esa-sceva/satcom-chunk-collection huggingface dataset:
# Landslide Susceptibility Assessment in Hong Kong with Consideration of Spatio-Temporal Consistency
## 6 Conclusions  
In this study, multi-source geospatial data were collected to assess the landslide susceptibility in Hong Kong over a period of 20 years. Specifically, historical landslide data from 2000 to 2019 in Hong Kong were used as labels, while elevation, slope, aspect, curvature, TWI, and lithology were considered as static assessment factors for landslide risk. Additionally, AAR, AMN, and LC were identified as dynamic assessment factors. VIF was used to determine the collinearity among the assessment factors, and RF and SVM models were employed to predict the landslide susceptibility in the study area over a 20-year period. By conducting a comparative analysis of the results and discussing them in the context of local conditions, the accuracy of this study was fully validated. The main conclusions of this study are as follows:  
1 The prediction accuracy of the RF model is superior to that of the SVM model, and the stability and generalization ability of the RF model are also better than those of the SVM. Based on the research results obtained using the RF model, the findings can serve as a reference for landslide disaster prevention and control in Hong Kong.  
Figure 16: Lantau Island area.  
* [2] Lithology, AAR, and elevation were the primary driving factors for landslide disasters in Hong Kong from 2000 to 2019, and the type of future landslide disasters in Hong Kong is still expected to be rainfall-induced.
* [3] The LSA system proposed in this study, which takes into account spatio-temporal consistency, has been well validated in terms of accuracy and applicability.  
The research findings focus on LSA and can provide critical spatial insights for disaster prevention, government decision-making, and public safety [54]. They help develop early warning systems and mitigation strategies, such as guiding land use planning and infrastructure development in stable areas.  
Conceptualization and writing, A.Q. and K.T.; methodology, A.Q., Q.W., X.P., and L.G.; software, A.Q. and Y.C.; funding acquisition, A.Q., Y.C., and K.T.; visualization, Q.W., X.P., and O.G.; data curation, Y.C., W.H., L.G., and F.Z.; writing--original draft preparation, A.Q., Q.W., and W.H.; writing--review and editing, K.T., Q.W., O.G., and F.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR, CASM, grant number 2023-04-13; the Qinghai Province basic research project, grant number 2024-ZJ-927; the Chinese Academy of Surveying and Mapping Basic Research Fund Program, grant number AR2204; and the National Key R&D Program of China, grant number 2023 YFC3007201.  
Not applicable.  
The data presented in this study are available in Section 2.2 of the article.  
The authors declare no conflicts of interest.
# Energy Aware and Quality of Service Routing Mechanism for Hybrid Internet of Things Network
## 3 System Model
### Interference Model  
The wireless network interference between nodes can be represented by a conflict graph [21] with respect to the network graph. The conflict graph \(CG=(V^{\prime},E^{\prime})\) is an undirected graph in which the vertices represent links of the network \(G\), and the edges represent the interference relation between the wireless links. The model that is used to compute the conflict graph is the N-hop interference model. In this model, a node interferes with its neighbors up to a distance of N-hops. This paper uses the 2-hop interference model as used in [22]. We represent a set of mutually interfering links by a maximal clique [23] in the conflict graph (i.e., a complete sub-graph of CG). By computing the maximum cliques from the conflict graph, we obtain the sets of links that cannot be active simultaneously in the network. Consequently, only one conflict graph node in a clique (one link in the connectivity graph) may be active at once. Accordingly, the sum of the rates of the conflict graph nodes in each maximal clique cannot exceed the capacity of the channel. Therefore, cliques can be used to derive necessary and sufficient constraints to accept or reject the flow requests based on the bandwidth available in the multi-hop wireless network [23].
## 2 Radar Jamming Signal Analysis and Modeling
### Deception Jamming
#### 2.3.2 Smeared Spreading Jamming  
Smeared Spreading Jamming (SMSPJ) is also a type of active jamming based on DRFM. It was proposed for dedicated pulse compression radars, and belongs to range gate pull-off jamming. The generation principle of this type of jamming is: the jammer first stores the acquired LFM signal in the DRFM, then performs n times time domain compression on the intercepted signal to obtain a jamming sub-pulse with a modulation slope n times that of the LFM signal, and then continuously replicates the obtained jamming sub-pulse n times,thus forming the SMSP jamming signal mentioned above. The mathematical modeling of SMSP jamming is as follows:  
\[J_{\text{SMSP}}(t)=\sum_{i=0}^{n-1}I^{i}(t) \tag{8}\]  
where, for LFM radar, the jamming sub-pulse \(J^{i}(t)\) is n times oversampling of the LFM signal, \(A_{i}\) is the amplitude of the \(i^{th}\) pulse, and its expression is as follows:  
\[J^{i}(t)=A_{i}\text{exp}\bigg{\{}j2\pi\bigg{(}f_{0}t+\frac{1}{2}k^{\prime}t^{2 }\bigg{)}\bigg{\}},0\leq t\leq T/n \tag{9}\]
# On the Communication Performance of Airborne Distributed Coherent Radar
## 4 Conclusions and Future Work  
A communication system model designed for ADCR has been established. Compared with the existing research, our model mainly considers two different factors: one is the instability of transmitting power of radar UAV and communication UAV caused by limited load. The other is the coherent detection of distributed radar, which leads to the direct accumulation of communication signals at the communication UAV. Based on the modeling of various errors and fading, the analytical OP expression of the base station is derived. The approximate expressions of Rician distribution and noncentral chi-squared distribution are fully used in the derivation. Numerical simulation verifies the rationality of the theoretical derivation, which will promote application of our proposed communication system model in real scenarios. It provides an important reference for the communication performance optimization of ADCR systems. In future work, we will continue to finely design the communication system model of ADCR, and consider more communication transmission modes, such as amplify-and-forward mode.  
Conceptualization, Q.W.; methodology, Q.W.; software, Q.W. and B.Z.; validation, Q.W.; formal analysis, Q.W. and B.Z.; investigation, Q.W. and B.Z.; resources, Q.W. and B.Z.; data curation, Q.W.; writing--original draft preparation, Q.W.; writing--review and editing, Q.W.; visualization, Q.W.; supervision, H.W. and J.P.; project administration, H.W. and J.P.; funding acquisition, H.W. and J.P. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China under Grant No. 91948303.  
The authors declare no conflict of interest.
## 1 Introduction  
Emergency scenarios can benefit from the deployment of a remote wireless sensor network (WSN) in the target area for a two-fold task: (1) gathering important information from the field; and (2) supporting audio, video and data communication when other terrestrial systems are not available. Additionally, sensor devices are frequently complemented by additional multimedia traffic sources (_i.e._, laptop computers, cameras and smart phones) [1].  
Emergency communications can provide information transfer services for rescuers and victims in disasters using various sensor devices through a remote WSN [2]. The capability to exchange information (e.g., video, voice and data) is essential to improve the coordination of rescuers during an emergency crisis and the response efforts.  
Due to extreme conditions, high altitude platforms (HAPs) [3] and satellites [4] are vastly underused and can be utilized for various uses to construct a remote WSN. Integrated HAP/satellite (IHS) networks are expected to optimally meet the emergency communication requirements of emergency relief and recovery operations for tackling large-scale natural and man-made disasters [5]. IHS networks have a number of potential advantages over conventional technologies [6], including:  
* High capacity regional coverage;
* Rapid deployment;
* Low power consumption;
* Potentially low cost.  
The IHS network infrastructure can indeed provide services for a wide range of distributed sensor devices with adapted and scalable access network capacity and coverage, owing to the low delay and high capacity HAP links [7], while reliable backhauling links to remote networks are supplied by the satellite segment [8].
## 3 Results and Discussion
### Chemical and Physical-Chemical Parameters
#### 3.1.3 Effect of the Harvesting Time  
With respect to the harvesting time, the ANOVA revealed a slight effect, PV being the only parameter significant affected (Table 1). PV showed significant fluctuations throughout the six-week period instead of a steady trend (data not shown). Previous studies have reported that increased ripeness causes an undesirable increase in the values of the quality parameters, although with significant fluctuations, and a decrease in the oxidative stability and phenol content [12; 29]. However, in our study harvesting was adjusted to real circumstances, where orchards management is set to harvest first the orchards which maturate first, as it is usually done in the commercial mills to achieve the best overall results, which could explain the lack of a clear trend. Our results show that in real conditions the harvesting time itself is not a critical quality factor for the Verdial de Badajoz oil as long as harvesting management is adequately set. The slight effect of harvesting time may anticipate slight changes in the volatile compound profile.
## 6 Performance Evaluation
### Performance Analysis of CL-APCC
#### 6.1.2 The average queue length of node  
The average queue length (AQL) of a node reflects the relationship between the inputting and outputting rate of the node, which affects the time from the data being generated until it is sent to BS.  
Figure 11: (a). Different node density on the impact for the RPR of BS; (b). Different routers on the impact for the RPR of BS.  
As the network becomes stable after 40 seconds, we make a sampling every 5 seconds on the queue length of each node between 60 seconds and 150 seconds to obtain statistical data by random sampling nodes. Then the average queue lengths of nodes are calculated with different networks densities.  
Figure 12 shows that AQL keeps around half of the total memory of the node (3 packets), which shows that the network is in a stable state. Whilst, AQL is less than \(L_{\text{max}}\) (\(L_{\text{max}}=3.75\) packets), which is due to the fact that CL-APCC protocol is able to adjust the sending rate of the node when the occupied memory size (\(L\)) is more than \(L_{\text{max}}\), This further avoids network congestion.
## 1 Introduction
Additionally, the shelf life models combined with the use of time/temperature integrators (TTI) could be an effective tool for monitoring the quality of chilled fish during distribution and storage, allowing better management and optimization of the chill chain from production to the point of consumption [17]. Despite the advantages of MAP on the shelf life of packed fish and fish products, it may be space-demanding due to the need for a high gas volume/product volume ratio in order to show a significant preservative effect on fish products. At the same time, high concentrations of CO\({}_{2}\) in the package headspace and increased gas volume/product ratios may result in the significant dissolution of CO\({}_{2}\) in the fish tissue. Carbon dioxide emitters have been reported in the literature, and they are also known to utilize the O\({}_{2}\) in the package headspace so as to form CO\({}_{2}\) and enhance the concentration of a CO\({}_{2}\)/N\({}_{2}\) headspace in the package without requiring an additional insertion of gas [18; 19; 20; 21; 22; 23]. Another significant drawback of using MAP is the significantly shortened shelf life once MAP integrity is compromised. Novel smart packaging solutions have been developed for the controlling and/or monitoring of the package integrity and gas concentration in the headspace [1; 24]. The aim of the study is the evaluation and mathematical modeling of the effect of active modified atmosphere packaging by the incorporation of CO\({}_{2}\) emitters into the package on the microbial stability and shelf life of gutted sea bass during refrigerated storage.
## 3 Results and Discussion  
### Proximate Composition  
The proximate compositions of fruit samples are shown in Table 1. The moisture contents for the shade-, sun-, and oven-dried treated samples were 4.15 \(\pm\) 0.09%, 3.77 \(\pm\) 0.29%, and 2.80 \(\pm\) 0.14%, respectively. A significant difference (_p_ < 0.05) was observed in moisture content between sun-dried and oven-dried as well as shade-dried and oven-dried samples; however, there was no significant difference (_p_ > 0.05) between sun-dried and shade-dried conditions. This might be due to the fact that both drying methods likely achieved a similar equilibrium moisture content due to the ambient humidity and temperature conditions being relatively consistent during the drying period. Additionally, the natural convection and air flow in both environments may have led to a comparable moisture evaporation rate. A moisture content of 76.39 \(\pm\) 0.60% was obtained for the fresh sample and this dropped drastically after drying. The moisture contents measured in this study are lower than that in the study of [PERSON] et al., which was 80.97 \(\pm\) 1.65% [17].  
The ash content in the fresh sample was found to be 1.43 \(\pm\) 0.05%. The ash content of the fruit was 1.00 \(\pm\) 0.06%, 1.02 \(\pm\) 0.02%, and 0.93 \(\pm\) 0.06% for shade-, sun-, and oven-dried samples, respectively. The ash content remained consistent for all drying methods; however, there was a slight difference observed in the ash content of fresh samples and after drying. The crude fiber in the study was found to be 2.35 \(\pm\) 0.61%, 2.23 \(\pm\) 0.71%, and 1.97 \(\pm\) 0.34% for shade-, sun-, and oven-dried samples, respectively (Table 1). There was no significant variation between all three dried conditions. The crude protein contents of _Physali sperviana_ L. fruit were 0.57 \(\pm\) 0.01%, 0.46 \(\pm\) 0.02%, and 0.35 \(\pm\) 0.03% for shade-, sun-, and oven-dried samples, respectively. No significant difference (_p_ > 0.05) was observed in terms of the protein content between all the three conditions. The crude protein content reported by [PERSON] et al. was found to be higher (1.85 \(\pm\) 0.31) than that obtained in the present study [17]. This might be attributed to sampling area variation. In addition, the total carbohydrate content was found to be 13.34 \(\pm\) 1.05%, 13.66 \(\pm\) 1.17%, and 14.13 \(\pm\) 0.71% for shade-, sun-, and oven-dried samples, respectively. The total carbohydrate content remained consistent for all drying methods and was in line with the study reported by [PERSON] et al.
## 5 Discussion
### Implications and Limitations  
The findings in this study have significant implications for the field of deep learning and computer vision. The Google ViT's consistent and exceptional performance, even on challenging datasets, suggests its potential for a wide range of medical image analysis and diagnostic applications. Its robustness to dataset size and quality could lead to more accurate and reliable results in various healthcare settings, providing valuable support for medical professionals.  
One of the strengths of this study was its focus on key metrics such as accuracy, loss, accuracy difference (AD), and loss difference (LD), which provided a comprehensive evaluation of the models' performance. The results were clear and consistent across all datasets, supporting the conclusion that the Google ViT is a powerful choice for medical image classification tasks.  
This work featured many novel aspects and perspectives when compared to the previously cited works [7; 8; 9; 10; 11; 12; 13; 14].  
Firstly, it utilized the Google ViT for the first time and proved its superiority in performance and stability compared to the ImageNet CNNs under the same circumstances and conditions. The Google ViT achieved superior performance, with an average 100% accuracy. Secondly, this work shed light on and stressed the significance of data processing techniques, such as data balancing, in order to achieve better performance and a higher accuracy. Additionally, it demonstrated the negative impacts of poor data processing habits, such as the overuse of data augmentation methods without considering the preservation of an acceptable ratio between the original data and their augmented versions. Finally, it clearly showed how such a case could be exaggerated in the event of unclean noisy image data.  
One limitation of our study lay in its exclusive focus on the classification of four mature WBC types. This raises the question of whether our findings would hold true if additional blood cell classes, such as basophils; segmented/banded neutrophils; immature granulocytes (pro-myelocytes, myelocytes, meta-myelocytes); and erythroblasts, were included. The inclusion of these additional cell classes could significantly increase the complexity of  
Figure 8: Score-CAM for DenseNet-169 model fitted with the DS-3 PBC dataset.  
the classification task due to their numerous similarities, presenting a challenging avenue for future research.
# Energy-Efficient and QoS-Aware Computation Offloading in GEO/LEO Hybrid Satellite Networks
### Motivations  
Although the above efforts have achieved effective computation offloading in OEC, there still remain some problems.  
**Role of satellites:** in most studies, satellites still mainly play the role as communication relays and the computing capabilities of satellites carrying edge servers are often overlooked, which ignores the potential benefits of in-orbit computing [3; 19].  
**Limitations of single-tier satellite network:** due to the time window problem of LEO satellites and the long communication delay of GEO satellites, relying solely on LEO or GEO satellites for in-orbit computing has significant limitations. Therefore, the GEO/LEO hybrid satellite networks that integrate LEO and GEO satellites can fully utilize the advantages of both layers to achieve more efficient in-orbit computing.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Works**} & \multirow{2}{*}{**GEO**} & \multirow{2}{*}{**LEO**} & \multicolumn{2}{c}{**Processing**} & \multicolumn{2}{c}{**Energy**} & \multirow{2}{*}{**QoS**} & \multirow{2}{*}{**Role of Satellites**} \\  & & & **Delay** & & & & \\ \hline
[6] & & & ✓ & ✓ & ✓ & & computing \\
[7] & & & ✓ & ✓ & ✓ & & computing \\
[13] & & & ✓ & ✓ & & & computing \\
[14] & & & ✓ & ✓ & & & communication \\
[17] & ✓ & ✓ & ✓ & & & computing \\
[18] & ✓ & ✓ & ✓ & & & computing \\
[19] & ✓ & ✓ & ✓ & ✓ & & communication, \\
[20] & ✓ & ✓ & ✓ & ✓ & & computing \\ Our work & ✓ & ✓ & ✓ & ✓ & ✓ & computing \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison between related works.  
**Objective:** overly emphasizing the minimization of processing delay may lead to excessive allocation of resources and an increase in total energy consumption [21; 22; 23]. Under the premise of ensuring QoS, an appropriate increase in mission processing delay can lead to lower energy consumption, which is more suitable for energy-sensitive in-orbit computing.  
**Offloading granularity:** most existing research adopts binary offloading modeling, which leads to suboptimal energy consumption when coordinating the offloading of multiple missions. As indicated in [20; 24], partial offloading, which allows missions to be partially processed on both LEO and GEO satellites, is more appropriate for missions with stringent QoS requirements.
# Recent Advances on Surface Modification of Halloysite Nanotubes for Multifunctional Applications
## 3 Application of Surface Modification of HNTs
### As the Catalysts  
With the development of the industry, catalysts have been widely used to change the reaction rate [57]. The modified HNTs were used as catalyst due to their large special surface area, high-activity, and luxviant surface hydroxyl groups [58]. In addition, the HNTs could be modified by catalysts and synthesized composites [59].  
It is reported that the HNTs were modified with APTES and HCl to prepared mod functionalized HNTs (HNTs-NH\({}_{2}\cdot\)HCl) as metal nanoparticles to product H\({}_{2}\)[60]. The results pointed out that the HNTs-NH\({}_{2}\cdot\)HCl catalysts obtain higher reaction values of HRG than the HNTs catalysts, with the value 813.08 mL\(\cdot\)min\({}^{-1}\cdot\)g\({}^{-1}\) catalyst and 630.80 mL\(\cdot\)min\({}^{-1}\cdot\)g\({}^{-1}\) catalyst, respectively. The modified HNTs have the activation energy of 30.41 kJ\(\cdot\)mol\({}^{-1}\), the enthalpy of 27.93 kJ\(\cdot\)mol\({}^{-1}\), the entropy of \(-163.27\) J\(\cdot\)mol\({}^{-1}\)\(\cdot\)K\({}^{-1}\), and catalytic activity of 91%. In addition, the modified HNTs catalysts have a higher efficiency than the common H\({}_{2}\) generation rate, which only keep \(220.5\) mL\(\cdot\)min\({}^{-1}\)\(\cdot\)g\({}^{-1}\) catalyst.  
The catalytic system (HNTs-APTMS-Mo-SL) has been synthesized by grafted APTMS and self-assembly [61]. The results revealed that the functionalized catalysts could be filtered and maintained high-activity to catalyze the alkene epoxidation. It hardly loses catalytic activity, even though it repeated at least eight times. The catalysts easily converted the active material, such as the linear aromatic alkenes and cyclic, in spite of being recycled several times in the catalyze reaction system. The functionalized catalysts composited the Mo salen have effect on epoxidation. The catalytic mechanism is the interact bonding between Mo and the salen ligands.