esa-sceva/satcom-chunk-collection huggingface dataset:
# Dynamic Network Resource Autonomy Management and Task Scheduling Method
## 5 Conclusions  
This study proposes a dynamic task scheduling method based on a unified resource management architecture, which has obvious advantages in satellite schedule. The technique combines resource management with dynamic scheduling algorithms, realizes real-time monitoring of resources, can better adapt to the satellite scheduling environment, and can intelligently allocate tasks according to their priority and available resources. Experiments show that the method can guarantee the completion rate of satellite scheduling tasks and improve resource utilization. The results of this study provide the necessary guidance for the design and management of satellite scheduling algorithms and systems and verify the effectiveness and practicality of the method. Importantly, our research is relevant regarding sustainability, market demand, and impact on policy. Our approach can reduce energy consumption by improving resource utilization, reducing environmental impact, and meeting changing market demands flexibly with dynamic scheduling algorithms. It helps related companies improve productivity and competitiveness, as well as can help realize digital transformation and informatization to promote global economic prosperity and development. However, our architecture still needs to be improved. For example, more resource types, task types, and performance metrics can be introduced to more comprehensively consider the utilization of resources, meet different requirements, and evaluate the overall system's performance. Where machine learning and deep learning algorithms can provide strong support for improving such architectures, there is more significant potential for development in this area. In the future, we will continue to delve into extending the approach to other applications.  
**Author Contributions:** Conceptualization, H.F.; Methodology, X.L., J.Y. and H.F.; Software, J.Y. and H.F.; Validation, X.L. and J.Y.; Formal analysis, J.Y. and H.F.; Investigation, X.L., J.Y. and H.F.; Resources, H.F.; Data curation, H.F.; Writing--original draft, H.F.; Writing--review and editing, X.L., J.Y. and H.F.; Visualization, X.L.; Project administration, X.L. and H.F.; Funding acquisition, X.L.  
**Funding:** This research was funded by Xinjiang Natural Science Foundation grant number 2020D01C026.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Analysis on Free Vibration and Stability of Rotating Composite Milling Bar with Large Aspect Ratio
###### Abstract
In addition, the design and manufacture schemes of composite boring bar have been proposed in previous reports [25; 26], in which the researchers attempted to improve the static and dynamic rigidity of the boring bar. So far, most of the work has been directed to the structural design and subsequential experimental verification, while only little work has focused on a dynamic analytical model of a rotating composite milling bar. [PERSON] et al. [27] studied the response and stability of a high-speed rotating composite shaft subjected to the typical cutting forces of milling, and Timoshenko beam theory was used for the structural dynamic model of rotating composite shaft. Meanwhile, a deflection-dependent cutting forces model with regeneration delay effects was established and the dynamic milling model was solved by frequency domains method. The influence of inertial force (Square term of rotating speed) was not considered in the model. This paper aims at providing a new dynamic model of composite milling bar, which is a cylindrical tubular composite shaft modeled as a continuous distributed Euler Bernoulli beam without considering the thickness of the bar. For shaft made of isotropic material, when the aspect ratio is larger than 10, the Euler Bernoulli beam theory is usually used. This is a simple model, but accurate results can be obtained [28]. When the Euler beam theory is used, the number of unknown functions of the model is greatly reduced because it does not consider the shear deformation, which greatly promotes the modeling of the cutter bar structure and the stability of the cutting system, and ensures the accuracy of the solution [PERSON]'s principle was used to derive free vibration equations of the bar, then Galerkin approach was used to obtain the characteristics of the free vibration of the bar. To measure the stability of the bar in a cutting process, the cutting loads including regeneration delay effects were incorporated into the free vibration equations. The stability lobes were obtained in the discrete time domain [14], and the variation of stability lobe diagrams as a function of different parameters including external damping, internal damping, ply angle and gyroscopic and inertial effects was investigated. In addition, the methods in the frequency domains based on zero-order solution [14] were also used in the analysis. The chatter frequency and angular displacement curves corresponding to the stable lobes indicate the physical significance of the regenerated chatter of the milling bar. It was found that the application of composite expanded the stable regions in milling process to a certain extent (15.87% with the given material and aspect ratio). For the first time, the effect of whirl caused by rotation on the cutting stability of composite milling bar was analyzed. The results show that the backward whirl has a negative damping effect, which is not conductive to the cutting stability.
## 2 Methods
### Layerwise Theory  
Equivalent single theories and layerwise theories are two approaches that are mostly adopted to model the displacement fields for multi-layered laminated and sandwich plates. Compared to the most commonly used equivalent single theories [32; 33; 34], such as classic laminate theory, first-order or higher-order shear deformation theory, layerwise theories are capable of predicting more accurate static and dynamic behavior of soft-core sandwich structures by a separate description of displacement fields for each layer [35; 36; 37; 38].  
In this paper, a layerwise theory is employed to describe displacement fields for the HCS plates with three layers. The piecewise linear in-plane displacement field is assumed through the plate thickness, maintaining displacement continuity at layer interfaces and allowing different slopes in each layer. The displacement field of the \(k\)th layer (\(k=1\), \(2\), \(3\)) is given as  
\[\begin{split} u^{(k)}(x,y,\zeta_{k})&=U^{(k)}(x,y )\Psi_{1}^{(k)}(\zeta_{k})+U^{(k+1)}(x,y)\Psi_{2}^{(k)}(\zeta_{k})\\ v^{(k)}(x,y,\zeta_{k})&=V^{(k)}(x,y)\Psi_{1}^{(k) }(\zeta_{k})+V^{(k+1)}(x,y)\Psi_{2}^{(k)}(\zeta_{k})\\ w^{(k)}(x,y,\zeta_{k})&=w^{0}(x,y)\end{split} \tag{1}\]  
where \(U^{(k)}\), \(V^{(k)}\) and \(U^{(k+1)}\), \(V^{(k+1)}\) are the in-plane displacements at lower and upper surfaces of the \(k\)th layer and \(w^{0}\) is the out-plane displacement of any point on the mid-plane of the sandwich plates. \(\Psi_{1}^{(k)}\) and \(\Psi_{2}^{(k)}\) are the linear interpolation functions through the thickness direction and \(\zeta_{k}\) is the local thickness coordinate, given as  
\[\Psi_{1}^{(k)}=\frac{1}{2}(1-\zeta_{k}),\,\Psi_{2}^{(k)}=\frac{1}{2}(1+\zeta _{k}),\,\zeta^{(k)}=\frac{h_{k}}{2}z-\frac{z_{l}^{(k)}+z_{u}^{(k)}}{h_{k}} \tag{2}\]  
Figure 1: A typical hybrid corrugated sandwich plate with its composition.  
where \(h_{k}\) is the thickness and \(z_{k}^{(l)}\) and \(z_{k}^{(u)}\) are the \(z\)-axis coordinates of the lower and upper surfaces.
## 3 LORAWAN Operation
### LoRaWAN Joins and Communications
For example, a Class A mote sends a message that a measured variable has reached a particular value. The monitoring system makes a decision and sends a reply that the mote should act in a certain way (change an output). When the initial message was sent, the NS received that message, immediately arranged the ACK, and forwarded that message to the mote monitoring system. This system made a decision based on the data and sent a reply to the NS that needs to be forwarded to the mote, but the ACK has already been prepared, sent to the gateway, and may have already been transmitted. In that case, the reply message will sit until the following uplink message then the reply will be included in the ACK. For a system transmitting once an hour, the response to a particular condition may be delayed an hour. The system designer of the mote application needs to take this into account.
# Visual Sentiment Analysis Using Deep Learning Models with Social Media Data
## 6 Experimental Results and Discussion
### Result of Visual Sentiment Classification with the Fine-Tuned pre-Trained Models
#### 6.4.2 Generation of Confusion Matrix  
The pre-trained models were compiled with a suitable optimizer (\"Adam\"). A loss function (\"categorical cross-entropy\") was applied. The Adam optimizer can work perfectly even with large datasets and also has a learning rate that is adaptable. The training of the model was done with a set of images allocated for training with 50 epochs, and a batch size of 20 was maintained. After training, the model was evaluated using test samples. Figure 18 shows the confusion matrix generated after evaluating the testing samples with the fine-tuned VGG-19 model.  
The confusion matrix generated by the DenseNet-121 and ResNet50V2 deep learning networks for image sentiment categorization is shown in Figure 19 below.  
Figure 17: Accuracy plot of the grid search of regularization parameter (DenseNet-121 and Resnet50V2 models).  
Figure 18: Confusion matrix generated by the VGG-19 model.  
The above plots show the model accuracy and model loss over the epoch for 50 epochs. It is indicated that the fine-tuned DesneNet121 model had the highest testing accuracy. The maximum model loss was at the beginning of the epoch and continued to decrease as it went beyond 4 epochs, settling to a lower value as it reared 50 epochs. When we evaluated the proposed and other transfer learning models on the collected dataset, we noted that the performance increased when there was a much deeper architecture, such as DenseNet121, in our dataset.
## 3 Results and Discussion
### Thermodynamic Adsorption Experiments  
The Van't Hoff plot obtained from Sb(V) adsorption experiments at 15, 25, and 35 \({}^{\circ}\)C are presented in Figure 5, and the enthalpy (\(\Delta H^{0}\)), entropy (\(\Delta S^{0}\)), and Gibbs free energy (\(\Delta G^{0}\)) obtained from the thermodynamic analysis are presented in Table 4. The Sb(V) adsorption by Fe-CMB decreased with increasing reaction temperature, which is consistent with the negative value of \(\Delta H^{0}\). The negative value of \(\Delta H^{0}\) indicates that Sb(V) adsorption  
Figure 4: Equilibrium adsorption results for Sb(V) adsorption by Fe-CMB and model fits using [PERSON], [PERSON], and Temkin models.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Model Parameter**} & \(\mathbf{R^{2}}\) & \(SSE\) \\ \hline Freundlich & \(K_{F}\) (L/g) & 1/n (-) & 0.960 & 83.8 \\  & 4.910 & 0.575 & & \\ Langmuir & \(Q_{m}\) (mg/g) & \(K_{L}\) (L/mg) & 0.982 & 39.1 \\  & 58.3 & 0.051 & & \\ Temkin & \(B_{T}\) (kJ/mol) & \(K_{T}\) (L/g) & 0.877 & 260.3 \\  & 0.217 & 0.423 & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Model parameters and model suitability for equilibrium adsorption data obtained from [PERSON], [PERSON], and Temkin models.  
onto Fe-CMB is exothermic. The free energy (\(\Delta G^{0}\)) values under all conditions in this study were negative, which suggests that the Sb(V) adsorption process was spontaneous.
## 2 Material and Methods
### Biodegradable Synthetic Vascular Grafts
#### 2.1.3 PCL  
Poly (\(\varepsilon\)-caprolactone) (PCL) is an aliphatic polyester that has been thoroughly investigated. PCL has one of the slowest degradation profiles out of all biodegradable polymers [14]. PCL is hydrophobic and exhibits a low melting point. Therefore, the PCL polymer is pliable at lower temperatures, in addition to being highly tunable and easy to fabricate [20].  
A series of in vivo studies have evaluated electrospun PCL in rats at 3, 6, and 9 month timepoints. The PCL graft patency was 100% and did not display signs of thrombosis. PCL scaffolds were also found to lose 20%, 50%, and 78% of their initial molecular weight at 3, 12, and 18 month timepoints [21,22].  
As a result of it's long durability and ease of handling, PCL is frequently used to create grafts suitable for arterial environments [23]. PCL demonstrates favorable mechanical properties with 70% elongation at break compared to 30% and 25% for PGA and PLA, respectively [14]. Additionally, while numerous studies on a multitude of PCL grafts have been conducted in mice and rats, the material has yet to be fully characterized because rodent lifespans expire before the material fully degrades.  
In the case of Poly(l-lactic-co-\(\varepsilon\)-caprolactone)(PLCL), controlling the composition ratios and molecular weights of the individual polymers from which it is derived, allows for better control of mechanical properties and degradation rates. For example, the PLCL (LA/CL=75/25) heteropolymer is stronger than PCL individually, but manages to keep the 70% elongation at break of PCL [14]. We have confirmed the in vivo feasibility of PLA-PLCL scaffolds in high pressure, small-diameter arterial environments [24]. However, when we attempted to translate the material to a sheep carotid artery model, all grafts ruptured and thrombosed. PCL is a hydrophobic material, and without modifications, will most likely lead to a thrombotic or occluded graft.
# Dynamically Triggered Damage Around Rock Tunnels: An Experimental and Theoretical Investigation
## 5 Discussion  
### Insights from Experimental Results for In Situ Observations  
Through conducting indoor impact experiments and transient dynamic analysis based on complex variable functions, the damage patterns and mechanisms of arched holes under dynamic impact have been thoroughly evaluated. The effects of different dynamic incidence angles on the stress distribution and deformation development around the arched hole were analyzed. As a common form of underground space section, the arched shape is widely used in mining and hydraulic engineering [39]. In practical engineering, dynamic disturbances come from all directions, such as blasting construction [40], far-field earthquakes [41], rockfall impacts, etc. These dynamic disturbances impose risks on existing tunnels, potentially triggering rockburst and spallation [3; 21; 42]. Some typical geotechnical catastrophe patterns of arched tunnels under dynamic disturbances are presented in Figure 12.  
Coincidentally, the destruction patterns presented in Figure 12 are matched in Figure 7, which indicates that small-scale laboratory experiments are capable of reproducing engineering-scale destruction to a certain extent, and this also highlights the necessity and reliability of this study. Therefore, their damage mechanisms are similar, i.e., under the action of dynamic disturbances due to a local concentration of tensile/compressive stresses. In Figure 7e, spalling failure is observed, which is not caused by dynamic tensile forces but by compression [31]. Spalling resulting from dynamic tensile was not detected in this experiment [45] due to the utilization of incident wavelengths much larger than the hole size (wavelength/hole radius > 100). When the incident wavelength is small relative to the hole size (wavelength/hole radius < 20-30), the stress wave is treated as reflected tensile stress between the stress wave and the tunnel. However, with incident wavelengths significantly greater than the tunnel size, the stress wave is considered to be scattered around the tunnel [3; 32]. In situations where short-wavel  
Figure 12: Dynamic damage to arched tunnels: (**a**) rockburst in a deep tunnel at the Jinping II hydropower station [43]; (**b**) dynamically triggered rockburst in a Shandong Linglong Gold Mine tunnel (dot boxes indicate local zoom in) [21]; and (**c,d**) splitting, spalling and rockburst caused by blasting in the Bayu Tunnel, Shannan City [44].  
radial tensile stresses are generated on the incident side due to reflection, resulting in the occurrence of spalling damage [46]. Conversely, in cases of long-wavelength incidence, the stress wave diffracts around the hole, avoiding the generation of radial tensile stress and instead leading to the concentration of circumferential tensile stresses.
# A Hybrid PAPR Reduction Method Based on SLM and Multi-Data Block PTS for FBMC/OQAM Systems
## 3 Conventional PAPR Reduction Schemes
### PTS Scheme  
Let \(S\) denotes the input signal in frequency domain. \(S\) is partitioned into \(V\) sub-blocks with \(S_{m}^{v}=\left[S_{1}^{v},S_{2}^{v},\ldots,S_{M}^{v}\right]^{T}\), \(V\) denotes the number of sub-blocks. In the PTS technique [14], scrambling (rotating its phase independently) is applied to each sub-block. Then, each partitioned sub-block is multiplied by a corresponding complex phase factor \(b^{v}=e^{j\varphi v}\),\(v=1,2,\ldots,V\). The time-domain signal after the combination is given as:  
\[s_{m}(t)=\sum_{v=1}^{V}b^{v}s_{m}^{v}(t) \tag{5}\]  
where \(\{s_{m}^{v}(t)\}\) is presented as a partial transmit signal. The phase vector is chosen to minimize the PAPR as:  
\[\left[\widetilde{b}^{1},\ldots,\widetilde{b}^{V}\right]=\arg\min_{\left[b^{1},\ldots,b^{v}\right]}\max_{0\leq t\leq T}\left|\sum_{v=1}^{V}b^{v}s_{m}^{v}(t) \right|^{2} \tag{6}\]  
Then, the corresponding time-domain signal can be obtained, which has the lowest PAPR vector as:  
\[\widetilde{s}_{m}(t)=\sum_{v=1}^{V}\widetilde{b}^{v}s_{m}(t) \tag{7}\]  
A set of elements limits the selection of the phase factors \(\{b^{v}\}_{v=1}^{V}\), and reduces the search complexity. One simple example is to use the binary phase factor of \(\{1,-1\}\).  
The phase rotation operation is used for each transmit data block signal independently in the PTS scheme. When utilizing the PTS scheme to reduce PAPR in FBMC/OQAM systems, the overlapped structure debates the optimization performance. This conclusion could be verified by the simulations in Section 5.
## 3 Materials and Methods
### Improved Immune Particle Swarm Optimization
#### 3.3.1 Immune Particle Swarm Optimization  
In the 1990s, scholars [PERSON] and [PERSON] introduced the concept of PSO. The fundamental premise of this concept is to simulate a flock of birds by establishing a set of massless particles. Each particle represents a bird within the flock and emulates the process of foraging. The particles independently search the problem space to identify the optimal solution, with the best solution found regarded as the individual extreme value. Subsequently, the individual extreme values are compared to those of other particles, with the optimal individual extreme value obtained serving as the local optimal solution at the current stage. Concurrently, each particle modifies its velocity and position in accordance with its current optimization status and that of other particles. Ultimately, a globally optimal solution is achieved through the continuous updating and iteration of the particles. Assuming there are \(D\) particles in a D-dimensional search space, where each particle represents a potential solution, then the position of the \(i^{th}\) particle can be denoted as \(x_{id}=\{x_{i1},x_{i2},\ldots,x_{iD}\}\), and the velocity of the \(i^{th}\) particle can be denoted as \(v_{id}=\{v_{i1},v_{i2},\ldots,v_{iD}\}\). These particles update their velocity and position using the following formula:  
\[v_{id}^{k+1}=wv_{id}^{k}+c_{1}r_{1}(p_{id,pbest}^{k}-x_{id}^{k})+c_{2}r_{2}(p_ {d,gbest}^{k}-x_{id}^{k}) \tag{1}\]  
\[x_{id}^{k+1}=x_{id}^{k}+v_{id}^{k+1} \tag{2}\]  
where \(i\) represents the particle index; \(k\) is the current number of iterations; \(w\) is the inertia weight; \(c_{1}\) and \(c_{2}\) are learning factors; \(r_{1}\) and \(r_{2}\) are two random numbers in the range of (0, 1) to ensure the diversity of the group; \(p_{id,pbest}^{k}\) is the historical best position of particle \(i\) in dimension \(d\) during iteration \(k\); and \(p_{d,gbest}^{k}\) is the historical best position of the group in dimension \(d\) during iteration \(k\).  
The IPSO employs an ingenious integration of the principles of the immune system into the foundational structure of the PSO. This approach utilises the concept of immune memory to ensure the preservation of superior solutions encountered during previous searches. The population is diversified through the use of cloning and mutation operations.
## 4 Contribution of Thermodynamic Calculations
### Phase Transitions in Mixed Oxide Systems  
When dealing with solid-gas reactions involved in TCES processes, one must keep in mind a fundamental difference between single metal oxides and oxide mixtures. Indeed, according to the Gibbs' phase rule, the redox reactions (Equations (2) and (3)) for a single metal oxide occur at constant temperature. Conversely, with two metal oxides in the system, the variance increases, and the coexistence of two solid phases can occur on a large temperature and composition range.  
A few typical examples of such behaviors are provided in Figure 10. The first case (Figure 10a,b) concerns the behavior of a single metal oxide, here Co\({}_{3}\)O\({}_{4}\), with a phase transition occurring at 890 \({}^{\circ}\)C. Conversely, the phase transition between the spinel (Co\({}_{0.75}\)Fe\({}_{0.25}\))O\({}_{4}\) and the monoxide Co\({}_{0.75}\)Fe\({}_{0.25}\)O (Figure 10c,d) occurs on a very large temperature range, between 935 and 1460 \({}^{\circ}\)C. However, most of the conversion of the spinel takes place in the first 100\({}^{\circ}\)C, and the enthalpy variation is also concentrated in this temperature range. This means that the maximal operating temperature does not need to be very high in order to store most of the achievable heat. Conversely, in the case of the conversion of the bixbyite (Mn\({}_{0.10}\)Fe\({}_{0.90}\))\({}_{2}\)O\({}_{3}\) into the spinel (Mn\({}_{0.10}\)Fe\({}_{0.90}\))\({}_{3}\)O\({}_{4}\) (Figure 10e,f), the concomitant formation of the hausmannite phase spreads the phase transition on about 200 \({}^{\circ}\)C, which implies a larger temperature of operation for the thermochemical cycle.  
Figure 10: Calculation of the influence of temperature on (**a**,**c**,**e**) the phase assemblage evolution and (**b**,**d**,**f**) the system enthalpy, for three oxide systems in air.  
Figure 9: Calculated minimal amount of Fe in the Mn-Fe-O system in order to avoid the formation of the hausmannite phase at any temperature (model from [47]).