esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussions  
### Shape Optimization of Femoral Implant  
The novel implant design was generated using topological optimization, resulting in a 26% reduction in mass compared to the standard design. This mass reduction was strategically achieved by lightening areas of the implant experiencing lower stress levels, as identified through the optimization process. Importantly, this reduction was carefully managed to maintain the essential mechanical functionalities of the prosthesis. However, while topological optimization can achieve a mass reduction in the implant design, it is crucial to consider the overall impact on the biomechanical performance. Simply being lighter does not guarantee superiority over other solutions. A comprehensive evaluation should compare this approach to alternative designs, including anatomically fitted implants, to determine the optimal balance of weight, stress distribution, and long-term clinical outcomes.  
Figure 6 illustrates the redesigned femoral stem, showcasing the section where material was removed based on the topological optimization results. Finite element analysis confirmed that this mass reduction did not significantly impact the prosthesis's mechanical performance.
# Numerical Modeling of Single Pile Behaviors Due to Groundwater Level Rising
## 2 Study Area
### Geology and Hydrogeology of Bangkok Area  
Bangkok is located in the Lower Central Plain of Thailand (Figure 1b), which is composed of thick deposits of marine clays and alluvial soils. The subsoils were complex and non-uniform in texture. To a depth of 35 m, the subsoil consists of soft clay (Bangkok clay), stiff clay and sand, but below that, it is stiff to hard clay and dense sand layers. The hydrogeology of Bangkok area shows an aquifer system, consisting mainly of Pliocene-Pleistocene-Holocene fluvial and deltaic sands, gravels and fine-grained deposits (silts and clays). From a detailed electrical and lithological logs of groundwater wells, the Japan International Cooperation Agency [24] identified and named eight aquifers with thicknesses of 30-70 m each, including the Bangkok (BK, ~50 m), Phra Pradeang (PD ~100 m), Nakorn Luang (sNL ~150 m), Nonthaburi (NB ~250 m), Sam Khok (SK ~300 m), Phayathai (PT ~350 m), Thbonburi (TB ~450 m), and Pak Nam (PN ~550 m) aquifers. The maximum thickness of the basin near the Gulf of Thailand is about 2000 m, but it has been studied only to a depth of ~600 m. The top of the BK aquifer from the Gulf of Thailandto Ayutthaya has Bangkok clay, a soft clay, 12-20 m below ground level, so building foundations were built on piles to protect the settlement.  
However, the pile foundations were constructed at \(\sim\)70 m in the PD aquifer, and groundwater was considered the major influence on the PD aquifer.
## 5 Conclusions  
In this paper, we have described the design and evaluation of our clustering system. Our clustering system reads incoming news reports from RSS streams, and clusters them \"on the fly\" according to the event they are describing. The clustering is performed by representing incoming news reports as Bag-of-Words with TF.IDF weighting, and using a variation of the k-means algorithm that works in a single pass without cluster reorganisation. The number of clusters to produce is not known beforehand, and new events are detected automatically. As we mentioned in Section 1, the clustering process described here is very fast--every news report is clustered in less than 1 second on average.  
The evaluation results show that our system is very effective when clustering documents into highly specific clusters (such as event-centric clusters), but performs rather poorly when clustering documents (or news reports) into more general categories. The fact that the results obtained on the _Google News_ clusters are very good may imply that our algorithm is similar to the one used by _Google News_ for clustering. Unfortunately, we could not confirm this since we could not find information about the inner workings of _Google News_.  
It is our opinion that our clustering approach can be applied in other domains apart from online news. For example, it can be applied successfully to the clustering of social media feeds to produce clusters according to the item being discussed by the different people.
## 3 Method
### BTDM Decoder
#### 3.2.3 Relation Judgement  
After subject-object alignment, we obtain all the entity pairs with possible relations; as shown in Figure 2, we defined a (entity pair, relation) bipartite graph for relation judgement, which takes the projected entity pairs \(\mathbf{E}_{head}\) representations and \(\mathbf{E}_{tail}\).  
\[\begin{split}\mathbf{E}_{head}&=\mathbf{W}_{h}\mathbf{E}_{s}+ \mathbf{b}_{h}\\ \mathbf{E}_{tail}&=\mathbf{W}_{t}\mathbf{E}_{o}+\mathbf{b}_{t}\end{split} \tag{6}\]  
where \(\mathbf{E}_{head}\) and \(\mathbf{E}_{tail}\) are the \(d\)-dimentional representations obtained by \(v_{sub\_k}\) and \(v_{obj\_k}\); \(\mathbf{W}_{h}\), \(\mathbf{W}_{t}\in\mathbb{R}^{d\times d}\) are two matrices, allowing for the model to extract subject-object characteristics of entity pairs; and \(b_{h}\), \(b_{t}\in\mathbb{R}^{d\times 1}\) are two biases.  
Lastly, we predicted the relations between each pair of entities for each relation \(r\) to determine if they can form a valid triple:  
\[p^{k}=\sigma\Big{(}\mathbf{E}_{head}^{T}\,\mathbf{U}_{k}\mathbf{E}_{tail}\Big{)} \tag{7}\]where \(U_{k}\in\mathbb{R}^{d+1\times d+1}\) is a relation-specific matrix. If the possibility \(p_{ij}^{k}\) exceeds the predefined threshold, the relational triple \((s_{i},r_{k},o_{j})\) will be considered to exist; otherwise, it will be considered not to exist.  
Linking a bipartite graph to judge relations can better encode the directional information of words during decoding and has an excellent classification ability. These two benefits help to increase the precision of the extraction. On the one hand, this keeps track of the matrix for every type of relation, which faithfully represents the traits of the relation; on the other hand, it accurately mines the relations between subjects and objects thanks to its probabilistic computational architecture.
## 3 Results and Discussion
### HPLC-PDA-tQ-ESI-MS Profiles of SPE Fractions of Silene repens: Qualitative Study
repens_  
The effect of phytohormones and elicitors on content of glycosylflavones **13-18** in introduced seedlings of _S. repens_ after 1 month of phytohormone and elicitor treatment was evaluated. Epibrasinolide, indole-3-butyric acid, 4-chlorophenylacetic acid, gibberell acid potassium salt, arachidonic acid, and ethyl arachid in different concentrations (1, 10, 100 mg/L) were used (Table 2). The maximum contents of dominant glycosylflavones of _S. repens_ (**13** and **14**) were observed when seedlings were sprayed with epibrasinolide (100 mg/L) and 4-chlorophenylacetic acid (100 mg/L), respectively. The content of sileneside E (**13**) increased from 0.60 to 0.79 compared with the control. The concentration of schaftsoside (**14**) increased more than 4 times from 0.73 mg/g to 2.97 mg/g. For meloside A (**15**) and isovitexin (**16**), the maximum accumulation was also observed after treatment with 4-chlorophenylaphenylacetic acid (100 mg/L). Compared with the control group, the content of **15** and **16** increased by 5.5 and 2.25 times, respectively. The maximum increase in the content of swertisin-2\({}^{\prime\prime}\)-O-glucoside (**17**) was revealed after the treatment with gibberellic acid potassium salt (100 mg/L) from 0.15 mg/g to 0.63 mg/g. The highest accumulation of swertisin (**18**) was observed in the case of treatment with arachidonic acid (100 mg/L). Previously, it was shown that the use of gibberellic acid increased the content of flavones in transgenic _Saussurea involucrata_[52]. The highest total content of glycosylflavones was observed after treatment of seedlings with 4-chlorophenylacetic acid (100 mg/L) and amounted to 4.17 mg/g vs. 1.65 mg/g in the control group. Thus, the treatment of _S. repens_ seedlings with 4-chlorophenylacetic acid is justified to obtain raw materials with a high content of glycosylflavones.
# A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks
## 3 The Glider-Assisted Link-Disruption Restoration Mechanism  
We first describe the network model that is the basis for our mechanism. Due to the wide range of deployment in wireless sensor networks and the complex communication environment, the network structure is generally clustered in UASNs. After that, we introduce the process of the glider-assisted link disruption restoration mechanism. Next, we design a reasonable link disruption recognition and glider-scheduling (LDR-GS) mechanism as the first part of the restoration. In LDR-GS every cluster head node can learn about the link interruption and transfer the status information to the glider when the glider is periodically close to the cluster head node. The previous work can fully prepare for glider-assisted link restoration.
## 3 Simulation Analysis
### Frequency Response Analysis by the State Space Method
Figure 10: Sorted DC value of each mode versus number of modes include. Figure 9: DC value of each mode contribution versus frequency. mode 6 is the main reason for the first peak of the overall frequency response function curve. As shown in Figure 13, the phase curve obtained by the state space method and the frequency response curve obtained by the finite element method do not completely coincide. The state space method performs high-frequency truncation, so only the first 10 modes are truncated for analysis. Starting from the 11 th mode, the frequency is much higher than that of the 10 th mode and the response of the structural system to high-order frequencies is extremely low, so there is no need for further analysis. The frequency response analysis of the finite element method is performed on the basis of structural modal analysis and contains high-frequency information. Because Patran and the state space method proposed in this paper have different fitting algorithms for the frequency response characteristic curve, the low-frequency response curve has errors. The structure is prone to damage and plastic deformation at the resonance peak, so we only care about the response of the structure at the resonance peak. The relative errors of the frequency response curves obtained by the two methods at the resonance peak response are 11.3% and 0.7% respectively, which are within the allowable range according to engineering experience. Therefore, the analysis of the state-space method is accurate. The method of analyzing the frequency transfer characteristics of the mirror assembly based on the state space method is accurate. However, it takes about 10 min to obtain finite element analysis results on the frequency response of the primary mirror assembly, while the state space method only needs tens of seconds to provide the frequency response characteristic curve and its calculation efficiency is far more limited. The finite element method is superior, and the contribution value of each mode can be viewed, which is more convenient for engineering analysis. The finite element method is used to analyze the frequency response characteristics of the structure. There are two kinds of numerical methods to choose: direct frequency response and modal frequency response. The direct frequency response directly solves the coupled motion equations according to the given frequency; while the modal frequency response uses the mode shape of the structure to reduce and decouple the coupled motion equations, a and at the same time, the corresponding results at a given frequency are obtained by the corresponding superposition of a single mode. Since the modal frequency response method can only be used to decouple the equations when there is no damping or only modal damping, this paper uses the direct method to solve the problem. As shown  
Figure 13: Comparison of finite element analysis (MSC.Patran) and the state space method. in Table 1, the state space method simplifies the model by reducing the modal frequency response, which can improve the computational efficiency.
# Multiset-Trie Data Structure
## 4 Mathematical Analysis of the Structure
### Space Complexity  
As in any efficient algorithm, there is always some trade-off between space and time complexity. While offering efficient sub- and super-multiset queries, an additional space must be provided for multiset storage. As we increase the parameter \(p\), the number of sets we need to store (i.e., number of leaves) increases linearly. Figure 2 shows that the additional overhead space that our data structure uses does not increase as the tree is becoming more and more dense.  
As we see in Figure 2, the value of \(|\mathcal{M}|\) is slightly shifted with respect to the value of \(|M|\).  
Now, we demonstrate a more descriptive comparison between \(|\mathcal{M}|\) and \(|M|\). Figure 3 shows the ratio between the expected cardinality of a multiset-true \(|\mathcal{M}|\) and the actual number of multisets stored \(|M|\) for parameters \(n\) and \(\sigma\) being 10 and 26, respectively.  
Analyzing the graph in Figure 3, we can safely say that the upper bound for the ratio is \(\sigma+1\). The argument holds because of the limit  
\[\lim_{p\to 0^{+}}\mathbb{E}(\xi_{i})=1, \tag{15}\]  
where \(\xi_{i}\) is the number of nodes on the \(i\)-th level and \(1\leq i\leq\sigma+1\).  
However, the ratio \(\sigma+1\) can be obtained only with a very small cardinality of the set \(M\), in particular \(|M|=1\). In order to obtain such a case, the probability \(p\) must be at most \(\frac{1}{p^{n}}\).  
Figure 2: Size of a tree (\(\mathbb{E}(|\mathcal{M}|)\)) compared to the number of stored sets (\(\mathbb{E}(|M|)\)), as the probability parameter \(p\) increases. Parameters \(\sigma\) and \(n\) are 26 and 10, respectively. The additional overhead space that our data structure uses does not increase as the tree is becoming more and more dense.  
The lower bound for the ratio is obviously at \(p=1\) and is equal to 1:  
\[\lim_{n,\sigma\to\infty}\frac{n^{\sigma+1}-1}{n^{\sigma}(n-1)}=1. \tag{16}\]  
Since the ratio \(\sigma+1\) can be obtained for a very specific case only and with a small increase in probability, the ratio drops rapidly and it can be concluded that the space complexity of the multiset-trie is \(O(|M|)\).
# Investigation of Microseismic Characteristics of Rock Burst Based on Fractal Theory
## 5 Discussion  
The Maoping mine is located in a deep area, where ground pressure phenomena are common. To prevent ground pressure disasters, it is necessary to strengthen the monitoring of concentrated microseismic events and conduct regular underground inspections. If deformation damage, such as roadway collapse, is detected in the top plate, appropriate protective measures, such as closure or support, should be taken promptly. Therefore, the analysis of microseismic monitoring results for rock burst warnings plays a non-negligible role. The spatial and temporal distribution patterns of microseismic events can help us observe their abnormal locations and provide early warnings. The process of microseismic events can be represented more intuitively using the fractal dimension.  
The results of the above analysis show that studying the spatiotemporal characteristics of microseismicity is of great significance for predicting rock burst hazards and providing guidance in the field. From the perspective of Section 4.1, with the continuous advancement in mining activities, the microseismic events in the area of concern continue to increase, and the time fractal dimension shows a steady growth phase. When the energy in the volume of the surrounding rock before the rock explosion exceeds the energy storage capacity of the surrounding rock body, the damage in the surrounding rock accelerates. At this time, the number of microseismic events further increases, the time fractal dimension rapidly increases, the time fractal dimension is rapidly reduced owing to the stabilization of the surrounding rock after the rock explosion. It can be seen that the fractal dimension is a concise and efficient generalization for the analysis of the microseismic time evolution law. Studying the spatial distribution of microseismic events can visually reflect the area of microseismic event anomalies to further refine the study area and provide early warning, prevention, and control of the rock burst phenomenon.  
In view of the above analysis methods of the spatial and temporal distribution law, further research is needed. (1) The use of fractal theory to study the law of temporal distribution is consistent with field reality, but the index is single, and more methods of microseismic temporal distribution law need to be explored for comprehensive analysis, and the refinement and comprehensive analysis of this law is necessary. (2) It is necessary  
Figure 9: Deformation damage of quasi-ramp support in I-8# orebody.  
to further summarize the spatial distribution law of microseismic events and to analyze the relationship between the dense area of microseismic events and the occurrence of rock burst phenomena. The next step is to promote the rapid identification of early warnings. (3) In the future, it is necessary to analyze the microseismic results from a graphical point of view, achieve accurate and intelligent identification, establish a microseismic image identification and analysis system, automatically generate reports, and continuously correct and improve them in the field.
# mmSight: A Robust Millimeter-Wave Near-Field SAR Imaging Algorithm
## 3 System Design
### Target Imaging
#### 3.3.3 Flow of mmSight  
The pseudo-code of the Algorithm 1 is shown below, describing the whole process of adding windows, imaging, and filtering, and describing the implementation of adding windows in detail, as well as the individual steps of the imaging algorithm. Among them, step 1 collects data, step 2 is the detailed process of windowing, step 3 obtains distance plane data, steps 4 to 7 are the execution parts of Analytical Fourier Transform, and step 8 uses mean filtering to remove spatial noise.  
```
Input: original cube data Output: image
1. Collect three-dimension raw data (radar data cube) \(m(x,y,t)\) by a virtual aperture
2. Add Blackman window to three-dimension raw data while i from 1 to amounts of rows while j from 1 to amounts of cols \(r(i,j)\) acquired by adding Blackman to \(m(i,j)\) endwhile endwhile then get three-dimension optimized data \(r(x,y,t)\)
3. Perform range FFT to three-dimension optimized data, then focusing in \(z_{0}\) distance with Formula (5), then get two-dimension focusing data \(s(x,y)\)
4. Perform 2D FFT to two-dimension focusing data \(s(x,y)\),then get \(S(k_{x},k_{y})=FT_{2D}[s(x,y)]\)
5. Create Phase Factor \(e^{-\beta_{k}z_{0}}\). create \(k_{x}k_{y}\)
6. get \(e^{-\beta_{k}z_{0}}=e^{-\gamma\sqrt{4k^{2}-k_{x}^{2}-k_{y}^{2}}2_{0}}\) with Formula (11)
7. Get \(F(k_{x},k_{y})\) through \(S(k_{x},k_{y})\) multiplying by \(e^{-\beta_{k}z_{0}}\)
8. Perform 2D FFT to \(F(k_{x},k_{y})\), then get reflectivity data \(f(x,y)\) \(f(x,y)=IFT_{2D}[F(k_{x},k_{y})]\)
9. Add two-dimension mean filter to reflectivity data \(f(x,y)\)  get final image and display it.
```  
**Algorithm 1** mmSight
## 4 Results and Discussion
### The Comparative Analysis of Test Data
The schematic presentation facilitates a better visual understanding of the obtained results, which serve to prove the negative impact of low temperatures on a cuff's lifespan, which, in previously described experiments, was presented through the number of oscillations a cuff underwent before its failure on the adapted simulator. Figure 12 gives a better overview of the obtained results from two groups of cuffs that were tested at different temperature conditions. The numerical analysis has shown that the maximal equivalent stresses at different temperatures are smaller than the breakage boundary of the cuff's material. The results of our experimental research have proven that the failure of a cuff, namely breakage, is not exclusively the consequence of material fatigue due to a large number of oscillations, but that the failure depends on ambient temperatures where the cuff, namely within a vehicle, was used. Therefore, our effective fatigue life prediction at different temperatures has a profound significance for the manufacture of cuffs to ensure their reliability and safety.
## 1 Introduction  
Fiber interferometry has great application potential in the field of optical fiber sensing due to advantages such as its small size, light weight, anti-electromagnetic interference, high sensitivity, and low cost. It can accurately measure physical parameters such as pressure [1], strain [2], temperature [3; 4], displacement [5; 6], amongst others. Fiber interferometry is widely used to monitor the health of large steel structures [7], underwater acoustic detection [8], biomedical imaging [9; 10], etc. There are polarization and phase fading problems in most fiber interferometers, and many methods have been proposed to solve these problems. Previously, polarization-maintaining fiber and polarization controllers [11] were used to avoid polarization fading. This solution often makes the resulting fiber-optic system too expensive for practical use. [PERSON] used a Faraday rotation mirror (FRM) as the reflector in the arms of a Michelson interferometer [12]. [PERSON] et al. designed an optic current sensor based on a Faraday mirror and studied the birefringence [13]. [PERSON] et al. reported a phase-stepping method based on direct current phase tracking to stabilize the phase [14]. An active feedback regulation based on the proportional-integral-derivative algorithm was applied in a Michelson interferometer [15]. [PERSON] et al. studied a homodyne interferometer with zero-crossing triggering to avoid phase fading [16]. Although these methods are effective, polarization and phase fading problems are not considered at the same time. The active and passive phase stabilization for the fiber Michelson interferometer with FRM was studied by [PERSON] et al. [17]. However, its sensing part is limited to the fiber itself, which is not suitable for noncontact and high-frequency detection.  
In this paper, we report a novel self-designed probe with a built-in Faraday rotator that is connected to one arm of a [PERSON] interferometer, with an FRM in another arm. The result shows that polarization fading is well controlled. Meanwhile, the sensing light is focused on the surface of the object under detection, which can realize high-frequency noncontact detection. A feedback control scheme based on a \(3\times 3\) fiber coupler is proposed, resolving the phase difference uncertainty problem. The performance detection result with the proposed normalization shows that the interferometry system can detect high-frequency- and micro-vibrations. Photoacoustic technology has unique advantages in biological imaging [18; 19]. The proposed experimental system detects the photoacoustic wave with a non-contact style, which is of great potential for point-by-point imaging scanning in nondestructive inspections.