esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
Considering the positional shift of the remote GSNN stations as far as the Zagreb area, it is possible that the late 2020 Petrinja event additionally relaxed a strain accumulated on the thrust fault system of Mt. Medvednica which ruptured in early 2020, but with a lower magnitude than expected [33]. However, the vertical displacements could be the result of the consolidation of the superficial deposits in the Sava, Kupa, and Glina river plains [34] due to the earthquake shaking [33]. In comparison with prior research, our study addressed a critical gap by elucidating the spatial heterogeneity of displacements resulting from the earthquake. The identification of the specific stations experiencing the most substantial displacements, such as Novi Grad (NOVI), Zagreb (ZAGR), Novska (NOVS), and Bjelovar (BJEL), contributes to a more nuanced understanding of the seismic effects. Furthermore, the recognition that eastern stations exhibit a greater impact than those in the west adds a novel layer to the seismic response characterization. The significance of our work lies in its potential to refine geodetic and geophysical applications, offering insights that were not apparent in previous literature. By identifying not only the magnitude but also the spatial intricacies of station displacements, our study overcomes limitations in the existing body of knowledge, providing a more comprehensive and nuanced perspective on the aftermath of the Petrinja earthquake while also filling a gap in the understanding of the heterogeneity of seismic impacts on geodetic stations and introducing a methodological innovation that contributes significantly to the overall state of knowledge in seismogeodesy.
# Optimization of Multi-Day Flexible EMU Routing Plan for High-Speed Rail Networks
## 1 Introduction
### Research on Operation Optimization in EMU Routing Plans
A branch-and-price algorithm was developed to handle large-scale instances, and the model was further extended by integrating maintenance constraints into subproblems. [PERSON] et al. [15] proposed a two-stage heuristic for rolling stock scheduling with maintenance constraints for China's high-speed railway. Candidate schedules are first generated via MIP without maintenance and then evaluated for feasibility using an assignment approach. Tested on Zhengzhou Group data, the method outperformed manual planning and reduced operating costs by 10.5%. [PERSON] et al. [16] developed a mixed-integer linear programming model to minimize the number of EMUs used, incorporating constraints such as overnight storage locations, platform track assignments, and both mileage- and time-based maintenance requirements. A two-stage branch-and-bound algorithm was designed to solve the model efficiently.
## 1 Introduction
The effects of both the vibration and payload variation are considered as uncertain disturbance torques. That is, in the control implementation for both approaches, we do not require prior knowledge about the frequencies of the vibration and payload variation; however, high position tracking accuracy is achieved. Moreover, the theoretical analysis presents important features in the performance of both controllers. Where the first approach gives less conservative tracking error. Simply put, it ensures the tracking error to be arbitrarily small through two constants that are injected into the controller. While the second approach introduces an arbitrarily high rate of convergence for the tracking error; however, the convergence rate can be easily adjusted by tuning the gains in the control law. The paper is organized as follows. In Section 2, the dynamic model of the robot and some preliminaries are introduced. In Section 3, the problem formulation is defined, the control approaches are presented, and the controllers are designed. Simulations are carried out to illustrate the performance of the proposed controllers, and the results are discussed in Section 4. The conclusions are given in Section 5.
# Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues
## 4 Localization Techniques
### Device-Based Localization
#### 4.1.3 Bluetooth-Based Localization  
In this method, the location of a moving device is treated the same as that of an individual object. Location precision is dependent on the number and the size of the cells. Several localization schemes based on Bluetooth technology have generated enhanced accuracy. The location approximation algorithm proposed in [48] determines smartphone location with the help of RSSI measurement. The unified sensor node in the smartphone and the structure card request for the source data. Trilateration, established in [49], is used as a localization approach to the fingerprint to minimize earlier errors. Enhanced Bluetooth technology platform [50] for the remote-control application in an irrigation system which provides location information to the users.
## 2 Theoretical Background and Hypotheses Development  
The unified theory of acceptance and use of technology (UTAUT) has been applied, since it is the main methodological framework for knowing the intention to use a certain technology [36; 37; 38; 39; 40; 41; 42]. This model was developed by [PERSON] et al. [43] to explain the behavior and predisposition of users to use the technology. The main factors of the UTAUT model have been extracted from eight different theoretical frameworks that make up the central constructions of the model: performance expectancy, effort expectancy, facilitating conditions, and social influence [43; 44]. In this study, the different constructs were adapted to the IoT. Therefore, all of the dimensions were adequately contextualized with the central topic of the research.  
The research model was composed of the constructions of the UTAUT: performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), attitude toward using technology (ATUT), and behavioral intention to use (BI). In the established hypothetical model, BI is affected by PE, EE, SI, FC, and ATUT. While gender and age affect PE, EE, SI, FC, and ATUT (Figure 1).
## 1 Introduction  
With the expansion and renovation of cities, it is common to excavate deep foundation pits around existing tunnels. The construction of the pits inevitably has an effect on tunnels, and it is difficult to accurately assess whether this effect is within acceptable limits [1; 2; 3; 4; 5]. Even in similar cases, tunnels may respond differently. [PERSON] et al. observed settlement of the tunnel after excavation [6], while [PERSON] et al. observed substantial tunnel heave [7]. An increase in tunnel lining stress or excessive displacement can cause cracking, leakage, train speed reduction, and even collapse, so an accurate assessment of the effect of excavation on the tunnels is very important [8; 9].  
Over the years, many scholars have used theoretical analysis and numerical simulation to study the effect of excavation on tunnels and have had fruitful results. Among the existing theoretical methods, the elastic foundation beams theory is the most widely used [10]. Its basic principle is to simplify the tunnel as an elastic foundation beam to calculate the tunnel deformation, and the excavation is simplified as unloading [11]. The unloading is determined by the Boussinesq or Mindlin theoretical stress solution [12; 13]. However, using the theoretical method, it is difficult to calculate the tunnel deformation response in non-uniform soil strata, so many scholars use numerical simulation to study this problem. [PERSON] et al. established a 3D model for the excavation of the Shanghai subway tunnel and the foundation pits are adjacent to the subway station [14]. The numerical results are in good agreement with the field data. [PERSON] et al. used the finite element method to study the effect of excavation sequence on tunnel heave [15]. [PERSON] et al. studied the effect in sand and cobble strata [16]. [PERSON] et al. developed a simplified method to calculate tunnel deformation and additional stress based on finite element calculation results [17]. Moreover, for planar problems, a large number of two-dimensional models were developed [11; 18; 19; 20]. However, most of the tunnel axes in the above studies are straight, and the deformation and stress response of intersecting curving tunnels are less studied. The complexity of the shape of tunnels makes it more difficult to predict the effect of excavation on the tunnels.  
In this paper, a 3D numerical model is established through the finite element software PLAXIS\({}^{\text{3D}}\) V20, based on a case of the tunnel hub of Nanjing metro line 2. Four tunnels are under the excavation pits and intersect each other with a complex shape. Advanced constitutive models, HSS and HB models, and input parameter determination methods are applied in this study. The numerical analysis results are compared with the field data. Attention is paid to the analysis of displacement characteristics and stress changes in the tunnel under the effect of excavation. This study will deepen the understanding of the effect of foundation excavation on intersecting tunnels, optimize monitoring arrangements, and provide a basis for excavation for an increasing number of similar projects in the future.
## 5 Conclusions  
This paper presents a novel PSO-FCM algorithm designed specifically for accurately identifying modulation orders within MQAM schemes. This hybrid approach integrates the SN-SC algorithm for initial cluster center obtainment and combines FCM and PSO techniques to enhance precision in determining modulation orders. By evaluating fitness using FCM's objective function and analyzing the ratio between maximum and minimum cluster center radii, the algorithm effectively discerns various MQAM modulation schemes. The simulation results validate the algorithm's superior performance, especially in accurately identifying modulation orders even in low-SNR scenarios. This robustness underscores its potential practical application in real-world communication systems where precise QAM modulation order identification is crucial.  
Conceptualization, Z.Q., H.Z., J.L. and H.S.; methodology, Z.Q. and H.S.; writing--original draft preparation, Z.Q.; writing--review and editing, H.Z., J.L. and H.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China under the grant number U1604160.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.  
The authors declare no conflict of interest.
## 3 Models and Assumptions
### The Technological Context  
Technical factors mainly refer to the cognitive attributes of the new technology to be adopted by the enterprise (including comparative advantage, compatibility, complexity, observability, and trialability). Comparative advantage means that enterprises adopt innovations when they realize that there are potential benefits of using innovation. Compared with traditional industrial robots, collaborative robot innovation has the comparative advantages of low investment costs, high safety, ergonomics, and high flexibility [34; 35]. Compatibility indicates the coexistence degree of innovation and existing technology. Atthis stage, collaborative robots and traditional industrial robots are complementary and can coexist well with the existing technologies of enterprises [29]. Comparative advantage and compatibility have long been considered the necessary conditions for innovation to be adopted [30]. For instance, the data analysis result of a sample of 200 SMEs in Malaysia shows that comparative advantage and compatibility have a significant impact on the adoption of e-commerce [56]. In addition, another study on the determinants of e-commerce adoption by Romanian SMEs confirms that the main factor determining e-commerce adoption is the comparative advantage brought by e-commerce activities, while the main obstacle is the lack of compatibility between e-commerce activities and the business patterns of SMEs [57].  
Complexity refers to the degree to which innovation is hard to comprehend and use, and is generally considered to be negatively correlated with adoption [30; 39; 58; 59]. Collaborative robots are far less complex than traditional industrial robots, mainly in terms of simple programming, convenient installation, and flexible deployment [5; 11; 36].  
As previously mentioned, observability and trialability have not been widely studied in innovation adoption. However, the collaborative robot has the advantages of being small in size, lightweight, and plug-and-play [23; 41; 42], which makes it easy for collaborative robot manufacturers (or vendors) to display robots in an exhibition hall and for enterprises to conduct on-site trials [29], reflecting the observability and trialability of the collaborative robot. Based on the above, the following hypotheses are proposed:  
Figure 1: Research Model.  
**H1.**_The comparative advantage of collaborative robot innovation is positively correlated with the adoption intention of SMEs._  
**H2.**_The compatibility of collaborative robot innovation is positively correlated with the adoption intention of SMEs._  
**H3.**_The complexity of collaborative robot innovation is negatively correlated with the adoption intention of SMEs._  
**H4.**_The observability of collaborative robot innovation is positively correlated with the adoption intention of SMEs._  
**H5.**_The trialability of collaborative robot innovation is positively correlated with the adoption intention of SMEs._
## 4 Experiments and Analysis
### Experimental Setup  
#### 4.1.1 Dataset and Experimental Platform  
We collected three source codes from GNU software programs: Glpk (v4.65), Xml (v2.9.4), and Sqlite3 (v0.8.6). Each program was compiled into 12 binary versions using GCC (v11.3) across various architectures (ARM, MIPS, X86) and optimization levels (O0-O3). These binary codes were disassembled with IDA Pro (V7.3), yielding 87,488 functions, 1,802,028 basic blocks, and 10,269,352 instructions, as shown in Table 4. We constructed the experimental dataset by generating pairs of homologous and non-homologous function samples, dividing it into training (80%), validation (10%), and testing (10%) subsets.  
We implemented the GMN+ using PyTorch (v1.8.1) and trained it on two 24 GB NVIDIA GeForce RTX 3090 ti GPUs. The values of the key hyperparameters used in our experiments are detailed in Table 5. A batch size of 128 is used to optimize computational efficiency. Node and edge embedding dimensions are set at 256 to capture detailed graph structures effectively. A graph-embedding dimension of 128 is chosen to balance detail with computational efficiency, and a learning rate of 0.0001 ensures gradual optimization of the model.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Software** & **FNs** & **BBs** & **INs** \\ \hline Glpk(v4.65) & 19,457 & 431,144 & 2,792,595 \\ Xml(v2.9.4) & 35,107 & 757,433 & 3,831,902 \\ Sqlite3(v0.8.6) & 32,924 & 613,451 & 3,644,855 \\ All & 87,488 & 1,802,028 & 10,269,352 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of the dataset used in our study (FN, BB, IN representing the number of FuNctions, Basic Blocks, and INstructions, respectively).
###### Abstract  
For the full use of fish by-products to produce antioxidant peptides, skipjack tuna (_Katsuwonus pelamis_) heads generated during can processing were defatted and hydrolyzed using the in vitro gastrointestinal (GI) digestion (pepsin-trypsin system) method and six antioxidant peptides (P1 to P6) were purified from the head hydrolysate (KPH) using ultrafiltration and serial chromatography methods. Six isolated peptides (P1 to P6) were identified as Val-Glu-Glu (VEE, P1), Trp-Met-Phe-Asp-Trp (WMFDW, P2), Asp-Ala-Gly-Pro-Tyr-Gly-Pro-Ile (DAGPYGPI, P3), Trp-Met-Gly-Pro-Tyr (WMGPY, P4), Glu-Arg-Gly-Pro-Leu-Gly-Pro-His (ERGPLGPH, P5), and Glu-Met-Gly-Pro-Ala (EMGPA, P6), respectively, using a protein sequencer and electrospray ionization-mass spectrometer. Among skipjack tuna head hydrolyses, fractions, and six isolated peptides (P1 to P6), WMFDW (P2), WMGPY (P4), and EMGPA (P6) showed the highest radical scavenging activities on 2,2-diphenyl-1-picrylhydrazyl (DPPH) (EC\({}_{50}\) values of 0.31, 0.33, and 0.46 mg/mL for WMFDW, WMGPY, and EMGPA, respectively), hydroxyl (EC\({}_{50}\) values of 0.30, 0.43, and 0.52 mg/mL for WMFDW, WMGPY, and EMGPA, respectively), and superoxide anion (EC\({}_{50}\) values of 0.56, 0.38, and 0.71 mg/mL for WMFDW, WMGPY, and EMGPA, respectively). Moreover, WMFDW, WMGPY, and EMGPA showed strong capability in reducing power and lipid peroxidation inhibition in the linoleic acid system. In addition, WMFDW, WMGPY, and EMGPA can retain strong antioxidant activity at temperatures lower than 60 \({}^{\circ}\)C and pH values ranged from 5 to 9. The results showed that six isolated peptides (P1 to P6) from skipjack tuna heads, especially WMFDW, WMGPY, and EMGPA, might be applied in health care products acting as powerful antioxidant agents.  
Keywords:skipjack tuna (_Katsuwonus pelamis_); head; peptide; antioxidant activity; stability +
Footnote †: journal:
## 2 Related Works
The research in [13] examines the use of IPsec for establishing VPNs tailored to e-business requirements. It utilizes a Linksys router as an access point and a VPN concentrator, with OpenSWAN as the system daemon. The setup employs IKEv1-L2 TP for authentication and traffic management and IPsec for encryption. The article [14] proposes an approach to deploy VPN technologies for securely encrypting traffic in untrusted networks. This includes environments like bars, lounges, conferences, free hotspots, airport Wi-Fi, and,more broadly, during any travel scenario. The IPsec stack generally consists of three main parts: Encapsulating Security Payload (ESP), Authentication Header (AH), and the Internet Key Exchange protocol (IKE). The previously mentioned work [13] discusses the AH protocol with an emphasis on VPN security and Quality of Service (QoS) aspects. The IKE protocol can generate session keys for secure communications between VPN endpoints through a proper message exchange, with two existing versions: IKEv1 and IKEv2 [9; 15; 16]. IKEv1 offers extensive configuration options but suffers from architectural complexity, making it difficult to deploy in modern networks. In contrast, IKEv2 improves upon IKEv1 by addressing its limitations and providing more efficient encryption, with native support on platforms like OS X 10.11+, iOS 9.1+, Linux 3.x+, and Windows 8+. Additionally, IKEv2 is well-supported on mobile devices and compatible with IKEv2-aware clients and third-party iOS, Android, Blackberry, and Windows applications. In [17], a comparative analysis of VPN technologies such as L2 TP, PPTP, OpenVPN, Ethernet over IP (EoIP), and MPLS evaluates their suitability for specific business needs based on performance metrics and packet transit characteristics. In [11], the focus is on the authentication parameters required for VPN server access. While some implementations may only necessitate the traditional username/password combination, other deployments like IKEv1-XAUTH may require additional parameters. Microsoft's Secure Socket Tunneling Protocol (SSTP) [18; 19] is proposed to channel PPP device traffic through an encrypted VPN tunnel via HTTP using SSL/TLS transport, handling key negotiation, channel encryption, and traffic integrity. Quick UDP Internet Connections (QUIC) is highlighted as suitable for IoT devices with limited resources [20] with implementation guidance in general TrAnsPort services (TAPS) [10], as discussed in [12]. VPNaaS simplifies network security by integrating configurations into a single product to meet various corporate security needs and enable access to virtualized networks on the cloud. The implementation of VPNaaS using WireGuard with a 5G WAN backbone is proposed in [21]. In [22], an experimental analysis on a Debian Linux environment implements the IPsec tunneling protocol with various encryption algorithms, concluding that IPsec AES-sha1 performs comparably to IPsec 3 DES-sha1. However, UDP VPN encryption/decryption can degrade performance due to high memory/CPU usage.
## 1 Introduction
Depending on the working gases used and operating parameters (duration of non-thermal plasma application, choice of non-thermal plasma source...), various reactive species such as reactive oxygen and nitrogen species (ROS and RNS) are formed, which can lead to the formation of toxic by-products or impair food quality. Under laboratory conditions, research is conducted with smaller quantities of food, which leads to scaling problems when processing larger quantities of food. The standardisation protocols require precise process monitoring, subsequent diagnostics of the plasma used and the use of Industry 4.0 technologies for reliable prediction of results [48; 49; 50]. The monitoring and control of any process in plasma technology is linked to a fundamental understanding of the physical and chemical properties of the plasma system used or generated. Optical emission spectroscopy is used as a diagnostic sensor to collect useful information about the properties of the plasma and to identify the excited species generated in the plasma, as these are critical parameters in all plasma technology applications. Optical emission spectroscopy is compatible with non-thermal plasma environments and contamination-sensitive applications and provides near-real-time feedback. The spectral resolution of the optical emission spectroscopy system allows the separation of many closely spaced emission peaks, which is a characteristic of any plasma system [51; 52]. The aim of this study was to demonstrate the necessity of using optical emission spectroscopy as a non-invasive sensor for the monitoring and diagnosis of non-thermal plasma. The particular novelty of this research is the performance of spectroscopic measurements in an experimental setup with high-voltage electrical discharge, which is already used in the laboratory for the extraction of bioactive components or for the inactivation of microorganisms. The measurements performed in our experiment with the optical emission spectrometer allowed us to determine the composition of generated plasma, and the valuable contribution of this study is the determination of the most important plasma properties, electron temperature and electron density, using actual measurement data rather than theoretical assumptions or simulations. When using non-thermal technologies, the working temperature interval is important, and by applying our spectroscopic method, it could be shown that plasma technology, as a non-thermal technology, can be suitable for use in the food sector after optimising the process parameters. No comparable studies can be found in the literature, and no data on electron temperatures and electron densities are available that have been determined in actual experimental measurements with non-thermal plasma technology in the food sector. The authors found this topic to be of interdisciplinary interest and, despite the increasingly widespread use of non-thermal plasma technology, still under-researched. Researchers, not only from the food sciences but also from the natural sciences and computer science, can make an important contribution to these investigations.
## 5 Results and Discussion
### Reliability of the Evaluation Tool  
The survey results fall under the category of an attitude scale. In quantitative analysis, reliability analysis assesses the credibility of the survey research, referring to the extent to which the tool can produce the same results when it is measured again under the same conditions. Typically, CA (Cronbach's alpha) is used to calculate the reliability of the scale. [PERSON] (2018) considers a CA value greater than 0.70 to be reliable for a questionnaire. In this study, the standardized System Usability Scale (SUS) was used, with a reliability of 0.91 ([PERSON] et al., 2018), indicating that the questionnaire is reliable and possesses sufficient internal consistency.