esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluation of _Jatropha curcas_ and Pistachio Shell Particles as Modifier for Asphalt Binder
## 2 Materials and Methods
### Asphalt Binders Characterization  
Dynamic viscosity was measured on a Fungilab EVO Expert viscosimeter according with ASTM 4401-02 using 10.5 g samples and a TR9 geometry. The measurements were performed at 135, 160, and 190 \({}^{\circ}\)C, establishing 30 min as thermal equilibrium time, the shear rate used was 68 s\({}^{-1}\) developing a torque resistance between 50% and 98%, the shear rate was maintained for a period of 5 min to establish the steady state. The softening point of the asphalt was determined according to the specifications of the ASTM D36/D36M-14e1 method. The phase separation or storage stability test was carried out based on the ASTM D5892-00/M-MMP-4-05-022/02 methods to identify the compatibility between the asphalt and the modifier particles since this is one of the main indicators revealing the efficiency of the asphalt modification process. This test consisted of pouring asphalt into a collapsible aluminum tube heated at 163 \({}^{\circ}\)C for 48 h. After the heating period, the sample was placedin a freezer at 0 \({}^{\circ}\)C for at least 4 h. The sample tube was then divided into three sections, discarding the intermediate portion, and the softening points of the top and bottom sections were measured. If the difference between the softening points of both sections wasless than 2.5 \({}^{\circ}\)C, then the sample wasconsidered to show good storage stability [26].  
Fluorescence microscopy was used to evaluate how the modifier particles are dispersed into the asphalt matrix. This analysis was carried out using a Carl Zeiss Axiotech microscope, using a 20\(\times\) magnification. The technique is based on the fluorescence phenomenon, which largely depends on the concentration of modifier in the asphalt, and it is a good method that allows the identification of the dispersion pattern of modifier particles in asphalt matrix; the absence of fluorescence reveals a homogenous dispersion attributed to a compatibility between modifier and asphalt matrix [27; 28].  
The rheological behavior of the asphalt blends was measured on an [PERSON] dynamic shear rheometer (DSR) MCR 301 model. Temperature sweeps on oscillatory mode were applied at a fixed deformation of 12% and a frequency of 10 rad/s, from 52 to 82 \({}^{\circ}\)C, at intervals of 6 \({}^{\circ}\)C. The behavior of the ratio of the complex modulus to the phase angle sine (\(\,\mathrm{I}\,\mathrm{G}^{\ast}\)\(\,\mathrm{\SIUnitSymbolMicro}\)\(\,\mathrm{s}\)) as a function of temperature was monitored since this parameter has been related to a traffic speed of about 100 km/h.  
The thermal stability of the asphalt samples was investigated through thermogravimetric analysis, which is useful for revealing any possible intermolecular interactions between the asphalt fractions and the modifier components. For this purpose, a TA Instruments equipment, model SDT Q600, was used, with samples of 15 mg and a heating rate of 10 \({}^{\circ}\)C/min at temperatures ranging from room temperature to 700 \({}^{\circ}\)C.
# An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers
###### Abstract  
In recent years, the botnets have been the most common threats to network security since it exploits multiple malicious codes like a worm, Trojans, Rootkit, etc. The botnets have been used to carry phishing links, to perform attacks and provide malicious services on the internet. It is challenging to identify Peer-to-peer (P2P) botnets as compared to Internet Relay Chat (IRC), Hypertext Transfer Protocol (HTTP) and other types of botnets because P2P traffic has typical features of the centralization and distribution. To resolve the issues of P2P botnet identification, we propose an effective multi-layer traffic classification method by applying machine learning classifiers on features of network traffic. Our work presents a framework based on decision trees which effectively detects P2P botnets. A decision tree algorithm is applied for feature selection to extract the most relevant features and ignore the irrelevant features. At the first layer, we filter non-P2P packets to reduce the amount of network traffic through well-known ports, Domain Name System (DNS). query, and flow counting. The second layer further characterized the captured network traffic into non-P2P and P2P. At the third layer of our model, we reduced the features which may marginally affect the classification. At the final layer, we successfully detected P2P botnets using decision tree Classifier by extracting network communication features. Furthermore, our experimental evaluations show the significance of the proposed method in P2P botnets detection and demonstrate an average accuracy of 98.7%.  
Keywords: botnet detection; anomaly detection; network traffic identification; machine learning +
Footnote †: journal: Applied Sciences
However, chlorine also reacts with other constituents in water to generate unwanted organic and inorganic chlorination byproducts (CBPs); in seawater, for example, trihalomethane, haloacetic acids, chloramines, bromate, chlorite, and perchlorate are produced [17]. Due to their persistency in the environment and potential negative impacts on aquatic lives, ClO\({}_{3}\)\({}^{-}\) and ClO\({}_{4}\)\({}^{-}\) have been of special public interest. In humans, ClO\({}_{3}\)\({}^{-}\) causes hematological imbalance by decreasing erythrocyte count and hemoglobin. ClO\({}_{4}\)\({}^{-}\) also interferes with iodine uptake to cause thyroid malfunctions [19]. According to a report from WHO, ClO\({}_{3}\)\({}^{-}\) may also cause renal tumors [20]. In this study, we have evaluated the fate of the total residual oxidant (TRO) and formation of inorganic CBPs including ClO\({}_{3}\)\({}^{-}\) and ClO\({}_{4}\)\({}^{-}\) during in situ electrochlorination with seawater using Ti/RuO\({}_{2}\) electrodes. Then, the results were compared with those during direct OCl\({}^{-}\)-injection to seawater. The specific goals of this study were to: (1) monitor TRO fate when electrochlorination or direct OCl\({}^{-}\)-injection was applied for seawater; (2) compare the amounts of ClO\({}_{3}\)\({}^{-}\) and ClO\({}_{4}\)\({}^{-}\) formed during electrochlorination or direct OCI\({}^{-}\)-injection. We believe that the findings presented in the manuscript will contribute to our understanding of the potential environmental risk associated with CIO\({}_{3}\)\({}^{-}\) and CIO\({}_{4}\)\({}^{-}\) formed during in situ electrochlorination of seawater, which is used for the cooling system of a power plant.
## 1 Introduction
They are also modified by the mobility and structure of the surrounding macromolecules (i.e., starch, proteins, and polysaccharides) through proton exchange. Moreover, relaxation times are affected by the exchange of molecules between different compartments that is determined by water diffusion and, therefore, by the compartment size and membrane permeability. The transverse relaxation of each water pool can be distinguished thanks to the slow diffusion process between cell compartments compared to the NMR relaxation process. In oilseed rape leaves, a new attribution was recently demonstrated [30]. The palisade and spongy cells of young oilseed rape leaves are similar in size but develop differently, resulting in cells of very different size between the tissues in old leaves. NMR relaxation was shown to be able to finely describe the changes in cell size that occur during leaf development and can be used to monitor the water in vacuoles of palisade or spongy cells in old leaves separately [30]. Applied on a wide leaf panel collected from plant grown in both controlled and field conditions, the low field NMR relaxometry was shown to provide precise and robust markers of development of oilseed rape leaves [30]. NMR relaxation is thus a powerful tool to monitor changes in water relations inside the leaf caused by development or different stress as Nitrogen deficiency [35] or thermal stress [36]. Only a few studies have focused on the impact of water stress on the NMR relaxation signal of the leaf [37; 38]. [PERSON] et al. demonstrated that the mean NMR relaxation time of the leaf was longer in drought tolerant wheat varieties [31]. Furthermore, a unilateral instrument operating at a low magnetic field enables non-destructive NMR measurements. Using that tool, [PERSON] et al. measured a decrease in the mean T\({}_{2}\) of the leaf with the decrease in leaf relative water content of different species directly in the field [37]. The aim of this study was to answer to three questions: first, is it possible to monitor leaf development in tobacco leaves through low field NMR? Secondly, is NMR sensitive enough to detect the impact of mild drought stress on tobacco leaves? Finally, can foliar biostimulants correct the effects of mild drought stress? We investigated the impact of water stress on two different ranks of leaves in order to check if the sensitivity of NMR is affected by the stage of development of the leaf. Two early stages of plant development were studied, very young plants 42 days after sowing (DAS) and 15-day old plants in order to evaluate if NMR relaxation can be used for the early detection of water stress. The stress used in the study was very mild, i.e., 80% of field capacity but was maintained over a period of several weeks Physiological measurements (water content, photosynthetic related parameters, leaf area, etc.) were used to assess the impact of water stress. Finally, the plants were harvested and the impact of water stress was measured through nitrogen concentration and amino acid composition.
# Mechanically Reconfigurable, Beam-Scanning Reflectarray and Transmitarray Antennas: A Review
## 4 Feed Movement  
Moving the array (discussed in Section 3) requires fewer actuators, which simplifies mechanical reconfiguration. However, the implementation of actuators controlled by external circuits still renders the antenna system complicated. Moving the feed antenna further simplifies the realization of mechanically reconfigurable TA and RA antennas.  
Feed displacement enables beam scanning by mechanically moving the phase center of the feed antenna over an aperture of elements along a displacement path, typically a focal arc, as shown in Figure 8. Moving the feed antenna creates spatial phase delay between the feed antenna and array aperture, which results in an adjustment of the phase center of the aperture. This generates the required phase distribution to direct the beam towards the desired direction. Feed displacement methods only rely on the mechanical movement of the feed antenna, thereby providing a simple configuration, low-cost implementation and low-power consumption.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**References** & **Methodology** & **Operating Frequency (GHz)** & **Beam Scanning Range** & **Aperture Efficiency** \\ \hline
[20] &
\begin{tabular}{c} Risley-prism-based \\ beam-steerable antenna \\ \end{tabular} & 30.0 & \(\pm 75^{\circ}\) & 21.7\% \\ \hline
[23] &
\begin{tabular}{c} Risley-prism-based \\ beam-steerable antenna \\ \end{tabular} & 11.0 & \(\pm 51^{\circ}\) & 19.2\% \\ \hline
[29] &
\begin{tabular}{c} Moving and/or \\ rotating a lens \\ \end{tabular} & 30.0 & \(\pm 50^{\circ}\) & 20.5 \\ \hline
[37] &
\begin{tabular}{c} Tiling the ground \\ plane of RA \\ \end{tabular} & 9.5 & \(\pm 30^{\circ}\) & NA \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparative analysis of mechanically reconfigurable beam-steerable antennas using array movement approach.  
Figure 7: Illustrative typologies of mechanical beam-steerable reflectarray by moving/tilting the ground plane. (**a**) Reflectarray topology with tilting the single ground plane. (**b**) Piezoelectric actuators implemented prototype. (**c**) Topology of the reflectarray with a segmented ground plane. (Reprinted with permission from [37]).  
With feed displacement, beam scanning performance, including scan coverage, scan speed and scan resolution [5], is determined by several factors including the aperture properties of the RA/TA, the focal arc position and the feed system characteristic. Typically, aperture properties and focal-distance-to-aperture-diameter (F/D ratio) determine the scan coverage, while the feed system's properties determine scan speed and resolution. Our discussion in this section emphasizes the impact of the array aperture and the focal position and does not focus on the feed system. Feed displacement techniques can be categorized into two general groups: (i) feed displacement on fully illuminated apertures and (ii) feed displacement on partially illuminated apertures.
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} ADR & Angle diversity receiver \\ AWGN & Additive white gaussian noise \\ BER & Bit error rate \\ CDF & Cumulative distribution function \\ DC & Direct current \\ DD & Direct detection \\ EGC & Equal gain combining \\ FET & Field-effect transistor \\ FFR & Fractional frequency reuse \\ FoV & Field-of-view \\ ICI & Inter-cell interference \\ IM & Intensity modulation \\ ISI & Inter-symbol interference \\ I2M & Infrastructure-to-miner \\ JT & Joint transmission \\ LED & Light-emitting diode \\ LiFi & Light fidelity \\ LoS & Line-of-sight \\ MIMO & Multiple-input-multiple-output \\ MRC & Maximum ratio combining \\ M2M & Mining-to-miner \\ NLoS & Non-Line-of-sight \\ OOK & On-off keying \\ PD & Photo-diode \\ RF & Radio frequency \\ RMS & Root mean square \\ SBC & Select best combining \\ SER & Symbol error rate \\ SINR & Signal-to-interference-plus-noise-ratio \\ UDR & User data rate \\ VLC & Visible light communication \\ \end{tabular}
## 4 Materials and Methods  
### Materials  
MIGOU has been evaluated and compared with other representative platforms in terms of power consumption and hardware features. Specifically, these platforms are:  
* _YetiMote_[16]: This platform was chosen as a representative traditional wireless sensor node. Its architecture is based on a STMicroelectronics STM32L476 RE microcontroller and three COTS radio transceivers, two STMicroelectronics SPIRIT1 operating in the 433 MHz and 868 MHz bands, and a Texas Instruments CC2500 for the 2.4 GHz band.
* _MarmotE SDR_[29]: This platform was selected as a representative low-power SDR system, which was specifically designed to be battery-powered. In addition, amongst the two presented in Section 2, this is the one with more detailed power consumption data. As mentioned before, it is mainly based on a Maxim Integrated MAX2830 I/Q transceiver and a Microsemi SmartFusion SoC.
* _B200 mini and B210 USRPs_[18]: Within the group that we consider high-performance SDR platforms, these two were chosen for having lower features and being widely used. The B200 mini model is based on a Xilinx Spartan-6 XC6 SLX75 FPGA and an Analog Devices AD9364 radio transceiver. On the other hand, the B210 model, which is more powerful, consists of a Xilinx Spartan-6 XC6 SLX150 FPGA and an Analog Devices AD9361.  
As for the proposed MIGOU platform, it should be mentioned that there are multiple models of the main SmartFusion2 SoC, each with a different amount of logical and memory resources. Our platform design is pin compatible with many of them for flexibility and scalability. The MIGOU platforms used in this work have been manufactured with the model M2S050, equipped with 56,340 logic elements, 256 kB of embedded non-volatile memory (eNVM), and multiple SRAM blocks distributed between the MSS and the FPGA.  
The MIGOU power consumption measurements presented in the results of this work were taken with the Keysight B2902A precision source-measurement unit (SMU) [34]. This instrument was also used to calibrate the dedicated current-measuring hardware that our platform incorporates and to measure the YetiMote power consumption in sleep mode, where high precision is required due to its very low power consumption. On the other hand, the Ruiteng AT35 USB Tester [35] was used to measure the power consumption of the USRPs and the YetiMote operating in its active modes. Spectrum analyzers were used to calibrate the transmission power of all of them. Finally, the power consumption data of the MarmotE SDR platform used in this work was not directly measured by us. Instead, we used the empirical data published by its authors [8; 29].
## 3 Numerical Simulations  
### Model Building  
Vibration control related to the pile foundation construction immediately adjacent to the oil transportation pipeline [21] is the key problem studied in this paper. A two-dimensional numerical model is established, according to the location of pier No. 6 of the mainline left bridge of Wengcun No. 1 Bridge and the oil transportation pipeline, as shown in Figures 3 and 4. During the whole simulation process, the impact on the oil pipeline caused by the vibration from the construction of the pile foundation closest to the oil pipeline is mainly considered during the construction.  
In this paper, the Rhino 8.0 finite element software is used to establish the model; a cube is constructed in the software, which is then meshed and given boundary conditions, followed by some adjustments to make it more realistic and improve the accuracy of the simulations. The processed mesh file is then imported into the FLAC3D software. The pile foundation is equivalent to a cylinder, with a diameter of 1 m and a length of 10 m, and the pipeline is simplified as a steel column, with a diameter of 30 cm and a length of 20 m. The minimum distance of the pile foundation from the oil transportation pipeline is 6 m. The top view and front view of the model are shown in Figure 3.
## 2 Materials and Methods
### Experimental Design and Introduction
#### 2.1.5 Introduction of Robotic Arm Rotary Axis Drive and PAM Selection  
When the pressure inside the PAM increases, it will cause the PAM to compress in the axial direction and expand in the radial direction. The displacement caused by the axial compression is used to drive the robotic arm joint to rotate through the steel rope and pulley. Moreover, there are bearings embedded in the robotic arm, which can reduce the friction caused by the rotation of the mechanism. In this study, besides the first axis, which uses a single PAM and a spring that interact with each other, the other three axes use two PAMs to drive the rotating axis. The schematic diagrams are shown in Figures 5 and 6.  
In Figure 6, since only a single PAM is required, it is more practical for economic consideration. However, when a single PAM drives a joint and interacts with a spring, the spring can only be stretched because of its poor controllability. Therefore, when the rotating axis is operating, the load object must be cooperated with to enable the rotating axis to return to the original angle. Due to the direction of the rotating axis and the loading effect, only a single PAM drive can be used for the first axis of the robot arm in this study. For the other three rotating axes, the drive method of Figure 6 is used because of the larger operation angle or the absence of load object.  
The size of the PAM is selected with two considerations, one of which is the length. The length \(L\) (mm) of the PAM is selected with the angle \(\theta\) and the radius \(r\) of the rotation of the joint of the mechanism. The relationship is shown in Equation (16):  
\[L=S\times\frac{1}{h}=(r\times\theta)\times\frac{1}{h} \tag{16}\]  
where \(S\) is the stroke of PAM contraction (mm); \(\theta\) is the angle of rotation (rad); \(r\) is the half diameter of the pulley (mm); \(h\) is the ratio of the contraction stroke according to the datasheet of PAM (\(\%\)); and \(L\) is the calculated minimum PAM length, so the actual length of the PAM purchased must be greater than \(L\). The PAM diameter \(\phi\) is related to the force that can be generated by the PAM; the torque required for the rotation of each joint of the mechanism should be considered in the selection. The relationship is shown in Equation (17):  
\[t_{1}=F_{1}\times d=(M\times 9.8)\times d \tag{17}\]  
where \(M\) is the mechanical structure mass (kg); \(d\) is the mechanical structure lever (m); and \(t_{1}\) is the mechanical structure torque (Nt-m). Equation (7) can be used to calculate \(F_{2}\), which is the force to be generated by the PAM (Nt), so the force that can be generated by the selected PAM must be greater than \(F_{2}\). Since Festo only produces three PAM diameters (\(\phi=10,20,40\)), the PAM diameters selected for this study are all (\(\phi=40\)). Table 3 shows the data used in selecting the PAM.  
Figure 5: Schematic diagram of the drive of robotic arm (1 st axis).  
Figure 6: Schematic diagram of the drive of robotic arm (2 nd, 3 rd, and 4 th axes).
## 2 Experiment  
### Experimental Instrument  
The rotational spectra of tert-butyl chloride and its isotopologues (\({}^{13}\)C, \({}^{37}\)Cl) were measured by a broadband cp-FTMW spectrometer built at Nanjing University of Science and Technology [26]. One single scan bandwidth of the spectrometer is 2 GHz in the working frequency range of 1-20 GHz. Its working principle is consistent with the design of current mainstream broadband microwave spectrometers, as shown in Figure 1. First of all, the sample gas passes through the solenoid valve nozzle at the injection end and enters the vacuum chamber by ultrasonic expansion. When the gas beam reaches the center of the sample chamber after a one millisecond delay, a fast linear microwave frequency sweep of 2 GHz bandwidth, that is upconverted by mixing a chirped pulse of 1 GHz bandwidth from the arbitrary waveform generator (AWG, 2.5 G-sample/s) with a single frequency from the microwave source (1-20 GHz), radiates from a double-ridged horn antenna to excite molecules in the beam. Due to the existence of a spherical aluminum mirror, the broadband microwave pulse can be reflected back once to enhance the excitement. After that, the molecular relaxation emission signal (FID, free induction decay) is received by the same feedhorn and transferred out of the chamber through the circulator. The FID signal is then amplified and downconverted to fundamental frequency by mixing with the same single frequency from the microwave source before it is collected by a high-speed digital oscilloscope (40 G-sample/s). The AWG, microwave source and digital oscilloscope are all locked by a 10 MHz rubidium frequency standard oscillator to ensure phase matching and stability during signal transmission. The single-pole single-throw (SPST) electronic switch is used to protect downstream electronic devices from high-power radiation damage.  
In order to improve the sensitivity of the instrument, special design changes have been made in this work compared with the mainstream broadband microwave spectrometer. (1) A reflective focusing spherical aluminum mirror was designed to compensate for the lack of excitation microwave power; (2) the vacuum chamber, the reflective aluminum mirror and the gas injection nozzle were arranged in a coaxial manner to enhance the interaction between the molecular beam and the excitation radiation, so as to improve the excitation efficiency; (3) the broadband technology of multiple free induction decay (multiple FID) was developed to improve the signal sampling efficiency.