esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Study Area and Data  
### The Ludoialm Landslide  
The Ludoialm is located in the municipality of Munster in Tyrol, Austria (Figure 1), where the Northern Calcareous Alps form the regional geological framing. The landslide area is mainly pasture and partly covered by forest. Except for the periods of reactivations with high velocities, the landslide could be classified as a very slow to slow planar soil slide [50]. According to geological surveys in 2014 and before, the landslide was moving at a certain speed every year, e.g., approximately 0.6 m per year between 1992 and 2004 [51].  
The initiation of the landslide is dated to 1952 according to aerial views, historic information, and maps [51]. Two remarkable reactivations of the Ludoialm landslide occurred on 15 April 1967 and 5 February 1999, in the past decades. The landslide event in 1967 was most probably due to intensive snow melting. Furthermore, several, either active or inactive, rotational secondary slides have occurred at the toe of the landslide area, leading partly to debris flow events.  
The horizontal length of the landslide is about 550 m, the maximum width is 180 m, and the maximum thickness is about 20 m. After the two reactivation events, a material loss of approximately 486,000 m\({}^{3}\) in the landslide area can be estimated by the analysis of GIS data. The basal sliding surface is roughly parallel to the slope surface, with a small dip angle of only about 12\({}^{\circ}\) based on the geological survey.
# Hunting Molecules in Complex Matrices with SPME Arrows: A Review
## 5 SPME Arrow Applications
### Terpenes in Cannabis  
With the rapid growth of the cannabis market taking place, the need for analytical testing has become more critical. An area of interest in this market is being able to identify and place cannabis flowers into the correct chemical variety, otherwise known as chemovar. To properly classify cannabis chemovars, a comprehensive chemical profile examining compounds, such as terpen and cannabinoids, is collected [57]. An analysis of terpen is typically done via headspace--gas chromatography--mass spectrometry (HS-GC-MS). Herein, a 1.1 mm 120 \(\upmu\)m divinylbenzene (DVB)/PDMS SPME Arrow was used to analyze the terpene content in _Humulus lupulus_ (hops), and individual terpene responses were compared to that of a HS-syringe method typically used for this application and a 65 \(\upmu\)m DVB/PDMS traditional SPME fiber. Hops were used in place of cannabis, as cannabis could not be legally obtained. Hops were ground using drying ice and then stored in the freezer until needed. Ten-to-fifteen milligrams of ground hops were added to a 20 mL crimp top HS vial.  
Current methodologies recommend extraction times of 10 min for the traditional SPME fiber analysis of terpen [58]. Improvements to this parameter alone have the potential to decrease instrument runtimes and increasing the number of samples that contract laboratories are able to test. As can be seen in Figure 7, average responses for a 10 min extraction time using a traditional SPME fiber are equivalent to that of a 2 min extraction time with the SPME Arrow. This can be done without sacrificing reproducibility, as both techniques showed % RSDs under \(\leq\)10%. Lighter terpen (monoterpenes) gave better responses on the SPME Arrow, while the heavier terpen (sesquietrepenes) were more comparable. However, the traditional fiber did provide slightly better responses for the sesquiterpenes.
# Secure Data of Industrial Internet of Things in a Cement Factory Based on a Blockchain Technology
## 3 Architecture for a Cement Factory Based on Blockchain Technology
### Blockchain Service Layer  
The blockchain service layer split into two subsections: a set of lightweight nodes and a private blockchain. This layer also contains the suitable modules, which work to organize the common services needed to provide features of blockchain technology. ECC [29] adopted in order to give a high-speed implementation. We designed the lightweight nodes using an STM32F427 that based on ARM Cortex-M4, which has been shown to be effective and efficient for IIoT applications and is an appropriate choice, especially for cryptographic algorithms [32]. The device authentication mechanism used public and private keys generated by ECDSA, which is an algorithm that is characterized by low complexity, very fast execution and requirements low storage capacity [29]. The use of ECDSA for industrial applications has been approved and certified by the NIST Cryptographic Algorithm Validation Program [32].  
In our Blockchain service layer, we designed several lightweight nodes instead of a single node, which helps the registered users, devices or machines to efficiently access the blockchain network, reducing the pressure and preventing system failure from occurring, compared with a single node strategy, which can lead to problems of instability and overall system failure [9]. Our architecture also achieved the system stability and availability of services that make it an efficient solution for integrating blockchain technology with industrial IoTs, which require continuous data processing in real-time.
# A New Method of Applying Data Engine Technology to Realize Neural Network Control
## 2 Theoretical Background
### Objective of the Control Method  
Most of the current advanced control technology uses independent software system, through OPC implementing data communication with the DCS system, and the advanced control algorithm and its execution process often present the 'black box' feature, which makes it difficult for users to perform monitoring and online debugging of advanced control algorithms, and the application is not effective. The purpose of this study is to use DE technology to overcome the shortcomings of existing technology, providing an advanced method to implement integrated control technology in industrial control system: advanced control is integrated into the configuration software IAPlogic of the industrial control system based on the unified real-time shared memory by advanced control configuration components, the management, and configuration of advanced control components are in accordance with the conventional control components. The configuration interface is shown in Figure 3 below; the method has the following advantages:  
(1) The data structure of the advanced control algorithm is the same as that of the conventional control algorithm. The computing resources of the advanced control algorithm are close to each other. The calculation process of the advanced control can be handled directly in the control station such as PLC and IPC. Therefore, it is no longer necessary to configure the high-end computer to run the advanced control algorithm.  
(2) The advanced control algorithm is integrated into the configuration software in the form of advanced control components, which can greatly improve the real-time performance of the advanced control strategy.  
(3) The functions of parameter modification, input/output, and calculation of intermediate variables in advanced control strategy can be realized through the simple combination of configuration components, and the calculation process of each group of components is monitored by the monitoring software so that the graphical configuration relationship very intuitive, real-time data processing transparent, which brings great convenience to the user's online debugging.  
(4) The advanced control and traditional control adopt uniform configuration and management modes. There is no essential difference between the resources used and the methods used, and user operation is very convenient, effectively reducing the costs of the development, commissioning, operation, and maintenance of industrial control systems. The integrated graphical configuration programming environment and reusable configuration components make it more flexible for engineers to handle heterogeneous controlled devices and more with online optimization of scalability.  
Figure 2: The data engine control component performs a multi-agent structure.
## 3 Results and Discussion
### Gallium Nitride (GaN) Readout Circuit for Position-Sensitive Photomultiplier Tube (PSPMT)
Figure 13a shows the detected positions of the PMT arranged in an \(8\times 8\) array and Figure 13b shows the corresponding position coordinates. The identification of the positions is accurately determined. Figure 10: (a) Equivalent circuit of SiPM. (b) Current pulse generated from scintillation. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline \(N_{ph}\) & 1000 \\ G & \(7.5\times 105\) \\ PDE & 0.40 \\ \(\tau_{d}(ns)\) & 50 \\ \(\tau_{r}(\mu s)\) & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Silicon photomultiplier (SiPM) current pulse parameters. Figure 9: Simulation model of the GaN readout system. Figure 11: (**a**) Output current from four channels of discretized position circuit (DPC). (**b**) Output voltage of transimpedance amplifiers (TIAs). Figure 12: Simulation output of adder and integrator. Figure 13: Position verification of the readout circuit. (**a**) position of the input current pulse applied. mutual exclusively. (**b**) Computed position coordinates that correspond to the individual input current pulse.
## 3 Results
### Perceived Usefulness (PU)  
As the PU data follows a non-normal distribution, this study employed the Wilcoxon-signed rank test. The result indicated that users' perceptions of the usefulness of hand gesture recognition and joystick control are statistically significantly different. It was observed that the rank mean, \(Z=-3.636\) and the level of significance, \(p<0.001\), indicated that users' PU is affected by different types of interactive interfaces. Further analysis showed that users perceive the joystick control (gesture recognition: M = 17.21, SD = 4.24; joystick control: M = 28.12, SD = 5.360) to be more useful for completing tasks while operating the system (see Figure 6).  
To control the effects of other relevant factors like gender, college major, and task completion time, this study analyzed these factors' effects on PU. The results suggested  
Figure 6: Users’ subjective evaluations of different interactive interfaces (i.e., hand gesture recognition/joystick control). \(\mathbf{\texttt{{}^{***}}}p<0.001\), \(\mathbf{\texttt{{}^{*}}}p<0.05\).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Name** & **Notation** & **Description** \\ \hline Wilcoxon Signed-Rank Test & \(Z\) & Rank Mean value \\ Kruskal-Wallis Test & H & Test Statistics \\ Paired-Sample T & T & T Statistics based on mean and SD error \\ One-Way ANOVA & F & Variation between sample mean \\ General Notation & p, M, SD & Significance level, Mean, and Standard \\  & & Deviation, respectively \\ \hline \hline \end{tabular}
\end{table}
Table 5: The Description of Various Statistical Analyses Used.  
that there was no statistically significant effect, meaning that users' PU is not influenced by differences in gender, college major, and task completion time.
# Recent Advances in Bio-Based Wood Protective Systems: A Comprehensive Review
## 3 Bio-Based Preservatives and Impregnators  
One of the most immediate barriers to counter the weathering and/or biological-induced decay of wood is the application of preservatives or impregnators on wood samples. The manifested trend toward environmental sustainability and eco-friendly solutions calls for the need to shift from the classical chemical wood preservatives, which can be harmful to the environment, toward bio-based products. A comparative study was conducted to investigate the impacts and effectiveness of bio-based and commercially available chemicals for wood preservation [91]. According to the documented results, Colatan GT10, a Quebracho tennin mix, was identified as the most promising bio-based wood preservative, with lower toxicity compared with copper-based chemicals, which are frequently commercially sold. Although it is generally assumed that bio-based chemicals have lower ecotoxicity, this is not always true. As pointed out in the same study, in some circumstances, bio-products may be even more toxic than the commercially available ones, highlighting the importance of conducting extensive ecotoxicity studies before the employment of a product and carefully investigating the environmental effects possibly associated with it [91]. Several natural wood preservatives are extracts derived from plants and from vegetables. They include plant essential oils as well as plant extracts, containing several and varying active molecules. For example, stillenes have been investigated as possible impregnators for Scots pine sapwood (_Pinus sylvestris_ L.). The impregnation of wood with crude heartwood extract containing the stillenes pinosylvin (PS) and pinosylvin monomethyl ether (PSM) was able to reduce fungal growth and, consequently, the decay of the material [92]. The main issue related to stilbenes is that they are prone to fungi-induced
## 3 Environmental Applications of Graphene-Based Photocatalysts
### Antimicrobial Properties of Graphene-Based Composite Photocatalysts
The possible mechanism of the antibacterial activity is based on the assumption that the positively charged amino group in CS could interact with negatively charged components on the surface of bacterial cells [110]. Chitosan-modified GO (CS@GO) significantly inhibits the bacterial survival (ca. 96% of inhibition) with good stability during three cycles of experiments (above 90%), and importantly, CS@GO shows higher effect than reference samples, i.e., CS or GO [92]. In addition, chitosan-polyethyleneimine (PEI)-graphene oxide (GO) nanocomposite removes also the heavy metals (Cr(VI), Cu(II), and Pb(II)), nitrate and bacteriophage [103]. It has also been reported by [PERSON] et al. [108] that the alizarin (AZ), the dye known as anti-biofilm formation agent [111; 112], has conjugated on GO (AZ-GO), which results in the inhibition of biofilm formation of _C. albicans_. Additionally, the treatment of _C. albicans_-infected nematode (_Caenorhabditis elegans_) with AZ-GO has caused an increase in the survival of _C. elegans_. Accordingly, the presence of GO stabilizes the conjugated antimicrobial agents and gives higher activity than agents themselves. The nanohybrids of graphene with metals and metal oxides have also been proposed in order to obtain the efficient antimicrobial agents, e.g., Ag [113; 114; 115; 116; 117], Ti [118], NiO [119], ZnO [120; 121; 122; 123] and TiO\({}_{2}\)[124; 125; 126], as summarized in Table 3.  
Silver deposition on GO/rGO significantly enhances the antimicrobial activity (against _E. coli_, _S. aureus_, oral pathogens _C. albicans_, _Lactobacillus acidophilus_, _Streptococcus mutans_, and _Aggregatibacter actinomycetemcomitans_) due to the intrinsic activity of silver [113; 114; 115; 116; 117]. The effects for aquatic microbial communities have been studied by [PERSON] et al. [115], and it has been proposed that both GO and Ag-GO decrease the activity of extracellular enzymes and generate ROS, e.g., singlet oxygen, hydroxyl radicals (\({}^{\bullet}\)OH), super oxide anion rad
## 4 Results and Discussions  
The proposed optimization method is employed to determine the full-range energy consumption of the bipedal robot model across different lengths and mass ratios within specific ranges of walking speed and step length. The variations in this parameter are analyzed to identify the optimal link mechanism for the bipedal robot. The following Table 2 defines the considered parameters and specifies their ranges.  
The aim of this study is to optimize the full-range energy consumption. Starting with the consideration of the overall structural design of the bipedal robot, the robot configuration is optimized by adjusting the mass and linkage ratios among different structures. Considering that the simplified robot consists of the thigh, calf, hip joint, and upper body, the mass ratio of leg to body and hip, \(m_{per}\); the mass ratio of hip to body, \(m_{hyper}\); the length ratio of body to leg, \(l_{hyper}\); and the length ratio of thigh length to leg, \(l_{hyper}\), are adjusted. By solving the walking gait and energy consumption within a certain speed range, the optimal configuration for the bipedal robot can be identified.  
The walking gait parameters \((V,D)\) for the bipedal robot are obtained as indicated in the table above (the gait parameter ranges are derived from the range of step lengths and walking speeds observed in human walking). Following the optimization approach for the full-range energy consumption introduced in the previous section, the walking performance of the bipedal robot is assessed under different mechanism parameters. The average full-range energy consumption, \(COT_{ave}\), is calculated for different walking speeds and step length ranges. Subsequently, the \(COT_{ave}\) values for different mechanism parameters are compared to identify the minimum value, \(COT_{min}\). By analyzing the gait of the bipedal robot, the optimized mechanism parameters for the linkage system are determined.  
This study draws inspiration from the walking speed and step length range of human walking to optimize the design within the typical gait range. For specific requirements, such as longer step lengths or larger walking speeds, the optimization of the mechanism can be based on the conclusions derived from the above general range, obtained via similar research methods.
# Spreading-Based Voice Encryption by Means of OVSF Codes
## 5 Conclusions  
The proposed scheme presented an alternative for the secure transmission of voice signals. Its main characteristic is the generation of a signal with a high level of uncertainty (which sounds like noise), that has no relation to the original signal. The experimental validation showed a high entropy value of the encrypted signal and a very low correlation between the original and encrypted signal. On the other hand, the key space was very high thanks to the process of spreading and scrambling. Finally, the execution times for encryption and recovery allowed the application of the algorithm in real-time systems.  
As future work we propose to analyze the memory consumption of this solution and the implementation of this solution in mobile phone systems.  
Conceptualization, D.R.; Formal analysis, D.M.B.; Investigation, D.R.; Methodology, D.M.B.; Supervision, E.M.; Validation, D.R.; Visualization, E.M.; Writing--original draft, D.M.B.; Writing--review and editing, E.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Confirmation of Carbanation of Cellulose  
To confirm the successful modification of cellulose, Fourier Transform Infrared Spectroscopy (FTIR) of the original cellulose and CC with different DS were performed, and the results are shown in Figure 2. The obvious absorption peak at 1715 cm\({}^{-1}\) for the CC sample was assigned to the stretching vibration of the carbonyl group of the carbamate [32; 33]. This indicated that urea had successfully reacted with cellulose to form CC.  
Figure 1: Relationship between the CC degree of substitution and carbamate reaction conditions: temperature (time: 3 h and W\({}_{\text{urea}}\)/W\({}_{\text{cellulose}}\): 0.334) (**a**), time (temperature: 140 \({}^{\circ}\)C and W\({}_{\text{urea}}\)/W\({}_{\text{cellulose}}\): 0.334) (**b**), and weight ratio of urea/cellulose (time: 3 h and temperature: 140 \({}^{\circ}\)C) (**c**).  
Figure 2: FTIR of (**a**) cellulose (bleached eucalyptus kraft pulp), (**b**) CC (DS = 0.143), (**c**) CC (DS = 0.133), (**d**) CC (DS = 0.123), and (**e**) CC (DS = 0.098).  
NMR spectroscopy has been proven to be a convenient and reliable method to elucidate the chemical structure of modified cellulose CC [31]. The solid-state NMR carbon spectra of the cellulose and cellulose carbamate were determined in the form of solid powder, as shown in Figure 3. Typical chemical shifts of cellulose carbamate was observed, in which the carbon shift of C-1 was at 110 ppm, C-4 at 88 ppm, C-2, C-3 and C-5 at 74.1 ppm, and C-6 at 64 ppm [20]. Significant signal of carbonyl carbon appeared at 161 ppm [34]. The results showed that carbamate groups were successfully introduced into the cellulose skeleton.
## 3 Results and Discussion
### Solubilisation Test and Soil-Washing Tests with Hradcany Soil
flask, with 10 g/L of glucose, 10 g/L of rapeseed oil and without any nitrogen source, performed best in contaminant removal among all the surfactants. To date, the most successful commercial application is that of _Candida bombicola_ ATCC 22,214 as it produces more than 400 g/L sophorolipids [12]. A group of researchers investigated different properties of sophorolipids produced by _Candida bombicola_, including emulsifying activity, fat and oil solubilisation capacity and their stability at wide ranges of pH, salt concentrations and temperatures, and concluded that this biosurfactant has an important potential for environmental applications [34]. Biosurfactant A (also from _Candida bombicola_ CB2107) cultivated with 1 g/L each of glucose and rapeseed oil, devoid of nitrogen source, was less effective in C10-C40 hydrocarbon remediation than H. Hence there could be an influence of concentration of carbon source on the remediation potential of biosufactants. Despite identical production conditions as for H, biosurfactant B (_Yarrowia lipyolytica_) was seen to be less efficient. Biosurfactant C, also by _Yarrowia lipolytica_, but grown in an automatic bioreactor, and the rest of the conditions being identical to H, also was less efficient than H. Clearly, both strain and production conditions significantly impact the potential efficiency of the produced biosurfactant for extractive soil cleaning. Although _Yarrowia_, among other yeasts isolated from petroleum-contaminated soil, was shown to be the major organism responsible for the degradation of hydrocarbon [35], novel research with different strains has been limited so far.
# Pilot-Based Adaptive Channel Estimation for Underwater Spatial Modulation Technologies
## 1 Introduction
\begin{table}
\begin{tabular}{l l} \hline AWGN & Additive White Gaussian Noise \\ BER & Bit Error Rate \\ bpcu & Bit Per Channel Use \\ CSI & Channel State Information \\ EFGSM & Enhanced Fully Generalized Spatial Modulation \\ FGSM & Fully Generalized Spatial Modulation \\ GSM & Generalized Spatial Modulation \\ GSSK & Generalized Spatial Shift Keying \\ IAS & Inter-antenna Synchronization \\ ICI & Inter-carrier Interference \\ LMS & Least Mean Square \\ LoS & Line of Sight \\ LS & Least-Squares \\ MIMO & Multiple-Input Multiple-Output \\ ML & Maximum Likelihood \\ M-PSK & M-ary Phase Shift Keying \\ M-QAM & M-ary Quadrature Amplitude Modulation \\ MSE & Mean Square Error \\ P-CSI & Perfect Channel State Information \\ pdf & Probability Density Function \\ PSAM & Pilot Symbol Assisted Modulation \\ RF & Radio Frequency \\ RLS & Recursive Least-Squares \\ SIMO & Single-Input Multiple-Output \\ SM & Spatial Modulation \\ SMT & Spatial Modulation Technology \\ SNR & Signal to Noise Ratio \\ SSK & Spatial Shift Keying \\ UWA & Underwater Acoustic \\ UWAC & Underwater Acoustic Communication \\ UWC & Underwater Communication \\ V-BLAST & Vertical-Bell Laboratories Layered Space-Time \\ \hline \end{tabular}
\end{table} 
Table 1: Acronyms. Section 4. In Section 5, RLS adaptive channel estimation algorithm described in brief. The simulation results and discussion are presented in Section 6. Finally, the paper is concluded in Section 7.