esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Structural Analysis
As increasing the amount of ES to 6 wt %, the intensity of cristobalite was decreased associates to promote the growth of wollastonite (CaSiO\({}_{3}\), 96-900-5778). Similarly, at 9 wt % ES revealed the growth of wollastonite (CaSiO\({}_{3}\), 96-900-5778) due to the remaining calcium oxide would be induced to the crystallization process. The high content of ES would promote crystallization which led to the high viscosity of the system thus limiting the ability of foam expansion [14; 21]. The previous study by using clamshell as a foaming agent states that an increasing amount of clamshell would increase the degree of crystallization because the presence of calcium oxide in the samples has reached the solubility limit [6]. Figure 9 shows that FTIR analysis at different content of ES to identify a functional group in an element as well as to assist the finding of XRD results. The low-frequency bands in the range 400-600 cm\({}^{-1}\) of wavenumber originate from Ca-O stretching and bending modes of O-Si-O [23]. Homogeneous silica is formed only by Si-O-Si bonds meanwhile heterogeneous silica atom is formed with different bonds other than silica. An asymmetric stretch network of silica is increased with the presence of heteroatom meanwhile symmetric of silica bonding is decreased. The band of Ca-O was slight intense for 6 wt % and 9 wt % ES at 600 cm\({}^{-1}\) of wavenumber compared to the 1 wt % and 3 wt % ES due to the growth of CaSiO\({}_{3}\) as found in XRD analysis meanwhile, the band of symmetric, vs. SiO\({}_{2}\) at \(\sim\)750 cm\({}^{-1}\) of wavenumber were decreased due to the bonding of heteroatom, Ca-Si-O. The wavenumber of asymmetric, v\({}_{a}\) of Si-O was located in the range of 800-1250 cm\({}^{-1}\) indicate the main strong peak with the rich in phase because of the presence of silica in SLS glass powder. Moreover, the wider band at 950 cm\({}^{-1}\) of wavenumber was caused by the superposition of the absorption peak related to the stretching vibration of bridging and nonbridging Si-O chemical bonds [24]. Consequently,  
Figure 8: XRD pattern at different content of ES with a reference peak of wollastonite (CaSiO\({}_{3}\), 96-900–5778). it promotes the migration of the ions, Ca, and change the structural silica network. The band at 1440-1450 cm\({}^{-1}\) of wavenumber assigned that band of carbonate, C-O group. As increasing the content of ES to 9 wt % of ES the band indicates strongly intense at 1450 cm\({}^{-1}\) of wavenumber compared to the band at 1 wt %-6 wt % of ES. This is because of the partial decomposition of calcium carbonate from ES to carbon dioxide at 810 \({}^{\circ}\)C of temperature as discussed from TGA analysis. There is a little amount of calcium carbonate at high content of ES since the other previous study stated that calcium carbonate is undetectable above 824 \({}^{\circ}\)C of temperature [25]. Lastly, there was a slight peak located in the range of 2050-2250 cm\({}^{-1}\) represent the ambient of carbon dioxide, CO\({}_{2}\) the main element in this research [26].
## 1 Introduction
Potentiostats use stripping analyses to detect electrochemically active analytes in a sample. A varying potential applied to an electrode results in the measured current flowing through the electrochemical cell. The applied potential causes the analyte to oxidize or reduce at the sensor surface, therefore changing the concentration of the electroactive species and causing the measured current change. Potentiostats are dynamic, robust, have a high sensitivity, and can produce large organic and inorganic linear concentration curves [17; 18]. Potentiostats can also measure more than one analyte simultaneously [17; 18]. This allows for a wide range of analyte detection including ethanol, gas and heavy metal detection, as well as biosensing. For these reasons, studies focusing on potentiostats for point-of-need applications have increased rapidly in the past few years [2; 3; 19; 20; 21; 22; 23; 24]. The integration of off-the-shelf silicon components and paper-based substrates allows for parallel development, low cost manufacturing, and rapid prototyping [5; 6; 7; 8; 25; 26]. The well-established silicon platform allows the use of off-the-shelf potentiostat chips together with user-friendly processors such as Beetle board [27], Arduino [28], and Raspberry Pi [29], to create a lower cost solution [14; 15]. This decreases the price of a potentiostat by more than a factor of 10 in comparison to laboratory equipment [30; 31]. Another hybrid printed potentiostat example include an integrated biosensor platform that was screen-printed on an PET substrate and displayed the detected glucose levels on an electrochromic display [6]. Portable potentiostats are available, but when considering a device that can be manufactured in volume, is disposable and maintenance free, these portable potentiostats are still expensive [32] for pervasive deployment. Other important factors to take into account when developing a low-cost device include initial cost, maintenance, and user-friendliness of the software, and therefore freeware such as Gobetwino [33] on the open-source Arduino [29] was selected for the development of the low-cost point-of-need potentiostat. A potentiostat front-end was manufactured on a paper substrate and compared to a prototype of the device manufactured on a printed circuit board (PCB), an off-the-shelf potentiostat front-end development board, and a laboratory-based potentiostat instrument [14,15]. Cyclic voltammetry was performed using a 5 mM ferri-ferrocyanide 80 \(\mu\)L sample dropped onto a commercial screen-printed electrode. The paper-based potentiostat displayed similar contour characteristics to those of the PCB potentiostat, development board and the laboratory-based potentiostat. The oxidation and redox peaks validated the paper-based potentiostat, which are indicators of electron transfer characteristics.
## 3 Key Technologies
### Real-Time Data Collection and Driving
#### 3.2.2 Real-Time Driving of the Digital Twin System  
Figure 7 shows the design flowchart of the drive module. By conducting a kinematic and dynamic analysis of the magnetic levitation knitting needle, displacement, velocity, and acceleration curves of the needle motion are obtained, describing the needle's movement state at different time points. By collecting drive data from the needle and motor, a twin model is established that can accurately simulate and reflect the motion process of the physical entity, allowing for precise simulation and testing in the virtual environment.  
Finally, the visualization control platform for the magnetic levitation knitting needle is programmed using the Unity3D engine based on the.NET platform. Unity3D provides powerful graphics and physics engines, making the presentation of the virtual model more realistic and intuitive. The OPC-UA industrial communication protocol is used to achieve the real-time invocation and saving of drive data. This allows users to control the virtual model and physical entity in real-time through the control platform, meaning operations on the virtual platform can be synchronously reflected on the physical device.  
The system design enables users to perform various operations and tests in the virtual environment, reducing the cost and risk of physical experiments. Additionally, through real-time data collection and analysis, control algorithms can be continuously optimized, improving system performance and efficiency.  
Figure 6: OPC-UA server architecture.  
Figure 7: Design flowchart of the driving module.
## 4 Simulations and Results
### Case II  
In this case, we are considering nine sub-bands mentioned as regions in Figures 6 and 7. We assume that regions I, III, V, VII, and IX are occupied by PUs, while regions II, IV, VI, and VIII are occupied by SUs. Each SU has an equal number of subcarriers, _i.e.,_ 32 OFDM subcarriers modulated with BPSK, whose power is normalized to \(|d_{n}|^{2}=1\). The bandwidth allocated to each PU is considered equal in all regions. The comparison of the proposed technique is done with already existing techniques including CC [14], CC using GA and DE [17], ACC [18], and ASW [21]. In CC techniques, two CC_s_ have been used on either side of data subcarriers, while in the SW technique all subcarriers are taken into consideration. Figures 6 and 7 show the superiority of the proposed technique in terms of PSD, even in a spectrum-sharing scenario. The proposed technique performs well: it outclasses all these techniques and gets significant suppression in all regions.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Techniques used**} & \multicolumn{3}{c}{**Sidelobe Powers**} \\ \cline{2-3}  & **Left Side of the Data Subcarriers** & **Right Side of the Data Subcarriers** \\ \hline Original & \(-\)25 dB & \(-\)25 dB \\ CCs (Brandes) & \(-\)43 dB & \(-\)43 dB \\ CCs (GA) & \(-\)52 dB & \(-\)52 dB \\ CCs (DE) & \(-\)61 dB & \(-\)61 dB \\ ACCs & \(-\)30 dB & \(-\)30 dB \\ ASCW & \(-\)45 dB & \(-\)45 dB \\ Proposed technique & \(-\)117 dB & \(-\)117 dB \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of sidelobe suppression between existing and proposed techniques.  
Figure 5: The PSD comparison between the proposed technique and existing techniques including ASW and ACC.  
The comparison of suppression of the sidelobe power level achieved in a spectrum-sharing scenario using the existing technique and our proposed technique are given in Table 2, which also shows the performance of our proposed technique in all regions of PU.
# IoT Group Membership Management Using Decentralized Identifiers and Verifiable Credentials
## 4 Implementation and Evaluation
### Comparison to Other Approaches  
#### 4.3.1 Registry-Based DID Methods  
Being registry-less, the _did:self_ DID method allows a DID identifier to be mapped to multiple DID documents. Our system takes advantage of this property and allows endpoint owners to define a single DID and then use a different DID document for each IoT endpoint, each of which includes only a single key used by that particular endpoint. This makes the management of IoT endpoints easier, since an endpoint owner can easily add or remove an IoT endpoint. On the other hand, if a registry-based approach was used (e.g., did:web), all public keys of all IoT endpoints should had been included in the (single) DID document; hence, adding or removing an IoT endpoint means that the corresponding DID document must be updated as well.  
Additionally, since DID documents in _did:self_ are \"self-protected\" (as they are signed by the DID owner), they can be included directly in CoAP responses. On the other hand, in a registry-based system, DID documents must be resolved from a registry. This not only adds communication overhead (e.g., extra roundtrips for resolving the DID document) but it also creates new security threats since the registry must be trusted, secured, and available.
# Estimation and Adjustment of Interface Stiffnesses for Machine-Tool
###### Abstract  
This study adopts a practical approach to establish the estimation and adjustment methods of the interface stiffness for the machine-tool through the finite element analysis (FEA). First, numerical and experimental modal analysis (FMA and EMA) for each single subsystem of the machine-tool structure are performed. Then, the parameters obtained from EMA are used as the objective criterion function, and the FMA is conducted iteratively to solve the material Young's modulus and Poisson's ratio for each single subsystem structure, in which the geometrical model is simplified and FE mesh convergence is performed to ensure the quality and efficiency of the numerical analysis. Next, by considering that the machine-tool is assembled by subsystem stacking and that loading on each contact surface is deduced, the FE method is used to calculate the deformation of each contact interface after the single subsystem is stacked successively. The initial value of the interface stiffness estimated by the deformation formula in the mechanics of material is utilized as the initial condition for the iterative calculation in FMA. The changes of the modal parameters are observed in the analysis and the interface, which have a significant impact on the natural frequency variations of the whole machine-tool is selected as the main adjustment object. Then, the adjustment method proposed in this study is applied repeatedly to modify this interface stiffness. The results show that footing interface stiffnesses play the most important role that intensively affects the numerical analysis results of modal parameter. After the repeated adjustments of the interface stiffnesses of the footing, the error of the natural frequency of the whole machine-tool is less than 5%, which is calculated from the comparison between EMA and FMA results. It indicates that the proposed adjustment method in this study for footing interface stiffness determination has a valuable reference in practical use.  
interface stiffness; estimation method; adjustment method; modal analysis; footing Article
###### Abstract
However, its use in subgrade temperature prediction within seasonally frozen soil regions has not been fully explored, underscoring a significant gap in the literature. This study addresses this gap by developing a short-term temperature prediction model for highway subgrades in seasonally frozen areas, especially focusing on the Golmud-Nagqu segment of National Highway 109 in China. The NARX model leverages monitoring data, including temperature, water content, and frost heave [9; 10]. The primary focus is on subgrade temperature, recognizing that the moisture migration and frost heave in subgrades are closely related to temperature [28; 29], which ultimately affects the stability of the subgrade [30; 31]. From the perspective of the NARX network, water content and frost heave serve as external inputs that complement the temperature data. Consequently, the NARX network's ability to integrate exogenous inputs is particularly well-suited to this situation. Additionally, its feedback and delay mechanisms are ideal for capturing the hysteresis effects between temperature and the external variables of water content and frost heave. This study is dedicated to exploring the practicality and benefits of the NARX network in predicting temperatures in seasonally frozen subgrades, providing insights for the development of more precise and effective tools in seasonally frozen subgrade engineering.
# Attack Classification Schema for Smart City WSNs
## 2 Background and Related Work
### Smart Cities  
Cities, private companies and other institutions are already involved in smart city projects to provide solutions to the contemporary challenges that cities are facing. From a technological point of view, smart city systems are often designed as service-oriented architectures (SOA) that can be divided into three conceptual layers. The first layer includes the elements that collect information from the city (e.g., sensors, surveillance cameras, social networks, citizen complaint applications, supervisory control and data acquisition (SCADA) systems). The second layer acts as a middleware, which provides the city with an API to connect the elements of the first layer to the services offered in this layer. Among others, these services include relational and non-relational storage, geographic information systems, data analysis, cloud computing, natural language processing, business intelligence or open data. Finally, the third layer is an application layer, in which the city council and third parties implement applications based on data and services offered by the middle layer. For instance, projects that can be framed in these three conceptual layers are: the PlanIT Urban Operating System [7,8], Ubiquitous city (u-city) [9,10] and SmartSantander [11].  
The communication channel between street sensors and smart city central servers is represented in Figure 1. As shown in the figure, some WSNs are also equipped with actuators, which can be operated from the central servers with a downlink transmission or triggered by other first layer systems using machine-to-machine (M2M) communication. For example, vehicle detection sensors embedded in the asphalt send information to traffic controllers installed in traffic lights [12]. Nevertheless, principally, the infrastructure shown in Figure 1 is designed to collect information generated by sensors and send it to the city servers. The information flow in this schema begins in the sensors, which gather data about their environment and then send them to a gateway. Gateways finally deliver sensor data to the smart city premises. The next section will review the main characteristics of WSNs.  
Figure 1: WSN data collection infrastructure.
# Review of Studies on User Research Based on EEG and Eye Tracking
## 4 Application Scope
### Spatial Environment
#### 4.3.3 Consumer Space  
In consumer scenarios, electroencephalography (EEG) is one of the most commonly used neuroscience technologies in marketing research, and provides key information for studying users' observation and consumption decisions of products. Its low cost and high temporal resolution have been widely used in consumer research, including product features, pricing, advertising attention and memory, and rational and emotional information [17]. Especially in diversified retail environments, the advancement of eye-tracking technology can play a key role in capturing attention, as well as in analyzing which elements attract consumers, to better understand their views on product displays. For instance, in situations where consumer reviews exhibit consistency, whether positive or negative, positive reviews may evoke a diminished P2 component, an amplified N2 component, and an enhanced late positive potential (LPP). These distinct components signify the allocation of attentional resources, perception of cognitive conflicts, and evaluative categorization processes linked to the LPP [94]. Researchers and practitioners can use this information to improve the sales efficiency of displays, and help promote standardized research methods for consumers in many retail market environments [95].  
In the typical retail environment of a shopping mall supermarket, [PERSON] [96] used ET as a method to determine the key elements that attract the attention and selection of salespoints. By changing visual marketing stimuli on real supermarket shelves, the impact of brand positioning and brand strength was explored. [PERSON] et al. (2018) analyzed spectral activity (delta, alpha, and beta activity in the frontal lobe area) related to preferences by changing the shape and flavor of product feature stimuli and combining user behavior, electroencephalography, and eye-tracking data. [PERSON] et al. (2018) investigated consumers' processing of pricing and discount information, and found enhanced P300 responses in individuals with high mathematical anxiety. Tasks involving pricing and discount stimuli in these individuals revealed outcomes that were indicative of heightened emotional arousal and motivational processes. [PERSON] et al. (2018) measured the brain activity with EEG and eye gaze of people visiting specific areas of the supermarket. The eye-tracking heat map shows that the \"coldest\" department (fruit and vegetable department) of the store has the potential to fully attract customers at an emotional level. In terms of neural measurement indices, fruit provides higher pleasure, while vegetables have higher attention, memory and workload, which provides the best predictive indicators for future customer purchasing behaviors. The experiment showed that innovative packaging, displays, and storytelling forms are highly attractive. Undoubtedly, these findings also provide key information for management, design, and marketing strategies in studying consumers.
## 4 Analysis of Internal Forces and Deformations in Circular Shaft Structures
### Analytical for Internal Forces and Deformations  
The problem is treated as axisymmetric, where the stress and strain components depend only on \(\rho\), not \(\varphi\), and the shear stress \(\tau_{\rho\varphi}\) is zero.  
Figure 9: Schematic and analytical model of the circular shaft. (**a**) Circular shaft schematic; (**b**) analytical model of the circular shaft. (Green arrows indicate inner pressure \(p_{1}\); blue arrows indicate outer pressure \(p_{2}\)).  
Since Equation (32) defines the stress boundary conditions, the solution can be obtained using the stress function method. The stress function is a scalar function of \(\rho\) and is expressed as Equation (33):  
\[\Phi=\Phi(\rho) \tag{33}\]  
where \(\Phi\) is the stress function, while \(\rho\) and \(\varphi\) represent the radial and circumferential coordinates in the polar coordinate system, respectively.  
In elasticity theory, the stress function in Equation (33) must satisfy the compatibility equation, given in Equation (34), and the general solution is given by Equation (35):  
\[\Delta^{2}\Phi=0 \tag{34}\]  
\[\Phi=A\ln\rho+B\rho^{2}\ln\rho+C\rho^{2}+D \tag{35}\]  
where \(\Delta\) is the Laplace operator; \(A\), \(B\), \(C\), and \(D\) are constants to be determined.  
The general stress solution is derived from Equation (35) and given in Equation (36):  
\[\left\{\begin{array}{l}\sigma_{\rho}=\frac{A}{\rho^{2}}+B(1+2\ln\rho)+2C\\ \sigma_{\varphi}=-\frac{A}{\rho^{2}}+B(3+2\ln\rho)+2C\\ \tau_{\varphi\varphi}=0\end{array}\right. \tag{36}\]  
Substituting Equation (36) into the physical equation and combining it with the geometric equation yields the deformation solution to this problem, as shown in Equation (37):  
\[\left\{\begin{array}{l}u_{\rho}=\frac{1}{E}\Bigl{[}-(1+v)\frac{A}{\rho}+2(1- v)B\rho(\ln\rho-1)+(1-3v)B\rho+2(1-v)C\rho\Bigr{]}\\ u_{\varphi}=\frac{4B\varphi\varphi}{E}\end{array}\right. \tag{37}\]  
where \(E\) is the elastic modulus; \(v\) is the [PERSON]'s ratio; \(u_{\rho}\) is the radial deformation; \(u_{\varphi}\) is the radial deformation.