esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results
### Structural Equation Modeling and Hypothesis Verification  
The structural model, depicted in Figure 3, requires evaluation. Structural equation modeling (SEM) serves as an extensive methodology for examining the proposed relationships among variables, which, within this study, involve the connections between UTAUT factors, user experience factors, and intentions for sustainable online learning. Figure 3 presents the ultimate structural model that emerged following the application of refinement standards mentioned in the Measurement Models section, which encompasses 39 items.  
The entire model was subjected to an evaluation process. The structural model analysis, as indicated in Table 6, reveals values according to widely recognized model fit indicators, demonstrating an overall good fit. In particular, the measures of CMIN/DF, IFI, TLI, CFI, and RMSEA all suggest that the model adequately aligns with the data.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Variable** & **Item** &
\begin{tabular}{c} **Factor** \\ **Loading** \\ \end{tabular} & **CR** & **AVE** \\ \hline Performance Expectancy & PE1 & 0.724 & 0.769 & 0.527 \\  & PE2 & 0.788 & & \\  & PE3 & 0.661 & & \\ Effort Expectancy & EE1 & 0.755 & 0.806 & 0.581 \\  & EE2 & 0.813 & & \\  & EE3 & 0.716 & & \\ Social Influence & SI1 & 0.745 & 0.810 & 0.587 \\  & SI2 & 0.834 & & \\ Facilitating Conditions & FC1 & 0.815 & 0.884 & 0.718 \\  & FC2 & 0.928 & & \\  & FC3 & 0.792 & & \\ Behavioral Intention & BI1 & 0.817 & 0.889 & 0.728 \\  & BI2 & 0.821 & & \\  & BI3 & 0.917 & & \\ \hline \end{tabular}
\end{table}
Table 5: _Cont._Table 7 enumerates the path coefficients, critical ratios (C.R.), and significance levels (\(p\)-values). Both H1-H3 and H6-H12 are significant since the C.R. is satisfied over 1.96, and the \(p\)-value is less than 0.05. Meanwhile, from the results of the routing test, it can be obtained that learning experience does not constitute a significant influence on effort, expectancy (\(\beta\) = 0.0.058, \(p\) > 0.05), and company atmosphere is not a positive influence factor for social influence (\(\beta\) = 0.079, \(p\) > 0.05), and, therefore, H4 and H5 are not valid; all other paths have a significant positive influence and the rest of the hypotheses are valid.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Measurement Indicators** & **CMIN** & **DF** & **CMIN/DF** & **IFI** & **TLI** & **CFI** & **RMSE** \\ \hline Measured value & 1320.846 & 662 & 1.995 & 0.940 & 0.933 & 0.94 & 0.042 \\ Reference standard & — & — & \(\leq\)3.00 & \(\geq\)0.90 & \(\geq\)0.90 & \(\geq\)0.90 & \(\leq\)0.08 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Measurement model fit indices.  
Figure 3: Structural equation modeling.
## 2 System Overview  
The complete system architecture of a mobile sensor network includes a group of mobile sensor nodes, a base station, upper communication network infrastructures and clients. As shown in Figure 1, the sensor nodes are scattered in the target environment and they form a multi-hop mesh networking architecture. Each of these sensor nodes has the capability of collecting data and routing data peer-to-peer to base stations. The mobile sensor node is in fact an enhanced sensor node. It not only has all the capabilities of the static sensor node, but also realizes mobility by adding a robotic base and a driver board. A base station is used to bridge the sensor network to another network or platform, such as Internet.  
A mobile sensor network is well suited for distributed measurement and control applications. Its architecture can be divided into three layers: node layer, server layer and client layer. The node layer consists of all the sensor nodes that can be either static or mobile. This layer is directly embedded into the physical world to get all kinds of data. The server layer includes a personal computer or a single board computer running server software. The client layer includes local clients and remote clients. The devices of the client layer can be any smart terminals, such as PCs, PDAs, Pocket PCs and smart phones. The server layer and the client layer communicate with each other and they form a typical example of Internet [10].
# A Synergistic Elixir-EDA-MQTT Framework for Advanced Smart Transportation Systems
## 3 Architecture Design
### MQTT for Event Transport in Edge Computing
#### 3.3.2 Leveraging MQTT 5.0 for Scalability and Feature Enhancement  
The introduction of MQTT 5.0 significantly strengthens its scalability and caters to both large-scale systems and small clients. Features like shared subscriptions and message expiry enhance message management and distribution in large deployments [27]. Session and message expiry intervals offer greater control over session states and message lifetimes, optimizing resource usage, especially in resource-constrained environments. Additionally, MQTT 5.0 introduces new message properties like content type, correlation data, and user properties, enriching the contextual information available for complex data processing and real-time decision making in edge computing systems.
# Optimizing Retransmission Threshold in Wireless Sensor Networks
## 1 Introduction
Simulation results show that the proposed algorithms in the paper have better performance for real-time data delivery. The rest of this paper is organized as follows. The related works on real-time data delivery are surveyed in Section 2. In Section 3, the problem is described. In Section 4, a dynamic programming-based distributed algorithm for finding optimal retransmission thresholds is provided. Section 5 gives a linear programming-based approximation algorithm, and the ratio bound is analyzed. In Section 6, a Lagrange multiplier-based distributed \(O(1)\)-approximation algorithm with time complexity \(O(1)\) is proposed. Experimental results are illustrated in Section 7, and Section 8 concludes this paper.
# A Simple Alternative Method for Preservation of 2-Methylisoborneol in Water Samples
## 4 Conclusions  
The experimental results for the deionized water show that both sodium hypochlorite at 2-10 mg/L and potassium permanganate at 10 mg/L may preserve 2-MIB in water for 14 days at 4 and 25 \({}^{\circ}\)C, with 2-MIB concentration reduction by <10% and <16%, respectively. However, when tested in natural water, permanganate failed to prevent concentration reduction of 2-MIB because of the formation of manganese dioxide particles from the reduction of permanganate and 2-MIB adsorption on the particle surface. The concentration reduction was 15%-50% for the three tested water samples. Sodium hypochlorite successfully inhibited the reduction of 2-MIB from biodegradation at both temperatures. If the residual chlorine was higher than 0.5 mg/L during the 14 day experimental period, the concentration change in 2-MIB was less than 13% for all three tested natural water samples. The rate of 2-MIB degradation during the preservation may be described by first-order reaction, with the rate constants decreasing with increasing chlorine concentration. This study demonstrates that sodium hypochlorite may be used as an alternative chemical to prevent 2-MIB from biodegradation in water samples before analysis.  
All author make substantial contributions to conception and design, acquisition of data, and analysis of data. All Authors participate in drafting the article or revising it critically for important intellectual content. T-F.L. for critical revision.  
This research was supported by the Taiwan Ministry of Science and Technology (Number: MOST 103-2221-E-006-011-MY3 and NSC 98-2221-E-006-022-MY3) and National Cheng Kung University, Taiwan (the University Advancement Project sponsored by the Taiwan Ministry of Education).  
The authors declare no conflict of interest.
Figure 13: Changes of 2-MIB concentration in natural water preserved with chlorine and stored at 4 \({}^{\circ}\)C, where **(A)** is for the AGD reservoir; **(B)** is for the ZW reservoir; **(C)** is for the NH reservoir; and **(D)** is the residual chlorine concentrations.
# Highly Adaptive Reconfigurable Receiver Front-End for 5G and Satellite Applications
## 5 HARRF LNA Design
### K/Ka-Band LNA Design Procedure  
The K/Ka-Band LNA covers the frequency range 23 GHz to 28 GHz, including the 24.25 GHz to 27.5 GHz band allocated for 5G applications [18]. Similar to the X-band LNA, this K/Ka-Band LNA is also a three-stage cascade design (see Figure 12) using a 0.15 um InGaAs pHEMT process. The design aims for both low noise figure and high gain while maintaining stability and adequate output power.
## 3 Results
### Specific Gravity, Absorption Rate and Length Change  
Extrusion concrete panels are primarily used as interior and exterior materials for buildings, and thus, KS specify the requirements for not only strength, but also specific gravity, absorption rate, and rate of change in length caused by water absorption. In this experiment, the latter three factors were measured at each curing stage, and of the results are shown in Table 5. In the case of specific gravity, it was positively correlated to the silica powder-WCP substitution ratio. This is thought to be due to the fact that the specific gravity of WCP (2.80 g/cm\({}^{3}\)) was slightly higher than that of silica powder (2.66 g/cm\({}^{3}\)). After the curing processes, the specific gravity decreased by about 0.2 g/cm\({}^{3}\) in all of the specimens. This was due to the formation of voids in the crystal structures as a result of cement hydrates forming C-S-H systems during the steam and autoclave processes, and accordingly, the specific gravity decreased after the specimens became dry. All of the specimens satisfied the specific gravity criterion prescribed by KS, which is below 2.0.  
KS prescribes that the absorption rate be lower than 18%. The results of the absorption rate test showed that the more curing stages (air-dried curing, steam curing, and autoclave curing) and the higher the substitution ratio, the higher the absorption rate was. To be more specific, the specimen with a 100% substitution ratio that was autoclave cured, had an absorption rate of 14.69%. An increase in the absorption rate caused by curing is deemed to be caused by the enlargement of voids in the crystal structures resulting from the formation of tobermorite crystals and C-S-H hydrates, as mentioned above. On the other hand, an increase in the absorption rate, caused by an increase in the substitution ratio, is deemed to result from the fact that there are more pores in the old cement paste hydrates in WCP than in silica powder. KS prescribes that the rate of change in length caused by absorption to be lower than 0.12%. The results of the experiment showed that the changes caused by the substitution ratio were minor, while there were variations caused by the number of curing stages that were conducted. The rate of change in length decreased with more curing stages, and this was determined to be due to the stabilization of the hydrate structures. The specimen, which was autoclave cured, was the only one that satisfied the specification of KS. Based on the results of the three tests above, it was determined that the autoclave curing is an essential element in producing extrusion concrete panels that conformed to KS, and that the formation of tobermorite had a strong influence on product stability.
# RAC1B: A Rho GTPase with Versatile Functions in Malignant Transformation and Tumor Progression
## 6 Regulation of Signaling Pathways by RAC1B
### NF\(\kappa\)B  
Both RAC1 and RAC1B are able to activate NF\(\kappa\)B to the same extent [8]. Active RAC1B induced the phosphorylation and membrane translocation of IxB\(\alpha\), a prerequisite for the activation of NF\(\kappa\)B [41]. In addition, RAC1 and RAC1B stimulate transcriptional activation from reporter genes driven by NF\(\kappa\)B motifs or the _CCND1_ promoter in an IxB\(\alpha\)- and ROS-dependent manner. However, in colorectal cells RAC1B was unable to induce nuclear translocation of RelB and p52, and to activate transcription from a RelB-specific reporter. These data provide evidence that increased levels of RAC1B in colorectal tumors may promote tumorigenesis by stimulating canonical NF\(\kappa\)B signaling while circumventing a negative feedback from the RelB pathway [61]. RAC1B overexpression stimulates NF\(\kappa\)B-mediated pro-proliferative and anti-apoptotic signaling also in thyroid cancer cells as judged by an increase in NF\(\kappa\)B reporter gene activity and a decrease in IxB\(\alpha\) protein levels [26]. However, [PERSON] and colleagues reported in NIH3T3 cells that unlike activated Rac1 (Rac1-Q61L), Rac1b did not exhibit an enhanced ability for transcriptional transactivation of NF\(\kappa\)B [7]. In addition, RAC1B, unlike RAC1 signaling, is unable to control the expression of genes regulated by the transcriptional repressor BCL-6, such as the p50 precursor NF\(\kappa\)B1/p105 and the cell adhesion molecule CD44 [62].  
Figure 4: Illustration of the predominant involvement of RAC1B in cancer-associated signaling pathways. Green arrows pointing away from RAC1B indicate activation, those pointing toward RAC1B indicate upregulation of expression (MEK1/2) or activation (DVL3). Red lines indicate suppression. For details see text.
# Automated Clinical Impression Generation for Medical Signal Data Searches
## 4 Discussion
### Limitations and Future Directions  
This work addresses the novel problem of indexing commercial term-based databases using EEG signals and proposes a promising method based on a CNN and a transformer-based deep learning architecture. However, a major challenge arises from the limited availability of large-scale EEG datasets due to the sensitivity and privacy concerns associated with medical signals. To overcome this limitation, the authors intend to explore the development of a continually learning system that can adapt and improve over time without relying heavily on sharing private and sensitive medical data.
# Algebraic Point Projection for Immersed Boundary Analysis on Low Degree NURBS Curves and Surfaces
###### Abstract  
Point projection is an important geometric need when boundaries described by parametric curves and surfaces are immersed in domains. In problems where an immersed parametric boundary evolves with time as in solidification or fracture analysis, the projection from a point in the domain to the boundary is necessary to determine the interaction of the moving boundary with the underlying domain approximation. Furthermore, during analysis, since the driving force behind interface evolution depends on locally computed curvatures and normals, it is ideal if the parametric entity is not approximated as piecewise-linear. To address this challenge, we present in this paper an algebraic procedure to project a point on to Non-uniform rational B-spline (NURBS) curves and surfaces. The developed technique utilizes the resultant theory to construct implicit forms of parametric Bezier patches, level sets of which are termed algebraic level sets (ALS). Boolean compositions of the algebraic level sets are carried out using the theory of R-functions. The algebraic level sets and their gradients at a given point on the domain are then used to project the point onto the immersed boundary. Beginning with a first-order algorithm, sequentially refined procedures culminating in a second-order projection algorithm are described for NURBS curves and surfaces. Examples are presented to illustrate the efficiency and robustness of the developed method. More importantly, the method is shown to be robust and able to generate valid solutions even for curves and surfaces with high local curvature or \(\mathcal{G}_{0}\) continuity--problems where the Newton-Raphson method fails due to discontinuity in the projected points or because the numerical iterations fail to converge to a solution, respectively.  
NURBS; implicit representation; resultant; algebraic level sets; point projection and inversion +
Footnote †: journal:
## 2 The Subject of Study and Failure Background  
Because of the large number of applications of Pb-free components, the Pb-free circuit board used for deep-space applications attracts a lot of interest. At present, users want to know whether the Pb-free circuit board can be used reliably in space.  
In order to verify the reliability of a typical Pb-free circuit board in aerospace applications, five circuits were put into low-temperature and shock test, which was called a qualification test in the subsequent section. Combining with application requirements and JEDEC standards (JESD22-B110 and JESD22-A119), the test temperature was \(-100\)\({}^{\circ}\)C, and the test acceleration was 100G, 0.5-millisecond duration, and half-sin pulse. After the tests, all five circuits had failed, depending on the results of the printed circuit board (PCB) function test. There was no output of the circuit. Function tests for every component were conducted, and it could be confirmed that the failure of the PCB was caused by the memory (Figure 1) on the circuit. The memory could not store and read data normally. The package of the memory was Ball Grid Array (BGA), and the solder material was SAC305. Further analysis is needed in order to find out the root cause of the failure.
## 8 Conclusions  
In this work, we surveyed the smart grid project from different points of view, analysing the efforts that the scientific community is making to implement this infrastructure. We presented management solutions, technological aspects and different kinds of optimization techniques. We also analysed the current European regulatory environment and listed the relevant organisms and EU bodies responsible of supporting the smart grid.  
One of the facts that this survey has shown is that, from a technological point of view, there are plenty of solutions already available. Several management systems have been tested and are ready for deployment. However, another fact is evident: although many different standards exist, especially for data communication and protocols, few of them have been widely accepted for application in energy distribution networks. This can be an issue, because one of the keys to an efficient energy network is interoperability between different energy providers. A partial solution can be using Web Services and system integration techniques, but there has to be a standard definition for data structures and models in order to enlarge the scope of the network. The biggest obstacle to standardization, and in general to smart grid implementation in Europe, from our point of view, is given by the complex situation of the European energy market, where regulated and liberalized regimes still coexist. In regulated markets, the main grid operator establishes a monopoly business that does not allow consumers to choose among different technologies. Typical examples are metering services, forecasting, and so on. Also, energy retailers, although present on the territory, are not able to assume their innovative role in the Future Energy Market depicted in Section 3, in terms of demand response, consumer services and network operation.  
As far as concerns the research activity, what should be done is embracing a common view of the problem, focusing on interoperability and supporting the creation and affirmation of technology standards. In this way, the development of solutions and optimization techniques can be immediately followed by field testing and deployment, speeding up the overall infrastructure realization process.
## 3 PLC Production Line Signal and IoT Connection
### Raspberry PI application of fog system.  
For the fog controller, choosing a single chip, such as an Arduino computer, to perform as the fog (middle) layer of the network is not suitable because it might limit the performance of the power and storage of the computer. In this study, Raspberry PI 4 Model B was used in the fog system. This device processor was a 1.5-GHz BCM2711 (quad-core Cor-tex-A72), the storage memory capacity was increased to 4 GB, and it had Bluetooth 5.0, with four USB 2.0/3.0 interfaces, HDMI vision interfaces, and a power supply with USB-C interface. These specifications enabled the portability of this device across the entire supply chain of the factory. However, the original technical decision-making strategy may have an impact on portability. Fortunately, cloudlets or microcomputer cluster methods can also be used. It can be faster to solve engineering problems and special requirements for a larger computer stream source are not then needed. This research uses a Raspberry PI embedded system for video streaming. First, the test was carried out using a camera lens and pictures/videos. Image streaming should then be performed to connect to internet services. Finally, OpenCV was used to process the images and build a hardware development platform. The basic image technology of this system is as follows:  
* Image transformation: color space and basic image processing; color space (RGB, YUV, HSV).
* Affine transformation includes translation, rotation, scaling, and cropping. Image-processing methods include (a) blur, (b) erosion, and (c) dilation.
* Optimal edge path: Canny edge detection, Hough transform, and moment invariance finish the contour.
* For image applications, except for the above-mentioned color recognition function, a face-detection (Haar classifier) method was developed as a simulate-type lights-out smart factory constructed with an application of the machine learning method. Based on its image-recognition system, Raspberry PI was used with the fog system to create a smart factory for this study.
* Fog computing and node control.  
A suitable wireless node controller needs to be developed that is used to intercept the face recognition of the neural algorithm and the color recognition of the processed product to detect product targets on the production line.  
An algorithm, for example, for detecting a signal can be used to detect abnormalities in a factory. The image detector is shown in Figure 8. The embedded system of the Raspberry PI is defined as a fog-computing controller, and the general input and output of the node are extended and connected as a relay to control the terminal node to transmit the status of the control light. The output was linked to the PLC. The main purpose was to immediately stop the operation of the production line until no dangerous elimination was expected, at which point the production line could be restarted.