esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Works  
Numerous works have been published in the scientific literature investigating the advantages of using 5G for smart grid communications. Examples include the works in [13; 14; 15]. Improving communications and application performance with Multi-access Edge Computing (MEC) provides the advantage of more reliable systems with higher fault tolerance and better end-user experience. Such efforts focus particularly on protocols with low-latency requirements, such as IEC-61850 GOOSE. The authors of [16] encapsulated GOOSE packets for transmission over a virtualized 5G core in a Non-Stand-Alone (NSA) configuration and reported the simulated delay of a virtual network. Latency measurements were also reported for R-GOOSE in [17], which utilized a testbed with both 4G and 5G subscriptions through a Finnish cellular service provider. The whole suite of protocols in IEC-61850 was encapsulated into UDP and TCP packets in [18], showing promising results for the latency of these protocols operating over cellular services. The GOOSE protocol's performance has been measured in a Hardware-In-the-Loop (HIL) simulator, targeting a physical IED's response time to virtual IED faults over a simulated 5G network [19]. The authors of [20] investigated the capabilities and constraints encountered when utilizing the IEC-61850 protocol suite for protection systems communicating over 5G. All of these results show promise for GOOSE communications between substations over wide geographical areas. However, none of these reviews investigated the specific latency effects of replacing standard GOOSE communication within a substation with a 5G wireless approach while maintaining GOOSE's strict latency requirements.  
Modbus has also been studied over a 5G network for additional industrial applications. For example, the authors of [21] utilized a Raspberry Pi as a protocol gateway for a TCP-to-5G conversion. Additionally, 5G has been utilized for other smart grid applications. The authors of [22] proposed using an IOT gateway that communicates with a controller server utilizing 5G and translates decisions made by the server into Modbus protocol messages. In [23], the authors utilized a 5G network to communicate with a server external to a smart grid, which uses a neural network to detect attacks on the Modbus TCP/IP protocol. However, less research has been directed toward the transition of the DNP3 protocol. In [24], the authors suggested a neural network for \"artifact for security in 5G\", which improves the security of common attacks in multiple OT protocols. The authors of [25] provided an overview of the potential challenges in moving critical infrastructure communication to 5G, including for DNP3. These reviews investigated improving the security of Modbus and DNP3 without investigating the operational impact of using 5G as a transportation method.
# Skin-Compatible Amorphous Oxide Thin-Film-Transistors with a Stress-Released Elastic Architecture
## 3 Results and Discussion
Figure 2: Micrograph images of fabricated stretchable _a_-IGZO TFTs. (**a**) An SEM image for edge of reverse-trapezoid structure. (**b**) An image of fully fabricated stretchable _a_-IGZO TFTs on the reverse-trapezoid structure. TFTs on a reverse-trapezoid PDMS had an average saturation mobility of 4.77 cm\({}^{2}\) V\({}^{-1}\)s\({}^{-1}\) and threshold voltage of \(-1.3\) V. After fully transferring to the PDMS, the variation of saturation mobility was less than 4%, and negligible changes of threshold voltage were observed for both _a_-IGZO TFTs on conventional and reverse-trapezoid structures. Therefore, it can be suggested that the mechanical transference technique and the O\({}_{2}\) plasma treatment barely affected the electrical performance, possibly assisted by the top-gate, bottom-contact, and self-passivated structure of the device. As shown in Figure 4a, the _a_-IGZO TFTs showed proper switching behaviors with an on/off ratio of \(>\)10\({}^{8}\) under 15% strain. The stretchable _a_-IGZO TFTs on conventional PDMS showed a variation of \(>\)10% for both saturation mobility and threshold voltage even under 1% strain, as shown in Figure 4b,c and Figure S3. On the contrary, the _a_-IGZO TFTs on the reverse-trapezoid PDMS showed about 5% variation of saturation mobility and threshold voltage under 10% strain. These variations in the electrical properties might be related to the generation of oxygen vacancy in _a_-IGZO thin-films by the mechanical stress, leading to a negative threshold voltage shift and increased saturation mobility of _a_-IGZO TFTs [25; 26; 27]. Although the electrical changes abruptly increased over 10% under 15% strain, importantly, the stretchable _a_-IGZO TFTs on the reverse-trapezoid PDMS exhibited appropriate operation as switching devices to realize stretchable TFT-based skin-compatible applications. Figure 4: Electrical characteristics of stretchable _a_-IGZO TFTs on conventional and reverse-trapezoid PDMS. (**a**) Transfer characteristics of stretchable _a_-IGZO TFTs under a 15% strain. Variation of normalized (**b**) saturation mobility and (**c**) threshold voltage of stretchable _a_-IGZO TFTs on a conventional and a reverse-trapezoid PDMS as a function of strain. Figure 3: Effects of substrate types on the electrical properties of _a_-IGZO TFTs. (**a**) Transfer characteristics, (**b**) the saturation mobility and threshold voltage of _a_-IGZO TFTs on various substrates.
# Intelligent Thermal Comfort Controlling System for Buildings Based on IoT and AI
## 3 Material and Methods  
### Theory  
This chapter introduces a building intelligent thermal comfort control system based on the Internet of Things. The system contains sensors, controllers, and other IoT devices, and data is collected and analyzed by intelligent algorithms. By using BP neural network algorithm and fitting, the relationship between the actual comfort temperature of the occupants and input/output variables such as PMV is established. Then, the system optimizes and controls the indoor thermal environment. Figure 4 below outlines the process of the system.  
Figure 4: System Working Mode Schematic Diagram.  
**Step 1**: First use the temperature and humidity detection system to collect data over a period of time, including air temperature (Ta), average radiant temperature (Tr), air velocity (Va), relative humidity (HR), metabolic rate (met), and Clothing situation (clo);  
**Step 2**: Use the data collected in step 1 to obtain PMV values through the Fanger method, and use BP neural network to establish a multivariate logical relationship;  
**Step 3**: Use statistics and analysis methods to establish the relationship between the optimal comfort temperature of the occupants and the PMV value during that period;  
**Step 4**: Predict the trend of the temperature, humidity, wind speed, and PMV value in the room over the next period, and adjust the parameters of each controller to complete the goal of the indoor thermal comfort;  
**Step 5**: Predict the optimal comfort temperature for room occupants over the next period. And compare with the real measurement value.  
**Step 6**: Collect feedback from users to see if they reach the optimal comfort temperature. Finally, it achieves intelligent control of building thermal comfort system.
## 3 System Design
### Torsion Pendulum Facility  
The torsion pendulum designed by Changchun Institute of Optics, Fine Mechanics, and Physics, Chinese Academy of Science (CIOMP) is depicted in Figure 9a. It consists of a precision adjustment unit, a vacuum system, a sensitive structure, a suspension mechanism, and a bracket. A suspension wire with a low stiffness in the torsion direction is used to mitigate the impact of the Earth's gravity. Thereby, the horizontal direction displacement measurement and static control of the TM can be achieved.  
The precise alignment between the TM and the EH is implemented by the precision adjustment unit, which consists of a two-level tilt adjustment mechanism and a two-dimensional translation mechanism. The second-level tilting mechanism adopts a classic three-point adjustment structure for coarse adjustment. The differential heads (NewPort-AJS) has a resolution of 25 \(\upmu\)rad. The first-level tilting stage with an adjustment resolution less than 5 \(\upmu\)rad is used for fine adjustment. In order to accurately control the gap between the TM and the electrodes, we design a two-dimensional motion mechanism without kinematic coupling, which has flexible adjustment space. As shown in Figure 9b, the two-dimensional motion mechanism is driven by four differential micrometer heads. The displacement resolution of the flexible hinges is less than 1 \(\upmu\)m.  
The vacuum maintenance system consists of a vacuum chamber, an ion pump, a vacuum gauge, and an external pump set, which is used to maintain the vacuum of the system and reduce the influence of gas noise during the test. The vacuum cavity is evacuated to a high-vacuum state of about \(4\times 10^{-5}\) Pa by combining an external mechanical pump and a molecular pump, and then the vacuum is maintained by an ion pump. A vacuum gauge displays the air pressure in real-time.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Bias Voltage V\({}_{p}\) & 5 V \\ Effective value of sensing voltage V\({}_{d}\) & 4 V \\ Frequency of sensing voltage & 100 kHz \\ Peak of feedback voltage & \(\pm\)10 V \\ \hline \hline \end{tabular}
\end{table}
Table 3: Circuit parameter list.  
Figure 9: Schematic of the torsion pendulum facility. (**a**) The main components of the torsion pendulum facility; (**b**) Two-dimensional space non-coupling motion mechanism.  
In the suspension system, the base of the vacuum chamber is fixed on the motion mechanism, the EH is placed on the base, and the TM is suspended in the middle of the EH by a 0.55 m long tungsten wire with a diameter of 50 \(\upmu\)m and a purity of 99.5%. One side of the suspension wire is connected to the Z-plane of the TM through a wire fixture. Since the direction of the suspension wire must exactly pass through the centroid of the TM, the entire connection is performed through the CMM. Release the tungsten wire stress and adjust the angle between the TM and the EH by a rotating mechanism.
# Optimization of Redundant Degrees of Freedom in Robotic Flat-End Milling Based on Dynamic Response
## 3 Milling Experimental Validation
### Analysis of Milling Stability with Redundant Angles  
To assess the chatter stability at different redundancy angles, we selected reference points #2, #6, #10, and #14 along feed directions, as shown in Figure 4. The corresponding coordinates and cutting parameters are detailed in Table 2. The joint angles corresponding to these points can be found in Table 1.  
Due to practical physical constraints, the redundant angle \(\gamma\) is in the range of \([-45^{\circ},45^{\circ}]\). In this section, the redundant angle \(\gamma\) is set to the specific values of \(-30^{\circ}\), \(0^{\circ}\), and \(30^{\circ}\) for comparison. The modal tests indicate minimal changes in modal parameters on the upper surface due to the small size of the workpiece. Consequently, the robot maintains a fixed posture while milling each slot.  
Figure 7 illustrates the distinct effects of different redundant angles on the milling stability at the same reference point. This suggests that the choice of the redundant angle can influence the stability of the milling process. The results indicate considerable variation in the cutting depth limit across different reference points, highlighting the substantial impact of robot posture on machining stability. Therefore, avoiding chatter is crucial to ensure an optimal posture.  
Furthermore, an accelerometer is utilized to measure the vibration signal, and Fourier transform is applied to obtain the frequency spectrogram, allowing the identification of chatter occurrence during the machining process. The examination of the spectrogram focuses on the increase in amplitude associated with the main mode (flutter frequency). Figure 8 illustrates the acceleration spectrum diagram at different redundancy angles.  
Figure 7: Stability lobes of different redundant angles for different points: (**a**) Point #2, (**b**) Point #6, (**c**) Point #10, and (**d**) Point #14.  
Given the use of a three-tooth cutting tool in the experiment, the milling force frequency was approximately 250 Hz when the spindle speed was 5000 r/min. The results indicate that at a milling depth of 1.0 mm, the dominant frequency in the \(x\), \(y\), and \(z\) directions is roughly 250 Hz. The experiment did not exhibit any jitter or harsh sounds, and the spectrum diagram indicates that no other frequency with rising amplitude appeared except for the larger amplitude at the conversion frequency. Thus, the experimental observations of chatter align with the theoretical calculations, confirming stability in the machining process at this posture. These findings highlight the impact of the redundant angle of the milling robot on machining stability.
###### Abstract  
The study presents an analysis of the concentrations of polycyclic aromatic hydrocarbons (PAHs) and particulate matter with a diameter of less than 10 \(\upmu\)m (PM\({}_{10}\)) in the air across various locations, as well as their impact on human health. Research in this area was conducted at eight stations as part of the national environmental monitoring system run in Poland by the Chief Inspectorate for Environmental Protection. Daily measurement data of PM\({}_{10}\) and the concentrations of PAHs associated with these particles were analyzed for the period from January to December 2023. The results showed that pollutant concentrations in the atmosphere vary depending on location, season, and meteorological conditions. The highest concentrations were observed during the winter season, when the combustion of solid fuels increases, while the lowest concentrations were recorded in the summer. The total concentration of PAHs ranged from 0.35 to 34.50 ng/m\({}^{3}\). The annual average concentration of PM\({}_{10}\) at the analyzed stations was 19.29 \(\pm\) 3.01 \(\upmu\)g/m\({}^{3}\). Principal component analysis indicated that PAHs in the air primarily originate from emissions related to transportation, biomass combustion, and industry. Furthermore, the estimated health risk, considering the Incremental Lifetime Cancer Risk (ILCR) index, showed that the risk of cancer associated with inhaling PAHs by children and adults did not exceed the permissible limits. The main contributor to the total carcinogenic activity of the PAH mixture was benzo(b)fluorantene (BBF) (31.5%), followed by benzo(a)pyrene (BaP) (5.5%), indeno(1,2,3-cd)pyrene (IP) (18.2%), benzo(j)fluorantene (BJF) (12.9%), benzo(k)fluorantene (BKF) (8.5%), benzo(a)anthracene (BaA) (2.5%), and dibenzo(a,h)anthracene (DBahA) (1.0%).  
air pollution; PAHs; PM\({}_{10}\); risk assessment; environmental pollutants 2020 IEEE/Mechanical Engineering Conference on Communications and Control, IEEE, 2015, pp. 1-5.
## 3 Analysis and Discussion of Test Results
### Validation of the Model  
The pre-capillary water absorption of 150 freeze-thaw cycles was substituted into the above model, and the calculated and measured values of the prediction model of the pre-capillary water absorption of recycled concrete at 150 freeze-thaw cycles were obtained to verify the accuracy of the above pre-capillary water absorption model. As shown in Figure 10, the difference between the measured and calculated values of capillary water absorption in freeze-thaw specimens in different media is small, and the mean values of the ratio between the measured and calculated values are 1.002196, 1.004881, and 0.989241, respectively, with standard deviations of 0.014466, 0.004166, and 0.006897, indicating that the calculated and measured values of the model have small errors and high fitting accuracy. Thus, they can be used as an experimental control for the capillary water absorption of modified recycled concrete under freezing and thawing cycles in different media.  
\begin{table}
\begin{tabular}{c c c} \hline
**Number** & **Predictive Models** & **R2** \\ \hline RAC & y = (7.942 \(\times\) 10\({}^{-5}\)) x \({}^{2}\) + 0.02329x + 4.544 & 0.997 \\ WRAC & y = (6.317 \(\times\) 10\({}^{-5}\)) x \({}^{2}\) + 0.01867x + 4.353 & 0.997 \\ GRAC & y = (6.991 \(\times\) 10\({}^{-5}\)) x \({}^{2}\) + 0.01146x + 4.335 & 0.993 \\ WGRAC & y = (5.2 \(\times\) 10\({}^{-6}\)) x \({}^{2}\) + 0.0153x + 4.025 & 0.964 \\ \hline \end{tabular}
\end{table}
Table 12: Freeze–thaw initial capillary water absorption prediction model for chloride salt medium.  
Figure 10: (**a**) Freshwater freeze-thaw cycle (**b**) Sulfate freeze-thaw cycle (**c**) Chlorine salt freeze-thaw cycle.  
Figure 9: (**a**) clear water medium; (**b**) sulfate medium; (**c**) chloride salt medium.
# Impact of Environmental Factors on Passenger Ride Comfort
## 2 Ride Comfort Factors  
The factors that affect the level of ride comfort can be divided into groups of environmental factors and factors directly related to the individual [1]. The first group includes mechanical vibrations, noise levels, and light intensity, as well as air pressure and air quality (CO\({}_{2}\) concentration) [2]. In addition, the conditions of the thermal environment, such as temperature and the asymmetry of temperature distribution inside the vehicle, relative humidity, and air velocity, are important for passenger comfort. The intensity of the above-mentioned factors and the duration of exposure to them and the combinations in which they occur are also important.  
Among environmental factors, there are also those directly related to the vehicle interior. Of particular importance is the ergonomics of the seat, which includes its size, the possibility to adjust the angle of the backrest and headrest, and the presence of armrests [3]. In addition, especially with regard to public transport, factors such as the amount of legroom, the level of congestion in the vehicle, the cleanliness of the interior, the availability of toilets, and efficient air-conditioning and ventilation systems should be mentioned [4]. Also important for ride comfort is the provision of access to understandable passenger information, both visual and vocal.  
Passengers' sensitivity to individual environmental stimuli varies. The perceived level of comfort is related to a second group of factors that relate directly to the individual. This group includes the gender, weight, age, and height of the passenger, their psycho-physical condition, their health status, and the position occupied. In addition, previous travel experiences and attitudes, the availability of the means of transport at the desired place and time, and punctuality are important [5]. All the above-mentioned factors result in different perceptions of ride comfort between passengers. Figure 1 presents the key factors of ride comfort.  
Ride comfort is therefore a complex and highly subjective concept. An unambiguous and direct assessment carried out in a quantitative manner is therefore much more difficult. Different approaches have been proposed by various authors in the literature. Most often, studies on ride comfort are based on measurements of physical quantities characterising one or more selected environmental factors. Researchers also apply survey-based approaches. Whatever the method used to assess ride comfort, the key is to isolate the factors that are dominant and relevant from the passenger's point of view. Too few or too many criteria can lead to a misleading assessment. In addition, due to different operating conditions or the distance covered by different modes of transport, the selection of factors should be considered separately for each situation.
# Cybersecurity of Microgrid: State-of-the-Art Review and Possible Directions of Future Research
## 3 The Cybersecurity Aspects of Microgrid
### Efforts and Initiatives for Smart Grid and Microgrid Security
It also provides authentication and authorisation services in the application layer. Deploying IPv6-based networks leads to several gaps in security. If IPv6 and IPv4 are run simultaneously, IPv6 should be tunnelled over IPv4 or run independently. In the tunnelling mode, configuration problems can create security holes in the system [52]. If the two protocols are run in parallel, firewalls must be configured to filter IPv6 traffic, which isnot very common. A typical firewall does not filter IPv6 traffic, and an attacker can leverage this unsecured channel to enter the system. Administrators must also use new (and better) ways to deploy, configure, and monitor networks. Essential tasks include troubleshooting networks, configuring firewalls, enforcing secure configurations, monitoring security logs, analysing real-time behaviour, and performing network audits. Most intrusion detection/prevention systems are still not very effective at handling IPv6 traffic, which increases the potential for attacks. CERTSMicroGrid is a novel approach for integrating distributed energy resources in a microgrid to seamlessly island it from and them reconnect them to the power grid [60]. All distributed energy resources appear to be a single entity for coordination and control to the control centre. The traditional method involves integrating a small number of distributed energy sources and shut down the microgrid when problems arise (according to the IEEE P1547 standard). However, unlike the SNAPE architecture, the CERTS model does not explicitly focus on the cybersecurity of microgrids. The Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS) project was conducted by the US Department of Energy, Department of Defense, and Department of Homeland Security [61]. The goal was to provide secure control of on-base generation at military bases by building secure and robust microgrids that incorporate renewable energy sources. [PERSON] [62] has discussed research undertaken according to the NSF ERC FREEDM project. The project has investigated challenges posed by the cyber-physical nature of microgrids, and has highlighted novel opportunities for providing selective power delivery during power outages. [PERSON] recognises the need to secure microgrids from cyberattacks. However, the FREEDM Project does not propose any security solutions. SNAPE stands out because it recognises the need to secure microgrids and presents a comprehensive cybersecurity architecture that adheres to industry standards, and satisfies the requirements of the microgrid.
## 5 Results and Discussion
### Aluminosilicate Glasses  
The experimental and the calculated longitudinal and transversal ultrasonic velocities and the elastic properties of the aluminosilicate glasses investigated in [30] are summarized in Table 4. Also, in this case, the first row for each glass composition corresponds to the experimental results, while the second row represents the corresponding calculated value after the simulation procedure. From Table 4, it is obvious that the longitudinal and transversal elastic constants, the Young's modulus, and the bulk modulus are higher in aluminosilicate glasses relative to that of pure SiO\({}_{2}\) glass. This behavior can be explained considering that the structure of the aluminosilicate glasses is characterized by a high network rigidity. The 15 La\({}_{2}\)O\({}_{3}\)\(\rightarrow\)\(\mathrm{Al}_{2}\)O\({}_{3}\)\(\rightarrow\)(85-x)SiO\({}_{2}\) glasses reveal an increase in the elastic moduli with Al\({}_{2}\)O\({}_{3}\) content. On the contrary, the elastic moduli of the 25 La\({}_{2}\)O\({}_{3}\)-yAl\({}_{2}\)O\({}_{3}\)-(75-y)SiO\({}_{2}\) glasses exhibit a completely different behavior with varying the Al\({}_{2}\)O\({}_{3}\) content. The addition of lanthanum ions in the structure affects the coordination number of Al\({}^{3+}\), which is evidenced experimentally [30] and references therein. Indeed, Al\({}^{3+}\) ions are five-fold and six-fold coordinated in the structure of these glasses.