esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Challenges
### Trust-Based Routing  
While trust models can defend WSNs against DoS attacks that cause observable changes in node behavior, they are less effective in stopping attacks that lead to network resource overuse or communication breakdown. Several of the reviewed studies explored the use of trust information by routing protocols as a means of strengthening the defense of WSNs. For example, the trust model proposed by [PERSON] et al. [42] works within a routing protocol. The cluster head that controls intra-cluster communication uses trust information to prevent communication with untrustworthy nodes. The trust evidence includes the number of successful or failed data transmissions between the cluster head and the sensors in the cluster or between the cluster head and other cluster heads. However, the model does not consider node authentication and the data/control packet forwarding metric, which limits the range of DoS attacks it can counter. Somewhat similarly, the routing protocol proposed in [41] uses trust information to select forwarding nodes and achieve better transmission efficiency. In addition, each node is assigned a verification probability that is dynamically adjusted, which makes the network more resistant to DoS attacks. However, the trust model focuses mainly on packet forwarding trust evidence. It ignores other direct trust evaluation metrics and does not consider indirect trust evaluation. Finally, the SDWSNs trust routing protocol proposed in [4] considers the trust values and the remaining energy of the nodes when selecting a data transmission path. However, the model is rather complex as it operates both in the control and the data planes of the network and involves multiple network layers (base stations, controllers, cluster heads, and other sensor nodes) and the network's functional layers (control plane and data plane). The trust model also needs further refinement.  
The models reviewed show that trust-based routing in WSNs is a promising approach to mitigating the impact of DoS attacks in WSNs. However, the reviewed models are neither limited nor too complex to be implemented. In addition, they do not consider the critically important data accuracy trust evidence. Further research is needed to develop effective and feasible trust-based routing protocols for WSNs.
## 4 Technologies for Nanocellulose Production
### Production of Nanocellulose from Cellulose
#### 4.2.3 High-Pressure Homogenization  
High-pressure homogenization is the most extensively used method for the preparation of CNFs. It is based on the fundamental principle of passing the cellulose slurry (0.5-1%) constantly through the small flow orifice of the homogenization valve under high pressure (>150 MPa) and velocity. This results in the generation of shear and impact forces, which break down the cellulose microfibrils into nanofibrils size by decreasing the cellulose fibrillation [99]. There are few disadvantages associated with this method such as clogging, energy intensity, disintegration of the cellulose fibers and the disruption of the crystalline structure [102]. High-pressure homogenization treatment was used for the production of NC from okara. The function properties of NC such as thickening, gelling, and thermal stability were improved by the high-pressure homogenization [103].
## 3 Results and Discussion
### Antimicrobial Activity of AuNPs
subtilis_>_C. albicans_>_A. brasiliensis_. The inhibitory effect of AuNPs is correlated with the chemical structure of Gram-positive and Gram-negative bacteria. In Gram-positive strains, the cell wall is composed of a thick layer of peptidoglycan (approximately 20-80 nm), compared with a thin layer (10 nm) in Gram-negative bacteria. Hence, the penetration of NPs into bacterial cell walls can be hindered, which explains the higher activity of synthesized AuNPs toward Gram-negative bacteria [1]. Another antimicrobial mechanism consists of the destruction of the cytoplasmic membrane because AuNP penetration leads to the inhibition of the selective permeability function [64]. After penetrating inside microbial cells, AuNPs react with cell components; nanoparticles inhibit the main functions, such as protein synthesis and DNA replications, and interact with the -SH group of amino acids,ultimately causing cell death [91]. The release of toxic ions, including Au+, upon treatment of microbial strains with AuNPs is another inhibitory mechanism. This release occurs faster at high concentrations and with smaller NPs; this mechanism could explain the high activity of synthesized AuNPs at high concentrations, as reported previously [1]. Upon bacterial treatment, released Au+ ions cover cell organelles and cell membranes through a reaction with -SH groups to form Au-SH groups, which, in turn, cause protein coagulation [92]. In addition, the formation of this new group (Au-SH) can involve the inhibition of the cell wall synthetase pathway, the disruption of microbial respiration, and the blocking of active transport chains [93]. Finally, ROS (reactive oxygen species)-mediated oxidative stress strongly contributes to the inhibitory mechanism [28]. The presence of NPs inside the cells enhances the production of free radicals, such as O2-, H2O2, and \(\bullet\)OH [93]. Under normal conditions, bacterial cells have the capacity to inhibit these toxic free or activated ions, whereas under stress (such as in the presence of NPs), the cells lose their potential to scavenge these ions. This blockage causes oxidative stress and redox imbalance, with ultimate cell death [94]. The disruption of sterol profiles in _Candida_ cell walls occurs through the inhibition of the ergosterol pathway by NPs; this is considered the main mechanism for the growth inhibition of _C. albicans_. Indeed, sterols are crucial components responsible for _Candida_ cell wall rigidity, integrity, homogeneity, and fluidity [95; 96].
# Response of NDVI and SIF to Meteorological Drought in the Yellow River Basin from 2001 to 2020
## 2 Materials and Methods
### Methods  
#### 2.3.1 Theil-Sen and Mann-Kendall (M-K)  
The advantage of Theil-Sen median trend analysis is that it does not require samples to obey a certain distribution, and is not disturbed by outliers. It has a strong ability to avoid measurement errors or outlier data [38]. Mann-Kendall is a nonparametric statistical test method used to judge the significance of trends [39]. The calculation formula is as follows:  
\[\beta=\text{median}\left(\frac{V_{k}-V_{j}}{k-j}\right),\forall\ k<j \tag{1}\]  
\[Z_{c}=\left\{\begin{array}{cc}\frac{S-1}{\sqrt{var}(S)}&S>0\\ 0&S=0\\ \frac{S+1}{\sqrt{var}}&S<0\end{array}\right. \tag{2}\]  
\[S=\sum_{k=1}^{n-1}\sum_{j=k+1}^{n}sign\big{(}V_{k}-V_{j}\big{)} \tag{3}\]  
\[var(S)=\frac{n(n-1)(2n+5)-\sum_{i=1}^{n}t_{i}(t_{i}-1)(2t_{i}+5)}{18} \tag{4}\]  
\[sign(V_{k}-V_{i})=\left\{\begin{array}{cc}1&V_{k}-V_{i}>0\\ 0&V_{k}-V_{i}=0\\ -1&V_{k}-V_{i}<0\end{array}\right. \tag{5}\]  
where, \(\beta\) is the change trend of time series; \(k\) and \(j\) are the corresponding times; \(V_{k}\) and \(V_{j}\) represent the NDVI or SIF values of the \(k\)th and \(j\)th years respectively. If \(\beta>0\), it indicates an increasing trend, and vice versa. At a given significance level \(\alpha\), when \(\ |\ Z_{c}\ |>Z_{\text{1-}\alpha/2}\) it means that the sequence is in \(\alpha\); the level changes significantly. When \(\ |\ Z_{c}\ |>1.96\), it means that 95% of the significance test has been passed.
# Aerial Physical Interaction in Grabbing Conditions with Lightweight and Compliant Dual Arms
## 2 System Description  
### Compliant Dual Arm  
The manipulator used for validating the methods described in Section 4 is a lightweight and compliant dual arm system developed at the GRVC Robotics Labs. A picture of the arms can be seen in Figure 2, indicating in Table 1 its main features. Each arm provides three degrees of freedom for end effector positioning in the following kinematic configuration [22]: shoulder yaw at the base (\(q_{1}\)), shoulder pitch (\(q_{2}\)), and elbow pitch (\(q_{3}\)). The arms are built with the Herkulex DRS-0201 smart servos, and a customized frame structure manufactured in carbon fiber and aluminum, providing full servo protection at the shoulder yaw joint with a pair of polymer bearings, and partial servo protection in the other two joints [21]. In order to estimate and control the torques and forces, the grabbing arm (right arm) integrates 14-bit resolution magnetic encoders that are interfaced through a STM32F303 microcontroller board, sending the deflection measurement to the main computer at 200 Hz with 1 ms latency. Each of the arms and the sensors are connected to the Raspberry Pi 3B+ through USB-to-USART interfaces, where control program of the arms is executed. The manipulator is fed with a 2S, 650 mAh LiPo battery, providing an operation time of around 20 min.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Total Weight** & **1.0 (kg)** \\ \hline
**Maximum lift load** & At elbow: 0.3 (kg) \\ (1 s playtime) & At shoulder: 0.12 (kg) \\ \hline
**Joint stiffness** & 5 (Nm/rad)—all joints \\ \hline
**Maximum joint speed** & 300 (\({}^{\circ}\)/s) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main features of the lightweight and compliant dual arm.  
Figure 2: Compliant dual arm used in the experiments.  
The tip of the forearm link includes an aluminum flange to facilitate the integration of the end effector in the manipulator. For safety reasons, the grabbing operation is conducted with a magnetic gripper (around 5 N force), using the linear metallic structure shown in Figure 1 for grabbing.
## 2 Materials and Methods
### Atmospheric Teleconnection Patterns  
Values of atmospheric circulation pattern indices were taken both from the Climate Prediction Center available on the NOAA National Climatic Data Center (NCDC) website ([[https://www.ncdc.noaa.gov/teleconnections/](https://www.ncdc.noaa.gov/teleconnections/)]([https://www.ncdc.noaa.gov/teleconnections/](https://www.ncdc.noaa.gov/teleconnections/)) accessed 4 May 2020), similar to previous research [18; 27; 39]. Due to the lack of Real-Time Multivariate Madden-Julian Oscillation (RMM) indices in NCDC, these indices were obtained from the Australian Bureau of Meteorology ([[http://www.bom.gov.au/climate/mjo/graphics/rmm.74](http://www.bom.gov.au/climate/mjo/graphics/rmm.74) toRealtime.txt]([http://www.bom.gov.au/climate/mjo/graphics/rmm.74](http://www.bom.gov.au/climate/mjo/graphics/rmm.74) toRealtime.txt) accessed 1 June 2020). We have chosen each one of the teleconnection patterns that can influence climate in the United States and the State of California. Namely El Nino 3.4 (ENSO) and the Pacific Decadal Oscillation (PDO) [31; 68], besides the Antarctic Oscillation (AAO), Arctic Oscillation (AO), Madden-Julian Oscillation (MJO), North Atlantic Oscillation (NAO), Pacific-North American Pattern (PNA), West Pacific Oscillation (WPO) and East Pacific Oscillation (EPO) were also taken in consideration.  
To find out the relationships between temperature and teleconnection patterns in California a correlation analysis using the partial non-parametric Spearman Test was performed at a 95% confidence level [63]. This method (the Spearman test) assigns less significance to outliers and is a more robust and resistant alternative for measuring correlation (linear or nonlinear). In addition, this partial test eliminates the effect that the time variable can exert on the temperature and telepattern variables to avoid fictitious relationships [51]. Finally, all the correlation results and their statistical significance are represented in monthly maps.
# Leveraging Energy Harvesting and Wake-Up Receivers for Long-Term Wireless Sensor Networks
## 5 Experimental Setup
### Ultra-Low Power Wake-Up Receiver  
Each wireless sensor node is equipped with a ULP WuRx presented in [13] only when the proposed approach is evaluated. This ULP WuRx employs On-Off Keying (OOK) modulation, the simplest form of Amplitude-Shift Keying (ASK) modulation, in which digital data are represented by the presence or absence of the carrier wave. The analog front-end of the receiver is designed for the 868-MHz frequency band and has a sensitivity measured to be \(-55\) dBm at a bitrate of 1 kbps. The computational capabilities of the ULP WuRx are achieved by the use of a ULP 8-bit microcontroller, the PIC12 LF1552 from Microchip, which was selected for its low current consumption (20 nA in sleep mode), fast wake-up time (approximately 130 \(\mu\)s at 8 MHz) and for the serial port supporting I2C and SPI, allowing easy communications with the node MCU and enough computational capability for parsing data and commands. When a carrier is detected, the front-end wakes up the microcontroller that reads the address embedded in the WuB and performs address matching. If the received address is not valid, the microcontroller goes back to a sleep state. If it is the valid one, it wakes up the node MCU using an interrupt.
# Dynamic Reconfiguration of Active Distribution Network Based on Improved Equilibrium Optimizer
## 4 Optimization Algorithms
### The Proposed Improved Equilibrium Optimizer Algorithm
#### 4.3.1 Population Initialization Based on Tent Mapping  
The initial population significantly influences the performance of the Intelligent Optimization Algorithm. In EO, the initial population concentration is generated based on the random vector \(\boldsymbol{rand}\) in Equation (17). However, this completely random initialization cannot ensure a uniform distribution of the initial population within the search space. Additionally, if the initial population is overly concentrated, it may lead to local optimization, hindering the search for the optimal solution in the distribution network reconfiguration problem.  
Chaotic sequences exhibit characteristics such as randomness, orderliness, and transversality. The Tent Chaotic Map is capable of quickly generating uniform random sequences, offering advantages over other mapping algorithms. In this study, the TentChaotic Map is employed to improve the initialization of the EO population, ensuring a well-distributed initial population that covers the search space effectively with good uniformity and diversity. This enhancement improves both the performance and efficiency of EO in the early stages of the process. The expression is given in Equation (36), and the population initialized using the Tent Chaotic Map is shown in Equation (37):  
\[Y_{t+1}=\left\{\begin{array}{ll}2Y_{t}&0\leq Y_{t}<0.5\\ 2(1-Y_{t})&0.5\leq Y_{t}\leq 1\end{array}\right. \tag{36}\]  
\[\mathbf{C}_{i}^{initial}=\mathbf{C}_{min}+Y_{i}(\mathbf{C}_{max}-\mathbf{C}_{min})\;i=1,2, \ldots,n \tag{37}\]  
where \(C_{max}\) and \(C_{min}\) denote the upper and lower bounds of the search space, respectively.
###### Abstract  
In maritime communications, the ubiquitous Morse lamp on ships plays a significant role as one of the most common backups to radio or satellites just in case. Despite the advantages of its simplicity and efficiency, the requirement of trained operators proficient in Morse code and maintaining stable sending speed pose a key challenge to this traditional manual signaling manner. To overcome these problems, an automatic system is needed to provide a partial substitute for human effort. However, few works have focused on studying an automatic recognition scheme of maritime manually sent-like optical Morse signals. To this end, this paper makes the first attempt to design and implement a robust real-time automatic recognition prototype for onboard Morse lamps. A modified k-means clustering algorithm of machine learning is proposed to optimize the decision threshold and identify elements in Morse light signals. A systematic framework and detailed recognition algorithm procedure are presented. The feasibility of the proposed system is verified via experimental tests using a light-emitting diode (LED) array, self-designed receiver module, and microcontroller unit (MCU). Experimental results indicate that over 99% of real-time recognition accuracy is realized with a signal-to-noise ratio (SNR) greater than 5 dB, and the system can achieve good robustness under conditions with low SNR.  
automatic recognition; Morse code; k-means clustering; machine learning; maritime communication; real-time; free space optical communication +
Footnote †: journal: Applied Sciences
## 3 Research Execution and Analysis
### Derivation of Usability Indicators
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**N = 20** & \multicolumn{2}{c}{**Round One Delphi Data**} & \multicolumn{2}{c}{**Round Two Delphi Data**} \\ \hline
**Indicator** & **M** & **SD** & **CV** & **M** & **SD** & **CV** \\ \hline Effectiveness & 4.700 & 0.470 & 0.100 & 4.250 & 0.444 & 0.104 \\ Learnability & 4.750 & 0.444 & 0.093 & 4.250 & 0.444 & 0.104 \\ Efficiency & 4.600 & 0.503 & 0.109 & 4.150 & 0.366 & 0.088 \\ Memorability & 2.600 & 0.995 & 0.383 & - & - & - \\ Error & 3.650 & 0.813 & 0.223 & 4.100 & 0.447 & 0.109 \\ Satisfaction & 4.400 & 0.503 & 0.114 & 4.350 & 0.489 & 0.112 \\ User-Centered & 4.900 & 0.308 & 0.063 & 4.600 & 0.503 & 0.109 \\ Easy to use & 4.200 & 0.410 & 0.098 & 4.100 & 0.447 & 0.109 \\ Navigation & 4.250 & 0.550 & 0.129 & 4.000 & 0.324 & 0.081 \\ Screen Design and Layout & 4.150 & 0.745 & 0.180 & 3.750 & 0.550 & 0.147 \\ Terminology & 4.100 & 0.447 & 0.109 & - & - & - \\ Feedback & 4.150 & 0.745 & 0.180 & 3.800 & 0.410 & 0.108 \\ Consistency & 4.250 & 0.550 & 0.129 & 4.000 & 0.459 & 0.115 \\ Remote Presentation & 3.200 & 0.616 & 0.193 & 3.650 & 0.489 & 0.134 \\ Customization & 1.750 & 0.851 & 0.486 & - & - & - \\ Sensory Forms & 3.200 & 0.768 & 0.240 & 2.350 & 0.671 & 0.286 \\ Unnecessariness & 3.900 & 0.308 & 0.079 & 3.950 & 0.224 & 0.057 \\ Controllability & 4.050 & 0.394 & 0.097 & 3.900 & 0.447 & 0.115 \\ Task Consistency & 2.300 & 1.031 & 0.448 & - & - & - \\ Findability & 4.650 & 0.489 & 0.105 & 4.250 & 0.550 & 0.129 \\ Accessibility & 4.650 & 0.489 & 0.105 & 4.100 & 0.553 & 0.135 \\ Interactivity & 3.850 & 0.875 & 0.227 & 4.000 & 0.324 & 0.081 \\ Credibility & 4.900 & 0.308 & 0.063 & 4.900 & 0.308 & 0.063 \\ Content Relevance & 4.350 & 0.489 & 0.112 & 4.050 & 0.224 & 0.055 \\ Readability & 4.650 & 0.489 & 0.105 & 4.100 & 0.308 & 0.075 \\ Responsiveness & 3.750 & 0.910 & 0.243 & 3.500 & 0.607 & 0.173 \\ Convenience & 3.950 & 0.394 & 0.100 & 3.950 & 0.224 & 0.057 \\ Privacy Protection & 4.950 & 0.224 & 0.045 & 4.850 & 0.366 & 0.075 \\ Property Protection & 4.950 & 0.224 & 0.045 & 4.900 & 0.308 & 0.063 \\ Download Speed & 1.750 & 1.020 & 0.583 & - & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Data from two rounds of the Delphi survey. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Effectiveness** & **Learability** & **Efficiency** & **Error** & **Satisfaction** & **User-Centered** \\ \hline Easy to use & Navigation & \begin{tabular}{c} Screen Design \\ and Layout \\ \end{tabular} & Feedback & Consistency & \
\begin{tabular}{c} Remote \\ Presentation \\ \end{tabular} \\ \hline Unnecessariness & Controllability & Findability & Accessibility & Interactivity & Credibility \\ \hline Content Relevance & Readability & Responsiveness & Convenience & Privacy Protection &
\begin{tabular}{c} Property \\ Protection \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Usability indicators for medical websites.
# Design of SWB Antenna with Triple Band Notch Characteristics for Multipurpose Wireless Applications
## 7 Comparative Analysis  
Some distinct techniques were already well demonstrated in achieving a wideband antenna with single/dual/triple band-notch characteristic [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 17; 18; 19; 20; 21; 22; 23; 24; 25] in the introductory section of this article. Thus, it is worth comparing the proposed design with the existing designs stated in the literature as presented in Table 3. It can also be seen from Table 3 that the presented antenna has considerably larger bandwidth ratios than the other referenced antennas. Although the size of the antenna is somewhat larger than those in the reported literature, this is nevertheless the best one with respect to size of frequency range compared to other works. The main advantage of the proposed antenna is that it can be tuned independently, ensuring that the notch frequencies are minimally mutually coupled. Rejection levels of \(-9.9\) dB, \(-3.6\) dB, and \(-1.8\) dB were encountered at notch frequencies of 2 GHz, 6 GHz, and 10 GHz, respectively, which confirms the efficacy of band-notched features of this presented design. The higher the rejection levels, the better the triple band notch antenna performance is. It could be observed that the proposed antenna showed superior performance compared to most of the previous studies in terms of bandwidth, gain at passband, ratio bandwidth, bandwidth percentage, and bandwidth dimension ratio. Therefore, the proposed triple band-notched design is a prominent radiating structure for SWB applications.  
Figure 18: Transfer function (S\({}_{21}\)) for the proposed triple band notch antenna for face-to-face and side-by-side configuration.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Ext.**} & \multicolumn{1}{c}{**Single-
## 2 Materials and Methods
### Discrete Approach: Shortest Paths in Airway Networks
#### 2.3.1 Graph Construction  
Discrete approaches to (flight) path planning fall into two classes. The first class are sampling-based algorithms. They construct the search graph by some kind of sampling during the execution of the shortest path algorithm, which is usually an \(A^{*}\)-method. This class includes rapidly exploring random trees (RRT) and graph (RRG) algorithms, that are often used in robot path planning [8]. There are versions that guarantee convergence to a global optimum with probability one [39], however, although undoubtedly often extremely efficient in practice, these methods do not provide a priori error bounds or complexity estimates.  
The second class are graph-based algorithms, that take the search graph as an input. Impressive super-fast performance in practice, and also theoretically for special classes of graphs, has been achieved by making use of preprocessing as well as sophisticated data structures. However, \"proving better running time bounds than those of [PERSON]'s algorithm is unlikely for general graphs\" [6]. In many applications, including traditional flight plannning on airway networks, the search graph is canonical. In applications involving space and time discretization, like in free flight, graph construction is a degree of freedom. Using an appropriate discretization, a priori bounds on the runtime and the accuracy of the solutions can be derived. This is the approach that we take.  
We cover free flight zones with \"locally densely\" connected digraphs, i.e., digraphs with a certain density of vertices and arcs.  
Definition 1: A digraph \(G=(V,A)\) is said to be \((h,l)\)-dense in a convex set \(\Omega\subset\mathbb{R}^{2}\) for some \(h,l>0\), if it satisfies the following conditions:  
1. containment: \(V\subset\Omega\)
2. vertex density: \(\forall x\in\Omega:\exists v\in V:\|x-v\|\leq h\)
3. arc density: \(\forall x,y\in V,\|x-y\|\leq 2h+l:(x,y)\in A\). We call \(h\) the vertex density and \(2h+l\) the connectivity radius of an \((h,l)\)-dense graph.  
With this definition, \(|V|\in\mathcal{O}(h^{-2})\) and \(|E|\in\mathcal{O}((2h+l)^{2}h^{-4})\) hold. Furthermore, it is easy to see that this graph structure implies that \(G\) is strongly connected and therefore \(P\) is nonempty, i.e., a path from \(x_{\Omega}\) to \(x_{\Omega}\) exists.