
\[x_{i}(t+1)=x_{i}(t)+V_{i}(t+1) \tag{2}\]  
where \(V_{ij}\) and \(x_{i}\) represent the velocity and the position of the i-th particle (from the total n particles) in the \(j\) dimension (from the \(J\) total dimensions) during the t-th execution of the algorithm respectively. Additionally, w represents the inertia of the particle, \(c_{1}\) and \(c_{2}\) symbolize acceleration coefficients, and \(r_{1}\) and \(r_{2}\) are random numbers in the range [0, 1].
# Comprehensive Assessment of the Dynamics of Banana Chilling Injury by Advanced Optical Techniques
## 2 Materials and Methods
### Chlorophyll-Fluorescence Analysis--Rapid Light Curves  
Rapid light curves (RLC) [35; 56; 57] were obtained at three positions distributed near stem-end, at the middle part and close to fruit tip with PAM fluorometers (MiniPAM, PAM2000, Heinz Walz GmbH, Effeltrich, Germany). After measuring the basic fluorescence signal, \(F_{0}\), the maximum fluorescence (\(F_{\rm m}\)) was obtained by applying a saturation light pulse (0.8 s; PPFR > 2.5 mmol m\({}^{-2}\) s\({}^{-1}\)). Then, actinic light was provided with a halogen lamp, fitted to the fluorometers, in nine steps for 30 s each (approx. 5, 10, 20, 30, 50, 70, 110, 155, and 235 mmol m\({}^{-2}\) s\({}^{-1}\)). At the end of each illumination period, the semi-steady-state fluorescence signal (\(F_{\rm t}\)) was measured, and a saturation pulse given to induce the maximum fluorescence signal obtained under light conditions (\(F_{\rm m}\)').  
From these parameters, initial \(F_{\rm v}/F_{\rm m}\) (variable fluorescence \(F_{\rm v}=F_{\rm m}-F_{0}\)) was calculated and the respective values of \(\left|\phi_{\rm PSII}\right.\left(\left(F_{\rm m}{}^{\prime}-F_{\rm t}\right)/ F_{\rm m}\right.\right)\), photosynthetic electron transport rates (\(ETR=\phi_{\rm PSII}\times PPFR\times a\times d\); with \(a\) (absorption coefficient, assumed as \(a=0.84\)) \(\times\)\(PPFR\) providing the number of absorbed photons and \(d\) (distribution coefficient, \(d=0.5\)) reflecting their assumed (equal) distribution between PSI and PSII. From the analysis of the relationship between \(ETR\) and \(PPFR\), the maximum photosynthetic quantum yield (\(\alpha\)) was obtained as the initial slope and \(ETR_{\rm max}\), the maximum light saturated electron transport rate obtained by fitting an exponential model [57]. Furthermore, from the above basic parameters, also the photochemical quenching coefficient (\(q_{\rm P}=(F_{\rm m}{}^{\prime}-F_{\rm t})/(F_{\rm m}-F_{0})\)), the non-photochemical quenching (\(NPQ=(F_{\rm m}-F_{\rm m}{}^{\prime})/F_{\rm m}\)'), and the quantum yields of regulated (\(Y_{\rm NPQ}=F_{\rm t}/F_{\rm m}{}^{\prime}-F_{\rm t}/F_{\rm m}\)) and non-regulated non-photochemical energy loss in PSII (\(Y_{\rm NO}=F_{\rm t}/F_{\rm m}\)) were calculated for each \(PPFR\) step (c.f. [35; 58]).
# Full-Scale Train Derailment Testing and Analysis of Post-Derailment Behavior of Casting Bogie
## 4 Conclusions  
This study presented full-scale train bogie derailment test methodologies and post-derailment behavior based on the test results. The derailment tests were conducted at the bogie level, and the test speeds were 28.08 km/h and 55.05 km/h. The major findings of this study are as follows:  
1. Train bogie derailment tests can be successfully conducted by using the methodologies proposed in this study. A push system and automatic release device for the test bogie were proposed. Also, a derailment device to induce wheel-climbing derailment and a simultaneous trigger system to synchronize different pieces of equipment were suggested. The proposed methodologies may be applicable to other types of full-scale derailment tests.
2. For the test in Case #1 (derailment velocity of 28.08 km/h), the derailed bogie ran the track with significant right (direction of derailment) lateral movement, and the left (opposite direction to derailment) wheel continuously came into contact with the hump of the concrete track. Then, the bogie moved to the left without contact between the right rail and left wheel. This indicates that the lateral movement for Case #1 was controlled by the humps, and the humps in this track significantly affected the post-derailment behavior of the derailed bogie. In Case #1, the maximum vertical acceleration was approximately 5.57 g at the second impact with the hump. The maximum lateral acceleration was approximately 2.62 g at the first impact with the hump.
3. For the test in Case #2 (derailment velocity of 55.05 km/h), the maximum vertical impact to the track was observed at 0.460-0.560 s, and the maximum vertical acceleration was approximately 3.53 g. The test bogie ran the track with considerable lateral movement, similar to Case #1. However, in Case #2, the wheel flange came into contact with the rail, and then the test bogie impacted the containment wall. The lateral acceleration values were approximately 1.17 g and 0.75 g for the rail and containment wall impacts, respectively. Thus, it was found that the impact force on the containment wall was reduced by approximately 36% by the first guide by the rail. Finally, the test bogie returned to the track center direction after containment wall impact.  
Investigation, Conceptualization, Methodology, Data Curation, Project Administration, Supervision, Writing (original draft, review & editing) from [PERSON], [PERSON] and [PERSON]; Experiment, Data processing from [PERSON] and [PERSON]. All authors have read and agreed to the published version of the manuscript.  
This research was supported by a grant (19 RTRP-B122273-04) from the Railway Technology Research Program, funded by the Ministry of Land, Infrastructure, and Transport of the Korean government.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Geometric Model of Brace  
Based on the existing orthosis shown in Figure 1, a 3-dimensional (3D) computer model of the orthosis was generated using reverse engineering techniques--3D scanning. As shown in Figure 4a, the braces were subjected to processes to prepare them for proper scanning [23]. The brace was stiffened for 3D measurement by adjusting the belt at the level of the drawstring straps (1). The surface of the orthosis was covered with matting material (2), and reference points (3) were pasted on to allow subsequent 3D scans to be spatially correlated. An optical scanner, the Atos Core 200 (GOM--a ZEISS company, Brunswick, Germany), was used to create the point cloud. After preliminary, rough processing, an STL triangle mesh represented as a binary mapping of 3,547,641 elements was obtained from the point cloud. For this purpose, 35 exposures were applied, using 28 markers. The fastening buckles were removed from the model, artefacts were repaired, and losses were filled in using Geomagic Wrap 2017 point cloud processing computer software (3D Systems, Rock Hill, SC, USA). A representation of the outer surface of the brace was created on such a modified mesh. The next step was to create, on the basis of this surface, a 4 mm thick shell that corresponds to the brace's structure as defined by NURBS splines. Through such processing of the point cloud, a model was created to represent the actual orthoses (Figure 4b). In addition, at the level of the apex of the spine curvature, an interior pad and a soft material corrective ring were modelled. The 3D model for the brace was created and then exported to the Ansys 2021 R2 (21.2) for finite element (FE) numerical calculations.  
Figure 4: Reverse engineering as the process of creating a 3D model of an orthopaedic brace from the actual facility: (**a**) orthosis ready for scanning: 1—fixing brace stiffener, 2—matted outer layer of the orthoses, 3—reference markers, (**b**) CAD computer model of the orthosis.
## 2 Materials and Methods
### Tree-Ring Width Analysis  
In November 2018 (30 months after spring burning and 24 months after autumn burning), one core was extracted from each selected _P. nigra_ tree at breast height (\(n=135\) in each stand; they were the same trees used to estimate burn severity at tree level), perpendicular to the terrain slope, with an increment borer (0.5 cm inner diameter) [22]. All cores were prepared following standard dendrochronological techniques [55]. The cores were mounted on grooved boards and sanded until the tree rings were clearly visible.  
Tree ring widths were measured using a tree ring measuring stage with a precision of 0.01 mm (Lintab \({}^{\text{TM}}\), Rinttech, Heidelberg, Germany) and recorded in a computer with TSAP software [56]. Our study species at our study site formed clearly defined rings boundaries with abrupt transitions between late wood and early wood [57]. All cores were dated and visually cross-dated to detect the presence of false and incomplete rings. COFECHA software was used to check cross-dating and validate measurement quality [58] (Table 3). The ring widths were converted into annual basal area increments (BAI) by using the equation \(\text{BAI}=\pi\left(\text{r}^{2}\text{t}-\text{r}^{2}_{\text{(t-1)}}\right)\), where \"r\" is the tree radius and \"t\" is the year of tree-ring formation. BAI was used as a proxy for tree growth because it is less dependent on age and thus prevents the need for detrending [59], which could also remove low frequency variability. In addition, the BAI was standardized and shown in box plots. The standardization was performed using the mean tree growth value of the immediately five preceding years unaffected by the burning treatment (2010-2015).
# Study of the Effect of Laser Radiation Parameters on the Efficiency of Lithotripsy
## 1 Introduction
Thulium lasers are universal in the treatment of kidney stones of various chemical compositions and have power comparable to holmium lasers [11; 22]. Another promising direction is to reduce the laser pulse duration, which, due to the physical basis of laser interaction with the substance, proportionally reduces the thermal influence zone, shock wave impact, and residual fraction size [23; 24; 25; 26]. The main accompanying processes of calculus crushing by ultrashort pulse (USP) laser radiation are the formation of a plasma torch and the evaporation of the target material. At high peak powers of laser radiation in the focusing spot region, the radiation is rapidly absorbed, causing the development of local nonlinear processes and instabilities, which is accompanied by shock wave development in the environment [12; 13; 14; 15; 27]. At the same time, these shock waves have much lower energy than those generated by lasers with high pulse energies, which are used in LL today. In this regard, a promising development direction may be the application of ultrashort pulse fiber lasers generated in the near-infrared range with high energy and short pulse duration to create laser lithotripers. The main advantage of lasers in this spectral range is the reduced absorption of radiation by water molecules. This feature will minimize the heating of the fluid in the kidney parenchyma and increase the efficiency of renal calculi destruction. At the same time, the relatively low energy of USP laser pulses, combined with their high peak power, will make it possible to destroy kidney calculi without a large shock wave effect on kidney tissue. For example, a femtosecond laser Coherent Hidra 10 with a wavelength of 800 nm, pulse energy of the order of 0.64 mJ, a pulse duration of 140 fs, and processing power density of 107 W/cm\({}^{2}\) showed in [28] the possibility of ensuring the residual fraction size in the range from 1 to 20 um. The mechanism of such laser treatment is photoionization and differs from the photothermal one by the essential decrease of shock wave influence from 1.5 bar when using a nanosecond pulse duration to 0.4 bar when using a laser pulse duration of 0.1 ps [28]. In this regard, the purpose of this study is to experimentally establish the influence of the main characteristics of laser radiation, such as the generation wavelength, energy, and pulse duration, on the efficiency of laser lithotripsy of renal calculus samples and their phantoms, among which the main focus was on the performance when removing the material volume in a unit of time, as well as the processed sample displacement due to the retropulsion phenomenon and environmental thermal heating, which should not exceed 40 \({}^{\circ}\)C.
## 8 Conclusions and Ongoing Work
_AADL for the OS simulation and verification:_ The AADL (Architecture Analysis and Design Language) is a model-based engineering language used to analyze the reliability, availability, timing, responsiveness, throughput, safety and security of the software and hardware architectures [44]. In the ongoing work, the AADL will be used in MIROS to achieve the objective of developing a formal verifiable, highly reliable, fail-detectable and self-recoverable system.