esa-sceva/satcom-chunk-collection huggingface dataset:
# Evolution Model of Coal Failure Using Energy Dissipation under Cyclic Loading/Unloading
## 4 Analysis and Discussion
### Evolution Law of Coal Dissipated Energy  
#### 4.3.1 Verification of Evolution Law of Coal Dissipated Energy  
Some scholars have considerably studied the stress-strain relationship and the strength characteristics of the material from the perspective of mechanics [30; 31; 32]. However, the stress-strain relationship cannot fully describe the failure processes of rocks. The stress-strain  
Figure 10: Elastic energy–dissipation energy tangent factor curve of coal under graded cyclic loading/unloading.  
Figure 9: Schematic diagram of energy growth rate calculation of coal failure.  
curves of rocks may be almost the same, but show different failure patterns and energy release characteristics [33]. From the perspective of thermodynamics, energy dissipation and release are the essence of rock deformation and destruction, which constitute an irreversible process [8]. Therefore, strengthening the research of energy dissipation characteristics can better verify the evolution law of coal rock damage.  
According to the analysis in Section 3.2 above, the energy consumption ratio of coal was characterized by a sharp increase. Therefore, based on experimental research, a cusp mutation model of the coal failure process was constructed using the catastrophe theory [34; 35], and the theoretical derivation of the evolution law of dissipated energy was obtained.  
During the cyclic loading-unloading process, the dissipated energy of the coal accumulated gradually. Its dissipative energy state can be represented by \(U_{d}=f(\varepsilon)\), which can be expanded by the Taylor series:  
\[U_{d}(\varepsilon)=a_{0}+a_{1}\;\varepsilon+a_{2}\;\varepsilon^{2}+a_{3}\; \varepsilon^{3}+\cdots+a_{m}\;\varepsilon^{m} \tag{3}\]  
According to Equation (3), the first five items are taken to construct the cusp mutation model:  
\[U_{d}(\varepsilon)=a_{0}+a_{1}\;\varepsilon+a_{2}\;\varepsilon^{2}+a_{3}\; \varepsilon^{3}+a_{4}\;\varepsilon^{4} \tag{4}\]  
Set \(\varepsilon=x-n\); since the state variable \(x\) is still a function of the time \(\varepsilon\) in the cusp mutation model, so  
\[U_{d}(x)=b_{0}+b_{1}x+b_{2}x^{2}+b_{3}x^{3}+b_{4}x^{4} \tag{5}\]  
In the formula:  
\[\begin{pmatrix}b_{0}\\ b_{1}\\ b_{2}\\ b_{3}\\ b_{4}\end{pmatrix}=\begin{pmatrix}n^{4}&-n^{3}&n^{2}&-n&1\\ -4n^{3}&3n^{2}&-2n&1&0\\ 6n^{2}&-3n&1&0&0\\ 1&-3n&1&0&-3n\\ 1&0&1&0&0\end{pmatrix}\begin{pmatrix}a_{4}\\ a_{3}\\ a_{2}\\ a_{1}\\ a_{0}\end{pmatrix}\]  
If \(b_{3}=0\), that is, \(a_{3}-4 na_{4}=0\), then \(n=\frac{a_{3}}{4a_{4}}\).  
Make \(U_{d}(x)=\frac{U_{d}(x)}{4b_{4}}\), \(p=\frac{b_{2}}{2b_{4}}\), \(q=\frac{b_{1}}{4b_{4}}\), and \(c=\frac{b_{0}}{4b_{4}}\); then, we obtain:  
\[U_{d}(x)=\frac{1}{4}x^{4}+\frac{1}{2}px^{2}+qx+c \tag{6}\]  
According to the mutation theory, Equation (7) satisfies the basic form of the mutation function. This is consistent with the abrupt growth of dissipated energy in the process of coal failure. Therefore, the evolution law of dissipated energy can be used as the judgment basis for the precursor characteristics of the coal fracture.
# Deformation and Stress Analysis of Pile-Supported Immersed Tunnels under Seismic Loads
## 4 Parametric Analysis  
### Effects of the Seawater Depth  
#### 4.1.1 Peak Stresses in the Top and Bottom Plates of the Tunnel  
The stress changes after an earthquake are very important for immersed tunnel design. Figure 8 shows the maximum principal stress distribution of the tunnel bottom plate (a) and top plate (b) under seismic loads. Under seawater pressure and seismic loads, the stress curves of the top plate and bottom plate are saddle-shaped. From Figure 8, it can be seen that stress concentration occurs on both sides of the top and bottom plates of the tunnel. With the increase in seawater depth, the maximum principal stresses of the tunnel bottom and top plates show an increasing trend of decreasing growth rate. This indicates that the seawater depth has a suppression effect on the vertical frequency of the tunnel [53].  
Figure 7: (**a**–**c**) settlement of the piled foundation, (**d**) acceleration amplitude of the tunnel.  
With the increase in the replacement rate of the piled foundation, the stress peaks of the top and bottom plates are shifted toward the wave source direction, and the shift angle in the middle is about twice the shift angle of the left and right sides (\(\theta_{1}=2\theta_{2}\)), as shown in Figure 8a.  
The maximum principal stresses in the top plate of the tunnel are always greater than those in the bottom plate. It can be seen that the effect of seismic loads on the bottom plate is greater than on the top plate. The difference between the two maximum principal stresses is due to the damping effect of the \"H-shaped\" structure of the tunnel. In addition, the maximum principal stresses in the top and bottom plates at a 50% replacement rate are smaller than the maximum principal stresses at 37% and 62% replacement rates.
## 4 Result and Analysis  
In this section, we present the results of the classification models applied to the network intrusion detection dataset and evaluate their performance in terms of accuracy, F-measure, and training time. We start by detailing the overall performance metrics achieved by each model, offering a comprehensive overview of how well they classified network traffic as either normal or malicious. Accuracy serves as a key metric, indicating the proportion of correctly classified instances out of the total dataset. Specific accuracy scores for each model will be provided, emphasizing those that performed exceptionally well and discussing any patterns observed across the different algorithms.  
F-measure, also known as the F1 score, is another critical evaluation metric that balances precision and recall. It is especially relevant in this context, where detecting malicious activities (true positives) while minimizing false positives is crucial. We will compare the F-measure scores of the models to identify which ones strike the optimal balance between precision and recall. Additionally, we will discuss the training time for each model, an important consideration in practical applications. Longer training times can be a significant disadvantage, particularly in environments that require real-time or near-real-time intrusion detection.  
By evaluating training times alongside accuracy and F-measure, we can gain valuable insights into the efficiency and feasibility of deploying each model in real-world scenarios. This analysis aims to identify the strengths and limitations of each classification approach, offering guidance on selecting the most appropriate model for network intrusion detection tasks.
Marginal Adaptation and Porosity of a Novel MTA Brand Applied as Root-End Filling Material: A Micro-CT Study  
[PERSON]  
developed and brought into the dental market in recent years in an effort to overcome these shortcomings. They are referred to as bioceramics, and it is believed that they have superior characteristics to conventional MTA products [6; 7].  
One of the latest restorative brands of this group of biomaterials is Harvard MTA Universal. This repair cement is commercially available as a hand-mix formula or in predosed capsules. The manufacturer claims that this MTA-based material is biocompatible, possesses outstanding physical properties, and does not require moisture during the setting process, allowing for the following clinical step to be completed after 5 min [8]. However, only limited scientific evidence has been reported in the literature considering its properties to date. The chemical composition of Harvard MTA was determined by X-ray powder diffraction analysis, which indicated the presence of two distinct forms of calcium silicates in its formulation: 75 wt% merwinite and 20 wt% harturite, and 5 wt% bismuth oxide as a radiopacifier. In contrast, harturite constitutes 90 wt% of the mineral composition in ProRoot MTA plus 10 wt% bismuth oxide [9].  
When compared to ProRoot MTA, Harvard MTA Universal showed a significantly higher pH value (12.5) and a lower solubility (0.32%) in phosphate-buffered saline solution; however, after a 14-day period of storage, it exhibited significantly lower calcium ion release values [9]. The cement showed a much lower push-out bond strength than Biodentine in terms of its dislodgement resistance, although there was no statistically meaningful difference with ProRoot MTA [10; 11]. As for its biological properties, it was found that ProRoot MTA and MTA Flow showed better biocompatibility than Harvard MTA [12].  
As can be seen from this brief review of the available literature, the properties of Harvard MTA have not yet been thoroughly investigated. There are almost no studies on the sealing capacity of this new MTA brand, and its marginal adaptation, in particular, has not been investigated volumetrically so far. In light of the paucity of scientific evidence on this topic, the present study was designed to quantitatively assess the marginal adaptability and interior microporosity of this innovative biomaterial applied as root-end filling material using three-dimensional micro-computed tomography (micro-CT) analysis.
## 3 Results and Discussion
### Temporally Resolved Spectra of LS-APPJ  
The temporally resolved OES of N\({}_{2}\) (C\({}^{3}\Pi\)\({}_{\rm u}\)\(\rightarrow\) B\({}^{3}\Pi\)\({}_{\rm g}\)) is measured when an ICCD is employed as the spectrometry detector. Figure 9 shows the dynamic evolution of N\({}_{2}\) (C\({}^{3}\Pi\)\({}_{\rm u}\)\(\rightarrow\) B\({}^{3}\Pi\)\({}_{\rm g}\)) at various distances from the jet nozzle for the discharges in both the positive pulse and negative pulse of the BPPJ. The gate width of the ICCD is set at 5 ns and the pulse peak voltage, pulse repetition rate, and gas flow rate are kept at 24 kV, 150 Hz, and 3.5 L/min, respectively. It is clearly shown that the N\({}_{2}\) (C\({}^{3}\Pi\)\({}_{\rm u}\)\(\rightarrow\) B\({}^{3}\Pi\)\({}_{\rm g}\)) emission exhibits different behaviors in the discharges during the positive half-cycle and negative half-cycle. In the positive discharges, the temporally resolved OES of N\({}_{2}\) (C\({}^{3}\Pi\)\({}_{\rm u}\)\(\rightarrow\) B\({}^{3}\Pi\)\({}_{\rm g}\)) can be observed over a much larger distance from the jet nozzle, which is about 10-15 cm. Near the plasma jet nozzle, the emission intensity increases sharply as the \"plasma bullet\" moves away from the nozzle, and it reaches the maximum at the distance of 3 cm, which is owing to the increase in the N\({}_{2}\) concentration. As the distance increases, the discharge is dominated by the secondary discharge ignition, where the discharge can be sustained after the pulse voltage extinguishes. Additionally, the relaxation time of the plasma can be influenced by the distance. The full width at half maximum (FWHM) of the N\({}_{2}\) (C\({}^{3}\Pi\)\({}_{\rm u}\)\(\rightarrow\) B\({}^{3}\Pi\)\({}_{\rm g}\)) emission intensity is only about 100 ns at the distance of 3 cm; however, it is about 500 ns at the distance of 12 cm. However, in the negative pulse, the movement of the \"plasma bullet\" is significantly lower than that in the positive pulse discharge. The FWHM of the N\({}_{2}\) (C\({}^{3}\Pi\)\({}_{\rm u}\)\(\rightarrow\) B\({}^{3}\Pi\)\({}_{\rm g}\)) emission intensity is larger than 1000 ns, and the signal can only be detected in the range of 0-6 cm, far from the jet nozzle.
# Biomotor Abilities for Law Enforcement Officer Readiness
## 3 Results
#### Fitness and Occupational Abilities Measures  
Regarding the frequency of evaluation, muscular strength was assessed in 9 articles [16; 17; 18; 19; 22; 23; 28; 29; 31], muscular endurance was measured in 17 articles [15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 31], muscular power was measured in 13 articles [15; 16; 17; 18; 19; 22; 23; 24; 25; 27; 28; 29; 30; 31]. Other fitness measurements included aerobic capacity, assessed in 7 articles [16; 18; 19; 20; 28; 30; 31] and anaerobic capacity in 4 articles [16; 18; 19; 30]. Agility was assessed in 9 [15; 16; 18; 19; 22; 28; 29; 31] articles, and the least commonly reported fitness measure was flexibility, which was assessed in 6 articles [15; 16; 19; 22; 29; 31]. The most common biomotor abilities associated with occupational task performance included relative aerobic capacity, muscular strength, and agility (Table 3). Secondarily, muscular endurance, absolute aerobic capacity, and power were found to be related to occupational task performance. Those studies evaluated anaerobic capacity and flexibility less frequently and unrelated to occupational task performance. There was considerable variability in the task composition and application of the occupational physical ability assessments. For instance, some studies utilised exercises that simulate occupational tasks like running and pushing objects to simulate foot chases and suspect engagement. Most studies included the victim rescue/body drag [19; 22; 23; 26; 29; 31] and foot pursuit [19; 22; 24; 25; 31]. The 99-yard obstacle course [23; 26; 27], chain link fence [19; 23; 26; 29; 31], solid wall climb [21; 22; 23; 27; 28; 29; 31], and 500-yard run [23; 26; 27] were used less frequently. The application of the test battery also varied between studies, with most studies requiring completion of the occupational physical ability assessment on a separate day from fitness assessments. Ten of the studies completed occupational physical ability and fitness assessments on the same day [17; 19; 22; 23; 24; 25; 26; 29; 31], whereas the remaining seven studies completed each testing battery on different days [15; 16; 18; 20; 27; 28; 30]. In addition, some physical ability assessments required multiple occupational tasks to be completed continuously, whereas others allowed for recovery between tasks. This could be important for further studies as performing various tasks in succession (especially high-intensity, short-duration tasks) generally correlates with aerobic endurance. To encapsulate the critical findings of our systematic review and to directly address the aim of identifying key biomotor abilities essential for law enforcement officers' occupational performance, Table 5 below provides a concise summary of these abilities, along with their evaluation frequency, correlation strength, and relevance to specific occupational tasks.
# Securing Smart Grid Enabled Home Area Networks with Retro-Reflective Visible Light Communication
## 2 Methodology
### Heterogeneous Retro-VLC and WLAN System  
In the proposed heterogeneous Retro-VLC and WLAN system (Figure 4), each smart appliance or IoT sensor (denoted as host) in a smart-grid-enabled HAN is equipped with a hybrid network adapter, which enables a two-way communication between the device and the HAN gateway through two different wireless access technologies. The idea of connecting a client to the AP through two different channels originates from the concept of channel aggregation [16] (i.e., binding the two squares in Figure 4). This can be implemented on different layers of the OSI reference model, ranging from the data link layer to the application layer. Relying on higher layers requires considerable modifications at both the client and server sides, which prohibits large-scale deployment. On the other hand, lower layer channel aggregation can be implemented only at the client side with some adaptive changes at higher layers. In our heterogeneous testbed (Section 2.3.2), socket programming is adopted to gain complete control of the data link layer for packet-type-based link selection.  
The architecture of the heterogeneous system consists of a Retro-VLC tag, a photodetector, and a WiFi transceiver on the host side, as well as a light source with a embedded PD, and a WiFi transceiver on the gateway side. The full-duplex VLC link is asymmetric, i.e., traditional VLC [13] is used to send downlink data from the gateway to the host and Retro-VLC is used to send uplink data from the host to the gateway. Retro-VLC uplink  
Figure 4: Architecture of heterogeneous Retro-VLC and WLAN system.  
significantly reduces the interception range (experimentally evaluated in Section 3.3 and also provides several unique advantages, e.g., highly directional communication with narrow beam for reduced interference, dense spatial multiplexing for enhanced spectral efficiency, self-alignment for reliable connectivity, and \(\mu\)W power consumption for ultra-low power applications [17; 18; 19]. Nevertheless, the state-of-the-art optical modulator (i.e., liquid crystal shutter) has a limited modulation bandwidth which results in throughput up to several kbps [20]. Therefore, we consider the Retro-VLC uplink suitable for low-volume and sensitive data exchange. In Section 3.2, we experimentally study the key-exchange latency of the asymmetric VLC link.
# Analysis and Design of Integrated Blocks for a 6.25 GHz Spacefibre PLL
## 3 Transistor Level Design of the PLL
### Charge Pump and Phase/Frequency Detector
#### 3.1.4 PFD/CP Layout  
The CP's layout is shown in Figure 15. The output mirrors, since their slaves are composed of two MOS in parallel, are interleaved with the master transistor to enhance the technology process matching. Moreover, every mirror and the switch transistors are surrounded by guard rings connected to the voltage supply. These rings have two main functions:  
1. They reduce the possibility of SEL (Single Event Latch-Up) and Latch-Up in general;
2. They reduce the drift current generated after an SEE in the sensitive nodes near the hit node [22].  
Regarding the PFD, as for the CP, guard rings have been placed around the transistor to avoid latch-up and to reduce the drift current deriving from an SEE. Moreover, the triplicated cells have been placed at a distance of 10 \(\upmu\)m from each other to avoid MBUs (Multi Bit Upsets). The TMR technique would become useless if an SEE causes an SEU (Single Event Upset) in more than one PFD each time. In Figure 16, the complete layout of the TMR PFD is shown: the three PFDs with their reset majority logic can be recognized on the left, while the output majority logic can be recognized on the right.  
\begin{table}
\begin{tabular}{l l l} \hline \hline  & **CMOS** & **CML** \\ \hline Charge Pump DC current mismatch (worst case) & 1.454 \(\upmu\)A & 1.66 \(\upmu\)A \\ Power Consumption Charge Pump + PFD & \(\approx\)200 \(\upmu\)W & \(\approx\)5 mW \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison between the two CP/PFD architectures in terms of CP’s current matching and CP+PFD’s power consumption.  
Figure 14: Comparison between the two CP/PFD (Phase Frequency Detector) architectures in terms of phase noise: Current Mode Logic (CML) architecture’s results in red, CMOS architecture’s results in black.
## 1 Introduction
This leaves the usability of these methods in post-fire management of forests not well understood, to date. To fill this gap, the current study evaluates the ability of VARI, estimated by both satellite and UAV images, to quantify the vegetation recovery after post-fire treatments (LEBs and CFDs) in a Mediterranean forest of Central Eastern Spain. Possible correlations between the vegetation cover measured in field plots and VARI values estimated from satellite (LANDSAT8) or UAV images, are identified. Processing of this information at two spatial scales (catchment and hillslope) allows validation of one or both methods.
## 4 Discussion
### Adsorption of Ultraviolet Radiation  
From the tested LBMs (Table 6), a UV light absorption potential from 29.43 to 52.01% was observed in FC membranes and a greater potential for UV light absorbance was observed in FL membranes (from 51.56 to 82.45%). This could be due to lower solubility and higher concentration and dispersion of components over the entire surface. This behavior is because secondary metabolites such as flavonoids and esters in plant leaves can absorb UV radiation [63; 64]. Presumably, the polyphenols in the Aloe extracts were the main UV absorbing elements. Aloe gel is believed to have a modulating effect on the skin by preventing sunlight from sensitizing the skin, especially in the first 24 h after exposure [65]. This is corroborated in the FT-IR results, by showing bands associated with Aloe.  
Since UV radiation penetrates deeply, affecting the dermis, destroying elastic and collagen fibers, and conditioning aging, immune suppression, photoallergic reactions, and phototoxic reactions [66], a full scan of the UV radiation spectrum was performed. However, the behavior of the percentage of UV light absorbance in both the LBM FC and FL do not show significant differences in the evaluation of the near, medium, and far UV spectrum.  
Due to its phenolic structure, both lignin and Aloe vera provide the membrane with light-absorbing properties, a natural potential for protection against UV rays, while also presenting stability against thermal oxidation when present in mixtures with other polymers. Previous research has modified the potential of lignocellulosic materials as a component in UV light-blocking membranes [67].  
In addition to this, considering the impediment of the passage of UV radiation through the treated fibrous material, this gives the property of sunscreens, which absorb and/or prevent UV radiation from reaching the skin. The link between chronic human skin exposure to the sun and harmful clinical consequences such as photoaging and skin cancers is indisputable. Sun exposure can quickly induce well-characterized and visible clinical consequences, such as sunburn [68].
## 2 Materials and Methods  
### Dynamic Model of the Lower Limb Prosthesis  
The 2-DOF powered robotic leg prosthesis has an active ankle joint and an active knee joint. As shown in Figure 1, the dynamics of the leg prosthesis in the joint space can be written as  
\[M\ddot{q}+C\dot{q}+G=\tau+\tau_{e} \tag{1}\]  
where \(q=[q_{1},q_{2}]^{T}\in\mathbb{R}^{2}\) denotes the real angle of joints, \(q_{1}\) denotes the angle of the ankle joint, and \(q_{2}\) denotes the angle of the knee joint. \(\tau\in\mathbb{R}^{2}\) denotes the control torque to drive the motor. \(\tau_{e}\in\mathbb{R}^{2}\) denotes the interaction torque derived from the contact force between the stump and the leg prosthesis. \(M\in\mathbb{R}^{2\times 2}\) denotes the inertia matrix, \(M=\left[ \begin{array}{cc}M_{11}&M_{12}\\ M_{21}&M_{22}\end{array} \right]\), where \(M_{11}=m_{1}d_{1}^{2}+I_{1}+I_{2}+m_{2}(l_{1}^{2}+d_{2}^{2}+2l_{1}l_{2}\cos q _{2})\), \(M_{12}=m_{2}d_{2}^{2}+I_{2}+m_{2}l_{2}d_{2}\cos q_{2}\), \(M_{21}=m_{2}d_{2}^{2}+I_{2}+m_{2}l_{2}d_{2}\cos q_{2}\), \(M_{22}=m_{2}d_{2}^{2}+I_{2}\). \(C\in\mathbb{R}^{2\times 2}\) is the centripetal-Coriolis matrix, \(C=\left[ \begin{array}{cc}C_{11}&C_{12}\\ C_{21}&C_{22}\end{array} \right]\), where \(C_{11}=-m_{2}l_{1}d_{2}\sin q_{2}q_{2}\), \(C_{12}=-m_{2}l_{1}d_{2}\sin q_{2}(q_{1}+q_{2})\), \(C_{21}=m_{2}l_{1}d_{2}\sin q_{2}q_{1}\), \(C_{22}=0\). \(G\in\mathbb{R}^{2}\) is the gravitational torque, \(G=\left[ \begin{array}{c}G_{1}\\ G_{2}\end{array} \right]\). where \(G_{1}=m_{1}d_{1}g\cos q_{1}+m_{2}g(d_{2}\cos(q_{1}+q_{2})+l_{1}\cos q_{1})\), \(G_{2}=m_{2}d_{2}g\cos(q_{1}+q_{2})\). In these equations, \(l_{1}\) denotes the distance from the ankle joint to the knee joint, and \(l_{2}\) denotes the distance from the knee joint to the mass center of human body. \(m_{i}\) denotes the mass of \(i\)-th limb, \(d_{i}\) represents the distance from the joint to the center of the \(i\)-th limb, \(I_{i}\) represents the moment of inertia of \(i\)-th limb, \(g\) is the gravity, and \(i=1\), \(2\). The mathematical notations and definitions are shown in Table 1.