esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion

Table 2: Results of the proposed model with different measures and training/testing datasets sizes. Figure 4: Precision–recall analysis of the proposed model with different training/testing dataset sizes. Where (**a**) considers 90:10 training/testing data split, (**b**) considers 80:20 training/testing data split, (**c**) considers 70:30 training/testing data split, and (**d**) considers 60:40 training/testing data split. Figure 6 reports a comparative \(accu_{y}\) investigation of the AFSA-WELM model and existing models. The figure shows that the SVM (RBF algorithm) achieved a lower \(accu_{y}\) of 87.28%. Next, the SVM (linear algorithm) and the Naive Bayes algorithm achieved a slightly increased \(accu_{y}\) of 95.17% and 95.59%, respectively. Along with that, the SVM (poly-algorithm) and SVM (sigmoid algorithm) models achieved a reasonable \(accu_{y}\) of 98.55% and 98.29%, respectively. However, the AFSA-WELM model achieved the maximum \(accu_{y}\) of 99.14%. Figure 5: The ROC analysis of the proposed model with different training/testing dataset sizes. Where (**a**) considers 90:10 training/testing data split, (**b**) considers 80:20 training/testing data split, (**c**) considers 70:30 training/testing data split, and (**d**) considers 60:40 training/testing data split. Figure 6: The \(Acc_{y}\) analysis of the proposed model and existing algorithms. Figure 7 shows a comparative \(prec_{n}\) investigation of our proposed model and existing models. The figure portrays that the SVM (RBF algorithm) obtained a lower \(prec_{n}\) of 88.57%. Moreover, the SVM (linear algorithm) and the Naive Bayes algorithm attained a slightly increased \(acc_{y}\) of 93.75% and 95.24%, respectively. Next, the SVM (poly-algorithm) and SVM (sigmoid algorithm) models reached a reasonable \(prec_{n}\) of 97.94% and 98.43%, correspondingly. Finally, the proposed method achieve a maximal \(acc_{y}\) of 95.22%. Figure 8 showcases a comparative \(rec_{l}\) investigation of the proposed method and existing models. The figure shows that the SVM (RBF algorithm) achieved a lower \(rec_{l}\) of 89.67%. Moreover, the SVM (linear algorithm) and the Naive Bayes algorithm reached a somewhat increased \(rec_{l}\) of 95.07% and 96.70%, correspondingly. At the same time, the SVM (poly-algorithm) and SVM (sigmoid algorithm) models reached a reasonable \(rec_{l}\) of 98.795% and 98.43%, correspondingly. Finally, the proposed model achieved a maximum \(rec_{l}\) of 99.53%. Figure 8: The \(Rec_{l}\) analysis of the proposed model and existing algorithms. Figure 7: The \(Prec_{n}\) analysis of the AFSA-WELM technique and existing algorithms. After examining the results and discussion, it was verified that the proposed model resulted in maximum performance in terms of the detection and classification of cyberbullying.
###### Abstract  
In Mediterranean regions, extreme weather conditions during the growing season may alter grapevine physiology and metabolism, thus modifying the quality of wines. The objective of this study was to investigate the effects of _Ascophylum nodosum_ treatments on plant physiology and berry metabolism in _Vitis vinifera_ exposed to water stress. The experiment was performed on potted vines subjected to two irrigation regimes (well-watered, WW, and water stressed, WS) both associated with _A. nodosum_ treatments (SWE), compared with control plants (CTRL). Gas exchanges, chlorophyll fluorescence, and water relations were monitored on SWE and CTRL leaves, both in WW and WS vines at three times. Moreover, the quantification of secondary metabolites and their partitioning were performed in berry skins. Plants treated with _A. nodosum_ extract showed higher photosynthesis and stomatal conductance than CTRL in both irrigation regimes and maintained a better plant hydraulic conductivity at the end of the sampling period. In addition, secondary metabolites in berry skins and their partitioning were significantly affected by the treatments in both irrigation regimes. Our results suggest that foliar application of _A. nodosum_ extract may help the acclimation of grapevines to post-veraison water stress, likely improving plant physiological and biochemical performances under environmental constraints.  
biostimulants; abiotic stress; climate change; drought; water potential; gas exchanges; berry skin metabolites; enzymatic activity; phenylpropanol pathway
# An Adaptive Security Framework for Internet of Things Networks Leveraging SDN and Machine Learning
## 6 Performance Analysis
### Channel Latency
\begin{table}
\begin{tabular}{c c c} \hline
**Network Scenario** & **Normal Latency (ms)** & **Attack Latency (ms)** \\ \hline
**WiFi Network** & 32 & 34 \\ \hline
**LTE Network** & 48 & 52 \\ \hline
**Wired Network** & 14 & 15 \\ \hline
**Custom IoT Traffic** & 38 & 42 \\ \hline
**Video Conference** & 76 & 79 \\ \hline
**SSH Sessions** & 41 & 44 \\ \hline
**High Load** & 62 & 68 \\ \hline
**Medium Load** & 53 & 58 \\ \hline
**Low Load** & 48 & 51 \\ \hline \end{tabular}
\end{table} 
Table 12: Normal vs. attack channel latency. comparison with other security frameworks. The protocol is ready for practical implementation, as these results demonstrate, and it can improve the security and functionality of IoT systems.
# Experimental Study of LoRa Transmission over Seawater
## 4 Experimental Results and Analysis
### LOS Scenario  
These experiments were carried out within the fixed bandwidth, \(BW=125\) kHz, and using constant coding rate, \(CR=4/6\), while the spreading factor was varied, \(SF\in[7,10,12]\). The measurements were performed in the 868 MHz and 434 MHz bands concurrently.
## 2 Materials and Methods
### Mathematical Model of System Coupling  
The mathematical model uses a block diagram for the representation of a system, where one can define input vector, output vector, and transfer function (expressing the dependence of output vector on the input vector and system structure). The structure of a system is given by the nature of its subsystems, their number, the nature, and the number of relationships that exist between subsystems.  
There is a coupling relationship between two subsystems if at least one output of a system represents the input of the other system. The coupling of two systems represents the systemic connection between them, regardless of the material nature.  
In the decomposable structural diagram in Figure 3, the pairs of input and output quantities in/from the subsystems were noted:  
- inputs (Xci), where (c) is the number of components and (i) is the number of coupling  
- outputs (Ypj), where (p) is component part number; (i) is the number of coupling; and p, q, i, and j \(\in\) N.  
The system coupling can be in series or in parallel. The mathematical relation of coupling of two systems in series is characterized by Relation (1), in which \(p=\overline{1,m};q=\overline{1,n}\)  
\[y(1)_{q}=x(2)_{p}\]  
\[\begin{array}{l}y_{1}=y_{1}(y_{11},y_{12},\ldots,y_{1q},\ldots,y_{1n})\\ x_{2}=x_{2}(x_{21},x_{22},\ldots,x_{2p},\ldots,x_{2n})\end{array} \tag{1}\]  
After drawing the decomposable structural scheme (based on the principle of decomposability and optimality) and the establishment and representation of couplings between subsystems, we move on to the next stage of determining coupling matrices and structure matrix.
# Proposed New Analytical Method of Tower Load in Large-Span Arch Bridge Cable Lifting Construction
## 2 Proposed Calculation Method
### Simplification of Calculation Model and Basic Assumptions  
The load on the tower before lifting is mainly provided by the main cable, towing cable, and lifting cable. Figure 2 shows the simplified cable lifting system that is used for calculation. The role of the main cable is to transfer all of the load to the tower by a cable saddle. At the same time, the sliding trolley transports arch ribs on the main cable, so it is also a track cable. The role of the lifting cable is to lift the arch rib in a vertical direction. The role of the towing cable is to tow the sliding trolley in a horizontal movement. The role of the sliding trolley is to run and lift arch rib segments on the main cable and then transport them to their target positions. The tower is the major load-bearing structure, which is the key part in cable lifting and is related to the smoothness and safety of construction. The anchor is the device to fix the cable system; its main role is to fix the cable, wind cable and winch, etc.  
The calculation method is based on the following basic assumptions:  
* It is assumed that the cable is flexible and can only bear tension;
* The stress-strain curve of the cable varies linearly, which means that it conforms to the generalized Hooke's law;
* The cross-sectional area of the cable does not change when the cable is under force;
* The self-weight load of the cable is uniformly distributed along the span length;
* The cable is absolutely flexible and cannot be used to bear bending moments in any section.
## 4 Discussion
### Developing Tendency Coefficient \(m\) Against Cyclic Amplitudes
More importantly, the classification criterion corresponds approximately to \(P_{d}/P_{\sigma}=0.05\) (or \(m=1.5\)). In other words, only on the condition of \(m>1.5\) can plastic deformation be limited to 0.001 mm with 30,000 loading times. Therefore, \(m=1.5\) or \(P_{d}/P_{\sigma}=0.05\) can be regarded as the boundary of the rapid stabilization zone and the tardy one. Finally, it should be noted that horizontal deformation increases sharply at 150-200 kPa, 300-350 kPa, and 400-450 kPa for Model 1, Model 2, and Model 3 respectively. Given the fact that dead load bearing capacity for the three testing models is 341.4 kPa, 552.6 kPa, and 910.2 kPa respectively, the relevant cyclic amplitudes levels \(P_{d}/P_{\sigma}\) are nearly 0.45-0.55, 0.55-0.65, and 0.45-0.55, which are quite close to the boundary from the tardy failure zone to the rapid one. Obviously, once horizontal deformation starts to increase overwhelmingly, vertical plastic deformation also tends to develop sharply. This indicates that vertical plastic deformation enters into rapid development process and model fillings begin to collapse completely. A summary can be carried out with the comments mentioned above. When \(P_{d}/P_{\sigma}<0.05\) or \(m>1.5\), plastic deformation rate decreases to zero rapidly with just a few of loading times. This status can be judged to locate in rapid stabilization zone. When \(0.05<P_{d}/P_{\sigma}<0.15\) or \(1.0<m<1.5\), although the decreasing trend of accumulative deformation rate weaken, plastic deformation also finally converges towards a constant value. Undoubtedly, the fillings fall into tardy stabilization zone. The transitional zone corresponds to the condition of \(0.15<P_{d}/P_{\sigma}<0.20\) or \(0.7<m<1.0\). If \(P_{d}/P_{\sigma}\) continuously increases from 0.20 to 0.60 and the parameter \(m\) decreases from 0.7 to 0.4, plastic deformation tends to develop abidingly, but deformation rate remains at a relatively low level when loading times are large enough. The relevant status can be termed as tardy failure. Finally, as \(P_{d}/P_{\sigma}\) increases beyond 0.60 and the parameter \(m\) decreases below 0.40, not only does accumulative deformation develop continuously, but also the deformation rate stays at a relatively high level from beginning to end. Model fillings can be regarded to fall into rapid failure zone.
# Static Evaluation of a Midimew Connected Torus Network for Next Generation Supercomputers
## 5 Cost Effectiveness Analysis of MTNs
### Message Traffic Density  
This factor was related to the alternative paths that were available from a single node to another. Multiple paths enabled the system to consider alternative choices in the event of faulty links. In other words, this factor indicated whether the traffic distribution of the network was efficient. The traffic distribution relied on the availability of multiple paths for a packet. The MTN was evaluated using Equation (7), along with other networks for comparison.  
\[MTD=average\:distance\times\frac{total\:nodes}{W_{L}} \tag{7}\]  
The MTD of the MTN provided a better average MTD, as compared to the high TESH and TFBN results.  
The MTN provided satisfactory costs with respect to various performance parameters. Therefore, using MTMNs for supercomputing is feasible, with better bandwidth, latency, fault tolerance, time, and costs, as compared to conventional topologies. As compared to other hierarchal interconnection networks, there were many similarities and some differences. For supercomputing, MTMNs are more expensive; however, they provide better performance with better diameter, node degree, and fault tolerance due to wrap-around links of torus BMs that are supported with hierarchal connections via midimew links.
## 3 Results and Discussion
### Effect of Inorganic Nanofillers on CNC/Photopolymer Composites
#### 3.3.1 Mechanical Properties of Photopolymer Composites with CNC and/or Inorganic Nanofillers
Thus, the stress transfer mechanism described above negatively affected on the tensile strength. Unlike tensile strength, the tensile modulus represented a higher value for CNC filled composites, especially for CNC/nanoclay/photopolymer composite. It is believed that the CNCs having a high crystallinity and stiffness act synergistically with inorganic nanofillers, thereby imparting improved rigidity to the composite. For the elongation at break (Figure 18), the composites with inorganic nanofillers showed lower values than the pure resin composites because the inorganic nanofillers gave the composites rigidity and reduced ductility. In addition, voids were generated around the evenly distributed inorganic particles in the composites during the tensile test, and they had a negative effect on the elongation of the composites [38]. Moreover, with the addition of CNC particles, this trend was exacerbated, resulting in a 50% reduction in elongation at break compared to pure resin. Impact strength also showed toughen effects by inorganic nanofillers, resulting in strength improvements of about 15% for nano-PCC and about 23% for nanoclay (Figure 19) [39]. Composites with CNCs had lower impact strength values compared to the composites with inorganic nanofiller only. The addition of CNC particles to the photopolymer resin negatively affected the impact strength value of the composite. Impact strength is the capability of a material to withstand a suddenly applied load, and it is expressed in terms of energy. In the case of the composites filled with CNCs, the CNCs act as impurities  
Figure 16: Tensile strength of composites filled with CNC and/or inorganic nanofillers. Figure 17: Tensile modulus of composites filled with CNC and/or inorganic nanofillers. in the composite matrix, and sudden strong loads are concentrated on the CNCs, causing instantaneous fracture and weakened impact resistance. Additionally, when the CNCs are added to the photopolymer resin with inorganic nanofillers, the ductility of the composites is further lowered. Therefore, the stress concentration by CNC particles is accelerated, and the impact strength is accordingly decreased.
## 1 Introduction  
The Para rubber tree (_Hevea brasiliensis_) is the only economic plant to produce natural rubber [1; 2]. The rubber particle, which is a specific organelle in the rubber latex, is widely considered as the only site for natural rubber biosynthesis (NRB) and storage [3]. Based on their sizes, rubber particles are classified as large rubber particles (LRPs) and small rubber particles (SRPs) [4]. Rubber transferase activity in SRPs is much higher than that in LRPs [5]. Small rubber particle protein (SRPP), a rubber biosynthesis-related protein that accumulates mainly in SRPs, plays a more positive role in rubber biosynthesis [6]. The histochemical localization of the SRPP and rubber elongation factor (REF) indicates that rubber biosynthesis in the rubber laticifer is mostly concentrated in SRPs [7]. In natural rubber production, latex is collected from laticifers by regularly tapping the trunk banks of the Para rubber tree [3; 8]. Treatment of the rubber tree bark with ethephon increases the volume of the rubber latex several-fold, and this practice has been widely used in commercial latex production [9; 10]. However, it is a longstanding mystery that most key genes in natural rubber biosynthesis are significantly repressed upon the application of ethylene [11; 12].  
Here, we have performed a comprehensive proteomics study of ethylene-stimulated rubber latex and have identified more than four hundred ethylene responsive proteins from the total rubber latex [12]. We also noticed that specific isoforms of REF and SRPP are important for ethylene-stimulated latex production in rubber latex. Notably, we found that ethylene improves the generation of SRPs in the rubber latex, and proteins in SRPs might play more important roles in the total rubber latex production [12]. Therefore, in this study, we further performed an in-depth proteomics study of SRPs with different ethylene treatments using two quantitative proteomics methods, namely, differential in-gel electrophoresis (DIGE) and using isobaric tags for relative and absolute quantification (iTRAQ). As a gel-based method, DIGE can determine highly abundant proteins on the 2-DE gels. Different to DIGE, iTRAQ is a gel-free high throughput method, and it can usually produce several thousands of unique proteins in many plants. Based on the new data produced by the two complementary proteomics methods, we uncovered some novel mechanisms of ethylene-stimulation in rubber latex production in SRPs.
## 4 Simulation
### Number of join Requests  
Our second set of experiments measured the number of join requests, which is the maximum number of join requests processed by a router. We counted the number of join requests processed by each router and got the maximum of these values. In the experiment shown in Figure 7a, the number of routers, load threshold, number of groups, and number of sources per group were set to 100, 5, 100, and 20. In the experiment shown in Figure 7b, the number of routers, load threshold, number of sources per group, and number of receivers per group were set to 100, 5, 20, and 20.  
From Figure 7a,b, we can find that the maximum number of join requests handled by a router in ILDM was less than other multicast methods. Moreover, as the number of receivers or groups increased, the maximum number of join requests handled by a router in ILDM grew much slower than in other methods. This was because we used a path state-aware multicast tree node selection mechanism to select an MTN with the best path state for each receiver to join. The load of the routers on the path between the receiver and the MTN was low. Although the maximum number of join requests handled by a router in PIM-SM with multi RP was close to that in ILDM, from the results of other experiments, we found that ILDM has advantages over PIM-SM with multi RP in terms of core load, link load, traffic concentration and routing state.
# Analysis of Road Sign-Related Factors Affecting Driving Safety with Respect to City Size
## 5 Discussion  
### Road Sign Recognition Survey  
The primary results obtained from the road sign recognition survey are as follows: Navigation systems were observed to be the most common means to access road information, although road signs also exhibited a considerable utilization rate of approximately 30%. Road signs were primarily used to acquire information on road facilities (rest areas, toll gates, etc. ), check for exits, and identify difficult roads (multilevel intersections, etc.). Similarly, the most commonly used types of road signs were direction signs (place names
## 3 Obstacle Avoidance Scenario
### Target Based  
The target-based obstacle detection method using computer vision uses known obstacle features to find the obstacles in a known environmental situation. Target-based obstacle detection using computer vision on various platforms has a vast and long history of research [262; 263]. Besides, target-based methods on UAVs are also rising. The classical morphological filtering method has been used to detect and avoid obstacles from UAVs by [PERSON] et al. [264], and the same method has been employed in finding landmine-like objects using UAVs, by [PERSON] et al. [265]. [PERSON], [PERSON], [PERSON], and [PERSON] [165] used Ecological Recognizer architecture, which uses a pattern matcher, and was trained offline to make a path estimation. A color-based, robust tracking method was developed by [PERSON] et al. [266], which was tracked through particle filtering. [PERSON] and [PERSON] [161] designed a scale expansion detector to detect obstacles with a monocular camera and used SURF (Speeded-Up Robust Features) to match the obstacle detail with the given data. Targeting forward motion, [PERSON], [PERSON], and [PERSON] [166] proposed an integration method using push-broom stereo perception and control. [PERSON] and [PERSON] [124] proposed a local object-based subtraction method to get the object's outline.  
One advantage of target-based obstacle detection is that it usually uses a single camera for detection, and another benefit is its faster method than others because of its low computation. However, even though it can detect the position of the obstacle in the image correctly, it cannot detect the actual distance. Thus, it requires an additional distance sensor fusion to solve this problem [267; 268].
# Theoretical and Numerical Research on High-Speed Small Refrigeration Twin-Screw Compressor
## 5 Results and Analysis  
### The Efficiency of Different Rotors at the Rated Rotational Speed  
Figure 7 demonstrates the variation in the volumetric efficiency across different rated rotational speeds for the screw compressor. At lower speeds, the compressor exhibits reduced volumetric efficiency, which shows a significant improvement as the speed increases from low to high ranges. While the efficiency continues to rise into ultra-high speed regimes, the rate of increase diminishes considerably. Specifically, when the rotational speed is elevated from 6000 rpm to 9000 rpm, 12,000 rpm, and 15,000 rpm, the volumetric efficiency increases by 5.07%, 3.45%, and 1.33%, respectively, indicating a nonlinear relationship between the speed and efficiency. The adiabatic efficiency of different rotors exhibits a similar trend with an increasing rated rotational speed.  
For screw rotors with identical displacement capacities, operating at ultra-high rotational speeds presents limited improvements in the volumetric and adiabatic efficiencies, while introducing significant challenges in rotor dynamics and operational stability. The clearance dimensions, which are intrinsically linked to the manufacturing precision and assembly tolerances, cannot be reduced without compromising the mechanical reliability.