esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The Xiaojiang watershed in Luxi, Yunnan, is a typical rocky desertification area, in which karst groundwater pollution is severe and water resources are scarce. This article takes the watershed as an example and investigates the response mechanisms of surface karst spring water quality to agricultural pollution in rocky desertification areas. Specifically, the study was conducted as follows: (I) A total of 108 water samples from 54 sources were collected during the dry and wet seasons for analysis. (i) Principal component and correlation analyses identified the main pollution indicators in the soil surface karst zone of the area, including total bacterial count, total coliforms, COD, pH, and redox potential. (ii) It was also discovered that surface soil, impacted by agricultural activities, directly contributes to groundwater pollution in the soil surface karst zone. (II) Local soil was used to prepare soil columns under various conditions for simulation. The findings indicate: (i) Temperature significantly affects the surface karst springs, with higher temperatures leading to more pronounced water quality responses, increased enrichment of pathogen-microbiota indicators, and degraded water quality. (ii) Soil porosity substantially influences the water quality of surface karst springs. Increased porosity results in looser soil, more oxidizing conditions in the storage matrix, reduced pathogen-microbiota development, and consequently, less water pollution. This study offers theoretical and technical references for evaluating, monitoring, and issuing early warnings for pathogenic bacteria-microbiota pollution in groundwater in rocky desertification areas.  
rocky desertification; surface karst spring; groundwater pollution; pathogenic microbiota; simulated in situ experiment +
Footnote †: journal: Applied sciences  
0000-0002-2330-3300][PERSON]  
1 Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China; [EMAIL_ADDRESS] (W.S.); [EMAIL_ADDRESS] (X.W); [EMAIL_ADDRESS] (Z.N.)
## 3 Results and Discussion
### Dynamic Strain Sensing Properties
#### 3.4.2 Wide Sensing Range  
In this study, we analyzed the effect of the hybrid structure on the sensing range of each MWNT content. Figure 6 shows the results for the 1 wt.% MWNT/NR composite. Because the 1 wt.% content is small, the electrical network may be relatively easily destroyed by external strain. Therefore, the tensile strain increases the electrical resistance of the composite, which leads to an increase in the relative resistance. Figure 6a presents the 150% stretching/releasing cycle test of the 1 wt.% MWNT/NR single composite at 30 s/cycle rates. The relative resistance increased to approximately 130%; however, above that, the electrical network was destroyed and an unrecognizable region appeared. This is shown in the inset of Figure 6a. However, the measurement at 150% strain was uniformly performed in the hybrid system (Figure 6b). Although the change in the relative resistance of the hybrid structure decreased, R/R\({}_{0}\) could be stably controlled, and sensing could be possible in a strain range of 150%, which would not be achieved in a single composite.  
In Figure 7, the dynamic strain-sensing curve of the 5 wt.% MWNT/NR is shown. According to the results presented in Figure 4, the 5 wt.% MWNT/NR single composite broke by \(\sim\)105%, while the hybrid structure broke by \(\sim\)142%. That is, because the hybrid structure can be measured in a strain range that was impossible in the single composite, the result of repeating 130% stretching/releasing under 100 cycles was possible, as shown in Figure 7a. The cyclic tests were conducted at a rate of 30 s/cycle. Figure 7b shows that the sample can be operated stably. Furthermore, the 5 wt.% MWNT/NR hybrid structure composite could be a strain sensor with excellent repeatability and durability in the 130% strain range.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Plastic Deformation**} & \multicolumn{2}{c}{**1 wt.\%**} & \multicolumn{2}{c}{**5 wt.\%**} \\ \cline{2-5}  & **Single** & **Hybrid** & **Single** & **Hybrid** \\ \hline at strain 50\% & 8.54 & 4.01 & 17.12 & 10.19 \\ at strain 100\% & 12.81 & 9.53 & 18.62 & 11.68 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Degree of plastic deformation of the MWNT/NR composite, based on each concentration and structural formation.  
Figure 6: Dynamic strain-sensing curve for (**a**) 1 wt.% single composite strain at 150% and (**b**) 1 wt.% hybrid composite strain at 150% under 5 cycles.
## 5 Performance Evaluation of EMOR
### Results
#### 5.2.3 Energy Consumption
The main reason is that in DCBONC, the probe message forwarding mechanism in the data collection period consumes less energy due to the incorporation of EOH [22]. Furthermore, the spanning tree is constructed and broadcasted by mobile sink so that the source node could obtain the max path connectivity information beforehand, thus saving a lot of energy consumed by selecting the forwarders. However, the additional energy consumed during the selection of optimal paths for real-time and non-real-time traffic is the difference in total energy of EMOR and DCBONC.
# Authentication Securing Methods for Mobile Identity: Issues, Solutions and Challenges
## 2 Mobile Authentication Method and Issues  
Many research studies have produced solutions to address mobile online authentication issues, such as a mobile authentication system based on the Blowfish encryption algorithm [7], handover authentication protocols using ID-based PKC [8], a trajectory-based identity authentication method [9], the integration of cryptographic methods for anonymous biometric authentication [11], authentication using a public behavior dataset (i.e., keystrokes on touch screens) with different feature selections to improve the authentication accuracy [12], and using cipher policy attribute-based encryption bonded with the geographical location [13]. However, few have narrowed the issues down to the mobile identity authentication service, for example, the national electronic identities (eID) [4] and decentralized and self-sovereign identity (SSI) solutions [14]. This section will address the issues of standard authentication commonly used for mobile transactions.
###### Abstract  
Polymer matrix composites (PMC) play important roles in modern industry. Increasing the number of such structures in aerospace, construction, and automotive applications enforces continuous monitoring of their condition. Nondestructive inspection of layered composite materials is much more complicated process than evaluation of homogenous, (mostly metallic) structures. Several nondestructive methods are utilized in this case (ultrasonics, shearography, tap testing, acoustic emission, digital radiography, infrared imaging) but none of them gives full description of evaluated structures. Thus, further development of NDT techniques should be studied. A pulsed terahertz method seems to be a good candidate for layered PMC inspection. It is based on picosecond electromagnetic pulses interacting with the evaluated structure. Differences of dielectric parameters enables detection of a particular layer in a layered material. In the case of multilayered structures, only layers close to surface can be detected. The response of deeper ones is averaged because of multiple reflections. In this paper a novel inspection procedure with a data processing algorithm is introduced. It is based on a double-sided measurement, acquired signal deconvolution, and data combining. In order to verify the application of the algorithm stress-subjected glass fiber-reinforced polymer (GFRP) was evaluated. The obtained results enabled detection and detailed analysis of delaminations introduced by stress treatment and proved the applicability of the proposed algorithm.  
Keywords:nondestructive testing (NDT); terahertz imaging; composite materials; multilayered structures; deconvolution +
Footnote †: journal: Applied Sci. **2017**, \(7\), 661; doi:10.3390/app700661
## 1 Introduction
The results showed that transcriptional levels of _SgHMGR_, _SgSSS_, _SgCS_ and _SgCYP45_ were up-regulated and their responses in the presence of MeJA were related to the concentration and timing of MeJA treatment in _Siraitia grosvenorii_[31]. MeJA-regulated rubber biosynthesis, based on a differential expression analysis, showed that the expression of _HMGCR_, _FPPS_, _IDI_, _GGPPS_, _REF/SRPP_ and transcription factors (bHLH, MYB, AP2/EREBP and WRKY) increased with MeJA treatment in TKS [32]. Based on the date of the transcriptome in _Taxus_, there were 18 genes showing increased transcript abundance following elicitation of MeJA, which was involved in the biosynthesis of terpenoid backbone, and then multiple candidates for the unknown steps in paclitaxel biosynthesis were identified [33]. A total of 40,952 unigenes and 19 coumarin compounds, 7 cytochrome-P450, 8 multidrug resistance transporter unigenes and 8 marker compounds were obtained, involved in coumarins biosynthesis and transport pathway with a parallel analysis of transcript and metabolic profiles in _Peucedanum praeruptorum_[34]. The secondary metabolites are the main components of their active functions in plant. Therefore, transcriptome technology was widely used as an effective means to research the biosynthesis of active compounds and the mining of key enzyme genes. MeJA could promote the biosynthesis of terpenoids and phenylpropanoids, through revealing differential expression of the genes involved in biosynthesis and plant hormone signal transduction and TFs in plants. At present, no study has shown the transcriptome of rosemy responding to MeJA. In our study, we investigated the transcriptome of rosemy suspension cells responding to different concentrations of MeJA using high-throughput sequencing technologies. Putative gene expression profiles of rosemy suspension cells were investigated and DEGs were classified under different concentrations of MeJA. By comparing and analyzing the sequencing data of control and illuminated groups, the genes involved in the regulation of primary and secondary metabolism and their regulatory networks were established. These experiments reveal dynamic gene expression changes in responding to different concentrations of MeJA and provide new insights into the genetic and genomic regulation of plant functional metabolites.
## 2 Design and Fabrication
### Dual-Function Landing Gear  
As shown in Figure 3a, the dual-function landing gear is primarily divided into two parts: the quick-release mechanism and its drive plate located within the lower casing, and the landing gear itself. The landing gear consists of three axially symmetric main rods and the interconnecting auxiliary rods (aux-rods). The main rods are carbon fiber tubes, while the support fingers, cable brackets, auxiliary rod connectors (ARC), and rod connectors are made of resin material and fabricated using stereolithography (SLA) 3D printing. These components are sequentially bolted onto the main rods from bottom to top.  
Figure 3: The design of the dual-function landing gear: (**a**) the force analysis and grasping mechanism of the landing gear for a spherical object; (**b**) a detailed diagram of the quick-release mechanism, showing the position and form of each component; (**c**) the exploded view of the quick-release mechanism; (**d**) the motion trajectory of the side-mounted guide shaft of the dual-function release mechanism (DFR) along the guide groove; (**e**) the principle of the clutch mechanism; and (**f**) rotation angles and displacements of components over time (time is plotted on the horizontal axis., the left vertical axis representing the angular displacement of each actuating component relative to its initial position, and the right vertical axis representing the linear displacement of components with linear movement, the rotating arrow in the figure indicates the direction of rotation of the pawl during the state transition process).  
The cable, which drives the movement of the landing gear, is fixed at one end to the cable bracket and at the other end to the cable drum of the quick-release mechanism. Under the traction force \(F_{\text{P}}\) of the cable, the main rods resist the tension force \(F_{\text{T}}\) of the tension spring and open to their maximum angle. The ARC not only connects the aux-rods but also mounts the tension springs between adjacent main rods. The aux-rods have a certain degree of curvature, providing a wrapping and centering effect on the object for more reliable grasping. The end of the aux-rod connected to the ARC is termed the fixed end, while the opposite end is termed the free end. The free ends of adjacent aux-rods are secured by rubber joints, which function as ball joints during the transformation of the landing gear's shape, thus simplifying the entire mechanism.
# HiGoReg: A Hierarchical Grouping Strategy for Point Cloud Registration
###### Abstract  
To address the persistent computational bottlenecks in point cloud registration, this paper proposes a hierarchical grouping strategy named HiGoReg. This method incrementally updates the pose of the source point cloud via a hierarchical mechanism, while adopting a grouping strategy to efficiently conduct recursive parameter estimation. Instead of operating on high-dimensional matrices, HiGoReg leverages previous group estimates and current observations to achieve precise alignment with reduced computational overhead. The method's effectiveness was validated using both simulated and real-world datasets. The results demonstrate that HiGoReg attains comparable accuracy to traditional batch solutions while significantly improving efficiency, achieving up to 99.79% speedup. Furthermore, extensive experiments confirmed that optimal performance is achieved when each group contains approximately 100 observations. In contrast, excessive grouping could undermine computational efficiency.  
point cloud registration; hierarchical grouping; recursive estimation; Gauss-Helmert model; moderate grouping Article
# Robust Control with Uncertain Disturbances for Vehicle Drift Motions
## 4 Simulation and Discussion
### Simulation Result  
The controller is verified by simulation experiments in MATLAB/Simulink to achieve target circle motions in drift conditions and parameter values of target motions are shown in Table 2 including a circle motion with a maximum velocity.  
The origin motions of Groups (a) and (b) both are the same uniform linear motion in non-limit motion as shown in the following, and the target motions are the drift circle motions as shown in Table 2a,b.  
\[v=8\;\text{m}/\text{s},\;\beta=\gamma=0,\;\delta_{f}=0,\;\kappa_{f}=\kappa_{r}=0\]  
Considering variation ranges of the steering angle and longitudinal slip ratios in practice, amplitudes and gains of them are restricted in simulations. The controller is used to achieve drift circle motions with uncertain disturbances and simulation results are shown in Figures 5 and 6 which respectively correspond to Groups (a) and (b) in Table 2, respectively. The uncertain disturbance \(\mathbf{d}_{e}\) is composed of three band-limited white noises which all observe the normal distribution and are same in the two simulations.  
The conclusion is obtained by analyzing simulation results. The results in Figures 5a and 6a show that drift motions with different velocities can be realized whether the target velocity is the same as the origin or not, maximum velocity errors in control can be less than 10 percent of the target without regard to differences between the origin and the target velocities, and final velocities are stable near target velocities. As shown in Figures 5b and 6b, the controller can realize circle drift motion with both larger and smaller target sideslip angles. Figures 5c and 6c suggest that larger yaw rates in drift motions can be realized with stability. It can be seen from the Figures d and e of Figures 5 and 6 that steering angles and longitudinal slip ratios are stable with fine adjustments finally, but the system stability is unaffected because adjustments pale beside their values. The circle radiuses are calculated as the equation in Section 2.3 to show radius variations from the uniform linear origin motion to target drift circle motions in Figures 5f and 6f and include sudden changes because of lateral acceleration changes.  
Combining all result figures, it is verified that the designed controller can accomplish the drift circle motions stably with robustness. Because of the neglect of slight differences during matching the tire model and target tire forces to obtain longitudinal slip ratios after gathering other targets, simulation results are not identical with targets and differences between results and targets of main status parameters, velocities, sideslip angles, yaw rates, and circle radiuses, are all less than 5 percent of targets, in spite of this, simulations are successful and finally stable near target stable groups in drift conditions and drift circle motions are realized. According to Figures 5 and 6, it can easily be found that the controller can effectively resist against uncertain external disturbances to realize drift motions.
## 2 Materials and Methods
In addition, based on the results of the pilot experiment in the present study (22.2 \(\pm\) 8.9 \(\upmu\)m), the distance limit of the pairs selected in the software program was set to 50 \(\upmu\)m, and pairs exceeding the distance limit were considered as incorrect corresponding pairs and excluded from the calculation. The dimensional differences between the CRM and the CTM were calculated for all data point clouds of the CRM. Next, the data points were calculated using the RMS value, using the following formula:  
\[RMS=\frac{1}{\sqrt{n}}\cdot\sqrt{\sum_{i=1}^{n}(X_{1,i}-X_{2,i})^{2}}\]  
where, \(X_{1,i}\) is the measurement point of \(i\) of the CRM, and \(X_{2,i}\) is the measurement point of \(i\) of the CTM. In addition, \(n\) refers to the number of all points measured in each analysis. The RMS value shows how much the deviation between the two different sets of data differs from 0. Thus, a low RMS value represents a high degree of three-dimensional agreement of the overlapped data [19]. All the data were analyzed using SPSS statistical software (release 25.0, IBM, Chicago, IL, USA). The normal distribution of the data was investigated with the Shapiro-Wilk test. Using one-way and two-way ANOVA, the statistical significance was tested and the difference between the groups was tested using the Tukey HSD test as a post-test (\(\alpha=0.05\)). To analyze the correlations of the volume and area of the 10 abutments with the accuracy of the four types of scanners, Pearson's correlation analysis was conducted (\(\alpha=0.00625\) with the Bonferroni correction method). The correlations were divided according to the Pearson's correlation coefficient (PCC) [37]. The correlations among the variables were expressed through perfect correlations (PCC = +1 or \(-1\)), strong correlations  
Figure 3: Scanning strategy for intraoral scanner. (PCC = +0.7 to +0.9 or \(-0.7\) to \(-0.9\)), moderate correlations (PCC = +0.4 to +0.6 or \(-0.4\) to \(-0.6\)), and weak correlations (PCC = +0.1 to +0.3 or \(-0.1\) to \(-0.3\)).
# Revealing Development Trends and Key 5G Photonic Technologies Using Patent Analysis
## 4 Empirical Study
### Key Technology Network Analysis  
In terms of the key technologies of patents, this study focused on third-order CPCs. The network model results of the key technologies are shown in Figure 1 and the key CPCs are shown in Table 3.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Ranking** & **Patentee** & **Number of Patents** & **Percentage** \\ \hline
1 & CommScope Technologies LLC. & 8 & 22.86\% \\
2 & Redwood Systems INC. & 3 & 8.57\% \\
3 & Allen Telecom LLC. & 3 & 8.57\% \\
4 & Andrew LLC. & 2 & 5.71\% \\
5 & Lockheed Martin Corporation & 2 & 5.71\% \\ \hline \end{tabular} Note: A patent may have more than two assignees.  
\end{table}
Table 2: Number of approvals of the top ten patentees.  
Figure 1: Third-order Cooperative Patent Classification (CPC) network diagram for 5G photonic technology. Note: The node size represents the number of nodes. The thickness of the arc represents the strength of the link and the number of patents.  
Table 3 shows that codes H04B, H04W, H01Q, H04L, G02F, G02B, and H01S relate to the top three technological fields in terms of closeness centrality, betweenness centrality, and RSHs. This illustrates that the key 5G photonic technologies relate to data transmission (H04B), wireless communication networks (H04W), antennas (H01Q), the transmission of digital information (H04L), and devices or arrangements. The optical operation of such devices and arrangements was modified by changing their optical properties to control the intensity, color, phase, polarization, or direction of light (G02F). Furthermore, optical elements, systems, or apparatuses (G02B) were altered using the process of light amplification through the stimulated emission of radiation (laser) to amplify or generate light (H01S). Accordingly, the most important 5G photonic technologies mainly involve applying optical and electrical communication techniques, all of which are indispensable for conducting related interdisciplinary research.
# A Correction Method of Mixed Pesticide Content Prediction in Apple by Using Raman Spectra
## 1 Introduction
And now Raman technology have been a fast, accurate method for non-destructive detection and in several cases in-situ method for detection of various materials is gaining its importance in agricultural application as well [17]. Surface enhanced Raman spectroscopy (SERS) technique, based on Raman scattering effect and combined with surface enhancement mechanism, is an analysis techniques with high sensitivity. It's one of the important developments of conventional Raman spectroscopy. It can not only detect the detailed structure information of the object, but also provide higher sensitivity with several orders of magnitude than the conventional Raman technology, which improves trace substances detection limit greatly. In Raman spectra detection, it's obvious that in the case of pesticide samples with same concentration, the characteristic peak intensity of pesticide mixture was lower than the ones of single pesticide. The declining degree of peak intensity changes with the concentration of pesticides. The characteristic peak intensity reflected the concentration of pesticide. So the characteristic peak intensity of pesticide mixture could not reflect the content accurately. This increased the risk of misclassifying agricultural product with excessive pesticide as qualified product. Thus the phenomenon affected Raman spectral detection on pesticide mixture severely. In the study, acetamiprid and deltamethrin, two pesticides which were commonly used on apples, were the research objects. According to the Raman signal enhancement effect, silver sol was used as surface enhancer. And the exposure time, laser power, enhancement methods, and the number of collection points were optimized to get the best result. In order to find the declining degree and changing rule of peak intensity and pesticide concentration, the characteristic peaks intensity of single pesticide and pesticides mixture with gradient concentration were all detected and compared and the rates of intensity were calculated. Then the rates between single pesticide and mixture with concentration from 100 mg\(\cdot\)kg\({}^{-1}\) to 10\({}^{-3}\) mg\(\cdot\)kg\({}^{-1}\) were worked out with Lagrange interpolation method. A correction method was applied in Raman spectral detection of deltamethrin and acetamiprid residue. And a reasonable assessment of model validity was made. The correction method could be used in Raman spectral detection of other pesticides mixture.