esa-sceva/satcom-chunk-collection huggingface dataset:
# Stripe-Assisted Global Transformer and Spatial-Temporal Enhancement for Vehicle Re-Identification
## 3 Methodology
### SaGT  
#### 3.1.1 Embedding Basic Features  
Consider a vehicle image \(X\in\mathbb{R}^{H\times W\times C}\), where \(H\), \(W\), and \(C\) denote the height, width, and the number of channels of images, respectively. Following the ViT, we first split the image into \(N\) patches \(x_{p}\in\mathbb{R}^{P\times P\times C}\), where \(N=\frac{H}{P}\times\frac{W}{P}\), \((P,P)\) is the size of each patch. Then, we flatten each patch and map it to 1D with a trainable linear function \(\mathcal{F}_{l}(\cdot)\). Furthermore, we also prepend a learnable class embedding \(x_{cls}\) as the global feature and add a 1D learnable position embedding \(E_{pos}\) to retain spatial information. Therefore, the input \(Z_{0}\) of the transformer encoder can be expressed as follows:  
\[Z_{0}=[x_{cls},\mathcal{F}_{l}(x_{p}^{1}),\mathcal{F}_{l}(x_{p}^{2}),\cdots, \mathcal{F}_{l}(x_{p}^{N})]+E_{pos}, \tag{1}\]  
where \(x_{cls}\in\mathbb{R}^{1\times D}\) and \(E_{pos}\in\mathbb{R}^{(N+1)\times D}\).  
Finally, the basic features \(E_{b}\) of image patches are generated by a transformer encoder including \(L\) standard transformer layers, which is described in Equation (3). The transformer layer consists of two layer-normalization (LN) units, a multi-head self-attention (MHSA), and a multi-layer perceptron (MLP) with two hidden layers, detailed in Equation (2) as follows:  
\[\begin{split} Z_{i}^{\prime}&=\text{MHSA}(\text{ LN}(Z_{i-1}))+Z_{i-1},\\ Z_{i}&=\text{MLP}(\text{LN}(Z_{i}^{\prime}))+Z_{i }^{\prime},\end{split} \tag{2}\]  
\[E_{b}=Z_{L}, \tag{3}\]  
where \(Z_{i}\in\mathbb{R}^{(N+1)\times D}\) is the output of the \(i\)th transformer layer.  
Figure 2: **The overall framework of our proposed approach**. It consists of two streams. The top is the visual feature stream that employs an SaGT to extract global and stripe-based features for vehicle images. The lower left is the STPro stream that utilizes the location and timestamp of vehicles to estimate the probability when vehicles take time to move from one camera to another. The fusion module in the lower right fuses the global feature distance and the STPro for vehicle re-identification. (Best viewed in color.)
## 3 System Descriptions and Assumptions
### DESCO Task Processing Model
#### 3.4.3 Cache-Based Offloading Mode  
When user \(n\) requests a service that is stored locally in the cache pool of \(d\), or when the service \(k\) is located in another server through executing Algorithm 1 (denoted as \(\text{ServerIP}^{t}_{k}\lor p^{d,t}_{k}=1\)), MUs only need to transmit \(\theta_{k}\) to server. The corresponding transmission cost is then quantified as  
\[\psi_{n}\frac{\theta_{k}}{l_{n}^{d,t}}; \tag{10}\]  
similarly, the latency in cache-based offloading can be expressed as  
\[T^{C}_{n,k,d,t}=\text{sgn}(1-p^{d,t}_{k})T^{R}_{d,k,t}+\frac{\phi_{k}}{\eta_{d }}+\frac{\theta_{k}}{l_{n}^{d,t}}, \tag{11}\]  
where signum function \(\text{sgn}(x)\) be subjected to  
\[\text{sgn}(x)=\left\{\begin{array}{ll}1,&x>0\\ 0,&x=0.\end{array}\right. \tag{12}\]  
In Equation (12), \(\text{sgn}(1-p^{d,t}_{k})T^{R}_{d,k,t}\) denotes the latency of executing the routing algorithm to acquire application data \(\omega_{k}\) in the Cache Chord. In this state, users do not need to further transmit data \(\omega_{k}\) for task \(k\), thereby reducing some of the time overhead. To simplify the model, consistent with other studies [3; 29; 30], we assume that the computational capacity of MEC servers is much greater than that of MUs, i.e., \(\eta_{d}\gg o_{d,n}\). Therefore, the latency caused by MEC servers performing computations can be eliminated.  
During the process of MEC servers utilizing the Cache Chord to execute indexing algorithms, the data volume transmitted between MEC nodes is very small, containing only information such as the IP address of the resources and the hash value of the destination server node address. Additionally, as MEC nodes are geographically adjacent and communicate through ideal wired backhaul links, without any transmission bottlenecks, the propagation delay of MEC servers transmitting application data to each other can be neglected. Therefore, in our modeling, we assume that the delay of MEC servers retrieving and transmitting corresponding application data \(\omega_{k}\) in the Cache Chord can be ignored. This can be represented by the following inequality:  
\[\frac{\phi_{k}}{\eta_{d}}+T^{R}_{d,k,t}\ll\frac{\phi_{k}}{o_{d,n}}\leq\tau \tag{13}\]
## 4 Verification
### Simulation Validation Utilizing Synthetic PMU Data
#### 4.1.2 Absolute Deviations in Noise Scenarios  
By adding white noise with a 40 dB SNR to the instantaneous signal, as can be seen in Table 1, regardless of whether \(f_{\text{sub}}\) varied at 1 Hz intervals within the range of [5; 45] Hz or \(x_{\text{sub}}\) varied at 1 Hz intervals within the range of [5; 100] HZ, the identification error of \(x_{0}\) exceeded 5% when using the traditional ERA algorithm with 200 ms and 1 s time frames. The primary reason for this is that the paired association of the angular velocities \(\omega_{1}\) and \(\omega_{2}\) contenting \(\mathrm{j}\omega_{0}\) and \(-\mathrm{j}\omega_{0}\) was not considered, leading to significant errors in fundamental wave parameter identification. Meanwhile, the existing ERA exhibited a significant identification error rate of nearly 8% for \(\phi_{\text{sub}}\) under the 200 ms data window and an even higher error rate exceeding 12% for \(x_{\text{sub}}\). In contrast, the fitting-based ERA could control the relative error of the identification results to below 1.75% even with a 200 ms data window. Therefore, there is clear evidence that the fitting-based ERA provides more rigorous identification results for synchrophasor parameters under SSO conditions featuring a 40 dB SNR level than the existing ERA, validating the correctness and feasibility of this algorithm for identifying synchrophasor parameters under SSO conditions.
## 4 Numerical Analysis Software and Methods Used
### Safety Calculation  
\"Safety calculation type\" is an option in PLAXIS for calculating global safety factors. This option can be selected as a separate \"Calculation type\" in the \"General tabsheet\" [39]. In the safety method, the shear strength parameters \(\text{tan}\varphi\) and \(c\), as well as the tensile strength of the soil, are gradually reduced until structural failure. In principle, the phi/c reduction process has no effect on the dilatancy angle \(\psi\)[39]. However, the dilatancy angle can never be greater than the friction angle. When the friction angle has reduced so much that it equals the given dilatancy angle, any further reduction in the friction angle results in the same reduction in the dilatancy angle [39].  
The total multiplier safety factor, \(\Sigma\)_Msf_, is used to define the soil strength parameter values at a given stage of the analysis [39]:  
\[\Sigma\textit{Msf}=\frac{\text{tan}\varphi_{input}}{\text{tan}\varphi_{reduced }}=\frac{c_{input}}{c_{reduced}} \tag{2}\]  
where the parameters with the subscript \"input\" refer to the attributes entered in the material set, and the parameters with the subscript \"reduce\" refer to the reduced values used in the analysis. \(\Sigma\textit{Msf}\) is set to 1.0 at the beginning of the calculation to set all material strengths to their input values.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Site** & **Point A** & **Point B** & **Point C** & **Point D** & **L (m)** & **H (m)** \\ \hline Site 1 & (0, 0) & (0, 60) & (180, 107.2) & (180, 0) & 180 & 107.2 \\ Site 2 & (0, 0) & (0, 65) & (170, 142.5) & (170, 0) & 170 & 142.5 \\ Site 3 & (0, 0) & (0, 48) & (160, 101.2) & (160, 0) & 160 & 101.2 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Model boundaries for each analysis site.  
The \"Load advancement number of steps procedure\" was used to perform safety calculations in this study. The incremental multiplier _Msf_ was used to specify the increment of intensity reduction in the first calculation step. This increment was preset to 0.1, which is generally considered a good starting value. The strength parameter is automatically and continuously reduced until all additional steps have been performed. The number of steps in this study was set to 100. It is important to always check whether the last step resulted in a fully developed failure mechanism. If this is the case, the slope safety factor (SF) is given by the following [39]:  
\[\text{SF}=\frac{\text{available strength}}{\text{strength at failure}}=\text{ value of }\Sigma Msf\text{ at failure} \tag{3}\]
## 5 Conclusions  
In order to solve the problems of high cost, low welding efficiency, and complex process in vacuum brazing, the welding method of EU-assisted brazing was proposed, and the CF behavior of liquid solder Al-12 Si in the gap between SiC ceramic and TC4 alloy under the action of an EU wave was analyzed. The following findings were revealed:  
(1) After the alternating current was introduced, a periodically rotating alternating magnetic field was induced in the air near the coil. The static MF generated by the permanent magnet was directed vertically downwards. Under the combined action of the two MFs, the maximum MIS of the liquid solder in the horizontal and vertical directions was 0.629 T and 0.342 T, respectively.  
(2) The eddy current generated in the liquid solder interacts with both the alternating and static MFs, resulting in a downward deflection trend of the LF inside the liquid solder. The maximum LF in the horizontal and vertical directions was 48.91 kN m\({}^{-3}\) and 60.93 kN m\({}^{-3}\), respectively.  
(3) Under the influence of the LF with a frequency of 20 kHz, an EU wave was generated in the liquid solder, resulting in sinusoidal sound pressure at multiple positions within the liquid solder. The liquid solder moved due to the combined effect of the acoustic pressure difference and positive half-wave offset between different positions. At 26 ms, the maximum CF length of the liquid solder was 12.21 mm. These results indicate that applying a high-frequency MF to the liquid solder could make the liquid solder undergo macroscopic fluid movement, and then complete the connection between dissimilar materials.  
Conceptualization, G.C. and M.Z.; methodology, G.C.; software, M.Z.; validation, Q.G.; formal analysis, M.Z.; investigation, Q.G.; data curation, Q.G.; writing--original draft preparation, G.C.; writing--review and editing, M.Z.; visualization, Q.G.; supervision, H.Y.; project administration, H.Y.; funding acquisition, H.Y. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.
## 3 Performance Predictions of Cement-Eggshell Powder Binary System
### Prediction of the Amount of Hydration Products
From Figure 3b, Figure 4b, and Figure 5b, at 28 days, for samples with 0%, 7.5%, and 15% eggshell powder, the calcium hydroxide at 28 days is 0.183, 0.179, and 0.173 g/g binder, respectively. The development trend of calcium hydroxide is similar to that of chemically bound water. In addition, we can see that at 28 days, as shown in Figure 5a (15% eggshell powder), the calculated chemically bound water is slightly higher than the experimental chemically bound water. This may be because in the calculation, we ignored the pore refinement effect of the chemical reaction of eggshell powder. In our calculation, it is assumed that all capillary water (W\({}_{0}\) \(-\) 0.38 C0\(\alpha\)) can be used by cement hydration. However, the chemical reaction of eggshell powder will refine the pores, resulting in an increase in the fine pore content [26,27]. In fact, the capillary water available for cement hydration reaction is lower than (W\({}_{0}\)\(-\) 0.38 C0\(\alpha\)). Since this pore refinement effect is not considered in our calculation, the calculated values of hydration degree and chemically bound water are slightly higher. At 28 days, for the specimens containing 15% eggshell powder, the calculated results of chemically bound water and calcium hydroxide are slightly higher than the experimental results. In addition, because the experimental results of Figures 3-5 are from reference [24], in which the authors only give the test results of two time points (1 day and 28 days), we cannot add more test time points in this paper. In future research, more samples/experiments should be used to verify the correctness of the proposed model. Figure 3: Combined water and calcium hydroxide contents—no eggshell powder. (**a**) Combine water content—no eggshell powder. (**b**) Calcium hydroxide content—no eggshell powder.
## 3 Some Key Issues on the Use of SLNs and NLCs as Oral Nanovehicles for Nutraceuticals or Bioactives
### Poorly Soluble Bioactive Compounds
#### 4.2.3 Phytosterols and Phytostanols
In a more recent work, using the same strategy to fabricate \(\beta\)-sitosterol-loaded NLCs as in the previous work [167], [PERSON] et al. [168] investigated the physical and oxidative stability, in vitro, digestion, and hypocholesterolem activity, of \(\beta\)-sitosterol loaded in NLCs. They indicated that the as-fabricated NLCs exhibited greater physical stability during long-term storage and during simulated mouth and stomach digestion, as well as higher overall bioaccessibility at the end of digestion. They justified the remarkable affinity of \(\beta\)-sitosterol to the complex lipid mixture formed during the digestion, demonstrating the improved reduction of the encapsulated \(\beta\)-sitosterol (in the NLCs) in the total cholesterol and low-density lipoprotein cholesterol plasma levels in mice, as compared to free \(\beta\)-sitosterol suspension. Lastly, it warrants mention that the formation and stability of free phytosterol-loaded NLCs are also affected by the lipid composition and properties. On that note, [PERSON] and colleagues [169] investigated the influence of lipid composition and chemical interesterification on the formation and physical stability of free phytosterol-loaded NLCs with soy oil and fully hydrogenated palm oil (HPO) or crambe (HCO) as the liquid and solid lipids, respectively. They indicated that the as-fabricated NLCs with interesterifiedblends displayed smaller particle sizes and less particle agglomeration than those with simple blends. The intereesterification resulted in a reduction in the melting temperature and recrystallization index of the NLCs. Thus, they demonstrated the good encapsulation efficiency and loading capacity of free phytosterol in NLCs with interesterified blends.
###### Abstract  
Photacouscuit (PA) velocimetry holds the advantage of detecting ultrasound signals from selective targets sensitive to specific wavelengths of light irradiation. In particular, it is expected to be applied for measuring blood flow in microvasculature. However, PA velocimetry has not been sufficiently investigated for small velocity ranges down to several tens of millimeters per second. This study evaluates the performance and uncertainty of PA velocity measurements using a single graphite cylinder (GC) as a moving object. A pair of short laser pulses irradiated the object within a brief time interval. The velocity was measured based on the cross-correlation peak of successive PA signal pairs in the time domain. The limiting measurement uncertainty was 3.4 mm/s, determined by the sampling rate of the digitizer. The object motion was controlled in a sinusoidal linear motion, realized using a loudspeaker. With the PA measurement, the velocity of the object was obtained with a time resolution in milliseconds and with directional discrimination. Notably, the PA velocity measurements successfully provided the local velocities of the object across a wide range, with the reference velocity obtained as the time derivative of the displacement data acquired using a laser displacement sensor (LDS). The PA measurement exhibited uncertainties ranging from 0.86 to 2.1 mm/s for the maximum and minimum velocities during the experiment. The uncertainties are consistent with those in stationary cases, and nearly constant in the investigated velocity range. Furthermore, the PA measurements revealed local fine velocities of the object, which were not resolved by the reference velocities of the LDS measurements. The capability of the PA velocity measurement was found to be advantageous for measurements of objects with dynamic variations in magnitude and direction.  
photoacoustic; ultrasound; velocity measurement; cross-correlation; pulsed laser; sinusoidal motion; measurement uncertainty; phase-resolved measurement Article
# TACRP: Traffic-Aware Clustering-Based Routing Protocol for Vehicular Ad-Hoc Networks
## 3 AODV Routing Protocol for VANETs  
In general, VANETs are networks with huge mobility. Due to the characteristics of VANETs various issues are created, such as routing, congestion, quality of service, and movement in vehicle nodes. In order to achieve an efficient path during the process of communication between the sender to receiver routing, protocols are introduced which are classified into reactive, proactive and hybrid routing protocols [27]. AODV is one of the reactive types, and stands for Ad-Hoc On-Demand Distance Vector. The features of this protocol are that it can provide unicast, multicast, and broadcast communications. To perform the action of route discovery, a route request (RREQ) message is transmitted from the sender, then, after the receiver receives the RREQ message the receiver transmits a route reply (RREP) message. The other messages are route error message (RERR) and hello message (HELLO) for route maintenance [28].  
From Figure 1, it can be seen that the sender previously transmitted the RREQ message before transmitting the actual message. Any neighbor hop which is in the path towards the receiver responds with the RREP message and then rebroadcasts the RREQ to the next hop to reach the receiver. Once the RREQ is received by the destination it replies by transmitting the RREP to the sender. Only after receiving the RREP from the receiver, does the sender node initiate the data transmission. In case link failure occurs at that time, the corresponding node reports the RERR message to the sender and repeats the route discovery process [29]. The best path is selected by the sender using the hop count and sequence number, which has to be the shortest and most reliable. AODV initiates the route establishment only at the time the sender wants to transfer the data packets. During the process of data transmission, the sender transmits the RREQ for connection. The hop nodes store and then transmit the RREQ towards the receiver. All the entries which are used for the process are erased after some time. In case route failures occur, the RERR message is transmitted to the sender node to recreate a new path to the receiver.  
Figure 1: AODV Route Discovery Process.
# Study on Frost Heave and Thaw Settlement Characteristics of Sanya Estuary Channel Soil Layer
###### Abstract  
In order to explore the frost heave and thaw settlement characteristics of soil layers in the Sanya Estuary Channel Project, the frost heave rate and thaw settlement coefficient of gravel sand, fine sand, silty clay, and clay are obtained. The most unfavorable soil layers are then compared and analyzed. The variation law of frost heave and thaw settlement performance of the most unfavorable soil layer under different water content is studied. The results are as follows: (1) The freezing stage of the passage through the typical soil layer is divided into four stages: frost shrinkage, rapid frost heave, slow frost heave, and frost heave stability. The melting stage is divided into three stages: slow thaw settlement, rapid thaw settlement, and thaw settlement stability. (2) The most unfavorable soil layer in the typical soil layer of the Sanya Estuary Channel Project is silty clay, with a frost heave rate and thaw settlement coefficient of 4.51% and 5.88% at \(-28~{}^{\circ}\)C. (3) The frost heave and thaw settlement performance of the most unfavorable soil layer is linearly related to water content. The larger the water content, the greater the frost heave rate and thaw settlement coefficient, and the more prone to damage.  
frost heave rate; melting settlement coefficient; moisture content; indoor test Article  
Study on Frost Heave and Thaw Settlement Characteristics of Sanya Estuary Channel Soil Layer  
1 Hainan Hongling Architectural Design Co., Ltd., Haikou 570228, China; [EMAIL_ADDRESS]  
School of Civil and Architectural Engineering, Hainan University, Haikou 570228, China; [EMAIL_ADDRESS] (J.H.); [EMAIL_ADDRESS] (J.S.); [EMAIL_ADDRESS] (H.X.)  
Marine Science and Technology Collaborative Innovation Center, Hainan University, Haikou 570228, China  
4 Faculty of Applied Technology, Huaiyin Institute of Technology, Huai'an 223001, China
# Multivariate Analysis of Laser-Induced Tissue Ablation: Ex Vivo Liver Testing
## 3 Results and Discussion
Although the difference in the ablation volume between the maximal and the optimal VEDs (i.e., 500 vs. 80 J/mm\({}^{3}\)) was 2.6-fold, the optimal VED could yield 140% faster removal of tissue due to shorter interaction times. Given the same irradiation time, the optimal VED could ablate more tissue due to high AR. In clinical situations, the typical size of large prostates for BPH treatment ranges from 80 to 120 cc [12]. Based upon the current findings, surgical urologists can remove 100 cc of prostate in around 34 min at the optimal VED while removing the same size in approximately 80 min at the maximal VED. However, it should be noted that the average clinical procedure for a 100 cc prostate gland takes around 120 min, which is 1.5-3.5 times long as the estimated procedure times [12]. One of the explanations could [18] be tissue component. Unlike BPH consisting of stromal tissue [6], the liver is glandular tissue, which is relatively easy to ablate and can thus be associated with a lower ablation threshold (i.e., high AR). Furthermore, optical properties of the liver are greatly different from those of prostate. For instance, the absorption coefficient of the liver at 532 nm is 4.5-fold higher than that of the prostate (i.e., 10.9 cm\({}^{-1}\) for liver vs. 2.4 cm\({}^{-1}\) for prostate [18]). Although easy and abundant procurement of the liver tissue was quite beneficial for the current feasibility testing,  
Figure 5: Collective effect of volumetric energy density (J/mm\({}^{3}\)) on laser-induced ablation volume. the tissue properties could substantially affect the ablative tissue responses. Another explanation is the progress of thermal denaturation of the collagen in the prostatic tissue, which is thermo-mechanically resistant to the laser ablation process. Further investigations on collagenous tissue are currently underway in order to compare with the current findings. Specifically, two consecutive tests with (1) bull/canine prostate and (2) cadaveric human prostate will be conducted to validate the proposed parametric analysis for clinical translation in terms of ablation efficiency.