esa-sceva/satcom-chunk-collection huggingface dataset:
# Enhanced Radiation Therapy of Gold Nanoparticles in Liver Cancer
## Materials and Methods
### Cell Culture and Cytotoxicity Assay  
Mouse H22 hepatoma cell line and human liver cancer cell line HepG2 were used in all cell culture experiments. These two cell lines were cultured in RPMI-1640 (HyClone) medium supplemented with 10% fetal bovine serum (FBS; Hangzhou Sijiqing, Hangzhou, China), 45 IU/mL streptomycin-penicillin. All cells were maintained at 37 \({}^{\circ}\)C in a 5% CO\({}_{2}\) incubator and replenished with fresh medium every 3 days. Cells from passages six to eight were suitable for experiments.  
A cell Titer-Glo luminescent cell viability assay, which quantifies metabolically active cells, was performed to determine cytotoxicity of PEG-coated GNPs in two cell lines. Briefly, cells were seeded at an initial density of 3000 cells/100 \(\mu\)L per well in a 96-well plate. After an overnight growth, the cells were replenished with fresh medium and treated with PEG-coated GNPs at different concentrations (0, 12.5, 25, 50, 100, and 200 \(\mu\)g/mL, Au atom concentration), then incubated for 24 h and 48 h. After replenishing with freshly prepared RPMI-1640 medium (100 \(\mu\)L), equal volume of CellTiter-Glo Reagent was added to each well. The solution was mixed on an orbital shaker for 2 min lyses before it was incubated at room temperature in order to obtain stable detection signals. Luminescent signal was measured (Infinite 200. Tecan, Lausanne, Switzerland). Triplicate measurements were obtained for each dosage.
## 3 Motivation
### Port Layer  
The port layer refers to the opening ports, which are associated with the host's communication protocol and specific service types. Unlike traditional hosts, most IoT devices are made for specific tasks, which can reflect the device fingerprint. In Appendix A, we shows the default open ports for the main IoT device manufacturers. For example, webcams need to receive control data and send image data via the network. Therefore, they use the real-time streaming protocol (RTSP) and Onvif protocols.  
Table 1 shows three typical categories of devices: webcam, network printer, and network-attached storage (NAS). Several unique ports are used by only one type of device. For example, the Dahua uses port 37777 to run its private protocol. Thus, we can perform coarse-grained identification for IoT devices based on the extracted port features at the first step.  
\begin{table}
\begin{tabular}{c c c} \hline
**Device Type** & **Protocol Type** & **Default Ports** \\ \hline \multirow{4}{*}{Webcam} & HTTP/HTITPS & 81, 80, 82, 8080, 443, 8443 \\  & RTSP & 554 \\  & Data Service & 8000, 37777 \\  & Onvif & 80, 2020, 3702 \\ \hline \multirow{4}{*}{Printer} & HTTP/HTITPS & 80, 8000, 8080, 8081, 443, 8443 \\  & IPP & 631 \\ \cline{1-1}  & FTP & 21, 9600 \\ \cline{1-1}  & Telnet & 23 \\ \cline{1-1}  & PJL & 9100, 9101, 9102, 515 \\ \hline \multirow{4}{*}{Firewall} & HTTP/HTITPS & 443, 10443, 8443, 80, 8888, 8080 \\  & SSH & 22 \\ \cline{1-1}  & Telnet & 23 \\ \cline{1-1}  & SNMP & 161 \\ \hline \multirow{4}{*}{NAS} & HTTP/HTITPS & 80, 8080, 443, 8443, 5000, 5001, 8000 \\ \cline{1-1}  & UPnP & 1900 \\ \cline{1-1}  & FTP & 21 \\ \cline{1-1}  & NDMP & 10,000 \\ \cline{1-1}  & Rpcbind & 111 \\ \hline \end{tabular}
\end{table}
Table 1: Typical open port combinations.
## 4 JTAG Security Solutions
### JoKER, Trusted Detection of Kernel Rootkits in Android Devices via JTAG Interface  
In recent years, there has been tremendous development in OS for handheld devices. These smartphones and tablets have become very popular and consist of full-fledged operating systems such as Android, iOS, etc. As we know, there are many antivirus programs available in the market that promise security against malicious apps. In practice, most of them provide application level security not low level (kernel) security, which is more prone to attacks. However, it is always best to prevent kernel level system attacks. Moreover, the JTAG hardware debugging standard is the most trusted debugging technique at hardware level in the industry.  
[PERSON] et al. [36] demonstrated detection of kernel level of rootkits in recent Android devices through the JTAG interface. Kernel level attacks can grant permissions to hide virus/malware from antivirus programs so that authors used well known JTAG hardware debugging techniques to get low level memory screenshots. This experiment is performed on Android versions 2.6.35 and 3.4.0. The authors downloaded vanilla OS version from its website and compared its memory contents with the same version OS, which already had hidden malware installed in it. The authors followed three main steps in the detection process: (1) halting the target processor; (2) extracting kernel data structures from memory; and (3) running analysis programs to hunt for rootkit footprints. They performed tests on Samsung Galaxy (S2 and S4) mobile phones with a RIFF Box JTAG controller to execute the first two steps. The third step consists of two important analysis, i.e., integrity checks and detection of stealthy hidden processes. Integrity checks comprises testing system call tables, the exception vector table, and software interrupt handler, since these objects are not usually modified on regular Android system. However, malicious processes can remove their entry from a process list, hiding their details. Thus, the authors compared objects from normal process list objects with the protected cache pool objects to acquire their presence. Although JTAG is designed for system testing and verification, in this experiment, it is also used for low level threat analysis of Android OS.
## 4 Discussion
### Characterization of a Hazelnut Polygon  
By employing K-means analysis, a discernible geographical pattern of distinct hazelnut classified zones emerges. Cluster 1, predominantly situated in the volcanic crater of Lake Vico and its surroundings, exhibits elevated altitudes and higher meteoric precipitation [95]. On-site observations and historical imagery affirm the maturity of these hazelnut groves, surpassing a 20-year age threshold, with heights exceeding 3 m and dense canopies.  
Index analysis reveals that Cluster 1 hazelnut groves show increased NDWI during summer, indicating elevated water availability. A distinct temporal shift in vegetative vigor patterns is observed in the NDVI index, potentially linked to lower temperatures during the vegetative phase. The persistent elevation of the VH/VV ratio in Cluster 1 aligns with a denser canopy, supporting the hypothesis of mature hazelnut groves.  
Cluster 2, at lower altitudes, features mature hazelnut groves with narrower spacing, lower heights, and less dense canopies. Drip irrigation systems are consistently used in response to lower precipitation levels. The lower VH/VV ratio suggests a less developed canopy to facilitate mechanical intervention, with the NDVI index indicating early vegetation development due to higher temperatures. The NDMI index shows reduced intensity in summer, likely due to water deficit and elevated temperatures.  
Field and historical investigations link Cluster 3 to young hazelnut groves, not present before 2014-2015, suggesting cultivation expansion. A lower VH/VV ratio and reduced vegetation indices during summer indicate diminished canopy volume, attributed to  
Figure 20: Density plot for VHVV backscattering in May.  
significant soil contribution. Higher NDVI values during winter suggest the prolific growth of inter-row weeds. Notably, Cluster 3 includes large recent plantations or areas with sparse hazelnut coverage or gaps between plants, necessitating subsequent agronomic ground studies.  
In summary, the clusters represent discrete hazelnut cultivation zones (Figure 21). Cluster 1 hosts mature hazelnut groves at a higher elevation with extensive canopies, coinciding with the historical core of hazelnut cultivation. Cluster 2 comprises relatively younger mature orchards with tighter spacing, an irrigation system, earlier development of the canopy, and notable mechanized interventions. Cluster 3 encompasses young orchards (<10 years) as well as areas where canopy coverage is lacking for various reasons, warranting on-site agronomic investigations.  
For the characterization phase, a comprehensive collection of meteorological data from ground-based sensors could contribute to a better understanding of the dynamics governing the diverse spectral and temporal responses of the different hazelnut groves.  
The approach pursued has enabled the achievement of a high level of accuracy, although certain limitations can be identified. Specifically, the methodology, which relies on median values over a four-year timeframe in the optical dataset, faced challenges in effectively identifying hazelnut groves younger than four years old.
## 3 Proposed Techniques
### Statistical Learning  
As opposed to the conventional unbiased regression, biased regression can balance the trade-off between forecasting errors and model complexities. Typical biased regression schemes include Ridge, Lasso, and ElasticNet [40; 41]. The differences between them are regularized distance measures: L\({}_{1}\) norm is for Lasso (see Equation (4)), L\({}_{2}\) norm is for Ridge (see Equation (5)), and a compromise is for Elastic Net (see Equation (6)). Specifically, L\({}_{1}\) norm is Manhattan distance (\({\left\|{\beta}\right\|_{1}}=\sum\limits_{i}{{{|\beta_{i}|}}}\)) and L\({}_{2}\) norm is Euclidean distance (\({\left\|{\beta}\right\|_{2}}=\sqrt{\sum\limits_{i}{{{\beta_{i}}^{2}}}}\)).  
\[{\hat{\beta}_{Lasso}}=arg\underset{\beta}{Min}\{\left\|{Y-X\beta}\right\|_{2} ^{2}+\lambda{\left\|{\beta}\right\|_{1}}\}, \tag{4}\]  
\[{\hat{\beta}_{Ridge}}=arg\underset{\beta}{Min}\{\left\|{Y-X\beta}\right\|_{2} ^{2}+\lambda{\left\|{\beta}\right\|_{2}}\}, \tag{5}\]  
\[{\hat{\beta}_{Elastic}}=arg\underset{\beta}{Min}\{\left\|{Y-X\beta}\right\|_{2 }^{2}+\lambda{\left\|{\beta}\right\|_{1}}+(1-\lambda){\left\|{\beta}\right\|_{ 2}}\}, \tag{6}\]  
Figure 1: Proposed research techniques.  
where \(Y\) means a response, \(X\) are multivariate predictors, \(\beta\) represents regression coefficients, and \(\lambda\) is a regularization constant. Lasso is adopted to identify significant economic indicators because it can diminish a lot of redundant predictors.  
Unlike multiple linear regression (MLR), multivariate adaptive regression splines (MARS) is a nonparametric and nonlinear methodology. It is defined as follows:  
\[f(x)=a_{0}+\sum_{m=1}^{M}a_{m}\prod\
olimits_{k=1}^{K_{m}}[S_{k,m}(x_{k,m}-t_{ k,m})], \tag{7}\]  
where \(a_{0}\) is a constant, \(a_{m}\) are regression coefficients of the model, \(M\) is the number of basis functions (degree of nonlinearity), \(K_{m}\) is the number of splits for the \(m^{\text{th}}\) basis, \(S_{k,m}\) takes values of either \(1\) or \(-1\) to indicate the right or the left step function, \(x_{k,m}\) are input variables, and \(t_{k,m}\) are \"_knot_\" locations in each interval [40]. In Figure 2, a nonlinear mapping is approximated by using \"_knots,_\" in which BF means basis functions.
# Single Leg Gait Tracking of Lower Limb Exoskeleton Based on Adaptive Iterative Learning Control
## 4 Results and Analysis  
The ground truth for the gait prediction was captured by the experiment and the initial values were assumed as the initial angles at time equal to zero. The tracking error was calculated through the experiment process. The initial PID parameters \(\mathbf{K}_{P}\) and \(\mathbf{K}_{D}\) were set as \(\left[\begin{array}{cc}10&0\\ 0&10\end{array}\right]\) and the adaptive law parameter \(\gamma\) was set as 10. After a preliminary test, as the results tend to converge after eight iterations, the results were reported for the first ten iterations, in other words, N was set as 10. Each iteration is composed of a supporting phase (approximately 1.2 s, 60% gait cycle) and a swinging phase (approximately 0.8 s, 40% gait cycle). The tracked angle trajectories of the hip joint and knee joint are shown in Figure 7. The tracked angular velocity of the hip joint and knee joint after 10 iterations is shown in Figure 8. Figure 9 shows the tracking errors of both the angle and angular velocity through all 10 iterations.  
Figure 8: Gait angular velocity tracking results of the hip (**left**) and knee (**right**) joint after 10 iterations.  
Figure 7: Gait angle tracking results of the hip (**left**) and knee (**right**) joint over 10 iterations.  
With Figures 7 and 9 (left), it can be seen that with the proceeding of iterations, the predicated trajectory approached the object trajectory. After 10 iterations, the maximum tracking error of the hip joint was reduced to 0.20 degrees and that of the knee joint was reduced to 0.22 degrees. There was about a 3% relative error of the hip joint angle within 80% of the gait period, while the relative error for the knee joint was about 4.4% over 70% of the gait cycle. With Figures 8 and 9 (right), it can be seen that the angular velocity tracking errors kept decreasing. After 10 iterations, the angular velocity tracking error of the hip joint was 1.52 deg/s, and that of the knee joint was 2.78 deg/s. Both maximum errors suggest that the lower extremity exoskeleton robots can be safely operated.  
The tracking error inevitably leads to human-robot interaction force/torque, and at the same time, it also is affected by human movement force/torque. To investigate the impact of human-robot interaction torque (\(\mathbf{T}_{HR}\)) on the trajectory tracking error, this study also investigated four forms of human-robot interaction torque \(\mathbf{T}_{HR}\), including fixed value, sine change, random change, and sine *random change, as shown in Equation (8). Among them, the function of \(\mathbf{rand}(1)\) generates standard normal probability.  
\[\mathbf{T}_{HR}=\left\{\begin{array}{cc}A&\\ \quad\quad\quad\quad Asin(t)&\\ \quad\quad\quad\quad\quad\
## 2 Methods and Steps
### Data Sample Processing Method  
In the process of data collection, considering the complexity of the open-pit mine stope transportation environment, weak signals in local areas, and the large size of the mining truck leading to large seismic activity during the driving process, the massive data indexes collected by sensors may contain noise data, missing data, and redundant data [19; 20]. Therefore, in order to minimize the deviation of data anomalies resulting in subsequent data analysis, this paper first needs to analyze and preprocess abnormal data before data analysis and data mining.
## 3 Results
### Hardware Costs  
Several authors pointed out the importance of pricing of such devices [65; 66]. Of course, the final price respects many parameters, not only the hardware. Food and Drug Administration (FDA) approval, for instance, is a costly and long procedure process that is applied to medical devices as well. However, we estimated hardware costs when producing ten prototypes. From this small charge, the hardware price is as low as 132 Euros (Table 6, which will significantly be reduced when charge size is increased.  
\begin{table}
\begin{tabular}{l r r} \hline \hline
**Item** & **Quantity** & **Price (€)** \\ \hline Host platform & 10 & 690.00 \\ PCB (physiological layer) & 10 & 4.50 \\ PCB (hardware interface) & 10 & 4.50 \\ PCB (gas sensor driver) & 10 & 1.80 \\ Gas sensor & 10 & 170.00 \\ UV sensor & 10 & 26.00 \\ Microphone & 10 & 18.00 \\ LM358 & 10 & 2.83 \\ MCP6001T-I / OT & 10 & 2.20 \\ MAX3020 SMA + T(skin temp.) & 10 & 31.60 \\ AM2520 ZGC09 (LED) & 10 & 6.80 \\ APDS-9008-020 & 10 & 12.80 \\ DF37B-24 DP-0.4V (connector) & 10 & 9.00 \\ DF37 NB-24 DS-0.4V (connector) & 10 & 7.30 \\ LMP91000 & 10 & 34.00 \\ MCP6041-T-I/OT & 10 & 5.40 \\ ISL60002 DH320Z-TK & 10 & 27.30 \\ Capacitors + resistors & 10 & 60.00 \\ Bracelet & 10 & 150.00 \\ Battery & 10 & 60.00 \\ \hline
**Estimated total price** & **1** & **132.40** \\ \hline \hline \end{tabular}
\end{table}
Table 6: Hardware costs for the prototype. final expense of the wrist-worn prototype.  
Figure 12: A subject wearing the prototype for 25 min.
# Design of Wideband Decoupling Antenna Array for 5G Smartphones at N77/N78/N79/WLAN 5 GHz Bands
## 1 Introduction
[29] The bandwidth is expanded by characteristic mode theory, and the isolation is enhanced by introducing a multiple defect ground structure (DGS) to achieve an impedance bandwidth of 3.23-5.24 GHz (\(-10\) dB), and a high isolation of 17.24 dB is achieved at the antenna pairs with a 2 mm interval, but the isolation between Ant 2 and Ant 3 still needs to be further improved. A flexible and transparent broadband four-element MIMO antenna with a connected ground plane is innovatively proposed in [31]. The design uses flexible conductive oxide material AgHT-4 and Melinex substrate to obtain optical transparency with \(-10\) dB impedance bandwidth from 2.21-6 GHz (92.32%). Due to its flexible and transparent nature, it can be used in scenarios where aesthetics are important, such as glass. The above shows that wider-frequency bands allow the combination of antennas operating in different frequency bands, effectively saving space inside the terminal. However, in the process of broadband antenna design, different decoupling structures will affect the overall structure and performance of the antenna system, and how to achieve a good balance between antenna performance and compact size is a challenging task. In this paper, a base antenna pair is first constructed, and CMA is applied to capture the important patterns of the base antenna pair. The modal significance, modal weighting coefficient, and characteristic currents of each mode are analyzed and used to optimize the antenna structure. This process is repeated to gradually evolve the antenna pair and thus expand the bandwidth. Meanwhile, in order to make the antenna pairs as compact as possible while ensuring the isolation, we add a strip-shaped defective ground structure in the middle of the antenna pairs and utilize the band elimination property of the defective ground structure to block the surface current on the common ground plane from one antenna to the other antenna, so as to obtain good isolation in the broadband range. Second, we utilize the obtained broadband decoupled antenna pairs to construct an eight-element MIMO antenna system, and apply the complex decoupling structure composed of the defected ground and the decoupling strips to decouple the two antenna pairs that are more seriously affected by the mutual coupling, which significantly improves the isolation between the two antenna pairs. In addition, we simulate and prototype the eight-element MIMO antenna system to verify the performance of the antenna system. Finally, we also simulate the effect of a user's hand on the antenna system to verify the robustness of the antenna system. The results show that the antenna system largely covers the n77/n78/n79 and WLAN 5 GHz bands, with good isolation in the full operating band, and the performance meets the 5G terminal antenna requirements.
## 3 Experimental Verification and Comparison  
In order to verify the correctness of the calculation method, the result in this paper is compared with the relevant test in literature [16]. In the literature, the Phase Doppler Particle Analyzer (PDPA) is used to sample 3000 oil droplet diameters in the aero-engine bearing chamber, and the histogram of oil diameter distribution is obtained. The distribution of droplet diameter is in a range of 14 to 120 \(\upmu\)m. The operating condition in literature is air inflow m\({}_{g}\) = 10 g/s and oil inflow V\({}_{L}\) = 100 L/h. The oil droplet diameter distribution is calculated under these conditions. It should be noted here that in the calculation, the oil droplets larger than 120 \(\upmu\)m in diameter are not considered, so only the oil droplet diameter distribution in a range of 10 to 120 \(\upmu\)m is calculated. The calculation results are compared with the results in the literature in Figure 4. Through comparison, the calculation results are consistent with the experimental results in the literature, which verifies the rationality of the research method in this paper. The calculation results given in this paper can provide more accurate initial conditions for the analysis of the flow and heat transfer, and also can provide reference for the further test of oil mist concentration in the bearing chamber.
# Peptide Mediated Antimicrobial Dental Adhesive System
## Materials and Methods
### Antimicrobial Activity Assays of Resin-disc Diffusion in Solution  
In-solution antimicrobial activity of peptide-treated resin discs was assessed. For these studies, each disc was soaked overnight in 100 \(\upmu\)L sterile deionized water, peptide, or CHX solution at 4 \({}^{\circ}\)C. The soaked discs were rinsed 4 times with 100 \(\upmu\)L of H\({}_{2}\)O, with excess H\({}_{2}\)O on the disc surface gently removed by blotting with Kimwipes. Each soaked and rinsed disc was carefully transferred to a microwell of a 96-well plate. 20 \(\upmu\)L H\({}_{2}\)O, 80 \(\upmu\)L of BHI broth and 100 \(\upmu\)L of BHI broth containing 1 \(\times\) 10\({}^{6}\) CFU/mL _S. mutans_ UA159 cells were added to each well. The final bacterial concentration in each well was 5.0 \(\times\) 10\({}^{5}\) CFU/MI [74]. _S. mutans_ UA159 bacteria without any disc present served as the positive control and the negative control was 20 \(\upmu\)L of 63 \(\upmu\)g/mL CHX solution instead of H\({}_{2}\)O. The blank well contained 20 \(\upmu\)L H\({}_{2}\)O and 180 \(\upmu\)L medium without cells. The 96-well plate was incubated in the presence of 5% CO\({}_{2}\) at 37 \({}^{\circ}\)C overnight. The solution of each well was transferred to a new plate and the OD\({}_{600}\) was recorded by Cytation3.  
Absorbance-based in-solution measurements rely on turbidity at OD\({}_{600}\) and therefore do not provide quantitative delineation between viable and non-viable _S. mutans_ UA159 cells. Thus, an alternative fluorescent method, described below, was used to ensure the antimicrobial activity of the system was accurately assessed.