esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on the Obstacle-Avoidance Steering Control Strategy of Tracked Inspection Robots
## 3 Kinetics of Tracked Robot during Steady-State Turning
### Analysis of the Torque of Skid-Steering  
The steering resistance of the robot was a combination of the steering resistance moments of the two tracks. Because the center of gravity of the robot does not coincide with the center of its geometry, the steering axis of the robot moves the distance \(s_{H}\) along its \(y\)-direction. The minute element \(dy\) is used for the right track, and the component force of the tangential reaction force \(dF_{R}\) in the \(x\)-direction is \(dF_{Rx}\). Additionally, the steering resistance moment of the robot can be expressed as  
\[M_{RR}=-\int_{-L/2-s_{y}}^{L/2-s_{y}}q\mu\cos(\pi+\alpha_{M})ydy \tag{5}\]  
where \(\cos\alpha_{M}=\frac{p_{Rx}}{\sqrt{e_{Ry}^{2}+e_{Rx}^{2}}}=\frac{-\left(y+s_ {y}\right)}{\sqrt{s_{R}^{2}+\left(y+s_{y}\right)^{2}}}\).  
After integration of the above equation, it can be concluded that:  
\[\begin{array}{rl}M_{RR}&=-\int_{-L/2-s_{y}}^{L/2-s_{y}}q\mu\cos(\pi+\alpha_ {M})ydy\\ &=-q\mu\int_{-L/2-s_{y}}^{L/2-s_{y}}yd\sqrt{s_{R}^{2}+\left(y+s_{y}\right)^{2 }}\\ &=-q\mu\frac{L}{2}\sqrt{\left(\frac{L}{2}\right)^{2}+s_{R}^{2}}+q\mu s_{R}^{2 }ln\left|\frac{L/2+\sqrt{\left(L/2\right)^{2}+s_{R}^{2}}}{s_{R}}\right|\\ \end{array} \tag{6}\]  
\(A_{R}=\sqrt{a_{R}^{2}+1}-a_{R}^{2}ln\left|\frac{1}{a_{R}}+\sqrt{\frac{1}{a_{R }^{2}}+1}\right|\), \(a_{R}=\frac{s_{R}}{(L/2)}\), Equation (6) can be simplified as follows:  
\[M_{RR}=-\frac{G\mu L}{8}A_{R} \tag{7}\]  
Figure 2: Analysis diagram of robot steering force.  
Similarly, the resistance moment of the right track can be obtained as follows:  
\[M_{RL}=-\frac{G\mu L}{8}A_{L} \tag{8}\]  
It can be seen that in a certain environment, the resistance moment suffered by the robot during the steering process is not related to the longitudinal offset of the robot's center of gravity; it is only related to the relative lateral offset of the instantaneous steering center of the robot's tracks on both sides, and the negative sign indicates that the steering resistance of the robot is opposite to the specified direction. The total steering resistance moment of the robot track is  
\[M_{R}=M_{RR}+M_{RL}=-\frac{G\mu L}{8}(A_{R}+A_{L}) \tag{9}\]  
When \(s_{L}\to 0\) and \(s_{H}\to 0\), the skid and slip rates of the robot are zero; that is, the influence of the robot's skid and slip on the robot's steering motion is not considered, and the motion at this time is the ideal steering motion, \(M_{RR}\rightarrow-\frac{G\mu L}{4}\) and \(M_{RL}\rightarrow-\frac{G\mu L}{4}\).
# GNSS-Assisted Visual Dynamic Localization Method in Unknown Environments
## 2 GNSS-Assisted Visual Dynamic Localization Method Framework
### Initialization
#### 2.1.4 Scale Determinations  
Although the above yielded the translation vector \(t_{C_{2}}^{C_{1}}\), \(t_{C_{2}}^{C_{1}}\) was a translation vector that lost scale. According to the Euclidean transformation distance preserving property, the baseline length of the \(C_{1}\) motion to \(C_{2}\) in a GNSS coordinate system and the Euclidean distance of the translation vector of the \(C_{1}\) motion to \(C_{2}\) were equal; therefore, according to Equation (6), the scale factor \(\lambda_{1,2}\) could be calculated as follows:  
\[\left\|t_{C_{2}}^{C_{1}}\right\|=\lambda_{2,1}\left\|X_{C_{2}}^{n}-X_{C_{1}}^{ n}\right\| \tag{6}\]  
The real translation vector was as follows:  
\[\widetilde{t}_{C_{2}}^{C_{1}}=t_{C_{2}}^{C_{1}}/\lambda_{2,1} \tag{7}\]
## 6 Results and Discussion
### Performance Metrics
#### 6.1.3 Sensitivity (Recall)  
It is determined by dividing the total number of correctly classified Urgent referrals by total number of actual Urgent referrals [4]. Equation (11) depicts single class sensitivity measurements  
\[Sensitivity=\frac{True\,Positive}{True\,Positive+False\,Negative} \tag{11}\]
## 2 Nonlinear Switch Characterization  
The PIN diode MACOM MA4 AGBLP912, operating over the 50 MHz-40 GHz frequency range, was selected for testing. The measurements are performed using a Keysight N5245A PNA-X network analyzer capable of extracting X parameters, connected by means of a Cascade-Microtech 150 \(\upmu\)m-pitch Ground-Signal-Ground (GSG) Co-Planar Waveguide (CPW) probe to the test fixture.
# Pipe Spatter Detection and Grinding Robot
###### Abstract  
This paper proposes a robotic system that automatically identifies and removes spatters generated while removing the back-bead left after the electric resistance welding of the outer and inner surfaces during pipe production. Traditionally, to remove internal spatters on the front and rear of small pipes with diameters of 18-25 cm and lengths of up to 12 m, first, the spatter locations (direction and length) are determined using a camera that is inserted into the pipe, and then a manual grinder is introduced up to the point where spatters were detected. To optimize this process, the proposed robotic system automatically detects spatters by analyzing the images from a front camera and removes them, using a grinder module, based on the spatter location and the circumferential coordinates provided by the detection step. The proposed robot can save work time by reducing the required manual work from two points (the front and back of the pipe) to a single point. Image recognition enables the detection of spatters with sizes between 0.1 and 10 cm with 94% accuracy. The internal average roughness, \(Ra\), of the pipe was confirmed to be 1 \(\upmu\)m or less after the spatters were finally removed.  
pipe robot; welding; spatter; grinding robot +
Footnote †: journal: Applied Sciences
## 1 Introduction
To the best of authors' knowledge, this article is the first to present the integration of LDA and MLP algorithms to localize Wi-Fi users in complex and hierarchical environments. The rest of this paper is organized as follows: In Section 2, we describe relevant works to show the gap of our contributions. In Section 3, the working environment and experimental data collection approaches are discussed. Details of the proposed technique are described in Section 4. Section 5 presents the results and discussion. Finally, conclusions of the work and possible future directions are given in Section 6.
# Is Precision Therapy in Infantile-Onset Epileptic Encephalopathieshes Still Too Far to Call Upon?
## 4 Precision Therapy: A Paradigm Shift  
Precision therapy aims to tailor medical interventions to the unique genetic and molecular characteristics of epileptic and developmental encephalopathies (EDEs) [22]. This strategy offers a transformative approach, moving beyond conventional seizure control to directly address the underlying causes of these disorders. The implementation of precision therapy leverages a variety of innovative mechanisms and approaches, including:  
1. Gene-Specific Targeting: Approaches such as sodium channel modulators for SCN2A mutations, antisense oligonucleotides (ASOs) for Angelman Syndrome, and CRISPR-based gene editing for mutation correction exemplify how genetic insights can directly inform therapeutic strategies [23].
2. Pathway-Specific Interventions: Examples include mTOR inhibitors for tuberous sclerosis complex (TSC) [24], AMPA receptor modulators for GRIN2A-related encephalopathies [25]. These interventions target disrupted molecular pathways to restore cellular function. Additionally, pyridoxine (Vitamin B6) is a cornerstone therapy for pyridoxine-dependent epilepsy (PDE), effectively reducing seizures by addressing the metabolic defect caused by ALDH/A1 mutations. Similarly, the ketogenic diet, a high-fat, low-carbohydrate regimen, is a precision therapy for GLUT1 Deficiency Syndrome (GLUT1-DS), providing an alternative energy source (ketones) for the brain and mitigating seizures caused by impaired glucose transport.
3. Early Diagnosis and Intervention: Early identification of genetic mutations through newborn screening programs facilitates the timely initiation of treatments during critical neurodevelopmental periods, potentially mitigating irreversible damage. For instance, recognizing ALDH/A1 mutations in PDE [26] or SLC2A1 mutations in GLUT1-DS allows for the immediate application of therapies like pyridoxine or the ketogenic diet, which are most effective when initiated early.
4. Biomarker-Driven Outcomes: Biomarkers, such as CSF neurofilament light chain levels and EEG patterns, enable real-time monitoring of disease progression and treatment efficacy, providing valuable feedback for optimizing interventions [27].
5. Multidisciplinary Care: Precision therapy necessitates collaboration among geneticists, neurologists, metabolic specialists, and dieticians to develop and implement comprehensive care plans that address both the genetic and metabolic needs of patients [28].  
Although these advancements represent a paradigm shift, significant challenges remain in implementing precision therapy on a broader scale. The cost of gene-specific treatments, limited availability of advanced diagnostic tools, and the need for robust clinical evidence to validate emerging therapies hinder their widespread adoption. Moreover, even precision therapies like pyridoxine for PDE or the ketogenic diet for GLUT1-DS, while impactful, do not fully mitigate the neurological and developmental challenges posed by these conditions, highlighting the need for ongoing innovation and refinement.
# Experimental Study and Parameter Optimization of a Magnetic Coupled Piezoelectric Energy Harvester
## 4 Results and Discussion  
### Experimental Results  
#### 4.1.1 Static Analysis  
First, the static state is analyzed with \(B_{r}\) = 0.09 T and \(D\) = 10-50 mm. Figure 6a shows the magnets spacing curve as beams spacing changes. As the spacing \(D\) increases, the magnetic force drops rapidly, and the simulation results with or without magnets become very close. Therefore, the study is mainly carried out in the range of 10-25 mm, and the magnetic force is obvious in this range. The results of four experiments (10, 15, 20, 25 mm) show that the model can effectively predict the magnets spacing with an error of less than 4%. Figure 6b shows the static shape at different spacing based on the simulation. It can be more clearly seen from the figure that as the spacing \(D\) increases, the magnetic force and deflection decrease.
## 1 Introduction
The presence of fractures in the subsurface affects the fluid flow and make the propagation of seismic waves azimuthally anisotropic in individual layers. Thus, the estimation of fracture anisotropy parameters is very important for tight reservoir description. There are two commonly used fracture rock physics models. One is the penny-shaped model for cracked media, which assumes that there are thin, penny-shaped ellipsoidal cracks or inclusions in elastic solids [21]. The other is the linear slip model of a fracture medium, which regards fractures as infinitely thin and highly compliant planes regardless of their shape, microstructure, and density, and assumes that the displacement across the fracture surface is linearly correlated with the stress acting on the fracture surface under low-frequency conditions [22]. These fracture rock physics models connect fracture micro-parameters (fracture density, weaknesses, aspect ratio) with rock macro-properties (elastic parameters) and are widely used in characterizing fractures by logging and seismic data [23]. However, it is difficult to characterize the influence of the rock mineral matrix and fluid on rock physical properties only by fracture rock physics models. Hence, some scholars established the anisotropic rock physical model of tight reservoirs by combining the penny-shaped model with the Xu-White model. This combined modeling method is more suitable for underground rocks [24; 25]. Therefore, according to the characteristics of storage space in tight sandstone reservoirs, considering the effects of mineral matrix, pore structures, fractures and fluid substitution in anisotropic rocks, we referred to the modeling workflow of the Xu-White model, combined the dual-connected pore model with the linear slip model, and proposed a practical rock physics model scheme for fractured tight sandstone reservoirs. The model can accurately predict the elastic modulus and anisotropic parameters of a formation from limited logging information. The application results in the actual study area show that the variation charac teristics of the fracture parameters predicted by the model can directly identify the location of fracture development, which can provide the basis for fine reservoir characterization.
# Tibetan Judicial Event Extraction Based on Deep Word Representation and Hybrid Neural Networks
## 2 Related Work
### Event Extraction  
Event extraction methods have evolved from rule-based to machine learning-based and then to deep learning-based models. [PERSON] et al. [31] first used CNN to solve the problem of complex feature engineering and feature generation error propagation. [PERSON] et al. [32] introduced the dynamic multi-pooling mechanism based on the traditional CNN model, which effectively avoided the problem of omitting key information due to processing multiple event sentences. [PERSON] et al. [33] constructed a skip-gram model based on CNN, which breaks through the previous limitation of relying on consecutive k-grams only and further promotes the application of CNNs in the event extraction task. However, although CNN can effectively extract local features, its ability to model long-distance word dependencies is still insufficient.  
Recurrent neural networks (RNNs) are commonly utilized in event extraction tasks due to their effectiveness in handling sequential dependencies. However, they are prone to gradient vanishing or information decay when dealing with long texts. LSTM, as a special RNN model, can learn long-term dependencies and perform better in long texts. For instance, [PERSON] et al. [34] introduced a unified framework leveraging bidirectional LSTM and explored different aspects of parameter memory matrices to enhance the effectiveness of trigger detection and argument recognition. [PERSON] et al. [35] further enhanced the encoding ability of LSTM by incorporating syntactic dependency information into the bidirectional LSTM model. [PERSON] et al. [9] introduced VE Extractor, a method for vulnerability event extraction that combines BERT, BiLSTM, and CRF, enabling the automatic identification of relevant events from textual descriptions in vulnerability reports. However, while LSTM captures global contextual information, it struggles to pay enough attention to local critical information, which limits its performance in event extraction tasks.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Number** & **Model** & **Base** & **Tokenizer** & **Vocab** & **Affiliations** & **Year** \\ \hline
1 & CINO [26] & XLM-R & Sentencepiece & 25 K & HFL & 2021 \\
2 & TiBERT [27] & BERT & Sentencepiece & 30 K & Minzu University of China & 2022 \\
3 & Tibetan-BERT [28] & BERT & Sentencepiece & 32 K & Tibet University & 2022 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Details of Tibetan pre-trained language models.  
Given the respective advantages of different neural networks in capturing syntactic and semantic features, many studies have attempted to combine CNN with LSTM. [PERSON] et al. [36] introduced architecture combining CNN and LSTM to capture sequence and local block information in a specific context. This approach eliminates the need for manual feature engineering and performs well in event extraction tasks in English, Chinese, and Spanish, further demonstrating the applicability of hybrid models for multilingual event extraction.
Sensors_**2012**, _12_, 16557-16570; doi:10.3390/s121216557  
_Sensors_  
ISSN **1424-8220**  
www.mdpi.com/journal/sensors  
_Article_  
Signal Transmission in a Human Body Medium-Based Body Sensor Network Using a Mach-Zehnder Electro-Optical Sensor  
**[PERSON], [PERSON] *, [PERSON], [PERSON], [PERSON] and [PERSON]**  
School of Opto-Electronic, Beijing Institute of Technology, Beijing 100081, China;  
E-Mails: [EMAIL_ADDRESS] (Y.S.); [EMAIL_ADDRESS] (K.Z.);  
[EMAIL_ADDRESS] (J.W.); [EMAIL_ADDRESS] (X.J.); [EMAIL_ADDRESS] (H.S.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel./Fax: +86-10-6891-8406.  
_Received: 17 October 2012; in revised form: 22 November 2012 / Accepted: 23 November 2012 / Published: 30 November 2012_  
**Abstract:** The signal transmission technology based on the human body medium offers significant advantages in Body Sensor Networks (BSNs) used for healthcare and the other related fields. In previous works we have proposed a novel signal transmission method based on the human body medium using a Mach-Zehnder electro-optical (EO) sensor. In this paper, we present a signal transmission system based on the proposed method, which consists of a transmitter, a Mach-Zehnder EO sensor and a corresponding receiving circuit. Meanwhile, in order to verify the frequency response properties and determine the suitable parameters of the developed system, _in-vivo_ measurements have been implemented under conditions of different carrier frequencies, baseband frequencies and signal transmission paths. Results indicate that the proposed system will help to achieve reliable and high speed signal transmission of BSN based on the human body medium.  
**Keywords:** BSN; IBC; electro-optical sensor; signal transmission; human body
## 2 Results  
### Qualitative Composition of Wine Aroma by HS-SPME-GC/MS  
The qualitative identification of volatile components of TRE and PEC aroma was performed by GC/MS analysis by comparing both retention indices (RIs, collected in Table S1 available as Supplementary Material) and mass spectral patterns with the data reported in the literature and in the NIST14 library [29]. Using the three different fibers under the various experimental conditions defined by the DoEs adopted in the respective cases, we detected and identified more than 70 volatile components (listed in Table 1). The compounds found in the wine aroma belong to different chemical classes, including esters, organic acids, alcohols, aldehydes, and ketones. It can be observed that the number and variety of the detected volatiles are dependent on the fiber coatings. In particular, the DVB/CAR/PDMS fiber, which combines three stationary phases with different adsorbtion/absorption properties, can extract the maximum number of volatile components from the wine headspace, whereas the compounds extracted by the PDMS and CW/DVB fibers are lower in number and are mainly esters, followed by alcohols and organic acids. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Compound**} & \multicolumn{4}{c}{**SPME Fiber**} \\ \cline{2-4}  & **PDMS** & **CW/DVB** & **DVB/CAR/PDMS** \\ \hline ethyl acetate & x & x & - \\
2-methyl-1-propanol & x & x & x \\ butanol & - & - & x \\ ethyl propanoate & x & x & x \\
1,1-dethoxyethane & - & - & x \\
3-methyl-1-butanol & x & x & x \\
2-methyl-1-butanol & x & x & x \\ ethyl 2-methylpropanoate & x & x & x \\
1,3-butandiole/2,3-butandiole & x & x & x \\ ethyl butanoate & x & x & x \\ ethyl lactate & x & x & x \\
2-furfural & - & - & x \\
3-methylbutanoic acid & - & - & x \\
4-methyl-1-pentanol & - & x & x \\ ethyl 2-methylbutanoate & x & - & x \\ ethyl 3-methylbutanoate & x & x & x \\
1-hexanol & x & x & x \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of the volatile compounds detected (x) in wine aroma by means of different SPME fibers.
## 3 Results and Discussion
### Antioxidant Activity  
The antioxidant activity values by the DPPH* assay ranged from 11.23 to 255.08 uM Trolox equivalents (uM TE)/g DW; those of the ABTS* assay ranged from 20.47 to 392.65 uM TE/g DW (Table 3). The PI flowers exhibited a high antioxidant capacity in both methods, with values 10-22-fold higher than the rest of the flowers (CA, XU and XC). Conversely, the flowers of XU presented the minimum values in both methods. The results by means of the DPPH* test displayed high antioxidant activity compared to results reported by [PERSON] et al. (2018) in flowers of cucumber (_Cucumis sativus_ L.), globe amaranth (_Gomphrena globosa_ L.), and day lily (_Hermercoallis citrina_). Nonetheless, they were lower compared to those reported by [PERSON] et al. (2018) in red plum (_Pruus mume_), globe amaranth (_Gomphrena globosa_ L.) and carnation (_Diantlus carophyllus_ L.) flowers, as well as values reported by [PERSON] et al. (2018) in flowers of nasturtium (_Tropaeolum majus_ L.), paracess (_Spilanthes oleracea_ L.) and amaranth (_Amananthus hypochondriacus_ L.). Additionally, the antioxidant activity in petals of May rose (_Rosa \(\times\) centifolia_), forget-me-not (_Myosotis sylvatica_) and rugosa rose (_Rosa rugosa_) was higher than that found in PI ([PERSON] et al., 2018).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Assay**} & \multicolumn{4}{c}{**Flowers**} \\ \cline{2-5}  & **Cardón** & **X. ‘Ulapa’** & **X. ‘Cuaresmenño’** & **Pitaya** \\  & **(C. _rosea_)** & **O. _oligacantha_** & **O. _matudae_** & **(E. _cinarcascens_)** \\ \hline DPPH* A & 24.67 \(\pm\) 0.11 b  & 11.23 \(\pm\) 0.11 d  & 11.96 \(\pm\) 0.05 c  & 255.08 \(\pm\) 0.49 a  \\ ABTS* A & 33.10 \(\pm\) 0.31 b  & 20.47 \(\pm\) 0.50 c  & 29.13 \(\pm\) 0.32 b  & 392.65 \(\pm\) 3.54 a  \\ \hline \hline \end{tabular}
\end{table}
Table 3: Antioxidant activity of catus flowers from Hidalgo, Mexico.  
The antioxidant activity values obtained using the ABTS\({}^{\bullet+}\) method, were found to be higher compared to the DPPH\({}^{\bullet}\) assay, which can be explained by the differences in sensitivity between both methods [49]. Except for PI, the antioxidant activity of cactus flowers was higher compared to safron flowers (_Crocus sativus_ L.) and globe amaranth (_Gomphrena globosa_ L.) reported by [PERSON] et al. [46], but lower than values reported by [PERSON] et al. [47] in flowers of globe amaranth (_Gomphrena globosa_ L.), calendula (_Calendula officinalis_ L.), and red plum (_Prunus mume_).  
PI, CA, XU and XC flowers could be considered as rich sources of antioxidant compounds with possible beneficial effects on health. Edible flowers have been shown to be a rich source of bioactive compounds such as anthocyanins, vitamins, carotenoids, polyphenols, and flavonoids [6].