esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract
The goal is to investigate the performance associated with the computational costs, i.e., the total execution time, and the space complexity, i.e., the parametricity of these methods under identical conditions in order to determine the suitability through comparison, from which general recommendations can be derived. Furthermore, a unified approach for the classification task using different methods but a common preprocessing technique is proposed. The importance of careful preprocessing of the input data is highlighted in two variational studies. In the first study, variations in the lower color value limit of the derived feature maps are observed, and the impact on the accuracy is evaluated. This is important since the characteristic patterns rely strongly on the color range, where high thresholds are associated with a higher degree of loss of important information, whereas low thresholds may contain redundant information, which, regardless of the model, could increase the risk of overfitting. In the second study, the impact of data compression on the accuracy of the feature maps is evaluated, since data reduction leads to lower storage requirements and hence reduced costs for hardware or faster data transmission rates for online systems. The remaining sections are organized as follows. In Section 2, the basic principles of radar are outlined and briefly explained. Then, common preprocessing techniques are presented in Section 3, whereas Section 4 emphasizes the recent progress of DL-based approaches after providing a short introduction. In Section 5, a comparative study of the most successful approaches and state-of-the-art methods related to the preceding sections based on benchmark data is presented, and the performance, computational effort, and space complexity are evaluated and discussed in Section 6. Finally, the paper concludes by presenting open research topics derived from current gaps and challenging issues anticipated in the future.
# Radiometric Calibration of the Near-Infrared Bands of GF-5-02/DPC for Water Vapor Retrieval
Finally, the radiometric calibration coefficients for the 865 and 910 nm bands of the DPC can be determined. To obtain DPC data with a higher quality and enhance the accuracy of existing PWV data, a radiometric calibration method applicable to the near-infrared bands of GF-5-02/DPC for water vapor retrieval is developed. The structure of this paper is outlined as follows: Section 2 introduces the data utilized. Subsequently, Section 3 presents the radiometric calibration method for the DPC. Section 4 details the results of the radiometric calibration of the DPC. Following that, Section 5 discusses the calibration method. Finally, this study is concluded in Section 6.
# Effects of Lithium Chloride and Nitric Oxide Inhibitor on Orthodontic Tooth Movement in the Rat
###### Abstract  
Orthodontic tooth movement in a rodent model is reduced by lithium chloride (LiCl), a mood-stabilizing agent with antihyroid effects. Considering the established inhibitory effect of N(omega)-nitro-L-arginine methyl ester (L-NAME) on orthodontic tooth movement and the possible role of nitric oxide synthase in LiCl mechanism of action, the question arises if these two mechanisms are synergistic. To answer this question, 70 male Sprague Dawley rats were randomly divided into seven groups: untreated group without any interventions (i), and the orthodontic tooth movement groups receiving daily saline injection (ii), 300 (iii), and 600 mg/kg (iv) of LiCl per os, 10 mg/kg of L-NAME (v) and the combinations of 300 (vi) and 600 mg/kg LiCl (vii) with L-NAME. The first molar was moved towards the incis with 60 g of mesial tipping force applied by an activated fixed coil spring for two weeks. The resulted distance between the first and the second molar was measured using a feeler gauge. The serum parameters were also determined. We report here that both concentrations of LiCl significantly decreased tooth movement. Even though L-NAME was capable of reducing orthodontic tooth movement, no synergistic effects with LiCl were observed.  
Moreover, L-NAME had no impact on the robust and significant increase of thyroid-stimulating hormone (TSH) and decrease of triiodothyronine (T3) and thyroxine (T4) in the LiCl treated rats. These findings suggest LiCl significantly decreases the orthodontic tooth movement in rats; however, this ability seems not to be principally mediated through nitric oxide synthase.  
orthodontic tooth movement; lithium chloride; L-NAME; rats; thyroid-stimulating hormone; thyroid hormones +
Footnote †: journal: Applied Sci. 2021, 11, 3607. [[https://doi.org/10.3390/app11083607](https://doi.org/10.3390/app11083607)]([https://doi.org/10.3390/app11083607](https://doi.org/10.3390/app11083607))
# FREDA: Few-Shot Relation Extraction Based on Data Augmentation
## 2 Related Work
### Relation Extraction  
RE is one of the fundamental tasks of information extraction, and its purpose is to provide fundamental support for the construction of structured knowledge by identifying semantic relations between known entity pairs in an instance. Traditional RE has mainly used kernel-based approaches [30] and feature-based approaches [31] and has achieved good results. However, traditional relation extraction relies excessively on manual annotation and the ability to understand context. With the introduction of deep learning in natural language processing, several neural-network-based models were introduced for RE, such as convolutional neural networks (CNNs) [2], long short-term memory (LSTM) [32], and transformer [33], which continue to improve their effectiveness in supervised RE. The large amount of data that drives the model makes its generalization ability overly dependent on high-quality datasets. Therefore, using supervised learning requires labelling a large amount of high-quality data, and labelling a batch of RE datasets is time-consuming and laborious. To address the difficulty of labelling data, [PERSON] et al. [8] introduce the idea of distant supervision to RE, which typically automatically generates labelled data by using an existing knowledge base aligned to the text. [PERSON] et al. [34] refer to [PERSON] et al.'s idea as the \"distant supervision hypothesis\" and propose the at-least-one hypothesis to introduce multiple instances into distant supervision of data but ignore the possibility of multiple relations per entity pair. [PERSON] et al. [35] propose an algorithm combining PCNN with multiple instances to classify and extract the generated data, but this approach still tends to introduce excessive noise problems. The main task of the existing DSRE is to denoise and improve the correctness of the labelled dataset as much as possible [36]. However, this method still cannot solve the long-tail problem that exists in the dataset. In order to improve the performance of the RE model more effectively, the FSRE method is proposed to solve the long-tail problem and the data scarcity problem.
## 4 Establishment of Contact Mechanics Model
### Solution of Porosity and Real Contact Area  
The calculation steps of porosity and real contact area are as follows:  
(1) For the rough sealing surface, determine the comprehensive elastic modulus \(E\) and the yield strength \(\sigma_{\rm y}\) of the softer surface.  
Figure 11: Comparison of established model with other models.  
(2) By assigning or measuring, the detailed value of fractal dimension \(D\) and fractal roughness \(G\), the maximum distance \(h^{\prime}\) between the rough surfaces and the maximum height of the asperity on each rough surface \(h_{1}\) and \(h_{2}\) can be achieved. The corresponding \(l_{1}\) and \(l_{2}\) can be obtained according to Equation (1), \(A_{0}\) can be achieved through Equation (4), and the initial porosity can be gained by Equation (5). Under the action of contact pressure, there exists compression \(w^{\prime}\), and the porosity can be calculated by Equation (10).  
(3) Calculate the critical elastic deformation \(a_{\rm ec}\) and critical plastic deformation \(a_{\rm pc}\) of the asperity through Equations (11) and (12), obtain the contact area \(a_{\rm L}\) of the largest asperity on the sealing surface by Equations (16), (18) and (20) according to the given specific pressure \(p_{\rm c}\), then compare \(a_{\rm L}\) with \(a_{\rm ec}\) and \(a_{\rm pc}\) to determine the deformation properties of the asperity.  
(4) Obtain the real contact area \(A_{\rm r}\) according to Equations (15), (17) and (19), and then the specific value of \(A_{\rm r}/A_{0}\) is achieved.  
The parameters of the sealing surface are as follows:  
Material: Graphite M106k  
\(D\): 1.3, 1.35, 1.4, 1.45, 1.5  
\(G\): 17 \(\times\) 10\({}^{-11}\) m, 25 \(\times\) 10\({}^{-11}\)m, 33 \(\times\) 10\({}^{-11}\)m, 41 \(\times\) 10\({}^{-11}\)m, 49 \(\times\) 10\({}^{-11}\)m.  
\(D_{1}\) = \(D_{2}\), \(G_{1}\) = \(G_{2}\), \(E_{1}\) = \(E_{2}\) = 20 GPa, \(\sigma_{y1}\) = \(\sigma_{y2}\) = 117.6 MPa, \(\
u_{1}\) = \(\
u_{2}\) = 0.29.  
The porosity and contact area ratio \(A_{\rm r}/A_{0}\) of the above sealing surfaces were calculated, and the influence of contact pressure (the unit is MPa) and surface topography parameters \(D\) and \(G\) (the unit is 10\({}^{-11}\)m) were analyzed.
## 2 Materials and Methods
### Instrumental Analysis and Quality Assurance  
A GC/MS (6890N/5975B, Agilent Technologies, Santa Clara, CA 95051, USA) was employed for PAHs determination. The GC instrument was equipped with a split/splitless injector and a HP-5 ms [5%-(phenyl)-methylpolysiloxane] (Agilent J&W GC Columns, Agilent Technologies, Santa Clara, CA, USA) capillary column. High purity Helium was the carrier gas with a velocity of 1.5 mL min\({}^{-1}\). A pulsed splitless mode was used for the injection, and the injector's temperature was set at 280 \({}^{\circ}\)C. The GC oven temperature program was: 65 \({}^{\circ}\)C (hold for 1 min) to 320 \({}^{\circ}\)C at 15 \({}^{\circ}\)C min with a final isothermal hold for 3 min. Inlet and MS source temperatures were 280 \({}^{\circ}\)C and 230 \({}^{\circ}\)C, respectively. Selected ion monitoring (SIM) mode was used for the quantification of the analytes. Detection limits (DLs) of the studied PAHs ranged from 0.0002 (ANT and DBA) to 0.002 (FLT and PYR) ng m\({}^{-3}\). Recoveries varied from 82% (FL) to 117% (CHR) calculated from spiked filters determination.  
The quantification of PCDD/Fs and PCBs was performed by High Resolution Gas Chromatography-High Resolution Mass Spectrometry (Electron-Impact) (HRGC-HRMS, EI), on Multiple Ion Detection (MID) mode, on a Trace 1310 gas chromatograph (ThermoScientific,Waltham, MA 02451, USA) equipped with an Agilent DB-5 MS GC column, 60 m length, 0.25 mm I.D., 0.10 \(\upmu\)m film, a TriPlus RSH autosampler, coupled to a DFS mass spectrometer (ThermoScientific, Waltham, MA, USA) performing at 10,000 resolving power (10% valley definition). Instrumental conditions and quality control criteria are according to US EPA Method 1613 and European Standard EN 1948. The quantification was carried out by the isotopic dilution method. According to the European guidance, in the field of PCDD/Fs and PCBs analysis, results are calculated as sum-parameters based on concentrations and on limits of quantitation (LOQs) only, while limits of detection (LODs) do not carry any relevant information, and due to high precision in measurement, are considered equal to LOQs. The limit of quantitation (LOQ) for each congener was determined as the concentration in the extract which produced an instrumental response at two different ions to be monitored with a signal to noise ratio of 3:1 for the less sensitive signal. LOQ values were 0.1 (PCDD/Fs and n.o.-PCBs) and 2 (m.o.-PCBs) pg/sample. LOQs were evaluated during accreditation of the method using different reference materials and the respective higher LOQ value is used for each group of congeners for all samples. These values are low enough to ensure that the difference between the upper-bound level and lower-bound level does not exceed 20%. Recovery rates of 70-120% were also calculated by spiked filters analysis.
# Wireless Remote Control for Underwater Vehicles
## 4 Scenario Description and Simulation Setup
### Optical Modem Simulator
Despite the shorter range, these solutions are not affected by the vehicle orientation in the x/y plane, thus providing good maneuverability. In this scenario, a larger coverage area is reached in Figure 5c because the attenuation coefficient decreases when increasing the sea depth (Figure 5a). The BlueComm modems use blue wavelengths (470 nm) and a time division multiple access (TDMA) medium access control (MAC) layer that can split its time frame either into two equal time slots or into two time slots, where the former takes 10% of the TDMA frame and the latter takes 90% of the frame. Hence, we configured the optical MAC layer with this last setting, assigning 90% of the frame to the underwater vehicle for transmitting real-time video streams and 10% of the frame to the control station for the joystick position control.
# Thermal-Mechanical Behaviour of Road-Embedded Wireless Charging Pads for EVs
## 10 Discussion  
### Insights into Thermal-Mechanical Behaviour of Full-Scale Pads  
The thermal-mechanical behaviour of the small-scale IPT pad investigated in this paper can offer valuable insights into the structural response of a full-scale pad to thermal loading. In partial and complete pads, an increase in temperature causes an upwards bow in the pad, because of the higher thermal expansion of the components in the top half of the pad. This overall deformation resulted in a predominantly bending stress on the ferrite, with tensile strains on the top surface and compression on the bottom. The sign of these strains is opposite to wheel induced strains, which are generally compressive on the top surface and tensile on the bottom, as numerically predicted and experimentally measured in [PERSON] et al. [14]. This indicates that strains along the length of the ferrite cores from wheel loading and thermal loading are unlikely to add to each other, in the case of combined loading.  
Based on the simulation and experimentation of the embedded pad, thermally induced strains in a full-scale pad are unlikely to increase linearly with temperature, due to the softening of the surrounding pavement. At an ambient temperature of 40 \({}^{\circ}\)C, thermally induced strains in the ferrite were still around 50% smaller than strains induced by an equivalent 50 kN wheel load [14]. This suggests that wheel loading remains the critical load case to be analysed for the durability of the system. However, being well within the same order of magnitude, thermal strains cannot be discounted from the analysis.  
Figure 21: Comparison between measured and predicted strains on Ferrite 1 of the pavement-embedded pad.
# Monitoring Water Area Dynamics in Kashgar (2003-2023) Using Multi-Source Remote Sensing Data
## 3 Results and Analysis
### Temporal Characteristics of Annual Water Area Changes in the Kashgar Region
This concordance lends credence to the accuracy and reliability of the experimental results, providing robust data support for local policymakers. By elucidating the dynamics of water body change in Kashgar, these findings can inform the development of evidence-based policies that promote sustainable development and safeguard the region's ecological integrity. Figure 5: Temporal trends in water body area and water level in the Kashgar region.
## 3 Results
### Accuracy Assessment Analytics
#### 3.3.6. Crops Used for RTM-Based Crop Traits Retrieval  
Crops analytics for accuracy assessment, as given in Figure 13, showed that maize crops had high and consistent accuracy for R\({}^{2}\) values with min, median and max values of 0.37, 0.85 and 0.95, respectively. Similar was the situation with wheat and rice investigations,  
Figure 11. Graph showing RTMs used for crop traits.  
Figure 12. Graph showing crop traits retrieval accuracy using RTMs.  
which had good accuracy values of R\({}^{2}\) for analytical parameters, as given in Figure 13. All screened articles that had more than one crop investigation were grouped under multiple crops and had reliable accuracies of R\({}^{2}\) values. Grasses, pastures and other vegetables or high-value crops were grouped under others. Crops having outliers [92; 98; 104; 114] shown as dots in Figure 13 were rice, maize and multiple crops, respectively. These outliers were not due to the specific crops but instead mainly linked to narrow variation ranges of crop traits and RTMs. However, in this case [98], it was due to the seasonal study of winter and spring cereals, folders and many other crops with varying crop growth stages.  
Cereals (wheat, rice and maize) cumulatively constitute more than 50% of the total available studies (Figure 6) of RTM applications for crop traits retrieval. There is a need to include other major crops like cotton, sugarcane or orchards to broaden the scope and application of RTMs for crop traits retrieval.
# A Study of Discriminatory Speech Classification Based on Improved Smote and SVM-RF
## 2 Related Work
### Topic Modeling  
LDA [3] is an unsupervised generative probabilistic approach for corpus modeling. It assumes that each document can be represented as a probability distribution of latent topics and that the topic distributions of all documents share a Dirichlet prior. Each latent topic is represented as a probability distribution over words, and the word distributions of topics also share a Dirichlet prior [4]. LDA-based topic modeling methods have been applied to natural language processing, text mining, social media analysis, and other fields [5]. In order to identify hate speech in the Twitter corpus, [PERSON] et al. used a semi-supervised learning method, the bootstrapping technique, and linguistic rules to classify unlabeled data, and finally used LDA to classify based on statistical topic model [6]. [PERSON] et al. used the LDA-based model to extract text topics and analyze topic head words, and completed the research of agricultural products e-commerce text classification [7]. When solving the sparsity problem of short text data, researchers have pointed out that traditional LDA may have limitations. For example, [PERSON] et al. proposed the Dual-sparse Topic Model (Dsparse TM), which solves the sparsity problem by applying a \"Spike and Slab\" prior to separate the sparsity and smoothness of the distribution of document topics and topic terms [8]. The Biterm Topic Model (BTM) proposed by [PERSON] et al. focuses on capturing the relationship between topics by using biterm information in short texts, and introduces two online BTM algorithms to deal with short texts [9]. [PERSON] et al. proposed a novel supervised pseudo-document-based maximum entropy discrimination latent Dirichlet allocation model (PSLDA), which combines the maximum entropy method and the pseudo-document technique to solve the sparsity of word occurrence [10]. However, LDA is a relatively simple and easy-to-interpret model based on the bag-of-words model and Dirichlet priors, which makes its parameter inference and topic explanation relatively intuitive and easy to understand. Moreover, the inference process of LDA is relatively simple, and there are mature optimization methods and tool libraries that can be used. In addition, LDA, as a model that has been widely studied and applied, may have a higher acceptability and widespread use in academia. To balance the need for complexity, interpretability, and use case, LDA might be an option [11].
# Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid
###### Abstract  
In this paper, we present a privacy-preserving scheme for Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed Demand Response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. To monitor the power consumption of the buildings, while respecting the privacy of the users, we extend our previous Overgrid algorithms to provide privacy preserving data aggregation (_PP-Oregrid_). This new technique combines a distributed data aggregation scheme with the Secure Multi-Party Computation paradigm. First, we use the energy profiles of hundreds of buildings, classifying the amount of \"flexible\" energy consumption, i.e., the quota which could be potentially exploited for DR programs. Second, we consider renewable energy sources and apply the DR scheme to match the flexible consumption with the available energy. Finally, to show the feasibility of our approach, we validate the PP-Overgrid algorithm in simulation for a large network of smart buildings.  
privacy; secret sharing; distributed; peer to peer; smart grid; overlay networks; P2P; gossiping; overgrid +
Footnote †: journal: Sensors
###### Abstract  
Based on the optimal estimation (OE) theory and information content analysis method, we discuss the ability to include the multi-angle satellite ultraviolet polarization channel to retrieve the aerosol layer height (ALH) for ten typical aerosol types in the China region. We also quantitatively evaluate the effects of polarization measurements and the number of viewing angles on ALH retrieval under different conditions (aerosol model, aerosol optical depth, etc.). By comparing the different degree of freedom for signal (DFS) results of ALH caused by the theoretical retrieval error changes in different microphysical parameters in the aerosol and surface model, we identify the key factors affecting ALH retrieval. The results show that the extended ultraviolet band provides important information for ALH retrieval and is closely related to the scattering and absorption characteristics of aerosol models. The polarization measurements in fine mode reduce the posterior error of ALH retrieval by 6-39%; however, this is relatively small for coarse mode. In particular, when it is applied to the transported dust and background dust aerosol types, the posterior error is only reduced by 1-8% after adding polarization measurements. For these two aerosol types with weak absorption at the ultraviolet band, increasing the number of angles observed in addition to increasing the polarization channel will more effectively improve ALH inversion. Compared with other aerosol and surface model parameters, the retrieval errors for the total volume column, effective variance, real part of the complex refractive index, and surface reflectance are the main factors affecting ALH retrieval. Therefore, reducing the theoretical retrieval error of these parameters will be helpful.  
Keywords:information content analysis; aerosol layer height; optimal estimation inversion; multiangle polarimetric remote sensing; a posteriori error +
Footnote †: journal: Remote Sens.
# Graphene-Based Flexible Electrode for Electrocardiogram Signal Monitoring
## 2 Research on Graphene-Based Flexible ECG Electrodes
### Invasive Graphene ECG Electrodes
#### 2.7.2 Radiolucent Graphene ECG Electrode  
Traditional implantable ECG electrodes are not electromagnetically transparent, which causes implantable ECG electrodes to interfere with X-ray imaging [82]. As an electromagnetically transparent material, graphene's good electrical properties, biocompatibility, and flexibility also make it suitable for use as an implantable electrode [83]. [PERSON], et al. proposed a radiolucent implantable graphene ECG electrode [84]. The electrode was fabricated on a biocompatible, CVD-prepared parylene C substrate. Monolayer graphene was CVD prepared and transferred onto the substrate, forming 16 graphene electrode sites by reactive ion etching. After wiring by Ti/Au/Pt, the electrode was encapsulated by another parylene C layer (Figure 5c). In vivo tests were carried out on a dog since humans and dogs have similar ECG characteristics. The test result show the radiolucent graphene ECG electrode has good biocompatibility and ECG monitoring performance. Besides, it does not interfere with the quality of X-ray imaging performed during ECG monitoring. The radiolucent graphene ECG electrode shows good application prospects in the field of implantable ECG monitoring.