esa-sceva/satcom-chunk-collection huggingface dataset:
# Developing a Fire Monitoring System Based on MQTT, ESP-NOW, and a REM in Industrial Environments
###### Abstract  
Fires and fire hazards in industrial environments pose a significant risk to safety, infrastructure, and the operational community. The need for real-time monitoring systems capable of detecting fires early and transmitting alerts promptly is crucial. This paper presents a fire monitoring system utilizing lightweight communication protocols, a multi-hop wireless network, and anomaly detection techniques. The system leverages Message Queue Telemetry Transport (MQTT) for efficient message exchange, the ESP-NOW for low-latency and reliable multi-hop wireless communications, and a radio environment map for optimal node placement, eliminating packet loss and ensuring robust data transmission. The proposed system addresses the limitations of traditional fire monitoring systems, providing flexibility, scalability, and robustness in detecting fire. Data collected by ESP32-CAM sensors, which are equipped with pre-trained YOLOv5-based fire detection modules, are processed and transmitted to a central monitoring server. Experimental results demonstrate a 100% success rate in fire detection transmissions, a significant reduction in latency to 150 ms, and zero packet loss under REM-guided configuration. These findings validate the system's suitability for real-time monitoring in high-risk industrial settings. Future work will focus on enhancing the anomaly detection model for greater accuracy, expanding scalability through additional communication protocols, like LoRaWAN, and incorporating adaptive algorithms for real-time network optimization.  
a _Article_
# HTN: Hybrid Transformer Network for Curvature of Cervical Spine Estimation
## 2 Materials and Methods  
### Datasets  
Two datasets are used to evaluate the superiority of our proposed method: our dataset and the public AASCE MICCAI 2019 challenge dataset. Figure 1 shows a few samples with corresponding landmarks of these two datasets. More details are presented as follows:  
CS799 dataset: Our dataset contains a total of 799 LAT X-ray images of the cervical spine. All the samples were captured from 799 distinct human subjects. The subjects in this dataset exhibit a wide age distribution (from 12 to 84 years), and the average age is 45.3 years. The curvature of the cervical spine is also diverse. The Cobb angles are  
Figure 1: Samples from our dataset CS799 (**a**,**b**), and the AASCE MICCAI 2019 challenge dataset (**c**,**d**). The yellow points represent landmarks marked by experts.  
distributed between 0\({}^{\circ}\) and 46.3\({}^{\circ}\). The cervical spine has a unique vertebral appearance. All images were collected by Shanghai ChangZheng Hospital, annotated, and proofread by spine surgery specialists. The minimum resolution of the picture is 1217 \(\times\) 1779, while the maximum resolution is 1916 \(\times\) 2695. We trained our models on the training dataset with 559 images (75%), of which 159 images were used for validation (15%), and 81 images werew used for testing (10%). Each image includes 24 landmarks.  
AASCE MICCAI 2019 challenge dataset: Each X-ray image has 68 landmarks corresponding to 17 vertebrae. Each vertebra includes four corner landmarks (top-left, top-right, bottom-left, and bottom-right). The challenge also supplies Cobb angles for proximal thoracic (PT), main thoracic (MT), and thoracolumbar (TL). In the same way as the data was split in [9], we divided the dataset into three parts: 348 images for training (60%), 116 images for validation (20%), and 116 images for testing (20%).  
It is noteworthy that the division ratios of the two datasets are different. The division of the public dataset is consistent with previous methods. For our dataset CS799, we tried to use more samples for training, which may have caused some doubts. However, the focus of this paper is to verify the effectiveness of our proposed module. Therefore, the division of the dataset does not affect the conclusion.
# Digital Twins, Virtual Devices, and Augmentations for Self-Organising Cyber-Physical Collectives +
## 2 Digital Twins and Virtual Devices for CPS Engineering: A Review and Taxonomy
### Logical and Physical Devices: A Taxonomy  
#### 2.2.1 Background: Cyber-Physical Systems (CPS)  
A _cyber-physical system (CPS)_ is a system where software and physical components are connected in a feedback loop and carry out sensing, actuation, and computation (communication can be regarded as a form of sensing and actuation). Of such aspects, sensing and actuation typically need to be _situated_, that is, _localised_ in the physical context to accomplish their application-specific function of perceiving and affecting the environment. The situatedness is obtained by deploying concrete sensors and actuators in the physical world, for example, by embedding them in a larger device (such as a smartphone or a drone). Conversely, computations may be often run (almost) _anywhere_ and hence be _offloaded_ from the concrete devices. However, since data must be communicated to/from computational processes, there might exist constraints on where computations can actually be executed while preserving functionality. Still, the possibility of detaching computation from for example, the device requesting a service or the device to be controlled, provides engineers with larger design spaces where trade-offs (in terms of flexibility or performance metrics) can be made.  
In general, it is possible to distinguish physical devices based on their role in the design of the system. For instance, it is significant to distinguish between _application-level_ physical nodes (APN), which are the target of monitoring and control in the application; and _infrastructure-level_ physical nodes (IPN), which are those providing support, for example, in terms of networking, storage, and execution offloading. For example, consider a cyber-physical swarm: the APNs are the robots, while the IPNs may consist of edge servers upon which certain computations can be offloaded (e.g., allowing robots to save energy). Essentially, a typical APN may be a sensor, an actuator, or a larger device (such as a smartphone or a drone) packaging multiple sensors, actuators, and computing units together.  
Another sensible demarcation in the CPS engineering approach, based on the nature of the modelled entities, is between _logical_ devices (which exist as abstractions or components in models), _software_ entities (providing a representation of logical devices in terms of computational and possibly deployable components), and _physical_ devices (namely, actual entities existing in the real world--such as smartphones and drones). Notice that the logical and software devices are related in a way similar to digital twins with their digital threads.
# Data Exfiltration through Electromagnetic Covert Channel of Wired Industrial Control Systems
###### Abstract  
Industrial control systems (ICS) often contain sensitive information related to the corresponding equipment being controlled and their configurations. Protecting such information is important to both the manufacturers and users of such ICSs. This work demonstrates an attack vector on industrial control systems where information can be exfiltrated through a electromagnetic (EM) radiation covert channel from the wired Ethernet connections commonly used by these devices. The attack leverages compromised firmware for the controller--capable of encoding sensitive/critical information into the wired network as packet transmission patterns. The EM radiation from the wired network's communication is captured without direct physical interaction using a portable software-defined radio, and subsequently demodulated on the attacker's computer. This covert channel facilitates the exfiltration of data from a distance of up to two metres with a data rate of 10 bps without any significant data loss. The nature of this covert channel demonstrates that having strong firewalls and network security mechanisms does not fully protect ICSs, or other critical networked or local, air-gapped infrastructure.  
covert channel; EM radiation; exfiltration; air-gap; Ethernet; software-defined-radio Article
## Appendix A Stability
### Stability Condition on Kerr Effect  
In addition to the wave equation, we have to deal with the differential equation associated to the Kerr effect \(\frac{\partial}{\partial t}\vec{D}(\vec{r},t)=e_{0}e_{\infty}\frac{\partial}{ \partial t}\vec{E}(\vec{r},t)+\frac{\partial}{\partial t}\vec{P}_{Kerr}(\vec{ r},t)\). The discretization of this equation by employing the operators results to  
\[\partial_{t}\vec{D}^{s}=\Big{(}e_{0}(e_{\infty}+\alpha\chi_{0}^{(3)}|\vec{E}^{ s-\frac{1}{2}}|^{2})\Big{)}\partial_{t}\vec{E}^{s}.\]  
It is evident that \(|\vec{E}^{s-\frac{1}{2}}|^{2}=\vec{\widetilde{E}}_{0}\vec{\widetilde{E}}_{0} ^{*}y^{2s-1}\) and this result leads to the characteristic polynomial  
\[\Phi(y)=(y-1)^{2}(e_{0}(e_{\infty}+\alpha\chi_{0}^{(3)}|\vec{\widetilde{E}}_{0 }|^{2}y^{2s-1}))+4 ye_{0}e_{\infty}v^{2}\]  
Comparing this characteristic polynomial with this one obtained from the wave difference differential equation \(\Phi^{\prime}(y)=(y-1)^{2}e_{0}e_{\infty}+4 ye_{0}e_{\infty}v^{2}\), we see that they are similar when \(e_{\infty}\gg\alpha\chi_{0}^{(3)}|\vec{\widetilde{E}}_{0}|^{2}y^{2s-1}\). Obviously, we assume that \(|y|<1\), but notice here that we are not assuming the same thing that we want to demonstrate. We know that \(\Phi^{\prime}(y)\), under the classical stability condition, leads to \(|y|<1\) and in general for \(\forall s\geq\frac{1}{2}\) we find that \(\Phi(y)\equiv\Phi^{\prime}(y)\) when \(e_{\infty}\gg\alpha\chi_{0}^{(3)}|\vec{\widetilde{E}}_{0}|^{2}\). We can identify the problem at a glance. The stability depends on the laser intensity \(|\vec{\widetilde{E}}_{0}|\) through its propagation. In that case, we find the classical condition for stability already presented. Therefore, we can impose a condition to the laser intensity in order to preserve the stability; for instance, we can define an arbitrary factor \(D_{f}\) such that \(e_{\infty}\simeq D_{f}\alpha\chi_{0}^{(3)}|\vec{\widetilde{E}}_{0}|^{2}\). Therefore, to ensure the stability \(|\vec{\widetilde{E}}_{0}|<\sqrt{\frac{e_{\infty}}{D_{f}\alpha\chi_{0}^{(3)}}}\). From the last expression, we see that stability is related to the medium, optical properties as well as laser intensity. Hence a heuristic search helps to establish an asymptotic limit for this factor \(D_{f}\geq 10^{4}\).
# Implementation and Security Test of Zero-Knowledge Protocols on SSI Blockchain
## 6 Security Tests and Evaluation
### User Input Verification  
There are two sources of input external to the application: the configuration of the connection port (and IP address in the case of the Prover) and the parameter configuration. Allowing the user to establish the global parameters on which the protocol calculations are made forces a series of restrictions to be established. Specifically, for each of the protocols:  
* \(p,q\) must be two prime integers;
* \(q\) must be divisor of \(p-1\);
* \(a\
eq 1\) such that \(a^{q}=1\ mod\ p\).  
The rest of the variables are calculated from these or randomly in each iteration of the protocol. If the entered parameters do not meet these restrictions, they should be discarded.
###### Abstract  
Topology control is one of the most essential technologies in wireless sensor networks (WSNs); it constructs networks with certain characteristics through the usage of some approaches, such as power control and channel assignment, thereby reducing the inter-nodes interference and the energy consumption of the network. It is closely related to the efficiency of upper layer protocols, especially MAC and routing protocols, which are the same as underwater acoustic sensor networks (UASNs). Directional antenna technology (directional transducer in UASNs) has great advantages in minimizing interference and conserving energy by restraining the beamforming range. It enables nodes to communicate with only intended neighbors; nevertheless, additional problems emerge, such as how to guarantee the connectivity of the network. This paper focuses on the connectivity problem of UASNs equipped with tri-modal directional transducers, where the orientation of a transducer is stabilized after the network is set up. To efficiently minimize the total network energy consumption under constraint of connectivity, the problem is formulated to a minimum network cost transducer orientation (MNCTO) problem and is provided a reduction from the Hamiltonian path problem in hexagonal grid graphs (HPHGG), which is proved to be NP-complete. Furthermore, a heuristic greedy algorithm is proposed for MNCTO. The simulation evaluation results in a contrast with its omni-mode peer, showing that the proposed algorithm greatly reduces the network energy consumption by up to nearly half on the premise of satisfying connectivity.  
UASNs; topology control; directional; connectivity; NP-complete +
Footnote †: journal: Sensors  
0000-0001-9998-22001  
1
Footnote 1: [[https://www.mdpi.com/journal/sensors](https://www.mdpi.com/journal/sensors)]([https://www.mdpi.com/journal/sensors](https://www.mdpi.com/journal/sensors))
###### Abstract  
Natural antimicrobials are effective against both food-borne pathogens and spoilage bacteria. The current study aimed to evaluate the in vitro antimicrobial activity of eight natural bioactive compounds (BACs) and one synthetic compound, butylated hydroxylouene (BHT), and to evaluate the effect of one selected BAC (AITC) on the safety and quality of minced chicken meat. Additionally, physicochemical (pH, color, water-holding capacity (WHC), chemical forms of myoglobin (deoxymyoglobin-DeoMb, oxymyoglobin-OxyMb, and metmyloglobin-MetMb), thiobarbituric-acid-reactive substances (TBARS)), and microbiological properties (in vitro antimicrobial activity and determination of minimum inhibitory concentration (MIC)) were also evaluated through electronic-nose odor detection. Allyl-isothiocyanate (AITC), thymol, eugenol, and geraniol showed the broadest spectrum of in vitro antibacterial activity against one major meat spoilage bacterium and five pathogenic bacteria that were tested. Subsequently, AITC was selected to be applied to fresh minced chicken meat at different concentrations (at concentrations of the MIC (MIC-1), two times the MIC (MIC-2), and four times the MIC (MIC-4)). The chicken meat was then vacuum-packaged and kept for up to 14 days at 4 \({}^{\circ}\)C, and its quality properties were checked during storage. In this study, the addition of low concentrations of AITC (MIC-1) maintained the lightness (\(L^{\star}\)) and increased the WHC of the meat. High concentrations (MIC-2 and MIC-4) caused a significant increase in lightness (\(L^{\star}\)) and folded yellowness (\(b^{\star}\)) value, and they significantly reduced the redness (\(a^{\star}\)) and TBARS values compared to the control meat. The amounts of MetMb and DeoMb were reduced and the quantity of OxyMb was increased as a result of the addition of AITC to the chicken breast. Throughout storage, particularly at MIC-4, AITC showed the lowest numbers of _arobic mesophilic_ cells, as well as a reduction in _Listeria monocytogenes_ cell numbers and a decrease in _Salmonella_ Typhimurium counts. In addition, the meat containing MIC-4 did not exhibit growth of _Pseudomonas lundensis_ after 10 days. During the storage period, an electronic-nose assay demonstrated a distinction in the odor buildup of AITC across the various meat groups, and meat treated with MIC-4 showed a trend that was clearly opposite to that of untreated meat. These encouraging results demonstrate the potential of AITC to improve the safety and shelf life of meat and meat products.  
bioactive compounds; allyl-isothiocyanate; physicochemical characteristics; antimicrobial activity; antioxidant activity; poultry meat; shelf-life extension; refrigerated storage +
Footnote †: journal: Applied Sciences
## 3 Methods
### The AQM-PROBA Algorithm
#### 3.1.2 Multitemporal Compositing  
Pixel quality assessment is provided for the product 1-day Synthesis Products Top-Of-Canopy reflectance (S1 TOC). Bi-weekly composites of the second lowest NIR value of the time series were computed, with the chosen span of two weeks. Choice of this compositing approach is based on the results obtained by [55]. Multi-temporal image compositing is the creation of a synthesis image with inputs from different dates selected according to spectral criteria that minimize cloud contamination and evidence target land cover types. This approach is frequently used in burned area mapping [7; 11; 56].
## 3 Results and Discussion
### Physical Appearances of Collagen Hydrolysate before and after Sterilization
\begin{table}
\begin{tabular}{c c c c} \hline \hline Sample & \multicolumn{2}{c}{\(m/z\)} \\ \hline Non-sterile & \(782.671+1018.481+1148.572+1401.716+1449.716+1665.809+1878.857+\) & \% Difference from the control group \\  & \(1978.894+2205.031+2352.098=15.881.845\) & \\ \hline Beta & \(760.342+964.483+1185.552+1316.668+1401.731+1449.731+1557.805+\) & \(-0.987\%\) \\  & \(1665.823+1878.867+1978.904+2213.046+2352.113=15.725.065\) & \\ \hline Gamma & \(1018.512+1148.609+1316.703+1401.767+1449.779+1557.850+1665.887\) & \(+0.626\%\) \\  & \(+1878.936+1978.956+2213.088+2352.163=15.981.250\) & \\ \hline Ethylene oxide & \(964.469+1185.538+1316.658+1401.714+1449.710+1557.791+1665.804+\) & \(+0.118\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The sums of the \(m/z\) values of collagen hydrolysate before and after sterilization using various techniques. Figure 6: Mass spectra of the MALDI TOF mass spectrometry technique for examining the molecular weight of collagen hydrolysate before and after sterilization. sterilization methods are used, consideration should be given to reducing the radiation dosage to minimize impacts on molecular structure while being mindful of the potential reductions in antimicrobial efficacy. Further research into the relationship between radiation dosage and sterilization efficiency is crucial to determining an optimal balance. This study demonstrates that while sterilization methods do affect the molecular structure of collagen hydrolysate to some extent, these impacts are limited and may not significantly compromise the material's biological properties.
# Mobile Autonomous Sensing Unit (MASU): A Framework That Supports Distributed Pervasive Data Sensing
## 4 MASU Evaluation Using Simulations
### Simulation Results
#### 4.2.2 Considering Different Mobility Patterns  
In order to evaluate the impact of the units mobility patterns on framework performance we simulated nodes when there is no Control Tier available. Figure 10 shows the average presence of Producer considering the different network infrastructures and mobility patterns. RandomWalk and Nomadic mobility patterns achieve a similar percentage of presence of the Producer in AP and TZT networks, whereas Self-similar Least Action Walk (SLAW) achieves a slightly higher percentage. Nevertheless, the improvement achieved by the SLAW mobility pattern is not significant.  
Figure 10: Presence of the Producer for different mobility patterns when no Control Tier is available.  
Figure 9: Cost of the different role architectures of the Control Tier for different network architectures. (a) Fixed Centralized; (b) Dynamic Centralized; (c) Distributed.  
On the other hand, MANET networks achieve the maximum percentage, regardless of the mobility pattern. These results suggest that more realistic mobility patterns yield to higher presence of the Producer. This can be explained due to the fact that such patterns consider the social tendency of human interactions and therefore people's inclination to form groups.  
Then, we evaluated the performance of an ideal Control Tier as well as the average presence of Consumers for the different mobility patterns considered. Figure 11 shows that the presence of Consumers varies slightly across mobility patterns and network infrastructures. In addition, the performance of an ideal Control Tier in terms of presence of the Producer is similar for all mobility patterns in T2T and MANETs, while RandomWalk obtains slightly better results for AP networks. Thus, the variation in the results obtained for different mobility patterns are not significant.
# Study of Heat Distribution in Railway Switch Using Resistive Heater in Cold Climate Conditions
## 2 Materials and Methods
This instability is defined by a Courant-Friedrichs-Lewy (CFL) condition. As per this criteria, the terms (\(\alpha\)\(\Delta\mathrm{t}\)/(\(\Delta\mathrm{x}^{2}\)), \(\alpha\)\(\Delta\mathrm{t}\)/(\(\Delta\mathrm{y}^{2}\))) in the finite difference equations are limited by a maximum value (typically 1) [15]. For this study, the values of \(\alpha\), \(\Delta\mathrm{x}\), \(\Delta\mathrm{y}\), and \(\Delta\mathrm{t}\) were chosen so that the Courant number was about 0.1. The values for these parameters, initial/boundary conditions, and some other constants are given in Table 2.  
Natural convection was simulated for the air around the rail. For that purpose, the film temperature was calculated as an average of rail surface temperature and ambient air temperature. This film temperature was, in turn, used to calculate viscosity, Prandtl, and Rayleigh numbers, which give the value of convective heat transfer coefficient (h) at varying air temperatures. The rate of convective heat transfer is given by:  
\[\frac{\mathrm{d}\mathrm{T}}{\mathrm{d}\mathrm{t}}=\mathrm{h}\mathrm{A}( \mathrm{T}_{\mathrm{rs}}-\mathrm{T}_{\mathrm{amb}}) \tag{4}\]  
where \(\mathrm{T}_{\mathrm{rs}}\) is the temperature obtained from conduction over the rail surface. Figure 5 explains the analytical model algorithm. \begin{table}
\begin{tabular}{c c} \hline \hline  & **Constant Parameters** \\ \hline Diffusion Constant (\(\alpha\)) & 0.1 cm\({}^{2}\)s\({}^{-1}\) \\ Time Step (\(\Delta\mathrm{t}\)) & 1 s \\ Spatial Domain Step (\(\Delta\mathrm{x}\), \(\Delta\mathrm{y}\)) & (1 cm, 1 cm) \\ \hline \multicolumn{2}{c}{Initial Conditions} \\ \hline Metal Sheet Temp. & 268 K (\(-\)5 \({}^{\circ}\)C), 253 K (\(-\)20 \({}^{\circ}\)C) \\ \hline \multicolumn{2}{c}{Boundary Conditions} \\ \hline Ambient Air Temp. (all 4 sides) & 268 K (\(-\)5 \({}^{\circ}\)C) \\ \hline \multicolumn{2}{c}{Other Constants} \\ \hline Heater Temp. & 110 K (383 \({}^{\circ}\)C) \\ Heater Turn ON Instant & From t = 5 s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Values of parameters for heat transfer study over a rail surface using the finite difference method.