esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Algorithm Description
### First Stage: Deleting Undesired Activities  
On the first stage of the proposed schema, undesired activities selected by the user must be removed. The resulting model must be still coherent. Therefore, the algorithm must delete the appropriate sequence flows in the BPMN models too (i.e., sequence flows connecting the deleted  
Figure 8: Opening a bank account. (**a**) All the operations; (**b**) Operations involving interaction with the bank staff.  
activity). Also, new sequences connecting the surrounding elements of a deleted activity (previous with next ones) must be created. In Figure 8 an example is shown of the input and the output of this stage, in case of aiming at getting a simplified version of the workflow for operations requiring interaction only with the bank staff, Figure 8a (representing the input) is considered as the starting point. In this line, Figure 8b represents the output model where sequence flows replace the operations without interaction with bank staff.  
As the reader can note, in this new model, not all elements in Figure 8b are required to represent the desired behaviour. This issue will be tackled later on, on the second stage of the algorithm.  
A fragment of the Java implementation for the first stage is presented in the Listing 3. The first stage function loops over the list of activities to be deleted and removes the activities defined by the user. To delete one single activity it is mandatory to establish a direct connection between the previous element and the upcoming one (another activity, a gateway, etc.). Upon the new connection is created, it is possible to delete the old activity and the old sequences as they are no longer of any use in the model.  
```
1 publicBpmnfirstStage(Bpmnmodel,ArrayList<BpmnId>tasksToDeleteIds){
2 for(IdtaskToDeleteId:taskToDeleteIds)
3{//Searcheachtasktodelete...
4 BpmnTasktaskt2 Del=model.searchTaskById(taskToDeleteId);
5
6//...anddeleteitsafetely
7 model=this.deleteTask(model,task2 Del);
8}
9 returnmodel;
10}
11
12//Deletesataskinasafetelyway
13 privateBpmndeleteTask(Bpmnmodel,BpmnTasktask2 Del){
14
15//SearchsequencesIds
16 BpmIdinSeq=task2 Del.getInSequenceId();
17 BpmIdoutSeq=task2 Del.getOutSequenceId();
18
19//Searchelementsbefore/afterthesesequences
20 BpmIdelmntBeforeTaskId=model.getSequenceById(inSeq).getSource();
21 BpmIdelmntAfterTaskId=model.getSequenceById(outSeq).getTarget();
22
23//Newconnectionskippingtheactivity
24 model.createSequenceBetweenElements(elmntBeforeTaskId,elmntAfterTaskId);
25
26//Deletesactivityandoldsequences
27 model.deleteTask(task2 Del);
28 model.deleteSequence(inSequenceId);
29 model.deleteSequence(outSequenceId);
30
31 returnmodel;
32}
```  
Listing 3: First Stage Java code.  
In this first stage, a simple method to remove the undesired activities is used: to delete one, a direct connection between the previous element and the upcoming one (another activity, a gateway, etc.) is established. Upon the new connection is created, it is possible to delete the old activity and the old sequences as they are no longer of any use in the model.
## 2 Materials and Methods
### Computed Tomography Simulation  
CT simulation was performed on an anthropomorphic torso phantom (CT torso phantom CTU-41, Kyoto Kagaku America Inc., Torrance, CA, USA) using a Philips Brilliance CT scanner (Philips Medical Systems, Cleveland, OH, USA) (Figure 2). This was used since phantom materials with radiation absorption approximates to human tissue (heart, aorta, and vena cava: 40 Hounsfield unit (HU); pulmonary vessels: 8 HU; rib cartilage: 90 HU; and liver: 70 HU) and allows scanning under actual clinical settings. To reproduce TE insertion following mastectomy, a male phantom was used with two types of TE, which were equally set to 345 cc and attached on the left chest wall. TEs were adjusted to be in the same position by referring to three-plane CT imaging. Afterwards, 2.5 mm thick axial images were acquired for RT planning. To reduce CT artifacts caused by the metal implants, a commercial metal artifact reduction for orthopedic implants (O-MAR, Philips Medical Systems, Cleveland, OH, USA) was also applied to the CT images.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Traditional Expander** & **Motiva Flora®** \\ \hline Identification of port location & Magnet & RFID coil \\ Material & Neodymium & Copper \\ Density & 7.01 g/cm\({}^{3}\) & 8.96 g/cm\({}^{3}\) \\ Diameter & 13.3 mm * & Outer: 24.7 mm \\  & & Inner: 20.3 \(\pm\) 0.2 mm \\ Height & 4.4 mm * & 2.150 \(\pm\) 0.1 mm \\ \hline Needle guide & & \\ Material & Stainless steel & Polyetheretherketone \\ Density & 7.5–8 g/cm\({}^{3}\) & 1.3 g/cm\({}^{3}\) \\  & & Dome: 40.1 mm *, \\ Diameter & 36.5 mm * & Needle stop: 26.8 mm * \\  & & Base: 42.5 mm * \\ Height & 10.0 mm * & 12.9 mm * \\ Thickness & 2.1 mm * & 1.5 mm * \\ \hline \hline \end{tabular}
* Average value of five individual measurements. RFID, radio frequency identification device.  
\end{table}
Table 1: Characteristics of breast tissue expanders.
## 4 The Seismic Performance Parameters of RCS Composite Joints Under Floor Effect Are Studied
### The Influence of Floor Thickness on Seismic Performance of Nodes
#### 4.2.2 Curve Characteristics and Ductility  
Under cyclic loading, the increase in slab thickness has a minimal effect on the shape and trend of the hysteresis curves. However, the improvement in the joint's bearing capacity during positive loading is more pronounced compared to negative loading. Different slab thicknesses enhance the load-bearing capacity of nodes (increasing by 4.8-9.5% in the positive direction), primarily due to the improved compressive strength and the shift of  
Figure 18: Comparison of failure modes of different floor thickness nodes. (**a**) Destruction morphology of node FJD-0; (**b**) Destruction morphology of node FJD-5; (**c**) Destruction morphology of node FJD-6.  
the neutral axis. The fullness of the hysteretic curve increases, demonstrating stronger load-bearing and energy dissipation capabilities, though it has a lesser impact on the shape of the curve. The skeleton curve shows that the thicker the slab, the higher the ultimate load-bearing capacity, but ductility slightly decreases (by about 1.7-3.7%). Therefore, the slab thickness should be reasonably selected to balance stiffness and toughness (Figure 19). The tabulated data showing the characteristic values of the skeleton curves for different slab thicknesses is represented in Table 5.
## 3 Long-Range, Low-Power IoT Communication Protocols and Their Security
### Summary of LPWA Networks  
In summary, Figure 6 and Table 6 highlight the LPWA networks' characteristics. There are many similarities. The payload sizes are very small, with the largest being 128 bytes in NB-IoT. Both LoRaWAN and Sigfox use a license-free spectrum, and the devices initiate uplink transmissions at random. Their performance depends on the number of devices per base station, the time for which the data are in the air (thus, small packet sizes are used), and the number of uplink data channels available. To support wide coverage areas and avoid losing packets, NB-IoT and Sigfox send the same message several times.  
As for security, the three LPWA network architectures use 128-bit AES-CTR mode for encryption and AES-CMAC for message authentication. AES-CTR mode has the following benefits: the same hardware or software can be used to encrypt and decrypt data and pre-processing can be done prior to encrypting the IoT device's data. According to [44], CTR mode makes a block cipher more versatile, as the block cipher becomes more similar to a stream cipher.  
In some cases, these architectures provide end-to-end confidentiality using the Encryptt-then-MAC approach; in other cases, the MAC-then-Encrypt strategy is adopted, which is not end-to-end.
# Process Optimization and Wear Performance of Plasma-Cladding Fe5 Coatings on Rotary Tillage Blades
## 3 Results and Discussion
### Structure and Properties of Fe5 Coatings Under Optimized Conditions
#### 3.2.3 Wear Performance of Fe5 Coatings  
Figure 8 presents the wear curves of the cladding layer and the substrate under wet sand rubber wheel abrasion testing conditions, with a load of 70 N, a sand-to-water ratio of 3:1, a quartz sand particle size of 40-70 mesh, and a rotational speed of 200 r/min. As the wear process continues, the wear volume gradually increases, as evidenced by the gradual elevation of the wear curves. However, the slope of the substrate is significantly steeper [36], indicating more severe wear, while the cladding layer exhibits relatively better wear resistance. Under identical wear durations, the weight loss of the Fe5 cladding layer is only 1/21 that of 65 Mn. Continuous wear testing of the Fe5 cladding layer in laboratory conditions reveals that the substrate begins to be exposed only when the wear distance reaches 150 km, at which point the coating starts to gradually lose its protective capability for the substrate.  
Using a DK7735-type CNC wire-cut machine, a sample of 10 \(\times\) 10 \(\times\) 6 mm was cut from the wear area of the specimen and observed under an SEM, as shown in Figure 9.  
Figure 8: Wear loss curves of the substrate and the plasma-cladding Fe5 coatings during the wet sand rubber wheel test.  
Figure 7: Hardness distribution of Fe5 coatings depends on the distance from the surface.  
From the figure, it can be seen that after wear, the surface of the 65 Mn steel is relatively rough, with numerous long and deep scratches and plough grooves spanning the entire wear surface. Additionally, there are extensive pits resulting from large-scale material loss. This phenomenon is attributed to the fact that during the wear process, quartz sand particles of various shapes come into contact with the substrate at different impact angles, leading to micro-cutting and micro-ploughing effects. Due to the lower hardness of 65 Mn steel, abrasive particles can easily penetrate the surface to a significant depth, leaving behind numerous deep scratches and plough grooves. Furthermore, repeated impacts by abrasive particles cause crack propagation in certain areas of the substrate, ultimately leading to extensive material loss. In contrast, the wear morphology of the Fe5 cladding layer exhibits a relatively smooth surface with shallow and less prominent scratches. The entire surface has fewer pits, indicating that the Fe5 cladding layer possesses superior wear resistance, effectively resisting the sliding and ploughing actions of abrasive particles.
## 4 Mission Reliability Modeling, Allocation, and Analysis Method Design
### Reliability Analysis Methodology Design
#### 4.3.1 Mapping of AADL to GO Method  
There is no way that the AADL reliability model can be directly used for accurate quantitative analysis of reliability. Therefore, the AADL reliability model needs to be converted into a GO map model that can be used for reliability analysis. The mapping relationship between the models is shown in Figure 8.  
Figure 7: Flowchart of mission reliability calculation algorithm.  
The list of operators corresponding to the constituent units of the reconfigurable ship electronic information system is presented in Table 6.
# Dynamic Path Planning for Unmanned Surface Vehicles with a Modified Neuronal Genetic Algorithm
## 6 Conclusions
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Input Number** & **Mutation Rate** & **Generation** & **Genome** & **Total Genome** & **Distance** & **Time** \\ \hline \multirow{6}{*}{3 inputs} & 0.025 & 13 & 37 & 557 & 267.42 & 80.52 \\ \cline{2-6}  & 0.055 & 11 & 5 & 445 & 255.96 & 44.06 \\ \cline{2-6}  & 0.105 & 18 & 2 & 722 & 256.62 & 66.25 \\ \cline{2-6}  & 0.155 & 5 & 0 & 200 & 266.07 & 35.67 \\ \cline{2-6}  & 0.205 & 9 & 8 & 368 & 258.20 & 55.44 \\ \cline{2-6}  & 0.255 & 5 & 4 & 204 & 260.91 & 77.00 \\ \cline{2-6}  & \multicolumn{3}{c}{Average} & \multicolumn{3}{c}{416.00} & 260.86 & 59.82 \\ \hline \multirow{6}{*}{5 inputs} & 0.025 & 15 & 6 & 606 & 261.62 & 38.18 \\ \cline{2-6}  & 0.055 & 19 & 0 & 760 & 256.11 & 73.35 \\ \cline{2-6}  & 0.105 & 6 & 0 & 240 & 263.27 & 60.87 \\ \cline{2-6}  & 0.155 & 17 & 19 & 699 & 255.57 & 81.94 \\ \cline{2-6}  & 0.205 & 13 & 4 & 524 & 254.34 & 30.76 \\ \cline{2-6}  & 0.255 & 13 & 2 & 522 & 258.79 & 33.27 \\ \cline{2-6}  & \multicolumn{3}{c}{Average} & \multicolumn{3}{c}{558.50} & 258.28 & 53.06 \\ \hline \multirow{6}{*}{7 inputs} & 0.025 & 17 & 36 & 716 & 270.44 & 78.50 \\ \cline{2-6}  & 0.055 & 1 & 32 & 72 & 271.06 & 48.56 \\ \cline{2-6}  & 0.105 & 24 & 1 & 961 & 269.28 & 43.37 \\ \cline{2-6}  & 0.155 & 26 & 1 & 1041 & 268.33 & 64.45 \\ \cline{2-6}  & 0.205 & 24 & 0 & 960 & 269.12 & 76.15 \\ \cline{2-6}  & 0.255 & 21 & 0 & 840 & 261.55 & 40.60 \\ \cline{2-6}  & \multicolumn{3}{c}{Average} & \multicolumn{3}{c}{765.00} & 268.30 & 58.61 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Detailed results from dynamic environment experiment using baseline method (NNGA).
# Reliability Analysis of Hybrid Laser INS Under Multi-Mode Failure Conditions
## 2 Mechanical Simulation Analysis of Hybrid Laser INS Structure
### Mechanical Simulation Analysis of the Hybrid Laser INS Structure  
2.1 Structural Mechanical Simulation Model of the Rotational Modulation Mode for Angular Motion Isolation  
The current mainstream inertial navigation systems are platform inertial navigation systems and strapdown inertial navigation systems. Strapdown systems, through the addition of a frame rotation device, effectively address self-calibration and rapid, precise self-alignment under installation conditions, achieving \"three self\" functions. However, during flight, the frame remains mechanically locked, meaning it essentially still functions as a strapdown system, and errors caused by missile body angular motion cannot be fully eliminated, limiting accuracy improvements.  
The hybrid laser INS is a new type of INS designed to meet the demands of high-dynamic, long-duration aerospace vehicles. To improve navigation accuracy under such conditions, it utilizes frame stability control to isolate interference from carrier angular motion during navigation. This method, combined with the strapdown algorithm in rotational modulation, suppresses coupling errors between angular and linear motion, effectively separating and compensating for accelerometer drift and partial gyroscope errors. This aims to meet new accuracy requirements for high-dynamic, long-duration carriers.  
This paper investigates the mechanical behavior of a hybrid INS structural mechanical simulation model in the rotational modulation mode for angular motion isolation, focusing on its performance under high dynamics and large overloads. The structural mechanics simulation model of the rotational modulation mode with angular motion isolation is shown in Figure 2. Frame stiffness directly determines load-bearing capacity, with the inner and outer frames, shaft-end modules, and rotation locking mechanism working together to achieve rotation and positioning of the shaft systems. Figure 2 shows a simplified model diagram of the hybrid INS structure, and Figure 3 shows a simplified model diagram of the outer frame assembly.  
Figure 1: System principle diagram of hybrid INS measurement unit.
## 3 Results
### Validation: Comparison of Experimental and Numerical Results  
The model of the composite plate with variable elastic modulus is adopted for simulating the four-point bending test. Results of the numerical force-displacement curve are then compared to those obtained with the progressively damaged plate. As shown in Figure 9, experimental and numerical results are in very good agreement, with limited discrepancies in slope. Results of numerical analysis are once again reported from 1 mm of displacement. The numerical displacement is measured on the rigid cylinders and these are initially distanced from the composite laminate, in order to avoid penetrations and numerical instabilities. Consequently, the initial path of the numerical force-displacement curve concerns the contact between laminate and cylinders and is not significant for the purpose.  
Experimental response shows an increasing stiffness as the plate is bent. This hardening effect can be explained by taking into account that the considered material fails under compressive loads, as shown in Figure 4. The four-point bending tests are repeated until incipient failures occur. Consequently, cracks propagate in the upper layers subjected to compressive loads. When testing the composite plate, these cracks are progressively closed under compression. This allows to sustain loads in the failed layers and an increasing stiffness is thus obtained. The hardening effect can be also appreciated in the force-displacement curves with progressive damage of Figure 5 (dotted lines).  
The limited discrepancy between experimental and numerical results highlights the accuracy of the \(DI_{d}\) technique in mapping the residual elastic properties of the damaged plate. Further, this result validates the proposed approach which accounts for the variable elastic modulus with a continuous polynomial curve in the finite element model.  
Figure 8: Top view of the finite element model of the composite laminate: longitudinal division of layers.
## 6 Data Transmission Comparison
The ASE spectrum-sliced source can reach \(Q^{2}\) values of 7.3 dB at a \(-\)31 dBm received power. The externally seeded RSOA and the RSOA-FCL reach \(Q^{2}\) values of 17 and 12 dB, respectively. The impact of the dispersion of the NZDSF on the externally seeded RSOA scheme is negligible. Eye diagrams of the 5 Gbit/s transmission experiments for the three schemes at various distances are plotted in Figure 15a. Depending on the transmitter scheme, fiber dispersion impacts the eye diagram opening to a different degree. For the externally seeded RSOA, the 25 km NZDSF eye diagrams are as open as the BtB case. This is due to the relatively narrow optical spectrum of this scheme. Thus, when transmitted through the NZDSF of only \(\sim\)5 ps/nm\(\cdot\)km dispersion, it does not suffer much inter-symbol interference (ISI) at 5 Gbit/s (symbol period of 200 ps). However, due to the broader spectra of the ASE spectrum-sliced and the RSOA-FCL sources, 25 km NZDSF does not offer similar performance as it  
Figure 14: Measured quality factor \(Q^{2}\) (dB) for transmission of (**a**) 5 Gbit/s and (**b**) 10 Gbit/s using the ASE spectrum-sliced scheme (blue), the self-seeded RSOA-FCL (red) and the externally seeded RSOA (green) transmitters. does for the BtB case. However, due to the relatively broader spectra of the ASE spectrum-sliced and RSOA FSL schemes, the overall dispersion accumulates and the signal quality degrades for 25 km. We also performed 10 Gbit/s transmission experiments. Figure 14b shows that only the externally seeded RSOA and the RSOA-FCL can achieve 10 Gbit/s with a \(Q^{2}\) above 9.8 and 7.3 dB, respectively. The performance limitation at 10 Gbit/s emanates from the limited modulation bandwidth of the RSOA, which was presented in Figure 13, and that causes ISI. This is illustrated by the closing of the 10 Gbit/s eye diagrams plotted in Figure 15b compared to that of the 5 Gbit/s eye diagrams in Figure 15a. In addition, at 10 Gbit/s, the transmission is limited to a 2 km SMF due to the interplay between chirp and chromatic dispersion. To summarize, it can be seen how the RSOA-FCL in any of the transmission experiments performs midway between the ASE spectrum-sliced and the externally seeded sources. It is thus an alternative source for many instances, where neither ultimate speed nor ultimate transmission distance is needed. Our experiments indicate that the RSOA-FCL is a valid source for transmission of up to 10 Gbit/s in SMF fiber over up to 2 km and up to 5 Gbit/s over 8 km SMF and 25 km of NZDSF. The need for a NZDSF to achieve longer reach may challenge the cost-efficiency of the RSOA. However, such dispersion management can either be obtained by deploying NZDSF or by deploying O-band RSOAs [41,42]. In central offices, electronic chromatic dispersion could also be an option.
## 2 Materials and Methods
### Total RNA Extraction and Real-Time qPCR Assay  
Seedless berry samples (about 10 g) were ground in liquid nitrogen with 1 g of polyvinylpolypyrrolidone (PVPP, Macklin, Shanghai, China). From the resulting powder, 0.1 g portions were set aside for RNA isolation, and the rest was thrown away. Total RNAwas extracted using the Spectrum(tm) Plant Total RNA Kit (Sigma-Aldrich, Wuxi, China) following the instructions provided, which included using DNase I to remove any genomic DNA contamination. The quality of the RNA was checked using a 1.5% agarose gel, and its purity and amount were measured with a NanoDrop 2000 spectrophotometer, showing OD260/OD280 ratios between 1.8 and 2.2. First-strand cDNA was made in 20 \(\upmu\)L reactions using 1 \(\upmu\)g of total RNA and HiScript(r) II Q RT SuperMix for qPCR + gDNA wiper (Vazyme, Nanjing, China). Transcript analysis of key genes in the LOX-HPL pathway was performed by real-time qPCR using the SYBR green method on a CFX96 Real-Time System, with the ubiquitin gene as the reference. The experimental methods are referred to by [PERSON] et al. [29] as follows: Each reaction (10 \(\upmu\)L) contained 5 \(\upmu\)L SYBR (Vazyme, Nanjing, China), 4.5 \(\upmu\)L ddH\({}_{2}\)O, 1/6 \(\upmu\)L cDNA, 1/3 \(\upmu\)L primer mixture (forward primer and reverse primer, 10 \(\upmu\)M). Reverse-transcription PCR (RT-PCR) was adapted from [PERSON] et al. with some modifications [30]. cDNA templates underwent initial denaturation (95 \({}^{\circ}\)C, 30 s) prior to 40 amplification cycles with the following thermocycling parameters: denaturation at 94 \({}^{\circ}\)C for 10 s, annealing at 60 \({}^{\circ}\)C for 30 s, culminating in a dissociation analysis (60-95 \({}^{\circ}\)C ramp). The specific gene primers for the lipoxygenase-hydroperoxide lyase (LOX-HPL) pathway and the reference genes are listed in Table S5 [31; 32; 33; 34]. For berry specimens representing distinct graft combinations, RNA isolation was conducted in triplicate biological replicates, with each extract subjected to triplicate technical replications during real-time quantitative PCR (qPCR) analysis.