esa-sceva/satcom-chunk-collection huggingface dataset:
# Crop Water Content of Winter Wheat Revealed with Sentinel-1 and Sentinel-2 Imagery
## 3 Results
### Choosing the Optical Vegetation Index and SAR Polarization Index
Study observed that the red edge band, near-infrared band, and short-wave infrared band of the Sentinel-2 satellite were highly sensitive to the water content of the winter wheat crop, suggesting that the Sentinel-2 data are suitable for establishing vegetation indices for used to estimate crop water content. The method (see Section 2.4) proposed in this study was used to construct 23 enhanced radar polarization indices. In order to select the optimal radar polarization index, a correlation analysis between the indices and ear water content, stem and leaf water content, crop water content, and soil water content was carried out. The correlation between the enhanced radar polarization indices and soil water content was also analyzed (Table 3). Correlation between the enhanced radar polarization indices and soil water content was generally low when vegetation coverage was high. Only the correlations between the polarization indices (\(\sqrt{\mathrm{v}\mathrm{h}_{\mathrm{en}}}/\mathrm{v}\mathrm{v}_{\mathrm{en}}\), \(\sqrt{\mathrm{v}\mathrm{h}_{\mathrm{en}}}^{2}+\mathrm{v}\mathrm{v}\mathrm{v} _{\mathrm{en}}^{2}/\mathrm{v}\mathrm{v}_{\mathrm{en}}\) and \(\left(\mathrm{v}\mathrm{h}_{\mathrm{en}}-\sqrt{\mathrm{v}\mathrm{v}_{\mathrm{en }}}\right)\)/\(\left(\mathrm{v}\mathrm{h}_{\mathrm{en}}+\sqrt{\mathrm{v}\mathrm{v} _{\mathrm{en}}}\right)\)) and soil water content reached significant levels (Pearson correlation coefficients were \(-\)0.355, \(-\)0.293 and \(-\)0.279, respectively). Most of the other radar polarization indices did not correlate well with soil water content. This is because radar signals produce complex responses to soil moisture in areas covered by vegetation. During the grain filling stage, vegetation coverage is high. This leads to complex scattering of the radar signal between vegetation layers, and therefore complex and changeable surface information contained in the scattered signal. The selected enhanced radar polarization index (\(\sqrt{\mathrm{v}\mathrm{h}_{\mathrm{en}}}/\mathrm{v}\mathrm{v}_{\mathrm{en}}\)) significantly negatively correlated with soil water content in vegetation-covered areas.
## 4 Discussion
### The GEE Map Composition  
In the proposed methodology, the integration of the three datasets within GEE is performed during the image composition step without applying advanced data fusion techniques. In RS applications, the latter aims to improve the information contents of remotely sensed datasets used separately [89]. In this regard, in the future, advanced data fusion techniques could be incorporated into the proposed methodology to assess the possibility of further improving the accuracy of classification results. Nevertheless, considering the characteristics of the OB approach and the information enhancement obtained by the combination of its various steps, the OB method can be considered a kind of data fusion process. Furthermore, the object recognition is performed using the higher resolution images (i.e., PlanetScope), and the information coming from the lower resolution images (i.e., S2 and S1) is averaged at the object level. Thus, the OB approach can limit the effects of possible mismatching issues of images from different sensors.  
The initial map composition, based on reducing several images by the period of interest (POI), is crucial in land cover classification since it allows the generation of cloud-free image composites representative of a specific time window [32; 90]. In some cases, POI was widened over more years, adopting seasonal time windows in areas with frequent cloud cover when using data with relatively low temporal resolution (e.g., Landsat) [16]. This approach can generate classification inaccuracies related to the land cover changes that may occur during the POI. Thus, a compromise must be found between the need to create a cloud-free composite and limiting the effects of possible land cover changes. The POI defined for this research (14 months) is related to the time window assumed for the initial ground points dataset. The length of the POI, although it can generate the abovementioned inaccuracies, is similar to that of other studies aimed at comparing various classification approaches [21; 91]. Moreover, these possible inaccuracies may equally influence the outcomes of each classification.
## Materials and Methods
### Quantification of Olive oil Polar Phenolic Compounds by HPLC-DAD-ESI/MS  
A previously reported procedure [12] was followed to extract and analyse polar phenolic substances. Briefly, 0.5 g of oil were dissolved in 0.5 mL of hexane. The internal standard solution was added (20 \(\upmu\)L of 100 mg L\({}^{-1}\) syringe acid in methanol) and extracted with 4 \(\times\) 0.5 mL of methanol: water (60:40, _v/v_). The hydro-alcoholic solutions were collected, washed with 1 mL of hexane to remove acylglycerols left, evaporated to dryness, and reconstituted with 0.25 mL of methanol before the analysis.  
Analyses were performed using an HPLC Agilent 1100 (Santa Clara, CA, USA) with a diode-array detector (DAD) and a mass spectrometer detector (ion trap G2445D SL) equipped with an electrospray ionization (ESI) source in reported conditions [13]. A Synergi Polar reverse phase (250 \(\times\) 4.6 mm, 4 m) analytical column from Phenomenex (Chesire, UK) was used with, as a mobile phase, water (A) and methanol/IPA 90:10 _v/v_ with (B) each containing 0.1% formic acid, working in the gradient mode at a flow rate of 1 mL min-1, and injecting 10 \(\upmu\)L of sample extract solution. Gradient used was: 0 min, 30% B, 0-40 min, 60% B, 40-50 min 95% B. In HPLC-DAD analysis, different wavelengths were monitored: 260 nm for vanillic acid, 280 nm for hydroxyytrosol, tyrosol, and secoiridoids derivatives, pinoresinol, acetoxypinoresinol, and syring acid, 310 nm for \(p\)-coumaric acid, 325 nm for ferulic acid, 338 nm for nigerenin, and 350 nm for luteolin. In HPLC-ESI-MS, the ion source was operated in a negative ionization (NI) mode and a mass analyser in full scan mode. Mass scan was performed in the range m/z 70-1100. The main secoiridid derivatives were quantified using the calibration curve of tyrosol. Acetoxypinoresinol was quantified with the calibration curve of pinoresinol, while all the other phenolics quantified each one with its own calibration curve, as reported in [12].
## 7 Conclusion and Future Work  
This paper introduces a method of natural gas pipeline leak detection based on the extended Kalman filter (EKF). The change of flow state in an actual pipeline operation is usually random and easily affected by all kinds of interferences. Therefore, it is difficult to reflect the real-time state of flow by the transient flow real-time model method directly. This paper proposes a time-varying real-time EKF method for pipeline leak detection. In applying the approach to simulated and laboratory case studies, this paper has shown that the separate treatment of system and measurement noise inherent within EKF means that the proposed approach has low sensitivity to random noise, and good capability for accurately estimating leakage rate and location. The results of simulation and experiment show that the method is sensitive to small leakages of a pipeline and the estimation of leakage rate and location are accurate.  
As the foundational work on an algorithm and experimental study, there are several limitations which we would like to address in future work. Firstly, the algorithm is only applied to long straight pipeline but not a pipeline network with complex topology. Secondly, the experimental study is verified on a lab testbed that is smaller than typical real-world gas pipelines. It will be critical to work with gas companies to experiment with real gas pipelines. Thirdly, while the probability of a multi-point leakage is much lower than that of a single-point leakage, it is still useful to conduct research in detecting leakage in more complex cases.  
[PERSON] derived the algorithms, led the experiments and wrote the paper. [PERSON] revised and proofread the paper.  
This research was funded by Scientific Research Project of Harbin University of Commerce (No. 17 XN013) entitled \"Research about detection and location of natural gas pipeline leakages based on Kalman filter and Fiber sensing,\" the Doctoral Research Project of Harbin University of Commerce (No. 2016 BS19), and National Natural Science Foundation of China (No. 51808092).  
The authors declare no conflicts of interest.
## 4 Pharmacological Potential
### Laurel Leaves
#### 4.1.8 Antioxidant Activity  
It was shown that an ethyl acetate extract from the leaves of _L. nobilis_ has antioxidant activity against lipid peroxidation [64]. This extract was also found to exhibit the largest radical scavenging capacity in neutralizing 2,2-diphenyl-1-picrylhydrazyl (DPPH), nitric oxide, oxygen, and hydroxyl radicals [65]. Moreover, methanolic extracts were shown to exhibit antioxidant activity due to the polar compounds they contain such as phenolic molecules [66]. An additional study found that the dehydrated aqueous and ethanolic extracts exhibited potent lipid peroxidation suppression, with 96.8% and 98.6% inhibition rates, respectively, using a linoleic acid emulsion at a concentration of 60 ug/mL [67]. Furthermore, both extracts demonstrated strong reducing capacity, superoxide anion radical scavenging, DPPH radical scavenging, hydrogen peroxide scavenging, and metal chelating properties [59].  
An _L. nobilis_ leaf extract was shown to be a potent scavenger of free radicals in the liver, which prevented in rats the hepatotoxic effects induced by carbon tetrachloride [68]. Indeed, it had a vascular protective effect, an angioprotective action on the capillary bed of the rat liver, and prevented the progression of necro-inflammation, which could be explained by the antioxidant and antimicrobial properties of flavonoids, terpen, and terpenoids [68].  
[PERSON] et al. [69] reported that at low concentrations, an EO of Moroccan laurel possessed significant DPPH scavenging activity. According to [PERSON] and [PERSON] [59], the EO derived from Turkish laurel exhibited remarkable antioxidant activities such as DPPH, hydroxyl, and hydrogen peroxide scavenging activities, as well as superoxide radical scavenging activities, which were higher than the activities of the control compounds, including curcumin, ascorbic acid, and butylated hydroxytoluene. The EO's high concentration of oxygenated and non-oxygenated monoterenes might account for these activities [70]. The antioxidant activity of _L. nobilis_ EO has been extensively discussed in the literature due to the plant's significance in food and traditional medicine [71; 72].  
EOs were studied and compared according to geographical areas. Two commercial EOs were evaluated by [PERSON] et al. [73]: one from Russia (RFBL) and another one from Serbia (SRBL); the results showed that that of SRBL had higher DPPH and total reducing capacity (TRC) values than that of RFBL. The values obtained for TRC (14.59 \(\pm\) 0.58 mg GA/g and 17.33 \(\pm\) 0.66 mg GA/g of EO from RFBL and SRBL, respectively) were close to those found by [PERSON] et al. [74].
# The Role of Earth Observation, with a Focus on SAR Interferometry, for Sinkhole Hazard Assessment
## 1 Introduction to Sinkhole Hazards
The recent advances in satellite and airborne imaging technologies have made it possible to derive information that can be used for sinkhole hazard assessment while minimising time and cost constraints. This paper aims to review the conventional and earth observation approaches used for sinkhole hazard assessment and highlights the advantages and limitations of the various techniques. The paper is organised as follows: In Section 2 we review the mechanisms of sinkhole formation, distinguishing between sinkhole types, their sizes and morphological expressions. This is followed in Section 3 by an introduction to the concepts of statistical modelling for sinkhole hazard assessments, focusing on the information requirements, advantages and pitfalls. The role of earth observation in the generation of information to assist with sinkhole hazard assessment is considered in Section 4 with a particular focus on the compilation of sinkhole inventories (Section 4.1) and the detection of precursors to sinkhole development (Section 4.2). We discuss, in Section 5, the advantages and current limitations of remote sensing techniques for sinkhole hazard assessment and highlight the future opportunities.
# Collision Risk Assessment and Operation Assistant Strategy for Teleoperation System
## 4 Collision Risk Assessment
### Selection of the Evaluation Factors  
The accurate and appropriate selection of risk indicators is the basis for correct collision risk assessment. Currently, most studies only consider distance as a factor, which leads to less accurate assessment results. In this section, three basic factors that have a significant effect on collision risk were selected to build a fuzzy factor indicator set, which included three factors such as the relative shortest distance D, the delay time of teleoperation T, and the speed of operation V. These factors can accurately reflect the risk degree of robots. Moreover, these indicators are irrelevant to each other.  
1. The relative shortest distance D:  
Since collision occurs at a distance of zero, the relative shortest distance has a direct impact on the collision risk. It is also the factor of most interest in the current research. The closest distance is the shortest physical distance between each obstacle nearby and the robot arm linkage. It is not just the distance from the robot arm's end to the workpiece's center, but is an object-to-object distance.  
2. The delay of teleoperation T:  
For teleoperation robots, the time delay is one of the critical factors affecting operation risk. The time delay includes the signal transmission delay caused by limits on the speed of radio transmission and the data processing delay at sending and receiving stations and satellite relay stations. Furthermore, the delay time of teleoperation is not a definite value, and it is very susceptible to the quality of signal transmission. The uncertain time delay will cause some uncertainty [5] in the whole teleoperation system, which directly increases the risk of collision. Therefore, the delay time of the system should also be considered as one of the factors.  
3. The operation speed V:  
Operation speed is closely related to collision risk. For example, the collision risk at a high speed is much higher than that in slow conditions. Especially in the case of large latency, fast speeds can cause large deviations between the remote operation and the visual display. Consequently, teleoperation robots are prone to colliding with non-target objects. As can be seen from the above, operation speed is an important factor that has a significant effect on the collision risk.  
Figure 6: Construction of virtual environments and virtual robots.
# Video Multi-Scale-Based End-to-End Rate Control in Deep Contextual Video Compression
## 1 Introduction
[19] propose deep contextual video compression (DCVC), which leverages the high-dimensional context to carry rich information for high-frequency content and exhibits higher video coding quality. [PERSON] et al. [20] propose an end-to-end strategy for surveillance videos. Since bit allocation can affect RD performances directly, [PERSON] et al. [21] exploited the gain unit to control bit allocation among intra-coding with end-to-end hierarchical bidirectional video compression. However, only allocating bits for every frame cannot result in finding the suitable \(\lambda\) to decrease RD costs, which are still far from a feasible rate control scheme in deep learning video compression. [PERSON] et al. [22] provided a learned rate control according to the derived R-D-\(\lambda\) relationship in DVC. However, bit allocation and \(\lambda\) are still obtained via predictive coding, and some coding parameters are not suitable for the coding features. It is necessary to develop an end-to-end rate control model, and this enables a paradigm shift from predictive coding to conditional coding. In this paper, video multi-scale-based end-to-end rate control is proposed. The major contributions of this paper are as follows: (1) To achieve optimal end-to-end rate control performance, a two-branch residual-based network and a two-branch regression-based network are designed to obtain a suitable bit rate ratio and the optimal \(\lambda\) according to the temporal encoded features. (2) To obtain a suitable video multi-scale model, multi-scale bicubic downsampling operation is used, and the hybrid efficient distillation SISR network (HEDS-Net), which contains the multi-branch distillation network, the lightweight attention LCA block, and the upsampling network, is designed to restore high-resolution video. The rest of this paper is organized as follows. Section 2 presents a brief analysis of related works from the literature. In Section 3, the proposed algorithm is described in detail. The experimental results are demonstrated in Section 4. Section 5 provides the conclusion.
## 1 Introduction and Literature Survey
### Related Work
The authors demonstrated that the approach, while being computationally efficient, achieves similar or better results than popular LDA-based multiple-label classification systems. Based on the literature reviewed, one would conclude that the high computational cost is the most notable drawback of the existing generative approaches to automated text annotation. On the other hand, the inability to deal with new topics is the most serious limitation of the discriminative approaches. The next section presents an attempt to overcome these problems by deploying classifiers trained on bronze-standard sets. To generate the training data, an LDA model fine-tuned with a novel text segmentation algorithm is used. The proposed approach is partly inspired by the ideas formulated in [32, 38], and by the success of the iterative algorithm [25].
# Structural Health Monitoring of Large Structures Using Acoustic Emission-Case Histories
## 2 Acoustic Emission Applications
This work further combined optimized ensemble empirical mode decomposition (EEMD) and a two-dimensional multiple signal classification algorithm for real-time impact localization on composite structures. This new method was validated on a cross-ply composite plate. Another improvement in AE data analysis was given by [PERSON] et al. [18] through a statistical concept, Bayesian analysis. They considered AE data during fatigue monitoring of crack growth. [PERSON] et al. [19] gave an analysis of transverse vibration on a beam that may be useful in preventing damages to high-rate systems. Lastly, a review paper by the present author, 'Review on structural health evaluation with acoustic emission' [3] gave an overview of the current status of AE contribution to SHM. This article first examined signal attenuation, since any AE application seeks minimizing the number of sensors. It is shown that signal loss from geometrical spreading is a key issue in many shell-type structures. Another issue is general lack of attenuation data, found after an extensive survey of existing experimental reports. Since theory cannot provide such attenuation data, more effort is needed before quantitative SHM design procedures can be implemented. This is followed by discussion on source location, bridge monitoring, sensing and signal processing, pressure vessels and tanks, and special applications.
# Velocity-Aware Handover Self-Optimization Management for Next Generation Networks
## 1 Introduction
The HO decision in the proposed algorithm depends on the signal-to-interference-plus-noise-ratio (SINR) rather than on the received signal strength indicator, which is then used to calculate the actual level of the HOM. [PERSON] et al. [12; 13; 14] have proposed an HO optimization technique based on a weighted function for carrier aggregation. The proposed algorithm automatically adjusts the values of the HOM in accordance with three functions: SINR, traffic load, and velocity. The simulation results have demonstrated that the proposed algorithm enhances the system performance in terms of spectral efficiency at cell edge and outage probability. Three types of HCPs are considered in this work: TTT, measurement interval, and hysteresis, all of which are adjusted according to the number of HOPP performed in a measurement interval. A three-layer filter technique is applied to improve the HO performance, which requires information about the mobility condition and speed state of UE. [PERSON] et al. [15] have adopted a comparison method that compares two parameters, namely, cell boundary crossings and HO execution, to optimize the overall network performance. The HO decision on a target cell is completely dependent on the signal strength measurement. [PERSON] et al. [16] have developed a model to optimize HOM based on fuzzy logic for HetNets. The fuzzy logic consists of two inputs: call drop rate and load balancing index, both of which adapt the HOM for macro and small cells. In other work [17], the reinforcement learning concept is used to detect an HO in the network. Effective session HOs lead to low drop call rates and also reduce the HOF and HOPP. However, this technique only supports the UE mobility speed up to 120 km/h. In [18; 19; 20], several algorithms have been proposed to investigate and evaluate the issue of mobility management in different mobile speed scenarios. Three types of HO are considered to adapt the HCPs: too early, too late, and HO to wrong cells. The results demonstrated that the adapted HCPs reduce the rates of HOPP, HOP, and RLF. The major contributions of this paper can be summarized as follows. First, we formulate and address the issue of MRO in HetNets by focusing on two performance main metrics: RLF and HOPP, which lead to service interruption. Then, we propose a velocity-based optimization algorithm to continuously adjust the HCPs based on the condition of UE. Finally, we evaluate and compare the performance of the proposed algorithm to other existing related works. The remainder of this paper is organized as follows. Section 2 explains the system model that used for this work. The proposed velocity-based algorithm is presented in Section 3. Section 4 presents the simulation and performance evaluation. The conclusions are provided in Section 5.